disagreement
Model 1 includes all five predictor variables. Model 2 excludes the two that showed no significant effects in Model 1. Numbers in brackets are adjusted R 2 s.
As in Study 1, we again observe that the providers and recipients of feedback formed very different impressions about past performance. A new and important finding in this study is that feedback conversations did not merely fail to diminish provider-recipient disagreements about what led to strong and weak performance; they actually turned minor disagreements into major ones. Recipients made more self-enhancing and self-protective attributions following the performance discussion, believing more strongly than before that their successes were caused by internal factors (their ability, personality, effort, and attention) and their failures were caused by external factors (job responsibilities, employer expectations, resources provided, and bad luck). There were also modest disagreements regarding the quality and importance of different aspects of the recipient’s job performance, but these did not worsen following discussion. The most important source of disagreement between providers and recipients then, especially following the feedback conversation, was not about what happened, but about why it happened.
What led recipients of performance feedback to accept it as legitimate and helpful? The best predictor of feedback effectiveness was the extent to which the discussion was perceived as future focused. Unsurprisingly, feedback was also easier to accept when it was more favorable. As predicted, recipients were more likely to accept feedback when they and the feedback providers agreed more about what caused the past events. Greater attribution agreement, however, did not increase recipients’ intention to change. These findings suggest that reaching agreement on the causes of past performance is neither likely to happen (because feedback discussions widen causal attribution disagreement) nor is it necessary for fostering change. What does matter is the extent to which the feedback conversation focuses on generating new ideas for future success. We further explore the relations among all these variables following the reporting of Study 3.
Performance feedback serves goals other than improving performance. For example, performance reviews often serve as an opportunity for the feedback provider to justify promotion and compensation decisions. For the recipient, the conversation may provide an opportunity for image management and the chance to influence employment decisions. People may fail to distinguish between evaluation and improvement goals when providing and receiving feedback. In Study 2, the instructions were intended to be explicit in directing participants to the developmental goal of performance improvement, rather than accountability or rewards. Nevertheless, the providers’ wish to justify their evaluations and the recipients’ wish to influence them might have contributed to the differences we observed in attributions and in judgments about the feedback’s legitimacy. To address this concern, we added a page of detailed company guidelines that emphasized the primacy of the performance-improvement goal over the goals of expressing, justifying, or influencing evaluations. There were two versions of these guidelines, which did not differ in their effects.
Participants were 162 executives and MBA students enrolled in advanced Human Resources classes in Australia. An international mix of businesspeople, 74% said they grew up in Australia or New Zealand, 10% in Europe, 22% in Asia, and 7% other. (Totals sum to more than 100% because some participants indicated more than one.) Participants averaged 39 years of age, ranging from 27 to 60. Females comprised 37% of the participants.
Participants read the same scenario and instructions as in Study 2, with an added page of guidelines for giving developmental feedback ( S8 Text ). They then completed the same post-discussion questionnaires used for the pre-post group of Study 2, minus the ratings of performance quality and importance for various aspects of the job, which showed no effects in Study 2. (The full text of the questionnaires is provided in S9 and S10 Texts). Taken together, these modifications kept the procedure to about the same length as in Study 2. This study was approved by the Institutional Review Board at the University of Melbourne. Written consent was obtained.
As in Study 2, we calculated the sum of the percentages of attributions assigned to internal causes (ability and personality + effort and attention), applying an arcsine transformation. As before, we analyzed the internal attributions measure with a mixed-model ANOVA treating each dyad as a unit. There were two within-dyads variables: role (provider or recipient), and outcomes (successes or failures) and one between-dyads variable (guideline version ). There were no effects involving guideline version (all F < 1). The main effects of role ( F (1, 79) = 50.12, p < .001, η 2 = .39) and outcomes ( F (1, 79) = 113.8, p < .001, η 2 = .59) and the interaction between them ( F (1, 79) = 86.34, p < .001, η 2 = .52) are displayed in Fig 3 , along with the parallel post-feedback results from the previous two studies. As in Study 2, the two parties’ post-discussion attributions were well apart on both successes and, especially, failures ( t (80) = 3.3 and 9.4 respectively, both p ≤ .001). Again, the correlations between the provider’s and the recipient’s post-conversation performance attributions across dyads were not significant for either successes ( r (79) = -.04, p > .69) or failures ( r (79) = -.13, p > .23) suggesting that conversation does not lead the dyad to a common understanding of what led to good or poor performance.
Results are shown by role (provider vs. recipient of feedback) and valence/outcomes (positive feedback for successes vs. negative feedback for failures), following feedback conversation. Error bars show standard errors.
We conducted regression analyses of the recipient’s feedback acceptance and intention to change as in Study 2. The regression models included three predictors: future focus, attribution disagreement, and feedback favorability. Results, shown in Table 4 , replicated our Study 2 finding that future focus is the best predictor of both feedback acceptance and intention to change. As before, attribution disagreement predicted lower acceptance, but in this study it also predicted less intention to change. We again found that feedback favorability ratings were associated with greater acceptance, but this time, not with intention to change. Recipients and providers were again significantly correlated in their judgments of how future focused the conversation was ( r (79) = .299, p = .007).
Feedback Acceptance [.373] | Intention to Change [.323] | |||||
---|---|---|---|---|---|---|
Beta | (77) | Beta | (77) | |||
Future focus | .411 | 4.432 | < .001 | .549 | 5.697 | .001 |
Attribution disagreement | -.193 | -2.131 | .036 | -.198 | -2.105 | .039 |
Favorability | .284 | 3.017 | .003 | -.050 | -.516 | .607 |
Numbers in brackets are adjusted R 2 s.
Future focus, as perceived by the recipients of feedback, was once again the strongest predictor of their acceptance of the feedback and the strongest predictor of their intention to change. Conversely, attribution disagreement between the provider and recipient of feedback was associated with lower feedback acceptance and weaker intention to change. As in Studies 1 and 2, recipients made more internal attributions for successes than providers did and, especially, more external attributions for failures. The added guidelines in this study emphasizing performance-improvement goals over evaluative ones did not alleviate provider-recipient attribution differences. Indeed, those differences were considerably larger in this study than in the previous one and were more similar to those seen in Study 1 (see Fig 3 ).
The strongest predictor of feedback effectiveness is the recipient’s perception that the feedback conversation focused on plans for the future rather than analysis of the past. We seek here to elucidate the relationship between future focus and feedback effectiveness by looking at the interrelations among the three predictors of effectiveness we studied: future focus, attribution disagreement, and feedback favorability.
The analyses that follow include data from all participants who were asked for ratings of future focus, namely those in Study 3 and in the pre-post group of Study 2. We included study as a variable in our analyses; no effects involving the study variable were significant. Nonetheless, because the two studies drew from different samples and used slightly different methods, inferential statistics could be impacted by intraclass correlation within each study. Therefore, we also tested for study-specific differences in parameter estimates using hierarchical linear modeling [ 58 , 59 ]. No significant differences between studies emerged, confirming the appropriateness of combining the data. (The HLM results are provided in S2 Analyses .)
The association between future focus and feedback effectiveness could be mediated by the effects of attribution disagreement and/or feedback favorability. Specifically, it could be that perceiving the conversation as more future focused is associated with closer agreement on attributions or with perceiving the feedback as more favorable, and one or both of those latter two effects leads to improved feedback effectiveness. Tests of mediation, following the methods of Kenny and colleagues [ 60 ], suggest otherwise (see Fig 4 ). These analyses partition the total associations of future focus with feedback acceptance and with intention to change into direct effects and indirect effects. Indirect effects via reduced attribution disagreement were 6.2% of the relation of future focus to feedback acceptance and 2.2% to intention to change. Indirect effects via improved perceptions of feedback favorability were 20.8% of the relation of future focus to feedback acceptance and 4.5% to intention to change. Thus, there is little to suggest that closer agreement on attributions or improved perceptions of feedback favorability account for the benefits of future focus on feedback effectiveness.
The two feedback effectiveness measures are feedback acceptance and intention to change. Following Kenny (2018), standardized regression coefficients are shown for the relations between future focus and two hypothesized mediators, attribution disagreement and feedback favorability ( a ), the mediators and the feedback effectiveness measures controlling for future focus ( b ), future focus and the effectiveness measures ( c ), and future focus and the effectiveness measures controlling for the mediator ( c′ ). The total effect ( c ) equals the direct effect ( c′ ) plus the indirect effect ( a · b ). Data are from Studies 2 and 3. a p = .072; * p = .028; ** p < .001.
Future focus might have synergistic or moderating effects. In particular, we hypothesized that perceiving the conversation as more future focused may moderate the negative impact of attribution disagreement on feedback effectiveness. Alternatively, future focus may be especially beneficial when agreement about attributions is good, or when attribution differences are neither so big that they cannot be put aside, nor so small that the parties see eye to eye even when they focus on the past. Similarly, future focus may be especially beneficial when feedback is most unfavorable to the recipient, or when it’s most favorable, or when it is neither so negative that the recipients can’t move past it, nor so positive that the recipients accept it even when the conversation focuses on the past.
We conducted regression analyses with feedback acceptance and intention to change as dependent variables and future focus, feedback favorability, attribution disagreement, and their first-order interactions as predictors. Because some plausible interactions are nonlinear, we defined low, intermediate, and high values for each of the three predictor variables, dividing the 198 participants as evenly as possible for each. We then partitioned each predictor into linear and quadratic components with one degree of freedom each. With linear and quadratic components of three predictors plus a binary variable for Study 2 vs. Study 3, there were seven potential linear effects and 18 possible two-way interactions. We used a stepwise procedure to select which interactions to include in our regressions, using an inclusion parameter of p < .15. Results are shown in Table 5 .
