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The Journal of Managerial Psychology (JMP) publishes research that contributes to an improved psychological and social understanding of workplaces, to benefit individuals, organizations and society (Stone, 2010). Thus, papers submitted to JMP should develop, test and/or extend theory that enable our discipline to build and sustain healthy, meaningful and productive organizations. JMP accepts papers from all methodological perspectives, including quantitative, qualitative, mixed-methods, as well as conceptual. A range of factors determine whether a paper successfully navigates the review process through to publication, although the key criteria throughout are whether the research and its write-up have been well-executed.

As authors of submitted manuscripts will know, the experience of receiving constructive criticism varies greatly across journals. Yet such feedback can be critical to improving a manuscript to a publishable standard. Recognizing the importance of constructive feedback, we are committed to JMP providing a developmental focus to benefit authors. That is, the editorial team ensures that authors receive constructive feedback to help them improve, whether a paper is rejected or offered a revise and resubmit. Notwithstanding our specific developmental feedback on each submitted manuscript, in this editorial we provide advice based on general and recurrent issues that hinder manuscripts from reaching their full potential. To develop this advice, we reviewed the common themes that lead us to reject papers either at their initial consideration (desk-reject) or following review (first-round reject). Many of these issues we identified are core to both the implementation and communication of the research process. Authors can address these problems through more careful manuscript preparation, greater attention to theory, deeper relevant literature review, the addition of another sample, appropriate analyses and taking greater care with writing and editing. These topics, while they may pose fatal flaws for progress to publication, could often be corrected with additional work. Moreover, we note that these common reasons for manuscript rejections hold true across journals, and are not idiosyncratic to JMP.

JMP's aims and scope (Journal of Managerial Psychology, 2020) are as follows:

The journal concerns itself with application of theory and practice of managerial psychology, which as a field focuses on the behaviours, theories, practice, methods, and tools used to solve workplace problems and increase the efficacy of people at work. Managerial psychology is a field that applies psychological principles and theory to executive and managerial roles, to support, improve, and advance the effectiveness of those in the roles towards achieving a healthy, meaningful, and productive organization.

JMP strives to be a bridge between theory and practice. As such, we welcome manuscripts that address not only the psychological processes underlying phenomena in organizational settings but also emphasize their relevance to managers. JMP publishes manuscripts generally classified as micro-, meso-, and, to some limited extent, macro-level issues. At the micro-level, phenomena that are suitable to the journal involve employee characteristics (e.g. personality, demography), perceptions (e.g. supervision, perceived organizational support), attitudes (e.g. satisfaction, commitment) and behaviors (e.g. performance, organizational citizenship behavior). At the meso-level, we highly encourage studies that focus on team characteristics, perceptions, attitudes and behaviors. At the macro-level, only limited research areas are considered suitable. For example, human resource management (HRM) issues at the organization level (e.g. strategic HRM) are welcome as long as they are tied to individual- and team-level issues.

Despite JMP's openness to the abovementioned areas, some types of manuscripts are out of scope. Manuscripts that are not suitable to the journal include reviews of literature that are neither relevant for theory development nor provide directions for future research. Similarly, manuscripts are not suitable if they examine individual and group phenomena without relevance to organizations (e.g. psychological development of children). Topics related to other related disciplines (e.g. strategy, sociology, entrepreneurship, finance, accounting, etc.) are not appropriate for JMP unless the relevance to managerial psychology is clearly outlined.

One critical reason for rejection stems from the lack of clearly articulated rationale for the study: answering the “So what?” question. There are two ways of answering this question: theoretical and practical – both are important for publication in JMP. Theoretically, a manuscript should clearly articulate what theory is being examined, extended or created, and how it extends and contributes to the conversations in the literature on the topic of interest; practically, manuscripts should persuasively communicate the implications of the findings for organizations and those working in them.

Considering these “So what?” issues in more detail, well-written introductions (which are hard to write) answer the three questions “Who cares?”, “What do we know, what do we not know, and so what?” and “What will we learn?” (see Grant and Pollock, 2011). JMP is in good company: Most peer-reviewed scientific journals require clear articulation of the theoretical contribution in the introduction. Insufficient justifications include simply filling a “gap” of a hitherto underexplored phenomenon or claiming the association between X and Y has not been studied before. These study justifications are inadequate for two reasons: (1) the relationship may have been studied and the authors are simply unaware of it and/or (2) just because a relationship has not been studied or published does not mean it is worthy of being studied or published. The onus is on the authors to explain the value of their study. This can be difficult, perhaps because authors tend to be passionately interested and intrinsically understand the value of their work – the key skill to develop is explaining to others the value of the work and how it connects to related conversations in the literature.

