Research Methodology References 

Academy of Management Publishing Series  

From AMJ Editors: https://journals.aom.org/journal/amj/fte-collection 

1. Colquitt, J. A., & George, G. (2011). Publishing in AMJ—part 1: topic choice. 

2. Bono, J. E., & McNamara, G. (2011). Publishing in AMJ—part 2: research design. 

3. Grant, A. M., & Pollock, T. G. (2011). Publishing in AMJ—Part 3: Setting the hook. 

4. Sparrowe, R. T., & Mayer, K. J. (2011). Publishing in AMJ—part 4: grounding hypotheses. 

5. Zhang, Y., & Shaw, J. D. (2012). Publishing in AMJ—Part 5: Crafting the methods and results. 

6. Geletkanycz, M., & Tepper, B. J. (2012). Publishing in AMJ–part 6: Discussing the implications.

7. Bansal, P., & Corley, K. (2012). Publishing in AMJ—Part 7: What's different about qualitative research?.  

8. George, G. (2012). Publishing in AMJ for non-US authors.

9. Mayer, K. J., & Sparrowe, R. T. (2013). Integrating theories in AMJ articles. 

10. Colquitt, J. A. (2013). Crafting references in AMJ submissions. 

11. Shaw, J. D., Tangirala, S., Vissa, B., & Rodell, J. B. (2018). New ways of seeing: Theory integration across disciplines. 

12. Nadkarni, S., Gruber, M., DeCelles, K., Connelly, B., & Baer, M. (2018). New ways of seeing: Radical theorizing. 

13. Shaw, J. D. (2017). Advantages of starting with theory. 

14. Tihanyi, L. (2020). From “that’s interesting” to “that’s important”. 

15. Hideg, I., DeCelles, K. A., & Tihanyi, L. (2020). From the Editors: Publishing Practical and Responsible Research in AMJ. Academy of Management Journal, 63(6), 1681-1686. 

16. George, G., Howard-Grenville, J., Joshi, A., & Tihanyi, L. (2016). Understanding and tackling societal grand challenges through management research. Academy of Management Journal, 59(6), 1880-1895. 

Academy of Management Review - Special Topic Forum Theory in Management Research 

1. Cronin, M. A., Stouten, J., & van Knippenberg, D. (2021). The theory crisis in management research: Solving the right problem. Academy of Management Review, 46(4), 667-683. 

2. Furnari, S., Crilly, D., Misangyi, V. F., Greckhamer, T., Fiss, P. C., & Aguilera, R. V. (2021). Capturing causal complexity: Heuristics for configurational theorizing. Academy of Management Review, 46(4), 778-799.

3. Haveman, H. A., Mahoney, J. T., & Mannix, E. (2021). The Evolving Science of Organization: Theory Matters. Academy of Management Review, 46(4), 660-666. 

4. Leavitt, K., Schabram, K., Hariharan, P., & Barnes, C. M. (2021). Ghost in the machine: On organizational theory in the age of machine learning. Academy of Management Review, 46(4), 750-777. 

5. Leone, P. V., Mantere, S., & Faraj, S. (2021). Open theorizing in management and organization studies. Academy of Management Review, 46(4), 725-749. 

6. Makowski, P. T. (2021). Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research. Academy of Management Review, 46(4), 702-724. 

7. Sætre, A. S., & Van de Ven, A. (2021). Generating theory by abduction. Academy of Management Review, 46(4), 684-701. 

Literature Review 

1. Bem, D. J. (1995). Writing a review article for Psychological Bulletin. Psychological Bulletin, 118(2), 172. 

2. Breslin, D., & Gatrell, C. (2020). Theorizing through literature reviews: The miner-prospector continuum. Organizational Research Methods, 1094428120943288. 

3. Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group. 2009. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ 339:332–36 

4. LePine, J. A., & King, A. W. (Eds.). (2010). Editors' comments: Developing novel theoretical insight from reviews of existing theory and research.

5. Paul, J., & Criado, A. R. (2020). The art of writing literature review: What do we know and what do we need to know?. International Business Review, 101717. 

6. Siddaway, A. P., Wood, A. M., & Hedges, L. V. (2019). How to do a systematic review: a best practice guide for conducting and reporting narrative reviews, meta-analyses, and meta-syntheses. Annual review of psychology, 70, 747-770. 

7. Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence‐informed management knowledge by means of systematic review. British journal of management, 14(3), 207-222. 

8. Webster, J., & Watson, R. T. (2002). Analyzing the past to prepare for the future: Writing a literature review. MIS quarterly, xiii-xxiii. 

9. Rousseau, D. M. (2024). Reviews as Research: Steps in Developing Trustworthy Synthesis. Academy of Management Annals. 

Construct Clarity 

1. Johnson, R. E., Rosen, C. C., Djurdjevic, E., & Taing, M. U. (2012). Recommendations for improving the construct clarity of higher-order multidimensional constructs. Human Resource Management Review, 22(2), 62-72. 

2. Law, K. S., Wong, C. S., & Mobley, W. M. (1998). Toward a taxonomy of multidimensional constructs. Academy of management review, 23(4), 741-755.

3. Suddaby, R. (Ed.). (2010). Editor's comments: Construct clarity in theories of management and organization. 

4. Yaniv, E. (2011). Construct clarity in theories of management and organization. Academy of management review, 36(3), 590-592.

