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The effect of motivation on employee engagement in public sectors: in the case of North Wollo zone

  • Abriham Ebabu Engidaw   ORCID: orcid.org/0000-0002-5081-5668 1  

Journal of Innovation and Entrepreneurship volume  10 , Article number:  43 ( 2021 ) Cite this article

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The purpose of this study was to examine the effect of intrinsic and extrinsic motivation on employee engagement in public sectors. To meet this purpose, a quantitative and qualitative study survey was conducted and the researcher used an explanatory survey research design. The study was used both primary and secondary sources of data. The target population for this study was selected four city administrative office employees including all kebeles office employees and as a sample size, 349 questionnaires were filled and collected from these employees. The study used proportionately stratified with simple random sampling because to collect the relevant data and to give equal chance for all employees. Later on, statistical package for social science (SPSS) was used to the required test of inferential statistics; including reliability analysis, bivariate correlation, analysis of variance (ANOVA) test, and multiple regression analysis. The finding of the study revealed that extrinsic motivation was considered more significant than intrinsic and there was a positive significant relationship between intrinsic and extrinsic motivations with employee engagement. From the results, it was also concluded that the relationship and effect of extrinsic motivation were stronger on employee engagement as compared to intrinsic motivation. As a recommendation, the organizations should find which ways are able to motivate employees, what drives them, then making sure they utilize appropriate motivational techniques with each employee. Managers should also endeavor to communicate the organization’s purpose to employees. Finally, the organizations should take steps to incorporate the vision of employees for the organization with its own vision.

Introduction

An unmotivated employee is likely to put little effort into work tasks, produce work of lower quality, avoid the workplace, and even exit his or her job if given the opportunity to do so. On the other hand, motivated employees are likely to willingly take on tasks, produce work of high quality, and be creative, persistent, and productive. Employees motivation has two forms, intrinsic and extrinsic. Intrinsic motivation arises from the intrinsic value of the work for the individual (for example, its interest value), whereas, extrinsic motivation arises from the desire to obtain some outcomes (for example, as rewards) that are apart from the work itself (Amabile, 1993 ). Each and every person in an organization is motivated in a different manner. Workers’ motivation depends on many intrinsic and extrinsic factors like interesting work, job appreciation, satisfaction, stress, job security, promotion and growth, rewards, work environment, punishment and recognition etcetera (Palaniammal, 2013 ).

The main purpose of these motivating factors is to create an environment where people are willing to work with zeal, initiative, interest, and enthusiasm, with a high personal and group satisfaction, with the sense of responsibility, loyalty, and confidence to achieve their personal as well as organizational goals (Palaniammal, 2013 ). Research has shown that there is a difference in strength between intrinsic and extrinsic motivation on their relationship and impact on employee engagement. Khan ( 2011 ) concluded that the relationship and impact of extrinsic motivation were stronger on employee engagement as compared to intrinsic motivation.

According to Shuck ( 2010 ) employee engagement is an individual employee’s cognitive, emotional, and behavioral state directed toward desired organizational outcomes. Recently, Rice ( 2012 ) defined engagement as full employee engagement represents an alignment of maximum satisfaction for the individual with a maximum contribution for the organization’s success. The focus of all definitions was on two things, employee satisfaction and contribution to organizational success.

According to different researchers’ study results, employee motivation can be used to engage employees in their work in the organization. Beyond motivation, to achieve success in today’s highly competitive environment many organizations have identified the need to engage their workforce. Habte ( 2016 ) concluded that managers perceive intrinsic motivation have a larger influence on the psychological aspects of employee engagement than extrinsic motivation. This supports the idea stated by Berl and Williamson ( 1987 ) but still contradict with the finding of Iqbal and Khan. When we see the above research findings: the study conducted by Khan ( 2013 ) is contradicted with the findings of Habte ( 2016 ), Thomas ( 2009 ) and Khan ( 2011 ).

This study was carried out in four selected city administration office employees in order to know and explain the effect of motivation on employee engagement. Basically, the researcher is initiated to conduct this study because based on his observation and preliminary investigation there is a problem of employees being motivated and engaged in public sectors and the other reasons are first there is the inconsistency of previous findings relating to this topic, second as the researcher’s knowledge there are few studies conducted directly related to this topic specifically in our country Ethiopia. So this study can try to fill these gaps. Based on the above research problems the researcher developed the following research questions:

Objectives of the study

General objective.

The main objective of this study was to identify the effect of motivation (intrinsic or extrinsic) on employee engagement in public sectors in the case of selected zones.

Specific objectives

To explain the effect of intrinsic motivation on employee engagement in selected city administration employees.

To describe the effect of extrinsic motivation on employee engagement in selected city administration office employees.

To identify which motivation factor (intrinsic or extrinsic) more significantly affects employee engagement in the organization.

To examine the effect of overall motivation on employee engagement.

Literature reviews

  • Employee engagement

Employee engagement is defined as “harnessing of organizational members selves to their work roles; in engagement, people employ and express themselves physically, cognitively and emotionally during role performance”, In other words, “individual involvement and satisfaction as well as enthusiasm for work” Andrew ( 2012 ).

According to Kahn ( 1990 , 1992 , cited in Saks, 2006 ) job engagement means worker should be psychologically available during the performance of the organizational role.

The organization is totally dependent on their employees; therefore, they need to be engaged in their jobs. Engagement in the organization’s jobs enables employees to make operations successful, as it runs with the mutual commitment of organizations and employees. When organization employees will engage, they will use their potential to drive high performance (provide better services and attract maximum customers). Engage employees are more dedicated and helping to maximize the organization’s productivity. They are more likely to consider themselves as an employer. Therefore, organizations should pay attention to the employee engagement concept. Otherwise, it can be the biggest threat to the organization’s success. If the organization’s management is not interested in engaging employees, consequently it would lead to unsatisfactory beneficiaries and lose their customers (Andrew & Sofian, 2012 ).

From the theories and literature discussed above the researcher identified two broad motivation factors called intrinsic and extrinsic motivation and these motivation factors are also identified as an independent variable because they have an effect on the dependent variable, employee engagement, in one way or another.

  • Intrinsic motivation

According to Berl and Williamson ( 1987 ) intrinsic motivation is defined as the doing of an activity for its inherent satisfactions rather than for some benefits. Intrinsic motivation can be defined as the motivation to perform an activity in order to experience the pleasure and satisfaction inherent in the activity. They also further stated intrinsic motivation focuses on factors inside the individual which are based on personal needs. Employees get intrinsic reward directly from the job they perform, job satisfaction, interesting work, job appreciation, or the sense they help a client, Intrinsic motivated workers employ in a job because of their own interest in it and enjoy the job due to search for new solutions for business challenges and are more likely to burn up energy to identify problems and find innovative solutions.

From the Khan ( 2013 ) findings, they concluded that managers perceive intrinsic motivation as generally having a larger influence on the psychological aspects of employee engagement. They found that extrinsic motivation is of importance to employee engagement, though to a lesser extent psychologically but rather as a part of the total package that is offered to the employee by the organization and the manager. Habte ( 2016 ) concluded that managers perceive intrinsic motivation have a larger influence on the psychological aspects of employee engagement than extrinsic motivation. This conclusion leads to the next research hypothesis development on this research:

Hypothesis 1

Intrinsic motivation has a positive significant effect on employee engagement.

  • Extrinsic motivation

Extrinsic motivation is defined as a construct that pertains whenever an activity is done in order to attain some separable outcome and refers to doing an activity simply for the enjoyment of the activity itself, rather than its instrumental value (Deci & Ryan, 2008 ). Or it can be the rewards offered to employees as an encouragement to engage in a behavior/task in which they cannot employ or “an employee is inner-directed, is interested or fascinated with a task and engages in it for the sake of task itself” (Zhang, 2010 ). When organizations wanted to fulfill a task from employees, they deal with monetary rewards and other tangible benefits. It referred to extrinsic rewards in motivational language. Management should know what motivates their workers and manipulate motivational techniques based on employees ’s desires. This would help organizations to recognize, educate and retain creative and productive employees for their engagement. For organizations to be better products and to have efficient performance, both extrinsic and intrinsic reward systems should be introduced. The purpose of explaining motivation (extrinsic, intrinsic) is to identify which motivation affects and has a relation with job engagement. Employees consider both important factors for their job motivation but some employees consider it more in line with extrinsic than intrinsic and vice versa (Zhang, 2010 ).

The study of Khan ( 2013 ) also concluded that the relationship and impact of extrinsic motivation were stronger on employee engagement as compared to intrinsic motivation. Thomas ( 2009 ) saying about intrinsic motivation at work stated that intrinsic rewards become more important and more prevalent in the workplace today. The above review leads to the following research hypothesis:

Hypothesis 2

There is a positive significant effect relationship between extrinsic motivation and employee engagement.

Overall motivation and employee engagement

Khan ( 2013 ) conducted research on the relationship between work motivation (intrinsic and extrinsic) and employee engagement on Allied Bank of Pakistan. The finding of the study revealed that there is a positive relationship between intrinsic motivation and employee engagement, and extrinsic motivation and employee engagement. Four intrinsic factors namely interesting work, job appreciation, satisfaction, and stress, and four extrinsic factors namely job security, good wages, promotion and growth, and recognition were identified as important factors for engagement. The study concluded that there is a positive relationship between intrinsic motivation and employee engagement, and extrinsic motivation and employee engagement. Furthermore, it is also concluded both intrinsic and extrinsic motivation has a strong positive impact on employee engagement.

Aworemi ( 2011 ) conducted research on the motivational factors of employees and their influence on employee engagement Nigeria and Marginson ( 1991 ) conducted research on academic salaries: will award restructuring make a difference in employees’ engagement? And many researchers raised many issues and get different findings of motivational factors for employee engagement. By considering these reviews the researcher developed the next hypothesis:

Hypothesis 3

There is a positive significant effect relationship between overall motivation and employee engagement.

Empirical literature review

Khan and Iqbal ( 2013 ) study concluded that there is positive relationship between intrinsic motivation and employee engagement, and extrinsic motivation and employee engagement. Furthermore, it is also concluded both intrinsic and extrinsic motivation has strong positive impact on employee engagement. The study also concluded that the relationship and impact of extrinsic motivation was stronger on employee engagement as compared to intrinsic motivation.

Bergstrom and García ( 2016 ) studied the influence of intrinsic and extrinsic motivation on employee engagement in private and public organizations. However the study focused on the perceptions of managers “not employees”. From the findings study they concluded that managers perceive intrinsic motivation as generally having a larger influence on the psychological aspects of employee engagement. They found that extrinsic motivation is of importance to employee engagement, though to a lesser extent psychologically but rather as a part of the total package that is offered to the employee by the organization and the manager. Thomas ( 2009 ) saying about intrinsic motivation at work, stated that intrinsic rewards become more important and more prevalent in the workplace today.

Habte ( 2016 ) concluded that managers perceive intrinsic motivation have a larger influence on the psychological aspects of employee engagement than extrinsic motivation. This supports the idea stated by Bergstrom and García ( 2016 ) but still contradict with the finding of Iqbal and Khan.

Michael ( 2008 ) conducted study on using motivational strategy as solution for employee retention and turnover in both public and private sector organizations in South Africa and the researchers used training and development, recognition, reward, a competitive salary package and job security as motivational factors. Kassa ( 2015 ) in his research on motivation and its effect on employee retention in Ambo Mineral Water Factory, stated that employees are highly motivated with reward motivational factors and are less motivated with interesting work and training and development and working environment motivational factors.

Owusu ( 2012 ) conducted research on the effects of motivation on employee performance of commercial bank in Ghana and the researcher used salary, fringed benefits, promotion, and loans as motivational factors. Pessaran and Tavakoli ( 2011 ) conducted research on identifying the employees’ motivation of Parsian hotels in Tehran and the study used salary, security, working condition, status, achievement, recognition, growth and advancement, work itself and responsibility as motivational factors.

Conceptual framework

After reviewing the relevant concepts and theories of motivation (intrinsic, extrinsic) and employee engagement mentioned in this chapter, the conceptual framework of the study has been developed as shown in the following figure (Fig. 1 ).