Beyond theoretical contribution, JMP aims “to provide a bridge from science to practice, and from practice to science.” JMP is somewhat unique in the organizational sciences by placing a summary of practical implications on the first page of the article, which emphasizes our concern with communicating the practical importance of the findings of each study published in JMP. Submissions to JMP should include a summary of the practical implications on the abstract page and a substantial (versus pro-forma) practical implications section. A good set of practical implications have actionable value to organizations, their managers and employees. They should be written clearly and simply, avoiding technical language and outlining useable suggestions (APA, 2020; Bartunek and Rynes, 2010; Meuser et al., 2020). While JMP has no specified rule on what practical implications should look like, one structure is to write short sections for each of the various stakeholders implicated in the findings, suggesting what each group of stakeholders might assess, re-evaluate or do differently.

Probably the most common issue in rejected quantitative manuscripts is underdeveloped theory. Formal theories provide a framework to describe why expected relationships between variables exist. Theory is “an explanation of relationships among concepts or events with a set of boundary conditions” (Van de Ven, 2007, p. 112) or a “story about why acts, events, structure, and thoughts occur” (Sutton and Staw, 1995, p. 378). Theory answers why and when X is related to Y (Kaplan, 1964; Merton, 1967; Sutton and Staw, 1995).

Identifying a theoretical framework is a crucial step in the scientific process in the hypothetico-deductive tradition because it guides the research, including working out new and important questions to answer, the selection of variables and the most suitable research method. Simply because a framework is common does not mean it is the best for your study. Consider that while social exchange is the most common framework for leader–member exchange (Dulebohn et al., 2012), it is not without criticism (Cropanzano et al., 2017a) and there are other possibilities, for example role theory (Kahn et al., 1964) and affective events theory (Weiss and Cropanzano, 1996; Cropanzano et al., 2017b).

A critical error we encounter is failure to interweave literature reviews into a logic that supports a manuscript's research focus. On one extreme, “theory name dropping” occurs, that is referencing a theory without explaining it. This is insufficient because the theoretical framework should be clearly explained in the manuscript such that a reader with no prior knowledge of the theory has sufficient orientation. Moreover, the theoretical framework must be used to argue the logic of the specific variables investigated and their relationships. On the other extreme, extensive literature reviews that exhaustively cover literature relevant to a theory wear out the reader, and usually preclude coherent argumentation for the hypotheses. Rather, the literature review should provide a balanced view of the literature, including the essential features or debates pertinent to the research being presented.

A well-crafted manuscript describes the chosen framework(s), and how the overall expectations of the framework apply to the specific variables in the study. This argumentation should derive from the conversation in the literature, and appropriate citations to relevant articles should be present; relatedly, paragraphs that lack citations suggest the authors are not sufficiently drawing on relevant literature. Some scholars suggest writing your logic before the literature review, and then adding literature review and citation components after your logic is sound (Sparrowe and Mayer, 2011).

One common mistake is to equate hypotheses with providing a theoretical framework. However, hypotheses are not theory; rather, they are “concise statements about what is expected to occur, not why it is expected to occur” (Sutton and Staw, 1995, p. 377). They lack the why that is provided by theory. It is not uncommon for rejected manuscripts to have poorly written hypotheses that do not follow clearly or logically from the argumentation provided before them. Long lists of hypotheses are usually indicative of inadequate argumentation and, as a rule, we suggest providing a rationale prior either to each hypothesis or small clusters of hypotheses.

Another issue is overreliance on prior empirical findings to assert a prediction. An important distinction here is the difference between explanations and predictions. While successful predictions are important to science, predictions alone are not science. Predicting X is related to Y can be done on the basis of prior observation or research – citing meta-analyses for example. Explanations go beyond mere predictions and are the target of scientific endeavor. Science seeks knowledge of why things occur, through theory, not simply that they do occur. Explanations give meaning to the universe.

We have dedicated considerable space in this editorial to theoretical issues because these are a key weakness that yield a rejection of a manuscript. Thus far our focus has been on theory in quantitative studies, reflecting the majority of manuscripts received at JMP. However, we welcome both quantitative and qualitative studies equally, as well as conceptual papers. Hence, we turn to a few points relating to theory in qualitative papers.

For qualitative research, theory is often developed inductively from data. The standards we expect as evidence for the rigor of theorizing are achieved through transparency, which itself may be attained via a range of approaches, including but not limited to plausibility, credibility and dependability (Grodal et al., 2020; Pratt et al., 2020). Ultimately, authors need to explain what issue is being studied and why, how the context and specific data are relevant, and how data were analyzed to support the concepts that emerged (Grodal et al., 2020; Pratt et al., 2020).