5. Wong, C. S., Law, K. S., & Huang, G. H. (2008). On the importance of conducting construct-level analysis for multidimensional constructs in theory development and testing. Journal of Management, 34(4), 744-764.

Research Question

1. Alvesson, M., & Sandberg, J. (2011). Generating research questions through problematization. Academy of management review, 36(2), 247-271. 

2. Clarke, R. (2020). The challenges involved in establishing a research technique. Australasian Journal of Information Systems, 24. 

3. Kock, F., Assaf, A. G., & Tsionas, M. G. (2020). Developing courageous research ideas. Journal of Travel Research, 59(6), 1140-1146. 

4. Sandberg, J., & Alvesson, M. (2011). Ways of constructing research questions: gap-spotting or problematization?. Organization, 18(1), 23-44.

On Theory

1. Aguinis, H., & Cronin, M. A. (2022). It's the Theory, Stupid. Organizational Psychology Review, 20413866221080629.

2. DiMaggio, P. J. (1995). Comments on" What theory is not". Administrative science quarterly, 40(3), 391-397. 

3. Sutton, R. I., & Staw, B. M. (1995). What theory is not.  Administrative science quarterly, 371-384.

4. Sandberg, J., & Alvesson, M. (2021). Meanings of theory: Clarifying theory through typification. Journal of Management Studies, 58(2), 487-516. 

5. Weick, K. E. (1995). What theory is not, theorizing is. Administrative science quarterly, 40(3), 385-390. 

On Phenomena

1. Alvesson, M., & Sandberg, J. (2023). The art of phenomena construction: A Framework for Coming Up with Research Phenomena beyond ‘the Usual Suspects’. Journal of Management Studies. 

2. Fuhse, J. A. (2022). How Can Theories Represent Social Phenomena?. Sociological Theory, 40(2), 99-123. 

3. Van de Ven, A. H. (2016). Grounding the research phenomenon. Journal of Change Management, 16(4), 265-270. 

Understanding contribution 

1. Barley, S. R. (2006). When I write my masterpiece: Thoughts on what makes a paper interesting. Academy of Management Journal, 49(1), 16-20. 

2. Bergh, D. D. (2003). Thinking strategically about contribution. 

3. Colquitt, J. A., & Zapata-Phelan, C. P. (2007). Trends in theory building and theory testing: A five-decade study of the Academy of Management Journal. Academy of management journal, 50(6), 1281-1303. 

4. J.P. Cornelissen & R. Durand (2014). Moving forward: Developing theoretical contributions in management studies. Journal of Management Studies, 51 (6), 995-1022. 

5. Feldman, D. C. 2004a. What are We Talking About When We Talk About Theory? Journal of Management, 30(5): 565-567

6. Locke, K., & Golden-Biddle, K. (1997). Constructing opportunities for contribution: Structuring intertextual coherence and “problematizing” in organizational studies. Academy of Management journal, 40(5), 1023-1062. 

7. Summers, J. O. (2001). Guidelines for conducting research and publishing in marketing: From conceptualization through the review process. Journal of the Academy of Marketing Science, 29(4), 405-415. 

8. Fisher, G., & Aguinis, H. (2017). Using theory elaboration to make theoretical advancements. Organizational research methods, 20(3), 438-464. 

Theory Building

1. Arndt, J. (1985). On making marketing science more scientific: role of orientations, paradigms, metaphors, and puzzle solving. Journal of marketing, 49(3), 11-23. 

2. Bacharach, S. B. (1989). Organizational theories: Some criteria for evaluation. Academy of management review, 14(4), 496-515. 

3. Carlile, P. R., & Christensen, C. M. (2005). The cycles of theory building in management research. Division of Research, Harvard Business School. 

4. Cornelissen, J., Höllerer, M. A., & Seidl, D. (2021). What theory is and can be: Forms of theorizing in organizational scholarship. Organization Theory, 2(3), 26317877211020328. 

5. Corley, K. G., & Gioia, D. A. (2011). Building theory about theory building: what constitutes a theoretical contribution?. Academy of management review, 36(1), 12-32.  

6. Dooley, L. M. (2002). Case study research and theory building. Advances in developing human resources, 4(3), 335-354. 

7. Doty, D. H., & Glick, W. H. (1994). Typologies as a unique form of theory building: Toward improved understanding and modeling. Academy of management review, 19(2), 230-251. 

8. Fry, L. W., & Smith, D. A. (1987). Congruence, contingency, and theory building. Academy of Management Review, 12(1), 117-132. 

9. Gioia, D. A., & Pitre, E. (1990). Multiparadigm perspectives on theory building. Academy of management review, 15(4), 584-602. 

10. Lewis, M. W., & Grimes, A. I. (1999). Metatriangulation: Building theory from multiple paradigms. Academy of management review, 24(4), 672-690. 

11. Klein, K. J., Tosi, H., & Cannella Jr, A. A. (1999). Multilevel theory building: Benefits, barriers, and new developments. Academy of Management review, 24(2), 248-253. 

12. Klein, K. J., Dansereau, F., & Hall, R. J. (1994). Levels issues in theory development, data collection, and analysis. Academy of Management review, 19(2), 195-229. 