Research methodology

To achieve this study’s purpose, the researcher has used an explanatory survey research design, and also quantitative and qualitative study survey was employed. Standard close-ended questionnaires were used as a survey tool. The study was used both primary and secondary sources of data. The target population for this research was four city administrative office employees including all kebeles office employees and 349 questionnaires were collected from employees. The study used proportionate stratified with simple random sampling because to collect the relevant data and to give equal chance for all employees.

Since the organization under the study has four city administrations in different area. The sample was drawn from all city administrative offices proportionally as follows (Table 1 ).

After the proper data collection, coding, and organization, the study data were analyzed using descriptive and inferential statistics. Under the descriptive statistics, mean and standard deviation are used and bivariate correlation was used to see whether the independent variables (intrinsic motivation and extrinsic motivation) have a relationship with the dependent variable (employee engagement). To determine the effect of independent variables (intrinsic motivation and extrinsic motivation) on the dependent variable (employee engagement) multiple linear regression analyses were used.

Measurements of variables

The independent variables for this study are intrinsic motivation and extrinsic motivation whereas the dependent variable was employee engagement. The researcher used standardized close-ended and some open-ended questionnaire instruments for collecting the primary sources of data. Questionnaires concerning employee engagement used are adapted from Gallup’s 12 standard questionnaires on the other hand questionnaires regarding intrinsic and extrinsic motivation is adopted from Khan ( 2013 ) Five-point Likert-Style rating scale was deployed in order to know the employees level of agreement on the effect of motivation (intrinsic and extrinsic) and employee engagement. The questionnaire has three parts; the first part is about demographic variables, the second part was about intrinsic and extrinsic motivation, and the last part also about employee engagement. Intrinsic and extrinsic motivation have 8 items each and employee engagement had 12 items and both are used five-point Likert scale ranging from strongly disagree (1) to strongly agree (5).

The study was aimed at analyzing the effect of motivation on employee engagement at selected city administration offices. The dependent variable employee engagement and independent variables extrinsic and intrinsic motivation mean score was comparatively moderate. This points out that the greater part of respondents has a minor agreement on all measures. And also it shows that there was not a problem of multi co linearity, normality, and linearity in the study variables.

Based on the Table 2 result, the Pearson product-moment correlation analysis result showed that there is a moderate positive and significant relationship between intrinsic motivation and employee engagement at .329 and sig .000. This implied if the intrinsic motivation for the employees is increased it will also increase their engagement level. Lower employee intrinsic motivation will also lower their engagement level. The results of bivariate correlation confirmed that there is a moderate positive significant relationship between extrinsic motivation and employee engagement at .444 and sig level of .000. This implied if the extrinsic motivation for the employees is increased it will make significant positive changes in employee engagement. By lowering employee extrinsic motivation, employee engagement will also be lower. The study result showed that there was a moderate positive relationship between overall motivation and employee engagement. Also, extrinsic motivation had a more moderate positive relation with employee engagement as compared to intrinsic motivation.

Table 3 multiple regression analysis results portray that R square is .252 and adjusted R square is .248. This implied that 24.8% variation in employee engagement is explained by motivation in selected city administrations. In addition, the significance value of F statistics indicates a value .000 and it was less than p  < .05 so that it means the model was significant enough.

Also based on Table 4 result, multiple linear regression analysis results also confirmed that intrinsic motivation has a positive significant effect on employee engagement with the unstandardized Beta value of (.249, sig. level .000). As a result, the regression coefficient clarifies the average amount of change in employee engagement was affected by a unit of change in intrinsic motivation.

Regression analysis results also confirmed that extrinsic motivation had also a moderate positive significant effect on employee engagement. Since the beta value is .389 with a significance level of .000. Also, the result of extrinsic motivation showed it had a more moderate positive significant effect on employee engagement as compared to intrinsic motivation.

Furthermore, regression analysis was used to find out the effect of motivation on employee engagement. The result of the model summary from regression analysis indicated that overall motivation has a moderately positive effect on employee engagement. As a result, the regression coefficient clarifies the average amount of change in employee engagement was affected by a unit of change in motivation. The finding of the study indicated that intrinsic motivation has a highly significant effect on employee engagement compared to extrinsic motivation.

Based on open-ended questions feedback in the mentioned offices promotion and other related benefits are based on the strength of relationship with administers, there is a high shortage of working materials, there is no clear authority and responsibility delegation, no attractive work environment, no clear plan is prepared, fairness problem, high workload with unsatisfactory incentive and salary, there is the unnecessary intervention of managers at work, even superiors are not punctual and their incompetency/low problem-solving ability, some employees are hired on the unrelated job with their profession. Additionally, payments are not delivered on time, availability of hostile attitude, no motivational packages are available in those offices, customers’ poor discipline and others are things leading to be demotivated at their work and other related problems are available on those offices.

Comparison of the result of this study with the result of previous researches

As mentioned in the literature reviewed, the study of Christian et al. ( 2011 ) and Chalofsky and Krishna ( 2009 ) suggested that there was link between work engagement and motivational factors. Kahn ( 1990 ) and May et al. ( 2004 ) also relate employee engagement to motivation. Fairlie ( 2011 ) and Macey and Schneider ( 2008 ) pointed out that an investigation is required to find the link between work motivation and employee engagement. Thomas ( 2009 ) saying about intrinsic motivation at work, stated that intrinsic rewards become more important and more prevalent in the workplace today. Habte ( 2016 ) concluded that managers perceive intrinsic motivation have a larger influence on the psychological aspects of employee engagement than extrinsic motivation. Hence the finding of this study also supports these previous findings and also it contradicted with Habte ( 2016 ) finding.

Conclusions of the study

The study also examined the effect of intrinsic and extrinsic motivation on employee engagement. Four hypothesis questions were tested to answer the research question and fulfilled the research purpose. To achieve this objective, a quantitative and qualitative study survey was conducted and the researcher used an explanatory survey research design. A Standard close-ended questionnaire was used as a survey tool. The study was used both primary and secondary sources of data. The target population for this study was selected four city administrative office employees including all kebeles office employees) and as a sample size, 349 questionnaires were filled and collected from these employees. The study used proportionately stratified with simple random sampling because to collect the relevant data and to give equal chance for all employees. Later on, statistical package for social science (SPSS) software was used for the required test of inferential statistics; including reliability analysis, bivariate correlation, analysis of variance (ANOVA) test, and multiple regression analysis. From the findings of the research, it is concluded by answering the research questions and there is a significant positive relationship between intrinsic motivation at .329 and sig .000 and employee engagement and there is a positive significant relationship between extrinsic motivation and employee engagement at .444 and sig level of .000.

Findings of multiple regressions analysis portray that that intrinsic motivation has a positive significant effect on employee engagement with the unstandardized Beta value of (.249, sig. level .000). As a result, the regression coefficient clarifies the average amount of change in employee engagement was affected by a unit of change in intrinsic motivation. So that the decision rule in this research’s first hypothesis is to accept the alternative hypothesis.

Intrinsic motivation has a positive and statically significant effect on employee engagement at (Beta value of .249, sig. level .000). So the decision is to accept the alternative hypothesis and reject null hypothesis.

And also the regression analysis results confirmed that extrinsic motivation had also a moderate positive significant effect on employee engagement. Since the beta value is .331 with a significance level of .000. Also, the result of extrinsic motivation showed it had a more moderate positive significant effect on employee engagement as compared to intrinsic motivation. Based on the above study result the decision is to accept the alternative hypothesis and reject the null hypothesis of hypothesis two.

There is a positive significant effect relationship between extrinsic motivation and employee engagement at the beta value of .331 with a significance level of .000. So the decision is to accept the alternative hypothesis and to reject the null hypothesis.

When we test hypothesis three, the study revealed that there exists a positive significant relationship between both intrinsic and extrinsic motivation and employee engagement. There was also sufficient evidence to conclude that in addition to these relationships successful motivational factors (intrinsic and extrinsic) had positive effects on employee engagement in selected city administration office employees. Hence, for the management to stimulate employees' motivation and also to improve the level of staff works engagement, greater efforts must be placed on the two perceived motivating factors. In addition, as the open-ended question result, there is a low motivation with weak employees’ engagement at work in those offices. So the decision is to accept the alternative hypothesis.

There is a positive significant effect relationship between overall motivation and employee engagement. The decision is to accept the alternative hypothesis and to reject the null hypothesis.

Limitation of the study

In this study, the independent variables, intrinsic and extrinsic motivations were explained only 24.8% of the variation in employee engagement, but the other 75.2% were explained by other factors that were not included in this study. So, future studies could examine the rest variables which can explain the variation in employee engagement.

The study was only focused on four city administration office employees. Therefore, future researchers relating to this topic should assess in a wider and larger scope to include other private organizations and increase the generalizability of the study.

Besides this study, a comparative study could be done to know what the difference is available in different sectors relating to this topic. And another limitation is the research variable taken is subject to the understanding and knowledge of the researcher.

Recommendations

Recommendations for policy and practice.

The study result shows that employees of selected city administrations were motivated by both extrinsic and intrinsic motivations but they were more motivated by intrinsic motivation factors than extrinsic ones. So the management of those offices should give relevant attention to these factors to stimulate the employee’s engagement while developing and or revising strategies and policies for their organization.

The management and policymakers of selected city administrations should use rigorous efforts in encouraging employees intrinsic and intrinsic motivation for better work engagement by creating an attractive work atmosphere and satisfaction, provide appreciation for good performers, moreover the management should also increase employees extrinsic motivation by creating job security, provided promotion and growth, benefits, and good salary, give appropriate reward and recognition for employees, provide opportunities to some form of ownership, as well as increased responsibility and authority.

The organization should find which ways are able to motivate employees, what drives them, then making sure they utilize appropriate motivational techniques with each employee. Managers should also endeavor to communicate the organization's purpose to employees. Finally, the organizations should take steps to incorporate the vision of employees for the organization with his or hers own vision. This will motivate employees to engage and contribute to the organization’s goals.

These offices should give a fair promotion and other related benefits, solve the shortage of working material problems, should set clear authority and responsibility delegation, create an attractive work environment, clear work plan to be prepared, minimize workload and make satisfactory incentive and reward based on their performance, avoid the unnecessary intervention of managers at work, solve unpunctuality problem and could improve managers skill by developmental programs to make them more experienced, some employees are hired on the unrelated job with their profession so review and correct this issue are better. Additionally, payments should to deliver on time, motivational packages should present in those offices, and also to increase employees engagement the office should facilitate short term and long term work-related training, perform periodic performance appraisal, make supervision and control at work, reduce time management problems and unpunctuality, prepare benefit package and equal reward systems, better to make decision makings more participative and open to motivate employees or to create a sense of ownership, should give induction pieces of training when new entrants have joined the office, minimize the availability of corruption and unethical activities, work to keep rule and regulations, try to solve the shortage of office facilities, better to make a fast decision, and other related problems should be solved on those offices.

Generally, selected city administrations should communicate with employees regarding how looks like their motivation and engagement, which things should be fulfilled and the organizations management could assess more factors that are most important to increase employees engagement at work and it should make important corrective actions, it will make employees more engaged, strengthen their relationship with the university as well as it will make employees more motivated and loyal to the organization.

Implications of the study

Theoretical implications.

This study can contribute to the existing literature in employees motivation, their engagement at work and effective human resource management and identifies the ways to satisfy/motivate these employees’ to increase organizational performance. Basically my findings are aligned with those of other scholar’s works relating to this topic and are important to show/provide interesting and recent perhaps promising areas to work on under the recent world.

Practical implications

The actual result of the paper also provide recommendations for public organizations on how to be more competitive through managing their employees, motivating them and also through resilience and renewal different human resource management strategies, and the researcher has also gave relevant recommendations for policymakers and other concerned bodies as shown in above.

Suggestion for future study

The research was conducted from employees’ perspective only by using employees’ engagement. It should be interesting to consider from the perspective of managers by using managers engagement.

The researcher conducted more of quantitative study; deep qualitative study could also be adopted to validate the results of this study. Employees of government organizations and none government organizations may motivate indifferent way, hence it should also be interesting to study from perspective of employees of government organizations.

From the findings of the study it is concluded that the model which included intrinsic motivation (IM) and extrinsic motivation (EM) explained only 25.2% of the variance of employee engagement the rest 74.8% may be due to the other variables which were not included in this study and left for further study.

Availability of data and materials

Not applicable.