JMP concerns itself with application of theory and practice of managerial psychology, which as a field focuses on the behaviors, theories, practice, methods and tools used to solve workplace problems and increase the efficacy of people at work, and to sustain healthy, meaningful and productive workplaces. The contribution(s) of an article may be across any of these areas.

Academic articles generally share a common structure that clarifies the contribution, although there is some variation, especially across different methodologies. However, most often a manuscript will start with an introduction, literature review and relevant theoretical frameworks or alternative ways of understanding the motivation for the research questions, hypotheses or research propositions. For empirical articles, these sections provide the context and logic underpinning the methods and results or findings. A discussion draws the common threads together, often including strengths and limitations, as well as theoretical and practical implications, and a conclusion. While not all articles have all components, this overall pattern is conventional, and the familiar structure helps readers navigate what are often complex ideas. Within this structure, the writing aims to be scholarly and precise. Together, they enable a manuscript to communicate how it extends understanding of phenomena and answers the “So what?” question. This means successful articles that achieve publication in JMP provide evidence to advance our understanding of organizational phenomena or make sound argumentation for how research should proceed via either a theory and/or methods contribution.

JMP also considers replication studies for publication. Here, authors should clearly articulate the contribution by specifying how their replication adds to what we already know and extends current theorizing. For example, many theories are tested almost exclusively in Western contexts. A manuscript reporting a replication in a different context should clearly articulate why one might expect specific aspects of theory to work differently in a different context. The authors need to answer the “so what” and “why” questions that justify the replication and what we might learn from it. In doing so, the authors also need to include variable(s) reflecting the context under consideration. Emerging research areas or nascent theories provide additional situations where a replication study might be valuable. Such replications highlight their contribution to the new research areas or emphasize how they provide further evidence for the new theory.

Practitioner articles' contributions focus on the how-to and much less the why of. These articles typically lack formal theory sections and formal hypotheses, discussions of methods and statistics, and other features common to scientific articles. Practitioner articles are written directly with managers and employees in mind. They focus on pro- and prescriptive advice, often furnish examples or vignettes to illustrate their points, and are typically much shorter than an academic manuscript. As important as practical implications are, JMP is not an outlet for practitioner-oriented manuscripts, which may find a more appropriate venue in established outlets (e.g. Harvard Business Review, California Management Review, MIT Sloan Management Review and Business Horizons).

For quantitative articles, analyses should closely match the associations presented within research propositions or hypotheses. At JMP, in addition to the relevant expertise of the Associate Editor assigned any particular manuscript, we have Associate Editors particularly focused on methods who are a resource for the editorial team. Advancing our discipline depends on findings that are supported by robust analyses, and this is an area where manuscripts often fall short. Here, we point out common issues we encounter that lead to manuscript rejection, along with citations. We recommend that prospective authors familiarize themselves with these issues as relevant to their prospective submission.

On the research design side, the variables measured must match the constructs hypothesized; samples must be relevant to the issues under investigation. Student samples must be used with care, and often cannot be the only sample in the manuscript. Reliance on single source one-time data collections will usually yield rejection. JMP has instituted a policy to reject manuscripts testing mediation models with cross-sectional datasets. In a case-by-case situation, JMP considers manuscripts that test moderated mediation, use strong theory and prior evidence for the directionality of the proposed mediation, and/or use strong statistical procedures to check for reverse causality. Single item measures are problematic because reliability cannot be estimated. Latent variables should be measured with multiple item scales with evidence of good validity and reliability; and steps should be taken to mitigate common method variance when planning the research (Podsakoff et al., 2003, 2012).

As noted above, following data collection, analyses need to help to test the relationships proposed between variables. A mismatch between theory and analyses invariably yields rejection. Some common issues include: omitting or inaccurately conducting or reporting confirmatory factor analyses (Crede and Harms, 2019); using ordinary least-squares regression when data are nested, implying a need for hierarchical methods (Raudenbush and Bryk, 2002), using the outdated Baron and Kenny (1986) method to test indirect (mediation) effects instead of more accurate approaches (Cheung and Lau, 2008; Hayes, 2009); not testing for moderated mediation when moderator(s) and mediator(s) are included in the theoretical model (Cheung and Lau, 2017); and not taking steps to assess the effects of common method variance (Podsakoff et al., 2012; Williams and McGonagle, 2016). Additionally, analyses should be at the level of sophistication required to test whether proposed relationships exist, rather than too simple to provide the depth of analysis required or unnecessarily complex. To this end, analyses using “simple” statistics, such a correlations or ANOVAs (with experiments a notable exception) are usually inappropriate. Authors using unusual or newer analytic techniques should provide sufficient explanation given that readers may not have previously come across them. Finally, we often encounter analyses that lack sufficient description in sample and other details, which obfuscate reviewers' and readers' ability to evaluate the science. Transparency of reporting is important for many reasons (Aguinis et al., 2019; APA, 2008). The list of potential methods issues is lengthy and a full treatment is beyond the scope of this editorial. Please see  Appendix for a list of common issues we encounter at JMP and citations as relevant.