13. Locke, E. A. (2007). The case for inductive theory building. Journal of Management, 33(6), 867-890. 

14. Morgan, G. (1980). Paradigms, metaphors, and puzzle solving in organization theory. Administrative science quarterly, 605-622. 

15. Okhuysen, G., & Bonardi, J. P. (2011). The challenges of theory building through the combination of lenses. Academy of Management Review, 36(1), 6-11.

16. Oswick, C., Fleming, P., & Hanlon, G. (2011). From borrowing to blending: Rethinking the processes of organizational theory building. Academy of management review, 36(2), 318-337. 

17. Rivard, S. (2021). Theory building is neither an art nor a science. It is a craft. Journal of Information Technology, 36(3), 316-328. 

18. Shepherd, D. A., & Suddaby, R. (2017). Theory building: A review and integration. Journal of Management, 43(1), 59-86. 

19. Simon, H. 1980. Random Thoughts about Methods of Research. Pittsburgh, Unpublished Manuscript, Carnegie Mellon University: 1-10. 

20. Wacker, J. G. (1998). A definition of theory: research guidelines for different theory-building research methods in operations management. Journal of operations management, 16(4), 361-385. 

21. Weber, R. (2003). Editor's comments: The problem of the problem. MIS Quarterly, 27(1), III. 

22. Whetten, D. A., Felin, T., & King, B. G. (2009). The practice of theory borrowing in organizational studies: Current issues and future directions. Journal of Management, 35(3), 537-563. 

Theory building through Machine Learning

1. Chou, Y. C., Chuang, H. H. C., Chou, P., & Oliva, R. (2023). Supervised machine learning for theory building and testing: Opportunities in operations management. Journal of Operations Management, 69(4), 643-675. 

2. Leavitt, K., Schabram, K., Hariharan, P., & Barnes, C. M. (2021). Ghost in the machine: On organizational theory in the age of machine learning. Academy of Management Review, 46(4), 750-777. 

3. Shrestha, Y. R., He, V. F., Puranam, P., & von Krogh, G. (2021). Algorithm supported induction for building theory: How can we use prediction models to theorize?. Organization Science, 32(3), 856-880. 

4. Choudhury, Prithwiraj and Allen, Ryan and Endres, Michael, Developing Theory Using Machine Learning Methods (September 17, 2018). Available at SSRN: https://ssrn.com/abstract=3251077 or http://dx.doi.org/10.2139/ssrn.3251077 

Factor Analysis 

1. Armstrong, J. S., & Soelberg, P. (1968). On the interpretation of factor analysis. Psychological Bulletin, 70(5), 361.

2. Beavers, A. S., Lounsbury, J. W., Richards, J. K., & Huck, S. W. (2013). Practical considerations for using exploratory factor analysis in educational research. Practical Assessment, Research, and Evaluation, 18(1), 6. 

3. Costello, A. B., & Osborne, J. (2005). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical assessment, research, and evaluation, 10(1), 7. 

4. DiStefano, C., Zhu, M., & Mindrila, D. (2009). Understanding and using factor scores: Considerations for the applied researcher. Practical Assessment, Research, and Evaluation, 14(1), 20. 

5. Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological methods, 4(3), 272.

6. Osborne, J. W. (2015). What is rotating in exploratory factor analysis?. Practical Assessment, Research, and Evaluation, 20(1), 2.

Regression Analysis 

1. Liang, K. Y., & Zeger, S. L. (1993). Regression analysis for correlated data. Annual review of public health, 14(1), 43-68. 

2. Nathans, Laura L., Oswald, Frederick L., & Nimon, Kim (2012). Interpreting Multiple Linear Regression: A Guidebook of Variable Importance. Practical Assessment, Research & Evaluation, 17(9).  

3. Nimon, K. F., & Oswald, F. L. (2013). Understanding the results of multiple linear regression: Beyond standardized regression coefficients. Organizational Research Methods, 16(4), 650-674.

Structural Equation Modeling 

1. Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411-423. 

2. Credé, M., & Harms, P. D. (2015). 25 years of higher-order confirmatory factor analysis in the organizational sciences: A critical review and development of reporting recommendations. Journal of Organizational Behavior, 36(6), 845-872. 

3. Jackson, D. L., Gillaspy, J. A., & Purc-Stephenson, R. (2009). Reporting practices in confirmatory factor analysis: an overview and some recommendations. Psychological methods, 14(1), 6-23. 

4. Tomarken, A. J., & Waller, N. G. (2005). Structural equation modeling: strengths, limitations, and misconceptions. Annu Rev Clin Psychol, 1, 31-65. 

5. Ullman, J. B. (2006). Structural equation modeling: Reviewing the basics and moving forward. Journal of personality assessment, 87(1), 35-50.  

6. Williams, L. J., Vandenberg, R. J., & Edwards, J. R. (2009). 12 structural equation modeling in management research: a guide for improved analysis. The Academy of Management Annals, 3(1), 543-604. 

Advanced Structural Equation Modeling 

1. Asparouhov, T., & Muthén, B. (2009). Exploratory structural equation modeling. Structural equation modeling: a multidisciplinary journal, 16(3), 397-438. 

2. Marsh, H. W., Morin, A. J., Parker, P. D., & Kaur, G. (2014). Exploratory structural equation modeling: An integration of the best features of exploratory and confirmatory factor analysis. Annual review of clinical psychology, 10(1), 85-110. 

