Dear colleagues,
We wanted to share a special issue in
Human Resource Management Review on inductive research in organizational sciences, which just came out in print (
http://www.sciencedirect.com/science/journal/10534822; References and abstracts are below).
Feel free to download our guest editorial at the following link (it will stay alive for the next 50 days):
https://authors.elsevier.com/a/1UduX3lYBnHvzD Given the active, ongoing conversations about doing better science in our field (e.g., Antonakis, 2017; Hollenbeck & Wright, 2016), we feel that this volume might be of interest to some of you. Would appreciate hearing from you if you have any thoughts to share.
Thanks!
Sang, Ernest, and Paul
Woo, S. E., O'Boyle, E. H., & Spector, P. E. (2017). Best practices in developing, conducting, and evaluating inductive research. Human Resource Management Review, 27(2), 255-264. doi:http://dx.doi.org/10.1016/j.hrmr.2016.08.004 This editors' introductory article to the Human Resources Management Review special issue on inductive research methods aims not only to provide an overview of the four main articles, but to provide guidance to researchers and gatekeepers about how best to conduct such research. We address four specific goals in the current article. First, we present a brief overview of each of the four papers. Second, we provide a general background on deduction, induction, and abduction: what they are, how they are distinguished from one another and should be used in a complementary manner, and how our field has moved away from inductive toward deductive paradigms over the last five decades. Third, we shed further light on the current representations of deductive versus inductive approaches in our collective published works, and what can/should be done to achieve a better balance between them as we move forward. Fourth, we offer several "best-practice" recommendations for how best to conduct and evaluate research that does not conform to the prevailing hypothetico-deductive model.
Folger, R., & Stein, C. (2017). Abduction 101: Reasoning processes to aid discovery. Human Resource Management Review, 27(2), 306-315. doi:http://dx.doi.org/10.1016/j.hrmr.2016.08.007 We propose that the process of abduction is a useful tool for how management scholars can better develop new explanatory hypotheses and theories. In doing so, we differentiate abduction from the more commonly studied methods of deduction and induction. We briefly explain the various research streams on abductive reasoning and propose a version that is focused more on the process of abductive reasoning and less on the outcomes. We argue that by using contrastive reasoning and by recognizing different triggers of abduction, this process can help guide researchers to the types of causal explanations that are interesting. We conclude with some examples of abduction in the history of management research and a discussion of features of the reasoning processes involved.
Jebb, A. T., Parrigon, S., & Woo, S. E. (2017). Exploratory data analysis as a foundation of inductive research. Human Resource Management Review, 27(2), 265-276. doi:http://dx.doi.org/10.1016/j.hrmr.2016.08.003 Across academic disciplines, scientific progress is maximized when there is a balance between deductive and inductive approaches. To promote this balance in organizational science, rigorous inductive research aimed at phenomenon detection must be further encouraged. To this end, the present article discusses the logic and methods of exploratory data analysis (EDA), the mode of analysis concerned with discovery, exploration, and empirically detecting phenomena in data. We begin by first describing the historical and conceptual background of EDA. We then discuss two issues related to EDA and its relationship to scientific credibility. First, we argue that EDA fosters a replication-based science by requiring cross-validation and by emphasizing the natural uncertainty of data patterns. Second, we clarify that EDA is distinguishable from other exploratory practices that are considered scientifically questionable (e.g., "p-hacking", "data fishing" and "data-dredging"). In the following section of the paper, we present a final argument for EDA: that it helps maximize the value of data. To illustrate this point, we present several graphical methods for detecting data patterns and provide references to further techniques for the interested reader.
McAbee, S. T., Landis, R. S., & Burke, M. I. (2017). Inductive reasoning: The promise of big data. Human Resource Management Review, 27(2), 277-290. doi:http://dx.doi.org/10.1016/j.hrmr.2016.08.005
Theory is a cornerstone of organizational research. Recently, however, some organizational scientists have argued that there is an overemphasis on theory development in our prominent publication outlets, calling for a rejuvenation of empirically driven research. To bring empirical research back to the forefront, the organizational sciences need a shock to the system: the advent of big data analytics in organizations provides just such a shock. The purpose of the following paper is to advocate for big data analytics as tools that can be used to support inductive research methods in the organizational sciences. We then highlight areas of organizational research and practice in which big data analytics can have an impact, provide readers with a tempered perspective on big data in the organizational sciences, and suggest a number of ways that researchers, reviewers, and editors can prepare themselves for the introduction of big data research in the organizational sciences.
Murphy, C., Klotz, A. C., & Kreiner, G. E. (2017). Blue skies and black boxes: The promise (and practice) of grounded theory in human resource management research. Human Resource Management Review, 27(2), 291-305. doi:http://dx.doi.org/10.1016/j.hrmr.2016.08.006 We provide an overview of the grounded theory approach, a methodology with significant (and largely untapped) potential for human resources (HR) research. Grounded theory is an abductive, data-driven, theory-building approach that can serve as a conceptual link between inductive and deductive research approaches. We begin by explaining the grounded theory approach in detail and outlining two versions of the method that have been used in high-impact management publications-the Gioia approach and the Tabula Geminus (twin slate) approach. We then provide an overview of the similarities and differences between grounded theory and other inductive and/or qualitative methodologies, namely, ethnography, discourse analysis, rhetorical analysis, and content analysis. Following this discussion, we offer a step-by-step guide to using grounded theory in human resources research, illustrating these principles with data and processes from extant research. Finally, we conclude by discussing best practices for achieving rigor with the grounded theory approach.
-- Sang Eun Woo, PhD Associate Professor Industrial and Organizational Psychology Department of Psychological Sciences Purdue University 703 Third Street West Lafayette, IN 47907-2081 Office: (765) 494-3126 Mobile: (217) 390-5985