Abbreviations

Statistical package for social science

Analysis of variance

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Engidaw, A.E. The effect of motivation on employee engagement in public sectors: in the case of North Wollo zone. J Innov Entrep 10 , 43 (2021). https://doi.org/10.1186/s13731-021-00185-1

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  • Published: 04 September 2021

Employee motivation and job performance: a study of basic school teachers in Ghana

  • Joseph Ato Forson   ORCID: orcid.org/0000-0002-5997-5713 1 ,
  • Eric Ofosu-Dwamena 2 ,
  • Rosemary Afrakomah Opoku 3 &
  • Samuel Evergreen Adjavon   ORCID: orcid.org/0000-0002-2713-3327 4  

Future Business Journal volume  7 , Article number:  30 ( 2021 ) Cite this article

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Motivation as a meaningful construct is a desire to satisfy a certain want and is a central pillar at the workplace. Thus, motivating employees adequately is a challenge as it has what it takes to define employee satisfaction at the workplace. In this study, we examine the relationship between job motivation factors and performance among teachers of basic schools in Ghana. The study employs a quantitative approach on a sample of 254 teachers from a population of 678 in the Effutu Municipality of Ghana, of which 159 questionnaires were duly answered and returned (representing 62.6% return rate). Using multiple regression and ANOVA, the study finds compensation package, job design and environment and performance management system as significant factors in determining teacher’s motivation in the municipality. Thus, these motivation factors were significant predictors on performance when regressed at a decomposed and aggregated levels. These findings support the self-determination theory, more specifically on the explanations advanced under the controlled and autonomous motivation factors. Significant differences were also observed in teachers’ performance among one of the age cohorts. The study urges the municipal directorate of education to make more room for young teacher trainees and interns who are at the formative stage of their careers to be engaged to augment the experienced staff strength. More should be done to make the profession attain some level of autonomy in the discharge of duty to breed the next genre of innovative educators in the municipality.

Introduction

Motivation as a meaningful construct is a central pillar at the workplace. Thus, motivating employees adequately is a challenge as it has what it takes to define employee satisfaction at the workplace. Quite a number of studies have been devoted to the link between motivation and its constituent factors and employee performance in different organizations [ 7 , 46 ]. Our study draws inspiration from the self-determination theory (SDT) advanced by Deci et al. [ 14 ] as a framework that can be applied to teachers motivation and performance in basic schools in Ghana. It is worth noting that SDT differentiates between controlled motivation and autonomous motivation. The latter is evident when individuals are faced with pressure and control. The former on the other hand emphasizes on the volitional nature of the behavior of individuals. The SDT provides evidence that suggests that motivation fuels performance [ 14 , 57 ].

In Ghana, the subject of motivation has always been at the apex of national agenda and is evident in the number of strike actions in the public service. In the early part of the 2000s, teachers were part of the public servants whose agitation for improved condition of service did not go unnoticed. Forson and Opoku [ 16 ] had stated that teachers’ emolument accounted for less than 35% of the public service wage bill although teachers were perceived to be in the majority in terms of numbers. This phenomenon did spark a wave of attrition of trained teachers to other sectors of the Ghanaian economy. The teaching profession as a matter of fact became a launched pad for the youth. It should be said that the nature of the school setting is basically a function of internal management and leadership. The head teacher or director of education as the Chief Executive needs to appreciate and recognize that results can be obtained through people. In today’s world, organizations are concerned with what should be done to achieve sustained high level of performance through people who are innovative thinkers [ 4 , 17 , 41 ]. These include paying more attention to how individuals can best be motivated and provision of an atmosphere that helps individuals to deliver on their mandates in accordance with the expectations of management [ 25 ]. This means that an educational manager or an individual engaged as a teacher cannot do this job without knowing what motivates people. The building of motivating factors into organizational roles and the entire process of leading people should be contingent on knowledge of motivation. Koontz and Weinrich [ 25 ] agree that the educational managers’ job is not to manipulate people but rather to recognize what motivates people.

A national debate ensued on the significant role played by teachers in nation building and the need to address the shortfall in the condition of service of teachers to motivate them to perform. Wider consultative meetings were held with stakeholders in the teaching fraternity and the outcome and the panacea was the introduction of a uniform pay structure based on qualification. The legislative arm of government passed Act 737 in 2007 that saw the birth of the Fair Wages Salary Commission (FWSC). The mandate of the commission was to ensure a fair and systematic implementation of government pay policy [ 18 ]. Although this has stabilized the teaching profession in terms of the level of attrition, concerns on how this inducement translate into teacher’s performance seem to dominate national discourse especially in the face of fallen standard of education in Ghana. Such concerns have raised questions such as the following: (1) Does pay rise correlate with performance? (2) Are there other factors that ought to be considered in the nexus between motivation and performance? (3) Are there any significant differences in the level of performance among various age cohorts (4) Do educational background motivate teachers to perform better? These and other questions are addressed in this study.

The objective of this paper is to examine the link between job motivation factors and performance among basic school teachers in Ghana. This is against the backdrop that teachers have for some time now complained about condition of service and with the passage of FWSC bill, one would have thought that would have impacted on performance of teachers as it has been proven that motivation leads to satisfaction and ultimately to high performance. The standard of education continues to be a major concern in the educational setup of Ghana.

We organize the paper as follows: section one is the introduction that sets the tone for the paper. The problem is defined in this section, and the necessary questions that warrant redress are asked. We continue with a brief literature review on the concept of motivation, leading to the development of a conceptual framework and hypothesis based on the self-determination theory (SDT). Section two focuses on the method deployed, with emphasis on the aim, design and setting of the study. The theoretical equation for the multiple regression is brought to the fore here. Section three is the results and discussion, and section four concludes with policy implications.

The concept of motivation and self-determination theory (SDT)

Maslow [ 33 ] is credited for being part of the early contributors of human motivation concept. Maslow classifies human needs that motivate them into two: (1) homeostasis and (2) finding that appetites (preferential choices among foods). The former refers to the body’s automatic efforts to maintain a constant, normal state of the blood stream. The latter concept, on the other hand, is of the view that if the body lacks some chemical, the individual will tend (in an imperfect way) to develop a specific appetite or partial hunger for that missing food element. Thus, Maslow was of the view that any of the physiological needs and the consummatory behavior involved with them serve as channels for all sorts of other needs. Relating this assertion to teachers and the need for a salary pay rise, it should be pointed out that a person who thinks he is hungry may actually be seeking more for comfort, or dependence and managers in the educational sector ought to know this. Contemporary researches have expanded on the theory of motivation as advanced by Maslow [ 33 , 34 ]. For an organization to thrive and be efficient, certain conditions ought to be available in order for managers to get the best out of its human resources (workers/employees). Employees of an organization are the greatest asset in a dynamic and competitive environment [ 49 ]. In the words of Martin [ 32 ], if an organization wants to be effective and aims to sustain the success for a longer period of time, it is important for it to have a motivated workforce made up of employees ready to learn. The last three decades have witnessed an avalanche of studies that emphasizes on the point that employee motivation is essential for the success of a business [ 2 ].

In exploring further on this connection, Mifflin [ 35 ] delved into the fundamental meaning of the word “motivation” and pointed out that it is a Latin word which means to move. Therefore, it is near impossible to move peoples’ behavior in an organization unless such move is triggered by certain incentives. Robins and Coulter [ 49 ] explained the term motivation as the desire and willingness to exert high level of inspiration to reach organizational goals, conditioned by the efforts ability to satisfy some individual need. In this study, we define motivation simply as the act of moving people triggered by the provision of some incentives to achieve a desired goal.

In the words of Deci and Ryan [ 13 ], the SDT focuses on human beings inherent desire to bring change and progress as they advance to their fullest potential. Several studies have applied the SDT in various research areas that includes education, medicine and other organizational context. The SDT is of the view that individuals are by nature active entities who will do everything possible to be integrated into the wider social environment in an attempt to be responsive to the behavior consistent with existing self. The theory according to Trépanier et al. [ 57 ] defines social context as the workplace which facilitate or frustrate ones striving toward self-determination.

The SDT theory has two major forms of motivation which may be differentiated on the basis of its nature and quality according to Howard et al. [ 22 ]. When employees engage in interesting activities or in pursuance of their needs, such a form of motivation is ascribed as autonomous motivation. Such a form of motivation facilitates employees’ vitality and energy including satisfaction and well-being [ 14 ]. When employees engage in activities out of pressure as a result of external factors such as attaining rewards including threat of being punished, or even endogenous sources of such pressure as maintaining self-esteem, want of approval, image management or avoiding guilt, such a form of motivation can be ascribed as controlled motivation. Gillet et al. [ 20 ] explain that people with controlled motivational behavior do so out of reason as long as these contingencies exist and thus it predicts maladaptive work outcomes (e.g., exhaustion of personal energy) and turnover intentions.

SDT and job performance

According to Motowildo et al. [ 38 ], job performance is a construct that elicits behavior related to achievement with evaluative components. Most studies on this relationship have emphasized on the role of autonomous and intrinsic motivation on performance with the argument that individuals autonomously motivated have certain inherent values and behaviors and thus give off optimal performance. The theory of self-determination explains that autonomous motivation should be the necessary ingredient for better performance. That is, when individuals are better informed about the purpose of their job and have a sense of ownership and the degree of freedom to operate (autonomy), the possibility of they performing better at work may be high. The source of such motivation according to Deci et al. [ 14 ] may be from one’s interest and values. It is purpose-driven, amplifies energy, enjoyable and provides enough rationalization for tasks to be accomplished effectively. Moreover, the intrinsic component of autonomous motivation has been linked with job performance in related literature and types of performance [ 7 ].

Empirically, there are evidence to suggest that autonomous motivation is linked with performance. Evidence pertaining to controlled motivation is less dispositive. Proponents of the SDT have argued that controlled motivation (e.g., performance management systems) could reduce employee functioning because action derived from personal values and interest may be disconnected, therefore leading to negative effects on performance [ 48 ]. Counter argument posits that controlled motivation may foster employee willingness to complete tasks in an attempt to avoid guilt or punishment or to earn external reward which may come in the form of compensation package [ 27 ]. In this study, we focus on both the controlled and autonomous motivational factors. More specifically, we focus on Herzberg et al. [ 21 ] motivators validated by Harvard Business Review in 2003 which were made up of two motivators: (1) intrinsic factors such as achievement, recognition for achievement, the work itself, growth, responsibility and advancement, and (2) extrinsic factors such as supervision, working conditions, payment, interpersonal relationship, appreciation and company policy. Therefore, the bundle of motivators used in this study are similar to the aforementioned ones and may include performance management systems, external rewards that come in the form of compensation packages, job environment and training and development [ 30 ]. We explain these constructs further with the empirical evidence leading to the development of the conceptual framework.

  • Compensation package

Rasheed et al. [ 44 ] posit that package of compensation offered to teachers in institutions of higher learning has to be made based on several factors that may include the experience that underpins the abilities of the teacher, qualifications and perhaps market rates. This is supported by Bohlander et al. [ 6 ] who argued that teachers compensation ought to be the most central concern for managers and administrators of schools in stimulating them. Most of these research studies are premised on the fact that compensation should be designed to meet the needs of teachers and has be fashioned in the form of tangible rewards. In corroborating this assertion, Marlow et al. [ 31 ] observed that low condition of service defined by salary creates stress among teachers in schools. Thus, teachers’ condition of service should be market competitive in order to get higher motivation and to maintain them. Other studies have found that salary levels have been the main challenge for education managers and are the reason for the high attrition and that education planners and managers should pay attention to the design of compensation packages.

Job design and working environment

The needs of teachers on the job ought to be planned properly. The workload on teachers should not be such that it will de-motivate [ 44 ], p. 103. Teachers at all levels should have a learning environment, and educational administrators should make a point to treat existing human resource (teachers) with maximum respect devoid of any discrimination.

Nowadays, job design is the central focus of managers and human resource researchers. Thus, a well-designed job has what it takes in getting interest of employees. On the contrary, poorly designed job breeds boredom among employees. Davidson [ 12 ] makes an important observation and remarked in his research that when teachers are overloaded and burdened with so many non-teaching activities, it portends as a hindrance in the job design. Other scholars such as Clarke and Keating [ 9 ] have argued that the working environment of an educational institution affects teachers’ motivation. Clarke and Keating [ 9 ] found students to be the main reason why teachers are motivated in schools. His emphasis was on talented and hardworking students who boost the morale of teachers. Students who do not produce the desired results, on the other hand, de-motivate teachers. Moreover, class size is another important consideration in motivating teachers. Other variants of the job design and environment are captured in Ofoegbu [ 39 ] research in which he argued that institutions provide support in the form of resources to the teachers in the form of computers with Internet connections. Moreover, other factors such as the provision of e-libraries and research equipment, and other logistics for students may also serve as an effective motivator for teachers.