Feedback acceptance | Intention to change | |||||
---|---|---|---|---|---|---|
Future focus—Linear | 0.487 | 5.09 | < .001 | 0.639 | 11.51 | < .001 |
Future focus—Quadratic | 0.024 | 0.40 | .687 | -0.068 | -1.27 | .206 |
Feedback favorability—Linear | 0.268 | 4.36 | < .001 | 0.096 | 1.74 | .083 |
Feedback favorability—Quadratic | -0.067 | -1.12 | .265 | -0.029 | -0.55 | .584 |
Attribution disagreement—Linear | -0.226 | -3.57 | .001 | -0.148 | -2.60 | .010 |
Attribution disagreement—Quadratic | -0.094 | -1.62 | .108 | -0.088 | -1.69 | .093 |
Study 2 vs. 3 | 0.073 | 1.13 | .259 | -0.078 | -1.34 | .182 |
Future focus—Linear x Feedback favorability—Linear | -0.119 | -1.91 | .057 | -0.116 | -2.09 | .038 |
Future focus—Linear x Attribution disagreement—Linear | -0.095 | -1.83 | .070 | |||
Future focus—Linear x Study | -0.136 | -1.46 | .145 | |||
Feedback favorability–Quadratic x Attribution disagreement–Quadratic | 0.084 | 1.60 | .112 |
Models include all main effects and those first-order interactions that met an entry criterion of p < .15, plus data source (Study 2 vs. Study 3). Statistically significant values are underlined.
Future focus interacted with feedback favorability—marginally for feedback acceptance and significantly for intention to change. As shown in Fig 5 , recipients who gave low or intermediate ratings for future focus accepted the feedback less when it was most negative ( t (128) = 5.21, p < .001) and similarly, reported less inclination to change ( t (128) = 3.23, p = .002). In contrast, the recipients who rated the feedback discussion as most future focused accepted their feedback and indicated high intention to change at all levels of feedback favorability. These patterns suggest that perceiving future focus moderates the deleterious effect of negative feedback on feedback effectiveness.
Results for each measure of feedback effectiveness are shown by three levels of perceived future focus and three levels of perceived feedback favorability. Error bars show standard errors. Data are from Studies 2 and 3.
On the other hand, we find no evidence that future focus moderates the negative effect of attribution disagreement on feedback effectiveness. Future focus did interact marginally with attribution disagreement for intention to change. However, the benefits of perceiving high vs. low future focus may, in fact, be stronger when there is closer agreement about attributions: The increase in intention to change between low and high future focus groups was 2.30 with high disagreement, 2.37 with intermediate disagreement, and 3.24 in dyads with low disagreement, on a scale from 1 to 7.
Regression-tree analyses can provide additional insights into the non-linear relations among variables [ 61 ], with a better visualization of the best and worst conditions to facilitate feedback acceptance and intention to change. These analyses use the predictors (here, future focus, attribution disagreement, and feedback favorability) to divide participants into subgroups empirically, maximizing the extent to which values on the dependent measure are homogeneous within subgroups and different between them. We generated regression trees for each of our two effectiveness measures, feedback acceptance and intention to change. Fig 6 shows the results, including all subgroups (nodes) with N = 10 or more.
The trees depict the effects of future focus, attribution disagreement, and feedback favorability on our two measures of feedback effectiveness. The width of branches is proportional to the number of participants in that branch. Node 0 is the full sample of 198. Values on the X axis are standardized values for each dependent measure. Data are from Studies 2 and 3.
Both trees show that future focus is the most important variable, dividing into lower and higher branches at Nodes 1 and 2, and further distinguishing highest-future groups at Nodes A8 and B6. These representations also reinforce the conclusion that perceived future focus does not operate mainly via an association with more positive feedback or with better agreement on attributions. However, attribution disagreement does play a role, with more agreement leading to better acceptance of feedback and greater intention to change, as long as future focus is at least moderately high (Nodes A3 vs. A4 and B7 vs. B8). (The lack of effect at Node B6 is likely a ceiling effect.) Unfavorable feedback makes matters worse under adverse conditions: when future focus is low (Nodes B3 vs. B4) or when future focus is moderate but attribution disagreement is large (nodes A5 vs. A6).
Our research was motivated by a need to understand why performance feedback conversations do not benefit performance to the extent intended and what might be done to improve that situation. We investigated how providers and recipients of workplace feedback differ in their judgements about the causes of performance and the credibility of feedback, and how feedback discussions impact provider-recipient (dis)agreement and feedback effectiveness. We were particularly interested in how interpretations of past performance, feedback acceptance, and intention to change are affected by the recipient’s perception of temporal focus, that is, the extent to which the feedback discussion focuses on past versus future behavior.
Management theorists typically advocate evaluating performance relative to established goals and standards, diagnosing the causes of substandard performance, and providing feedback so that people can learn from the past [ 19 ]. They also posit that feedback recipients must recognize there is a problem, accept the feedback as accurate, and find the feedback providers fair and credible in order for performance feedback to motivate improvement [ 7 , 14 , 35 ]. Unfortunately, we know that performance feedback often does not motivate improvement [ 4 ]. Our research contributes in several ways to understanding why that is and how feedback conversations might be made more effective.
Decades of attribution theory and research have elucidated the biases thought to produce discrepant explanations for performance between the providers and recipients of feedback. We show that for negative feedback, these discrepancies are prevalent in the workplace. We also show that larger attribution discrepancies are associated with greater rejection of feedback and, in our performance review simulations, with weaker intention to change. These findings support recent research and theory linking performance feedback, work-related decision making, and attribution theory: Instead of changing behavior in response to mixed or negative feedback, people make self-enhancing and self-protecting attributions and judgements they can use to justify not changing [ 8 , 14 , 62 ].
Our research suggests that the common practice of discussing the employees’ past performance, with an emphasis on how and why outcomes occurred and what that implies about the employees’ strengths and weaknesses, can be counterproductive. Although the parties to a feedback discussion may agree reasonably well about which goals and standards were met or unmet, they are unlikely to converge on an understanding of the causes of unmet goals and standards, even with engaged give and take. Instead, the feedback conversation creates or exacerbates disagreement about the causes of performance outcomes, leading feedback recipients to take more credit for their successes and less responsibility for their failures. This suggests that feedback conversations that attempt to diagnose past performance act as another form of self-threat that increases the self-serving bias [ 33 ]. Surely this runs counter to what the feedback provider intended.
At the same time, we find that self-serving attributions need not stand in the way of feedback acceptance and motivation to improve. A key discovery in our research is that the more recipients feel the feedback focuses on next steps and future actions, the more they accept the feedback and the more they intend to act on it. In fact, when feedback is perceived to be highly future focused, feedback recipients respond as well to predominantly negative feedback as to predominantly positive feedback. Future focus does not nullify self-serving attributions and their detrimental effects [see also 63 ], but it does enable productive feedback discussions despite them.
We used two complementary research methods. Study 1 used a more naturalistic and thus more ecologically valid method, collecting retrospective self-reports from hundreds of managers about actual feedback interactions in a wide variety of work situations [see 64 ]. Studies 2 and 3 used a role-play method that allowed us to give all participants identical workplace performance information, a good portion of which was undisputed and quantitative. With that design, response differences between the providers and recipients of feedback are due entirely to role, unconfounded by differences in knowledge and experience.
What role plays cannot establish is the magnitude of effects in organizational settings. Attribution misalignment and resistance to feedback might easily be much stronger in real workplace performance reviews where it would be rare for the parties to arrive with identical, largely unambiguous information. Moreover, managers’ investment in the monetary and career outcomes of performance reviews might lead feedback recipients to feel more threatened than in a role play and thus to disagree even more with unfavorable feedback. On the other hand, the desire to maintain employment and/or to maintain good relationships with supervisors might motivate managers to re-assess their past achievements, to change their private attributions, and to be more accepting of unfavorable feedback. Data from our role-play studies may not speak to the magnitude of resistance to feedback in work settings (although our survey results suggest it’s substantial), but they do show that feedback acceptance is increased when the participants perceive their feedback to be focused on the future.
There are few research topics more important to the study of organizations than performance management. Feedback conversations are a cornerstone of most individual and team performance management, yet there is still much we do not know about what should be said, how, and why. Based on research into the motivational advantages of prospective thinking, we hypothesized that feedback discussions perceived as future focused are the most effective kind for generating acceptance of feedback and fostering positive behavior change. Our findings support that hypothesis. The present research contributes to the literature on prospection by highlighting the role of interpersonal interactions in facilitating prefactual thinking and any associated advantages for goal pursuit [ 39 , 43 – 45 , 63 , 65 ]. In this section we suggest three lines of future research: (a) field studies and interventions; (b) research into the potential role of self-beliefs; and (c) exploration of the conversational dynamics associated with feedback perceived as past vs. future focused.
Testing feedback interventions in the workplace and other field settings is an important future step toward corroborating, elaborating, or correcting our findings. It will be necessary to develop effective means to foster a more future-focused style of feedback. Then, randomized controlled trials that contrast future-focused with diagnostic feedback can demonstrate the benefits that may accrue from focusing feedback more on future behavior and less on past behavior. Participant evaluations of the feedback discussions can be supplemented by those of neutral observers. Such evaluations are directly relevant to organizational goals, including employee motivation, positive supervisor-supervisee relations, and effective problem solving. Assessing subsequent behavior change and job performance is both important and complicated for evaluating feedback effectiveness: Seeing intentions through to fruition depends on many factors, including individual differences in self-regulation [ 66 , 67 ] and factors beyond people’s control, such as competing commitments, limited resources, and changing priorities [ 68 – 71 ]. Nevertheless, the ultimate proof of future-focused feedback will lie in performance improvement itself.
If future focus enhances feedback effectiveness, it may do so via self-beliefs. Growth mindset and self-efficacy, for example, are self-beliefs that influence how people think about and act on the future. Discussions that focus on what people can do in the future to improve performance may encourage people to view their own behavior as malleable and to view better results as achievable. If future focus helps people access this growth mindset, it should orient them toward mastering challenges and improving the self for the future: Whereas people exercise defensive self-esteem repair when in a fixed mindset, they prefer self-improvement when accessing a growth mindset [ 72 , 73 ]. Similarly, feedback conversations that focus on ways the feedback recipient can attain goals in the future may enhance people’s confidence in their ability to execute the appropriate strategies and necessary behaviors to succeed. Such self-efficacy expectancies have been shown to influence the goals people select, the effort and resources they devote, their persistence in the face of obstacles, and the motivation to get started [ 74 , 75 ]. Thus, research is needed to assess whether future focus alters people’s self-beliefs (or vice versa; see below) and if these, in turn, impact people’s acceptance of feedback and intention to change.
