research paper on social media and marketing

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Research Article

Sustainable customer retention through social media marketing activities using hybrid SEM-neural network approach

Roles Conceptualization, Data curation, Writing – original draft

Affiliation UCSI Graduate Business School, UCSI University, Cheras, Kuala Lumpur, Malaysia

Roles Conceptualization, Methodology, Writing – original draft

Affiliation Faculty of Entrepreneurship and Business, Universiti Malaysia Kelantan, Pengkalan Chepa, Kota Bharu, Kelantan, Malaysia

Roles Conceptualization, Formal analysis, Writing – review & editing

* E-mail: [email protected] , [email protected]

Affiliation UKM-Graduate School of Business, Universiti Kebangsaan Malaysia, Kuala Lumpur, Selangor Darul Ehsan, Malaysia

Roles Conceptualization, Methodology, Writing – review & editing

Roles Conceptualization, Formal analysis, Writing – original draft

• Qing Yang, 
• Naeem Hayat, 
• Abdullah Al Mamun, 
• Zafir Khan Mohamed Makhbul, 
• Noor Raihani Zainol

• Published: March 4, 2022
• https://doi.org/10.1371/journal.pone.0264899
• Reader Comments

Social media has changed the marketing phenomenon, as firms use social media to inform, impress, and retain the existing consumers. Social media marketing empowers business firms to generate perceived brand equity activities and build the notion among consumers to continue using the firms’ products and services. The current exploratory study aimed to examine the effects of social media marketing activities on brand equity (brand awareness and brand image) and repurchase intention of high-tech products among Chinese consumers. The study used a cross-sectional design, and the final analysis was performed on 477 valid responses that were collected through an online survey. Partial least squares structural equation modelling (PLS-SEM) and artificial neural network (ANN) analysis were performed. The obtained results revealed positive and significant effects of trendiness, interaction, and word of mouth on brand awareness. Customisation, trendiness, interaction, and word of mouth were found to positively affect brand image. Brand awareness and brand image were found to affect repurchase intention. The results of multilayer ANN analysis suggested trendiness as the most notable factor in developing brand awareness and brand image. Brand awareness was found to be an influential factor that nurtures repurchase intention. The study’s results confirmed the relevance of social media marketing activities in predicting brand equity and brand loyalty by repurchase intention. Marketing professionals need to concentrate on entertainment and customisation aspects of social media marketing that can help to achieve brand awareness and image. The limitations of study and future research opportunities are presented at the end of this article.

Citation: Yang Q, Hayat N, Al Mamun A, Makhbul ZKM, Zainol NR (2022) Sustainable customer retention through social media marketing activities using hybrid SEM-neural network approach. PLoS ONE 17(3): e0264899. https://doi.org/10.1371/journal.pone.0264899

Editor: Qihong Liu, University of Oklahama Norman Campus: The University of Oklahoma, UNITED STATES

Received: September 12, 2021; Accepted: February 19, 2022; Published: March 4, 2022

Copyright: © 2022 Yang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

By definition, social media encompass online applications, platforms, and media promoting interaction, collaboration, and content sharing among users [ 1 ]. The associated marketing component renders it highly convenient to spread information due to its synergy-inducing scale [ 2 ], thus highlighting social media as a practical choice for such purpose. In fact, effective information dissemination is a crucial factor in ensuring the success of social media marketing [ 3 ]. In 2018, Chinese social media users increased by 100 million [ 4 ], while the beginning of 2020 recorded an increment for global social media users amounting to 3.8 billion. Simultaneously, recent data has shown that more than 1 billion people in China employ social media, as reflected by its social media popularising rate of 74% [ 5 ]. In line with this, the Global Web Index has reported that a user typically makes use of social media for up to two hours and 42 minutes per day [ 6 ]. Therefore, the last decade has underlined social media marketing as an essential marketing tool, emerging as a mainstream research aspect [ 7 ].

In general, social media offer consumers a new platform for understanding a product and interacting with people anywhere globally to share product-related experiences [ 8 , 9 ]. This population is typically embedded with different awareness orientations before making a purchase decision, which can be divided into brand awareness and value awareness [ 10 ]. To compare: consumers having the brand awareness orientation perceive the brand as a symbol of credibility and prestige, whereas those with value awareness usually check and compare the prices and quality of different brands through social media to ensure a best-value purchase [ 11 ]. To this end, many companies employ social media in carrying out low-cost and high-efficiency marketing activities for consumers [ 7 , 12 ]. Social media is a marketing tool wielded for four primary purposes: market research and feedback; brand promotion and reputation management; customer service and customer relationship management; and business network [ 13 , 14 ]. Despite its active incorporation in companies to increase visibility and gain more customers, social media-focused customer loyalty-building and strengthening remain a less-explored area [ 13 , 15 ]. Therefore, understanding how social media activities affect customer loyalty is essential for enhanced marketing strategies.

The current study discussed the impact of social media-based marketing on brand loyalty through brand equity. Entrepreneurial and large business firms actively engage with social media-based marketing activities to inform and build attractiveness for their prospective and current consumers [ 16 ]. Furthermore, the study distinctively highlighted the impact of social media-based marking activities on consumer-level brand equity and brand loyalty in terms of repurchase intention.

The purpose of this article is to systematically and comprehensively examine the impact yielded by social media marketing activities (SMMA) towards the creation of consumer brand awareness and brand image. Accordingly, the research goal denotes filling the gaps identified in previous efforts, which include: (1) evaluating the effect of the components of SMMA (i.e., entertainment, customisation, trends, interaction, and word of mouth) on brand awareness and image; and (2) exploring the impact of SMMA on Chinese consumer repurchase intention through brand awareness and brand image of high-tech products.

2. Literature review

2.1 theoretical foundation.

Russel and Mehrabian initially conceived the pioneering Stimulus-Organism-Response (SOR) model in early 1974, which underlines the following operating principle: environmental stimuli (S) lead to emotional responses (O), thereby promoting behavioral responses (R). Subsequently, countless retail scholarships have utilised the SOR model to illustrate its importance in retailing [ 17 , 18 ]. The model is currently widely implemented in consumer behavior studies [ 19 – 22 ]. Based on previous studies, SMMA plays a vital role in influencing customer level of brand awareness and brand image. Accordingly, the SOR model offers a structured method for evaluating the impact of perceived SMMA on brand equity and repurchase intention [ 11 , 23 – 25 ].

The SOR model is selected as the research model for the current study for three specific reasons. First, previous studies have comprehensively implemented the SOR framework to study human-computer interaction leading to consumer buying behavior [ 26 – 28 ]. Secondly, the SOR theory provides the direction of investigations undertaken in the hotel management, food delivery, and other services industries [ 29 – 32 ]. Finally, a scant amount of literature is available pertaining to consumer behavior in China despite the model’s extensive implementation across different countries in assessing the particular topic.

2.1.1. SMMA recognised as an environmental stimulus.

Previous research efforts have detailed the role played by SMMA to aid in creating value, enhancing brand awareness, and building customer relationships [ 23 – 25 ]. Furthermore, some studies have particularly emphasised its use as a marketing stimulus towards enhancing the customer shopping experience and influencing purchase behavior. For example, Zhang and Benyoucef’s [ 22 ] research has supported SMMA as an environmental stimulus in the SOR model. In contrast, social media is thought to play an important role when companies build relationships with their customers via marketing activities [ 24 ]. Similarly, Kim and Ko [ 33 ] have differentiated its characteristics into five categories, namely: entertainment, interaction, fashion, customisation, and WOM, which are then applied to luxury brands. Subsequently, previous works led to this research defining SMMA components as entertainment, interactivity, popularity, customisation, and perceived risk accordingly.

Entertainment is the result of fun and entertainment in using social media [ 34 ]. Thus, the entertainment component of social media is deemed essential, whereby it enriches positive emotions and generates behaviours that involve purchase intentions [ 14 ]. Interaction is the exchange of opinions and ideas occurring between social media and consumers. A stronger interaction on social media allows consumers a deeper understanding of brand content and empowers better brand comprehension of user ideas and preferences, thereby contributing to the brand’s social media platform itself [ 24 ]. Concurrently, consumers can also exchange realised social media platform experiences [ 14 ], whereas social media user-generated content (UGC) has emerged as an alternative brand-customer interaction [ 24 , 35 ]. Trendiness is crucial and otherwise defined using the term ‘trends,’ which details the provision of the latest information pertaining to any products or services [ 25 ]. Tangentially, Valaei and Nikhashemi’s [ 36 ] research has underlined brand style and price as particularly notable factors determining Generation Y consumers’ willingness to buy fashion items. Therefore, the trends and styles positioned by brands can attract more consumers of the younger age range due to their likings for new trends and trendy brands [ 37 ]. Customisation is defined as the degree to which a brand provides specific services to meet the unique tastes and needs exhibited by consumers [ 38 ]. During the consumption process, most customers still want to obtain specific services. Therefore, the current research describes survey personalisation as customer perception of social media in providing customised services and meeting their preferences. Accordingly, brands can provide private and customised experiences tailored to each customer based on personalised portals and offline shops to improve further their brand image and brand loyalty [ 39 ]. Besides, personalisation will accurately help customers locate the products they require, thus indirectly promoting the purchases [ 40 ]. Word of mouth (WOM) is the most natural and common phenomenon encountered in consumer behavior [ 22 ]. It can denote a series of communication activities carried out by a company or product, which is usually regarded as non-commercial and private [ 41 ]. Similarly, WOM is also a source of information in the purchase decision process in which consumers will consider product performance, changes before and after purchase, and consequences of the purchase decision [ 42 , 43 ]. The more familiar and trustworthy the WOM information sources are, the more significant their impact on purchasing decisions [ 44 ]. WOM is more effective than alternative SMMA channels in influencing consumer decision-making [ 45 ].

2.1.2. Brand equity recognised as customer emotional response.

In general, brand equity is defined as intangible assets related to brand names and brand symbols due to the possible effect of brand preference on the brand value as perceived by brand consumers [ 46 ]. Keller [ 47 ] has classified it into brand awareness and brand image, thereby describing brand equity as a social and cultural phenomenon. Meanwhile, brand image is firmly embedded in consumer minds and denotes the associated symbolic meaning, which the brand pursues [ 48 ]. By definition, brand image denotes the impression held by a brand in consumer memory, thus categorised into deep, general, and vague impressions accordingly [ 47 ]. The brand image helps understand and accept the brand’s meaning through consumer perception [ 49 ], which is a collective result of various marketing activities and consumer experience [ 50 ]. In contrast, brand awareness refers to consumers’ ability to recognise or remember a brand [ 50 ], which aids them in searching for products to be purchased faster [ 51 ]. This element typically includes four levels, namely: brand recognition, brand recall, top of the mind brand, and dominant brand [ 52 ].

2.1.3. Repurchase intention recognised as consumer response.

Consumer response makes up the final part of the SOR model [ 28 ], which can be divided into two situations: response and avoidance. Here, the response behavior depicts customer willingness to purchase a product and positive WOM, whereas the avoidance behavior denotes opposite or negative WOM and unwilling purchase [ 20 ]. These responses underpin the current work’s investigation on Repurchase intention, which is otherwise characterised as consumer repurchase intention. Achieving customer loyalty is typically known as the most significant objective of marketing activities as the element is attributed to satisfied customers and consistent sales [ 33 ]. Therefore, repurchase intention is the key to fostering the relationship between customers and brands, whereby some studies have pinpointed increased loyalty and its correlated effect on reduced marketing costs and increased sales [ 53 ]. A brand owner may find it highly necessary to adjust its marketing strategy to retain valuable consumers and increase repurchase intention [ 25 ].

2.2 Repurchase intention

Repurchase intention generally refers to customer judgement of a specific brand product [ 54 ]. Alternatively, brand loyalty describes customer recognition of a particular brand, chosen among many brands as bolstered by the willingness to buy and repurchase products or services [ 55 ]. Therefore, brand loyalty is perceived as the repurchase intention, thus directly reflecting consumer thoughts when choosing to repurchase a particular brand [ 54 ]. Furthermore, brand loyalty is commonly expressed as the consumer tendency to purchase or repurchase brand-related products [ 56 , 57 ]. However, the level of attractiveness shown by their alternatives may affect the relationship between recovery satisfaction and repurchase intentions [ 58 ]. Here, elements influencing consumer repurchase intentions vary, including the lenient return policy and perceived fairness of return experience on top of the common return issues [ 59 ]. Besides, loyal brand users have low price sensitivity to associated brand products, which are also introduced to their friends. Therefore, these positive sharing behaviours allow many potential customers to the brand, increasing initial and second purchase intention [ 60 ].

2.3. Social media marketing activities and brand awareness

2.3.1 entertainment and brand awareness..

Entertainment generally refers to the fun aspect embedded in brand marketing content, which has been underlined by Kim and Ko [ 33 ] and Seo and Park [ 24 ] as an integral part of SMMA. Today, brand products are no longer tethered to traditional displays; instead, they are integrated with entertainment components to establish a stronger emotional connection with consumers [ 61 ]. Furthermore, it has been pinpointed as a factor that directly affects consumer attitudes towards brands [ 62 ], whereby Bilgin [ 63 ] has specifically detailed its significant effect on brand awareness and brand image. Accordingly, improving brand awareness is among the well-known corporate SMMA [ 33 , 64 ]. For example, Seo and Park [ 24 ] have pointed out that such activities performed by aviation and hotel businesses positively impact brand awareness and brand image. As such, the following hypotheses are formulated:

H1a: Entertainment positively affects brand awareness among Chinese consumers .

H1b: Entertainment positively affects brand image among Chinese consumers .

2.3.2 Customization and brand equity.

Consumers typically believe that personalised brand recommendations align with their product preferences, and their more personalised needs to a higher degree [ 65 ]. In social media, customisation refers to the target audience of a message. Zhu and Chen [ 66 ] have thus identified the two types of publishing, depending on the level of message customisation: custom message and broadcast [ 56 ]. Here, customised information targets specific people or a small number of audiences (e.g., Facebook posts), whereas a broadcast generally contains messages directed at anyone interested in the content material (e.g., Twitter tweets). Therefore, the following hypotheses are proposed:

H2a: Customisation positively affects brand awareness among Chinese consumers .

H2b: Customisation positively affects brand image among Chinese consumers .

2.3.3 Trendiness and brand equity.

Technology empowers firms to cultivate trends and enrich customer satisfaction and experience [ 67 ]. Trends are known for their significant impact on customer brand equity, especially in the context of young consumers [ 68 ]. Trendiness depicts the firms’ ability to foster and spread pertinent information that empowers their brand equity [ 8 ]. The adoption of social media to attract consumers has increased among SMEs [ 16 ]. In the luxury goods industry, fashion trends denote an essential element in SMMA and positively impact brand equity [ 60 ]. Kim and Lee [ 67 ] claimed that social media-based trendiness spurs brand awareness and brand image among the prospective consumers. Similarly, social media trends offer extensive awareness among users and help develop the brand image. Therefore, the following hypotheses are developed:

H3a: Trendiness positively affects brand awareness among Chinese consumers .

H3b: Trendiness positively affects brand image among Chinese consumers .

2.3.4 Interaction and brand equity.

Interaction mainly describes the dynamic communication between enterprises and consumers [ 35 ], and social media empowers both to interact facilitatively. Social media-based interaction simplifies the brand communication to the brand consumers and nurtures consumers’ brand experience and satisfaction [ 69 ]. Consumers and brands communicate and interact using various social media platforms [ 23 ]. Such platforms can be utilised to build consumer brand awareness and establish the right brand image concurrently [ 64 ]. Wang et al. [ 59 ] documented that social media-based interaction influences brand awareness and brand image building among young fashion retail consumers. Therefore, the following hypotheses are formulated:

H4a: Interaction positively affects brand awareness among Chinese consumers .

H4b: Interaction positively affects brand image among Chinese consumers .

2.3.5 Word of mouth and brand equity.

In general, word of mouth refers to consumer perception regarding the degree to which other customers recommend and share the latter’s social media experiences [ 13 ]. Consumers like to share their positive or negative experiences on social media [ 67 ]. An industry survey has revealed that a whopping 91% of respondents would consider online reviews, ratings, etc., prior to any product purchases from e-commerce sites. In contrast, nearly 46% agree that such reviews influence their purchasing decisions [ 70 ]. Consumers’ comments on social media facilitate prospective consumers’ awareness and help build the brand image that later influences purchase intention [ 44 ]. Chahal, Wirtz, and Verma [ 71 ] claimed that online brand reputation directly affects perceived brand equity among consumers. Kim and Lee [ 67 ] suggested the positive influence of word of mouth on the levels of brand awareness and brand image among young Bangladeshi consumers. As such, the following hypotheses are proposed:

H5a: Word of mouth positively affects brand awareness among Chinese consumers .

H5b: Word of mouth positively affects brand image among Chinese consumers .

2.4 Brand equity and repurchase intention

Theoretically, brand equity is a subjective assessment of consumer brand preferences [ 10 ], whereby a brand rated as unique and appropriate by consumers indicates a high level of brand equity perceived for it [ 32 ]. Accordingly, a positive brand attitude can positively influence the customers’ repurchase intentions [ 55 ]. Zhang et al. [ 21 ] have postulated the positive link between brand equity and customer loyalty. In particular, brand equity based on brand awareness and brand image positively influence repurchase intention. For instance, brand awareness and brand image promote brand purchase and repurchase [ 10 ]. Thus, the following hypotheses are generated:

H6a: Brand awareness positively affects repurchase intention among Chinese consumers .

H6b: Brand image positively affects repurchase intention among Chinese consumers .

2.5 Mediating effect of brand equity

The impact of SMMA on brand equity has been confirmed in multiple previous studies in which the latter is considered the reason or motivation for purchasing certain brands. Therefore, higher brand equity can be correlated with higher robustness for consumer preference and willingness to buy any products [ 72 , 73 ]. Alternatively, brand awareness also affects consumer attitudes towards brands, further stimulating their brand choice [ 64 ]. In this matter, Keller [ 47 ] believes that regardless of the attributes being related to specific brand products or not, they vigorously promote the formation of brand associations, which will, in turn, directly affect consumer purchase or repurchase intentions. Therefore, brand loyalty is considered a necessary factor for ensuring repeat purchases [ 72 , 74 , 75 ]. Hence, the following hypothesis is generated:

Hypothesis (HM): Brand awareness and brand image mediate the relationship between entertainment , customisation , trendiness , interaction , and word of mouth on the repurchase intention among Chinese consumers .

3. Research methodology

3.1 research design.

The current study aimed to measure the impact of SMMA on brand awareness and brand image, thereby leading to the repurchase of high-tech products from a brand among Chinese consumers. The hypotheses and associations are thus designed and tested according to Fig 1 . The explanatory research design was implemented to depict the relationship between tested variables and determine its cause and impact [ 76 ]. Concurrently, quantitative methods were incorporated to study the relationship between variables, whereby the cross-sectional survey method was utilised for data collection purposes. Gathered from the target population, this allowed an exploration of the phenomenon being studied in work.

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https://doi.org/10.1371/journal.pone.0264899.g001

3.2 Sample selection and data collection method

The current study targeted the general population living in China who use social media platforms, namely WeChat, Tencent QQ, Sina Weibo, Youku Tudou, and Douyin, which are used by firms to promote their products. Therefore, the target population of this study included a total of 999.95 million social media users in China [ 77 ]. The sample size calculation was performed using G-Power 3.1 software. With power of 0.95, effect size of 0.15, and a total of seven predictors, the required sample size for the current study was 168 [ 78 ]. Moreover, the minimum sample of 200 is suggested for PLS-SEM [ 79 ]. The study aimed to employ the second-generation statistical analysis technique of structural equation modelling; therefore, the study collected data from more than 400 respondents. As the study was conducted during the COVID-19 lockdown, online survey was opted to protect the respondents and surveyors from COVID-19. The survey was conducted online ( http://www.wjx.cn/ ) from May 2020 to June 2020.

Local ethics committees (Universiti Malaysia Kelantan, Malaysia) ruled that no formal ethics approval was required in this particular case based on the following reasons: (1) this study did not collect any medical information; (2) there was no known risk involved; (3) this study did not intend to publish any personal information; (4) this study did not collect data from underaged respondents. Moreover, this study was performed in accordance with the Declaration of Helsinki. Written informed consent for participation was obtained from all survey respondents. The respondents were required to read and provide their agreement to the following ethical statement posted at the start of the survey before they were allowed to proceed to answering the survey questions: “ There is no compensation for responding nor is there any known risk . In order to ensure that all information will remain confidential , please do not include your name . Participation is strictly voluntary and you may refuse to participate at any time ”. No data was collected from anyone under 18 years old.

3.3 Survey instrument

The questionnaire consisted of two parts, namely Parts A and B. First, Part A included question items about the population profile, gender, age, monthly income, and education level. Meanwhile, Part B comprised question items about SMMA, brand equity, and consumer loyalty. In total, 34 measurement items were employed to estimate SMMA, brand awareness, brand image, and repurchase intention. The measurements were subsequently evaluated using a 5-point Likert scale ranging from 1 (Strongly disagree) to 5 (Strongly agree). A list of the question items and sources for implemented scales is detailed in Table 1 accordingly.

https://doi.org/10.1371/journal.pone.0264899.t001

3.4 Preliminary data preparation and multivariate normality

The outlier analysis with the Mahalanobis distance (D2) measure was conducted to estimate multivariate outliers [ 79 ]. Multiple regression analysis engaged all input variables on the outcome construct and saved the Mahalanobis distance for all cases. Cases with D2 of more than 26.125 were declared outliers; as a result, 35 cases were dropped. The subsequent analysis was performed with only 477 valid cases. Peng and Lai [ 84 ] have cautioned against making general statements about the partial least squares (PLS) estimation model capability as the action may violate the typical multivariate assumption despite the model not requiring a multivariate normal data distribution. Therefore, this study employed the Smart-PLS online tool to test the multivariate normality. The calculations carried out revealed p-values less than 0.5 for the multivariate skewness and kurtosis for Mardias’ coefficient. These outcomes successfully confirmed the non-normality of the data.

