Past, Present and Future Compensation Research ...

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CBRXXX10.1177/0886368716681677Compensation & Benefits ReviewConroy et al.

Article

Past, Present and Future Compensation Research Perspectives

Compensation & Benefits Review 1–9 © The Author(s) 2016 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/0886368716681677 cbr.sagepub.com

Samantha A. Conroy, Colorado State University, Yeong Joon Yoon, Cornell University, Peter A. Bamberger, Tel Aviv University, Barry Gerhart, University of Wisconsin, Nina Gupta, University of Arkansas, Anthony J. Nyberg, University of South Carolina, Sanghee Park, Rutgers University, Tae-Youn Park, Vanderbilt University, Jason D. Shaw, The Hong Kong Polytechnic University, and Michael C. Sturman, Cornell University

Abstract Compensation decisions are some of the most important decisions made in organizations, and research in this area has the potential to inform these decisions. Yet compensation has been viewed as a neglected area of HR research. In order to encourage greater quantity and quality of compensation research, this article provides an overview of perspectives of compensation scholars on (1) the future of compensation research, (2) the bridging of individual-level and organization-level compensation research, and (3) the challenges common to publishing compensation research. These comments are based on a professional development workshop conducted at the 2016 Academy of Management meeting focused on encouraging interaction of junior and senior compensation researchers. Keywords compensation, research, performance-based pay, benefits, pay inequality Despite the importance of compensation and the need for theoretical integration and empirical testing, scholars in the field of compensation have expressed concern that compensation is an underresearched topic. For example, in a recent special issue of Human Resource Management Review, the editors made a plea for more compensation research, calling compensation, “the neglected area of HRM research” and noting this area of work is “among the most under-researched areas in HR” (pp. 1-2).1 In a similar vein, authors of review articles in subareas of compensation consistently emphasize the need for more research on the topic.2-6 Research on compensation is important for a number of reasons. First, we know from the work that has been done that compensation can have a powerful effect on many employee and organizational outcomes, ranging from individual emotions to firm performance.7,8 We also know that labor costs account for an increasingly large portion of the total costs of production. As such, a better understanding of how to maximize the efficiency of such resource layouts is key to competitive advantage. Second, compensation research has the potential to inform practitioner decisions. For example, work on compensation points to contextual considerations that should be considered when designing pay systems.9-16 Finally, the knowledge base

around compensation is a foundational part of human resource classes in undergraduate and graduate education and human resource professional certification programs.

A Brief Review of Compensation Compensation topics cover many different forms of “pay” and exist at multiple levels of analysis. For example, the popular textbook, Compensation, points to the forms of compensation within a total compensation framework as including two primary forms—cash compensation (e.g., base pay, pay-for-performance) and benefits (e.g., work/ life balance programs and insurance).17 Within these various categories, there are further distinctions. Base compensation can be based on job evaluations, of which there are multiple methods, or person considerations, such as skills or competencies,18 while pay-for-performance varies in distribution method and performance measurement approach.19,20 The wide variety of topics to be studied Corresponding Author: Samantha A. Conroy, College of Business, Department of Management, Colorado State University, 223 Rockwell Hall, Fort Collins, CO 80523, USA. Email: [email protected]

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Compensation & Benefits Review

means that many scholars are needed to engage in this area for progress to be made. The task for compensation researchers is also expanded by the relevance of compensation at multiple levels of analysis. Micro-focused compensation research has tended to focus on issues such as pay comparisons,21,22 pay-for-performance23 and the associated performance measurement processes24 and the relationship of these variables with individual-level outcomes, such as individual performance and satisfaction. Based on meta-analyses of the work in these areas, there is a general consensus that (1) pay-for-performance is positively correlated with individual performance quantity,25 (2) that creativity-contingent rewards are positively related to creative performance,26 (3) that actual pay levels and desirable pay comparisons are positively correlated with pay satisfaction27 and (4) that pay satisfaction has a positive relationship with desirable outcomes such as job performance and a negative relationship with undesirable outcomes such as turnover intentions and absenteeism.28 At higher levels of analysis, macro-focused compensation research has tended to focus on issues such as pay levels, pay structure and pay bases29 and the relationship of these variables with firm-level outcomes, such as firm performance30 and turnover rates.31 Arguably the most studied area in macro-focused compensation is the relationship between pay for a special group—C-Suite executives— and firm performance,32 with a meta-analysis reporting that executive compensation is sensitive to firm size and performance.33 Other work has integrated findings of the macro literature through qualitative reviews, and commonly include pleas for additional work to be done.34 A more recent development in the literature is a focus on integrating the micro and macro literatures.35-37 In sum, while some compensation topics have received a large amount of attention (e.g., executive compensation), other topics have received much less (e.g., benefits).