We found sizeable variation in the extent to which dyads reported focusing on the future. Pre-existing individual differences in self-beliefs may contribute to that variation. Recent research, for example, finds that professors with more growth mindsets have students who perform better and report being more motivated to do their best work [ 76 ]. In the case of a feedback conversation, we suspect that either party can initiate thinking prospectively, but both must participate in it to sustain the benefits.
Unlike most studies of people’s reactions to mixed or negative feedback, our studies use face-to-face, real-time interaction, that is to say, two people in conversation. Might conversational dynamics associated with future-focused feedback contribute to its being better accepted and more motivating than feedback focused on the past? Do managers who focus more on the future listen to other people’s ideas and perspectives in ways that are perceived as more empathic and nonjudgmental? Do these more prospective discussions elicit greater cooperative problem solving? Research on conversation in the workplace is in its early stages [ 77 ], but some studies support the idea that high quality listening and partner responsiveness might reduce defensiveness, increase self-awareness, or produce greater willingness to consider new perspectives and ideas [ 78 , 79 ].
Our studies provide the first empirical evidence that managers can make feedback more effective by focusing it on the future. Future-focused feedback, as we define it, is characterized by prospective thinking and by collaboration in generating ideas, planning, and problem-solving. We assessed the degree of future focus by asking participants to rate the extent to which the feedback discussion focused on future behavior, the two parties spent time generating new ideas for next steps, and the conversation centered on how to make the recipient successful. This differs greatly from feedback research that distinguishes past vs. future orientation “using minimal rewording of each critique comment” (e.g., you didn’t always demonstrate awareness of… vs. you should aim to demonstrate more awareness of…) [ 80 p. 1866].
Because future-focused feedback is feedback, it also differs from both advice giving and “feedforward” (although it might be advantageous to incorporate these): It differs from Kluger and Nir’s feedforward interview, which queries how the conditions that enabled a person’s positive work experiences might be replicated in the future [ 81 ], and from Goldsmith’s feedforward exercise, which involves requesting and receiving suggestions for the future, without discussion or feedback [ 82 ].
The scenario at the very start of this article asks, “What can Chris say to get through to Taylor?” A future-focused answer might include the following: Chris first clarifies that the purpose of the feedback is to improve Taylor’s future performance, with the goal of furthering Taylor’s career. Chris applauds Taylor’s successes and is forthright and specific about Taylor’s shortcomings, while avoiding discussion of causes and explanations. Chris signals belief that Taylor has the motivation and competence to improve [ 83 ]. Chris then initiates a discussion in which they work together to develop ideas for how Taylor can achieve better outcomes in the future. (For a more detailed illustration of a future-focused conversation, see S11 Text .)
Our research supports the intriguing possibility that the future of feedback could be more effective and less aversive than its past. Performance management need not be tied to unearthing the determinants of past performance and holding people to account for past failures. Rather, performance may be managed most successfully by collaborating with the feedback recipient to generate next steps, to develop opportunities for interesting and worthwhile endeavors, and to enlarge the vision of what the recipient could accomplish. Most organizations and most managers want their workers to perform well. Most workers wish to succeed at their jobs. Everyone benefits when feedback discussions develop new ideas and solutions and when the recipients of feedback are motivated to make changes based on those. A future-focused approach to feedback holds great promise for motivating future performance improvement.
S1 analyses, s2 analyses, acknowledgments.
For helpful comments on earlier drafts of this paper, we are grateful to Pino Audia, Angelo Denisi, Nick Epley, Ayelet Fishbach, Brian Gibbs, Reid Hastie, Chris Hsee, Remus Ilies, David Nussbaum, Jay Russo, Paul Schoemaker, William Swann, and Kathleen Vohs.
This research received funding from the Melbourne Business School while the first three authors were either visiting (JG, JK) or permanent (IOW) faculty there. While working on this research, the first two authors (JG, JK) also worked as owners and employees of management consulting firm Humanly Possible. Humanly Possible provided support in the form of salaries and profit-sharing compensation for authors JG and JK, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the “author contributions” section.
PONE-D-20-05644
The future of feedback: Motivating performance improvement
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Reviewer #1: 1. I enjoyed reading this manuscript, but it appears to be unnecessary long in parts and readability would benefit of a more concise style. I would recommend condensing some parts, for example in the methods section for study 2 was overly long and lacked clarity in parts. The description of the second questionnaire was a little confusing in terms of the consistency in how items were measured and the hypothesis was not clear.
2. In the ethics statement for Study 1 (line 184), please explain the rationale behind the waiver of consent.
3. Procedure (line 187) please give details of the survey platform used.
4. Results -Please include the number of participants in each group.
5. Please comment on what normality checks were performed to assess the distribution of the data.
6. Line 470, correlations are discussed but I can’t see a table to support these.
7. The discussion did not address the results in relation to previous literature and lacked a theoretical explanation of the findings (See for example ‘Korn CW, Rosenblau G, Rodriguez Buritica JM, Heekeren HR (2016) Performance Feedback Processing Is Positively Biased As Predicted by Attribution Theory. PLoS ONE 11(2)’ for a discussion of attributional style and self-serving bias. I recommend some rewrite of the discussion with more reference to theory.
8. Some acknowledgement of the effect of individual differences in self-regulation would be useful to include as this may influence how feedback is received in terms of attributions. See for example, ‘Donovan, JJ, Lorenzet, SJ, Dwight, SA, Schneider, D. The impact of goal progress and individual differences on self‐regulation in training. J Appl Soc Psychol. 2018; 48: 661– 674’.
9. The suggestions for improvement at the end of the study would be better to be condensed to give a brief suggestion of methods.
Reviewer #2: The paper reports an interesting and comprehensive work about a relevant issue in organizational psychology. Both the theoretical frame and the applied methodology are original and thorough, though the use of role-play raises some doubts about the robustness of the results (some concerns are raised by the authors themselves (lines 752-760) ). This is, in my opinion, the main limitation of studies 2 and 3. I would suggest that the authors insert a wider reasoning about the choice of using this method to collect their data and the pros and cons.
In the "General Discussion" paragraph the authors state that "We investigated the sources of agreement and disagreement between feedback provider and recipient" (lines 712-713). I strongly suggest that this sentence is being modified, since it doesn't describe the aim nor the results in Study 1 correctly.
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Reviewer #2: Yes: Federica Biassoni
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12 May 2020
Please see uploaded document Response to Reviewers. Text copied here.
Response to Reviewers
We wish to thank the reviewers for their very helpful and constructive comments. We especially appreciate the clarity and specificity with which they framed their suggestions. Below we respond to each reviewer recommendation.
Reviewer #1:
1. I enjoyed reading this manuscript, but it appears to be unnecessary long in parts and readability would benefit of a more concise style. I would recommend condensing some parts, for example in the methods section for study 2 was overly long and lacked clarity in parts. The description of the second questionnaire was a little confusing in terms of the consistency in how items were measured and the hypothesis was not clear.
We revised the methods section for Study 2 (former lines 274-279; 285-414, revision lines 276-281; 299-402). The new version is a full page shorter and, in line with the reviewer’s suggestion, we believe this more concise version is now more readable. It includes a revised description of the post-discussion questionnaires (former 346-367; revision 350-361), clarifying the sequence and types of questions provided to each group. It also includes revisions, mainly in the Design section (former 387-414; revision lines 377-402) to clarify how the various measures related to our hypotheses.
Study 1 was approved by the Institutional Review Board at the University of Chicago, which waived the requirement for written consent as was its customary policy for studies judged to be minimal risk, involving only individual, anonymized survey responses. Their decision cited US Code 45 CFR 46.101(b). Citing the code in our manuscript seemed overly legalistic, but we have added the rest of the rationale to the ethics statement (former lines 184-185; revision 184-186).
We now identify the platform as Cogix ViewsFlash (revision line 188).
We have added the requested information for Study 1 (revision lines 214-215). Following up on the suggestion, we also made it easier to locate the corresponding information for Study 2 (revision lines 316-317).
The general consensus is that the analyses we use, i.e. ANOVA and linear regression, are generally quite robust with regard to moderate violations of normality with Ns on the order of ours (e.g., Blanca, Alarcón, Arnau, Bono, & Bendayan, Psichothema, 2017; Schmidt & Finana, Journal of Clinical Epidemiology, 2018; Ali & Sharma, Journal of Econometrics, 1996; Schmider, Ziegler Danay, Beyer, & Bühner, Methodology, 2010). Nevertheless, we used an arcsine transformation on the variables a priori most likely to suffer from systematic deviations, namely the attribution proportions. Most authors recommend checking for major deviations from normality by plotting model-predicted values against residuals and against the normal distribution (using P-P or Q-Q plots). We did that for our analyses (graphs attached), and found no troublesome deviations, with the possible exception of one variable of minor importance to our main results or theory, namely performance quality ratings for successes in Study 2. We note in the paper that that variable may suffer from ceiling effects (former 468-469, revision 456-457). We did not add a discussion of normality to the paper because of the increased length and complexity that would involve and because it’s seldom an issue of concern with data and analyses like ours. However, we could include the graphs we’ve attached here as supplemental material if you tell us you would like us to do so.
Thank you for alerting us to this inadvertent omission. We now include complete correlation tables for all the variables analyzed in each Study in the supplemental materials: S2 Table for Study 1 (revision lines 224-225) and S11 Tables for Studies 2 and 3 separately and combined (revision lines 458-459), with provider-recipient correlations identified by color shading. (S2 was formerly the dataset for Study 1, but now data from all three studies are contained in S17.)