3. Alamer, A. (2022). Exploratory structural equation modeling (ESEM) and bifactor ESEM for construct validation purposes: Guidelines and applied example. Research Methods in Applied Linguistics, 1(1), 100005. 

Partial Least Square Structural Equation Modeling 

A good number of references are available in smartpls website. For more details visit: https://www.smartpls.com/documentation

Mediation Analysis 

1. Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of personality and social psychology,51(6), 1173.  

2. Gonzalez, O., & MacKinnon, D. P. (2018). A bifactor approach to model multifaceted constructs in statistical mediation analysis. Educational and psychological measurement, 78(1), 5-31. 

3. Hayes, A. F. (2009). Beyond Baron and Kenny: Statistical mediation analysis in the new millennium. Communication monographs, 76(4), 408-420. 

4. Malhotra, M. K., Singhal, C., Shang, G., & Ployhart, R. E. (2014). A critical evaluation of alternative methods and paradigms for conducting mediation analysis in operations management research. Journal of Operations Management, 32(4), 127-137.  

5. Mathieu, J. E., & Taylor, S. R. (2006). Clarifying conditions and decision points for mediational type inferences in organizational behavior. Journal of Organizational Behavior, 27(8), 1031-1056. MacKinnon, D. P. (2011). Integrating mediators and moderators in research design. Research on Social Work Practice, 21(6), 675-681. 

6. Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior research methods, instruments, & computers, 36(4), 717-731. 

7. Rungtusanatham, M., Miller, J. W., & Boyer, K. K. (2014). Theorizing, testing, and concluding for mediation in SCM research: Tutorial and procedural recommendations. Journal of Operations Management, 32(3), 99-113.  

8. Zhao, X., Lynch, J. G., & Chen, Q. (2010). Reconsidering Baron and Kenny: Myths and truths about mediation analysis. Journal of consumer research, 37(2), 197-206. 

Parallel Mediation Analysis

1. Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior research methods, 40(3), 879-891. 

2. Coutts, J. J., & Hayes, A. F. (2022). Questions of value, questions of magnitude: An exploration and application of methods for comparing indirect effects in multiple mediator models.  Behavior Research Methods 

Serial Mediation Analysis

1. Taylor, A. B., MacKinnon, D. P., & Tein, J. Y. (2008). Tests of the three-path mediated effect. Organizational Research Methods, 11(2), 241-269. 

Moderation Analysis 

1. Dawson, J. F. (2014). Moderation in management research: What, why, when, and how. Journal of Business and Psychology, 29(1), 1-19. 

2. Dawson, J. F., & Richter, A. W. (2006). Probing three-way interactions in moderated multiple regression: development and application of a slope difference test. Journal of Applied Psychology, 91(4), 917.

3. Murphy, K. R., & Aguinis, H. (2022). Reporting Interaction Effects: Visualization, Effect Size, and Interpretation. Journal of Management, 01492063221088516. 

4. Gardner, R. G., Harris, T. B., Li, N., Kirkman, B. L., & Mathieu, J. E. (2017). Understanding “it depends” in organizational research: A theory-based taxonomy, review, and future research agenda concerning interactive and quadratic relationships. Organizational Research Methods, 20(4), 610-638. 

5. Liu, H., & Yuan, K. H. (2021). New measures of effect size in moderation analysis. Psychological Methods, 26(6), 680. 

6. Cortina, J. M., Markell-Goldstein, H. M., Green, J. P., & Chang, Y. (2021). How are we testing interactions in latent variable models? Surging forward or fighting shy?. Organizational Research Methods, 24(1), 26-54. 

7. Pieters, C., Pieters, R., & Lemmens, A. (2022). Six methods for latent moderation analysis in marketing research: A comparison and guidelines. Journal of Marketing Research, 59(5), 941-962. 

Conditional Process Model 

1. Edwards, J. R., & Lambert, L. S. (2007). Methods for integrating moderation and mediation: a general analytical framework using moderated path analysis. Psychological methods, 12(1), 1. 

2. Hayes, A. F. (2015). An index and test of linear moderated mediation. Multivariate Behavioral Research, 50(1), 1-22. 

3. Hayes, A. F. (2018). Partial, conditional, and moderated moderated mediation: Quantification, inference, and interpretation. Communication Monographs, 85(1), 4- 40. 

4. Preacher, K. J., Rucker, D. D., & Hayes, A. F. (2007). Addressing moderated mediation hypotheses: Theory, methods, and prescriptions. Multivariate behavioral research, 42(1), 185-227. 

5. Sardeshmukh, S. R., & Vandenberg, R. J. (2016). Integrating Moderation and Mediation A Structural Equation Modeling Approach. Organizational Research Methods.

6. Cortina, J. M., Dormann, C., Markell, H. M., & Keener, S. K. (2022). Endogenous Moderator Models: What They are, What They Aren’t, and Why it Matters. Organizational Research Methods, 10944281211065111. 

7. Igartua, J. J., & Hayes, A. F. (2021). Mediation, moderation, and conditional process analysis: Concepts, computations, and some common confusions. The Spanish Journal of Psychology, 24, e49. 

Nonlinear Interaction Effect Reference

1. Haans, R. F., Pieters, C., & He, Z. L. (2015). Thinking about U: theorizing and testing U‐ and inverted U‐shaped relationships in strategy research. Strategic Management Journal. 