Poor quality writing continues to be a pervasive issue plaguing many submitted manuscripts (see also Rogelberg et al., 2009; Stone, 2010), affecting especially the introduction and discussion sections. Key issues at the outset include a poor or missing description of intended contribution, unclear or insufficient theoretical reasoning, poorly defined constructs, and, for quantitative papers, a lack of precision in developing or presenting hypotheses. For the discussion section, common issues are a lack of analysis and insight linking back to the literature, and a lack of practical implications, these latter being particularly important given that JMP aims to positively impact employees and managers, the organizations they work in, and society more broadly (Stone, 2010).

More general problems include grammatical issues, overly complex writing, excessive use of acronyms, inappropriate causal language, missing references and poor formatting (including text, tables, figures and/or references). Authors need to make their ideas and analyses easily accessible so that reviewers can focus on the value of what is being said, rather than trying to fathom out what is being said. As Ragins (2012, p. 494) notes in her editorial on clear writing, “the beauty of clear writing is that it creates nearly effortless reading”.

There are various ways to improve the quality of your writing. Universities often provide writing centers and workshops to help staff members and students develop crucial writing skills. Beyond these, one solution is to use software (e.g. Grammarly, ProWritingAid, WhiteSmoke). Another solution is to use copy-editing services, which are offered by many publishers (e.g. Emerald offers Peerwith) and many universities also keep records of individual copy-editors or companies that they recommend. However, note that none of these provide a guarantee as by and large these ameliorate only the spelling and grammar of your text – they rarely improve the quality or clarity of your arguments. Perhaps a better alternative is to ask a native English speaker for a review. We emphasize that none of these offers a panacea that will result in an error-free manuscript. Indeed, one of us is a native English speaker and received a review comment at a different journal “The manuscript can be improved significantly by having edited by [sic] a proficient/native English writer.” Equivalently, one of us has recommended in our editorial comments to authors that they get their manuscript copy-edited, only to be told that it already had been, which suggests the copy-editing was substandard. Ultimately, thorough editing across multiple drafts is needed to achieve concise, accurate, clear and interesting writing.

Beyond these issues of the quality of writing, we note also that authors, in presenting the unique contributions of their work, should link into ongoing research conversations in JMP and/or other journals. It is generally the case that a manuscript that has very few or even no citations to a journal is a bad fit for that journal. Citations that link to ongoing conversations in JMP and/or other journals allow authors to identify both how their research contributes to those ongoing discussions, as well as the distinctive contribution of their research (Stone, 2010).

Finally, authors should follow JMP's style guide in preparing their manuscripts. This includes Harvard style referencing in the body of the manuscript and the reference section. Tables and figures should adhere to American Psychological Association (APA) style (APA, 2020). Authors who do not attend to these important details convey an impression of sloppiness in their work, and thus reduce the editorial and review team members' confidence in the quality of the manuscript. Articles that are too long (or too short) will be rejected by the editorial assistant, delaying the progress of your manuscript. Please note JMP's guidelines on word count, and the standard word allowance per table or figure. Note also that JMP requires a concise title; reviewing the titles of recently published articles may be helpful.

There can be no doubt: knowledge creation is a challenging endeavor and successful scholars must hone myriad skills spanning from creative inspiration to painstakingly detailed record keeping. Here, we take a step toward JMP's mission to be a developmental journal and provide current advice based on recent rejections at JMP to help scholars improve the quality of their research and scientific reporting. While there exist a host of concerns when embarking on a project or constructing a manuscript, space prohibits us from covering them all; we hope this present exposition helps current and prospective authors achieve publication of their work in JMP and elsewhere.