To better address our results in relation to previous attribution literature and theory, we have revised former lines 723-740 in the General Discussion. Now we more clearly discuss our findings in relation to self-serving bias, self-threat, and both historical and more recent formulations of attribution theory, including the helpful reference the reviewer provided (revision lines 708-735). We have also added a brief discussion of how our results relate to previous literature on future thinking (revision lines 760-762). We attempted to minimize redundancy with the Introduction section. The new material includes several new references.
We added mention in the General Discussion of individual differences in self-regulation, citing two references, including the one helpfully provided by Reviewer #1 (revision line 776). Additionally, we reworded former lines 798-799 (revision lines 793-794) to make it clearer that we are acknowledging individual differences there as well.
We condensed former lines 828-846 from 19 lines to 8 lines (revision lines 823-830), referring the interested reader to new Supporting Information S16 Text for the expanded version. We trust this solution meets the recommendation for a brief suggestion of methods, while also satisfying the interests of those seeking more detail.
Reviewer #2:
1. The paper reports an interesting and comprehensive work about a relevant issue in organizational psychology. Both the theoretical frame and the applied methodology are original and thorough, though the use of role-play raises some doubts about the robustness of the results (some concerns are raised by the authors themselves (lines 752-760)). This is, in my opinion, the main limitation of studies 2 and 3. I would suggest that the authors insert a wider reasoning about the choice of using this method to collect their data and the pros and cons.
We now include a wider reasoning about our choice to use a role-play method and the pros and cons. The new version comprises revision lines 282-298. (We also revised the subsequent paragraph for increased clarity, given the insertion of the new paragraph about the role-play method.)
2. In the "General Discussion" paragraph the authors state that "We investigated the sources of agreement and disagreement between feedback provider and recipient" (lines 712-713). I strongly suggest that this sentence is being modified, since it doesn't describe the aim nor the results in Study 1 correctly.
Thank you for your careful reading. We have re-written that sentence to more accurately capture the results of Study 1 as well as the other two studies (revised lines 697-700).
[Figures attached--please see uploaded document Response to Reviewers.]
Submitted filename: Response to Reviewers.docx
27 May 2020
The future of feedback: Survey and role-play investigations into causal attributions, feedback acceptance, motivation to improve, and the potential benefits of future focus for increasing feedback effectiveness in the workplace
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The future of feedback: Motivating performance improvement through future-focused feedback
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International Journal of Operations & Production Management
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Article publication date: 15 November 2018
Issue publication date: 15 November 2018
Bourne, M. , Melnyk, S. and Bititci, U.S. (2018), "Performance measurement and management: theory and practice", International Journal of Operations & Production Management , Vol. 38 No. 11, pp. 2010-2021. https://doi.org/10.1108/IJOPM-11-2018-784
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Performance measurement has been a key theme of this journal for many years ( Neely et al. , 1995 ; Neely, 2005 ). This should not come as a surprise since performance measurement and management plays a critical role in the operation of any organisation, be it a factory, business, hospital or school. As noted by Magretta and Stone (2002) , performance measures are critical because they enhance communication – they enable the organisation to address the following critical question – “Given our mission, how is our performance going to be defined?” Yet, it should also come as a surprise that in spite of this longevity of focus, this topic is still surprised by a great deal of confusion and conflict. For example, until more recently we have not agreed on what we mean by performance measurement ( Franco-Santos et al. , 2007 ; Bourne and Bourne, 2011 ; Melnyk et al. , 2004, 2014 ) and performance management ( Bourne and Bourne, 2011 ; Melnyk et al. , 2004, 2014 ). This confusion is present in both academic research and in the practitioner press. Confounding this confusion is the tight interrelationship that exists between theory and practice.
It has been long argued that many of the developments in performance measurement have come from practice ( Johnson, 1972, 1975, 1978, 1981 ; Wilcox and Bourne, 2003 ) and this practice has informed the academic performance measurement literature. A very clear example of this phenomenon is the Balanced Scorecard, originally developed at Analogue Devices ( Schneiderman, 2001 ) and subsequently made widely accessible by Kaplan and Norton (1992) . But although this type of research is to be applauded, it is not enough. Ultimately, it suffers from being a theoretical, using Sutton and Staw (1995) categorisation scheme. Such research, while important for improving performance and the ability of the firm to record and monitor activities, does not build causality or help to explain or, as is becoming more important in today’s dynamic environment ( Nudurupait et al. , 2016 ), predict and deal with the increasing complexity now being faced by researchers and managers alike.
We need to build theory, whether from practice or other areas of business research, and validate our theory through empirical research to develop a deeper understanding and platform for the future development of the field. Furthermore, we need to build theory that operates at the various levels of the organisation – inter-organisational (relevant for a world where supply chain management is becoming so important); organisational at macro or top management levels (the focus of much of the current body of research in this area) and the lower levels of the organisation (i.e. at the function, group and, ultimately, the individual levels – the micro levels). We need to build theories that are anchored not only in the economic world but that also recognise the increasing importance of behavioural issues. So, for this special issue, we were particularly interested in papers that explore the interface between theory and practice and that add richness, as described in the preceding discussion, to the resulting theoretical developments.
But performance measurement and management are broad subjects and performance measurement and management systems (PMMS) have a wide scope. They include the top down processes of aligning the business with strategic direction as promulgated by process approaches to the development and implementation of PMMS (e.g. Kaplan and Norton, 1993 ; Neely et al. , 1996 ; Bititci et al. , 1997 ; Neely et al. , 2000 ) and to the bottom up use of performance measurement in lean ( Bhasin and Burcher, 2006 ; Krafcik, 1988 ). They include the dynamics of people and teams, interactions between department, relationships between parent and subsidiary organisations as well as performance measurement and management in the supply chain.
Performance measurement and management is not only the preserve of the private sector. Articles in this journal have reported on the impact of PMMS in both public and third sector organisations ( Greatbanks and Tapp, 2007 ; Moxham and Boaden, 2007 ). This special issue too reflects this pervasiveness of PMS, despite the fact that the papers published here happen to have focused on the private sector. We have a number of different perspectives on performance measurement and management. This includes three papers on buyer–supplier relationships, one on collaborative performance measurement systems, one the impact of supplier performance management systems (PMSs) and one on contracting. We have five papers looking at the complexities and interactions between different elements of the performance measurement system inside organisations with two of these focusing on lean. The final paper develops a framework for swift and even flow.
So in the rest of this editorial we will discuss the following. Let us begin with an overview of the early literature and the development of the four phases of PMMS before turning our attention to the need for theory to focus on the use of PMMS in directing and managing organisations. Then we will move on to the range of theory used in empirical research and in the papers presented here before going on to describe the contributions made in this special issue. We will then discuss the contribution of the Ferriera and Otley (2009) framework before suggesting future direction for theory development.
Early literature on PMMS focused on the four phases of PMMS, design, implementation, use and refresh ( Neely et al. , 2000 ; Bourne et al. , 2000 ). There is a strong argument that the debate has now moved on from the design and implementation of PMMS to its use, Franco-Santos and Bourne, 2005 ), impact ( Franco-Santos et al. , 2012 ) and emergence ( Pavlov and Bourne, 2011 ).
The work on approaches ( Dixon et al. , 1990 ) and processes for the design and implementation of PMMS ( Neely et al. , 1997 ; Bititci et al. , 1997 ; Olve et al. , 1999 ) initially adopted the three tests on feasibility, usability and utility ( Platts, 1993 ) before considering the success and failure of the design to implementation phase ( Bourne et al. , 2002 ; Bourne, 2005 ) and the quality of implementation. One of the overarching pieces here was the Bititci et al. (2006) paper which identified the need for different cultures and management styles when moving from the design and implementation phases to measurement in use phases. We would argue that it is possible to theorise about the design and implementation phases but in reality, these are as much about the implementation of change ( Bourne et al. , 2004 ) as anything else. There have also been interesting insights into the formal approaches to refreshing measurement systems ( Kennerley and Neely, 2003 ) and more recently addressing the issue of how to keep measurement systems up to date ( Melnyk et al. , 2014 ), but we strongly suggest that there is now a compelling need to develop theory around the continuing use and emergent development of PMMS.
agency theory ( Eisenhardt, 1989 ; Feltham and Xie, 1994 ; Jensen and Meckling, 1976 ; Jensen and Murphy, 1990 );
contingency theory ( Donaldson, 2001 ; Hayes, 1977 ; Otley, 1980 );
resource-based view of the firm ( Barney, 1991 ; Day, 1994 );
cognitive and information processing theories ( Miller, 1956 ; Simon, 1976 ; Talyer, 2010 ; Kunda, 1990 );
goal setting theory ( Locke and Latham, 1990 ); and
equity, distributive and procedural justice theories ( Adams, 1965 ; Greenberg, 1990 ).
In this special issue, we have papers too that use theories matching three of the six groups of theories identified in Franco-Santos et al. (2012) . Papers published here are using resource-based view (2), cognitive theories and decision making (2) and contingency theory. But we also have papers focusing on theories more relevant to PMMS in operations (performance-based contracting (PBC) and swift even flow) as well as theories related to complementarity in PMMSs, and extending the concept of levers of control ( Simons 1991 ). The papers in this special issue are summarised in Table I . We will briefly describe these papers next.
The first paper by Vieri Maestrini, Veronica Martinez, Andy Neely, Davide Luzzini, Federico Caniato and Paolo Maccarrone looks at how buyers and suppliers can collaborate in their use of their performance measurement system. In this paper, they present a tool they have called the “Relationship Regulator” which they develop, test and refine. The development was based on the literature and empirical research, whilst the testing was undertaken through workshops and feedback obtained from semi-structured interviews. This is theory building and testing of a collaborative approach to performance measurement.
The second paper by Vieri Maestrini, Davide Luzzini, Federico Caniato, Paolo Maccarrone and Stefano Ronchi is an impact paper in that it researches the impact of supplier performance measurement systems on supplier performance through hypothesis testing using survey data. However, the interest in this paper is the use of resource orchestration theory (ROT) as the theoretical framework for their analysis. They found ROT to be a suitable theoretical framework to explain the role of a mature supplier performance measurement system in orchestrating the suppliers.