Performance management system

Management of teachers and educational administrators in all levels of education should focus on implementing basic performance management systems to continually appraise teachers’ accomplishments. For instance, the use of a so-called 360-degree feedback system is important where students’ feedback is attended to with the attention it deserves.

Stafyarakis [ 53 ] corroborated this and asserted that ‘Annual Confidential Reports’ have become obsolete. Yet there has been an emergence of a scientific approach on the field of performance management as time goes on. In discussing this further, Milliman [ 37 ] is of the view that although there are many practices available in this field, but a performance management system based on 360-degree feedback approach is the most effective.

Contrary to the norm that teachers are most motivated by the intrinsic factors and least motivated by the monetary aspects of teaching, Rao [ 43 ] demonstrates that poor appraisal systems, lack of recognition and lack of respect from the head and other co-workers are some common reasons of distress and de-motivation among teachers in educational institutions. The lack of recognition from supervisors is one of the many reasons why teachers would want to leave the teaching profession Stafyarakis [ 53 ].

Moreover, Rasheed et al. [ 45 ] points out that teachers are much concerned about students’ feedback; hence, feedback from the students should be given a proper weightage and in appraising and managing teachers’ performance in the institutions of higher education. Jordan [ 23 ] stressed that the feedback of students is a major issue of that motivates teachers and therefore teachers should be given feedback from their students in scientific manners.

Training and development

It is of significance that educational administrators focus on training activities as an essential means of both motivating employees and sustaining the survival of that organization according to Photanan [ 42 ] and Bohlander et al. [ 6 ]. Leslie [ 28 ] identified professional growth as basic motivator for teachers. He stressed that the professional learning platform available to a teacher is the basic path of his/her career development [ 29 ].

Conceptual framework and hypothesis development

In this section, the study harmonizes the components of the SDT theory into a conceptual framework on motivation and performance connection. The framework developed in this research may be useful as a guide by academicians and practitioners in understanding the mechanisms through which motivational factors affect job performance among teachers in the Effutu Municipality of Ghana. On elucidating on what a framework is, Chinn and Kramer [ 8 ] explained that a framework can be seen as a complex mental formulation of experience. Further clarification was given to distinguish conceptual framework from a theoretical framework. They assert that while theoretical framework is the theory on which the study is based, the conceptual framework deals with the operationalization of the theory. Put in another way, it represents the position of the researcher on the problem at hand and at the same time gives direction to the study. It may be entirely new, or an adoption of, or adaptation of, a model used in previous research with modification to fit the context of the inquiry [ 8 ].

The framework developed in this research has three components: the first component looks at the factors necessary to induce motivation among teachers. The second component focuses on motivation as a concept. The last component which is on job performance looks at the link between the aggregate motivational factors and performance. The extant literature survey on motivational factors and performance provides all the necessary ingredients for the construction of the framework. First, the extant literature shows that motivation as a concept is simply the act of moving people triggered by the provision of some incentives to achieve a desired goal. The triggers of motivation may include such factors such as compensation packages, job design and working environment, performance management system and training and development which are controlled and autonomous factors as crucial elements for motivation.

The second component of the framework is the aggregate motivation, which is the interaction of the controlled and autonomous factors of motivation. Motivation according to Reeve (2001) refers to the excitement level, the determination and the way a person works hard at his work setting. Ricks et al. [ 47 ] explicating on the thesis of motivation was of the view that motivation is an internal aspiration of a man that compels him to reach an objective or the goal set for him.

The third component of the framework is performance. According to Culture IQ [ 11 ] and Motowildo et al. [ 38 ], job performance is the assessment of whether an employee has done their job well. It is an individual evaluation (one measured based on a single person’s effort). In the words of Viswesvaran and Ones [ 58 ], p. 216, the term job performance is used in reference to actions that are scalable, behavior and outcomes that employees engage in or bring about that are linked with and contribute to the goals of an organization. It is linked to both employee- and organizational-level outcomes. A distinctive feature of the framework developed in this research is that it shows the interaction between autonomous and controlled factors and motivation and how it affects the performance of teachers in Fig.  1 .

figure 1

Source : Created by the authors

A Conceptual model of the relationship between Motivation and Teachers’ Performance.

It can be visibly seen from the framework that teachers motivation may be defined by both controlled and intrinsic motivational factors that may include those that fall under compensation packages, working environment, performance management system and training and development of teachers [ 44 ]. Yet the performance of teachers in itself motivates management and policy makers to institute compensation packages, improved psychological aura through enhanced working environment and job design and implementing appropriate performance management policy for a continued performance enhancement. It should also be emphasized here that these job satisfaction factors may pass as job motivational factors and theorize that a highly motivated teacher may be related to the level of satisfaction.

Scholars such as Thus Milda et al. [ 36 ] and Spector [ 52 ] collectively share the opinion that teachers differ from typical employees in various ways. Therefore, instruments that usually measure such job satisfaction and motivation dimensions as appreciation, communication, coworkers, fringe benefits, job conditions, nature of work, organization itself, organizations’ policies and procedures, pay, personal growth, promotion opportunities, recognition, security, supervision may not always match with teachers’ motivation aspects on the teaching field. However, some of these factors according to some researchers can be used in understanding motivation and performance among teachers. The consensus on these dimensions is especially on supervision, work itself, promotion and recognition being important dimensions of teachers’ motivation at work [ 50 , 51 , 56 ]. In addition, several researchers have used the same measurement or dimension but with different wording (synonym). For instance, Kreitner and Kinici [ 26 ] define job satisfaction with the synonym “motivation” which they argue contains “those psychological processes that cause the arousal, direction and persistence of voluntary actions that are goal directed” Motivation depends on certain intrinsic, as well as extrinsic factors which in collaboration results in fully committed employees. Based on this relationship, we hypothesize that:

Hypothesis 1

Teachers’ compensation package, job environment and design, performance management systems, training and development significantly affect teachers’ motivation.

In a similar manner, Board [ 5 ] asserted that tangible incentives are effective in increasing performance for task not done before, to encourage “thinking smarter” and to support both quality and quantity to achieve goals. Incentives, rewards and recognitions are the prime factors that impact on employee motivation. Aarabi et al. [ 1 ] confirmed this assertion by making use of factors such as payment, job security, promotion, freedom, friendly environment, and training and employee job performance to measure the term organizational motivation with positive relationship found on these factors. On rewards (which comes in various forms, e.g., income/pay, bonus, fringe benefits among others ) and recognition/appreciation, according to other researchers keep high spirit among employees which boost employee’s morale which may have a direct impact on performance and output. The study hypothesizes that:

Hypothesis 2

Teacher’s motivation positively affects their performance.

The aim, design and setting of the study

The paper aims to examine the link between motivation factors and performance among basic school teachers in Ghana. Data for this study were collected from primary. Primary data were sourced from the field of study through questionnaire administration. The researchers sought for permission from the municipal directorate of education to engage with teachers within the municipality. A written permission was granted, and questionnaires were administered to all basic schools’ teachers in the municipality.

At the preparatory stage, the questionnaires designed were tested to make sure participants understood the demands of the questions in the questionnaires. Informal interviews method has been adopted to make sure that additional information that could not have been gathered through the use of questionnaires was captured. The formal interviews using questionnaires ensured that we stayed focused on the background objective that formed the basis of the study.

Sampling technique and data analysis

On the determination of the sample size, different authors have differing views, but in most cases, the recommendation is that it should be large. Stevens [ 54 ] recommends at least 15 participants per predictor for reliable equation in the case of factor analysis. Tabachnick and Fidel [ 55 ] provides a formula for calculating sample size requirements, taking into consideration the number of independent variables that one wish to use: N  > 50 + 8  m (where m  = number of independent variables). In line with these and other requirements like Yamane [ 60 ], the exact sample size will be determined and questionnaires distributed accordingly to the selected public and private schools in the Effutu Municipality.

The human resource unit of the educational directorate of education in the municipality has indicated that there are over 678 teachers teaching at various levels in the municipality [ 15 ]. Thus, the 678 teachers become the population in the municipality. Using Yamane [ 60 ] and validating with other sampling size technique, a sample size of 254 has been adopted with a 0.5 level of precision. Thus, 254 questionnaires were distributed among the various schools, but 159 were filled and returned (representing 62.6% return rate).

Quantitative data are analyzed by means of a software called Statistical Package for Social Sciences (SPSS version 20). This is necessitated by the fact that the analyzed quantitative data ought to be presented by graphs to give quick visual impression of what it entails.

The scale measurement of the questionnaires included nominal scale, ordinal and intervals. Questionnaires used were segmented to capture the demographic characteristics of the respondents and the constructs that feeds into the multi-level latent variables using a five-point Likert scale (see [ 19 , 24 ]). A verification was done to assess the suitability of the data for factor analysis with the expectation that Kaiser–Meyer–Olkin Measure of Sampling Adequacy ( \({\mathrm{i.e}}., {\rm KMo}\ge 0.6)\) and Bartlett’s Test of Sphericity value are significant ( p  = 0.05), which was the case for our sample data. In measuring some of the latent variables, the study developed a 9-scale item on compensation package with the following loadings (e.g., how high is your qualification and pay ( \(\alpha =0.72)\) , “is your experience linked to your current pay?” ( \(\alpha =0.80)\) , “are you satisfied with the market premium” ( \(\alpha =0.75)\) etc.). All items were rated on a five-point Likert scale ranging from 1 = “not important” to 5 = “very important.” A confirmatory factor analysis (CFA) indicates that the hypothesized correlated 3-factor structure fits well with the responds of the participants ( \({\chi }^{2}/df = 2.01, {\rm RMR}=0.05,{\rm RMSEA}=0.06,{\rm TLC}=0.94,{\rm CFI}=0.94)\) .

Job design and working environment was measured by a 7-item scale based on questions such as “how do you perceive your workload” ( \(\alpha =0.88)\) , “does your work type offer learning environment?” ( \(\alpha =0.83),\) “Are you inspired by your working environment?” ( \(\alpha =0.87)\) , “Talented student boost morale” ( \(\alpha =0.84)\) etc. Similarly, all items were rated on a five-point Likert scale ranging from 1 = “not important” to 5 = “very important.” A confirmatory factor analysis reveals that the hypothesized one-factor structure fits well with the data ( \({\chi }^{2}/df = 3.06, {\rm RMR}=0.05,{\rm RMSEA}=0.06,{\rm TLC}=0.94,{\rm CFI}=0.94)\) .

Performance management system was assessed using a 9-item scale based on these inferences (e.g., “number of times supervisor visits” ( \(\alpha =0.69)\) , “how often are you visited by the municipal director of education” ( \(\alpha =0.78)\) , “work recognition” ( \(\alpha =0.72)\) , etc.). All constructs were rated as 1 = “not important” to 5 = “very important.” A confirmatory factor analysis reveals that the hypothesized two-factor structure was in line with the data ( \({\chi }^{2}/df=2.86, {\rm RMR}=0.05,{\rm RMSEA}=0.06,{\rm TLC}=0.94,{\rm CFI}=0.94)\) .

The last but not the least concept explored was job performance. It was assessed on a 12-item scale based on the inferences such as (e.g., “are pupils treated with respect?” ( \(\alpha\) =0.77), “do you help pupils work on their social-emotional skills?” ( \(\alpha\) = 0.69), “are you fair and consistent with pupils” ( \(\alpha\) = 0.87), etc.). All items were rated on a five-point Likert scale ranging from 1 = “not important” to 5 = “very important.” A confirmatory factor analysis reveals that the hypothesized two-factor structure was in line with the data ( \({\chi }^{2}/df = 2.06, {\rm RMR} = 0.05,{\rm RMSEA} = 0.06,{\rm TLC} = 0.94,{\rm CFI} = 0.93)\) . The study proceeds to make use of the proposed measurement models to assess the relationship outlined in the conceptual model in Fig.  1 .