3.5 Common Method Bias (CMB)

As suggested by Podsakoff, Mackenize, and Podsakoff [ 85 ], CMB was evaluated based on the results of Harman single factor analysis, which served as a diagnostic tool in this study. The obtained results suggested that a single factor accounted for 35.19%, which was less than the prescribed limit of 50%. In other words, CMB was not a critical issue for the current study [ 85 ]. Moreover, Kock [ 86 ] recommended performing a full collinearity test to gauge the CMB issue. A common variable formed, and all the variables regressed on the common variable as an outcome variable. The variance inflation factor (VIF) for entertainment (1.685), customisation (2.063), Interaction (3.451), trendiness (2.948), word of mouth (2.202), brand awareness (3.433), brand image (2.277), and repurchase intention (2.781) did not exceed 5. This reaffirmed that CMB was not a severe issue for the current study [ 86 ]. The correlations matrix of the latent variables also showed that CMB was not an issue, as all correlations did not exceed 0.900 [ 85 ].

3.6 Data analysis method

Partial Least Squares—Structural Equation Modelling (PLS-SEM) is driven by maximising the interpretation variance of related latent structures [ 79 ]. It was implemented in this study to explore the impact of SMMA on Chinese consumer repurchase intentions in the presence of non-normality issues. Artificial neural network (ANN) analysis is a non-compensatory analytical technique with deep learning algorithms based on three layers: input, output, and hidden layers. The hidden layer connects the input neurons with the output neurons [ 87 ], acting as the block-box similar to the human brain [ 88 ]. The data are divided into three parts for training, testing, and holding out part of the sample. The study utilized the Root Mean Square Errors (RMSE) value of trained and tested data to identify the predictive accuracy [ 89 , 90 ].

4. Data analysis

4.1 demographic characteristics of respondents.

As presented in Table 2 , the majority of the respondents in this study were female (59.7%), while the remaining 40.3% were men. The respondents were grouped into the following age groups: (1) 18–26 years (46.3%); (2) 27–34 years (22.8%); (3) 35–42 years (13.8%); (4) 43 years and above (16.9%). Furthermore, 34.5% of the total respondents recorded monthly income of less than 3,000 yuan, followed by those with monthly income of between 3,001 and 6,000 yuan (30.6%), monthly income of between 6,001 and 9,000 yuan (15.3%), and lastly, monthly income of more than 9,000 yuan (19.4%). Among 477 respondents, only 16.4% consisted of high school students. The majority of the respondents (63.3%) were undergraduates, followed by graduate students (20.5%). In terms of the usage of electronic gadgets, the majority of the respondents (43.1%) used zero to two types, followed by those who used three to five types (33.9%). About 22.8% of the total respondents reported using more than six types. It should be noted that this study was not limited to any specific product brand or category, but rather a general assessment of high-tech products collectively.

https://doi.org/10.1371/journal.pone.0264899.t002

4.2 Reliability and validity

Reliability refers to the consistency shown by the measurement items according to the results obtained via the measurement tools implemented, thereby objectively reflecting the reasonable degree of the measured characteristics. In contrast, validity denotes their effectiveness by measuring whether the comprehensive evaluation system can accurately reflect the evaluation purposes and requirements. Thus, it echoes the measurement of feature accuracy in measuring by using the measuring tool.

Table 3 details the descriptive statistics, validly, and reliability criteria employed to evaluate the items used in the study. However, in reliability analysis, the Cronbach’s alpha (CA) coefficient size was assessed in measuring the questionnaire reliability. In general, a coefficient larger than 0.9 indicates excellent reliability, while a coefficient above 0.8 is good. Meanwhile, values between 0.5 and 0.9 reflect a reasonable outcome, whereas coefficients lower than 0.5 render the outcomes non-trustworthy. Accordingly, CA values shown in Table 3 reveal that all variables generated values greater than 0.8, indicating the latent constructs’ reliabilities.

https://doi.org/10.1371/journal.pone.0264899.t003

Moreover, Dillon Goldstein rho (DG rho) values more than 0.80 as seen for all variables, further confirming the measurement item reliability. We also utilized the composite reliability (CR), and the CR score for all the study constructs are well above 0.85, showing satisfactory reliabilities. Table 3 depicts the acceptable convergent validity attained by the constructs due to values higher than 0.50. According to the recommendation, convergent validity was obtained if the average variance extracted (AVE) value is higher than 0.50. Finally, testing for multicollinearity issues was performed by assessing the variance inflation factors (VIF). The VIF value of each factor is less than 5, suggesting that no major collinearity problem was present. From the reliability and validity testing undertaken, the Composite Reliability (CR) and Average Variance Extracted (AVE) for each factor were relatively good, indicating relatively good data validity.

4.3 Discriminant validity

For the current study, Fornell-Larcker criterion, heterotrait-monotrait (HTMT) ratio of correlations, as well as loadings and cross-loadings were used for the evaluation of discriminant validity. As for the estimation of Fornell-Larcker criterion, the square root of AVE of the construct must be greater than the corresponding correlation coefficient in order to establish discriminant validity. The obtained results in Table 4 showed that the study’s constructs showed suitable discriminant validity. Following that, the HTMT ratio served as a tool to estimate discriminant validity [ 91 ]. As shown in Table 4 , all HTMT ratios did not exceed the threshold value of 0.900, which showed that the study’s latent construct achieved suitable discriminant validity [ 79 ]. This study further verified discriminant validity via a comparison between the loadings and cross-loadings of the tested constructs. Generally, loading is the contribution of an item to the latent variable to which it belongs [ 79 ], whereas cross-loading is the contribution of an item to other latent variables. The loading of an item that exceeds its cross-loadings indicates that the item contributes more to the latent variable to which it belongs. For the current study, discriminative validity was deemed good. Table 5 shows all loadings and cross-loadings generated, whereby almost all loadings in the current study exceeded 0.7. Besides that, the loadings of all items on their respective corresponding latent variables exceeded their cross-loadings, substantiating the goodness of the questionnaire design and data validity.

https://doi.org/10.1371/journal.pone.0264899.t004

https://doi.org/10.1371/journal.pone.0264899.t005

4.4 Path analysis

Table 6 presents the results of path analysis. The recorded path coefficient for the influence of entertainment on brand awareness ( β = 0.042, p = 0.114) indicated the insignificant but positive influence of entertainment on brand awareness. Thus, H1a was not supported. Meanwhile, the path coefficient for the influence of customisation on brand awareness ( β = -0.033, p = 0.163) revealed that it did not affect brand awareness. Thus, H2a was not statistically supported. Similarly, the path coefficient for the influence of trendiness on brand awareness ( β = 0.390, p = <0.001) displayed its significant effect on brand awareness; thus, offering support to accept H3a. In contrast, the path coefficient for the influence of interactions on brand awareness ( β = 0.188, p < 0.001) indicated its significant and positive influence on brand awareness, which supported H4a. As for the influence of word of mouth on brand awareness, the recorded path coefficient ( β = 0.109, p < 0.001) denoted its significant influence on brand awareness. Thus, H5a was supported.

https://doi.org/10.1371/journal.pone.0264899.t006

Meanwhile, the recorded path coefficient for the influence of entertainment on brand image ( β = -0.014, p = 0.379) indicated its non-effect on brand image, rendering the rejection of H1b. Similarly, the recorded path coefficient for the influence of customisation on brand image ( β = 0.093, p = 021) revealed its influence on brand image. Thus, H2b was accepted. In contrast, the recorded path coefficient for the influence of trendiness on brand image ( β = 0.312, p < 0.001) showed its significant and positive influence on brand image. Thus, H3b was accepted. Likewise, the recorded path coefficient for the influence of interaction on brand image ( β = 0.389, p < 0.001) revealed its significant and positive impact, rendering the acceptance of H4b. Additionally, the recorded path coefficient for the influence of word of mouth on brand image ( β = 0.179, p < 0.001) revealed its significant and positive influence. Thus, H5b was supported.

In this study, both H6a and H6b were also accepted. The recorded path coefficients for the effects of brand awareness ( β = 0.544, p < 0.001) and brand image ( β = 0.255, p < 0.001) on repurchase intention indicated their respective significant and positive effects.

4.5 Mediation effects

As shown in Table 7 , this study employed indirect effect coefficients, confidence intervals, and p-values to measure the mediation effects of brand equity in terms of brand awareness and brand image on SMMAs (in terms of entertainment, customisation, trendiness, interaction, and word of mouth) and repurchase intention. The obtained results revealed that brand awareness ( β = 0.023, CI min = -0.011, CI max = 0.059, p > 0.05) insignificantly mediated the relationship between entertainment and repurchase intention. Similarly, brand awareness was found to insignificantly mediate the relationship between customisation and repurchase intention ( β = -0.018, CI min = -0.048, CI max = 0.013, p > 0.05). On the other hand, brand awareness mediated the effects of trendiness ( β = 0.212, CI min = 0.159, CI max = 0.267, p < 0.001), interaction ( β = 0.212, CI min = 0.157, CI max = 0.266, p < 0.001), and word of mouth ( β = 0.059, CI min = 0.023, CI max = 0.101, p < 0.001) on repurchase intention.

https://doi.org/10.1371/journal.pone.0264899.t007

The obtained results of the analysis further revealed that brand image ( β = -0.004, CI min = -0.022, CI max = 0.016, p > 0.05) insignificantly mediated the relationship between entertainment and repurchase intention. Besides that, brand image was found to mediate the effects of customisation ( β = 0.024, CI min = 0.005, CI max = 0.047, p < 0.05), trendiness ( β = 0.080, CI min = 0.045, CI max = 0.120, p < 0.001), interaction ( β = 0.048, CI min = 0.017, CI max = 0.085, p < 0.01), and word of mouth ( β = 0.046, CI min = 0.021, CI max = 0.077, p < 0.01) on repurchase intention.

4.6. Artificial Neural Network (ANN) analysis

Three ANN models were employed in this study to evaluate the data. Model A consisted of five input constructs for brand awareness. Model B had five exogenous variables, and brand image served as the outcome variable. Lastly, Model C had brand awareness and image as input for repurchase intention. Table 8 depicts the results of ANN analysis. Overall, Model A, Model B, and Model C demonstrated high prediction accuracy, as both RMSE training and RMSE scores for testing were rather similar [ 90 ]. Apart from that, the results showed that all ANN models had good data fitting. The goodness of fit for Model A was 59%, while Model B recorded 62%. Model C recorded the highest goodness of fit at 68%.

https://doi.org/10.1371/journal.pone.0264899.t008

Sensitivity analysis was performed on all three ANN models to evaluate the contribution of each exogenous predictor for the endogenous constructs [ 89 ]. The results in Table 9 for Model A confirmed trendiness, word of mouth, and interaction as the most influential three factors that affect brand awareness. As for Model B, trendiness, interaction, and word of mouth were identified as three critical factors that meaningfully instigate brand image. For repurchase intention, brand awareness was the most significant factor, followed by brand image for high-tech products among Chinese consumers.

https://doi.org/10.1371/journal.pone.0264899.t009

The PLS-SEM results were compared with the outcomes of these ANN models. The results are tabulated in Table 10 . The comparison depicts that the ranking of factors varies for Model A and Model B. However, the ranking of factors appeared the same for Model C.

https://doi.org/10.1371/journal.pone.0264899.t010

5. Discussion

This study provided evidence about the impact of SMMA on the repurchase intention held by Chinese high-tech consumers. The assessment was carried out on the five dimensions of SMMA (i.e., entertainment, customisation, trends, interaction, and WOM), two dimensions of brand equity (i.e., brand awareness and brand image), and one dimension of brand loyalty (i.e., repurchase intention). The research conclusively revealed the positive impact by entertainment and WOM on brand awareness in carrying out social media activities. This aligns with the outcomes of Seo and Park’s [ 24 ] study, which has indicated that social media marketing activities harness brand equity, creating brand awareness. Meanwhile, trendiness, interaction, and WOM positively impacted brand image, paralleling the results by Yadav and Rehman [ 25 ]. Therefore, WOM was explicitly associated with a significantly positive impact on brand awareness and image. Similarly, the work verified the hypothesis that brand awareness and brand image significantly impact customer loyalty. Thus, the current research fully supported and confirmed the SOR model.

Furthermore, the mediation effect obtained in this study depicted a satisfactory mediating effect between brand awareness and the factors of entertainment, WOM, and repurchase intention. Therefore, brand equity could be attributed as responsible for the relationship between the three factors. Besides, it yielded a sufficient mediating effect between trendiness, interaction, WOM, and repurchase intention, its weight for the relationship between brand image and all four factors. In contrast, brand image and brand awareness generated no mediating effect between customisation and repurchase intention.

5.1. Theoretical and practical implications

Social media marketing activities nurture and change consumer behaviour, which predictively influence their purchase and repurchase intention. The current study offered theoretical and practical implications. Most previous studies investigated the direct effects of social media marketing activities on purchase intention, but the current study successfully advanced the current literature by examining the mediating role of brand awareness and brand image in relation to repurchase intention of the brand offerings. The study’s findings would undoubtedly add value to the growing literature on social media marketing, brand equity, and repurchase intention. The current study utilised the SOR framework to justify the effects of social media marketing activities on brand awareness and brand image in relation to repurchase intention. Social media marketing activities have become powerful marketing strategies to meet consumers’ expectations and inclination to repurchase firms’ brand offerings. These marketing strategies are relevant to attract new consumers and significantly empower firms to manage customer relationships in order to retain the existing consumers.

The current study also offered three practical implications. Firstly, the study’s findings address firms’ management needs of developing and improving entertainment and customisation attributes in their social media marketing that can advance their efforts to harness brand equity, nurturing repurchase intention among technology product consumers [ 16 ]. Secondly, the current study emphasised repurchase intention as the function of customer loyalty. Social media marketing activities can significantly harness consumer-level of brand equity through brand awareness and brand image. All types of firms need to consider investing and building brand equity with the help of social media marketing activities. Currently, firms only concentrate on trendiness and the need to build social media marketing activities through entertainment, Interaction, customisation, and word of mouth. Lastly, the results of the current study confirmed the effects of social media marketing activities on brand awareness and brand image in relation to repurchase intention. Firms need to concentrate on building brand awareness and brand image with social media marketing activities. Consumers’ inclination to repurchase would develop with the right social media marketing activities, and marketers must harness brand-level equities to promote repurchase intention.

6. Limitation

However, this study has several limitations requiring further attention. For example, the components included in the current research model did not exhaustively list the explanatory variables possibly affecting SMMA. Moreover, the current research mainly focused on high-tech Chinese consumers, limiting the outcome generalisability across the market. Therefore, future works should look into designing research embedded with more variables to explore different social media’s effects on brand equity and brand loyalty across different brand-consumer segments. Besides, using the SOR-based model in this study might limit the research results. Thus, future researchers recommend confirming, replicating, or expanding the outcomes by integrating additional model constructs or using it across dissimilar cultural or geographic environments. This would deepen the scholarly understanding of customers’ repurchase intentions with more depth.

Supporting information

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ORIGINAL RESEARCH article

Role of social media marketing activities in influencing customer intentions: a perspective of a new emerging era.

• 1 School of Economics and Management, North China Electric Power University, Beijing, China
• 2 Department of Management Sciences and Engineering, Zhengzhou University, Zhengzhou, China
• 3 Faisalabad Business School, National Textile University, Faisalabad, Pakistan

The aim of this study is to explore social media marketing activities (SMMAs) and their impact on consumer intentions (continuance, participate, and purchase). This study also analyzes the mediating roles of social identification and satisfaction. The participants in this study were experienced users of two social media platforms Facebook and Instagram in Pakistan. A self-administered questionnaire was used to collect data from respondents. We used an online community to invite Facebook and Instagram users to complete the questionnaire in the designated online questionnaire system. Data were collected from 353 respondents, and structural equation modeling (SEM) was used to analyze the data. Results show that SMMAs have a significant impact on the intentions of users. Furthermore, social identification mediates the relationship between social media activities and satisfaction, and satisfaction mediates the relationship between social media activities and the intentions of users. This will help marketers how to attract customers to develop their intentions. This is the first novel study that used SMMAs to address the user intentions with the role of social identification and satisfaction in the context of Pakistan.

Introduction

There has been tremendous growth in the use of social media platforms such as WhatsApp, Instagram, and Facebook over the past decade ( Chen and Qasim, 2021 ). People are using these platforms to communicate with one another, and popular brands use them to market their products. Social activities have been brought from the real world to the virtual world courtesy of social networking sites. Messages are sent in real time which now enable people to interact and share information. As a result, companies consider social media platforms as vital tools for succeeding in the online marketplace ( Ebrahim, 2020 ). The use of social media to commercially promote processes or events to attract potential consumers online is referred to as social media marketing (SMM). With the immense rise in community websites, a lot of organizations have started to find the best ways to utilize these sites in creating strong relationships and communications with users to enable friendly and close relationships to create online brand communities ( Ibrahim and Aljarah, 2018 ).

Social media marketing efficiently fosters communications between customers and marketers, besides enabling activities that enhance brand awareness ( Hafez, 2021 ). For that reason, SMM remains to be considered as a new marketing strategy, but how it impacts intentions is limited. But, to date, a lot of research on SMM is focused on consumer’s behavior, creative strategies, content analysis and the benefits of user-generated content, and their relevance to creating virtual brand communities ( Ibrahim, 2021 ).

New channels of communication have been created, and there have been tremendous changes in how people interact because of the internet developing various applications and tools over time ( Tarsakoo and Charoensukmongkol, 2020 ). Companies now appreciate that sharing brand information and consumer’s experience is a new avenue for brand marketing due to the widespread use of smartphones and the internet, with most people now relying on social media brands. Therefore, developing online communities has become very efficient. Social groups create a sense of continuity for their members without meeting physically ( Yadav and Rahman, 2017 ). A community that acquires products from a certain brand is referred to as a virtual brand community. Customers are not just interested in buying goods and services but also in creating worthwhile experiences and strong relationships with other customers and professionals. So, when customers are part of online communities, there is a cohesion that grows among the customers, which impacts the market. Therefore, it is up to the companies to identify methods or factors that will encourage customers to take part in these communities ( Ismail et al., 2018 ).

The online community’s nature is like that of actual communities when it comes to creating shared experiences, enabling social support, and attending to the members’ need to identify themselves, regardless of the similarities and variances existing between real-world communities and online communities ( Seo and Park, 2018 ). Regarding manifestations and technology, online communities are distinct from real-life communities since the former primarily use computers to facilitate their operation. A certain brand product or service is used to set up a brand community. Brand communities refer to certain communities founded based on interactions that are not limited by geographical restrictions between brand consumers ( Chen and Lin, 2019 ). Since consumers’ social relationships create brand communities, these communities have customs, traditions, rituals, and community awareness. The group members learn from each other and share knowledge about a product, hence appreciating each other’s actions and ideas. So, once a consumer joins a particular brand community, automatically, the brand becomes a conduit and common language linking the community members together because of sharing brand experiences ( Arora and Sanni, 2019 ).

Based on the perspective of brand owners, most research has focused on how social communities can benefit brands. However, there are also some discussions regarding the benefits that come from brand community members according to the members themselves to analyze how social community impacts its members ( Shareef et al., 2019 ). Consumer’s behavior is influenced by value so, when a consumer is constantly receiving value, it leads to consumer’s loyalty toward that brand. According to Alalwan et al. (2017) , a valuable service provider will create loyalty to a company and enhance brand awareness. Consumer value is essentially used in evaluating social networking sites. With better and easier options to create websites coming around, most consumers are attracted to a social community to know about a company and its goods. Furthermore, operators can learn consumer’s behavior through maintaining social interactions with customers. However, the social community should have great value. It should be beneficial to the potential customers by providing them with information relevant to the brand in question. Furthermore, customers should be able to interact with one another, thus creating a sense of belonging. From that, it is evident that a brand social community’s satisfaction affects community retention and selection.

Literature Review

Social media marketing activities.

Most businesses use online marketing strategies such as blogger endorsements, advertising on social media sites, and managing content generated by users to build brand awareness among consumers ( Wang and Kim, 2017 ). Social media is made up of internet-associated applications anchored on technological and ideological Web 2.0 principles, which enables the production and sharing of the content generated by users. Due to its interactive characteristics that enable knowledge sharing, collaborative, and participatory activities available to a larger community than in media formats such as radio, TV, and print, social media is considered the most vital communication channel for spreading brand information. Social media comprises blogs, internet forums, consumer’s review sites, social networking websites (Twitter, Blogger, LinkedIn, and Facebook), and Wikis ( Arrigo, 2018 ).

Social media facilitates content sharing, collaborations, and interactions. These social media platforms and applications exist in various forms such as social bookmarking, rating, video, pictures, podcasts, wikis, microblogging, social blogs, and weblogs. Social networkers, governmental organizations, and business firms are using social media to communicate, with its use increasing tremendously ( Cheung et al., 2021 ). Governmental organizations and business firms use social media for marketing and advertising. Integrated marketing activities can be performed with less cost and effort due to the seamless interactions and communication among consumer partners, events, media, digital services, and retailers via social media ( Tafesse and Wien, 2018 ).

According to Liu et al. (2021) , marketing campaigns for luxury brands consist of main factors such as customization, reputation, trendiness, interaction, and entertainment which significantly impact customers’ purchase intentions and brand equity. Activities that involve community marketing accrue from interactions between events and the mental states of individuals, whereas products are external factors for users ( Parsons and Lepkowska-White, 2018 ). But even though regardless of people experience similar service activities, there is a likelihood of having different ideas and feelings about an event; hence, outcomes for users and consumers are distinct. In future marketing, competition will focus more on brand marketing activities; hence, the marketing activities ought to offer sensory stimulation and themes that give customers a great experience. Now brands must provide quality features but also focus on enabling an impressive customer’s experience ( Beig and Khan, 2018 ).