The third paper by Andreas Glas, Florian Henne and Michael Essig is a literature review on the intersection of PBC and performance measurement and management. The review highlights the performance measurement and management gap in PBC identifying for research opportunities: strategic alignment (which the authors consider astonishing as PBC is supposed to be outcome orientated), action and refreshing, performance monitoring and reporting, and other aspects including the selection of appropriate KPIs.
The fourth paper by Mohamed Afy-Shararah and Nicholas Rich creates a model that captures the design elements of high performance operating management systems for swift even flow. The work builds on ten longitudinal case studies selected from the UK’s high value manufacturing sector highlighting the links between policy deployment, operational control and improvement to open collaborative partnerships.
The fifth paper by Henrik Nielsen, Thomas Kristensen and Lawrence Grassol is the first of two papers focusing on lean. The paper uses survey research to investigate the impact of social control mechanisms, behavioural control mechanisms and their complementarity on firm performance using data collected from over 4,000 subjects in nearly 700 facilities. The respondents to the survey behind this work were identified from through the “Shingo Prise”.
The sixth paper by Martijn van der Steen and Sandra Tillema takes a different approach and looks at lean implementation. Using case studies in three subsidiary companies, they suggest that lean can be severely constrained by the parent organisations accounting based control systems. The paper demonstrates how external context creates local conditions that may be detrimental to lean in manufacturing.
The seventh paper by Bijana Pesalji, Andrey Pavlov and Pietro Micheli uses the levers of control framework from Simons (1991) to investigate practices in a Dutch-based SME. The paper advances our understanding of the use of technical and social aspects of performance management and suggests that performance management requires the active and continuous use of all four control mechanisms that comprise the levers of control approach.
The eighth paper by Marcus Hasegan, Sai Nudurupati and Stephen Childe reports on the use of action research for developing dynamic performance measurement systems with real-time controls on the production lines to study the impact. The paper explains how the use of tacit knowledge and modelling were used in developing effective cause and effect analysis.
The last paper by Anthony Alexander, Maneesh Kumar and Helen Walker considers the application of decision theory under volatility, uncertainty, complexity and ambiguity (VUCA). Drawing on the Cynefin framework ( Snowden, 2000, 2002 ; Snowden and Boone, 2007 ), this paper develops the performance alignment matrix ( Melnyk et al. , 2014 ) drawing on interview research in seven case studies. The approach is designed to deal with complexity and emergence enabling managers in the positions of authority to take decisions. This paper highlights the need for organisations to adjust their performance measurement and management system over time to adapt to the external environment as a way of reformulating strategy, promoting intended behaviour and organisational learning.
So, from a theory and practice perspective, we must conclude that the special issue has attracted a wide variety of papers, research methods and applications from different contexts. The papers contribute to our understanding of performance measurement and management in buyer–supplier relationships, performance contracting and operational flow. The papers create insight into the issue of complimentary or conflicting aspects of control systems, especially in a lean setting and we have insights into balancing controls in SMEs as well as how to deal with VUCA environments. In the next section, we will focus of discussion on theory in PMMS.
If we review the theoretical approach taken both the papers in this special issue and by those empirical pieces identified in the Franco-Santos et al. (2012) literature review, it must be noted that they are not theories of performance measurement and management, but more general management theories applied to this subject area. What we are currently lacking is an underpinning theory to help us advance the field.
What is the vision and mission of the organisation and how is this brought to the attention of managers and employees? What mechanisms, processes and networks are used to convey the organisation’s overarching purposes and objectives to its members?
What are the key factors that are believed to be central to the organisation’s overall future success and how are they brought to the attention of managers and employees?
What is the organisation structure and what impact does it have on the design and use of PMSs? How does it influence and how is it influenced by the strategic management process?
What strategies and plans has the organisation adopted and what are the processes and activities that it has decided will be required for it to ensure its success? How are strategies and plans adapted, generated and communicated to managers and employees?
What are the organisation’s key performance measures deriving from its objectives, key success factors and strategies and plans? How are these are specified and communicated and what role do they play in performance evaluation? Are there significant omissions?
What the level of performance does the organisation need to achieve for each of its key performance measures (identified in the above question), how does it go about setting appropriate performance targets for them and how challenging are those performance targets?
What processes, if any, does the organisation follow for evaluating individual, group and organisational performance? Are performance evaluations primarily objective, subjective or mixed and how important are formal and informal information and controls in these processes?
What rewards – financial and/or non-financial – will managers and other employees gain by achieving performance targets or other assessed aspects of performance (or, conversely, what penalties will they suffer by failing to achieve them)?
What specific information flows – feedback and feedforward – systems and networks has the organisation in place to support the operation of its PMSs?
What type of use is made of information and of the various control mechanisms in place? Can these uses be characterised in terms of various typologies in the literature? How do controls and their uses differ at different hierarchical levels?
How have the PMSs altered in the light of the change dynamics of the organisation and its environment? Have the changes in PMSs design or use been made in a proactive or reactive manner?
How strong and coherent are the links between the components of PMSs and the ways in which they are used.
We should reflect that the framework, whilst informed by the management control literature, was developed inductively and informed by the experience of case study research ( Ferriera and Otley, 2009 , p. 276), which is why it has such a strong link to practice and why it is so useful as a holistic tool for examining the structure, operation and use of PMSs in organisations.
In many ways, this framework follows some of the early research works ( Neely et al. , 1996 ) and publications ( Kaplan and Norton, 1993, 2001 ) on PMMS, whereby the vision and mission of the organisation is translated into a strategy that is operationalised through the performance measurement and management systems. However, the Ferriera and Otley (2009) framework progresses far beyond this as it includes the development of targets, the processes of evaluation, information flow and link to rewards. Further, question 11 alludes to the dynamic nature of PMMSs and recognises that they evolve over time; so their development is not solely determined through interventions such as redesign initiatives.
Although this is an extremely useful theoretical framework, it is not a theory of performance measurement or performance management. To develop such a theory, we need to understand the mechanisms at play in the organisation when performance measures are being used to manage activities, changes of activity and future direction of the organisation. There have been calls for such a meta theory ( Franco-Santos et al. , 2012 ; Bittitci et al. , 2018 ) and we will suggest in the next section one possible direction to take in developing such an approach.
The Ferriera and Otley (2009) framework described above assumes that PMMSs are systems. In reality, they may be “systems of systems” ( Bourne et al. , 2018 ) but this framework does align with a recent call to take a more systemic approach to developing theory in performance measurement and management ( Bittitci et al. , 2018 ). These systems operate through practices and routines in organisations and it is to this subject we turn next.
If we reflect on the current theories used to inform PMMS research, it can be argued that they ignore the mechanisms by which the PMMS operates. From Franco-Santos et al. ’s (2012) six theories, four of them (agency, cognitive, goal setting and equity theories) focus on the influence of system parameters on what is usually considered to be the individual decision maker. The other two focus on the impact of the wider environment, be this the external (contingency theory) or internal (resource-based view) context. What we are not arguing here that these are not useful lenses to take in analysing the PMMSs in organisations, we are simply suggesting that adopting an alternative approach that takes a systems perspective by focusing of the operating mechanisms of PMMS could give use new insights.
One such approach is the adoption of routines ( Pavlov and Bourne, 2011 ). In their paper, the authors argue that performance measurement triggers, guides and intensifies the search for solutions to improve the performance of the organisation (see Figure 1 ). As this happens in performance review meetings (regular events where groups of managers meet to review, evaluate and act on performance information ( Martinez et al. , 2010 ); Pavlov and Bourne, 2011 ) when routines are developed which evolve into mechanisms used in the management of the organisation. This approach takes us away from the concept of the individual decision maker to the domain of multiple decision makers (albeit in a situation where some have considerably more power and influence than others). Understanding the mechanisms at play here would give us different insights.
In reality, organisations have multiple situations where performance is reviewed. These may be formal board meetings, operational planning meetings, sales management meetings, project management meetings, etc. Decisions may be made by individual decision makers acting on their own (although we would suggest that this happens far more infrequently than one would surmise from the focus of research in the management literature) but implementing action invariably requires involving others. This suggests (in all but the smallest organisations) a series of links between individuals at different levels of the organisation. Individual managers involved in running one routine (performance review meeting) will usually be participants in a higher level performance review meeting, whilst the people attending this manager’s meeting may well be running their own routine (performance review meeting) at a lower level in the organisation. In this situation, routines being influenced and guided by other routines (see Figure 2 ) together with the individual managers’ membership of performance review meetings being the conduit of the PMMS between different levels in the organisation (see Figure 3 ).
Because these mechanisms are routines, they develop over time as the mental models of what is happening influences the pattern of behaviours and the pattern of behaviours influence the mental models. This is not only sense making in practice, but probably also how emergent strategy develops and is implemented outside the formal mechanisms for strategy development in most organisation.
The domain of performance measurement and management continues to develop and, if performance measurement and management evolve to enable us to control new and emerging forms of organisations in new and emerging contexts, then it will always continue to do so. In this special issue, we have seen the development of interesting new frameworks and understanding based on using theory to reflect on practice and practice to inform our development of theory.
However, we still believe that future research in this field would benefit from adopting a more systems-based approach to understanding the mechanisms at play in PMMS. We have suggested that understanding these mechanisms in practice would be beneficial to the field and would give us a platform for future research. But, if and when we develop this better understanding, we suspect that we will still be using other more encompassing management theories, such as those used and identified here, to understand the pressures and influences on the mechanism.