Research Community of Practice One means to increasing the quantity and quality of work in a field is the development of a “community of practice,” which provides for member development and knowledge exchange.38 Individuals who are passionate about and identified with the expertise of the community self-select into a community of practice.39 Benefits of such communities include driving strategy, starting new lines of work, solving problems, transferring best practices, developing skills and retaining talent. At the 2016 Academy of Management Conference, compensation scholars gathered together at a Professional Development Workshop focused on building the compensation research community of practice as a means to increase the quality and quantity of compensation research.

In particular, we aimed to foster the collaborative learning process of “thinking together”40 in the field of compensation through this workshop. Scholars from a wide variety of international institutions (e.g., Rutgers University, Cornell University, University of South Carolina, The Hong Kong Polytechnic University, Tel Aviv University) and perspectives on compensation topics (e.g., micro- and macro-research) participated in the workshop. A set of panels was conducted combining junior and senior scholars in discussions about compensation research, designed to provide direction to the field (Topic 1: The Future of Compensation Research), consider complex problems in the literature (Topic 2: Bridging Micro and Macro Perspectives), and advise new scholars on how to contribute to the field (Topic 3: Challenges Common to Publishing Work on Compensation). The purpose of this article is to summarize the various perspectives provided by panelists in the session. Scholars were given the opportunity to review and edit their statements from the panels and these perspectives have been summarized in this article. Each of the panels included discussion around three questions posed to the panelist participants. These topics and questions guide the organization of this article. We note that some panel questions involved more nuanced ideas (e.g., those related to bridging macro and micro research), leading to varied depth of discussion across topics.

Topic 1: The Future of Compensation Research The topic of The Future of Compensation Research was intended to provide an overall direction to the field of compensation. Through the questions discussed, underresearched areas were identified (Question 1), perspectives on a recently popular topic were explored (Question 2), and the use of theory was discussed (Questions 3).

Question 1. What do you see as underresearched, yet important areas for work in compensation going forward? Peter Bamberger: Altogether, compensation is underresearched. There were only 30 people at the most recent EIASM rewards/compensation conference. Four particular areas where more research is needed are the following: (1) the sharing economy and how this has changed the nature of pay; (2) benefits—an increasingly large part of total compensation, yet receiving little research attention; (3) the nature and structure of compensation and benefits in small to medium enterprises and startup firms and (4) the relative efficacy of merit pay versus bonus pay. Research in all four domains could be practically quite valuable.


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Conroy et al. Barry Gerhart: I’d like to see more work that considers intrinsic motivation in the context of compensation. We’ve been pushing back on work that discounts the importance of pay because it isn’t based on the evidence and has inappropriately applied the findings by Deci and colleagues.41 So more proactively looking at the harmful outcomes that have been suggested with solid, empirical research would be important to this conversation. Jason Shaw: For the most part, I think you can choose any area of compensation research and conclude that it is underresearched. Beyond what the others have suggested, I would like to see more research on issues related to timing and form of pay, as well as studies over time that can assess how long reactions tend to last and under what conditions they are more stable.

Question 2. Wage inequality is currently receiving a lot of attention in the United States; how do you see compensation research contributing to the conversation on wage inequality in the years to come? Peter Bamberger: I think the structural and organizational aspects of pay that may exacerbate inequality should be considered. I’m also interested in seeing more work on transparency and its role in inequality and understanding the mechanisms through which pay practices effect inequality. Barry Gerhart: We need to think about how we define inequality. Inequity, or inequality without good reason, is the real problem, not inequality. This appears to be an important conversation, and we need to think about our role in it. Jason Shaw: This question is geared to the United States, but I see it as a global issue. Disparity and inequality issues are being discussed and debated around the world. The literature is fairly clear that the issue isn’t inequality, per se, but rather unexplained or indefensible inequality that is the problem. People are accepting of, and can even motivated by, inequalities that are linked to acceptable reasons for differences. We need a better understanding of how organizations get in the position of having a great deal of unexplainable variation in pay. Beyond this, we are frequently tied into pay dispersion types and issues, but we can also look at other forms of inequality.