Social Identification

A lot of studies about brand communities involve social identification, appreciating the fact that a member of a grand community is part and parcel of that community. Social identity demystifies how a person enhances self-affirmation and self-esteem using comparison, identity, and categorization ( Chen and Lin, 2019 ). There is no clear definition of the brand community or the brand owner, strengthening interactions between the community and its members or creating a rapport between the brand and community members. As a result, members of a community are separated into groups based on their educational attainment, occupation, and living environment. Members of social networks categorize each other into various groups or similar groups according to their classification in social networks ( Salem and Salem, 2021 ).

Brand identification and identification of brand communities emanate from a similar process. Users can interact freely, hence creating similar ideologies about the community, alongside strengthening bonds among members, hence enabling them to identify with that community. The brand community identity can also be considered as a convergence of values between the principles of the social community and the values of the users ( Wibowo et al., 2021 ).

According to Lee et al. (2021) , members of a brand social community share their ideas by taking part in community activities to help create solutions. When customers join a brand community, they happily take part in activities or discussions and are ready to help each other. So, it is evident that social community participation is impacting community identity positively. Community involvement entails a person sharing professional understanding or knowledge with other members to enhance personal growth and create a sense of belonging ( Gupta and Syed, 2021 ). According to Haobin Ye et al. (2021) , it is high time community identity be incorporated in virtual communities since it is a crucial factor that affects the operations of virtual communities. Also, community identity assists in facilitating positive interactions among members of the community, encouraging them to actively take part in community activities ( Assimakopoulos et al., 2017 ). This literature review suggests that social communities need members to work together. Individuals who can identify organizational visions and goals become dedicated to that virtual company.

Satisfaction

Customer’s satisfaction involves comparing expected and after-service satisfaction with the standards emanating from accumulated previous experiences. According to implementation confirmation theory, satisfaction is a consumer’s expected satisfaction with how the services have lived up to those expectations. Customers usually determine the level of satisfaction by comparing the satisfaction previously experienced and the current one ( Pang, 2021 ).

According to recent studies, community satisfaction impacts consumer’s loyalty and community participation. A study community’s level of satisfaction is determined by how its members rate it ( Jarman et al., 2021 ). Based on previous interactions, the community may be evaluated. When the members are satisfied with their communities, it is manifested through joyful emotions, which affect the behavior of community members. In short, satisfaction creates active participation and community loyalty ( Shujaat et al., 2021 ).

Types of Intentions

A lot of studies about information and marketing systems have used continuance intention in measuring if a customer continues to use a certain product or service. The willingness of customers to continue using a good or service determines if service providers will be successful or not. According to Zollo et al. (2020) , an efficient information marketing system should persuade users to use it, besides retaining previous users to guarantee continued use.

Operators of social networks must identify the reason propelling continued use of social network sites, alongside attracting more users. Nevertheless, previous studies on information systems in the last two decades have mainly concentrated on behavior–cognition approaches, for instance, the technology acceptance model (TAM), theory of planned behavior (TPB), and theory of reasoned action (TRA) with their variants ( Tarsakoo and Charoensukmongkol, 2020 ; Jamil et al., 2021b ). According to Ismail et al. (2018) , perceived use and satisfaction positively impact a user’s continuance intention. The continued community members’ participation has two intentions. Continuance intention is the first one. It defines the community member’s intent to keep on using the community ( Beig and Khan, 2018 ; Dunnan et al., 2020 ). Then, recommendation intention, also known as mouth marketing, describes every informal communication that takes place among community members regarding the virtual brand community. Previous studies about members of a virtual community mostly entailed the continuous utilization of information systems ( Seo and Park, 2018 ; Sarfraz et al., 2021 ). Unlike previous studies, this study focuses on factors that support the continued participation of community members. So, besides determining how usage purpose affects continuance intention, the study also investigated the factors that influence users’ willingness to take part in community activities ( Gul et al., 2021 ).

Nevertheless, it is hard to determine and monitor whether a certain action occurred (recommendation or purchase) during empirical investigations. Consumers will seek relevant information associated with their external environment and experiences when purchasing goods ( Shareef et al., 2019 ). Once they have collected significant information, they will evaluate it, and draw comparisons from which customer’s behavior is determined. Since purchase intention refers to a customer’s affinity toward a particular product, it is a metric of a customer’s behavioral intention. According to Liu et al. (2021) , the probability of a customer buying a particular product is known as an intention to buy. So, when the probability is high, it simply means that the willingness to purchase is high. Past studies consider purchase intention as a factor that can predict consumer’s behavior alongside the subjective possibility of consumer’s purchases. According to Chen and Qasim (2021) , from a marketing viewpoint, if a company wants to retain its community besides achieving community targets while establishing successful marketing via the community, at least three objectives are needed. They include membership continuance intention, which entails members living up to their promises in the community and also the willingness to belong to the community ( Yadav and Rahman, 2018 ; Naseem et al., 2020 ). On the other side, community recommendation intention entails the willingness of members to recommend or refer community members to other people who are not members ( Jamil et al., 2021a ; Mohsin et al., 2021 ). The next consideration is the community participation intention of a member, which involves their willingness to participate in the activities of the brand community. Unlike past literature about using information systems, this study demystified how SMMAs influence purchase intention and participation intention ( Alalwan et al., 2017 ).

Development of Hypotheses

People with similar interests can get a virtual platform to discuss and share ideas courtesy of social media. Sustained communication of social media allows users to create a community. Long-lasting sharing of growth and information fosters the development of strong social relationships. The information posted on social media platforms by an individual positively correlates with the followers the user has. Regarding the discussion above, we proposed the following hypothesis:

H1: Social media marketing activities (SMMAs) have a significant impact on social identification.

The study of Farivar and Richardson (2021) on users’ continuance intention confirmed that it is influenced by satisfaction after service. Social media studies are also of the thought that satisfaction significantly affects continuance intention. So, a consumer will measure the satisfaction of service after using it. Mahendra (2021) claims that satisfaction influences repurchase behavior. Repurchase intention emanates from a customer’s satisfaction with a good or service. People who have similar interests may interact and cooperate in a virtual world via social media platforms. A community on social media may be formed by regularly connecting with people and exchanging information with them. Members benefit from long-term information and growth exchanges that enable them to create strong social relationships. A lot of studies have pointed out that repurchase intention and customer’s satisfaction are positively and highly related. Besides, marketing studies noted that satisfactory experience after using a product would impact the intention of future repurchase. Hence, we proposed the following hypothesis:

H2: SMMAs have a significant impact on satisfaction.

The study by Suman et al. (2021) on American consumer’s behavior suggested that members taking part in community activities (meetups, discussion, and browsing) influence their brand-associated behavior. According to Di Minin et al. (2021) , the brand identity of a consumer has a positive impact on satisfaction. Consumers capitalize on online communities to share their experiences and thoughts about a grand regularly and easily ( Sirola et al., 2021 ). These experiences make up the customer to brand experiences and establish a sense of belonging, trust, and group identity. In a nutshell, this study suggests that identity will enable members to recognize their community, hence confirming that members have similar experiences and feelings with a particular brand and feel united in the group ( Shujaat et al., 2021 ). Strong group identity means that members are integrated closely into the brand communities and highly regard the community. Hence, we proposed the following hypothesis:

H3: Social identification has a significant impact on satisfaction.

Brand communities are beneficial in the sense that they enable sharing of marketing information, managing a community, and exploring demands ( Dutot, 2020 ). These activities are likely to enhance consumer’s rights and increase customer’s satisfaction ( Sahibzada et al., 2020 ). A customer who makes an online transaction will be highly satisfied with a website that provides a great experience ( Koçak et al., 2021 ). Enhancing customer’s satisfaction, encouraging customer intentions, creating community loyalty, and fostering communication and interactions between community users are crucial to lasting community platform management ( Pang, 2021 ). Hence, we proposed the following hypotheses:

H4: Satisfaction has a significant impact on continuance intention.

H5: Satisfaction has a significant impact on participate intention.

H6: Satisfaction has a significant impact on purchase intention.

Thaler (1985) proposed transaction utility theory, in which consumers’ willingness to spend money is influenced by their perceptions of value. Researchers such as Dodds (1991) claimed that buyers only become ready to purchase after they have established a sense of value for a product. According to Petrick et al. (2001) , a product’s quality is dependent on the customer’s satisfaction. Several studies have shown that enjoyment, perceived value, and behavioral intention are all linked together. Hence, we proposed the following hypothesis:

H7: Social identification mediates the relationship between SMMA and satisfaction.

When it comes to information systems, Bhattacherjee et al. (2008) discovered that people’s continual intention is derived from their satisfaction with the system after they have used it. Studies on employee’s satisfaction in the workplace have shown that it has a substantial influence on CI. The amount of satisfaction that users have with the system that they have previously used is the most important factor in determining their CI, according to research on information system utilization intention.

In other words, the customer’s contentment with the product leads to the establishment of a desire to buy the thing again, as mentioned by Assimakopoulos et al. (2017) . Numerous studies show a strong link between customer’s satisfaction and their propensity to return for another transaction. According to a lot of marketing studies, customers who have a pleasant experience with a product are more likely to repurchase it. Hence, we proposed the following hypotheses:

H8: Satisfaction mediates the relationship between social identification and continuance intention.

H9: Satisfaction mediates the relationship between social identification and participate intention.

H10: Satisfaction mediates the relationship between social identification and purchase intention.

Figure 1 shows the research framework of this study.

Figure 1. Conceptual framework.

Conceptual Framework

Research methodology.

This study designed a questionnaire according to the hypotheses stated above. The participants in this study were experienced users of two social media platforms Facebook and Instagram in Pakistan. A self-administered questionnaire was used to collect data from respondents. A pilot study with 40 participants was carried out. Since providing recommendations, revisions were made to the final questionnaire to make it more understandable for the study’s respondents. To ensure the content validity of the measures, three academic experts of marketing analyzed and make improvements in the items of constructs. The experts searched for spelling errors and grammatical errors and ensured that the items were correct. The experts have proposed minor text revisions to social identification and satisfaction items and advised that the original number of items is to be maintained. This study used an online community to invite Facebook and Instagram users to complete the questionnaire in the designated online questionnaire system. Online questionnaires have the following advantages ( Tan and Teo, 2000 ): (1) sampling is not restricted to a single geological location, (2) lower cost, and (3) faster questionnaire responses. A total of 353 questionnaires were returned from respondents. There were 353 appropriate replies considered for the final analysis.

The study used items established from prior research to confirm the reliability and validity of the measures. All items are evaluated through 5-point Likert-type scales where “1” (strongly disagree), “3” (neutral), and “5” (strongly agree).

Dependent Variable

To get a response about three dimensions of intention (continuance, participate, and purchase), we used eight items adopted from prior studies;

1. Continuance intention is measured by three items from the study of Bhattacherjee et al. (2008) , and the sample item is, “I intend to continue buying social media rather than discontinue its use.”

2. Participate intention is evaluated by three items from the work of Debatin et al. (2009) , and the sample item is, “my intentions are to continue participating in the social media activities.”

3. Purchase intention was determined by two items adapted from the work of Pavlou et al. (2007) , and the sample item is, “I intend to buy using social media in the near future.”

Independent Variable

To analyze the five dimensions of SMMAs, we used eleven items adopted from a prior study of Kim and Ko (2012) .

1. Entertainment is determined by two items and the sample item is, “using social media for shopping is fun.”

2. Interaction is evaluated by three items, and the sample item is, “conversation or opinion exchange with others is possible through brand pages on social media.”

3. Trendiness is measured by two items, and the sample item is, “contents shown in social media is the newest information.”

4. Customization is measured by two items, and the sample item is, “brand’s pages on social media offers customized information search.”

5. Word of mouth is measured by two items, and the sample item is, “I would like to pass along information on the brand, product, or services from social media to my friends.”

Mediating Variables

We used two mediating variables in this study,

1. Social identification was measured with five items adopted from the prior study of Bhattacharya and Sen (2003) , and the sample item is, “I see myself as a part of the social media community.”

2. Satisfaction was evaluated with six items adopted from the study of Chen et al. (2015) , and the sample item is, “overall, I am happy to purchase my desired product from social media.”

This research employs a partial least square (PLS) modeling technique, instead of other covariance-based approaches such as LISREL and AMOS. The reason behind why we pick PLS-SEM is that it is most suitable for confirmatory and also exploratory research ( Hair Joe et al., 2016 ). Structural equation modeling (SEM) has two approaches, namely covariance-based and PLS-SEM ( Hair et al., 2014 ). PLS is primarily used to validate hypotheses, whereas SEM is most advantageous in hypothesis expansion ( Podsakoff et al., 2012 ). A PLS-SEM-based methodology would be done in two phases, first weighing and then measurement ( Sarstedt et al., 2014 ). PLS-SEM is ideal for a multiple-order, multivariable model. To do small data analysis is equally useful in PLS-SEM ( Hair et al., 2014 ). PLS-SEM allows it easy to calculate all parameter calculations ( Hair Joe et al., 2016 ). The present analysis was conducted using SmartPLS 3.9.

Model Measurement

Table 1 shows this study model based on 31 items of the seven variables. The reliability of this study model is measured with Cronbach’s alpha ( Hair Joe et al., 2016 ). As shown in Table 1 , all items’ reliability is robust, Cronbach’s alpha (α) is greater than 0.7. Moreover, composite reliability (CR) fluctuates from.80 to.854, which surpassed the prescribed limit of 0.70, affirming that all loadings used for this research have shown up to satisfactory indicator reliability. Ultimately, all item’s loadings are over the 0.6 cutoff, which meets the threshold ( Henseler et al., 2015 ).

Table 1. Inner model evaluation.

The Cronbach’s alpha value for all constructs must be greater than 0.70 is acceptable ( Hair et al., 2014 ). All the values of α are greater than 0.7 as shown in Table 1 and Figure 2 .

Figure 2. Measurement model.

Convergent validity is measured by CR and AVE, and scale reliability for each item ( Hair Joe et al., 2016 ). The scholar says that CR and AVE should be greater than 0.7 and 0.5, respectively. By utilizing CR and average variance extracted scores, convergent validity was estimated ( Fornell and Larcker, 1981 ). As elaborated in Table 3 , the average variance extracted scores of all the indicators are greater than 0.50 and CR is higher than.70 which is elaborating an acceptable threshold of convergent validity and internal consistency. It is stated that a value of CR, that is, not less than 0.70, is acceptable and evaluated as a good indicator of internal consistency ( Sarstedt et al., 2014 ). Moreover, average variance extracted scores of more than 0.50 demonstrate an acceptable convergent validity, as this implies that a specific construct with greater than 50% variations is clarified by the required indicators.

Table 2. A mediation analysis.

Table 3. Discriminant validity.

This study determines the discriminant validity through two techniques named Fornell–Larcker criterion and heterotrait–monotrait (HTMT) ( Hair Joe et al., 2016 ). In line with Fornell and Larcker (1981) , the upper right-side diagonal values should be greater than the correlation with other variables, which is the square root of AVE, which indicates the discriminant validity of the model. Table 3 states that discriminant validity was developed top value of variable correlation with itself is highest. The HTMT ratios must be less than 0.85, although values in the range of 0.90 to 0.95 are appropriate ( Hair Joe et al., 2016 ). Table 3 displays that all HTMT ratios are less than 0.90, which reinforces the statement that discriminant validity was supported in this study’s classification.

To determine the problem of multicollinearity in the model, VIF was calculated for this purpose. The experts said that if the value of VIF is greater than 5, there is no collinearity issue in findings ( Hair et al., 2014 ). The results indicate that the inner value of VIF for all indicators must fall in the range of 1.421 to 1.893. Furthermore, these study findings show no issue of collinearity with data, and the study has stable results.

To evaluate “the explanatory power of the model,” the R 2 value was analyzed for every predicted variable. It shows the degree to which independent variables illustrate the dependent variables. R 2 value in “between 0 and 1 with higher values shows a higher level of predictive accuracy. Subsequent values of R 2 describe 0.25 for weak, 0.50 for moderate, and 0.75 for” substantial. An appropriate model is indicated by R 2 greater than 0.5 in primary results. In Figure 2 , the value of R 2 greater than 0.5 on all exogenous constructs, which also means that the model has strong predictive accuracy ( Hair Joe et al., 2016 ).

Table 4 displays the percentage of variance clarified for every variable: 62.7% of continuous intention, 55.5% of participate intention, 54.5% for purchase intention, 80.9% for satisfaction, and 81.8% for social identification. In general, results demonstrate that values of R 2 of endogenous variables are greater than 80%, which is the sign of a substantial “parsimonious model” ( Sarstedt et al., 2014 ). Most importantly, the outputs give a significant validation of the model. Q 2 values of all four 5 latent variables suggest that the model is extremely predictive ( Hair et al., 2014 ).

Table 4. Predictive accuracy and relevance of the model.

Hypothesis Testing

This study evaluates the significance of relationships using bootstrapping at 5,000 with a replacement sample ( Hair Joe et al., 2016 ; Awan et al., 2021 ). The findings show that SMMAs have significant relationship with social identification (β = 0.905, t -value = 36.570, p = 0.000) which accept the H1. The findings show that SMM significantly influences the satisfaction (β = 0.634, t -value = 8.477, p = 0.000). Social identification has significant positive relationship with satisfaction as shown in Table 5 (β = 0.284, t -value = 4.348, p = 0.000) which accept the H3. The results show that satisfaction has significant relationship with continuous intention (β = 0.792, t -value = 15.513, p = 0.000) which support the H4. The findings show that satisfaction has strong positive relationship with participant intention (β = 0.745, t -value = 12.041, p = 0.000), which support the H5. The findings show that satisfaction has strong positive relationship with purchase intention (β = 0.739, t -value = 12.397, p = 0.000) which support the H6. The findings of the current investigation support H1, H2, H3, H4, H5, and H6. The results show that H4, H1a, H1b, H3a, H3b, H2a, and H2b are accepted (refer to Table 5 and Figure 3 ).

Table 5. Hypothesis testing.

Figure 3. Structural model.

Preacher and Hayes (2008) argue that if the VIF value is greater than 80%, then it shows full mediation, and value of VIF equal to 20 to 80% which indicate the partial mediation and if VIF falls below 20%, then there is no mediation. The findings show that social identification mediates the relationship between SMM and satisfaction (β = 0.213, t -value = 3.570, p -value = 0.000) and indirect effect (β = 0.257, t -value = 4.481, p -value = 0.000) with variance accounted for (VAF) 75% which show partial mediation. In this, the VAF describes the size of the indirect effect in relation to the total effect ( Hayes and Preacher, 2010 ). The findings show that satisfaction mediates the relationship between social identification and continuous intention (β = 0.342, t -value = 3.435, p -value = 0.000) and indirect effect (β = 0.225, t -value = 4.636, p -value = 0.000) with VAF 64% which show partial mediation. In this, the VAF describes the size of the indirect effect in relation to the total effect ( Hayes, 2009 ). The findings show that satisfaction mediates the relationship between social identification and participant intention (β = 0.324, t -value = 5.325, p -value = 0.000) and indirect effect (β = 0.211, t -value = 4.338, p -value = 0.000) with VAF 73% which show partial mediation. The findings show that satisfaction mediates the relationship between social identification and purchase intention (β = 0.312, t -value = 3.434, p -value = 0.000) and indirect effect (β = 0.3.213, t -value = 5.437, p -value = 0.000) with VAF 78% which show partial mediation (refer to Table 2 ).

Discussion and Conclusion

The study was about SMMAs as proposed by Kim and Ko (2012) , and it investigated which factors influence social media usage. The findings of the study include the following:

Most studies about social websites have not exhausted the impact of SMMAs. According to this study, SMMAs significantly affect social identification, which ultimately influences purchase decisions, participation decisions, continuance intention, and satisfaction. The study demystified social media usage intention. The findings were that SMMAs could sustain corporate brands. According to Beig and Khan (2018) , unlike blog marketing and keyword advertising that were associated with content, SMM gets to the targeted audiences to enhance the impact of the information being shared by creating strong relationships in the online community. Therefore, service providers of social media must put into consideration means of increasing the impact of SMMAs. To boost SMMAs, operators should increase activity on the forum. The members of a community can be allowed to explain the guiding factors behind choosing a particular brand over that of competitors for other members to know the competing brands. From the discussions and sharing of knowledge, members get an opportunity to understand why they like a particular brand, thus enhancing brand loyalty and community cohesion ( Yadav and Rahman, 2017 ).

The study also confirmed that most administrators are concerned with the influence of brand community management in creating business advantage. According to Tarsakoo and Charoensukmongkol (2020) , marketing strategies and tools have undergone tremendous changes since the inception of social media. Consumers no longer must rely on traditional media to acquire information about a product before making their purchase since social media can effectively and easily avail such information. For that reason, social media service providers must come up with effective measures of controlling publication timing, frequency, and content to achieve the set marketing targets. According to this study, if a company can successfully assist users to easily identify with a particular brand community, strong relationships will be fostered between the consumers and the brand, hence creating customer’s loyalty ( Ebrahim, 2020 ). Besides, users may stop using competitors’ products. So, companies need to appreciate that proper management of online strategies and brand community in creating community identity enhances brand’s competitiveness and inspires members of the brand community to shun using goods and services from competitors.