Hypothesized theoretical equation

Based on the conceptual model in Fig.  1 , the study makes a number of hypothesis on the relation between motivational factors and motivation itself and subsequently the link between motivation and performance. Consequently, the study model leads to two structural equations as presented below:

where JM = job motivation, CP = compensation package, JDWE = job design and working environment, PMS = performance management system, TD = training and development, JP = job performance.

Results and discussion

The study begins with a frequency distribution and descriptive statistics to capture the responses of teachers regarding the itemized construct identified in the conceptual model. Beginning with these two is borne out of the fact that the data category used in the study included categorical, ordinal and nominal variables which may be difficult to have a summary descriptive statistic.

With the understanding that every statistical approach is guided by certain principles or in most cases what has come to be known as assumptions, a diagnostic check was undertaken. Multicollinearity and singularity, for instance, look at the relationship among the independent variables. Thus, multicollinearity exists when the independent variables are highly correlated (r = 0.5 and above). The study was particular about these assumptions because multiple regression abhors them (singularity and multicollinearity). Issues concerning outliers (i.e., very high and low scores) was dealt with given the fact that multiple regression is sensitive to them. On normality, the results of the Kolmogorov–Smirnov statics were used to assess the distribution of scores. The test result was insignificant (i.e., sig. value of more than 0.05), which pointed to normality. Having done these, the study was sure there were no errors in the data and that the descriptive phase of the data used can begin.

Consistent with the general distribution of gender in the demographic characteristics of Ghana, about 63 of the teachers were female (39.6%) with 59.1% made up of male and 1.3% being transgender. The transgender teachers were foreign teachers who were here on an exchange program. Most of the teachers in the sample taught at the primary level (46.5%), followed by junior high level (43.4%) and kindergarten (8.8%), respectively. About 34.6% of the respondent responded they have taught between 6 and 10 years and 22.0% had spent between 11 and 20 years teaching. In terms of educational background, about 50.3% of the respondent have had first degree, with the remaining 49.7% being holders of teachers Cert. A or Diploma from the training colleges, and master’s degree of the returned samples. The average number of years participants have taught was observed to be 2.34 years with a corresponding standard deviation of 1.010. We present the demographic characteristics of our participants in Table 1 .

As shown in Table 2 , the compensation package scale has good internal consistency, with a Cronbach alpha coefficient reported to be around 0.725. According to Pallant [ 40 ], Cronbach alpha values above 0.7 are considered acceptable; however, values above 0.8 are preferable. Therefore, the threshold value of 0.725 means our scale is internally consistent and acceptable. Similarly, the job design and working environment scale recorded a Cronbach alpha coefficient of 0.793.

Performance management on the other hand had a Cronbach alpha coefficient of 0.70, yet training and development recorded a lower Cronbach alpha of 0.53, which meant it lacked internal consistency. The study had to drop training and development as factor for job motivation and proceed with the others. Job performance, however conspicuously recorded a Cronbach alpha of 0.83. In terms of the output from the correlation matrix, it can be visibly seen that the scales computed were not highly correlated and fallen below the threshold of 0.8 as recommended (see [ 40 ], p. 56). Both the assumption of singularity and multicollinearity by extension have not been violated (see Durbin Watson results) and thus the study can proceed to run the regression as per the set objectives and the conceptual model.

We go further to examine the causal effect of the factors identified as triggers of motivation on teachers’ level of motivation using ordinary least square method with multiple regression as the exact approach. Having gained credence from the test of reliability and validity, examining the causal effect becomes imperative. Using the baseline model in Eq. ( 1 ), the study concurrently runs the regression with the output shown in Tables 2 , 3 and 4 .

In model one, the study regresses compensation package with the dependent variable without controlling for other related factors. By implication what the results in model (1) seeks to explain is that, as the value of compensation package for teachers increases by 73 percentage points in the municipality, the mean of job motivation increases by that same margin. The high compensation is evidenced by government of Ghana reform in salary structure and bolstered by the effort of the Member of Parliament (MP) through the sharing of teaching and learning materials (TLMs) in the municipality. By this gesture by the MP, teachers feel appreciated and derive high motivation. Moreover, the presence of a university (University of Education, Winneba) has helped to deepen the level of motivation. The model has cross-variable variance of 52 percentage and with close to about 48 percentage unexplained as inferred from the coefficients of both coefficient of determination ( R 2 ) and adjusted coefficient of determination. Generally, the model is jointly significant ( F  = 170, p  < 0.01) with a corresponding tolerance and variable inflationary factor (VIF) of 1.

In model (2), the study varies the variables used with the inclusion of job design and working environment to examine how well the model can be through it cross-variable variance. Controlling for job design and environment shows a significant drop in the coefficient of compensation package from 0.73 to 0.53 although highly significant. Job design and environment recorded a coefficient of 0.49 which meant this indicator increases teachers’ satisfaction and thus motivation by 49 percentage points. In explaining this phenomenon, one would say that jobs that are rich in positive behavioral essentials such as autonomy, task significance and identity and feedback contribute to employees’ motivation. Government has since the introduction of its flagship program on free senior high education emphasized the significance of education across all the strata. The autonomy of heads of unit was by this directive curtailed. Heads of unit were barred from initiating policies to ease their operations. This finding is supported in the literature [ 7 , 30 , 46 ] and is aligned with the SDT. For example, head teachers who had levied pupils with printing fees were sanctioned for such initiative. Thus, by this gesture, the autonomy of the profession was in doubt and this explains why the level of motivation when this parameter is mentioned is low. With this addition, model (2) marginally sees an improvement of 0.73 in the cross-variable variance which is a significant. Model (2) was jointly significant ( F  = 170, p  < 0.01).

All the identified job motivation variables are concurrently used in model (3) to infer whether there was going to be a significant increase in the coefficient of determination and a drop in the residue. As a confirmation to the priori assumption, there was a marginal improvement of the explanatory strength of the model (R 2  = 0.88). However, the model witnessed significant drop in the coefficients. Thus, compensation package dropped further from 0.53 to 0.42 and job design and environment from 0.49 to 0.34.

It is important to note that the value of Durbin Watson test results when all the identified factors are brought together in model (3) indicate a no autocorrelation in the model which validates the earlier point of having dealt with critical assumptions that borders on autocorrelation. Moreover, both our VIF and tolerance were within the acceptable level. For instance, models (1)–(3) had a VIF score less than or equal to 1, which meant there were no issues concerning a possibility of high multicollinearity. For tolerance, there are no clear-cut cut-off point, but there is a suggestion of a tolerance greater than 0.40 according to Allison [ 3 ]. Yet Weisburd and Britt [ 59 ] are of the view that anything below 0.2 is an indication of serious multicollinearity. Inferring from these, it therefore goes to suggest that the tolerance levels of above 1 meant no multicollinearity.

In examining the relationship between the aggregated motivational factors and performance, the study brings to the fore the following findings as shown in Table 3 . The study presents four (4) different models on the relationship between motivation and performance. Model (1) regresses the aggregate motivational factors on job performance, and the findings are quite interesting to note. The job performance indicator is increased by 46% for every unit increase in motivation. This relationship can further be explained to mean a teacher within the municipality with a sense of satisfaction with his/her teaching job may feel more inclined to be at post no matter what the prevailing circumstances are. The snowball effect of this phenomenon is the reduction in absenteeism with a corresponding curb on teachers’ turnover. Although the coefficient of determination which explains the cross-variable variance is by far lower than expected ( R 2  = 0.214), the model is jointly significant ( F  = 41.44, p  < 0.01). The VIF and tolerance levels are within acceptable threshold with a Durbin Watson of 2.04 that signals a no concern of autocorrelation in the model.

Models (2)–(4) regress the decomposed job motivation factors on performance to ascertain their level of significance, and indeed, as theorized, these factors were positively significant except with lower coefficient of determinations ( R 2 ). To explain the relation in model (2), it is important to note that compensation is the output and the benefit that a teacher within the municipality receives in the form of pay, or even any form of exchanges (in kind or in cash) to increase performance. The Member of Parliament for the area as part of effort to ensure teachers are well compensated shared over 700 laptops to teachers within the municipality for effective teaching and learning. This certainly explains why the attrition rate in the municipality is low vis-à-vis high morale of teachers which largely explains the level of motivation and satisfaction.

Model (3) touches on the psychological state the teacher finds him or herself owed to the nature and state of the job. This may include the job environment and the degree of specialization. Yet in model (4), there is an exponential increase in the coefficient of performance management systems as it increases job performance within the municipality by 51 percentage point. It should be noted that performance management sets expectations for teachers’ performance and thus motivates them to work harder in ways expected by the municipal directorate of education under GES. The results in model (5) confirm earlier ones, but the inclusion of the other variables as control seems to have increased the coefficients of the various motivational factors. This partly explains the performance of the municipality in the central region in successive BECE.

Further investigation is made to understand which of the age groups is responsible for the ensuing level of performance in the municipality. To do this, the study relies on one-way analysis of variance (ANOVA). Here, the mean scores of more than two groups are compared using a continuous variable as the dependent variable. Having transformed the ordinal variables to continuous, it makes it quite straightforward to do this. Using the categorical independent variable of age which has more than three categories and the job performance variable which we have transformed to be continuous variable, the study undertakes a one-way between groups ANOVA with post hoc tests. Teachers were divided into four groups according to their ages (group 1: 20–30 yrs.; group 2: 31–40 yrs.; group 3: 41–50 yrs.; group 4: above 51 yrs.). There was a statistically significant difference at the \(p<0.10\) level in job performance scores for the four age groups: F (4, 159) = 0.042, p  = 0.10. Despite reaching statistical significance for one of the groups, the actual difference in mean scores between the groups was quite small. The effect size was calculated using eta squared (eta squared = 179.1/8513 = 0.02) which in Cohen’s ([ 10 ], pp. 248–7) terms is considered far too small a size. Note should be taking that Cohen categorizes 0.01 as a small effect, 0.06 as a medium effect and 0.14 as a large effect. Post hoc comparisons using the Tukey HSD test indicated that the mean score for group 1 (56.12, SD = 4.26) is significantly different from the other three groups which were insignificant. The result has theoretical soundness. Group 1 was made up of young teachers who had either returned from training colleges after completion or on internship and thus had cause to perform for a possibility of being retained or given a very good report since internship supervision forms part of the trainees’ assessment.

In this study, we examined among a host of autonomous and controlled motivational factors and their relationship to performance among basic schools’ teachers in the Effutu Municipality of Ghana. A conceptual model was developed with the necessary hypotheses formulated. Using multiple regression and one-way analysis of variance (ANOVA), the causal effect as shown in the model is tested.

The study finds compensation package, job design and environment and performance management system to be positively significant factors in explaining teacher’s motivation in the municipality. These job motivation factors were significant predictors on job performance. The aggregated job motivation indicator when regressed on job performance reveals a positive and significant effect. Based on the results from the ANOVA, the study recommends the municipal directorate of education to make more room for young teacher trainees who are at the formative stage of their career to be engaged to augment the experienced staff strength. More should be done to make the profession attain some level of autonomy in the discharge of duty to breed the next genre of innovative educators in the municipality. A limitation of the study is its inability to treat job motivation as a mediatory variable as captured in the framework. The study recommends future research to explore this connection.

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Abbreviations

Analysis of variance

Self-determination theory

Single spine salary structure

Fair wages salary commission

Teaching and learning materials

Member of parliament

Job motivation

Job performance

Kaiser–Meyer–Olkin

Confirmatory factor analysis

Standardized root mean square residual

Root mean square error of approximation

Statistical package for social science

Variable inflationary factor

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Acknowledgements

The authors would like to acknowledge the support of the Effutu Directorate of Education, particularly the Municipal Director of Education for the support during the data collection stage. We thank all the basic school teachers in the municipality who devoted time to fill and return questionnaires sent to them. We are also grateful to the Directorate for the secondary materials given to the team.