Question 3. What other lines of work could or should inform our approaches? What theories could be promising to transfer to and apply in compensation research? Peter Bamberger: I think both signaling theory and affective events theory would be valuable in the compensation research domain.

Barry Gerhart: I question if we need new theories in this domain—do they really help? We have a lot of good theories already. Jason Shaw: I like the idea of being open to new ways of seeing our current issues with different theories. But there are certain things that existing theory explains rather well and we can always use these principles as a foundation for moving forward.

Topic 2: Bridging Micro and Macro Perspectives The next topic was focused on addressing a complex problem in the literature of bridging micro and macro perspectives on compensation. Through the questions discussed, the scholars identified the most important topic areas (Question 1) and challenges to overcome (Question 2) in each area. In addition, scholars discussed ways to promote integration of the literatures through good research (Question 3).

Question 1. Given the breadth of compensation as a research topic, what do you consider the most important compensation topics in micro research? In macro research? Nina Gupta: Compensation research faces increasing challenges as a result of growing international, informational, technological and similar developments around the world. It is very tempting to pursue these challenges— they are there, they are interesting, few people have addressed them before and so on. But, in my opinion, the pursuit of these challenges should be accompanied by an equally fervent search for answers to issues that provide broad answers to fundamental problems that compensation researchers must also address. Dealing with nuances also means that we must first deal with basics. One of the most significant incentive issues that has continued to challenge compensation researchers for decades (if not centuries) is that of performance-based pay. Both at the macro and micro levels, it is imperative that we get a cleaner understanding of how performance-based pay works, the outcomes it affects and the complexities inherent in its design. Micro researchers have addressed the challenges of performance-based pay for a long time, focusing both on the performance measures used and the ways these measures are tied to pay. We already know a lot about performance-based pay at the micro level. We know that objective measures of performance often suffer from criterion deficiency, so that large swaths of critical behaviors essential for good performance are ignored because


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good objective measures don’t exist. We know that subjective measures of performance, particularly supervisory ratings, suffer from criterion contamination, often reflecting more about supervisory biases than about differences in employee performance. We know that making minuscule performance-based differentiations in pay is likely to be demotivating. We know that the absence of widely shared pay information, that is, pay secrecy, can lead to widespread misperceptions about the actual pay system. The lessons from micro research are many and varied. But at the micro level, we still need to know a lot more about the dysfunctional consequences of poorly designed and poorly communicated performance-based pay systems. These deficiencies in micro-level performancebased pay systems allow consultants and motivational speakers to propagate the myth that financial incentives don’t work. We have much more work to do to demonstrate convincingly that they do work—that most of the problems we see with performance-based systems are problems of bad design and bad communication. At the macro level, many of the lessons from the micro level are often ignored. Partly because of the need for summary measures, research tends to combine any and all forms of performance-based pay into one measure of whether an organization uses performance-based pay. This despite the fact that we know, from the micro research, that objective and subjective measures act differently, that individual-, group-, and organizational-level measures act differently or that different incentives (whether at the same level or at different levels) can work at cross-purposes with one another. Even when a single type of performance-based pay system is considered (e.g., merit pay), we are likely to treat a merit system that dispenses an average of 20% of base pay in merit raises as being equivalent to one that dispenses 2% of base pay in merit raises. In essence, we ignore many of the lessons from micro research when we look at performance-based pay at the macro level. A macro-level understanding of performance-based pay that incorporates these micro lessons is essential. We need to be more diligent in our approaches. Only then can we truly understand compensation phenomena at the macro level as well. I do not mean to imply in the foregoing that all micro and all macro research on performance-based pay suffers from these problems. There is some great work being done. What I do hope is that we attend more carefully to the basics, both at the micro level and at the macro level. Anthony Nyberg: I agree with Nina, and I would also add that there is a need to better incorporate time and sort out theory when bridging micro and macro compensation research. From a micro perspective, we need to do more to tease apart how individual incentives function within group settings, and we need to think more in terms of understanding how those individual incentives influence