Limitations and Recommendations

Regardless of the efforts geared toward enabling in-depth data collection, research methodology, and research structure, there were still various limitations that ought to be dealt with in studies to be conducted in the future. For instance, using online questionnaires in data collection, some members might have been very willing to fill them because of their community identity, hence enabling self-selection bias that may impact the validity and authenticity of the outcomes. Besides, a cross-sectional sample was used in the study; hence, results from the analysis can only demystify individual usage patterns on well-known social media. Nevertheless, the different social media platforms provide different services; hence, long-term usage needs long-term observation. The outcomes of growth model analysis with the experimental values and browsing experiences of users at the various phases in longitudinal studies to be conducted in the future may be increasingly conclusive on casual relationships with variables. The third limitation of the study is that different countries or areas have different preferences regarding social media. Future studies should unravel the reasons behind individuals from various cultural backgrounds or countries using different social media platforms and what might be the demands and motivations behind their preferences. Besides, new social networking sites such as Facebook and Twitter have unique characteristics which are different from traditional sites. Future studies should also focus on this shift. For this study, the emphasis was on SMMAs’ influence on user’s behavior and usage demands.

Data Availability Statement

The raw data supporting the conclusion of this article will be made available by the authors, without undue reservation.

Author Contributions

All authors listed have made a substantial, direct, and intellectual contribution to the work, and approved it for publication.

This study was partly supported by the National Social Science Foundation of China (no. 19ZDA081).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The reviewer ZA declared a shared affiliation with one of the authors, SG, to the handling editor at time of review.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords : social media marketing activities, social identification, satisfaction, continuance intention, participate intention, purchase intention

Citation: Jamil K, Dunnan L, Gul RF, Shehzad MU, Gillani SHM and Awan FH (2022) Role of Social Media Marketing Activities in Influencing Customer Intentions: A Perspective of a New Emerging Era. Front. Psychol. 12:808525. doi: 10.3389/fpsyg.2021.808525

Received: 03 November 2021; Accepted: 20 December 2021; Published: 17 January 2022.

Reviewed by:

Copyright © 2022 Jamil, Dunnan, Gul, Shehzad, Gillani and Awan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Syed Hussain Mustafa Gillani, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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• 09 Apr 2024

Regardless of your experience, mastering digital marketing strategy can help advance your career . With impactful trends like the emergence of e-commerce and mobile shopping platforms, expectations for leaders have evolved .

“These technologies completely changed the way consumers connect with brands, how they search for information, and how they buy products,” says Harvard Business School Professor Sunil Gupta, who teaches the online course Digital Marketing Strategy . “They’re the reason digital marketing has become an integral and important part of every company.”

If you want to prepare for business’s demands in the digital age, earning a digital marketing certificate can be an effective method.

Access your free e-book today.

What Is a Digital Marketing Certificate?

A digital marketing certificate is a document denoting the completion of an online marketing course . Like many business certificates, pursuing one can enable you to elevate your career with practical skills and increased confidence .

Compared to in-person offerings, an online digital marketing certificate can be a flexible, cost-effective way to further your education if you’re a working professional who needs to balance coursework with your job .

For example, Digital Marketing Strategy is an online certificate program that can equip you with tools, frameworks, and tactics to engage and retain customers , make data-driven decisions , and position your organization for success. It also delves into how to:

• Compete with emerging brands
• Create a digital marketing plan
• Use paid, owned, and earned media

If you’re ready to become a more strategic marketer, here’s how a digital marketing certificate can help you gain the necessary knowledge and skills.

Related: What to Expect from HBS Online’s Digital Marketing Strategy Course

How a Digital Marketing Certificate Can Help Advance Your Career

1. boost your digital confidence.

No matter your workplace, technology likely plays a part in your daily responsibilities. According to a study by media and marketing technology company Foundry , 93 percent of companies have adopted or plan to adopt a digital-first business strategy .

Embracing that shift requires proficiency in emerging technologies like automation and online platforms. In Digital Marketing Strategy , Anne Lewnes, chief marketing officer at technology company Adobe, talks about technology’s role in understanding your customers.

“I don’t think marketing has actually changed fundamentally,” Lewnes says. “A good idea, a good product—those are always going to be core to marketing. I think engaging your audience with some emotional kind of stimulus is always going to be important. I think the thing that’s really changed is the ability to understand the customer deeply. So you need technology to be able to do that.”

Beyond understanding customer needs , boosting your technology proficiency can improve your ability to work and lead remotely . By taking an online digital marketing course, you can deepen your understanding of digital tools, improve project management and team collaboration, align strategies with consumers’ expectations, and prepare for and adapt to trends.

2. Develop Industry Skills

A certificate program can also enable you to jumpstart your career advancement with digital marketing skills .

Data show employers value skills more than any other asset on your resume. According to a report by software company TestGorilla , 73 percent of employers have adopted skills-based hiring—prioritizing them over past job titles.

Such skills include:

• Technology proficiency
• Data analysis
• Search engine marketing
• Search engine optimization
• Brand development
• Email marketing
• Social media

An interactive online learning experience cannot only help you acquire but practice those skills. For instance, Digital Marketing Strategy features insights from leading brands, agencies, and expert practitioners, including:

• The Growth Agency’s Vice President of Client Service and Inclusion Marketing Bianca Reed
• OOFOS’ Head of E-Commerce Kate Laliberte
• MMI Agency’s CEO Maggie Malek
• HBS Online’s Senior Managing Director Simeen Mohsen
• Blogger, podcaster, and social media influencer Erica Ligenza

Through their stories, you can apply course concepts to real-world scenarios and develop skills to engage and retain your target audience .

3. Expand Your Professional Network

While skills and confidence matter to reaching your professional development goals , building a strong professional network is also invaluable.

Your network can help you:

• Identify career opportunities
• Better understand your organization or industry
• Foster collaboration

For example, by joining the HBS Online Community , you can connect with like-minded business professionals from around the world before, during, or after your course to open yourself to new perspectives, cultivate lifelong learning, and participate in both in-person and virtual events.

Learn more about the HBS Online Community in the video below, and subscribe to our YouTube channel for more content!

“It’s rare to have the opportunity to learn from professionals around the world, in different stages in their career, and from an array of professions striving for the same objective,” said HBS Online learner Carlvin Sylvain Dorvilier . “Not only were we united on all social platforms, but each city had several meetups organizing study groups, group outings, and networking opportunities to learn from one another.”

Related: How to Build Your Network Through the HBS Online Community Platform

4. Improve Your Decision-Making

Being a digital marketer can entail making rapid decisions. With constantly evolving online platforms and channels, a digital marketing certificate can enhance your decision-making skills by teaching you how to measure business performance using key performance indicators (KPIs) across the marketing funnel’s three stages:

• Awareness: Introducing potential customers to your brand or product to address a problem they may have
• Consideration: Making customers aware of your brand or product while they evaluate it against alternatives
• Decision: Influencing consumers’ purchasing decisions using the information you gather during the previous stages

By focusing on specific KPIs in each stage—such as website traffic and social media impressions—you can improve your strategic planning and digital marketing budget allocation.

“As you balance multiple goals, the metrics you use and the data you get should influence where you put your marketing dollars,” Gupta says in Digital Marketing Strategy . “As you measure the effectiveness of your current efforts, these data can be a powerful tool to help inform where you should focus next.”

How to Become a Digital Marketer

Taking advantage of professional development opportunities is crucial to advancing your career. Whether you’re a marketing or non-marketing professional, Digital Marketing Strategy offers a flexible, cost-effective way to develop your skills and knowledge.

Through real-world cases and an interactive, online learning experience, you can learn how to develop data-driven strategies and use the latest digital marketing tools to engage and retain customers in a constantly changing market.

Are you interested in earning a digital marketing certificate? Enroll in Digital Marketing Strategy to develop the skills and knowledge to take your career to the next level. If you want to take an online course but aren’t sure where to start, download our free guide to online learning success .

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12 ways to elevate your social media strategy in 2024

No doubt about it: social media is one of the most crucial tools in any hotel’s marketing strategy for promotion and advertisement. Social networks can give your property exposure like never before to help increase brand awareness and drive more direct bookings.

As a lodging operator, you can showcase your property’s features and services and interact with guests and potential guests through various social channels. These channels allow you to promote your hotel as an experience , not just a place to stay for the night.

Through social media, hotel brands can communicate directly with guests and build meaningful relationships. Since the hospitality industry offers a highly personal experience that naturally inclines people to share and search for inspiring images, videos, travel hashtags, and testimonials, social media is the perfect platform to support and promote this rich content.

Read on to learn more about the importance of social media for hotels, along with 12 social media marketing strategies to try in 2024.

What is a social media marketing strategy?

A social media marketing strategy in the hotel industry is a collection of ideas and tactics for hoteliers to implement to achieve specific goals. It requires a thorough understanding of your target demographics and how they like to consume content online.

Social media marketing goals 

A good social media marketing strategy should be multi-pronged and designed to accomplish several goals simultaneously. While results may not be immediately visible, consistent posting over time can help achieve a sizeable impact. Ensure that you’re tracking metrics regularly to be sure your efforts are positively contributing to your hotel business. 

The goals of your hotel’s social media marketing strategy can include:

• Engagement. Interact and collaborate with current and potential customers.
• Brand awareness. Create a unique voice for your brand that speaks to your hotel guest demographics.
• Analytics . Acquire real-time market data and gain insight into your target audience and performance.
• Acquisition . Optimize advertising campaigns and promote products, services, special offers, and contests to drive direct bookings.
• Content marketing . Post content to drive traffic to your hotel website through search engine optimization (SEO) .
• Customer service. Respond to questions and streamline communication through comments and messenger.

Top 5 social media channels in 2024

The popularity of social channels rises and falls as trends change and new platforms emerge. Here are the 5 most popular social channels in 2024.

• Facebook. Still reigning as the largest social media network in the world, Facebook has over 3.03 billion monthly active users as of Q3 2023. It’s a great platform to build community, run ads, and connect with guests.
• YouTube. The video giant is the second largest social media platform, with 2.49 billion monthly active users. YouTube’s 2023 Culture and Trends report found that 68% of people surveyed watch videos about a specific topic that they are into in multiple different formats, which is easily done on YouTube (short form, long form, live stream). 
• Instagram. This popular visual platform with Gen Z and millennials boasts 2 billion monthly active users and is popular for travel inspiration and research. 
• TikTok. A platform racing to the top of this list is TikTok, with more than 1.2 billion monthly active users. TikTok users spend 22.9 hours per month on the app. On TikTok, hotel brands can express their authentic identity and connect with users on a more personal basis.
• Snapchat. A multifaceted messaging app that allows users to send pictures, videos, and texts, Snapchat has over 750 million monthly active users.

12 social media strategies for hotels

1. share your brand’s voice and story.

Most properties are looking to make a name for themselves in the travel industry through social channels; however, it’s easy for any brand to get lost in this crowded space. The key to standing out is to develop your brand’s voice and consistently share your values to attract like-minded travelers to your property.

Remember, today’s consumer appreciates authenticity from the brands they interact with, so whether your brand is casual and friendly or high-energy and adventure-based, your voice should be unique to your brand and feature the people behind the camera. Through social media, tell your brand’s story and what makes you unique – highlight your staff, origin, and behind-the-scenes insights.

Once you’ve found your brand’s voice, your visual content, videos, descriptions, and interactions with travelers must be consistent with your brand culture and follow brand guidelines where possible. If you get particularly good at promoting your brand, your property can be featured in publications. In July 2023, Travel + Leisure featured 25 hotel brands that have nailed sharing their brand concept.

The Leela, a property included on Travel + Leisure’s list, has established a strong and consistent brand voice across its social platforms, including Youtube, Instagram, LinkedIn, X, and Facebook. All of their posts convey the brand’s unparalleled luxury,’ and they are able to inspire guests through beautiful imagery and simple captions.

            View this post on Instagram                         A post shared by 𝐓𝐡𝐞 𝐋𝐞𝐞𝐥𝐚 (@theleela)

2. Create shareable social media content

Creating shareable content is an art. To get it right, you need to break through the clutter and get into your audience’s mind. As a lodging operator, you must emphasize features that make your hotel stand out , including your unique design, beautiful surroundings, local food specialties, and nearby attractions worth sharing.

For example, the Casetta Group promotes its unique hotel brands using beautiful, high-quality photos coupled with captions that not only entice guests to stay, but promote other offerings, such as day passes to their pools and dive-in movie nights. The result has been a significant following on Instagram (11.4K followers).

            View this post on Instagram                         A post shared by Casetta (@casetta_group)

3. Offer exclusive deals

Social media audiences usually engage with businesses and brands because they’re a loyal consumer or admire the content created. To nurture the relationship with your existing audience, launch a marketing campaign that offers exclusive loyalty discounts. This approach shows both past and potential guests that you value their loyalty and are willing to recognize them with rewards.

Hotels can boost their engagement and widen their audience by rewarding travelers for using social media to promote their brand. Consider offering on-site perks, such as free drinks or discount vouchers, just for following your page. This way, you not only grow your social following but encourage followers to visit your property.

4. Arrange contests on various platforms

By launching contests on various platforms, you engage with a larger portion of your customer base and accumulate more followers. Because word of mouth is a powerful marketing tool, posting across social channels can help grow your audience and social following. 

Some popular social media contests include “caption this photo” contests, giveaways (tag 2 friends in the comments to win a free night stay), trivia games with prizes, and share your best travel photo or video contest (the guest is then featured on your social media page and you get to share genuine user-generated content).

Accor Live Limitless (ALL) launched a 2023 Instagram contest with the hashtag #Allyouwishfor2023, offering travelers the chance to win an amazing trip for two. Their video clearly explains how to enter the contest, backed with imagery from their properties.

            View this post on Instagram                         A post shared by ALL – Accor Live Limitless (@all)

5. Be consistent on all your hotel’s social media profiles

Social media marketing efforts aren’t typically rewarded overnight but through consistency and continued usage. To maintain active engagement and foster new bookings, you need to make sure you:

• Regularly share updates (special events, new amenities, staff stories, and more)
• Answer prospect inquiries in a timely manner
• Add new, high-quality images and videos
• Showcase your property’s best features
• Promote a unique guest experience

Logging in to all of your social media accounts individually to create daily posts can be time-consuming. You can use tools like Hootsuite or Sprout Social to help manage your accounts by allowing you to schedule future posts in bulk and view and manage all your social media platforms from one dashboard.

6. Try influencer marketing to spread awareness

Social media influencers or people with a strong social media following and personal brand have become popular with businesses and properties to advertise online. Influencers are usually content creators or bloggers who are viewed by their followers as brand ambassadors and people who share authentic experiences.

Ensure that you find an influencer that aligns with your hotel’s brand and voice. Micro-influencers (those with 1,000 – 5,000 followers) on Instagram, TikTok, or YouTube will be your best bet, as they have loyal followings with above-average engagement rates .

Usually, the value for the influencers is a free stay at the hotel, plus comped food, drinks, and activities. If you have the means to work with an influencer to promote your property and think it will be beneficial for your brand, you can take a hint from a Canadian ski resort, Sun Peaks Resort. The property hosted Instagram influencer and adventure photographer Callum Snape (778k followers), who shared jaw-dropping images, Instagram Stories, and Facebook videos promoting the resort as the area’s best-kept secret. His contributions helped garner wide interest in the property from Sun Peaks’ target audience, and they now have 53.6K followers.

            View this post on Instagram                         A post shared by Sun Peaks Resort (@sunpeaksresort)

7. Utilize travel hashtags

Over 1 million travel-related hashtags are searched on Instagram every week and can seriously boost your visibility. By strategically adding popular hashtags to your content, you make your social media posts more searchable and easier for potential guests to find. Research and scope out some of your competitors to find travel hashtags relevant to your brand to help your property get noticed. Also, consider creating your own unique branded hashtag (like ALL’s contest above) and encourage visitors to use it so you can build authentic, user-created branded content on your platform.

One tip is to use Instagram’s “tags” search feature to see photos with the same hashtag you plan to use and discover other relevant travel hashtags you can borrow. You can also use a tool like Hashtagify to help you conduct more in-depth hashtag research so you can always find the most popular and trending travel hashtags for your property.

8. Invest in paid advertising

Another digital marketing tool you can use is paid social media campaigns . These ads can generate positive results without the considerable expense associated with traditional advertising because of the detailed audience targeting available via social media platforms. The benefits of paid social advertising include:

• Built-in retargeting features
• Ability to advertise to incredibly specific demographics
• Enormous potential reach

Facebook ads are probably the most popular way to target your audience, and from the Facebook Ads Manager platform, you can also create ad posts for Instagram. Facebook ads allow you to target your ideal travel market by creating very specific audiences based on demographics like age, interests, location, places recently visited, income, and more.

9. Drive direct bookings on social media

On Facebook, you can create a “call to action” button that links directly to your booking engine so visitors browsing your social media page can get to your booking engine in one click. This is a great solution, especially for mobile devices, and will allow visitors to see rates, availability, and book all in one easy step.

Cloudbeds offers a commission-free booking engine for your website and Facebook page that’s flexible, customizable, and can help you drive more direct bookings, not only on your website and Facebook page but also via Instagram and Twitter. Properties like Hotel am Markt – Munich use this feature to drive direct bookings straight from their Facebook page.

10. Get active on TikTok

Love it or hate it, TikTok is the social platform taking over the world of social media marketing. Increasingly travelers are using TikTok to research and plan their upcoming trips, especially Gen Z’s, who make up 60% of platform users .

As short-form videos rise in popularity with a shift away from perfect, polished videos, travelers are leaning on TikTok to provide a realistic look into what to expect from their next trip. Hoteliers can easily produce short videos highlighting their property’s amenities, staff, and local attractions while taking advantage of TikTok trends to increase relevancy.

TikTok’s 2024 trends report predicts that this year’s three major trends will include:

• Curiosity peaked. Users are looking for hyper-relevant, delightful, and useful content that piques every curiosity to discover new ideas.
• Storytelling unhinged. The shift to where everyone can have a voice has unleashed creativity for all, where diverse voices and collaborative formats are flipping traditional storytelling on its head.
• Bridging the trust gap. There’s a growing trust gap between consumers and brands, making it crucial for properties to consider each campaign and post as an opportunity to share, listen, and learn to generate deeper loyalty on and off the platform.

Rixos Hotels utilizes TikToks to show off its amenities and guest experience. The comments prove the value of TikTok, with previous guests reminiscing about their experience at a Rixos Hotel and others inquiring about how to book. 

@rixoshotels The best vacation at #rixospremiumseagate #rixoshotels #rixosmoments #sharmelsheikh #summer ♬ Rixos Hotels – orijinal ses – Rixos Hotels

 11. Prioritize short-form videos

To increase your online presence and rank higher in search engine results, 2023 is when hoteliers need to prioritize short-form video content as part of their marketing plan .

Instagram Reels, YouTube Shorts, Live Videos, and TikToks will play a crucial role in search engine rankings as Google’s algorithm evolves to favor short-form videos this year ( Google considers anything under 10-minute short-form – but the shorter, the better!). Repurpose your videos across platforms; for example, if you create a great TikTok video, post it on Instagram as a Reel. Keep a library of videos on YouTube and leverage applicable content on your website to increase the use of rich content.

 12. Collaborate with local businesses

Forming partnerships with other businesses in your area can help expand your reach and drive more engagement on your social media posts. Highlight activities or local places to visit, like restaurants or cafes, in exchange for a repost on their social platforms.

Ensure you partner with businesses that make sense for your brand and who share a similar voice and values. Set goals on what you want to accomplish through this partnership and the tactics that will help you to achieve this goal. For example, you may choose to partner with a local restaurant, with one of your tactics being a social media contest where followers comment to be entered to win a night’s stay and a three-course meal. To enter, users must follow your social accounts and tag 3 friends. This tactic will help increase reach and drive more followers for both businesses. 

Building a comprehensive strategy 

Used by millions of people, social media is a powerful tool that’s constantly evolving with new opportunities and trends for marketers. Crafting an effective social media presence is a journey that will give you an advantage over competitors and can lead to developing lifelong loyal guests. Start small and get active on the platforms most used by your target demographics. Over time, you can increase the frequency of your posts and the number of active channels to build a comprehensive social media marketing strategy. 

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Top 10 most popular social media platforms in 2024

S ocial media continues to evolve, with new platforms entering the fray with novel ideas. However, it is difficult to challenge the established players. The latest research by marketing measurement platform Lifesight.io has just proved that. The firm used data from SEMrush to determine the top 10 most popular social media platforms in 2024 based on total visits last year. The list contains familiar names.

YouTube is unmatched in terms of user visits

According to the report, YouTube was visited 1.35 trillion times in 2023. That’s a staggering 80.49% growth in annual visits from 263.3 billion in 2019. This helped Google’s video platform build a massive lead at the top. Facebook is the next most popular social media platform in 2024, and it had only 216.4 billion visits last year. The Meta-owned platform remained almost flat between 2019 and 2023, growing just 15.33%.

The fact that YouTube’s total visits in 2023 were almost double the next nine most popular social media platforms is a testament to its popularity. Facebook, meanwhile, isn’t under threat despite a stagnation in recent years. It is distantly followed by X (formerly Twitter) with annual visits of 112.9 billion in 2023. Meta should be wary of X’s growth rate, though. The Elon Musk-owned platform saw a 63.19% increase in visits from 41.6 billion in 2019.

Instagram , another Meta-owned platform , registered 87.3 billion visits in 2023, up 62.40% from 32.8 billion in 2019. It is predominantly used on mobile with male users constituting two-thirds (67%) of its total visits. Reddit is right on its heels, though. With a better growth rate between 2019 and 2023 (68.72%), Reddit is threatening to leapfrog Instagram soon. It had 81.0 billion visits last year, making it the fifth most popular social media platform in 2024.

What should be a more concerning stat for Instagram is how Reddit has a similarly male-dominated user base and a high percentage of mobile traffic (72.27%). TikTok , the next platform on this list, is also moble-centric. However, it is equally popular among male and female users. Debuted in 2018, the Chinese app had just 0.7 billion visits in 2019. It reached 41.8 billion in 2023. Started as a shot-form video platform , it has expanded to other areas in recent years.