Table A1

Common methods issues

IssueResources
(Ad-hoc) shortening of scalesStanton, J.M., Sinar, E.F., Balzer, W.K. and Smith, P.C. (2002), “Issues and strategies for reducing the length of self-report scales”, Personnel Psychology, Vol. 55 No. 1, pp. 167–194.
Smith, G.T., McCarthy, D.M. and Anderson, K.G. (2000), “On the sins of short-form development”, Psychological Assessment, Vol. 12 No. 1, pp. 102–111.
Common method variance (CMV)Fuller, C.M., Simmering, M.J., Atinc, G., Atinc, Y. and Babin, B.J. (2016), “Common methods variance detection in business research”, Journal of Business Research, Vol. 69 No. 8, pp. 3192–3198.
Podsakoff, P.M., MacKenzie, S.B., Lee, J.-Y. and Podsakoff, N.P. (2003), “Common method biases in behavioral research: A critical review of the literature and recommended remedies”, Journal of Applied Psychology, Vol. 88 No. 5, pp. 879–903.
Podsakoff, P.M., MacKenzie, S.B. and Podsakoff, N.P. (2012), “Sources of method bias in social science research and recommendations on how to control it”, Annual Review of Psychology, Vol. 63, pp. 539–569.
Simmering, M.J., Fuller, C.M., Richardson, H.A., Ocal, Y. and Atinc, G.M. (2015), “Marker variable choice, reporting, and interpretation in the detection of common method variance: A review and demonstration”, Organizational Research Methods, Vol. 18 No. 3, pp. 473–511.
Williams, L.J. and McGonagle, A.K. (2016), “Four research designs and a comprehensive analysis strategy for investigating common method variance with self-report measures using latent variables”, Journal of Business and Psychology, Vol. 31 No. 3, pp. 339–359.
Exploratory factor analysis (EFA)Bandalos, D.L. and Boehm-Kaufman, M.R. (2009), “Four common misconceptions in exploratory factor analysis”, in Lance, C.E. and Vandenberg, R.J. (Eds.) Statistical and Methodological Myths and Urban Legends: Doctrine, Verity, and Fable in the Organizational and Social Sciences, Routledge, New York.
Conway, J.M. and Huffcutt, A.I. (2003), “A review and evaluation of exploratory factory analysis practices in organizational research”, Organizational Research Methods, Vol. 6, pp. 147–168.
Fabrigar, L.R., Wegner, D.T., MacCallum, R.C. and Strahan, E.J. (1999), “Evaluating the use of exploratory factor analysis in psychological research”, Psychological Methods, Vol. 4 pp. 272–299.
Confirmatory factor analysis (CFA)Crede, M and Harms, P. (2019), “Questionable research practices when using confirmatory factor analysis”, Journal of Managerial Psychology, Vol. 34 No. 1, pp. 18–30.
Control variablesBecker, T.E. (2005), “Potential problems in the statistical control of variables in organizational research: A qualitative analysis with recommendations”, Organizational Research Methods, Vol. 8 No. 3, pp. 274–289.
Bernerth, J.B. and Aguinis, H. (2016), “A critical review and best-practice recommendations for control variable usage”, Personnel Psychology, Vol. 69, pp. 229–283.
Spector, P.E. and Brannick, M.T. (2011), “Methodological urban legends: The misuse of statistical control variable”, Organizational Research Methods, Vol. 14 No. 2, pp. 287–305.
Data qualityDeSimone, J.A., Harms, P.D. and DeSimone, A.J. (2015), “Best practice recommendations for data screening”, Journal of Organizational Behavior, Vol. 36 No. 2, pp. 171–181.
Hardy, B. and Ford, L. (2014), “It's not me, it's you: Miscomprehension in surveys”, Organizational Research Methods, Vol. 17, pp. 138–162.
Meade, A.W. and Craig, S.B. (2012), “Identifying careless responses in survey data”, Psychological Methods, Vol. 17 No. 3, pp. 437–455.
Difference scoresEdwards, J.R. and Parry, M.E. (1993), “On the use of polynomial regression equations as an alternative to difference scores in organizational research”, Academy of Management Journal, Vol. 36 No. 6, pp. 1577–1613.
Dominance/relative importance analysisBudescu, D.V. and Azen, R. (2004), “Beyond global measures of relative importance: Some insights from dominance analysis”, Organizational Research Methods, Vol. 7 No. 3, pp. 341–350.
Johnson, J.W. and LeBreton, J.M. (2004), “History and use of relative importance indices in organizational research”, Organizational Research Methods, Vol. 7 No. 3, pp. 238–257.