the aggregation of individual behaviors over time to influence higher order outcomes. From a macro perspective, we need more consideration of the mechanisms that drive individual behaviors over time (often referred to as microfoundations). Together, these suggest a deep need for developing meso-level compensation theory that incorporates time. For instance, we have solid theories about how incentives motivate individual behaviors, but know less about how incentives motivate group or team behaviors. Simply stated, to fully understand how compensation functions in an organization, we need to understand the causal mechanisms within and across levels, and the level that is currently most neglected is the meso-level. Tae-Youn Park: I think we need to explore the role of social psychological factors more when studying the effects of compensation practices. Recently, my collaborators and I conducted a review of the pay dispersion literature, and we were able to find 382 correlations from 149 studies that examined the relationship between pay dispersion and its outcomes. It was an impressive number. We found that most of those studies examined the direct effect of pay dispersion. Several studies investigated the role of contingent factors, which were mostly human resource (HR) practice-related factors such as average pay level, the use of pay-for-performance, the degree of individual productivity differences and task interdependence. We found almost no studies that considered social psychological factors. However, I would be surprised if social psychological factors such as relationships among team members, organizational culture and manager’s managerial style do not have any influence on pay dispersion effects. Although I base this on the status of the pay dispersion literature, I think the status of other compensation literature is similar in that they often focus too much on HR practice-related factors and overlook the role of social psychological factors. This may partly be due to the difficulty in obtaining data, but I think it is still important for us to make efforts to theorize and empirically examine the role of social psychological factors when studying compensation issues.

Question 2. What are the biggest challenges of bridging micro and macro research on compensation? Tae-Youn Park: We have good theories at the individual level—such as expectancy theory, equity theory and agency theory—but I often see that these theories are used to explain macro-level phenomena such as organizational performance. Perhaps this is because we do not have many good theories at the collective level. Although finding good macro-level compensation theories can be challenging, we still need to be very careful when


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Conroy et al. applying micro theories because, as we know, a practice that is good for micro-level outcomes can be bad for macro-level outcomes, especially when employees are working highly interdependently. Thus, it is important to understand the similarities and differences between micro-level compensation phenomena and macro-level compensation phenomena and use the right theory that fits the level of analysis. Anthony Nyberg: I see three major challenges to bridging micro and macro compensation research. First, we lack strong theory to help explain individual and organizational responses to incentives. Second, we lack clear understanding about what it means to combine different incentives within a person, people with different incentives in a group and groups with different incentives in an organization. For years, methods challenges complicated rigorous cross-level testing, but the increased use of tools for aggregating and the increased appreciation for examining these issues over time has led us to a time where we are now more advanced methodologically than theoretically. Third, if we are going to make progress in these areas, then we need reviewers and editors to work with authors to help bridge divergent areas rather than working against them by holding unrealistic standards. For instance, we would all do well when reviewing to help thoughtful authors to see additional paths and literatures while holding them accountable to their own literature’s criterion rather than enforcing our norms or railing against errors of omission. Nina Gupta: Again, theoretical and empirical work in the micro area tends to have advanced much more than work in the macro area, partly because it has a longer history. Compensation research at the macro level often extrapolates individual-level theories and applies these theories at the organizational level. This practice raises issues of the validity and appropriateness of cross-level generalizations. This is what Tae-Youn and Anthony have been highlighting. I agree with them—theories need to be developed at different levels, and cross-level theories need to be developed. At the empirical level, one of the most vexing problems is that of aggregation. We often take individual-level data and aggregate these data to the organizational level. Statistical techniques enable this work relatively easily, but they also obfuscate concerns about what specifically needs to be aggregated. They omit answers to many questions. For example, should data be aggregated across all employees? Should production employees be treated differently from managerial employees, since they are likely to have different attitudes and different reactions? Should data be aggregated at the group or meso level, or should data be aggregated at the organizational or macro level? Should data be aggregated across good and bad performers? Organizations often have different human research

management approaches to different segments of the work force. Should data be aggregated across these segments or within each segment? Answers to questions like these are unlikely to be absolute. They probably depend on the exigencies of the particular research question, the particular situation, the particular employee groups, and so on, under consideration. But it is essential that researchers think about these answers explicitly before undertaking their research.