Most popular social media platforms have a majority male user base

WhatsApp, LinkedIn, Twitch, and Quora made up the top 10 most visited social media platforms last year. All of these platforms registered strong growth in annual visits between 2019 and 2023, ranging between 48% and 68%. While each has its specialty—WhatsApp is used for communication, LinkedIn for building professional networks, Twitch is popular in the gaming community, and Quora is used for knowledge sharing—there is something in common. All of these apps have a majority male user base.

Considering the current social media landscape, the top ten most popular platforms should remain unchanged next year. There may be some changes in the order (unlikely in the top three) but we don’t see a new entrant on the list. The looming nationwide ban on TikTok in the US may cause some shake-ups, though. TikTok had 170 million users in the US last year.

The post Top 10 most popular social media platforms in 2024 appeared first on Android Headlines .

Gen Z's fading dream

Human influencers are being replaced by artificial intelligence — and maybe that's a good thing.

More than half of Gen Zers want to be full-time influencers, a recent Morning Consult poll found, and it's not hard to see why. They've grown up watching their peers on YouTube film makeup tutorials, narrate their "Fortnite" games, and explain money . It's both where they live their lives and where they learn about the world. Plus, the career path sounds like a dream: You get to be your own boss, you can make more than you could at a traditional job, and you just have to be good on camera. Success stories of influencers making millions of dollars have only galvanized the generation.

"Gen Z explicitly wants to become influencers, are trained to become influencers, do camps to become influencers, strategize in a variety of ways to become an influencer," Angèle Christin, a professor at Stanford studying the influencer industry, told me.

A decade ago, many successful influencers stumbled into fame ; they were just regular people sharing about their lives or showcasing a niche skill when they suddenly found themselves with a huge audience and brands desperate to work with them. Anyone could strike it lucky at any time. But over the past several years, the influencer economy has shifted. Gone are the days when casual posting could suddenly turn into a lucrative career. On top of the work being an influencer requires, the competition gets tougher each day as more people vie for fame.

To make matters worse, influencer wannabes aren't competing only with humans — they're soon going to be competing with artificial intelligence. Advancements in AI tech have given birth to an industry of AI influencers , and major companies are beginning to show interest in their far more cost-effective approach to marketing. And who can really compete with that?

The influencer market is thoroughly saturated, Nikita Baklanov, an analyst at the influencer-marketing company HypeAuditor, said. Out of Instagram's some 2 billion monthly active users, "only 800,000 accounts have over 100,000 followers," he said, citing his company's research. That's less than 1% of accounts — but still a lot of accounts. And the number is growing.

In a crowded field, standing out takes work. Julia Broome, a social-media manager for influencers and celebrities, is already seeing the impact on longtime influencers. "Creators that were able to get a big buzz or get a huge following back in the day, they're experiencing some drop-off," she said.

Today, most influencers need to have a variety of revenue streams to stay financially viable, Baklanov said. They need to offer subscriptions, create their own merch, or sell a course. Increasingly, they need to exist beyond social media. "Platforms keep changing. The algorithms keep on changing. The formats keep on changing. And at some point, the influencers realize that they have to build a loyal audience, and they have to take that audience outside of social-media platforms," Christin, the Stanford professor, told me. That means setting up a podcast, running events, or creating a newsletter.

With tools like the AI image generator Midjourney and OpenAI's forthcoming Sora, creating content is becoming much-more affordable.

A Wall Street Journal article from 2021 suggested that the chances of making enough money from TikTok influencing for it to be an at least five-year career were less than 0.0001%. Only 100 people out of more than 1 million will succeed.

As the career path slips further out of reach, some people are turning to creating user-generated content for brands, rather than for their own audiences. Broome told me she'd seen a "big surge in UGC creators," who come at a much-lower cost to brands than traditional influencers. For creators, it's a nice way to make some money, but if your dream is to call your own shots for your own fan community, it's not a good sign. And now AI is poised to be another threat to job opportunities.

In 2016, Miquela Sousa, aka Lil Miquela , was born, as a fully formed Brazilian American 19-year-old. With 2.7 million followers on Instagram Miquela has been reported to rake in over $10 million a year in brand deals, with campaigns for Prada and Calvin Klein. She, however, is not a real person.

She is one of roughly 200 virtual influencers, according to Virtual Humans, a site that tracks these faux influencers, fueled by advanced motion graphics and a sizable team of people. Along with others, like Imma , who gets millions of views on TikTok, and Shudu , a virtual model, she proved people were willing to engage with someone who wasn't exactly real.

Miquela's success didn't spark a virtual-influencer revolution, but that was largely because of cost — human influencers were still cheaper. In the past couple of years, however, AI has advanced enough to make digital influencers much easier to create and run. With tools like the AI image generator Midjourney and OpenAI's forthcoming Sora , which makes extremely realistic videos from text prompts, creating content is becoming much-more affordable. "It costs almost nothing," Baklanov of HypeAuditor said. "And they can actually duplicate it in different languages."

Companies have been quick to capitalize on the potential. Late last year, Meta announced "a universe of characters," fueled by AI, with Instagram and Facebook accounts you could message with. "We've been creating AIs that have more personality, opinions, and interests, and are a bit more fun to interact with," the announcement said. An AI-model agency called The Clueless launched last year with two models. The founder told Euronews, "We did it so that we could make a better living and not be dependent on other people who have egos." Also last year, the AI-influencer company 1337 emerged from startup stealth mode with $4 million in backing. It has built dozens of AI entities each with niche interests, intricate backstories, and their own Spotify playlists .

Aurora is a 24-year-old climate-crisis activist on a mission to preserve Antarctica. Ezra , a 20-year-old intellectual studying at Oxford, likes hanging out at flea markets and cozy cafés. Wai is a 21-year-old abstract artist and sports enthusiast who's opened an art school for young talent.

Jenny Dearing, the company's cofounder and CEO, has been busy selecting content creators who can shape the behaviors of these entities via prompts. Once paired with a person to run things, each AI influencer will create posts and videos and start interacting with its audience. The AI learns from each interaction and uses the data that's gathered to become more engaging. It's no problem for an AI persona to respond to every comment or question it receives, and turn that into instant feedback for whoever is running the show.

This model of influencing requires far less time from real people, and it's particularly suited to those who are interested in influencing but don't want to put their own lives up for consumption. "For us, the long game is enabling more and more creators and brands to come in, create their own entity, manage that entity, advocate for that entity, and evolve and grow them over time," Dearing said.

Does it matter that an influencer is a human using AI tools or an AI character guided by a human? Either way, they are trying to sell us something.

For brands, being able to manage a consistent and engaging social-media presence at a low cost is an attractive pitch — and some have already expressed interest, Dearing told me. She sees AI influencers being used to provide a deep level of information, support, and guidance on brands and products. "Product placement is such a tiny potential of the future," she said. "For us, it's really a lot of knowledge exchange."

It will take time to see whether AI personas catch on , but the initial shift spells trouble for the future of influencing. Dearing doesn't think traditional influencers will disappear, but she thinks a shift toward AI ones is possible. "I see both scenarios existing for some period of time," she said. "What that balance looks like, who knows?" She added: "Over time, maybe it's an 80-20 where brands get really excited about having that control" and human influencers make up a smaller portion of the budget.

Do AI influencers really stand a chance at building trust with an audience? Most marketing experts say that what audiences really want on social media is authenticity . How you define that is up for debate, but it's clear that an AI-generated influencer is going to raise some eyebrows. After all, if a computer animation is promoting a new skincare product, you probably wouldn't trust it as much as you would a human influencer swearing it was life-changing. On the flip side, though, anyone who has found themself apologizing to ChatGPT knows exactly how quickly we start to see AI as human.

A 2020 paper in the Journal of Advertising found that AI influencers "can produce positive brand benefits similar to those produced by human celebrity endorsers." But it also found that when things went wrong with an AI influencer, there was similar reputational brand damage. There's potential for financial harm, too: Earlier this year, an Air Canada AI chatbot gave incorrect information about a discount to a customer. A tribunal ruled that the company was bound by that and had to provide a refund. A study in the European Journal of Marketing found that consumers were just as likely to follow an AI influencer as a human influencer but that they didn't trust the AI influencer as much. They were, however, more likely to talk with others about the AI influencer, which could turn out to be a positive for brands.

The trust question may already be moot, though. As AI chatbots have become more commonplace, most of us are already using them regularly. Chatbots are used for healthcare support, for therapy , and to warn teens of the dangers of too much social media — how different is an AI influencer, really? Was the Air Canada customer wrong to trust the AI bot's information? Clearly, the court didn't think so.

You could even argue that there's something more authentic about a brand using an AI entity to market itself and engage with people than a human turning themself into a brand to appeal to the algorithmic robots of a social-media platform. We already know that influencers carefully craft their presentation, often with a manager or coach. Does it matter that an influencer is a human using AI tools or an AI character guided by a human? Either way, they are trying to sell us something.

The social-media-management platform Hootsuite's 2024 Social Media Trends report said: "The most successful brands will redefine 'authenticity.'" The focus won't be on who is creating the content but on whether the content is compelling. As Dearing sees it, we're moving toward an information-driven experience. "Ultimately, these influencers become a really lovely visual way to engage on social platforms that are more knowledge-based," she said.

Some experts have a significantly more pessimistic take: Eric Schmidt, a former Google CEO, and Jonathan Haidt, a social psychologist and author, wrote last year about the potential for "skillful manipulation of people by AI super-influencers." This would be possible, they suggested, by the potential for generative AI to be highly personalized to individual wants, needs, and interests. AI has also been used to create deepfakes of celebrities and influencers that can damage their reputations. Already, there's plenty of interest from marketers in AI's ability to exploit consumer cognitive biases. Essentially providing marketers with a highly targeted, souped-up version of the most effective human influencers.

If AI does catch on in the influencer world, Gen Z and Gen Alpha will have an even more challenging time striking influencer gold. What holds value online is already starting to undergo a fundamental shift, and influence will be up for grabs.

Clem De Pressigny is a   freelance writer and editor, and was previously the editorial director of i-D magazine. She covers the internet and technology, the climate crisis, and culture.

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Social media influencer marketing: foundations, trends, and ways forward

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• Published: 25 June 2023

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• Yatish Joshi 1 ,
• Weng Marc Lim   ORCID: orcid.org/0000-0001-7196-1923 2 , 3 , 6 ,
• Khyati Jagani 4 &
• Satish Kumar 4 , 5  

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The increasing use and effectiveness of social media influencers in marketing have intrigued both academic scholars and industry professionals. To shed light on the foundations and trends of this contemporary phenomenon, this study undertakes a systematic literature review using a bibliometric-content analysis to map the extant literature where consumer behavior, social media, and influencer marketing are intertwined. Using 214 articles published in journals indexed by the Australian Business Deans Council (ABDC), Chartered Association of Business Schools (CABS), and Web of Science (WOS) from 2008 to 2021, this study unpacks the articles, journals, methods, theories, themes, and constructs (antecedents, moderators, mediators, and consequences) in extant research on social media influencer marketing. Noteworthily, the review highlighted that the major research streams in social media influencer marketing research involve parasocial interactions and relationships, sponsorship, authenticity, and engagement and influence. The review also revealed the prominent role of audience-, brand-, comparative-, content-, influencer-, social-, and technology-related factors in influencing how consumers react to social media influencer marketing. The insights derived from this one-stop, state-of-the-art review can help social media influencers and marketing scholars and professionals to recognize key characteristics and trends of social media influencer marketing, and thus, drive new research and social media marketing practices where social media influencers are employed and leveraged upon for marketing activities.

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1 Introduction

Social media influencers are increasingly popular and affecting consumers’ attitudes, perceptions, preferences, choices, and decisions. Social media influencers are regular everyday people who have created an online presence from the grassroots level through their social media channel or page and, in the process, have created an extensive network of followers (Bastrygina and Lim [ 10 ]. In that sense, social media influencers are different than traditional celebrities or public figures, who rely on their existing careers (e.g., actors, singers, politicians) to become popular and exert influence [ 88 ].

Influencers first appeared in the early 2000s, and have since progressed from a home-based hobby to a lucrative full-time career. Influencer marketing has become so attractive that with the growing industry, there is an ever-growing set of social media users that aim to become an influencer. Influencers are now capitalizing on their popularity and visibility to further their career in mainstream media such as the film and television industry [ 1 ]. The segmentation of influencers is on the number of followers they have, whereby influencers can be classified as micro-, meso- and macro-influencers [ 44 ]. According to Lou and Yan [ 88 ], posts by influencers have two essential purposes from a marketing perspective: the first purpose is to increase the purchase intention of their followers, and the second purpose is to enhance their followers’ attractiveness and product knowledge. Influencers often curate posts with information and testimonials about the features of the product that they are promoting, which results in increased information value and product knowledge. In the process, they leverage and relay their attractiveness and aesthetic value through the use of sex appeal and posing [ 104 ].

Social media influencers have been defined by many scholars in numerous ways. Freberg et al. [ 44 ] characterized social media influencers as a new type of independent third-party endorser who shapes audience attitudes through blogs, tweets, and the use of other social media. Abidin [ 1 ] construed social media influencers as a form of microcelebrities who document their everyday lives from the trivial and mundane to the exciting snippets of the exclusive opportunities in their line of work, thereby shaping public opinion through the conscientious calibration of persona on social media. De Veirman et al. [ 28 ] defined social media influencers as people who built a large network of followers and are regarded as trusted tastemakers in one or several niches. Ge and Gretzel [ 45 ] denoted social media influencers as individuals who are in a consumer’s social graph and has a direct impact on the behavior of that consumer. More recently, Dhanesh and Duthler [ 30 ] described social media influencers as people who, through personal branding, build and maintain relationships with their followers on social media, and have the ability to inform, entertain, and influence their followers’ thoughts, attitudes, and behaviors. When these definitions are taken collectively and espoused through a marketing lens, social media influencers are essentially people who develop and maintain a personal brand and a following on social media through posts that intertwin their personality and lifestyle with the products (e.g., goods, services, ideas, places, people) that they promote, which can influence the way their followers behave (e.g., attitudes, perceptions, preferences, choices, decisions), positively (e.g., purchase) or negatively (e.g., do not purchase) .

Social media influencers, as digital opinion leaders, participate in self-presentation on social media. They form an identity by creating an online image using a rich multimodal narrative of their everyday personal lives and using it to attract a large number of followers [ 59 ]. Most critical to their success is the influencer-follower relationship [ 1 ], which future follower behavior (e.g., interaction, purchase intention) is dependent upon [ 13 ], [ 37 ], [ 126 ]. Indeed, social media influencers are often perceived to be credible, personal, and easily relatable given their organic rise to fame [ 28 ], [ 31 ], [ 104 ].

In collaborations between brands and social media influencers, the role of a social media influencer is to act as a brand ambassador by designing sponsored content for the brand to convey and enhance its brand image and brand name [ 104 ], and to drive brand engagement and brand loyalty [ 72 ]. Such content is often curated by social media influencers, as independent third-party endorsers, by sharing their experiences and lives in relation to the brand through pictures, texts, stories, hashtags, and check-ins, among others [ 28 ]. Indeed, social media influencers are highly sought after by brands because they have established credibility with their followers as a result of their expertise, which allow them to exert influence on the decision-making of their followers [ 60 ]. Moreover, influencer marketing through social media can provide opportunities to influencers and their followers to contribute to the co-creation of the brand’s image on social media [ 88 ].

With the growing importance of influencer marketing and the popularity of social media influencers, various brands have started promoting their products with the help of social media influencers in an attempt to influence consumers to behave in desired ways (e.g., forming positive brand attitudes and encourage product brand purchases) [ 104 ]. However, consumer behavior is highly complex [ 81 ], and increasing inconsistency has been noted in the effectiveness of this medium [ 124 ]. Thus, it is essential to understand the factors (i.e., antecedents) underpinning consumer decision making (i.e., consequences or decisions) toward brands promoted by social media influencers, including the factors (i.e., mediators and moderators) responsible for the inconsistency in consumer responses. In this regard, attempts to consolidate extant knowledge in the field is arguably relevant to address the extant gap and needs of marketing scholars and professionals interested in social media influencer marketing.

In recognition of the growing influence of social media influencers and influencer marketing in consumer decision making, this study aims to provide a one-stop, state-of-the-art overview of the articles, journals, methods, theories, themes, and constructs (antecedents, moderators, mediators, and consequences) relating to social media influencer marketing using a systematic review of articles in the area from 2008 to 2021. Though a recent review on social media influencers was conducted by Vrontis et al. [ 124 ], the present review remains warranted because the existing review only considered a small sample of 68 articles published in journals indexed in the Chartered Association of Business Schools Academic Journal Guide, and thus, cannot holistically encapsulate the state of the field. Indeed, the insights and the integrative framework resulting from their review was relatively lean, which can be attributed to the sample limitations that the authors had imposed for their review. The same can be said about another recent review by Bastrygina and Lim [ 10 ], which considered only 45 articles in Scopus that narrowly focused only on the consumer engagement aspect of social media influencers. To overcome these limitations , the present review will consider a more inclusive search and inclusion criteria while upholding to the highest standards of academic quality by relying on a broader range of indexing sources. The motivation of the present review is also in line with the call by Lim et al. [ 86 ] and Paul et al. [ 98 ] for new reviews that address the shortcoming of existing reviews in order to redirect research in the area onto a clearer and more refined path for progress. In addition, the present review adopts a bibliometric-content analysis to consolidate current findings, uncover emerging trends and extant gaps, and curate a future agenda for social media influencer marketing. Noteworthily, the rigorous multi-method review technique (i.e., the combination of a bibliometric analysis and a content analysis) adopted for the present review is in line with the recommendation of Lim et al. [ 86 ] to facilitate a deeper dive into the literature, and thus, enabling the curation of a richer depiction of the nomological network characterizing the field [ 94 ], in this case, the field of social media influencer marketing. In doing so, this study contributes to answering the following research questions (RQs):

RQ1. What is the publication trend of social media influencer marketing research, and which are the key articles?

RQ2. Where is research on social media influencer marketing published?

RQ3. How has social media influencer marketing research been conducted?

RQ4. What are the theories that can be used to inform social media influencer marketing research?

RQ5. What are the major themes of social media influencer marketing research?

RQ6. What are the constructs (i.e., antecedents, mediators, moderators, and consequences) employed in social media influencer marketing research?

RQ7. Where should social media influencer marketing be heading towards in the future?

The rest of the paper is structured as follows. The next section provides an account of the methodology used in the research, followed by the findings and conclusions of the study in subsequent sections.

2 Methodology

This study conducts a multi-method systematic literature review on social media influencer marketing using a bibliometric-content analysis in line with the recommendation of Lim et al. [ 86 ] and recent systematic literature reviews (e.g., Kumar et al. [ 64 ]. The assembling, arranging, and assessing techniques stipulated in the Scientific Procedures and Rationales for Systematic Literature Reviews ( SPAR-4-SLR ) protocol by Paul et al. [ 98 ] to carry out a systematic literature review are also adopted and explained in the next sections.

2.1 Assembling

Assembling relates to the identification (i.e., review domain, research questions, source type, and source quality) and acquisition (i.e., search mechanism and material acquisition, search period, search keywords) of articles for review. In terms of identification , the review domain relates to social media influencer marketing, but within the subject areas of business management, social sciences, hospitality, tourism, and economics due to their immediate relevance to the review domain, and thus, articles in other subject areas such as computer science, engineering, medical, and mathematics, which are peripheral to the review domain, were not considered. Next, the research questions underpinning the review pertain to the articles, journals, methods, theories, themes, and constructs in the field and were presented in the introduction section. Only journals were considered as part of source type as they are the main sources of academic literature that have been rigorously peer reviewed Nord & Nord, [ 96 ]. The source quality was inclusive yet high quality, whereby articles published in journals indexed in the Australian Business Deans Council (ABDC), Chartered Association of Business Schools (CABS), and Web of Science (WOS) were included. In terms of acquisition , the search mechanism and material acquisition relied on the WOS database, which is connected to myriad publishers such as Emerald, Sage, Springer, Taylor and Francis, and Wiley. The search period starts from 2008 and ends in 2021. The year 2008 was selected as the starting year because it was the year that the concept of influencer was first introduced by Kiss and Bichler [ 63 ], and thus, a review staring from 2008 can provide a more accurate and relevant account of the extant literature on influencer marketing, particularly from the lenses of consumers and social media influencers. The end year 2021 was selected because it is the most recent full year at the time of search—a practice in line with Lim et al. [ 83 ]. The search keywords—i.e., “consumer behavio*” (truncation technique), “social media,” “influencer,” and “marketing”—were curated through brainstorming and endorsed by disciplinary experts in marketing and methodological experts in review studies. In total, 320 articles were returned from the search, but 17 articles were removed as they were related to engineering, mathematics, and medicine, which resulted in only 303 articles that were retrieved for the arranging stage.

2.2 Arranging

Arranging relates to the organization (i.e., organizing codes) and purification (i.e., exclusion and inclusion criteria) of articles returned from the search. In terms of organization , the content of articles was coded based on the key focus of each research question: journal title, method, theory, and construct (antecedent, mediator, moderator, consequence). The bibliometric details of the articles were also retrieved and organized accordingly in this stage. In terms of purification , 89 articles were eliminated as they were not published in journals indexed by ABDC and CABS, with the rest of the 214 articles included for review.

2.3 Assessing

Assessing relates to the evaluation (i.e., analysis method, agenda proposal method) and reporting (i.e., reporting conventions, limitations, and sources of support) of articles under review. In terms of evaluation , a bibliometric analysis and a content analysis were conducted.