2. Rönkkö, M., Aalto, E., Tenhunen, H., & Aguirre-Urreta, M. I. (2022). Eight simple guidelines for improved understanding of transformations and nonlinear effects. Organizational Research Methods, 25(1), 48-87. 

Control Variables

1. Atinc, G., Simmering, M. J., & Kroll, M. J. (2012). Control variable use and reporting in macro and micro management research. Organizational Research Methods, 15(1), 57-74. 

2. Becker, T. E. (2005). Potential problems in the statistical control of variables in organizational research: A qualitative analysis with recommendations. Organizational Research Methods, 8(3), 274-289. 

3. Becker, T. E., Atinc, G., Breaugh, J. A., Carlson, K. D., Edwards, J. R., & Spector, P. E. (2016). Statistical control in correlational studies: 10 essential recommendations for organizational researchers. Journal of Organizational Behavior, 37(2), 157-167.

4. Bernerth, J. B., Cole, M. S., Taylor, E. C., & Walker, H. J. (2018). Control variables in leadership research: A qualitative and quantitative review. Journal of Management, 44(1), 131-160. 

5. Carlson, K. D., & Wu, J. (2012). The illusion of statistical control: Control variable practice in management research. Organizational research methods, 15(3), 413-435. 

6. Spector, P. E., & Brannick, M. T. (2011). Methodological urban legends: The misuse of statistical control variables. Organizational Research Methods, 14(2), 287-305. 

7. Spector, P. E. (2020). Mastering the Use of Control Variables: the Hierarchical Iterative Control (HIC) Approach. Journal of Business and Psychology, 1-14. 

Common Method Bias/ Method Variance

1. MacKenzie, S. B., & Podsakoff, P. M. (2012). Common method bias in marketing: Causes, mechanisms, and procedural remedies.. Journal of retailing, 88(4), 542-555. 

2. Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual review of psychology, 63, 539-569.

3. Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of applied psychology, 88(5), 879. 

4. Podsakoff, P. M., Podsakoff, N. P., Williams, L. J., Huang, C., & Yang, J. (2024). Common method bias: It's bad, it's complex, it's widespread, and it's not easy to fix. Annual Review of Organizational Psychology and Organizational Behavior, 11(1), 17-61. 

5. Kock, F., Berbekova, A., & Assaf, A. G. (2021). Understanding and managing the threat of common method bias: Detection, prevention and control. Tourism management, 86, 104330. 

Attention Check

1. Kung, F. Y., Kwok, N., & Brown, D. J. (2018). Are attention check questions a threat to scale validity?. Applied Psychology, 67(2), 264-283. 

2. Abbey, J. D., & Meloy, M. G. (2017). Attention by design: Using attention checks to detect inattentive respondents and improve data quality. Journal of Operations Management, 53, 63-70. 

3. Hauser, D. J., & Schwarz, N. (2016). Attentive Turkers: MTurk participants perform better on online attention checks than do subject pool participants. Behavior research methods, 48(1), 400-407. 

Formative Measurement

1. Cenfetelli, R. T., & Bassellier, G. (2009). Interpretation of formative measurement in information systems research. MIS quarterly, 689-707. 

2. Edwards, J. R., & Bagozzi, R. P. (2000). On the nature and direction of relationships between constructs and measures. Psychological methods, 5(2), 155. 

3. Finn, A., & Wang, L. (2014). Formative vs. reflective measures: Facets of variation. Journal of Business Research, 67(1), 2821-2826. 

4. Jarvis, C. B., MacKenzie, S. B., & Podsakoff, P. M. (2003). A critical review of construct indicators and measurement model misspecification in marketing and consumer research. Journal of consumer research, 30(2), 199-218. 

5. Lee, N., & Cadogan, J. W. (2013). Problems with formative and higher-order reflective variables. Journal of Business Research, 66(2), 242-247.

Item parceling in SEM

1. Little, T. D., Cunningham, W. A., Shahar, G., & Widaman, K. F. (2002). To parcel or not to parcel: Exploring the question, weighing the merits. Structural equation modeling, 9(2), 151-173. 

2. Matsunaga, M. (2008). Item parceling in structural equation modeling: A primer. Communication Methods and Measures, 2(4), 260-293. 

3. WU, Y., & WEN, Z. L. (2011). Item parceling strategies in structural equation modeling. Advances in Psychological Science, 19(12), 1859-1867.

Scale Development

1. Churchill Jr, G. A. (1979). A paradigm for developing better measures of marketing constructs. Journal of marketing research, 16(1), 64-73. 

2. Diamantopoulos, A., & Winklhofer, H. M. (2001). Index construction with formative indicators: An alternative to scale development. Journal of marketing research, 38(2), 269-277. 

3. Gerbing, D. W., & Anderson, J. C. (1988). An updated paradigm for scale development incorporating unidimensionality and its assessment. Journal of marketing research, 25(2), 186-192. 

4. Gilliam, D. A., & Voss, K. (2013). A proposed procedure for construct definition in marketing. European Journal of Marketing.

5. Hinkin, T. R. (1995). A review of scale development practices in the study of organizations. Journal of management, 21(5), 967-988. 