Effects of PM on organisational routines
Effects of the structure of PMMS on organisational routines
The overlap of points of membership in the hierarchy of organisation routines
Summary of papers in this special issue
Authors | Subject | Theoretical lens | Contribution |
---|---|---|---|
Vieri Maestrini, Veronica Martinez, Andy Neely, Davide Luzzini, Federico Caniato and Paolo Maccarrone | The development of a smart tool to allow buyer–supplier dyads to collaborate on relationship performance | Framework building and testing | A tested and improved buyer–supplier tool |
Vieri Maestrini, Davide Luzzini, Federico Caniato, Paolo Maccarrone and Stefano Ronchi | The impact of supplier performance measurement systems on supplier performance | Resource orchestration theory ( , 2011) | Resource orchestration theory explains the role of a mature supplier performance measurement system in orchestrating suppliers |
Andreas Glas, Florian Henne and Michael Essig | Performance measurement and management in performance-based contracting | Performance-based contracting | Creates a cross-understanding between performance measurement and management and performance-based contracting |
Mohamed Afy-Shararah and Nicholas Rich | A systems approach to measuring and managing flow performance in high value manufacturing | Systems theory Swift even flow ( ) | Design elements of a high performing operational management system for swift even flow |
Henrik Nielsen, Thomas Kristensen and Lawrence Grasso | The performance effects of complimentary control mechanisms in the implementation of lean | Complementarity of management control systems (MCS) | Deeper understanding of how the complementary effects of lean manufacturing impact on firm performance |
Martijn van der Steen and Sandra Tillema | Implication of context on lean implementation | Contingency | Better understanding of how organisational controls, especially accounting control, impact on lean |
Biljana Pešalj, Andrey Pavlov and Pietro Micheli | A levers of control perspective on the use of MCS and performance measures in SMEs | Levers of control ( ) | Extending the concept of levers of control by identifying practices and the importance of maintaining balance |
Marcus Hasegan, Sai Nudurupati and Stephen Childe | A dynamic performance measurement system (DPMS) | Dynamic capabilities Decision making | An understanding of using cause and effect relationships in manufacturing to better predict performance |
Anthony Alexander, Maneesh Kumar and Helen Walker | Decision theory and the emergence with complexity in performance measurement and management | Decision theory | Dealing with complexity and emergence, enabling managers in positions of authority to make decisions |
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2019, IJFANS International Journal of Food and Nutritional Sciences
This research endeavors to comprehensively evaluate and enhance the effectiveness of performance management systems (PMS) within organizational contexts. Through an extensive review of existing PMS across diverse industries, this study analyzes employee perceptions, organizational outcomes, and the role of leadership in shaping PMS efficacy. Key performance metrics are identified, encompassing both quantitative and qualitative indicators, to gauge system success. Additionally, the study explores the integration of innovative technologies in PMS and assesses their impact. The findings culminate in the development of a comprehensive framework, providing organizations with practical guidelines for measuring, improving, and optimizing their performance management systems.
International Journal of Academic Management Science Research (IJAMSR)
David E Amanawa
Abstract: This paper discusses the theoretical underpinnings, analysis, design, and implementation of performance tools and systems. Performance management tools are software applications that track individual, team, or organizational productivity. In contrast, a performance management system is a standardized process that provides feedback to management on how an organization’s employees perform. Theories of performance management serve as the foundation for performance management. They are crucial to organizational behavior and human resource management because they assist employers in leading and motivating their workforces. A critical evaluation of what performance tools and system entails revealed that it is a way of helping employees and managers achieve their goals and improve their work quality. According to the results, it is advised to consider the following ideas: Managers should encourage staff members to speak up and provide regular feedback to their managers. They should use goal-setting tools to help them define targets and key results and match their own goals with those of the organization. You may create a culture of trust and ongoing improvement by using this strategy. Finally, managers should recognize and praise employees socially for any contribution that they have made to the organization.
Amitabh Upadhya
This paper through literature review attempts to explore different types of Performance Management Systems prevalent in organizations across the UAE and to find out its influence on employees for better performance. The paper proposes an extensive organized assessment of PMS design on the basis of established theories; presenting both concepts and frameworks that feature on the ground. It also suggests for more studies on a complete PMS framework and screening of PMS related to development of both, competence and innovation resulting in long-term employee retention. By analyzing various PMS designs it is concluded that PMS has to be designed effectively in such a way that is contingent on both internal and external variables. Both the financial performance measures and non-financial performance measures are assessed together, the link between PMS and Strategic Organizational objectives should be ratified through various methods of PM mechanisms.
Seetha Pachchhapur
This paper focuses on the perceptions and experiences of employees in two different large organisations related to Performance Management Systems (PMS) in their respective organisations. Drawing on individual employee interview data, the research paper presents a comparative assessment of PMS and reports the interpretation of employee data under various themes pertaining to design and implementation considerations. The results suggest that PMS perceptions vary due to design anomalies and an incongruity in the implementation of PMS practices which has a bearing on the effectiveness and strength of the system. In considering PMS theory and practices, organisation intentions and actions, the paper seeks to engage in debates emerging on the organisation’s dependence on PMS process for achieving goals and also developing employees.
Journal of Applied Psychology
Junhyok Yim
eli suherli
Performance management systems are designed to improve employee performance. However, the introduction of the Balance Scorecard redesigned the objectives of the performance management system. This study examines the moderating effect of using Balance Scorecard on the impact of performance management systems on employee performance. This research was conducted at manufacturing companies listed on the stock exchange in Indonesia. The research tool is a survey that includes 192 top managers from 63 registered manufacturing companies. The findings show that the use of Balance Scorecard moderates the impact of performance management systems on employee performance. This implies that the use of Balance Scorecard strategically complements and enhances the relationship between employee performance and performance management systems. This study shows that the Balance Scorecard must be used as a multi-dimensional method for measuring performance and as a strategic management system to improve...
C. Jordaan , Cecile Schultz
Knowledge of employees’ perceptions of the performance management system will assist management to implement such a system more effectively. The purpose of the study was to determine the perceptions of employees regarding the effectiveness of the performance management system at a government department in South Africa. A quantitative research approach was employed and a questionnaire was distributed to 1 200 employees at the department under study. The response rate was 44%. A factor analysis resulted in three main factors, namely personal development, personal performance, and manager support. Descriptive statistics and the ANOVA were performed to determine the perceptions of employees on these three factors. Negativity towards personal development and manager support, and positivity towards personal performance were detected.
International Journal of Productivity and Performance Management
Andre de Waal
Developing Country Studies
dolores hervie
Performance management system (PMS) is the heart of any “people management” process in an organization. Organizations exist to perform. If employees do not perform, organizations would not survive. If employees perform at their peak level, organizations would be competitive and productivity would increase. Performance management supports an organisation in the achievement of strategic goals and objectives. It assists managers in setting clear performance expectation goals for all employees that are aligned with the strategic goals. It provides a structure for employees to develop the skills they need to achieve the organisation’s strategic goals. The key features of PMS involve setting objectives, measurable performance criteria expected of the individual employee must be made known to him/her from the beginning of the year. There is regular day-to-day meeting as well as periodic formal feedback meetings with subordinates. An unbiased annual assessment of performance based on speci...
Increasingly, organizations are finding themselves in operational environments that are more dynamic and resource scarce; as a result, many organizations are focusing on becoming more agile and competitive through organizational improvement initiatives. One major facilitator of these improvement initiatives is performance measurement (PM) which has experienced an increase in both academic focus and practitioner application. Although scholarly research has been conducted in the design, implementation, use, and continuous improvement of PM systems, the majority of applications in the literature report less than optimal results or, in some cases, failure of the PM system. In the past decade, research into the implementation phase of PM systems has identified many factors for both success and failure in an attempt to increase the likelihood that the full benefits from these systems will be realized. This paper characterizes the factors identified in the literature by means of systematic literature review, remarks on the maturity of this line of research, and identifies areas for future research.
Studies in Business and Economics
Mihaela HERCIU
The utility of performance measurement and management system can be said to have been proven, but the problem faced by both the theoreticians and practitioners is to set the right performance indicators. Developed models are tools that managers can use to measure and manage performance, but they need to be tailored to the context. Also, the trend towards using non-financial performance indicators makes it very difficult for managers to design a performance measurement and management system because it involves the integration of qualitative and non-quantitative variables and a profound understanding of the internal and external environment of the company.
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Aditya Gautam
Asia Pacific Journal of Human Resources
tricia vilkinas
Management Accounting Research
Aldonio Ferreira , David Otley
Alisa Hutchinson
Harini Perera
Dr. Sukanta Mishra
Operations Management Research
Roman A . Lewandowski
Ramyadevi Arumugham
Dickson Mdhlalose
International Journal of Business …
Dr. Bishnu Sharma
Neelam Gupta
iaeme iaeme
Industrial Engineering Letters
Chandan Kumar Sahoo
KnE Social Sciences
Fatimah Mahmud
Isuri Kumari
Adriana Buhovac , Maja Groff
Dr. Sukanta Mishra, Doctorate in Commerce & Management
International Business & Economics Research Journal (IBER)
Prakash Singh
Aditya Gautam , Sameeksha Jain
IJSRD - International Journal for Scientific Research and Development
Measuring Business Excellence
Kashi Balachandran , Flavio Tonelli
Like many other companies, Deloitte realized that its system for evaluating the work of employees—and then training them, promoting them, and paying them accordingly—was increasingly out of step with its objectives. It searched for something nimbler, real-time, and more individualized—something squarely focused on fueling performance in the future rather than assessing it in the past. The new system will have no cascading objectives, no once-a-year reviews, and no 360-degree-feedback tools. Its hallmarks are speed, agility, one-size-fits-one, and constant learning, all underpinned by a new way of collecting reliable performance data.
To arrive at this design, Deloitte drew on three pieces of evidence: a simple counting of hours, a review of research in the science of ratings, and a carefully controlled study of its own organization. It discovered that the organization was spending close to 2 million hours a year on performance management, and that “idiosyncratic rater effects” led to ratings that revealed more about team leaders than about the people they were rating. From an empirical study of its own high-performing teams, the company learned that three items correlated best with high performance for a team: “My coworkers are committed to doing quality work,” “The mission of our company inspires me,” and “I have the chance to use my strengths every day.” Of these, the third was the most powerful across the organization.
With all this evidence in hand, the company set about designing a radical new performance management system, which the authors describe in this article.
HBR Reprint R1504B
How one company is rethinking peer feedback and the annual review, and trying to design a system to fuel improvement
The problem.
Not just employees but their managers and even HR departments are by now questioning the conventional wisdom of performance management, including its common reliance on cascading objectives, backward-looking assessments, once-a-year rankings and reviews, and 360-degree-feedback tools.