For the bibliometric analysis, the Bibliometrix package in R studio software [ 4 ] was used to conduct (1) a performance analysis to reveal the publication trend as well as the key articles and journals (RQ1 and RQ2), and (2) a science mapping to uncover the major themes in the field (RQ5) in line with the bibliometric guidelines by Donthu et al. [ 32 ]. With regards to science mapping, a triangulation technique was adopted in line with the recommendation of Lim et al. [ 86 ] using:

co-citation using PageRank , wherein the major themes are revealed through the clustering of articles that are most cited by highly-cited articles,

bibliographic coupling , wherein the major themes are revealed through the clustering of articles that cite similar references, and

keyword co-occurrence , wherein the major themes are revealed through the clustering of author specified keywords that commonly appear together [ 32 ], [ 64 ].

For the content analysis, the within-study and between-study literature analysis method by Ngai [ 95 ] was adopted (RQ3, RQ4, and RQ6). The within-study literature analysis evaluates the entire content of the article (e.g., theoretical foundation, methodology, constructs), whereas the between-study literature analysis consolidates, compares, and contrasts information between two or more articles. The future research agenda proposal method is predicated on the expert evaluation of a trend analysis by the authors (RQ7). In terms of reporting , the conventions for the outcomes reported include figures, tables, and words, whereas the limitations and sources of support are acknowledged at the end.

The findings of the review are organized based on the research questions (RQs) of the study: articles, journals, methods, theories, themes, and constructs.

3.1 Articles

The first research question (RQ1) deals with the publication trend and key articles of social media influencer marketing research.

Figure  1 indicates that research on social media influencer marketing began to flourish 10 years (i.e., 2018 onwards) after the concept of was introduced in 2008 [ 63 ]. This implies that interest in social media influencer marketing is fairly recent (i.e., within the last five years at the time of analysis), wherein its stratospheric growth appears to have coincided with that of highly interactive and visual content-focused social media such as Instagram (e.g., Instagram Stories feature launched in December 2017) [ 17 ] and TikTok (e.g., international launch in September 2017) [ 129 ]. The growth of triple-digit publications observed in 2021 during the COVID-19 pandemic is especially noteworthy as it signals the importance of social media influencer marketing in the new normal and reaffirms past observations of an acceleration in technology adoption [ 77 ], [ 79 ].

Publication trend of social media influencer marketing research

Table 1 presents the top articles on social media influencer marketing. The most cited article is De Veirman et al.’s [ 28 ] (464 citations), which focused on social media influencer marketing using Instagram and revealed the impact of the number of followers and product divergence on brand attitudes among the followers of social media influencers. The burgeoning interest on Instagram as seen through this most cited article despite its recency corroborates the earlier observation on the stratospheric growth in research interest on highly interactive and visual content-focused social media. The top-cited articles in recent years demonstrate increasing research interest in comparative studies (e.g., celebrity versus social media influencer endorsements, [ 104 ],Instagram versus YouTube; [ 108 ], as well as review studies (e.g., Hudders et al., [ 48 ], [ 124 ], albeit the latter being limited (e.g., small review corpus, niche review focus) and thus reaffirming the necessity and value of the present review.

3.2 Journals

The second research question (RQ2) deals with the outlets that publish social media influencer marketing research and the source type chosen according to the recommendation of Paul et al. [ 98 ] is journals on the basis of academic quality and rigor. In total, the 214 articles in the review corpus were published in 87 journal titles indexed in ABDC, CABS, and WOS. Out of the 87 journal titles, 80 (37.38%) articles are published by the top 10 journals with the most articles on social media influencer marketing, with Journal of Business Research , International Journal of Advertising , and Journal of Retailing and Consumer Services emerging as the top three journals in terms of numbers of articles published in the area (Table 2 ).

3.3 Methods

The third research question (RQ3) focuses on the methods that can inform social media influencer marketing research and were identified and coded manually using the within-study technique and consolidated to portray the outcome of a between-study literature analysis suggested by Ngai [ 95 ]. In total, seven categories of methods were employed in 214 articles on social media influencer marketing research (Table 3 ). As a category, quantitative methods in the form of surveys were most prevalent ( n  = 64), followed by qualitative methods ( n  = 52), with individual interviews being the most popular method ( n  = 19). Experimental ( n  = 38) and machine learning ( n  = 33) methods were noteworthy too. Non-empirical methods ( n  = 19) such as conceptual ( n  = 9) and review ( n  = 10) methods were less prominent. Similarly, mix methods ( n  = 8) were the least popular. As a whole, the review indicates that extant research on social media influencer marketing were mostly empirical in nature albeit in silos (i.e., single rather than mixed methods).

3.4 Theories

The fourth research question (RQ4) pertains to the theories that can inform social media influencer marketing research and were identified, coded, and reported using the same Ngai [ 95 ] informed within- and between-study literature analysis as reported for the methods in the preceding section. In total, 46 different theories employed in 94 (43.93%) articles on social media influencer marketing research were revealed (Table 4 ). Persuasion knowledge theory emerged as the most popular theory with eight articles, whereas social learning theory, social comparison theory, social cognitive theory, social exchange theory, social identity theory, social influence theory, source credibility theory, reactance theory, theory of para-social interaction, theory of planned behavior, and uses and gratifications theory were among the other popular theories ( n  ≥ 3). The broad range of theories indicate that social media influencer marketing is an area of research with multi-faceted aspects worthy of exploration and investigation. The sociological theories manifested in the most ways—namely Bourdieu’s theory, Graph theory, network theory, observational learning theory, optimal distinctiveness theory, social cognitive theory, social comparison theory, social exchange theory, social identity theory, social influence theory, social learning theory, structural hole theory, system justification theory, and theory of para-social interaction—whereas media theories were not far behind—namely advertising literacy theory, media dependency theory, megaphone effect theory, source credibility theory, transfer theory, two-step flow theory, uses and gratifications theory, and visual framing theory. The manifestation of theories that infused “media” and “sociology” together , such as social media influencer value model and social-mediated crisis communication theory, were observed as well. Psychological theories , such as associative learning theory, attachment theory, attribution theory, consistency theory, construal level theory, dissonance theory, dual process theory, elaboration likelihood model, halo effect theory, reactance theory, similarity-attraction model, theory of planned behavior, and theory of reasoned action, and marketing theories , such as Doppelganger effect theory, human brand theory, relationship management theory, and source effect theory, were also noteworthy. Management theories , such as charismatic and transformational leadership theory and resource dependency theory, were also observed. Interestingly, only one economic (i.e., cost-signaling theory) and one technology (i.e., technology acceptance model) theory were observed, which may indicate that the economic and technology aspects are underexplored as compared to the media, psychological, management, marketing, and social aspects of social media influencer marketing.

The fifth research question (RQ5) involves the mapping of extant research on social media influencer marketing. To do so, three science mapping techniques that rely on different sources of bibliographic data were relied upon—namely (1) a co-citation analysis using PageRank to identify clusters of articles that are most cited by highly-cited articles, (2) a bibliographic coupling to locate clusters of articles that share common references, and (3) a keyword co-occurrence analysis to uncover clusters of author specified keywords that commonly co-appear [ 32 ], [ 65 ].

3.5.1 Foundational themes (or foundational knowledge)

The foundational themes and the top articles for each foundational theme in social media influencer marketing research are depicted in Table 5 . In essence, foundational themes exemplify the perspectives that a field’s research relies upon, and thus, these themes may encompass articles inside and outside that field [ 32 ]. In the case of social media influencer marketing, four foundational themes were revealed by the co-citation analysis using PageRank. Noteworthily, the PageRank scores indicate article prestige, wherein a higher score indicates that the article is cited more by highly-cited articles in the field, whereas the betweenness and closeness centrality scores reflect the article’s relevance across and within themes, wherein a higher score indicates greater relevance across and within themes, respectively [ 32 ].

The first foundational theme depicts the foundations and models for social media influencer marketing . The articles in this foundational theme signify the key characteristics of concepts associated to social media influencer marketing, such as the concept of engagement [ 49 ], “Instafamous” [ 55 ], influencer marketing [ 88 ], and social media influencers [ 44 ], including the difference between traditional celebrities and contemporary social media influencers [ 104 ].

The second foundational theme denotes the influence and impact perspectives for social media influencer marketing . The articles in this foundational theme represent a collection of insights in relation to influence and impact. For example, the most prestigious article under this theme examines the impact of the number of followers of Instagram influencers and the divergence of the products promoted by these influencers on the brand attitudes of their followers [ 28 ]. Other examples of influence and impact outcomes include attitudes and behavioral intentions [ 37 ], engagement [ 120 ], perceptions Lee & Watkins, [ 67 ], and purchase decisions [ 31 ].

The third foundational theme highlights the importance of endorsement and resonance perspectives for social media influencer marketing . The articles in this theme, which are widely cited by highly cited articles on social media influencer marketing, emphasize the importance of endorsement and resonance literature in grounding the reasons for and outcome of social media influencer marketing. This can be seen by the prominence of celebrity endorsement (e.g., [ 34 ], Mccracken, [ 93 ], Silvera & Austad, [ 107 ]) and congruence (e.g., Till & Busler, [ 116 ]; [[ 128 ]] literature that make up the most prestigious articles under this theme.

The fourth foundational theme relates to the profiling and measurement perspectives for social media influencer marketing research . This theme signifies and reaffirms the value of personal characteristics (e.g., personalities, profiles; [ 31 ], Ferchaud et al., [ 40 ]), measurement scales (e.g., expertise trustworthiness and attractiveness; Ohanian, [ 97 ]), and evaluation methods (e.g., structural models; Fornell & Larcker, [ 43 ]) in guiding and informing social media influencer marketing research, and thus, they form a considerable part of the knowledge relied upon by research in the field.

3.5.2 Major themes (or major research streams)

The major themes build upon the foundational themes to curate new knowledge and understanding on social media influencer marketing [ 32 ]. To uncover the major themes, a keyword co-occurrence analysis was initially conducted to gain a sense of the nomological network for the major themes [ 94 ], followed by a bibliographic coupling to gain an in-depth understanding of the content under each major theme in the field [ 32 ].

The keyword co-occurrence analysis indicates that four major themes characterize the knowledge curated by extant research focusing specifically on social media influencer marketing (Fig.  2 and Table 6 ), which is triangulated by the six major themes revealed through bibliographic coupling, in which four bibliographic coupling clusters corresponds to two keyword clusters (Table 7 ). The key peculiarities of these themes are presented as follows.

Nomological network of research streams in social media influencer marketing research

Parasocial interactions and relationships in social media influencer marketing . This major theme is most prominent (eight keywords) and relatively recent (2020.1429–2020.7499). This theme highlights the importance of the “credibility” ( n  = 6), “persuasion knowledge” ( n  = 7), and “source credibility” ( n  = 7) of social media influencers as essential “persuasion” ( n  = 5) factors that influence the “parasocial interactions” ( n  = 8) and “parasocial relationships” ( n  = 12) in social media influencer marketing. Most research in this area is conducted in the context of “Instagram” ( n  = 27), wherein “purchase intention” ( n  = 13) is a common outcome expected and examined. Noteworthily, extant research concentrating on influencing parasocial interactions have highlighted the importance of self-influencer congruence (Shan et al., [ 105 ]; [ 128 ] and the value of message value [ 88 ] and credibility [ 108 ], including the moderating role of audience comments [ 102 ], in fostering consumer trust and purchase intention toward branded content [ 88 ], [ 102 ], Shan et al., [ 105 ], [ 108 ], [ 128 ], whereas those focusing on developing and managing parasocial relationships emphasized the importance of being entrepreneurial (Fink et al., [ 41 ]) and personal branding (Ki et al., [ 61 ]) in the pursuit of becoming famous and garnering brand equity and loyalty among followers [ 18 ], [ 55 ], [ 57 ].

Sponsorship in social media influencer marketing . This major theme is fairly prominent (six keywords) and recent (2019.8–2021). This theme highlights the importance of “sponsorship disclosure” ( n  = 6) in “celebrity endorsement” ( n  = 5) and among “social media influencers” ( n  = 60) engaged for “native advertising” ( n  = 7) in “influencer marketing” ( n  = 63), with “YouTube” ( n  = 9) featuring prominently in this space. Noteworthily, extant research on this theme is divided into two notable streams, wherein the first stream sheds light on the commercialization and value of social media influencer marketing (Britt et al., [ 16 ]; Harrigan et al., [ 47 ]; Hudders et al., [ 48 ]; [ 124 ],), which highlights the importance of the second stream pertaining to the impact of disclosure (i.e., macro, micro—e.g., declaring sponsorship to establish and reaffirm the credibility of social media influencers and the brands they represent) on the behavioral responses of social media followers [ 13 ], [ 30 ], [ 58 ], [ 104 ], [ 110 ].

Authenticity of marketing and public relations in social media influencer marketing . This major theme is fairly prominent (five keywords) but with a longer history (2017.4286–2021) than the other major themes. This theme highlights the continuing importance of “authenticity” ( n  = 7) in the “marketing” ( n  = 5) and “public relations” ( n  = 7) endeavors of “influencers” ( n  = 29) on “social media” ( n  = 56). Thus, it is no surprise that extant research in this theme have focused on traditional marketing concepts such as advertorial campaigns [ 1 ], personal branding [ 59 ], rhetoric [ 45 ], strategic communication [ 33 ], and self-presentation [ 6 ].

Engagement and influence in social media influencer marketing . This major theme is fairly prominent (five keywords) and recent (2019.4–2020.6). This theme encapsulates “social media marketing” ( n  = 16) research that concentrates on the “social influence” ( n  = 5) of “opinion leadership” ( n  = 5) and the equivalent outcome of “brand engagement” ( n  = 5), with “Twitter” ( n  = 7) featuring prominently in this space. Noteworthily, the prominent studies under this theme concentrate on the power of social networks of social media influencers, including examining the influence of the number of followers [ 28 ], measuring the influence of customer networks [ 63 ] and social media influencers [ 5 ], and the value of opinion leaders [ 87 ] and sponsored campaigns [ 49 ] across these networks.

Taken collectively, these themes, which were triangulated across two bibliographic sources of data (i.e., keywords and references) and analytical techniques (i.e., keyword co-occurrence analysis and bibliographic coupling), suggests that social media influencer marketing has tremendous commercial value, which justify the sponsorship that brands are willing to provide to social media influencers in return for marketing and public relation campaigns for their brands and products. Nevertheless, it is important to note that the power of social media influencers resides in their authenticity, which is a crucial reason as to why social media influencers are followed and relied upon by their followers. The management of parasocial interactions and relationships are also highly important as they are essential to foster desired engagement among followers and influence their behaviors in ways desired by social media influencers and the brands that they represent. The next section provides a deeper dive into the mechanisms (constructs) that transpire in social media influencer marketing.

3.6 Constructs

The sixth research question (RQ6) involves the unpacking of constructs that relevantly explain consumer behavior toward social media influencer marketing, which were revealed through the same within- and between-study literature analysis as reported in the methods and theories sections previously [ 95 ]. The constructs (Fig.  3 ) were arranged according to testable categories in the form of antecedents (Table 8 ), mediators (Table 9 ), moderators (Table 10 ), and consequences (Table 11 ), with each category having sub-categories that encapsulate relevant constructs that fall under the theme of that sub-category. The thematic naming of sub-categories are mostly self-explanatory (i.e., audience-, brand-, content-, influencer-, social-, and technology-related), with only one sub-category being uncommon yet sensible due to the unique nature of the context under study—that is, the comparative-related sub-category, which captures the essence of constructs where comparison exist between two or more sub-categories (e.g., influencer-follower relationship is a construct that accounts for the comparison transcending the audience- and influencer-related sub-categories, whereas product-endorser fit is a construct that reflects the comparison between the brand- and influencer-related sub-categories).

Consumer behavior toward social media influencer marketing

In terms of antecedents , four sub-categories emerged, namely comparative-, content-, influencer-, and social-related antecedents (Table 8 ). The comparative-related antecedents (six counts) comprise of influencer-follower relationship (two counts) and perceived similarity (four counts). The content-related antecedents (36 counts) consist of authenticity (four counts), disclosure (14 counts), informativeness (nine counts), message construal (one count), perceived quality (two counts), perceived quantity (two counts), perceived originality (one count), and post credibility (three counts). The influencer-related antecedents (34 counts) consist of engagement and interaction (two counts), influencer attractiveness (10 counts), influencer credibility (six counts), influencer expertise (nine counts), influencer likeability (one count), perceived trustworthiness (five counts), and perceived uniqueness (one count). The social-related antecedent (four count) contains parasocial relationship (four count) only. In total, 18 antecedents emerged across four sub-categories. Content-related antecedents appear to be the most researched (36 counts), followed by influencer-related antecedents (34 counts), with few studies examining comparative- (six counts) and social- (four count) related antecedents. Disclosure (14 counts) is the antecedent that has been studied the most, followed by influencer attractiveness with 10 counts. As a whole, there is good breadth and depth for antecedents as a category, but is mixed for its sub-categories.

In terms of mediators , seven sub-categories were revealed, namely audience-, brand-, comparative-, content-, influencer-, social-, and technology-related mediators (Table 9 ). The audience-related mediators (13 counts) comprise of attachment (one count), attitude (five counts), interest (one count), psychological ownership (one count), and trust (five counts). The brand-related mediators (eight counts) consist of brand recognition (five counts), product attractiveness (one count), and sponsorship transparency (two counts). The comparative-related mediator (four counts) contains self-influencer connection (four counts) only. The content-related mediators (seven counts) encapsulate disclosure (two counts), message appeal (one count), message credibility (one count), message process involvement (one count), and source credibility (two counts). The influencer-related mediators (15 counts) encompass engagement and interaction (two counts), expertise (two counts), influencer credibility (five counts), opinion knowledge leadership (five counts), and perceived popularity (one count). The social-related mediators (three counts) include electronic word of mouth (one count) and parasocial interaction (two counts). The technology-related mediators (two counts) incorporate perceived ease of use (one count) and perceived usefulness (one count). In total, 22 mediators were revealed across seven sub-categories. Influencer- and audience-related mediators appear to be the most researched with 15 and 13 counts respectively, followed by brand- (eight counts) and content- (seven counts) related mediators. Attitude, brand recognition, influencer credibility, opinion leadership knowledge, and trust are the mediators studied the most with five counts each. Overall, there is reasonable breadth and depth for mediators as a category, but is mixed for its sub-categories.

In terms of moderators , six sub-categories were unpacked, namely audience-, brand-, comparative-, content-, influencer-, and social-related moderators (Table 10 ). The audience-related moderators (10 counts) comprise of advertisement literacy (one count), audience engagement (two counts), domains of interest (one count), envy identification (one count), interaction propensity (one count), purchase intention (one count), self-discrepancy (two counts), and social identification with social commerce (one count). The brand-related moderator (one count) consists of brand attitude (one count) only. The comparative-related moderators (three counts) contain perceived closeness (one count), perceived fit (one count), and product-endorser fit (one count). The content-related moderators (nine counts) encapsulate audience comments (one count), disclosure (one count), download volume (one count), message process involvement (one count), message valence (one count), number of hashtags (one count), online ratings (one count), structural assurance (one count), and visionary insights (one count). The influencer-related moderators (four counts) encompass influencer socio-economic status (one count), number of followers (one count), perceived self-serving motive (one count), and type of influencer (one count). The social-related moderators (two counts) include parasocial relationship (one count) and parental mediation (one count). In total, 27 moderators were unpacked across six sub-categories. Audience-related moderators (10 counts) appear to be the most researched, followed by content-related moderators (nine counts). All moderators had only one count except audience engagement and self-discrepancy, which have two counts, and thus indicating its breadth but not depth.

In terms of consequences , three sub-categories were unveiled, namely brand-, influencer-, and social-related consequences (Table 11 ). The brand-related consequences (73 counts) comprise of brand attitude (17 counts), brand awareness (one count), brand involvement (two counts), brand purchase or patronage (46 counts), brand recall (two counts), and brand trust (five counts). The influencer-related consequences (19 counts) consist of engagement and interaction (11 counts), following influencer (five counts), and influence (three counts). The social-related consequences (12 counts) contain recommendation and referral propensity (nine counts) and social sharing (three counts). In total, 11 consequences were unveiled across three sub-categories. Brand-related consequences (73 counts) appear to be the most researched, followed by influencer- (19 counts) and social- (12 counts) related consequences. Brand purchase or patronage (46 counts) represent the most studied consequence, followed by brand attitude (17 counts) and engagement and interaction (11 counts). Taken collectively, the consequences unveiled indicate its depth but not breadth.

4 Trend analysis and future research directions

Agendas for future research are a hallmark of systematic literature reviews [ 84 ]. While there are many approaches to develop future research agendas, the present study adopts an approach that the authors found to be most objective and pragmatic—that is, a trend analysis from thematic and topical perspectives. The suggestions for future research based on the analysis from these perspectives are presented in the next sections.

4.1 Thematic perspective

The thematic perspective comprises a trend analysis of bibliographic clusters representing the major themes of social media influencer marketing research. The choice of focusing on bibliographic clusters as opposed to keyword clusters was a deliberate decision taken in light of the finer-grained research streams in the former (six clusters) over the latter (four clusters), as well as the availability of the alternative perspective (i.e., the topical perspective) that will use keywords to shed light on the topical trend in the field.

The productivity of the six major themes (research streams) in social media influencer marketing research has generally improved in recent years, particularly in 2021, with the exception of research on parasocial relationships in social media influencer marketing (Cluster 6), which experience a slight decline (i.e., seven in 2020 to six in 2021). Though closely-related research on parasocial interactions has proliferated (Cluster 5), the difference between the two research streams and their relatively lower number of studies as compared to other research streams suggest that new research in both streams is very much required. Similarly, the research stream on disclosures (Cluster 4) is highly important, yet it remains relatively low as compared to its more popular counterpart, that is, the research stream on commercialization and value of social media influencer marketing (Cluster 3), both of which are important research streams to the larger umbrella research stream on sponsorship revealed by the keyword co-occurrence analysis. While the research streams on authenticity (Cluster 2) and engagement and influence (Cluster 1) in social media influencer marketing are highly popular, further research remains necessary in light of the evolving changes in the social media landscape. Notwithstanding the productivity of the research streams, several promising avenues avail for advancing knowledge across all research streams.