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Forson, J.A., Ofosu-Dwamena, E., Opoku, R.A. et al. Employee motivation and job performance: a study of basic school teachers in Ghana. Futur Bus J 7 , 30 (2021). https://doi.org/10.1186/s43093-021-00077-6

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Explaining research performance: investigating the importance of motivation

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In this article, we study the motivation and performance of researchers. More specifically, we investigate what motivates researchers across different research fields and countries and how this motivation influences their research performance. The basis for our study is a large-N survey of economists, cardiologists, and physicists in Denmark, Norway, Sweden, the Netherlands, and the UK. The analysis shows that researchers are primarily motivated by scientific curiosity and practical application and less so by career considerations. There are limited differences across fields and countries, suggesting that the mix of motivational aspects has a common academic core less influenced by disciplinary standards or different national environments. Linking motivational factors to research performance, through bibliometric data on publication productivity and citation impact, our data show that those driven by practical application aspects of motivation have a higher probability for high productivity. Being driven by career considerations also increases productivity but only to a certain extent before it starts having a detrimental effect.

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Introduction

Motivation and abilities are known to be as important factors in explaining employees’ job performance of employees (Van Iddekinge et al. 2018 ), and in the vast scientific literature on motivation, it is common to differentiate between intrinsic and extrinsic motivation factors (Ryan and Deci 2000 ). In this context, path-breaking individuals are said to often be intrinsically motivated (Jindal-Snape and Snape 2006 ; Thomas and Nedeva 2012 ; Vallerand et al. 1992 ), and it has been found that the importance of these of types of motivations differs across occupations and career stages (Duarte and Lopes 2018 ).

In this article, we address the issue of motivation for one specific occupation, namely: researchers working at universities. Specifically, we investigate what motivates researchers across fields and countries (RQ1) and how this motivation is linked to their research performance (RQ2). The question of why people are motivated to do their jobs is interesting to address in an academic context, where work is usually harder to control, and individuals tend to have a lot of much freedom in structuring their work. Moreover, there have been indications that academics possess an especially high level of motivation for their tasks that is not driven by a search for external rewards but by an intrinsic satisfaction from academic work (Evans and Meyer 2003 ; Leslie 2002 ). At the same time, elements of researchers’ performance are measurable through indicators of their publication activity: their productivity through the number of outputs they produce and the impact of their research through the number of citations their publications receive (Aksnes and Sivertsen 2019 ; Wilsdon et al. 2015 ).

Elevating research performance is high on the agenda of many research organisations (Hazelkorn 2015 ). How such performance may be linked to individuals’ motivational aspects has received little attention. Thus, a better understanding of this interrelation may be relevant for developing institutional strategies to foster environments that promote high-quality research and research productivity.

Previous qualitative research has shown that scientists are mainly intrinsically motivated (Jindal-Snape and Snape 2006 ). Other survey-based contributions suggest that there can be differences in motivations across disciplines (Atta-Owusu and Fitjar 2021 ; Lam 2011 ). Furthermore, the performance of individual scientists has been shown to be highly skewed in terms of publication productivity and citation rates (Larivière et al. 2010 ; Ruiz-Castillo and Costas 2014 ). There is a large body of literature explaining these differences. Some focus on national and institutional funding schemes (Hammarfelt and de Rijcke 2015 ; Melguizo and Strober 2007 ) and others on the research environment, such as the presence of research groups and international collaboration (Jeong et al. 2014 ), while many studies address the role of academic rank, age, and gender (see e.g. Baccini et al. 2014 ; Rørstad and Aksnes 2015 ). Until recently, less emphasis has been placed on the impact of researchers’ motivation. Some studies have found that different types of motivations drive high levels of research performance (see e.g. Horodnic and Zaiţ 2015 ; Ryan and Berbegal-Mirabent 2016 ). However, researchers are only starting to understand how this internal drive relates to research performance.

While some of the prior research on the impact of motivation depends on self-reported research performance evaluations (Ryan 2014 ), the present article combines survey responses with actual bibliometric data. To investigate variation in research motivation across scientific fields and countries, we draw on a large-N survey of economists, cardiologists, and physicists in Denmark, Norway, Sweden, the Netherlands, and the UK. To investigate how this motivation is linked to their research performance, we map the survey respondents’ publication and citation data from the Web of Science (WoS).

This article is organised as follows. First, we present relevant literature on research performance and motivation. Next, the scientific fields and countries are then presented before elaborating on our methodology. In the empirical analysis, we investigate variations in motivation across fields, gender, age, and academic position and then relate motivation to publications and citations as our two measures of research performance. In the concluding section, we discuss our findings and implications for national decision-makers and individual researchers.

Motivation and research performance

As noted above, the concepts of intrinsic and extrinsic motivation play an important role in the literature on motivation and performance. Here, intrinsic motivation refers to doing something for its inherent satisfaction rather than for some separable consequence. Extrinsic motivation refers to doing something because it leads to a separable outcome (Ryan and Deci 2000 ).

Some studies have found that scientists are mainly intrinsically motivated (Jindal-Snape and Snape 2006 ; Lounsbury et al. 2012 ). Research interests, curiosity, and a desire to contribute to new knowledge are examples of such motivational factors. Intrinsic motives have also been shown to be crucial when people select research as a career choice (Roach and Sauermann 2010 ). Nevertheless, scientists are also motivated by extrinsic factors. Several European countries have adopted performance-based research funding systems (Zacharewicz et al. 2019 ). In these systems, researchers do not receive direct financial bonuses when they publish, although such practices may occur at local levels (Stephan et al. 2017 ). Therefore, extrinsic motivation for such researchers may include salary increases, peer recognitions, promotion, or expanded access to research resources (Lam 2011 ). According to Tien and Blackburn ( 1996 ), both types of motivations operate simultaneously, and their importance vary and may depend on the individual’s circumstances, personal situation, and values.

The extent to which different kinds of motivations play a role in scientists’ performance has been investigated in several studies. In these studies, bibliometric indicators based on the number of publications are typically used as outcome measures. Such indicators play a critical role in various contexts in the research system (Wilsdon et al. 2015 ), although it has also been pointed out that individuals can have different motivations to publish (Hangel and Schmidt-Pfister 2017 ).

Based on a survey of Romanian economics and business administration academics combined with bibliometric data, Horodnic and Zait ( 2015 ) found that intrinsic motivation was positively correlated with research productivity, while extrinsic motivation was negatively correlated. Their interpretations of the results are that researchers motivated by scientific interest are more productive, while researchers motivated by extrinsic forces will shift their focus to more financially profitable activities. Similarly, based on the observation that professors continue to publish even after they have been promoted to full professor, Finkelstein ( 1984 ) concluded that intrinsic rather than extrinsic motivational factors have a decisive role regarding the productivity of academics.

Drawing on a survey of 405 research scientists working in biological, chemical, and biomedical research departments in UK universities, Ryan ( 2014 ) found that (self-reported) variations in research performance can be explained by instrumental motivation based on financial incentives and internal motivation based on the individual’s view of themselves (traits, competencies, and values). In the study, instrumental motivation was found to have a negative impact on research performance: As the desire for financial rewards increase, the level of research performance decreases. In other words, researchers mainly motivated by money will be less productive and effective in their research. Contrarily, internal motivation was found to have a positive impact on research performance. This was explained by highlighting that researchers motivated by their self-concept set internal standards that become a reference point that reinforces perceptions of competency in their environments.

Nevertheless, it has also been argued that intrinsic and extrinsic motivations for publishing are intertwined (Ma 2019 ). According to Tien and Blackburn ( 1996 ), research productivity is neither purely intrinsically nor purely extrinsically motivated. Publication activity is often a result of research, which may be intrinsically motivated or motivated by extrinsic factors such as a wish for promotion, where the number of publications is often a part of the assessment (Cruz-Castro and Sanz-Menendez 2021 ; Tien 2000 , 2008 ).

The negative relationship between external/instrumental motivation and performance and the positive relationship between internal/self-concept motivation and performance are underlined by Ryan and Berbegal-Mirabent ( 2016 ). Drawing on a fuzzy set qualitative comparative analysis of a random sampling of 300 of the original respondents from Ryan ( 2014 ), they find that scientists working towards the standards and values they identify with, combined with a lack of concern for instrumental rewards, contribute to higher levels of research performance.

Based on the above, this article will address two research questions concerning different forms of motivation and the relationship between motivation and research performance.

How does the motivation of researchers vary across fields and countries?

How do different types of motivations affect research performance?

In this study, the roles of three different motivational factors are analysed. These are scientific curiosity, practical and societal applications, and career progress. The study aims to assess the role of these specific motivational factors and not the intrinsic-extrinsic distinction more generally. Of the three factors, scientific curiosity most strongly relates to intrinsic motivation; practical and societal applications also entail strong intrinsic aspects. On the other hand, career progress is linked to extrinsic motivation.

In addition to variation in researchers’ motivations by field and country, we consider differences in relation to age, position and gender. Additionally, when investigating how motivation relates to scientific performance we control for the influence of age, gender, country and funding. These are dimensions where differences might be found in motivational factors given that scientific performance, particularly publication productivity, has been shown to differ along these dimensions (Rørstad and Aksnes 2015 ).

Research context: three fields, five countries

To address the research question about potential differences across fields and countries, the study is based on a sample consisting of researchers in three different fields (cardiology, economics, and physics) and five countries (Denmark, Norway, Sweden, the Netherlands, and the UK). Below, we describe this research context in greater detail.

The fields represent three different domains of science: medicine, social sciences, and the natural sciences, where different motivational factors may be at play. This means that the fields cover three main areas of scientific investigations: the understanding of the world, the functioning of the human body, and societies and their functions. The societal role and mission of the fields also differ. While a primary aim of cardiology research and practice is to reduce the burden of cardiovascular disease, physics research may drive technology advancements, which impacts society. Economics research may contribute to more effective use of limited resources and the management of people, businesses, markets, and governments. In addition, the fields also differ in publication patterns (Piro et al. 2013 ). The average number of publications per researcher is generally higher in cardiology and physics than in economics (Piro et al. 2013 ). Moreover, cardiologists and physicists mainly publish in international scientific journals (Moed 2005 ; Van Leeuwen 2013 ). In economics, researchers also tend to publish books, chapters, and articles in national languages, in addition to international journal articles (Aksnes and Sivertsen 2019 ; van Leeuwen et al. 2016 ).

We sampled the countries with a twofold aim. On the one hand, we wanted to have countries that are comparable so that differences in the development of the science systems, working conditions, or funding availability would not be too large. On the other hand, we also wanted to assure variation among the countries regarding these relevant framework conditions to ensure that our findings are not driven by a specific contextual condition.

The five countries in the study are all located in the northwestern part of Europe, with science systems that are foremost funded by block grant funding from the national governments (unlike, for example, the US, where research grants by national funding agencies are the most important funding mechanism) (Lepori et al. 2023 ).

In all five countries, the missions of the universities are composed of a blend of education, research, and outreach. Furthermore, the science systems in Norway, Denmark, Sweden, and the Netherlands have a relatively strong orientation towards the Anglo-Saxon world in the sense that publishing in the national language still exists, but publishing in English in internationally oriented journals in which English is the language of publications is the norm (Kulczycki et al. 2018 ). These framework conditions ensure that those working in the five countries have somewhat similar missions to fulfil in their professions while also belonging to a common mainly Anglophone science system.

However, in Norway, Denmark, Sweden, and the Netherlands, research findings in some social sciences, law, and the humanities are still oriented on publishing in various languages. Hence, we avoided selecting the humanities field for this study due to a potential issue with cross-country comparability (Sivertsen 2019 ; Sivertsen and Van Leeuwen 2014 ; Van Leeuwen 2013 ).

Finally, the chosen countries vary regarding their level of university autonomy. When combining the scores for organisational, financial, staffing, and academic autonomy presented in the latest University Autonomy in Europe Scorecard presented by the European University Association (EUA), the UK, the Netherlands, and Denmark have higher levels of autonomy compared to Norway and Sweden, with Swedish universities having less autonomy than their Norwegian counterparts (Pruvot et al. 2023 ). This variation is relevant for our study, as it ensures that our findings are not driven by response from a higher education system with especially high or low autonomy, which can influence the motivation and satisfaction of academics working in it (Daumiller et al. 2020 ).

Data and methods

The data used in this article are a combination of survey data and bibliometric data retrieved from the WoS. The WoS database was chosen for this study due to its comprehensive coverage of research literature across all disciplines, encompassing the three specific research areas under analysis. Additionally, the WoS database is well-suited for bibliometric analyses, offering citation counts essential for this study.