LeBreton, J.M. and Tonidandel, S. (2008), “Multivariate relative importance: Extending relative weight analysis to multivariate criterion spaces”, Journal of Applied Psychology, Vol. 93 No. 2, pp. 329–345.
Tonidandel, S. and LeBreton, J.M. (2011), “Relative importance analysis: A useful supplement to regression analysis”, Journal of Business and Psychology, Vol. 26 No. 1, pp. 1–9.
Tonidandel, S and LeBreton, J.M. (2015), “Relative importance analysis: Programs for calculating relative weights in multiple, multivariate, and logistic regression”, available at: http://relativeimportance.davidson.edu/multipleregression.html
Experience sampling methods (ESM)Beal, D.J. (2015), “ESM 2.0: State of the art and future potential of experience sampling methods in organizational research”, Annual Review of Organizational Psychology and Organizational Behavior, Vol. 2, pp. 383–407.
Gabriel, A.S., Podsakoff, N.P., Beal, D.J., Scott, B.A., Sonnentag, S., Trougakos, J.P. and Butts, M.M. (2019), “Experience sampling methods: A discussion of critical trends and considerations for scholarly advancement”, Organizational Research Methods, Vol. 22 No. 4, pp. 969–1006.
Experimental designsStone-Romero, E.F. and Rosopa, P.J. (2011), “Experimental tests of mediation models: Prospects, problems, and some solutions”, Organizational Research Methods, Vol. 14, pp. 631–646.
Grant, A.M. and Wall, T.D. (2009), “The neglected science and art of quasi-experimentation”, Organizational Research Methods, Vol. 12, pp. 653–686.
Highhouse, S. (2009), “Designing experiments that generalize”, Organizational Research Methods, Vol. 12 No. 3, pp. 554–566.
HeteroscedasticityRosopa, PJ., Schaffer, M.M. and Schroeder, A.N. (2013), “Managing heteroscedasticity in general linear models”, Psychological Methods, Vol. 18 No. 3, pp. 335–351.
Interrater reliability and agreement (ICCs, etc.)LeBreton, J.M. and Senter, J.L. (2008), “Answers to 20 questions about interrater reliability and interrater agreement”, Organizational Research Methods, Vol. 11, pp. 815–852.
Low survey response ratesRogelberg, S.G. and Stanton, J.M. (2007), “Introduction understanding and dealing with organizational survey nonresponse”, Organizational Research Methods, Vol. 10 No. 2, pp. 195–209.
MediationHayes, A.F. (2009), “Beyond Baron and Kenny: Statistical mediation analysis in the new millennium”, Communication Monographs, Vol. 79 No. 4, pp. 408–420.
Hayes, A.F. and Scharkow, M. (2013), “The relative trustworthiness of inferential tests of the indirect effect in statistical mediation analysis: Does method really matter?”, Psychological Science, online first, August 2013, doi: 10.1177/0956797613480187.
MacKinnon, D.P., Coxe, S. and Baraldi, A.N. (2012), “Guidelines for the investigation of mediating variables in business research”, Journal of Business and Psychology, Vol. 27 No. 1, pp. 1–14.
Preacher, K.J. and Hayes, A.F. (2004), “SPSS and SAS procedures for estimating indirect effects in simple mediation models”, Behavior Research Methods, Instruments, and Computers, Vol. 36, pp. 717–731.
Rosopa, P.J. and Stone-Romero, E.F. (2008), “Problems with detecting assumed mediation using the hierarchical multiple regression strategy”, Human Resource Management Review, Vol. 18, pp. 294–310.
Stone-Romero, E.F. and Rosopa, P.J. (2008), “The relative validity of inferences about mediation as a function of research design characteristics”, Organizational Research Methods, Vol. 11, pp. 326–352.
Stone-Romero, E.F. and Rosopa, P.J. (2010), “Research design options for testing mediation models and their implications for facets of validity”, Journal of Managerial Psychology, Vol. 25, pp. 697–712.
Meta-analysisAguinis, H., Dalton, D.R., Bosco, F.A., Pierce, C.A. and Dalton, C.M. (2011), “Meta-analytic choices and judgment calls: Implications for theory building and testing, obtained effect sizes, and scholarly impact”, Journal of Management, Vol. 37 No. 1, pp. 5–38.
Aguinis, H., Pierce, C.A., Bosco, F.A., Dalton, D.R. and Dalton, C.M. (2011), “Debunking myths and urban legends about meta-analysis”, Organizational Research Methods, Vol. 14, pp. 306–331.