Some companies have ditched the rankings and even annual reviews, but they haven’t found better solutions. Deloitte resolved to design a system that would fairly recognize varying performance, have a clear view into performance anytime, and boost performance in the future.
Deloitte’s new approach separates compensation decisions from day-to-day performance management, produces better insight through quarterly or per-project “performance snapshots,” and relies on weekly check-ins with managers to keep performance on course.
At Deloitte we’re redesigning our performance management system. This may not surprise you. Like many other companies, we realize that our current process for evaluating the work of our people—and then training them, promoting them, and paying them accordingly—is increasingly out of step with our objectives.
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🏆 best performance management topic ideas & essay examples, 👍 good essay topics on performance management, 💡 interesting topics to write about performance management, 📌 simple & easy performance management essay titles, 🔎 most interesting performance management topics to write about, ❓ research questions on performance management system.
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IvyPanda . "181 Performance Management Essay Topic Ideas & Examples." August 23, 2024. https://ivypanda.com/essays/topic/performance-management-essay-topics/.
The field of management is an extremely broad discipline that draws upon concepts and ideas from the physical and social sciences, particularly mathematics, philosophy, sociology, and psychology. Within business, the field of management includes research paper topics and ideas also common to marketing, economics, finance, insurance, transportation, accounting, computer technologies, information systems, engineering, and business law.
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Angel Investors and Venture Capitalists Balance Sheets Brainstorming Break-Even Point Budgeting Business Plan Business Structure Cafeteria Plan—Flexible Benefits Case Method of Analysis Cash Flow Analysis and Statements Competitive Advantage Consumer Behavior Cost Accounting Customer Relationship Management Diversification Strategy Domestic Management Societies and Associations Due Diligence Economics Economies of Scale and Economies of Scope Effectiveness and Efficiency Financial Issues for Managers Financial Ratios First-Mover Advantage Futuring Gap Analysis Generic Competitive Strategies Income Statements Initial Public Offering Innovation Intellectual Property Rights International Business International Management Societies and Associations Intrapreneurship Inventory Management Joint Ventures and Strategic Alliances Knowledge Management Knowledge Workers Leveraged Buyouts Licensing and Licensing Agreements Location Strategy Macroenvironmental Forces Make-or-Buy Decisions Market Share Marketing Concept and Philosophy Marketing Research Miles and Snow Typology Mission and Vision Statements New Product Development Non-Compete Agreements Organizational Development Outsourcing and Offshoring Patents and Trademarks Planning Poison Pill Strategies Popular Press Management Books Porter’s Five Forces Model Pricing Policy and Strategy Problem Solving Process Management Product Design Product Life Cycle and Industry Life Cycle Profit Sharing Research Methods and Processes Scenario Planning Securities and Exchange Commission Shareholders Stakeholders Strategic Planning Tools Strategy Levels Succession Planning SWOT Analysis Synergy Technology Transfer Value Creation Venture Capital Virtual Organizations
Activity-Based Costing Angel Investors and Venture Capitalists Balance Sheets Balanced Scorecard Break-Even Point Budgeting Capacity Planning Cash Flow Analysis and Statements Corporate Social Responsibility Cost Accounting Cost-Volume-Profit Analysis Debt vs. Equity Financing Domestic Management Societies and Associations Due Diligence Economics Electronic Data Interchange and Electronic Funds Transfer Employee Benefits Employee Compensation Executive Compensation Exit Strategy Financial Issues for Managers Financial Ratios Flexible Spending Accounts Health Savings Accounts Income Statements Initial Public Offering Insider Trading Internal Auditing International Management Societies and Associations International Monetary Fund Inventory Types Leveraged Buyouts Licensing and Licensing Agreements Long Tail Make-or-Buy Decisions Management Control Nonprofit Organizations Opportunity Cost Patents and Trademarks Profit Sharing Purchasing and Procurement Risk Management Securities and Exchange Commission Stakeholders Succession Planning Venture Capital Zero-Based Budgeting
Aggregate Planning The Art and Science of Management Autonomy B2B B2E Management Balanced Scorecard Barriers to Entry Best Practices Black Friday Brainstorming Budgeting Business Plan Business Structure Communication Competitive Advantage Competitive Intelligence Contingency Approach to Management Continuous Improvement Corporate Governance Corporate Social Responsibility Delegation Disaster Recovery Diversity Divestment Downsizing and Rightsizing Economics Effectiveness and Efficiency Electronic Commerce Empowerment Financial Issues for Managers Financial Ratios Forecasting Generic Competitive Strategies Globalization Goals and Goal Setting Human Resource Management Innovation International Management Knowledge-Based View of the Firm Knowledge Management Leadership Styles and Bases of Power Leadership Theories and Studies Line-and-Staff Organizations Logistics and Transportation Management Control Management Functions Management Information Systems Management Science Management Styles Management Thought Managing Change Mission and Vision Statements Motivation and Motivation Theory Operations Management Organization Theory Organizational Analysis and Planning Organizational Behavior Organizational Chart Organizational Culture Organizational Learning Organizational Structure Organizational Development Organizing Paradigm Shift Participative Management Patents and Trademarks Paternalism Pioneers of Management Planning Process Management Quality and Total Quality Management Request for Proposal/Quotation Social Networking Strategic Integration Strategy Formulation Strategy Implementation Strategy in the Global Environment Strategy Levels Subject Matter Expert Succession Planning Training Delivery Methods Trends in Organizational Change
Affirmative Action Artificial Intelligence Assessment Centers Autonomy Nonverbal Communication Brainstorming Cafeteria Plan—Flexible Benefits Coalition Building Communication Continuing Education and Lifelong Learning Trends Discrimination Diversity Downsizing and Rightsizing Electronic Data Interchange and Electronic Funds Transfer Employee Assistance Programs Employee Benefits Employee Compensation Employee Evaluation and Performance Appraisals Employee Handbook and Orientation Employee Recruitment Employee Screening and Selection Employment Law and Compliance Empowerment Executive Compensation Flexible Spending Accounts Group Dynamics Health Savings Accounts Human Resource Information Systems Human Resource Management Japanese Management Job Analysis Knowledge-Based View of the Firm Knowledge Workers Mentoring Morale Motivation and Motivation Theory Nepotism Non-Compete Agreements Organizational Behavior Organizational Chart Organizational Culture Performance Measurement Personality and Personality Tests Privacy, Privacy Laws, and Workplace Privacy Quality of Work Life Reinforcement Theory Results-Only Work Environment Safety in the Workplace Scalable or JIT Workforce Sensitivity Training Social Networking Stress Succession Planning Sweatshops Task Analysis Teams and Teamwork Theory X and Theory Y Theory Z Time Management Training Delivery Methods Virtual Organizations Women and Minorities in Management
Artificial Intelligence Bandwidth Bar Coding and Radio Frequency Identification Communication Competitive Intelligence Complexity Theory Computer Networks Computer Security Computer-Aided Design and Manufacturing Computer-Integrated Manufacturing Content Management System Data Processing and Data Management Decision Rules and Decision Analysis Decision Support Systems Delegation Electronic Commerce Electronic Data Interchange and Electronic Funds Transfer Environmentalism and Sustainability Experience and Learning Curves Expert Systems Forecasting Fuzzy Logic Handheld Computers Information Assurance Innovation The Internet Knowledge Centers Knowledge Management Knowledge Workers Leadership in Energy and Environmental Design Management Information Systems Manufacturing Control via the Internet Metadata or Meta-Analysis Mobile Commerce Nanotechnology Product Design Project Management Robotics Service-Oriented Architecture Technology Management Technology Transfer Telecommunications Virtual Corporations Virtual Organizations Web 2.0 WiMax
B2B Competitive Advantage Diversity European Union Expatriates Exporting and Importing First-Mover Advantage Franchising Free TradeAgreements and Trading Blocs Futuring Globalization International Business International Management International Management Societies and Associations International Monetary Fund International Organization for Standards Japanese Management Licensing and Licensing Agreements Location Strategy Macroenvironmental Forces Outsourcing and Offshoring Patents and Trademarks Popular Press Management Books Profit Sharing Strategy in the Global Environment Sweatshops Transnational Organization Value-Added Tax Vendor Rating Virtual Organizations World-Class Manufacturer
The Art and Science of Management Assessment Centers Best Practices Communication Contingency Approach to Management Corporate Governance Corporate Social Responsibility Delegation Domestic Management Societies and Associations Entrepreneurship Executive Compensation Expert Systems Goals and Goal Setting Human Resource Management International Management Societies and Associations Japanese Management Job Analysis Joint Ventures and Strategic Alliances Knowledge Management Knowledge Workers Leadership Styles and Bases of Power Leadership Theories and Studies Line-and-Staff Organizations Management and Executive Development Management Functions Management Levels Management Styles Management Thought Managing Change Mechanistic Organizations Mentoring Mission and Vision Statements Morale Motivation and Motivation Theory Open and Closed Systems Operant Conditioning Organizational Culture Paradigm Shift Participative Management Personality and Personality Tests Pioneers of Management Problem Solving Reinforcement Theory Sensitivity Training Span of Control Spirituality in Leadership Strategy Formulation Succession Planning Teams and Teamwork Theory X and Theory Y Theory Z Women and Minorities in Management
Affirmative Action Cafeteria Plan—Flexible Benefits Computer Networks Computer Security Corporate Governance Corporate Social Responsibility Discrimination Diversity Downsizing and Rightsizing Due Diligence Electronic Data Interchange and Electronic Funds Transfer Employee Assistance Programs Employee Benefits Employee Compensation Employee Evaluation and Performance Appraisals Employee Recruitment Employee Screening and Selection Employment Law and Compliance Ethics Executive Compensation Human Resource Management Insider Trading Intellectual Property Rights Job Analysis Leveraged Buyouts Management Audit Management Control Mergers and Acquisitions Nepotism Non-Compete Agreements Patents and Trademarks Personality and Personality Tests Privacy, Privacy Laws, and Workplace Privacy Quality of Work Life Risk Management Safety in the Workplace Stress Succession Planning Sunshine Laws Sweatshops Technology Transfer Whistle Blower Women and Minorities in Management