6. Hinkin, T. R. (1998). A brief tutorial on the development of measures for use in survey questionnaires. Organizational research methods, 1(1), 104-121. 

7. Newman, D. A., Harrison, D. A., Carpenter, N. C., & Rariden, S. M. (2016). Construct mixology: Forming new management constructs by combining old ones. Academy of Management Annals, 10(1), 943-995. 

8. Rossiter, J. R. (2002). The C-OAR-SE procedure for scale development in marketing. International journal of research in marketing, 19(4), 305-335. 

9. Worthington, R. L., & Whittaker, T. A. (2006). Scale development research: A content analysis and recommendations for best practices. The counseling psychologist, 34(6), 806-838. 

10. Bearden, W. O., & Netemeyer, R. G. (1999). Handbook of marketing scales: Multi-item measures for marketing and consumer behavior research. Sage publications (Sample Scale Development book) 

11. Lambert, L. S., & Newman, D. A. (2022). Construct development and validation in three practical steps: Recommendations for reviewers, editors, and authors. Organizational Research Methods, 10944281221115374. 

12. Carpenter, S. (2018). Ten steps in scale development and reporting: A guide for researchers. Communication methods and measures, 12(1), 25-44. 

Scale use: Best practices 

1. Haws, K. L., Sample, K. L., & Hulland, J. Scale use and abuse: Towards best practices in the deployment of scales. Journal of Consumer Psychology. 

2. Heggestad, E. D., Scheaf, D. J., Banks, G. C., Monroe Hausfeld, M., Tonidandel, S., & Williams, E. B. (2019). Scale adaptation in organizational science research: A review and best-practice recommendations. Journal of Management, 45(6), 2596-2627. 

Social Relation Modeling

1. Kenny, D. A., & La Voie, L. (1984). The Social Relations Model. Advances in Experimental Social Psychology Volume 18, 141–182. 

2. Back, M. D., & Kenny, D. A. (2010). The social relations model: How to understand dyadic processes. Social and Personality Psychology Compass, 4(10), 855-870. 

3. David Kenny: http://davidakenny.net/srm/soremo.htm

4. Other references on Social Realtions Modeling: http://davidakenny.net/doc/srmbiblio.pdf

Omitted Variable Bias

1. Busenbark, J. R., Yoon, H., Gamache, D. L., & Withers, M. C. (2021). Omitted Variable Bias: Examining Management Research With the Impact Threshold of a Confounding Variable (ITCV). Journal of Management.

Endogeneity

1. Bliese, P. D., Schepker, D. J., Essman, S. M., & Ployhart, R. E. (2020). Bridging methodological divides between macro-and microresearch: Endogeneity and methods for panel data. Journal of Management, 46(1), 70-99. 

2. Hill, A. D., Johnson, S. G., Greco, L. M., O’Boyle, E. H., & Walter, S. L. (2021). Endogeneity: A review and agenda for the methodology-practice divide affecting micro and macro research. Journal of Management, 47(1), 105-143. 

3. Rutz, O. J., & Watson, G. F. (2019). Endogeneity and marketing strategy research: An overview. Journal of the Academy of Marketing Science, 47(3), 479-498. 

4. Sande, J. B., & Ghosh, M. (2018). Endogeneity in survey research. International Journal of Research in Marketing, 35(2), 185-204. 

5. Zaefarian, G., Kadile, V., Henneberg, S. C., & Leischnig, A. (2017). Endogeneity bias in marketing research: Problem, causes and remedies. Industrial Marketing Management, 65, 39-46. 

Causal Claims or Causal Inferences 

1. Antonakis, J., Bendahan, S., Jacquart, P., & Lalive, R. (2010). On making causal claims: A review and recommendations. The leadership quarterly, 21(6), 1086-1120. 

2. Gangl, M. (2010). Causal inference in sociological research. Annual review of sociology, 36, 21-47. 

Item Response Theory Analysis 

1. Edelen, M. O., & Reeve, B. B. (2007). Applying item response theory (IRT) modeling to questionnaire development, evaluation, and refinement. Quality of life research, 16(1), 5-18. 

2. Samejima, F. (1997). Graded response model. In W. van der Linden & R. K. Hambleton (Eds.), Handbook of modern item response theory (pp. 85–100). New York: Springer. 

3. Bellamkonda, N., & Pattusamy, M. (2021). Validation of Fear of COVID-19 Scale in India: classical test theory and item response theory approach. International journal of mental health and addiction, 1-8. 

Multilevel Design

1. Kozlowski, S. W., Chao, G. T., Grand, J. A., Braun, M. T., & Kuljanin, G. (2013). Advancing multilevel research design: Capturing the dynamics of emergence. Organizational research methods, 16(4), 581-615. 

2. Hitt, M. A., Beamish, P. W., Jackson, S. E., & Mathieu, J. E. (2007). Building theoretical and empirical bridges across levels: Multilevel research in management. Academy of Management journal, 50(6), 1385-1399. 

3. Aguinis, H., & Molina-Azorín, J. F. (2015). Using multilevel modeling and mixed methods to make theoretical progress in microfoundations for strategy research. Strategic Organization, 13(4), 353-364. 

4. Molina-Azorín, J. F., Pereira-Moliner, J., López-Gamero, M. D., Pertusa-Ortega, E. M., & José Tarí, J. (2020). Multilevel research: Foundations and opportunities in management. BRQ Business Research Quarterly, 23(4), 319-333. 