Aytug, Z.G., Rothstein, H.R., Zhou, W. and Kern, M.C. (2012), “Revealed or concealed? Transparency of procedures, decisions, and judgments calls in meta-analysis”, Organizational Research Methods, Vol. 15, pp. 103–133.
Moderated mediationCheung, G.W. and Lau, R.S. (2008), “Testing mediation and suppression effects of latent variables: Bootstrapping with structural equation models”, Organizational Research Methods, Vol. 11 No. 2, pp. 296–325.
Cheung, G.W. and Lau, R.S. (2017), “Accuracy of parameter estimates and confidence intervals in moderated mediation models: A comparison of regression and latent moderated structural equations”, Organizational Research Methods, Vol. 20 No. 4, pp. 746–769.
Edwards, J.R. and Lambert, L.S. (2007), “Methods for integrating moderation and mediation: A general analytical framework using moderated path analysis”, Psychological Methods, Vol. 12, pp. 1–22.
Preacher, K.J., Rucker, D.D. and Hayes, A.F. (2007), “Addressing moderated mediation hypotheses: Theory, methods, and prescriptions”, Multivariate Behavioral Research, Vol. 42, pp. 185–227.
Hayes, A.F. (2018), “Partial, conditional, and moderated mediation quantification, inference, and interpretation”, Communication Monographs, Vol. 85, pp. 4–40.
Hayes, A.F. (2017), Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach, Guilford Press, New York.
Missing dataNewman, D.A. (2014), “Missing data: Five practical guidelines”, Organizational Research Methods, Vol. 17 No. 4, pp. 372–411.
Online panel data (e.g. MTurk)Keith, M.G., Tay, L. and Harms, P.D. (2017), “Systems perspective of Amazon Mechanical Turk for Organizational Research: Review and Recommendations”, Frontiers in Psychology, Vol. 8, p. 1359.
Porter, C.O.L.H., Outlaw, R., Gale, J.P. and Cho, T.S. (2019), “The use of online panel data in management research: A review and recommendations”, Organizational Research Methods, Vol. 45 No. 1, pp. 319–344.
Poor reliabilityCortina, J.M. (1993), “What is coefficient alpha? An examination of theory and applications”, Journal of Applied Psychology, Vol 78, pp. 98–104.
Qualitative issuesCreswell, J.W. (2009), Research Design: Qualitative, Quantitative, and Mixed Methods Approaches, 3rd ed., Sage Publications, Thousand Oaks, CA.
Golden-Biddle, K. and Locke, K. (2007), Composing Qualitative Research, 2nd ed., Sage Publications, Thousand Oaks, CA.
Grodal, S., Anteby, M. and Holm, A.L. (2020), “Achieving rigor in qualitative analysis: The role of active categorization in theory building”, Academy of Management Review. Advance online publication.
Locke, K. and Golden-Biddle, K. (1997), “Constructing opportunities for contribution: Structuring intertextual coherence and ‘problematizing’ in organizational studies”, Academy of Management Journal, Vol. 40 No. 5, pp. 1023–1062.
Miles, M.B. and Huberman, A.M. (1994), Qualitative Data Analysis: An Expanded Sourcebook, 2nd ed., Sage Publications, Thousand Oaks, CA.
Pratt, M.G., Kaplan, S. and Whittington, R. (2020), “Editorial essay: The tumult over transparency: Decoupling transparency from replication in establishing trustworthy qualitative research”, Administrative Science Quarterly, Vol. 65 No. 1, pp. 1–19.
Student (Recruited) samplesHochwarter, W. (2014), “On the merits of student-recruited sampling: Opinions a decade in the making”, Journal of Occupational and Organizational Psychology, Vol. 87, pp. 27–33.
Wheeler, A.R., Shanine, K.K., Leon, M.R. and Whitman, M.V. (2014), “Student-recruited samples in organizational research: A review, analysis, and guidelines for future research”, Journal of Occupational and Organizational Psychology, Vol. 87, pp. 1–26.
Structural equation modeling (SEM)Hu, L. and Bentler, P.M. (1999), “Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives”, Structural Equation Modeling, Vol. 6, pp. 1–55.
Schreiber, J.B., Stage, F.K., King, J., Nora, A. and Barlow, E.A. (2006), “Reporting structural equation modeling and confirmatory factor analysis results: A Review”, The Journal of Educational Research, Vol. 99 No. 6, pp. 323–337.
Vignette designsAguinis, H. and Bradley, K.J. (2014), “Best practice recommendations for designing and implementing experimental vignette methodology studies”, Organizational Research Methods, Vol. 17 No. 4, pp. 351–371.