In terms of engagement and influence in social media influencer marketing (Cluster 1), the emergence of augmented, virtual, and mixed realities, including the metaverse, signals the need for new research that unpacks the opportunities for engagement in these new social avenues along with the effectiveness of these avenues as compared to existing avenues for social media influencer marketing. In addition, the nature of engagement will benefit from finer-grained examination to account for the differences between its varied cognitive, affective, and behavioral manifestations [ 80 ], [ 85 ], which remains underexplored in social media influencer marketing.

In terms of authenticity in social media influencer marketing (Cluster 2), the key markers of authenticity and the strategies to communicate and strengthen a sense of authenticity are potential avenues to enrich understanding of this area. Noteworthily, future research on authenticity will need to go beyond traditional measures (e.g., scales; Ohanian, [ 97 ]) and engage in purposeful exploration to uncover the attributes and actions that if available and taken will enhance followers’ perceptions of the authenticity of social media influencers. In this regard, future qualitative and experimental research in this research stream is encouraged, wherein the former will lead to the discovery of new authenticity markers that the latter can test for cause and effect. Such research should lead to meaningful extensions on the understanding of authenticity that goes beyond treating the concept as a singular construct in the field.

In terms of commercialization and value of social media influencer marketing (Cluster 3), the potential of non-economic returns of social media influencer marketing could be explored in future research. With the advent of corporate social responsibility and environmental social governance (Lim et al., [ 83 ], it is imperative that the expectations and evaluations of returns goes beyond those that are economic in nature (e.g., sales) [ 78 ]. The advocacy and support of socio-environmental causes (e.g., hashtags of actions and statements) could be explored, which can be subsequently useful to develop sustainability ratings beneficial for illustrating the impact of both social media influencers and the brands that they represent.

In terms of disclosure in social media influencer marketing (Cluster 4), future research could explore the different ways in which explicit and implicit disclosures could be curated and signaled by social media influencers to their followers. Such research should be potentially useful as not all social media platforms provide options of explicit labels (e.g., sponsor ad) to social media users, especially when such social media posts are not paid to extend its reach and thus relies on social media users themselves to self-disclose. Moreover, the effectiveness of these forms of disclosure, including their combination, have not been adequately studied and thus should be worthwhile exploring. The negative connotation that may be attached to such disclosures should also be addressed in ways that make such disclosures an asset rather than a liability.

In terms of parasocial interactions in social media influencer marketing (Cluster 5), the multitude ways in which parasocial interactions could be curated represent a potentially fruitful avenue for future exploration. At present, the general focus has been on the influence of social media influencer credibility and the congruence of such interactions to follower expectations and perceptions [ 108 ]. In this regard, future research is encouraged to explore the different ways in which parasocial interactions could be curated, and in the midst of doing so, theorizing the entry points and sustaining factors that make such interactions parasocial between social media influencers and their followers. Given the complex nature of parasocial interactions, future research in this space could benefit from employing neuroscientific tools (e.g., eye tracker, wearable biosensors, [ 73 ], [ 74 ] to gain nuanced insights into biological responses that can be used to supplement self-reported responses in order to better ascertain the parasocial nature of interactions among social media influencers and their followers.

In terms of parasocial relationships in social media influencer marketing (Cluster 6), deeper insights on what makes parasocial relationships gratifying and lasting should be developed in future research. Such research should provide a better understanding on the constitution of parasocial relationships and how social media influencers can foster and maintain them over time. Nevertheless, errors or mistakes are bound to happen (e.g., slip of inappropriate word, unintentional non-disclosure of sponsorship). Thus, the repair and recovery of negatively-affected parasocial relationships among social media influencers and their followers could also be given scholarly attention in future research.

Taken collectively, these suggestions for future research should enrich research across all research streams in social media influencer marketing. The next section builds on the insights from this section and takes a closer look on topical trends in the field (Fig. 4 ).

Productivity trend of major themes in social media influencer marketing research. Note: Cluster 1 = Engagement and influence in social media influencer marketing. Cluster 2 = Authenticity in social media influencer marketing. Cluster 3 = Commercialization and value of social media influencer marketing. Cluster 4 = Disclosure in social media influencer marketing. Cluster 5 = Parasocial interactions in social media influencer marketing. Cluster 6 = Parasocial relationships in social media influencer marketing

4.2 Topical perspective

The productivity of topical research in social media influencer marketing has evolved over the years (Fig.  5 ). Noteworthily, the extant literature on social media influencer marketing has been largely predicated on “communication management”, “centrality”, and “viral marketing” up to 2018. Newer research has nonetheless made a stronger and more explicit connection to “influencer marketing” and “social media”, with “Instagram” emerging as the most prominent social media in the field. The transmission of “eWOM” or “electronic word-of-mouth” and how this translates into “parasocial interaction” or “immersion” between “social media influencers” and “followers” has taken center stage alongside “online marketing” and “social media marketing” considerations such as “advertising”, “brands”, “brand awareness”, and “purchase intention” from a “neoliberalism” perspective.

Productivity trend of major topics in social media influencer marketing research

Notwithstanding the trending topics in social media influencer marketing revealed by the trend analysis, it is clear that new research focusing on new phenomena is very much required. For example, new social media platforms such as Clubhouse and TikTok have been extremely popular platforms for social media influencers in recent years, and thus, future research should also consider exploring social platforms other than Instagram. Furthermore, the proliferation of augmented and virtual realities remains underexplored for social media influencer marketing. The rebranding of Facebook to Meta is a signal of the future rise of the metaverse . New research in this direction focusing on new-age technologies for social media influencer marketing should provide new knowledge-advancing and practice-relevant insights into contemporary trends and realities that remain underrepresented in the literature. Similarly, the diversity and evolution of social media followers also deserve further attention in light of accelerated technology adoption by societies worldwide in response to the COVID-19 pandemic and the new normal [ 77 ], as well as the changing nature of generational cohorts in the society [ 79 ].

5 Conclusion

The importance of consumerism for business survival and growth albeit in a more authentic, meaningful, and sustainable way [ 76 ] along with the increasing use of digital media such as social media [ 82 ] have led to the proliferation of social media influencer marketing and its burgeoning interest among academics and professionals [ 10 ], [ 124 ]. This was evident in the present study, wherein the consumer behavior perspective of social media influencer marketing took center stage. Using the SPAR-4-SLR protocol as a guide, a bibliometric-content analysis as a multi-method review technique, and a collection of 214 articles published in 87 journals indexed in ABDC, CABS, and WOS as relevant documents for review, this study provides, to date, the most comprehensive one-stop state-of-the-art overview of social media influencer marketing. Through this review, this study provides several key takeaways for theory and practice and additional noteworthy suggestions for future research.

5.1 Theoretical contributions and implications

From a theoretical perspective, this study provides two major takeaways for academics.

First, the review indicates that most articles on social media influencer marketing published in journals indexed in ABDC, CABS, and WOS were not guided by an established theory, as only 94 (43.93%) out of the 214 articles reviewed were informed by theories (e.g., persuasion knowledge theory, social learning theory, source credibility theory, theory of planned behavior). This implies that most articles relied on prior literature only to explain their study’s theoretical foundation, which may be attributed to a lack of awareness on the possible theories that may be relevant to their study. In fact, a similar review on the topic albeit with a relatively smaller sample of articles (i.e., 68 articles only) due to protocol limitations (i.e., CABS-indexed journals only) had acknowledged the issue but unfortunately failed to deliver a collection of theories informed by prior research [ 124 ]. In this vein, this study hopes to address this issue as it has revealed 46 different theories that were employed in prior social media influencer marketing research, which can be used to ground future research in the area. Furthermore, the list of theories can be used to justify the novelty of future research where a new theory is applied. In addition, future studies can take inspiration from the manifestation of theories emerging from multiple theoretical perspectives, such as the social influencer value model and the social-mediated crisis communication theory informed by the media and sociological theoretical perspectives, to develop new theories in the field, which may be challenging but certainly possible [ 81 ]. Alternatively, future studies can consider theoretical integration by using two or more theories in a single investigation, which can reveal richer insights on the phenomenon (e.g., which theoretical perspective is more prominent or which factors from which theoretical perspective yield strong impacts and therefore warrant investment prioritization).

Second, the review shows that social media influencer marketing research does not have to be limited to a simple direct antecedent-consequence relationship or the multiply of such relationships. Instead, research in the area can benefit from testing the mediating and moderating effects of various factors to enrich the insights derived from their study. Interestingly, the review reveals that antecedents can also play the role of mediators (e.g., engagement and interaction) and moderators (e.g., parasocial relationship) and vice versa, which implies that the conditions in research design setup are fundamental to the conclusions made about the consequences of social media influencer marketing [ 75 ], which can take the form of consumer responses to the brand (e.g., brand purchase or patronage), the influencer (e.g., following influencer), and the community (e.g., recommendation, social sharing). In total, seven categories in the form of audience-, brand-, comparative-, content-, influencer-, social-, and technology-related factors that could manifest as antecedents, mediators, and moderators were revealed. Noteworthily, the comparative-related factors such as perceived closeness, perceived fit, perceived similarity, self-influencer connection, and product-endorser fit transcended across multiple categories (e.g., audience and influencer, brand and influencer), which indicate the promise of social media influencer marketing as a research context suitable for the development of new factors to describe consumer behavior of a comparative nature. Indeed, comparative-related factors is, to the best knowledge of the authors, a new categorization that has not been revealed by prior systematic literature reviews, and thus, represent a key contribution to the literature that should be noted in future research and reviews. Moreover, the mapping of constructs in Fig.  3 and their counts in Tables 8 , 9 , 10 , and 11 provide useful starting points to identify the extant gaps in prior research (e.g., brand-related factors remain underexplored as moderators, comparative-related factors remain underexplored as mediators) and to inform the direction of future research accordingly. Finally, the constructs and their associated categories revealed can also be compared and contrasted in future investigations to delineate the difference in impact between constructs of different categories, and when paired with appropriate theories, can provide stronger grounds for managerial recommendations to brands and influencers interested to leverage off the benefits of social media influencer marketing to attract and persuade desired consumer behavior.

5.2 Managerial contributions and implications

From a managerial perspective, this study provides two major takeaways for brands and influencers.

First, the review indicates that brands indirectly influence consumers through influencers—that is to say, the strategy of brands engaging in influencer marketing on social media places influencers at the forefront, with brands taking a backseat in that strategy. This was evident from the literature review, where brand-related antecedents were absent; instead, the influence of brands manifests in the form of mediators (e.g., brand recognition, product attractiveness, sponsorship transparency) and moderators (e.g., brand attitude). In that sense, it is important that brands identify and engage with influencers strategically, particularly those who are perceived to be attractive, credible, engaging and interactive, experts, a good fit for their products, likeable, opinion leaders, popular, trustworthy, unique, and without overly self-serving motives in order to encourage desired consumer behavior toward their brands (e.g., brand purchase and patronage, brand trust), as revealed by the review herein.

Second, the review reveals that social media influencers directly influence consumer behavior toward the brands they promote (e.g., brand attitude, brand awareness, brand involvement, brand recall, brand trust), the influencers themselves (e.g., follower, influence), and the social media community at large (e.g., recommendation, social sharing). In particular, the content that influencers curate on social media can affect how consumers respond to these stakeholders. The review indicates that such content should be authentic, credible, informative, original, and transparent (disclosure). The message appeal and message process involvement are also important mediators to strengthen the influencer’s ability to encourage desired consumer behavior among their followers (e.g., positive audience, brand, influencer, and social behavior), whereas audience comments, assurance, hashtags, insights, and volume of posts can moderate or nullify the potential desired impact that influencers could elicit from their followers on social media. Indeed, the importance of electronic word of mouth, parasocial interaction, and perceptions of closeness and fit have also been highlighted through the review. Importantly, when promoting to kids and youth, it is essential that influencers consider what parents would think about their posts, as parental mediation was observed to occur in the review.

5.3 Review limitations and future review directions

From a review perspective, this study acknowledges three major limitations that can inform the curation of future reviews.

First, the systematic literature review herein does not capture article performance (i.e., citations) because it was mainly interested in unpacking the articles, journals, theories, methods, and content (themes, constructs) underpinning existing research on social media influencer marketing, and it kept in mind the space limitation of the journal. Notwithstanding the comprehensive and rigorous insights revealed using the SPAR-4-SLR protocol, future reviews may wish to pursue an impact analysis, which can lead to rich insights pertaining to article performance (e.g., difference in citations [e.g., total citations, average citations per year, h -index, g -index] between papers with and without theory, using empirical and non-empirical methods, or across different methods and thematic categories).

Second, the systematic literature review herein encapsulates only a qualitative evaluation of the constructs in existing social media influencer marketing research. To build on the insights herein, future reviews may wish to pursue a meta-analytical review, where a meta-analysis involving the antecedents, mediators, moderators, and consequences revealed in Tables 8 , 9 , 10 , and 11 in this review (in the short run) or unveiled in future reviews (in the long run) is performed. Such an endeavor should also provide finer-grained insights on conflicting findings and provide a resolution to such findings in the same study.

Third, the systematic literature review herein focuses only on the consumer behavior perspective of social media influencer marketing, which is mainly due to the maturity of research from this perspective [ 98 ], as seen through the number of articles available for review (i.e., 214 articles) under a rigorous protocol (i.e., the SPAR-4-SLR protocol). Moving forward, future reviews may wish to pursue a systematic review of social media influencer marketing from the business and industrial perspective, wherein the impact of influencer marketing on social media for business and industrial brands in general and across different industries are reviewed and reported.

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Joshi, Y., Lim, W.M., Jagani, K. et al. Social media influencer marketing: foundations, trends, and ways forward. Electron Commer Res (2023). https://doi.org/10.1007/s10660-023-09719-z

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Role of Social Media Marketing Activities in Influencing Customer Intentions: A Perspective of a New Emerging Era

Khalid jamil.

1 School of Economics and Management, North China Electric Power University, Beijing, China

Rana Faizan Gul

Muhammad usman shehzad.

2 Department of Management Sciences and Engineering, Zhengzhou University, Zhengzhou, China

Syed Hussain Mustafa Gillani

3 Faisalabad Business School, National Textile University, Faisalabad, Pakistan

Fazal Hussain Awan

Associated data.

The raw data supporting the conclusion of this article will be made available by the authors, without undue reservation.

The aim of this study is to explore social media marketing activities (SMMAs) and their impact on consumer intentions (continuance, participate, and purchase). This study also analyzes the mediating roles of social identification and satisfaction. The participants in this study were experienced users of two social media platforms Facebook and Instagram in Pakistan. A self-administered questionnaire was used to collect data from respondents. We used an online community to invite Facebook and Instagram users to complete the questionnaire in the designated online questionnaire system. Data were collected from 353 respondents, and structural equation modeling (SEM) was used to analyze the data. Results show that SMMAs have a significant impact on the intentions of users. Furthermore, social identification mediates the relationship between social media activities and satisfaction, and satisfaction mediates the relationship between social media activities and the intentions of users. This will help marketers how to attract customers to develop their intentions. This is the first novel study that used SMMAs to address the user intentions with the role of social identification and satisfaction in the context of Pakistan.

Introduction

There has been tremendous growth in the use of social media platforms such as WhatsApp, Instagram, and Facebook over the past decade ( Chen and Qasim, 2021 ). People are using these platforms to communicate with one another, and popular brands use them to market their products. Social activities have been brought from the real world to the virtual world courtesy of social networking sites. Messages are sent in real time which now enable people to interact and share information. As a result, companies consider social media platforms as vital tools for succeeding in the online marketplace ( Ebrahim, 2020 ). The use of social media to commercially promote processes or events to attract potential consumers online is referred to as social media marketing (SMM). With the immense rise in community websites, a lot of organizations have started to find the best ways to utilize these sites in creating strong relationships and communications with users to enable friendly and close relationships to create online brand communities ( Ibrahim and Aljarah, 2018 ).

Social media marketing efficiently fosters communications between customers and marketers, besides enabling activities that enhance brand awareness ( Hafez, 2021 ). For that reason, SMM remains to be considered as a new marketing strategy, but how it impacts intentions is limited. But, to date, a lot of research on SMM is focused on consumer’s behavior, creative strategies, content analysis and the benefits of user-generated content, and their relevance to creating virtual brand communities ( Ibrahim, 2021 ).

New channels of communication have been created, and there have been tremendous changes in how people interact because of the internet developing various applications and tools over time ( Tarsakoo and Charoensukmongkol, 2020 ). Companies now appreciate that sharing brand information and consumer’s experience is a new avenue for brand marketing due to the widespread use of smartphones and the internet, with most people now relying on social media brands. Therefore, developing online communities has become very efficient. Social groups create a sense of continuity for their members without meeting physically ( Yadav and Rahman, 2017 ). A community that acquires products from a certain brand is referred to as a virtual brand community. Customers are not just interested in buying goods and services but also in creating worthwhile experiences and strong relationships with other customers and professionals. So, when customers are part of online communities, there is a cohesion that grows among the customers, which impacts the market. Therefore, it is up to the companies to identify methods or factors that will encourage customers to take part in these communities ( Ismail et al., 2018 ).

The online community’s nature is like that of actual communities when it comes to creating shared experiences, enabling social support, and attending to the members’ need to identify themselves, regardless of the similarities and variances existing between real-world communities and online communities ( Seo and Park, 2018 ). Regarding manifestations and technology, online communities are distinct from real-life communities since the former primarily use computers to facilitate their operation. A certain brand product or service is used to set up a brand community. Brand communities refer to certain communities founded based on interactions that are not limited by geographical restrictions between brand consumers ( Chen and Lin, 2019 ). Since consumers’ social relationships create brand communities, these communities have customs, traditions, rituals, and community awareness. The group members learn from each other and share knowledge about a product, hence appreciating each other’s actions and ideas. So, once a consumer joins a particular brand community, automatically, the brand becomes a conduit and common language linking the community members together because of sharing brand experiences ( Arora and Sanni, 2019 ).

Based on the perspective of brand owners, most research has focused on how social communities can benefit brands. However, there are also some discussions regarding the benefits that come from brand community members according to the members themselves to analyze how social community impacts its members ( Shareef et al., 2019 ). Consumer’s behavior is influenced by value so, when a consumer is constantly receiving value, it leads to consumer’s loyalty toward that brand. According to Alalwan et al. (2017) , a valuable service provider will create loyalty to a company and enhance brand awareness. Consumer value is essentially used in evaluating social networking sites. With better and easier options to create websites coming around, most consumers are attracted to a social community to know about a company and its goods. Furthermore, operators can learn consumer’s behavior through maintaining social interactions with customers. However, the social community should have great value. It should be beneficial to the potential customers by providing them with information relevant to the brand in question. Furthermore, customers should be able to interact with one another, thus creating a sense of belonging. From that, it is evident that a brand social community’s satisfaction affects community retention and selection.

Literature Review

Social media marketing activities.

Most businesses use online marketing strategies such as blogger endorsements, advertising on social media sites, and managing content generated by users to build brand awareness among consumers ( Wang and Kim, 2017 ). Social media is made up of internet-associated applications anchored on technological and ideological Web 2.0 principles, which enables the production and sharing of the content generated by users. Due to its interactive characteristics that enable knowledge sharing, collaborative, and participatory activities available to a larger community than in media formats such as radio, TV, and print, social media is considered the most vital communication channel for spreading brand information. Social media comprises blogs, internet forums, consumer’s review sites, social networking websites (Twitter, Blogger, LinkedIn, and Facebook), and Wikis ( Arrigo, 2018 ).

Social media facilitates content sharing, collaborations, and interactions. These social media platforms and applications exist in various forms such as social bookmarking, rating, video, pictures, podcasts, wikis, microblogging, social blogs, and weblogs. Social networkers, governmental organizations, and business firms are using social media to communicate, with its use increasing tremendously ( Cheung et al., 2021 ). Governmental organizations and business firms use social media for marketing and advertising. Integrated marketing activities can be performed with less cost and effort due to the seamless interactions and communication among consumer partners, events, media, digital services, and retailers via social media ( Tafesse and Wien, 2018 ).

According to Liu et al. (2021) , marketing campaigns for luxury brands consist of main factors such as customization, reputation, trendiness, interaction, and entertainment which significantly impact customers’ purchase intentions and brand equity. Activities that involve community marketing accrue from interactions between events and the mental states of individuals, whereas products are external factors for users ( Parsons and Lepkowska-White, 2018 ). But even though regardless of people experience similar service activities, there is a likelihood of having different ideas and feelings about an event; hence, outcomes for users and consumers are distinct. In future marketing, competition will focus more on brand marketing activities; hence, the marketing activities ought to offer sensory stimulation and themes that give customers a great experience. Now brands must provide quality features but also focus on enabling an impressive customer’s experience ( Beig and Khan, 2018 ).

Social Identification

A lot of studies about brand communities involve social identification, appreciating the fact that a member of a grand community is part and parcel of that community. Social identity demystifies how a person enhances self-affirmation and self-esteem using comparison, identity, and categorization ( Chen and Lin, 2019 ). There is no clear definition of the brand community or the brand owner, strengthening interactions between the community and its members or creating a rapport between the brand and community members. As a result, members of a community are separated into groups based on their educational attainment, occupation, and living environment. Members of social networks categorize each other into various groups or similar groups according to their classification in social networks ( Salem and Salem, 2021 ).

Brand identification and identification of brand communities emanate from a similar process. Users can interact freely, hence creating similar ideologies about the community, alongside strengthening bonds among members, hence enabling them to identify with that community. The brand community identity can also be considered as a convergence of values between the principles of the social community and the values of the users ( Wibowo et al., 2021 ).