Question 3. What are some of the biggest mistakes you see people make when trying to using micro theories to inform macro research (and vice versa)? What do you recommend people think about early in their study design to prevent such problems? Anthony Nyberg: We are often too narrowly focused on our own literatures, which allows us to remain ignorant of others’ views. Too often, authors from one discipline fail to spend the time or make the effort to examine alternative paradigms. One obvious answer is to expand ones reading list. Perhaps a more effective means for incorporating a broader set of perspectives is to work with more varied authors who have different backgrounds and perspectives. Admittedly, working with authors who have very different perspectives can be extremely challenging, and often extremely frustrating, but the end product can be extremely rewarding, particularly in terms of bridging conversations, and hence making meaningful changes to our science. Tae-Youn Park: One of the mistakes I often see is that people overly focus on data analysis and the use of sophisticated statistical techniques and pay less attention to where and how the data are generated. The implications of compensation practices can be vastly different depending on the characteristics of tasks and jobs employees are working on. In particular, the consideration of job characteristics, such as interdependence and complexity, become very important when bridging micro and macro theories in the compensation literature. Thus, I think it is important to have a full understanding of the task and job characteristics of the sample when we analyze data, and also when possible we need to make efforts to explicitly measure those characteristics using a valid scale and consider their roles when analyzing data. Nina Gupta: Obviously, as Anthony said, we need to be careful—we need to make sure that micro researchers have a good understanding of the relevant macro theories and perspectives, and that macro researchers have a good understanding of the relevant micro theories and perspectives. Without such understanding, we cannot develop unified paradigms that address compensation issues


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within and across levels. Such an understanding would also help address the issues I raised above—it would allow us to delineate the employees and groups that must be aggregated to address a specific research question. In addition, I am troubled by the heavy reliance on existing data to answer compensation questions at the macro level. Micro research has typically used a variety of empirical approaches—surveys, laboratory experiments, simulations and field experiments, to name a few. Within the micro area, it is much more likely that the research design actually dovetails with the research question of interest. By contrast, a sizeable portion of macro compensation research relies on existing data sets obtained from settings where pay data are publicly available. The most common targets for study in macro compensation studies are sports teams and top management teams. This research is valuable. But our perspectives, particularly in macro research, must be broadened to include other samples, other settings and especially other empirical approaches. A significant constraint in using existing data is that key etiological dynamics may not have been measured properly (because the data were collected for purposes other than to answer a specific research question). If key variables are omitted from the research design, clear and comprehensive understanding of the relevant phenomena is impossible. We must have substantial macro research that asks key research questions first, and obtains the data to answer the questions with a targeted view to answering the questions.

Topic 3: Challenges Common to Publishing Work on Compensation This final topic addresses ways to improve the research conducted by advising new scholars working within the field. Through the questions discussed, scholars identified features of compensation research across disciplines (Question 1), discussed the perspectives of reviewers (Question 2) and provided advice related to data-collection challenges (Question 3).

Question 1. Compensation bridges many disciplines, including management, economics and psychology—how is publishing for outlets in these varied fields different? Barry Gerhart: I think the main focus of what is studied differs by field. For example, psychology journals tend to focus on publishing studies that examine psychological mechanisms (“black box”) between compensation practices and individual/team outcomes. On the other hand, economists tend to focus more at the policy level and

economics journals tend to focus on publishing studies that examine the outcomes of policies. Michael Sturman: Each field has different priorities, and this makes the conversation between fields challenging. For example, in explaining a phenomenon, economists tend to prioritize establishing mathematical models while psychologists tend to prioritize examining perceptions. In terms of methods, economists tend to focus on precision in parameter estimation, while psychologists pay much more attention to issues of measurement. Management research seems to be stuck in the middle. It is very difficult bridging these two fields and thereby convincing reviewers in different fields. Sanghee Park: The study topic that is frequently examined also differs by field. Psychologists frequently examine motivational issues such as subordinates’ intrinsic and extrinsic motivation, economists frequently study the topic of executive compensation and government policies and management scholars tend to study a wide range, including the topics from these two fields. However, other fields such as marketing, accounting/ finance and sociology also study compensation. In the field of marketing, there are many studies that examine compensation issues of sales force. Accounting and finance scholars are more similar to economists in that they frequently use theories in economics and archival data. Last, sociologists are more macro-focused and frequently examine the issue of wage inequality and discrimination such as the gender pay gap.

Question 2. As a compensation reviewer, what are the biggest mistakes/problems you see in work submitted on the topic of compensation? What recommendations do you have for researchers to avoid these mistakes? Michael Sturman: Fundamentally, a study needs to be a good study. There is no exception in the field of compensation. As in other fields, the research question should be interesting and contributing to the theory, research design should be well aligned with the research question, implementation should be sound, alternative explanations should be ruled out, measures should be good and so on. One problem I often do encounter specific to compensation research is the generalizability of the research when it is based on a micro experimental study. Some studies are often too context-specific to the experiment and cannot be applied to real-world compensation settings. Studies need to think more about generalizability and applicability in designing experiments. On the other hand, research with “real-world” compensation data can be quite messy. Pay gets adjusted in companies for many ad hoc reasons, and it often proves challenging to get