Two approaches were used to identify the sample for the survey. Initially, a bibliometric analysis of the WoS using journal categories (‘Cardiac & cardiovascular systems’, ‘Economics’, and ‘Physics’) enabled the identification of key institutions with a minimum number of publications within these journal categories. Following this, relevant organisational units and researchers within these units were identified through available information on the units’ webpages. Included were employees in relevant academic positions (tenured academic personnel, post-docs, and researchers, but not PhD students, adjunct positions, guest researchers, or administrative and technical personnel).

Second, based on the WoS data, people were added to this initial sample if they had a minimum number of publications within the field and belonged to any of the selected institutions, regardless of unit affiliation. For economics, the minimum was five publications within the selected period (2011–2016). For cardiology and physics, where the individual publication productivity is higher, the minimum was 10 publications within the same period. The selection of the minimum publication criteria was based on an analysis of publication outputs in these fields between 2011 and 2016. The thresholds were applied to include individuals who are more actively engaged in research while excluding those with more peripheral involvement. The higher thresholds for cardiology and physics reflect the greater frequency of publications (and co-authorship) observed in these fields.

The benefit of this dual-approach strategy to sampling is that we obtain a more comprehensive sample: the full scope of researchers within a unit and the full scope of researchers that publish within the relevant fields. Overall, 59% of the sample were identified through staff lists and 41% through the second step involving WoS data.

The survey data were collected through an online questionnaire first sent out in October 2017 and closed in December 2018. In this period, several reminders were sent to increase the response rate. Overall, the survey had a response rate of 26.1% ( N  = 2,587 replies). There were only minor variations in response rates between scientific fields; the variations were larger between countries. Tables  1 and 2 provide an overview of the response rate by country and field.

Operationalisation of motivation

Motivation was measured by a question in the survey asking respondents what motivates or inspires them to conduct research, of which three dimensions are analysed in the present paper. The two first answer categories were related to intrinsic motivation (‘Curiosity/scientific discovery/understanding the world’ and ‘Application/practical aims/creating a better society’). The third answer category was more related to extrinsic motivation (‘Progress in my career [e.g. tenure/permanent position, higher salary, more interesting/independent work]’). Appendix Table A1 displays the distribution of respondents and the mean value and standard deviation for each item.

These three different aspects of motivation do not measure the same phenomenon but seem to capture different aspects of motivation (see Pearson’s correlation coefficients in Appendix Table A2 ). There is no correlation between curiosity/scientific discovery, career progress, and practical application. However, there is a weak but significant positive correlation between career progress and practical application. These findings indicate that those motivated by career considerations to some degrees also are motivated by practical application.

In addition to investigating how researchers’ motivation varies by field and country, we consider the differences in relation to age, position and gender as well. Field of science differentiates between economics, cardiology, physics, and other fields. The country variables differentiate between the five countries. Age is a nine-category variable. The position variable differentiates between full professors, associate professors, and assistant professors. The gender variable has two categories (male or female). For descriptive statistics on these additional variables, see Appendix Table A3 .

Publication productivity and citation impact

To analyse the respondents’ bibliometric performance, the Centre for Science and Technology Studies (CWTS) in-house WoS database was used. We identified the publication output of each respondent during 2011–2017 (limited to regular articles, reviews, and letters). For 16% of the respondents, no publications were identified in the database. These individuals had apparently not published in international journals covered by the database. However, in some cases, the lack of publications may be due to identification problems (e.g. change of names). Therefore, we decided not to include the latter respondents in the analysis.

Two main performance measures were calculated: publication productivity and citation impact. As an indicator of productivity, we counted the number of publications for each individual (as author or co-author) during the period. To analyse the citation impact, a composite measure using three different indicators was used: total number of citations (total citations counts for all articles they have contributed to during the period, counting citations up to and including 2017), normalised citation score (MNCS), and proportion of publications among the 10% most cited articles in their fields (Waltman and Schreiber 2013 ). Here, the MNCS is an indicator for which the citation count of each article is normalised by subject, article type, and year, where 1.00 corresponds to the world average (Waltman et al. 2011 ). Based on these data, averages for the total publication output of each respondent were calculated. By using three different indicators, we can avoid biases or limitations attached to each of them. For example, using the MNCS, a respondent with only one publication would appear as a high impact researcher if this article was highly cited. However, when considering the additional indicator, total citation counts, this individual would usually perform less well.

The bibliometric scores were skewedly distributed among the respondents. Rather than using the absolute numbers, in this paper, we have classified the respondents into three groups according to their scores on the indicators. Here, we have used percentile rank classes (tertiles). Percentile statistics are increasingly applied in bibliometrics (Bornmann et al. 2013 ; Waltman and Schreiber 2013 ) due to the presence of outliers and long tails, which characterise both productivity and citation distributions.

As the fields analysed have different publication patterns, the respondents within each field were ranked according to their scores on the indicators, and their percentile rank was determined. For the productivity measure, this means that there are three groups that are equal in terms of number of individuals included: 1: Low productivity (the group with the lowest publication numbers, 0–33 percentile), 2: Medium productivity (33–67 percentile), and 3: High productivity (67–100 percentile). For the citation impact measure, we conducted a similar percentile analysis for each of the three composite indicators. Then everyone was assigned to one of the three percentile groups based on their average score: 1: Low citation impact (the group with lowest citation impact, 0–33 percentile), 2: Medium citation impact (33–67 percentile), and 3: High citation impact (67–100 percentile), cf. Table  3 . Although it might be argued that the application of tertile groups rather than absolute numbers leads to a loss of information, the advantage is that the results are not influenced by extreme values and may be easier to interpret.

Via this approach, we can analyse the two important dimensions of the respondents’ performance. However, it should be noted that the WoS database does not cover the publication output of the fields equally. Generally, physics and cardiology are very well covered, while the coverage of economics is somewhat lower due to different publication practices (Aksnes and Sivertsen 2019 ). This problem is accounted for in our study by ranking the respondents in each field separately, as described above. In addition, not all respondents may have been active researchers during the entire 2011–2017 period, which we have not adjusted for. Despite these limitations, the analysis provides interesting information on the bibliometric performance of the respondents at an aggregated level.

Regression analysis

To analyse the relationship between motivation and performance, we apply multinomial logistic regression rather then ordered logistic regression because we assume that the odds for respondents belonging in each category of the dependent variables are not equal (Hilbe 2017 ). The implication of this choice of model is that the model tests the probability of respondents being in one category compared to another (Hilbe 2017 ). This means that a reference or baseline category must be selected for each of the dependent variables (productivity and citation impact). Furthermore, the coefficient estimates show how the probability of being in one of the other categories decreases or increases compared to being in the reference category.

For this analysis, we selected the medium performers as the reference or baseline category for both our dependent variables. This enables us to evaluate how the independent variables affect the probability of being in the low performers group compared to the medium performers and the high performers compared to the medium performers.

To evaluate model fit, we started with a baseline model where only types of motivations were included as independent variables. Subsequently, the additional variables were introduced into the model, and based on measures for model fit (Pseudo R 2 , -2LL, and Akaike Information Criterion (AIC)), we concluded that the model with all additional variables included provides the best fit to the data for both the dependent variables (see Appendix Tables A5 and A6 ). Additional control variables include age, gender, country, and funding. We include these variables as controls to obtain robust effects of motivation and not effects driven by other underlying factors. The type of funding was measured by variables where the respondent answered the following question: ‘How has your research been funded the last five years?’ The funding variable initially consisted of four categories: ‘No source’, ‘Minor source’, ‘Moderate source’, and ‘Major source’. In this analysis, we have combined ‘No source’ and ‘Minor source’ into one category (0) and ‘Moderate source’ and ‘Major source’ into another category (1). Descriptive statistics for the funding variables are available in Appendix Table A4 . We do not control for the influence of field due to how the scientific performance variables are operationalised, the field normalisation implies that there are no variations across fields. We also do not control for position, as this variable is highly correlated with age, and we are therefore unable to include these two variables in the same model.

The motivation of researchers

In the empirical analysis, we first investigate variation in motivation and then relate it to publications and citations as our two measures of research performance.

As Fig.  1 shows, the respondents are mainly driven by curiosity and the wish to make scientific discoveries. This is by far the most important motivation. Practical application is also an important source of motivation, while making career progress is not identified as being very important.

figure 1

Motivation of researchers– percentage

As Table  4 shows, at the level of fields, there are no large differences, and the motivational profiles are relatively similar. However, physicists tend to view practical application as somewhat less important than cardiologists and economists. Moreover, career progress is emphasised most by economists. Furthermore, as table 5 shows, there are some differences in motivation between countries. For curiosity/scientific discovery and practical application, the variations across countries are minor, but researchers in Denmark tend to view career progress as somewhat more important than researchers in the other countries.

Furthermore, as table 6 shows, women seem to view practical application and career progress as a more important motivation than men; these differences are also significant. Similar gender disparities have also been reported in a previous study (Zhang et al. 2021 ).

There are also some differences in motivation across the additional variables worth mentioning, as Table  7 shows. Unsurprisingly, perhaps, there is a significant moderate negative correlation between age, position, and career progress. This means that the importance of career progress as a motivation seems to decrease with increased age or a move up the position hierarchy.

In the second part of the analysis, we relate motivation to research performance. We first investigate publications and productivity using the percentile groups. Here, we present the results we use using predicted probabilities because they are more easily interpretable than coefficient estimates. For the model with productivity percentile groups as the dependent variable, the estimates for career progress were negative when comparing the medium productivity group to the high productivity group and the medium productivity group to the low productivity group. This result indicates that the probability of being in the high and low productivity groups decreases compared to the medium productivity group as the value of career progress increases, which may point towards a curvilinear relationship between the variables. A similar pattern was also found in the model with the citation impact group as the dependent variable, although it was not as apparent.

As a result of this apparent curvilinear relationship, we included quadric terms for career progress in both models, and these were significant. Likelihood ratio tests also show that the models with quadric terms included have a significant better fit to the data. Furthermore, the AIC was also lower for these models compared to the initial models where quadric terms were not included (see Appendix Tables A5 – A7 ). Consequently, we base our results on these models, which can be found in Appendix Table A7 . Due to a low number of respondents in the low categories of the scientific curiosity/discovery variable, we also combined the first three values into one to include it as a variable in the regression analysis, which results in a reduced three-value variable for scientific curiosity/discovery.

Results– productivity percentile group

Using the productivity percentile group as the dependent variable, we find that the motivational aspects of practical application and career progress have a significant effect on the probability of being in the low, medium, or high productivity group but not curiosity/scientific discovery. In Figs.  2 and 3 , each line represents the probability of being in each group across the scale of each motivational aspect.

figure 2

Predicted probability for being in each of the productivity groups according to the value on the ‘practical application’ variable

figure 3

Predicted probability of being in the low and high productivity groups according to the value on the ‘progress in my career’ variable

Figure  2 shows that at low values of application, there are no significant differences between the probability of being in either of the groups. However, from around value 3 of application, the differences between the probability of being in each group increases, and these are also significant. As a result, we concluded that high scores on practical application is related to increased probability of being in the high productivity group.

In Fig.  3 , we excluded the medium productivity group from the figure because there are no significant differences between this group and the high and low productivity group. Nevertheless, we found significant differences between the low productivity and the high productivity group. Since we added a quadric term for career progress, the two lines in Fig.  3 have a curvilinear shape. Figure  3 shows that there are only significant differences between the probability of being in the low or high productivity group at mid and high values of career progress. In addition, the probability of being in the high productivity group is at its highest value at mid values of career progress. This indicates that being motivated by career progress increases the probability of being in the high productivity group but only up to a certain point before it begins to have a negative effect on the probability of being in this group.