According to Lee et al. (2021) , members of a brand social community share their ideas by taking part in community activities to help create solutions. When customers join a brand community, they happily take part in activities or discussions and are ready to help each other. So, it is evident that social community participation is impacting community identity positively. Community involvement entails a person sharing professional understanding or knowledge with other members to enhance personal growth and create a sense of belonging ( Gupta and Syed, 2021 ). According to Haobin Ye et al. (2021) , it is high time community identity be incorporated in virtual communities since it is a crucial factor that affects the operations of virtual communities. Also, community identity assists in facilitating positive interactions among members of the community, encouraging them to actively take part in community activities ( Assimakopoulos et al., 2017 ). This literature review suggests that social communities need members to work together. Individuals who can identify organizational visions and goals become dedicated to that virtual company.

Satisfaction

Customer’s satisfaction involves comparing expected and after-service satisfaction with the standards emanating from accumulated previous experiences. According to implementation confirmation theory, satisfaction is a consumer’s expected satisfaction with how the services have lived up to those expectations. Customers usually determine the level of satisfaction by comparing the satisfaction previously experienced and the current one ( Pang, 2021 ).

According to recent studies, community satisfaction impacts consumer’s loyalty and community participation. A study community’s level of satisfaction is determined by how its members rate it ( Jarman et al., 2021 ). Based on previous interactions, the community may be evaluated. When the members are satisfied with their communities, it is manifested through joyful emotions, which affect the behavior of community members. In short, satisfaction creates active participation and community loyalty ( Shujaat et al., 2021 ).

Types of Intentions

A lot of studies about information and marketing systems have used continuance intention in measuring if a customer continues to use a certain product or service. The willingness of customers to continue using a good or service determines if service providers will be successful or not. According to Zollo et al. (2020) , an efficient information marketing system should persuade users to use it, besides retaining previous users to guarantee continued use.

Operators of social networks must identify the reason propelling continued use of social network sites, alongside attracting more users. Nevertheless, previous studies on information systems in the last two decades have mainly concentrated on behavior–cognition approaches, for instance, the technology acceptance model (TAM), theory of planned behavior (TPB), and theory of reasoned action (TRA) with their variants ( Tarsakoo and Charoensukmongkol, 2020 ; Jamil et al., 2021b ). According to Ismail et al. (2018) , perceived use and satisfaction positively impact a user’s continuance intention. The continued community members’ participation has two intentions. Continuance intention is the first one. It defines the community member’s intent to keep on using the community ( Beig and Khan, 2018 ; Dunnan et al., 2020 ). Then, recommendation intention, also known as mouth marketing, describes every informal communication that takes place among community members regarding the virtual brand community. Previous studies about members of a virtual community mostly entailed the continuous utilization of information systems ( Seo and Park, 2018 ; Sarfraz et al., 2021 ). Unlike previous studies, this study focuses on factors that support the continued participation of community members. So, besides determining how usage purpose affects continuance intention, the study also investigated the factors that influence users’ willingness to take part in community activities ( Gul et al., 2021 ).

Nevertheless, it is hard to determine and monitor whether a certain action occurred (recommendation or purchase) during empirical investigations. Consumers will seek relevant information associated with their external environment and experiences when purchasing goods ( Shareef et al., 2019 ). Once they have collected significant information, they will evaluate it, and draw comparisons from which customer’s behavior is determined. Since purchase intention refers to a customer’s affinity toward a particular product, it is a metric of a customer’s behavioral intention. According to Liu et al. (2021) , the probability of a customer buying a particular product is known as an intention to buy. So, when the probability is high, it simply means that the willingness to purchase is high. Past studies consider purchase intention as a factor that can predict consumer’s behavior alongside the subjective possibility of consumer’s purchases. According to Chen and Qasim (2021) , from a marketing viewpoint, if a company wants to retain its community besides achieving community targets while establishing successful marketing via the community, at least three objectives are needed. They include membership continuance intention, which entails members living up to their promises in the community and also the willingness to belong to the community ( Yadav and Rahman, 2018 ; Naseem et al., 2020 ). On the other side, community recommendation intention entails the willingness of members to recommend or refer community members to other people who are not members ( Jamil et al., 2021a ; Mohsin et al., 2021 ). The next consideration is the community participation intention of a member, which involves their willingness to participate in the activities of the brand community. Unlike past literature about using information systems, this study demystified how SMMAs influence purchase intention and participation intention ( Alalwan et al., 2017 ).

Development of Hypotheses

People with similar interests can get a virtual platform to discuss and share ideas courtesy of social media. Sustained communication of social media allows users to create a community. Long-lasting sharing of growth and information fosters the development of strong social relationships. The information posted on social media platforms by an individual positively correlates with the followers the user has. Regarding the discussion above, we proposed the following hypothesis:

• H1: Social media marketing activities (SMMAs) have a significant impact on social identification.

The study of Farivar and Richardson (2021) on users’ continuance intention confirmed that it is influenced by satisfaction after service. Social media studies are also of the thought that satisfaction significantly affects continuance intention. So, a consumer will measure the satisfaction of service after using it. Mahendra (2021) claims that satisfaction influences repurchase behavior. Repurchase intention emanates from a customer’s satisfaction with a good or service. People who have similar interests may interact and cooperate in a virtual world via social media platforms. A community on social media may be formed by regularly connecting with people and exchanging information with them. Members benefit from long-term information and growth exchanges that enable them to create strong social relationships. A lot of studies have pointed out that repurchase intention and customer’s satisfaction are positively and highly related. Besides, marketing studies noted that satisfactory experience after using a product would impact the intention of future repurchase. Hence, we proposed the following hypothesis:

• H2: SMMAs have a significant impact on satisfaction.

The study by Suman et al. (2021) on American consumer’s behavior suggested that members taking part in community activities (meetups, discussion, and browsing) influence their brand-associated behavior. According to Di Minin et al. (2021) , the brand identity of a consumer has a positive impact on satisfaction. Consumers capitalize on online communities to share their experiences and thoughts about a grand regularly and easily ( Sirola et al., 2021 ). These experiences make up the customer to brand experiences and establish a sense of belonging, trust, and group identity. In a nutshell, this study suggests that identity will enable members to recognize their community, hence confirming that members have similar experiences and feelings with a particular brand and feel united in the group ( Shujaat et al., 2021 ). Strong group identity means that members are integrated closely into the brand communities and highly regard the community. Hence, we proposed the following hypothesis:

• H3: Social identification has a significant impact on satisfaction.

Brand communities are beneficial in the sense that they enable sharing of marketing information, managing a community, and exploring demands ( Dutot, 2020 ). These activities are likely to enhance consumer’s rights and increase customer’s satisfaction ( Sahibzada et al., 2020 ). A customer who makes an online transaction will be highly satisfied with a website that provides a great experience ( Koçak et al., 2021 ). Enhancing customer’s satisfaction, encouraging customer intentions, creating community loyalty, and fostering communication and interactions between community users are crucial to lasting community platform management ( Pang, 2021 ). Hence, we proposed the following hypotheses:

• H4: Satisfaction has a significant impact on continuance intention.
• H5: Satisfaction has a significant impact on participate intention.
• H6: Satisfaction has a significant impact on purchase intention.

Thaler (1985) proposed transaction utility theory, in which consumers’ willingness to spend money is influenced by their perceptions of value. Researchers such as Dodds (1991) claimed that buyers only become ready to purchase after they have established a sense of value for a product. According to Petrick et al. (2001) , a product’s quality is dependent on the customer’s satisfaction. Several studies have shown that enjoyment, perceived value, and behavioral intention are all linked together. Hence, we proposed the following hypothesis:

• H7: Social identification mediates the relationship between SMMA and satisfaction.

When it comes to information systems, Bhattacherjee et al. (2008) discovered that people’s continual intention is derived from their satisfaction with the system after they have used it. Studies on employee’s satisfaction in the workplace have shown that it has a substantial influence on CI. The amount of satisfaction that users have with the system that they have previously used is the most important factor in determining their CI, according to research on information system utilization intention.

In other words, the customer’s contentment with the product leads to the establishment of a desire to buy the thing again, as mentioned by Assimakopoulos et al. (2017) . Numerous studies show a strong link between customer’s satisfaction and their propensity to return for another transaction. According to a lot of marketing studies, customers who have a pleasant experience with a product are more likely to repurchase it. Hence, we proposed the following hypotheses:

• H8: Satisfaction mediates the relationship between social identification and continuance intention.
• H9: Satisfaction mediates the relationship between social identification and participate intention.
• H10: Satisfaction mediates the relationship between social identification and purchase intention.

Figure 1 shows the research framework of this study.

Conceptual framework.

Conceptual Framework

Research methodology.

This study designed a questionnaire according to the hypotheses stated above. The participants in this study were experienced users of two social media platforms Facebook and Instagram in Pakistan. A self-administered questionnaire was used to collect data from respondents. A pilot study with 40 participants was carried out. Since providing recommendations, revisions were made to the final questionnaire to make it more understandable for the study’s respondents. To ensure the content validity of the measures, three academic experts of marketing analyzed and make improvements in the items of constructs. The experts searched for spelling errors and grammatical errors and ensured that the items were correct. The experts have proposed minor text revisions to social identification and satisfaction items and advised that the original number of items is to be maintained. This study used an online community to invite Facebook and Instagram users to complete the questionnaire in the designated online questionnaire system. Online questionnaires have the following advantages ( Tan and Teo, 2000 ): (1) sampling is not restricted to a single geological location, (2) lower cost, and (3) faster questionnaire responses. A total of 353 questionnaires were returned from respondents. There were 353 appropriate replies considered for the final analysis.

The study used items established from prior research to confirm the reliability and validity of the measures. All items are evaluated through 5-point Likert-type scales where “1” (strongly disagree), “3” (neutral), and “5” (strongly agree).

Dependent Variable

To get a response about three dimensions of intention (continuance, participate, and purchase), we used eight items adopted from prior studies;

• 1. Continuance intention is measured by three items from the study of Bhattacherjee et al. (2008) , and the sample item is, “I intend to continue buying social media rather than discontinue its use.”
• 2. Participate intention is evaluated by three items from the work of Debatin et al. (2009) , and the sample item is, “my intentions are to continue participating in the social media activities.”
• 3. Purchase intention was determined by two items adapted from the work of Pavlou et al. (2007) , and the sample item is, “I intend to buy using social media in the near future.”

Independent Variable

To analyze the five dimensions of SMMAs, we used eleven items adopted from a prior study of Kim and Ko (2012) .

• 1. Entertainment is determined by two items and the sample item is, “using social media for shopping is fun.”
• 2. Interaction is evaluated by three items, and the sample item is, “conversation or opinion exchange with others is possible through brand pages on social media.”
• 3. Trendiness is measured by two items, and the sample item is, “contents shown in social media is the newest information.”
• 4. Customization is measured by two items, and the sample item is, “brand’s pages on social media offers customized information search.”
• 5. Word of mouth is measured by two items, and the sample item is, “I would like to pass along information on the brand, product, or services from social media to my friends.”

Mediating Variables

We used two mediating variables in this study,

• 1. Social identification was measured with five items adopted from the prior study of Bhattacharya and Sen (2003) , and the sample item is, “I see myself as a part of the social media community.”
• 2. Satisfaction was evaluated with six items adopted from the study of Chen et al. (2015) , and the sample item is, “overall, I am happy to purchase my desired product from social media.”

This research employs a partial least square (PLS) modeling technique, instead of other covariance-based approaches such as LISREL and AMOS. The reason behind why we pick PLS-SEM is that it is most suitable for confirmatory and also exploratory research ( Hair Joe et al., 2016 ). Structural equation modeling (SEM) has two approaches, namely covariance-based and PLS-SEM ( Hair et al., 2014 ). PLS is primarily used to validate hypotheses, whereas SEM is most advantageous in hypothesis expansion ( Podsakoff et al., 2012 ). A PLS-SEM-based methodology would be done in two phases, first weighing and then measurement ( Sarstedt et al., 2014 ). PLS-SEM is ideal for a multiple-order, multivariable model. To do small data analysis is equally useful in PLS-SEM ( Hair et al., 2014 ). PLS-SEM allows it easy to calculate all parameter calculations ( Hair Joe et al., 2016 ). The present analysis was conducted using SmartPLS 3.9.

Model Measurement

Table 1 shows this study model based on 31 items of the seven variables. The reliability of this study model is measured with Cronbach’s alpha ( Hair Joe et al., 2016 ). As shown in Table 1 , all items’ reliability is robust, Cronbach’s alpha (α) is greater than 0.7. Moreover, composite reliability (CR) fluctuates from.80 to.854, which surpassed the prescribed limit of 0.70, affirming that all loadings used for this research have shown up to satisfactory indicator reliability. Ultimately, all item’s loadings are over the 0.6 cutoff, which meets the threshold ( Henseler et al., 2015 ).

Inner model evaluation.

The Cronbach’s alpha value for all constructs must be greater than 0.70 is acceptable ( Hair et al., 2014 ). All the values of α are greater than 0.7 as shown in Table 1 and Figure 2 .

Measurement model.

Convergent validity is measured by CR and AVE, and scale reliability for each item ( Hair Joe et al., 2016 ). The scholar says that CR and AVE should be greater than 0.7 and 0.5, respectively. By utilizing CR and average variance extracted scores, convergent validity was estimated ( Fornell and Larcker, 1981 ). As elaborated in Table 3 , the average variance extracted scores of all the indicators are greater than 0.50 and CR is higher than.70 which is elaborating an acceptable threshold of convergent validity and internal consistency. It is stated that a value of CR, that is, not less than 0.70, is acceptable and evaluated as a good indicator of internal consistency ( Sarstedt et al., 2014 ). Moreover, average variance extracted scores of more than 0.50 demonstrate an acceptable convergent validity, as this implies that a specific construct with greater than 50% variations is clarified by the required indicators.

Discriminant validity.

CI, continuance intention; PI, participate intention; PUI, purchase intention; Sat, satisfaction; SI, social identification; SMMA, social media marketing activities.

This study determines the discriminant validity through two techniques named Fornell–Larcker criterion and heterotrait–monotrait (HTMT) ( Hair Joe et al., 2016 ). In line with Fornell and Larcker (1981) , the upper right-side diagonal values should be greater than the correlation with other variables, which is the square root of AVE, which indicates the discriminant validity of the model. Table 3 states that discriminant validity was developed top value of variable correlation with itself is highest. The HTMT ratios must be less than 0.85, although values in the range of 0.90 to 0.95 are appropriate ( Hair Joe et al., 2016 ). Table 3 displays that all HTMT ratios are less than 0.90, which reinforces the statement that discriminant validity was supported in this study’s classification.

To determine the problem of multicollinearity in the model, VIF was calculated for this purpose. The experts said that if the value of VIF is greater than 5, there is no collinearity issue in findings ( Hair et al., 2014 ). The results indicate that the inner value of VIF for all indicators must fall in the range of 1.421 to 1.893. Furthermore, these study findings show no issue of collinearity with data, and the study has stable results.

To evaluate “the explanatory power of the model,” the R 2 value was analyzed for every predicted variable. It shows the degree to which independent variables illustrate the dependent variables. R 2 value in “between 0 and 1 with higher values shows a higher level of predictive accuracy. Subsequent values of R 2 describe 0.25 for weak, 0.50 for moderate, and 0.75 for” substantial. An appropriate model is indicated by R 2 greater than 0.5 in primary results. In Figure 2 , the value of R 2 greater than 0.5 on all exogenous constructs, which also means that the model has strong predictive accuracy ( Hair Joe et al., 2016 ).

Table 4 displays the percentage of variance clarified for every variable: 62.7% of continuous intention, 55.5% of participate intention, 54.5% for purchase intention, 80.9% for satisfaction, and 81.8% for social identification. In general, results demonstrate that values of R 2 of endogenous variables are greater than 80%, which is the sign of a substantial “parsimonious model” ( Sarstedt et al., 2014 ). Most importantly, the outputs give a significant validation of the model. Q 2 values of all four 5 latent variables suggest that the model is extremely predictive ( Hair et al., 2014 ).

Predictive accuracy and relevance of the model.

Hypothesis Testing

This study evaluates the significance of relationships using bootstrapping at 5,000 with a replacement sample ( Hair Joe et al., 2016 ; Awan et al., 2021 ). The findings show that SMMAs have significant relationship with social identification (β = 0.905, t -value = 36.570, p = 0.000) which accept the H1. The findings show that SMM significantly influences the satisfaction (β = 0.634, t -value = 8.477, p = 0.000). Social identification has significant positive relationship with satisfaction as shown in Table 5 (β = 0.284, t -value = 4.348, p = 0.000) which accept the H3. The results show that satisfaction has significant relationship with continuous intention (β = 0.792, t -value = 15.513, p = 0.000) which support the H4. The findings show that satisfaction has strong positive relationship with participant intention (β = 0.745, t -value = 12.041, p = 0.000), which support the H5. The findings show that satisfaction has strong positive relationship with purchase intention (β = 0.739, t -value = 12.397, p = 0.000) which support the H6. The findings of the current investigation support H1, H2, H3, H4, H5, and H6. The results show that H4, H1a, H1b, H3a, H3b, H2a, and H2b are accepted (refer to Table 5 and Figure 3 ).

Hypothesis testing.

Structural model.

Preacher and Hayes (2008) argue that if the VIF value is greater than 80%, then it shows full mediation, and value of VIF equal to 20 to 80% which indicate the partial mediation and if VIF falls below 20%, then there is no mediation. The findings show that social identification mediates the relationship between SMM and satisfaction (β = 0.213, t -value = 3.570, p -value = 0.000) and indirect effect (β = 0.257, t -value = 4.481, p -value = 0.000) with variance accounted for (VAF) 75% which show partial mediation. In this, the VAF describes the size of the indirect effect in relation to the total effect ( Hayes and Preacher, 2010 ). The findings show that satisfaction mediates the relationship between social identification and continuous intention (β = 0.342, t -value = 3.435, p -value = 0.000) and indirect effect (β = 0.225, t -value = 4.636, p -value = 0.000) with VAF 64% which show partial mediation. In this, the VAF describes the size of the indirect effect in relation to the total effect ( Hayes, 2009 ). The findings show that satisfaction mediates the relationship between social identification and participant intention (β = 0.324, t -value = 5.325, p -value = 0.000) and indirect effect (β = 0.211, t -value = 4.338, p -value = 0.000) with VAF 73% which show partial mediation. The findings show that satisfaction mediates the relationship between social identification and purchase intention (β = 0.312, t -value = 3.434, p -value = 0.000) and indirect effect (β = 0.3.213, t -value = 5.437, p -value = 0.000) with VAF 78% which show partial mediation (refer to Table 2 ).

A mediation analysis.

Discussion and Conclusion

The study was about SMMAs as proposed by Kim and Ko (2012) , and it investigated which factors influence social media usage. The findings of the study include the following:

Most studies about social websites have not exhausted the impact of SMMAs. According to this study, SMMAs significantly affect social identification, which ultimately influences purchase decisions, participation decisions, continuance intention, and satisfaction. The study demystified social media usage intention. The findings were that SMMAs could sustain corporate brands. According to Beig and Khan (2018) , unlike blog marketing and keyword advertising that were associated with content, SMM gets to the targeted audiences to enhance the impact of the information being shared by creating strong relationships in the online community. Therefore, service providers of social media must put into consideration means of increasing the impact of SMMAs. To boost SMMAs, operators should increase activity on the forum. The members of a community can be allowed to explain the guiding factors behind choosing a particular brand over that of competitors for other members to know the competing brands. From the discussions and sharing of knowledge, members get an opportunity to understand why they like a particular brand, thus enhancing brand loyalty and community cohesion ( Yadav and Rahman, 2017 ).

The study also confirmed that most administrators are concerned with the influence of brand community management in creating business advantage. According to Tarsakoo and Charoensukmongkol (2020) , marketing strategies and tools have undergone tremendous changes since the inception of social media. Consumers no longer must rely on traditional media to acquire information about a product before making their purchase since social media can effectively and easily avail such information. For that reason, social media service providers must come up with effective measures of controlling publication timing, frequency, and content to achieve the set marketing targets. According to this study, if a company can successfully assist users to easily identify with a particular brand community, strong relationships will be fostered between the consumers and the brand, hence creating customer’s loyalty ( Ebrahim, 2020 ). Besides, users may stop using competitors’ products. So, companies need to appreciate that proper management of online strategies and brand community in creating community identity enhances brand’s competitiveness and inspires members of the brand community to shun using goods and services from competitors.

Limitations and Recommendations

Regardless of the efforts geared toward enabling in-depth data collection, research methodology, and research structure, there were still various limitations that ought to be dealt with in studies to be conducted in the future. For instance, using online questionnaires in data collection, some members might have been very willing to fill them because of their community identity, hence enabling self-selection bias that may impact the validity and authenticity of the outcomes. Besides, a cross-sectional sample was used in the study; hence, results from the analysis can only demystify individual usage patterns on well-known social media. Nevertheless, the different social media platforms provide different services; hence, long-term usage needs long-term observation. The outcomes of growth model analysis with the experimental values and browsing experiences of users at the various phases in longitudinal studies to be conducted in the future may be increasingly conclusive on casual relationships with variables. The third limitation of the study is that different countries or areas have different preferences regarding social media. Future studies should unravel the reasons behind individuals from various cultural backgrounds or countries using different social media platforms and what might be the demands and motivations behind their preferences. Besides, new social networking sites such as Facebook and Twitter have unique characteristics which are different from traditional sites. Future studies should also focus on this shift. For this study, the emphasis was on SMMAs’ influence on user’s behavior and usage demands.

Data Availability Statement

Author contributions.

All authors listed have made a substantial, direct, and intellectual contribution to the work, and approved it for publication.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer ZA declared a shared affiliation with one of the authors, SG, to the handling editor at time of review.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

This study was partly supported by the National Social Science Foundation of China (no. 19ZDA081).

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