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Conroy et al. good compensation data along with sufficient contextual information to rule out alternative explanations. Thus, for both experimental and field studies, researchers need to consider the implications of these difficulties, but editors and reviewers need to understand that compensation research has these particular kind of problems. Sanghee Park: First, from a theory perspective, I have seen many articles that are unclear about conceptualizing constructs and use of theories. For example, compensation practices at individual, team and executive levels obviously differ and different theories should be utilized in developing models. Studies need to be clearer about the construct that they are examining and why a certain theory is applied in building a model that the study is testing. Second, from an empirical perspective, reviewers are often concerned with the lack of information regarding the study context. Although it is difficult to be too rich in context due to the confidentiality agreement often made with the compensation data provider, it is true that thorough presentation of the empirical data you studied should be presented to help us understand a complete context and to fully assess the validity of the research. Michael Sturman: I strongly agree with Park’s comments on context. Study context needs to be described very specifically. Compensation systems are typically complex, and employees are often covered by multiple pay plans. Even sports pay data are highly complex, but I often see research articles that gloss over this complexity and make inappropriate assumptions about how well sports compensation data actually reflects performance or an individual’s market value. Basically, for all compensation studies using field data, we really need to understand the contexts in these studies. Barry Gerhart: I have to agree with Sturman’s comments on fundamentals. Focus on the basics of what is a good study. Have many people read your article. Address common issues raised in friendly reviews. In terms of methodology, try to use more advanced methodologies (e.g., longitudinal or multi-level methods) that address common statistical issues. Although this is not a requirement (and theoretical issues are certainly more important), use of these advanced methods can increase the possibility of your paper being published.

Question 3. One of the most widely acknowledged challenges in our field is obtaining data. What have you learned about obtaining data? Any recommendations that could help new researchers? Sanghee Park: Most firms are very concerned about maintaining confidentiality and compensation data are

often confidential. Companies are very reluctant to provide these data. Another hurdle is a company’s own employee surveys. In particular, with a big corporation, they tend to have their own analytics team and conduct their own employee surveys periodically. They are concerned because they don’t want their employees to be overwhelmed with too many surveys. Building a trustworthy relationship with practitioners is very important. I would suggest attending practitioner conferences. It can be a great starting point in building relationships with practitioners. Moreover, it is a great opportunity to know more about the concerns of companies. Companies are often restricted in budgets in getting professional consultants. You can also think about suggesting free consulting projects to these companies in exchange for data. Michael Sturman: I would add the use of an alumni network. Building a trustworthy relationship is very gradual. The fact that you went to the same school with the alumni or that you are a faculty of the alumni’s school can speed-up the relationship-building process. In my experience, this is a highly underutilized networking opportunity for researchers. Barry Gerhart: Other possible methods can be (1) sending out letters to companies, (2) working with consulting companies, (3) reaching out to former students and (4) conducting an experiment.

Conclusion The scholars participating in the panels brought a diverse set of perspectives, but also had many areas of convergence. Here we summarize themes raised across the panels. 1. Pressing Research Needs. Scholars agreed that while there is some excellent research in the field of compensation, much more needs to be done. Particular pay topic areas raised as pressing included studying an almost unstudied topic— benefits—and studying a topic that has gotten much attention, but needs more nuance in the literature—performance-based pay. Outcomes of pay were also noted. In particular, intrinsic motivation and the dynamics of responses to pay forms over time. Contextual concerns of importance were primarily in regard to the company characteristics, including transparency and other social psychological factors. 2. Definitional Concerns. The importance of defining constructs was raised multiple times in the panels, emphasizing the need to have clear definitions in any study of compensation. Significant discussion occurred around defining inequality as compared


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Compensation & Benefits Review to inequity and performance-based pay basics (e.g., performance measurement approaches, intensity). 3. Theory Development and Application. Scholars suggested the field has good theories at the individual level, but a pressing need for theoretical development at the macro level. It was also suggested that some theories from other disciplines could add value to the literature (e.g., signaling theory). 4. Methods and Analysis. The importance of good methods, as with any research endeavor, was emphasized. In addition, scholars emphasized the value of including more detailed discussion of the context of data collections, decisions around aggregation approaches and the mixes of incentives within people and groups in studies. 5. Relationships. Finally, scholars noted the importance of relationships for good research. For example, scholars discussed the value of building research teams that include varied perspectives (e.g., macro and micro researchers; economists and psychologists) and building relationships between practitioners and researchers to improve data collection quality. It is our hope that perhaps an article such as this one will help motivate both scholars and practitioners to get together and work to improve the state of knowledge developed by compensation research.