5. Bélanger, F., Cefaratti, M., Carte, T., & Markham, S. E. (2014). Multilevel research in information systems: Concepts, strategies, problems, and pitfalls. Journal of the Association for Information Systems, 15(9), 1. 

Multilevel Modeling 

1. Aguinis, H., Gottfredson, R. K., & Culpepper, S. A. (2013). Best-practice recommendations for estimating cross-level interaction effects using multilevel modeling. Journal of Management, 39(6), 1490-1528. 

2. González-Romá, V., & Hernández, A. (2017). Multilevel modeling: Research-based lessons for substantive researchers. Annual Review of Organizational Psychology and Organizational Behavior, 4, 183-210. 

3. González-Romá, V., & Hernández, A. (2022). Conducting and Evaluating Multilevel Studies: Recommendations, Resources, and a Checklist. Organizational Research Methods, 10944281211060712.

4. Hayes, A. F. (2006). A primer on multilevel modeling. Human communication research, 32(4), 385-410. 

5. Mathieu, J. E., Aguinis, H., Culpepper, S. A., & Chen, G. (2012). Understanding and estimating the power to detect cross-level interaction effects in multilevel modeling. Journal of applied psychology, 97(5), 951. 

6. Peugh, J. L. (2010). A practical guide to multilevel modeling. Journal of school psychology, 48(1), 85-112. 

7. Zhang, Z., Zyphur, M. J., & Preacher, K. J. (2009). Testing multilevel mediation using hierarchical linear models: Problems and solutions. Organizational Research Methods, 12(4), 695-719. 

Mixed-Method Research 

1. Grafton, J., Lillis, A. M., & Mahama, H. (2011). Mixed methods research in accounting. Qualitative Research in Accounting & Management. 

2. Jick, T. D. (1979). Mixing qualitative and quantitative methods: Triangulation in action. Administrative science quarterly, 24(4), 602-611. 

3. Johnson, R. B., Onwuegbuzie, A. J., & Turner, L. A. (2007). Toward a definition of mixed methods research. Journal of mixed methods research, 1(2), 112-133.  

4. Leech, N. L., & Onwuegbuzie, A. J. (2009). A typology of mixed methods research designs. Quality & quantity, 43(2), 265-275.

5. Venkatesh, V., Brown, S. A., & Bala, H. (2013). Bridging the qualitative-quantitative divide: Guidelines for conducting mixed methods research in information systems. MIS quarterly, 21-54.

Other references 

1. Aguinis, H., Ramani, R. S., & Alabduljader, N. (2018). What you see is what you get? Enhancing methodological transparency in management research. Academy of Management Annals, 12(1), 83-110. 

2. Echambadi, R., Campbell, B., & Agarwal, R. (2006). Encouraging best practice in quantitative management research: An incomplete list of opportunities. Journal of Management Studies, 43(8), 1801-1820.

3. Mantere, S., & Ketokivi, M. (2013). Reasoning in organization science. Academy of management review, 38(1), 70-89. 

4. Scandura, T. A., & Williams, E. A. (2000). Research methodology in management: Current practices, trends, and implications for future research. Academy of Management journal, 43(6), 1248-1264.

5. Spector, P. E. (2019). Do not cross me: Optimizing the use of cross-sectional designs. Journal of Business and Psychology, 34(2), 125-137. 

6. Lundberg, C. C. (1976). Hypothesis creation in organizational behavior research. Academy of Management Review, 1(2), 5-12. 

Why do papers get rejected?

1. Dwivedi, Y. K., Hughes, L., Cheung, C. M., Conboy, K., Duan, Y., Dubey, R., ... & Viglia, G. (2022). How to develop a quality research article and avoid a journal desk rejection. International Journal of Information Management, 62, 102426. 

2. Kilduff, M. (2007). Editor's Comments: The Top Ten Reasons Why Your Paper Might Not Be Sent out for Review. The Academy of Management Review, 700-702. 

3. Summers, J. O. (2001). Guidelines for conducting research and publishing in marketing: From conceptualization through the review process. Journal of the Academy of Marketing Science, 29(4), 405-415. 

Peer Review Process

1. Hanafizadeh, P., & Shaikh, A. A. (2021). Developing doctoral students'/researchers’ understanding of the journal peer-review process. The International Journal of Management Education, 19(2), 100500. 

2. LaPlaca, P., Lindgreen, A., Vanhamme, J., & Di Benedetto, C. A. (2018). How to revise, and revise really well, for premier academic journals. Industrial Marketing Management, 72, 174-180. 

3. Shaw, J. D. (2012). Responding to reviewers. 

 Survey research 

1. Stantcheva, S. (2023). How to run surveys: A guide to creating your own identifying variation and revealing the invisible. Annual Review of Economics, 15(1), 205-234. 

2. Krosnick JA. 1999. Survey research. Annu. Rev. Psychol. 50:537–67

Exeperience Sampling Designs 

1. Beal, D. J. (2015). ESM 2.0: State of the art and future potential of experience sampling methods in organizational research. Annu. Rev. Organ. Psychol. Organ. Behav., 2(1), 383-407. 