Note(s): There are many methods issues and many good papers on each of these issues. A complete methods bibliography is beyond the scope of this editorial

Aguinis
,
H.
,
Hill
,
N.S.
and
Bailey
,
J.R.
(
2019
), “
Best practices in data collection and preparation: recommendations for reviewers, editors, and authors
”,
Organizational Research Methods
,
Advance online publication
.
American Psychological Association
(
2008
), “
Reporting standards for research in psychology: why do we need them? What might they be?
”,
American Psychologist
, Vol.
63
No.
9
, pp.
839
-
851
.
American Psychological Association
(
2020
),
Publication Manual of the American Psychological Association
, (7th ed.) ,
American Psychological Association
,
Washington, DC
.
Cheung
,
G.W.
and
Lau
,
R.S.
(
2008
), “
Testing mediation and suppression effects of latent variables: bootstrapping with structural equation models
”,
Organizational Research Methods
, Vol.
11
No.
2
, pp.
296
-
325
.
Cheung
,
G.W.
and
Lau
,
R.S.
(
2017
), “
Accuracy of parameter estimates and confidence intervals in moderated mediation models: a comparison of regression and latent moderated structural equations
”,
Organizational Research Methods
, Vol.
20
No.
4
, pp.
746
-
69
.
Cropanzano
,
R.
,
Anthony
,
E.L.
,
Daniels
,
S.R.
and
Hall
,
A.V.
(
2017a
), “
Social exchange theory: a critical review with theoretical remedies
”,
The Academy of Management Annals
, Vol.
11
, pp.
479
-
516
.
Cropanzano
,
R.
,
Dasborough
,
M.T.
and
Weiss
,
H.M.
(
2017b
), “
Affective events and the development of leader-member exchange
”,
Academy of Management Review
, Vol.
42
, pp.
233
-
258
.
Dulebohn
,
J.H.
,
Bommer
,
W.H.
,
Liden
,
R.C.
,
Brouer
,
R.L.
and
Ferris
,
G.R.
(
2012
), “
A meta-analysis of antecedents and consequences of leader-member exchange: integrating the past with an eye toward the future
”,
Journal of Management
, Vol.
38
No.
6
, pp.
1715
-
1759
.
Grant
,
A.M.
and
Pollock
,
T.G.
(
2011
), “
Publishing in AMJ – Part 3: setting the hook
”,
Academy of Management Journal
, Vol.
54
No.
5
, pp.
873
-
879
.
Grodal
,
S.
,
Anteby
,
M.
and
Holm
,
A.L.
(
2020
), “
Achieving rigor in qualitative analysis: the role of active categorization in theory building
”,
Academy of Management Review
,
Advance online publication
.
Hayes
,
A.F.
(
2009
), “
Beyond Baron and Kenny: statistical mediation analysis in the new millennium
”,
Communication Monographs
, Vol.
76
No.
4
, pp.
408
-
420
.
Journal of Managerial Psychology
(
2020
), “
Aims and scope
”,
available at:
https://www.emeraldgrouppublishing.com/journal/jmp#aims-and-scope (
accessed
 23 August 2020).
Kaplan
,
A.
(
1964
),
The Conduct of Inquiry
,
Harper & Row
,
New York
.
Merton
,
R.K.
(
1967
),
On Theoretical Sociology
,
Free Press
,
New York
.
Meuser
,
J.D.
,
Atwater
,
L.
,
Lowe
,
K.B.
,
Brief
,
A.B.
,
Dierdorff
,
E.C.
,
Gilson
,
L.L.
,
Lorinkova
,
N.
,
Miller
,
C.C.
,
Nahrgang
,
J.D.
,
Riggio
,
R.E.
and
Cooper-Thomas
,
H.
(
2020
),
What Is the Point of the Practical Implications?
,
Academy of Management
,
Vancouver, BC
.
Podsakoff
,
P.M.
,
MacKenzie
,
S.B.
,
Lee
,
J.-Y.
and
Podsakoff
,
N.P.
(
2003
), “
Common method biases in behavioral research: a critical review of the literature and recommended remedies
”,
Journal of Applied Psychology
, Vol.
88
No.
5
, pp.
879
-
903
.
Podsakoff
,
P.M.
,
MacKenzie
,
S.B.
and
Podsakoff
,
N.P.
(
2012
), “
Sources of method bias in social science research and recommendations on how to control it
”,
Annual Review of Psychology
, Vol.
63
, pp.
539
-
569
.
Pratt
,
M.G.
,
Kaplan
,
S.
and
Whittington
,
R.
(
2020
), “
Editorial essay: the tumult over transparency: decoupling transparency from replication in establishing trustworthy qualitative research
”,
Administrative Science Quarterly
, Vol.
65
No.
1
, pp.
1
-
19
.
Ragins
,
B.R.
(
2012
), “
Editor's comments: reflections on the craft of clear writing
”,
Academy of Management Review
, Vol.
37
No.
4
, pp.
493
-
501
, doi: .
Raudenbush
,
S.W.
and
Bryk
,
A.S.
(
2002
),
Hierarchical Linear Models: Applications and Data Analysis Methods
,
Sage
,
London
.
Sutton
,
R.I.
and
Staw
,
B.M.
(
1995
), “
What theory is not
”,
Administrative Science Quarterly
, Vol.
40
, pp.
371
-
384
.
Weiss
,
H.M.
and
Cropanzano
,
R.
(
1996
), “
An affective events approach to job satisfaction
”,
Research in Organizational Behavior
, Vol.
18
, pp.
1
-
74
.

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