Authors’ Note Samantha A. Conroy and Yeong Joon Yoon organized the writing of this article and the session on which this article is based. All other authors were involved as scholars in the session. Authorship of session scholars is in alphabetical order.

Declaration of Conflicting Interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding The authors received no financial support for the research, authorship, and/or publication of this article.

Notes 1. Gupta, N., & Shaw, J. D. (2014). Employee compensation: The neglected area of HRM research. Human Resource Management Review, 24(1), 1-4. 2. For details on compensation in general, see, for example, Xavier, B. (2014). Shaping the future research agenda for compensation and benefits management: Some thoughts based on a stakeholder inquiry. Human Resource Management Review, 24(1), 31-40. 3. For details on pay dispersion, see, for example, Downes, P. E., & Choi, D. (2014). Employee reactions to pay

dispersion: A typology of existing research. Human Resource Management Review, 24(1), 53-66. 4. For details on pay dispersion, see, for example, Gupta, N., Conroy, S. A., & Delery, J. E. (2012). The many faces of pay variation. Human Resource Management Review, 22(2), 100-115. 5. For details on pay dispersion, see, for example, Shaw, J. D. (2014). Pay dispersion. Annual Review of Organizational Psychology and Organizational Behavior, 1(1), 521-544. 6. For details on pay-for-performance, see, for example, Gerhart, B., & Fang, M. (2014). Pay for (individual) performance: Issues, claims, evidence and the role of sorting effects. Human Resource Management Review, 24(1), 41-52. 7. Gerhart, B., & Rynes, S. (2003). Compensation: Theory, evidence, and strategic implications. Thousand Oaks, CA: Sage. 8. See Gupta and Shaw (2014). 9. Bamberger, P., & Belogolovsky, E. (2010). The impact of pay secrecy on individual task performance. Personnel Psychology, 63, 965-996. 10. Beer, M., & Cannon, M. D. (2004). Promise and peril in implementing pay-for-performance. Human Resource Management, 43(1), 3-20. 11. Conroy, S., Gupta, N., Shaw, J. D., & Park, T. Y. (2014). A multilevel approach to the effects of pay variation. Research in Personnel and Human Resources Management, 32, 1-64. 12. Gupta, N., & Conroy, S. (2013). Evidence-based lessons about financial incentives and pay variations. WorldatWork Journal, 22(2), 7-16. 13. Jenkins, G. D., Jr., Mitra, A., Gupta, N., & Shaw, J. D. (1998). Are financial incentives related to performance? A meta-analytic review of empirical research. Journal of Applied Psychology, 83, 777-787. 14. Nyberg, A. J., Pieper, J. R., & Trevor, C. O. (2013). Payfor-performance’s effect on future employee performance integrating psychological and economic principles toward a contingency perspective. Journal of Management, 42, 1753-1783. 15. Park, S., & Sturman, M. C. (2016). Evaluating form and functionality of pay-for-performance plans: The relative incentive and sorting effects of merit pay, bonuses, and long-term incentives. Human Resource Management, 55, 697-719. 16. Shaw, J. D., Gupta, N., & Delery, J. E. (2002). Pay dispersion and workforce performance: Moderating effects of incentives and interdependence. Strategic Management Journal, 23, 491-512. 17. Milkovich, G., Newman, J., & Gerhart, B. (2013). Compensation (11th ed.). New York, NY: McGraw-Hill. 18. See Milkovich et al. (2013). 19. Conroy, S. A., & Gupta, N. (2016). Team pay-for-performance: The devil is in the details. Group & Organization Management, 41(1), 32-65. 20. See Park and Sturman (2016). 21. Berkowitz, L., Fraser, C., Treasure, F. P., & Cochran, S. (1987). Pay, equity, job gratifications, and comparisons in pay satisfaction. Journal of Applied Psychology, 72, 544-551.