Balanced Scorecard Bandwidth Bar Coding and Radio Frequency Identification Barriers to Entry Complexity Theory Computer Networks Computer Security Computer-Aided Design and Manufacturing Computer-Integrated Manufacturing Content Management System Data Processing and Data Management Decision Rules and Decision Analysis Decision Support Systems Distribution and Distribution Requirements Planning Electronic Commerce Electronic Data Interchange and Electronic Funds Transfer Service-Oriented Architecture Statistical Process Control and Six Sigma Systems Design, Development, and Implementation Technology Management Technology Transfer
Bar Coding and Radio Frequency Identification Business Process Reengineering Computer-Aided Design and Manufacturing Concurrent Engineering and Design Decision Rules and Decision Analysis Decision Support Systems Distribution and Distribution Requirements Planning Expert Systems Location Strategy Logistics and Transportation Maintenance Make-or-Buy Decisions Manufacturing Resources Planning Models and Modeling Multiple-Criteria Decision Making New Product Development Operating System Operations Management Operations Scheduling Operations Strategy Product Design Production Planning and Scheduling Productivity Concepts and Measures Product-Process Matrix Project Management Purchasing and Procurement Quality and Total Quality Management Research Methods and Processes Reverse Supply Chain Logistics Scenario Planning Service Operations Service Process Matrix Simulation Statistical Process Control and Six Sigma Statistics Subject Matter Expert Systems Analysis Systems Design, Development, and Implementation Technology Transfer Warehousing and Warehouse Management World-Class Manufacturer
Activity-Based Costing Balance Sheets Balanced Scorecard Benchmarking Best Practices Break-Even Point Budgeting Cash Flow Analysis and Statements Continuous Improvement Cost Accounting Cost-Volume-Profit Analysis Cycle Time Debt vs. Equity Financing Due Diligence Effectiveness and Efficiency Executive Compensation Financial Issues for Managers Financial Ratios Forecasting Gap Analysis Goals and Goal Setting Management Audit Management Control Management Information Systems Market Share Multiple-Criteria Decision Making Nepotism Order-Winning and Order-Qualifying Criteria Performance Measurement Pricing Policy and Strategy Profit Sharing Simulation Stakeholders Value Analysis Value Chain Management Value Creation Vendor Rating Zero-Based Budgeting Zero Sum Game
The Art and Science of Management Brainstorming Coalition Building Communication Consulting Contingency Approach to Management Continuing Education and Lifelong Learning Trends Continuous Improvement Customer Relationship Management Delegation Diversity Employee Assistance Programs Empowerment Entrepreneurship Facilitator Feedback Goals and Goal Setting Group Dynamics Intrapreneurship Knowledge Workers Leadership Styles and Bases of Power Managing Change Mentoring Morale Motivation and Motivation Theory Multimedia Organizing Participative Management Personality and Personality Tests Planning Popular Press Management Books Problem Solving Profit Sharing Safety in the Workplace Sensitivity Training Spirituality in Leadership Strategic Planning Tools Stress Succession Planning SWOT Analysis Teams and Teamwork Time Management Trends in Organizational Change Value Creation
Activity-Based Costing Aggregate Planning Bar Coding and Radio Frequency Identification Benchmarking Break-Even Point Business Process Reengineering Cellular Manufacturing Computer-Aided Design and Manufacturing Computer-Integrated Manufacturing Concurrent Engineering and Design Continuous Improvement Cost-Volume-Profit Analysis Decision Rules and Decision Analysis Decision Support Systems Distribution and Distribution Requirements Planning Domestic Management Societies and Associations Five S Framework Flexible Manufacturing Forecasting Industrial Relations International Management Societies and Associations Inventory Management Inventory Types Japanese Management Layout Lean Manufacturing and Just-in-Time Production Location Strategy Logistics and Transportation Long Tail Maintenance Make-or-Buy Decisions Management Awards Manufacturing Control via the Internet Manufacturing Resources Planning Market Share New Product Development Operations Management Operations Scheduling Operations Strategy Order-Winning and Order-Qualifying Criteria Outsourcing and Offshoring Participative Management Poka-Yoke Popular Press Management Books Porter’s Five Forces Model Production Planning and Scheduling Productivity Concepts and Measures Product-Process Matrix Project Management Purchasing and Procurement Quality Gurus Quality and Total Quality Management Reverse Supply Chain Logistics Robotics Safety in the Workplace Scalable or JIT Workforce Service Factory Service Industry Service Operations Service Process Matrix Simulation Statistical Process Control and Six Sigma Statistics Strategic Integration Supply Chain Management Synergy Teams and Teamwork Technology Management Technology Transfer Theory of Constraints Time-Based Competition Upselling Warehousing and Warehouse Management World-Class Manufacturer
Communication Customer Relationship Management Domestic Management Societies and Associations Five S Framework Gap Analysis Goals and Goal Setting Innovation International Management Societies and Associations Japanese Management Management Awards Manufacturing Resources Planning Marketing Research Operations Strategy Opportunity Cost Order-Winning and Order-Qualifying Criteria Outsourcing and Offshoring Participative Management Popular Press Management Books Productivity Concepts and Measures Quality Gurus Quality and Total Quality Management Quality of Work Life Statistical Process Control and Six Sigma Strategic Planning Tools Teams and Teamwork Value Analysis Value Creation Vendor Rating World-Class Manufacturer
Activity-Based Costing Business Process Reengineering Capacity Planning Cellular Manufacturing Coalition Building Communication Competitive Advantage Competitive Intelligence Computer Networks Computer-Integrated Manufacturing Conflict Management and Negotiation Customer Relationship Management Cycle Time Decision Support Systems Distribution and Distribution Requirements Planning Economies of Scale and Economies of Scope Effectiveness and Efficiency Electronic Commerce Electronic Data Interchange and Electronic Funds Transfer Enterprise Resource Planning Expert Systems Fulfillment Group Dynamics Industrial Relations Inventory Management Inventory Types Joint Ventures and Strategic Alliances Lean Manufacturing and Just-in-Time Production Location Strategy Logistics and Transportation Long Tail Make-or-Buy Decisions Manufacturing Resources Planning Market Share Multiple-Criteria Decision Making New Product Development Operations Management Operations Scheduling Operations Strategy Organic Organizations Organizing Poka-Yoke Problem Solving Process Management Product Design Product Life Cycle and Industry Life Cycle Production Planning and Scheduling Productivity Concepts and Measures Product-Process Matrix Purchasing and Procurement Quality and Total Quality Management Reverse Auction Reverse Supply Chain Logistics Risk Management Span of Control Stakeholders Teams and Teamwork Vendor Rating Warehousing and Warehouse Management
Artificial Intelligence Assessment Centers Autonomy Concurrent Engineering and Design Conflict Management and Negotiation Consulting Contingency Approach to Management Continuing Education and Lifelong Learning Trends Continuous Improvement Corporate Social Responsibility Delegation Domestic Management Societies and Associations Downsizing and Rightsizing Employee Evaluation and Performance Appraisals Employee Handbook and Orientation Goals and Goal Setting Group Decision Making Human Resource Management Innovation Instant Messaging International Management Societies and Associations Job Analysis Knowledge Management Knowledge Workers Management and Executive Development Management Audit Marketing Communication Mission and Vision Statements Morale Motivation and Motivation Theory Multimedia Multiple-Criteria Decision Making Organizational Culture Organizational Learning Organizing Participative Management Personality and Personality Tests Popular Press Management Books Problem Solving Project Management Safety in the Workplace Sensitivity Training Simulation Stress Succession Planning SWOT Analysis Teams and Teamwork Training Delivery Methods Virtual Organizations Women and Minorities in Management
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The impact of AI on cultural management and cultural policy cuts across multiple disciplines and creative fields, from the theorisation of the very nature of cultural producers, to the practical construction of art form and audiences. Dynamic shifts in both conceptualisation and practice are rapidly ...
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Several investigations have evaluated the research trajectory concerning entrepreneurship; nonetheless, only a few studies have examined the literature trajectory regarding entrepreneurship in tourism. Therefore, this research explores papers spanning from 2013 to 2023, mapping thematic, intellectual, and conceptual frameworks using bibliometric techniques. The research delves into scientific output, prolific authors, influential articles, co-occurrence of keywords, co-citations, and many others. The keywords “tourism” OR “travel & tourism” AND “entrepreneurship” OR “entrepreneur” were strategically employed to encompass 514 articles and review papers published in English between 2013 and 2023. VOSviewer was used as a technique for doing topic grouping alongside performance analysis. With 85 articles, 2023 is the most productive year. The most influential institution is “ The Hong Kong Polytechnic University ” and the nation is the United Kingdom correspondingly. Likewise, the most renowned journal is “ Tourism management ,” and the most productive journal is “ journal of sustainable tourism ”. Furthermore, the most cited article is “ Scale, change and resilience in community tourism planning .” This research provides researchers with insights into the existing state of research on entrepreneurship in tourism and offers guidance for future research. This study is the inaugural endeavor to present both performance evaluations and scientific clusters of the literature on entrepreneurship in tourism.
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Research Scholar, Department of Commerce and Business Studies, Jamia Millia Islamia, New Delhi, 110025, India
Uzma Mumtaz
Guest Faculty, School of Banking, Financial Services, and Insurance, Delhi Skill and Entrepreneurship University, New Delhi, 110092, India
Mohammad Faisal
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The idea of writing this paper emerged after discussion between both the authors. UM who is the first author performed the literature search and data analysis, and MF who is the corresponding author drafted, supervised and revised the work. All authors read and approved the final manuscript.
Correspondence to Mohammad Faisal .
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Mumtaz, U., Faisal, M. Mapping the landscape: a comprehensive bibliometric analysis of literature on entrepreneurship in tourism (2013–2023). J Glob Entrepr Res 14 , 29 (2024). https://doi.org/10.1007/s40497-024-00399-z
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