We also included age and gender as variables in the model, and Figs.  4 and 5 show the results. Figure  4 shows that age especially impacts the probability of being in the high productivity and low productivity groups. The lowest age category (< 30–34 years) has the highest probability for being in the low productivity group, while from the mid age category (50 years and above), the probability is highest for being in the high productivity group. This means that increased age is related to an increased probability of high productivity. The variable controlling for the effect of funding also showed some significant results (see Appendix Table A7 ). The most relevant finding is that receiving competitive grants from external public sources had a very strong and significant positive effect on being in the high productivity group and a medium-sized significant negative effect on being in the low productivity group. This shows that receiving external funding in the form of competitive grants has a strong effect on productivity.

figure 4

Predicted probability of being in each of the productivity groups according to age

Figure  5 shows that there is a difference between male and female respondents. For females, there are no differences in the probability of being in either of the groups, while males have a higher probability of being in the high productivity group compared to the medium and low productivity groups.

figure 5

Results– citation impact group

For the citation impact group as the dependent variable, we found that career progress has a significant effect on the probability of being in the low citation impact group or the high citation group but not curiosity/scientific discovery or practical application. Figure  6 shows how the probability of being in the high citation impact group increases as the value on career progress increases and is higher than that of being in the low citation impact group, but only up to a certain point. This indicates that career progress increases the probability of being in the high citation impact group to some degree but that too high values are not beneficial for high citation impact. However, it should also be noted that the effect of career progress is weak and that it is difficult to conclude on how very low or very high values of career progress affect the probability of being in the two groups.

figure 6

Predicted probability for being in each of the citation impact groups according to the value on the ‘progress in my career’ variable

We also included age and gender as variables in the model, and we found a similar pattern as in the model with productivity percentile group as the dependent variable. However, the relationship between the variables is weaker in this model with the citation impact group as the dependent variable. Figure  7 shows that the probability of being in the high citation impact group increases with age, but there is no significant difference between the probability of being in the high citation impact group and the medium citation impact group. We only see significant differences when each of these groups is compared to the low citation impact group. In addition, the increase in probability is more moderate in this model.

figure 7

Predicted probability of being in each of the citation impact groups according to age

Figure  8 shows that there are differences between male and female respondents. Male respondents have a significant higher probability of being in the medium or high citation impact group compared to the low citation impact group, but there is no significant difference in the probability between the high and medium citation impact groups. For female respondents, there are no significant differences. Similarly, for age, the effect also seems to be more moderate in this model compared to the model with productivity percentile groups as the dependent variable. In addition, the effect of funding sources is more moderate on citation impact compared to productivity (see Appendix Table A7 ). Competitive grants from external public sources still have the most relevant effect, but the effect size and level of significance is lower than for the model where productivity groups are the dependent variable. Respondents who received a large amount of external funding through competitive grants are more likely to be highly cited, but the effect size is much smaller, and the result is only significant at p  < 0.1. Those who do not receive much funding from this source are more likely to be in the low impact group. Here, the effect size is large, and the coefficient is highly significant.

figure 8

Predicted probability for being in each of the citation impact groups according to gender

Concluding discussion

This article aimed to explore researchers’ motivations and investigate the impact of motivation on research performance. By addressing these issues across several fields and countries, we provided new evidence on the motivation and performance of researchers.

Most researchers in our large-N survey found curiosity/scientific discovery to be a crucial motivational factor, with practical application being the second most supported aspect. Only a smaller number of respondents saw career progress as an important inspiration to conduct their research. This supports the notion that researchers are mainly motivated by core aspects of academic work such as curiosity, discoveries, and practical application of their knowledge and less so by personal gains (see Evans and Meyer 2003 ). Therefore, our results align with earlier research on motivation. In their interview study of scientists working at a government research institute in the UK, Jindal-Snape and Snape ( 2006 ) found that the scientists were typically motivated by the ability to conduct high quality, curiosity-driven research and de-motivated by the lack of feedback from management, difficulty in collaborating with colleagues, and constant review and change. Salaries, incentive schemes, and prospects for promotion were not considered a motivator for most scientists. Kivistö and colleagues ( 2017 ) also observed similar patterns in more recent survey data from Finnish academics.

As noted in the introduction, the issue of motivation has often been analysed in the literature using the intrinsic-extrinsic distinction. In our study, we have not applied these concepts directly. However, it is clear that the curiosity/scientific discovery item should be considered a type of intrinsic motivation, as it involves performing the activity for its inherent satisfaction. Moreover, the practical application item should probably be considered mainly intrinsic, as it involves creating a better society (for others) without primarily focusing on gains for oneself. The career progress item explicitly mentions personal gains such as position and higher salary and is, therefore, a type of extrinsic motivation. This means that our results support the notion that there are very strong elements of intrinsic motivation among researchers (Jindal-Snape and Snape 2006 ).

When analysing the three aspects of motivation, we found some differences. Physicists tend to view practical application as less important than researchers in the two other fields, while career progress was most emphasised by economists. Regarding country differences, our data suggest that career progress is most important for researchers in Denmark. Nevertheless, given the limited effect sizes, the overall picture is that motivational factors seem to be relatively similar regarding disciplinary and country dimensions.

Regarding gender aspects of motivation, our data show that women seem to view practical application and career progress as more important than men. One explanation for this could be the continued gender differences in academic careers, which tend to disadvantage women, thus creating a greater incentive for female scholars to focus on and be motivated by career progress aspects (Huang et al. 2020 ; Lerchenmueller and Sorenson 2018 ). Unsurprisingly, respondents’ age and academic position influenced the importance of different aspects of motivation, especially regarding career progress. Here, increased age and moving up the positional hierarchy are linked to a decrease in importance. This highlights that older academics and those in more senior positions drew more motivation from other sources that are not directly linked to their personal career gains. This can probably be explained by the academic career ladder plateauing at a certain point in time, as there are often no additional titles and very limited recognition beyond becoming a full professor. Finally, the type of funding that scholars received also had an influence on their productivity and, to a certain extent, citation impact.

Overall, there is little support that researchers across various fields and countries are very different when it comes to their motivation for conducting research. Rather, there seems to be a strong common core of academic motivation that varies mainly by gender and age/position. Rather than talking about researchers’ motivation per se, our study, therefore, suggests that one should talk about motivation across gender, at different stages of the career, and, to a certain degree, in different fields. Thus, motivation seems to be a multi-faceted construct, and the importance of different aspects of motivation vary between different groups.

In the second step of our analysis, we linked motivation to performance. Here, we focused on both scientific productivity and citation impact. Regarding the former, our data show that both practical application and career progress have a significant effect on productivity. The relationship between practical application aspects and productivity is linear, meaning that those who indicate that this aspect of motivation is very important to them have a higher probability of being in the high productivity group. The relationship between career aspects of motivation and productivity is curve linear, and we found only significant differences between the high and low productivity groups at mid and high values of the motivation scale. This indicates that being more motivated by career progress increases productivity but only to a certain extent before it starts having a detrimental effect. A common assumption has been that intrinsic motivation has a positive and instrumental effect and extrinsic motivation has a negative effect on the performance of scientists (Peng and Gao 2019 ; Ryan and Berbegal-Mirabent 2016 ). Our results do not generally support this, as motives related to career progress are positively linked with productivity only to a certain point. Possibly, this can be explained by the fact that the number of publications is often especially important in the context of recruitment and promotion (Langfeldt et al. 2021 ; Reymert et al. 2021 ). Thus, it will be beneficial from a scientific career perspective to have many publications when trying to get hired or promoted.

Regarding citation impact, our analysis highlights that only the career aspects of motivation have a significant effect. Similar to the results regarding productivity, being more motivated by career progress increases the probability of being in the high citation impact group, but only to a certain value when the difference stops being significant. It needs to be pointed out that the effect strength is weaker than in the analysis that focused on productivity. Thus, these results should be treated with greater caution.

Overall, our results shed light on some important aspects regarding the motivation of academics and how this translates into research performance. Regarding our first research question, it seems to be the case that there is not one type of motivation but rather different contextual mixes of motivational aspects that are strongly driven by gender and the academic position/age. We found only limited effects of research fields and even less pronounced country effects, suggesting that while situational, the mix of motivational aspects also has a common academic core that is less influenced by different national environments or disciplinary standards. Regarding our second research question, our results challenge the common assumption that intrinsic motivation has a positive effect and extrinsic motivation has a negative effect on the performance of scientists. Instead, we show that motives related to career are positively linked to productivity at least to a certain point. Our analysis regarding citation patterns achieved similar results. Combined with the finding regarding the importance of current academic position and age for specific patterns of motivation, it could be argued that the fact that the number of publications is often used as a measurement in recruitment and promotion makes academics that are more driven by career aspects publish more, as this is perceived as a necessary condition for success.

Our study has a clear focus on the research side of academic work. However, most academics do both teaching and research, which raises the question of how far our results can also inform our knowledge regarding the motivation for teaching. On the one hand, previous studies have highlighted that intrinsic motivation is also of high importance for the quality of teaching (see e.g. Wilkesmann and Lauer 2020 ), which fits well with our findings. At the same time, the literature also highlights persistent goal conflicts of academics (see e.g. Daumiller et al. 2020 ), given that extra time devoted to teaching often comes at the costs of publications and research. Given that other findings in the literature show that research performance continues to be of higher importance than teaching in academic hiring processes (Reymert et al. 2021 ), the interplay between research performance, teaching performance, and different types of motivation is most likely more complicated and demands further investigation.

While offering several relevant insights, our study still comes with certain limitations that must be considered. First, motivation is a complex construct. Thus, there are many ways one could operationalise it, and not one specific understanding so far seems to have emerged as best practice. Therefore, our approach to operationalisation and measurement should be seen as an addition to this broader field of measurement approaches, and we do not claim that this is the only sensible way of doing it. Second, we rely on self-reported survey data to measure the different aspects of motivation in our study. This means that aspects such as social desirability could influence how far academics claim to be motivated by certain aspects. For example, claiming to be mainly motivated by personal career gains may be considered a dubious motive among academics.

With respect to the bibliometric analyses, it is important to realise that we have lumped researchers into categories, thereby ‘smoothening’ the individual performances into group performances under the various variables. This has an effect that some extraordinary scores might have become invisible in our study, which might have been interesting to analyse separately, throwing light on the relationships we studied. However, breaking the material down to the lower level of analysis of individual researchers also comes with a limitation, namely that at the level of the individual academic, bibliometrics tend to become quite sensitive for the underlying numbers, which in itself is then hampered by the coverage of the database used, the publishing cultures in various countries and fields, and the age and position of the individuals. Therefore, the level of the individual academic has not been analysed in our study, how interesting and promising outcomes might have been. even though we acknowledge that such a study could yield interesting results.

Finally, our sample is drawn from northwestern European countries and a limited set of disciplines. We would argue that we have sufficient variation in countries and disciplines to make the results relevant for a broader audience context. While our results show rather small country or discipline differences, we are aware that there might be country- or discipline-specific effects that we cannot capture due to the sampling approach we used. Moreover, as we had to balance sufficient variation in framework conditions with the comparability of cases, the geographical generalisation of our results has limitations.

This article investigated what motivates researchers across different research fields and countries and how this motivation influences their research performance. The analysis showed that the researchers are mainly motivated by scientific curiosity and practical application and less so by career considerations. Furthermore, the analysis shows that researchers driven by practical application aspects of motivation have a higher probability of high productivity. Being driven by career considerations also increases productivity but only to a certain extent before it starts having a detrimental effect.

The article is based on a large-N survey of economists, cardiologists, and physicists in Denmark, Norway, Sweden, the Netherlands, and the UK. Building on this study, future research should expand the scope and study the relationship between motivation and productivity as well as citation impact in a broader disciplinary and geographical context. In addition, we encourage studies that develop and validate our measurement and operationalisation of aspects of researchers’ motivation.

Finally, a long-term panel study design that follows respondents throughout their academic careers and investigates how far their motivational patterns shift over time would allow for more fine-grained analysis and thereby a richer understanding of the important relationship between motivation and performance in academia.

Data availability

The data set for this study is available from the corresponding author upon reasonable request.

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Acknowledgements

We are thankful to the R-QUEST team for input and comments to the paper.

The authors disclosed the receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Research Council Norway (RCN) [grant number 256223] (R-QUEST).

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Silje Marie Svartefoss

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Nordic Institute for Studies in Innovation, Research and Education (NIFU), Økernveien 9, 0608, Oslo, Norway

Silje Marie Svartefoss & Dag W. Aksnes

Department of Political Science, University of Oslo, 0315, Oslo, Norway

Jens Jungblut & Kristoffer Kolltveit

Centre for Science and Technology Studies (CWTS), Leiden University, 2311, Leiden, The Netherlands

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All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Silje Marie Svartefoss, Jens Jungblut, Dag W. Aksnes, Kristoffer Kolltveit, and Thed van Leeuwen. The first draft of the manuscript was written by all authors in collaboration, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Svartefoss, S.M., Jungblut, J., Aksnes, D.W. et al. Explaining research performance: investigating the importance of motivation. SN Soc Sci 4 , 105 (2024). https://doi.org/10.1007/s43545-024-00895-9

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