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Conroy et al. 22. Shore, T. H., Tashchian, A., & Jourdan, L. (2006). Effects of internal and external pay comparisons on work attitudes. Journal of Applied Social Psychology, 36, 2578-2598. 23. Durham, C. C., & Bartol, K. M. (2012). Pay for performance. In E. A. Locke (Ed.), Handbook of principles of organizational behavior: Indispensable knowledge for evidence-based management (2nd ed., pp. 150-165). Hoboken, NJ: John Wiley. doi:10.1002/9781119206422. ch12 24. Heneman, R. L., & Werner, J. M. (2005). Merit pay: Linking pay to performance in a changing world (2nd ed.). Greenwich, CT: Information Age. 25. See Jenkins et al. (1998). 26. Byron, K., & Khazanchi, S. (2012). Rewards and creative performance: A meta-analytic test of theoretically derived hypotheses. Psychological Bulletin, 138, 809-830. 27. Williams, M. L., McDaniel, M. A., & Nguyen, N. T. (2006). A meta-analysis of the antecedents and consequences of pay level satisfaction. Journal of Applied Psychology, 91, 392-413. 28. See Williams et al. (2006). 29. See Gerhart and Rynes (2003). 30. See Shaw (2014). 31. Shaw, J. D., & Gupta, N. (2007). Pay system characteristics and quit patterns of good, average, and poor performers. Personnel Psychology, 60, 903-928. 32. Devers, C. E., Cannella, A. A., Reilly, G. P., & Yoder, M. E. (2007). Executive compensation: A multidisciplinary review of recent developments. Journal of Management, 33, 1016-1072. 33. Tosi, H. L., Werner, S., Katz, J. P., & Gomez-Mejia, L. R. (2000). How much does performance matter? A metaanalysis of CEO pay studies. Journal of Management, 26, 301-339. 34. See, for example, Shaw (2014). 35. See Conroy et al. (2014). 36. See Gupta et al. (2012). 37. Yanadori, Y., & Cui, V. (2013). Creating incentives for innovation? The relationship between pay dispersion in R&D groups and firm innovation performance. Strategic Management Journal, 34, 1502-1511. 38. Wenger, E. C., & Snyder, W. M. (2000). Communities of practice: The organizational frontier. Harvard Business Review, 78(1), 139-146. 39. See Wenger and Snyder (2000). 40. Pyrko, I., Dorfler, V., & Eden, C. (2016). Thinking together: What makes communities of practice work? Human Relations. Advance online publication. doi:10.1177/0018726716661040 41. Deci, E. L., Koestner, R., & Ryan, R. M. (1999). A metaanalytic review of experiments examining the effects of extrinsic rewards on intrinsic motivation. Psychological Bulletin, 125, 627-668.

Author Biographies Samantha A. Conroy is an assistant professor of Management in the College of Business at Colorado State University. Her research focuses on compensation and reward systems, workrelated identity, and emotions. Yeong Joon Yoon is a PhD candidate in the Human Resource Studies Department of the ILR School, Cornell University. His research focuses on HR and compensation strategy, including pay cut, employee share ownership, and pay-for-performance. Peter A. Bamberger is professor of Organizational Behavior and Human Resource Management at Tel Aviv University’s Coller School of Management. Current research interests include peer relations and helping processes, occupational health psychology, and compensation strategy. Barry Gerhart is the Ellig Distinguished Chair at the School of Business, University of Wisconsin-Madison. His research interests include compensation, human resource strategy, and international human resources. Nina Gupta is Distinguished professor and John H. Tyson Chair of Management at the Sam M. Walton College of Business at the University of Arkansas. Her research focuses on the design of pay systems and employee responses to pay design. Anthony J. Nyberg is an associate professor and Moore Research Fellow in the Darla Moore School of Business at the University of South Carolina. His research focuses on strategic human capital resources with emphases on performance, compensation, employee movement, and executive succession. Sanghee Park is an assistant professor of Human Resources Management at Rutgers University School of Management and Labor Relations. Her research interests include the influence of compensation systems, supervisor-employee relationships, and the dynamics of compensation decisions and employee perceptions. Tae-Youn Park is an assistant professor of Management at Vanderbilt University. His research interests include the individual and organizational consequences of compensation, human capital theory, and employee-organization relationships. Jason D. Shaw is Chair Professor, Head of Department, and Director of the Centre for Leadership and Innovation at The Hong Kong Polytechnic University. His research interests include team effectiveness, employment relationships, envy, financial incentives, and turnover. Michael C. Sturman is a professor of Management and the Kenneth and Marjorie Blanchard Professor of Human Resources at Cornell University’s School of Hotel Administration. His current research focuses on the prediction of individual job performance over time and the influence of compensation systems.