2. Gabriel, A. S., Podsakoff, N. P., Beal, D. J., Scott, B. A., Sonnentag, S., Trougakos, J. P., & Butts, M. M. (2019). Experience sampling methods: A discussion of critical trends and considerations for scholarly advancement. Organizational Research Methods, 22(4), 969-1006. 

3. Fisher, C. D., & To, M. L. (2012). Using experience sampling methodology in organizational behavior. Journal of Organizational behavior, 33(7), 865-877. 

4. Ohly, S., Sonnentag, S., Niessen, C., & Zapf, D. (2010). Diary studies in organizational research. Journal of Personnel Psychology. 

5. Bolger, N., Davis, A., & Rafaeli, E. (2003). Diary methods: Capturing life as it is lived. Annual review of psychology, 54(1), 579-616. 

6. Wickham, R. E., & Knee, C. R. (2013). Examining temporal processes in diary studies. Personality and Social Psychology Bulletin, 39(9), 1184-1198. 

Silicon Sampling 

1. Sarstedt, M., Adler, S. J., Rau, L., & Schmitt, B. (2024). Using large language models to generate silicon samples in consumer and marketing research: Challenges, opportunities, and guidelines. Psychology & Marketing, 41(6), 1254-1270. 

2. Aher, G. V., Arriaga, R. I., & Kalai, A. T. (2023, July). Using large language models to simulate multiple humans and replicate human subject studies. In International Conference on Machine Learning (pp. 337-371). PMLR. 

 Academic Writing Resources 

1. Baird, A. (2021). On Writing Research Articles Well: A Guide for Writing IS Papers. Journal of the Association for Information Systems, 22(5), 1197-1211. 

2. White, L. (2005). Writes of passage: Writing an empirical journal article. Journal of Marriage and Family, 67(4), 791-798. 

3. Hahn Fox, B., & Jennings, W. G. (2014). How to write a methodology and results section for empirical research. Journal of Criminal Justice Education, 25(2), 137-156. 

4. Rogelberg, S. G., Adelman, M., & Askay, D. (2009). Crafting a successful manuscript: Lessons from 131 reviews. Journal of Business and Psychology, 24(2), 117-121. 

5. Ortinau, D. J. (2010). Primer for new authors: On the fundamentals of publishing in marketing journals. Journal of Marketing Theory and Practice, 18(1), 91-100. 

6. Summers, J. O. (2001). Guidelines for conducting research and publishing in marketing: From conceptualization through the review process. Journal of the Academy of Marketing Science, 29(4), 405-415.

7. Pollock, T. G., & Bono, J. E. (2013). Being Scheherazade: The importance of storytelling in academic writing. 

8. Barley, S. R. (2006). When I write my masterpiece: Thoughts on what makes a paper interesting. Academy of Management Journal, 49(1), 16-20. 

9. LaPlaca, P., Lindgreen, A., & Vanhamme, J. (2018). How to write really good articles for premier academic journals. Industrial Marketing Management, 68, 202-209. 

10. The University of Manchester writing resources

11. Writing in the sciences - Coursera Course

12. Zuckerman, E. W. (2017). On genre: a few more tips to article-writers. Confessions of a Supply-Side Liberal Blog. 

13. Zuckerman, E. W. (2008). Tips to Article-Writers. 

Useful Books

1. Byrne, B. M. (2010). Structural equation modeling with AMOS: basic concepts, applications, and programming (multivariate applications series). New York: Taylor & Francis Group, 396, 7384. 

2. Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2013). Applied multiple regression/correlation analysis for the behavioral sciences. Routledge. 

3. Dubin, R. (1978). Theory building (Rev. ed.). NY: Free Press. 

4. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2013). Multivariate data analysis, 7/e. Pearson India. 

5. Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. 2nd edition, Guilford Press. 

6. Huff, A. S. (1999). Writing for scholarly publication. Sage.

7. Jaccard, J., & Turrisi, R. (2003). Interaction effects in multiple regression (No. 72). Sage. 

8. Kaplan, A. (1973). The conduct of inquiry. Transaction Publishers. 

9. Kaplan, D. (2008). Structural equation modeling: Foundations and extensions (Vol. 10). Sage Publications. 

10. Kline, R. B. (2015). Principles and practice of structural equation modeling. Guilford publications. 

11. MacKinnon, D. P. (2008). Introduction to statistical mediation analysis. Routledge 

12. Monippally, M. M., & Pawar, B. S. (2008). Academic writing: A guide for management students and researchers. SAGE Publications India. 

13. Nunnally, J. C. (1994). Psychometric theory 3E. Tata McGraw-hill education.

14. Pawar, B. S. (2009). Theory building for hypothesis specification in organizational studies. SAGE Publications India. 

15. Smith, K. G., & Hitt, M. A. (Eds.). (2005). Great minds in management: The process of theory development. Oxford University Press on Demand.

16. Tabachnick, B. G., Fidell, L. S., & Ullman, J. B. (2007). Using multivariate statistics (Vol. 5, pp. 481-498). Boston, MA: Pearson. 

17. Van de Ven, A. H. (2007). Engaged scholarship: A guide for organizational and social research. Oxford University Press on Demand.

18. Venkatesh, V. (2011). Road to success: A guide for doctoral students and junior faculty members in the behavioral and social sciences. Dog Ear Publishing.

19. Viswanathan, M. (2005). Measurement error and research design. Sage.