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Meta-Analysis as a Business Research Method  

Alexander D. Stajkovic and Kayla S. Stajkovic

Mounting complexity in the world, coupled with new discoveries and more journal space to publish the findings, have spurred research on a host of topics in just about every discipline of social science. Research forays have also generated unprecedented disagreements. For many topics, empirical findings exist but results are mixed: some show positive relationships, some show negative relationships, and some show no statistically significant relationship. How, then, do researchers go about discovering systematic variation across studies to understand and predict forces that impinge on human functioning? Historically, qualitative literature reviews were performed in conjunction with the counting of statistically significant effects. This approach fails to consider effect magnitudes and sample sizes, and thus its conclusions can be misleading. A more precise way to reach conclusions from research literature is via meta-analysis, defined as a set of statistical procedures that enable researchers to derive quantitative estimates of average and moderator effects across available studies. Since its introduction in 1976, meta-analysis has developed into an authoritative source of information for ascertaining the generalizability of research findings. Thus, it is perhaps not surprising that meta-analyses in the field of management garner, on average, three times as many citations as single studies. A framework for conducting meta-analysis explains why it should be used, outlines what it has yielded to society, and introduces the reader to a fundamental conception and a misconception. More specifics follow about data collection and study selection criteria and implications of publication bias. How to convert estimates from individual studies to a common scale to be able to average them, what to consider in choosing a meta-analytic method, how to compare the procedures, and what information to include when reporting results are presented next. The article concludes with a discussion of nuances and limitations, and suggestions for future research and practice. Science builds knowledge cumulatively from numerous studies, which, more often than not, differ in their characteristics (e.g., research design, participants, setting, sample size). Some findings are in concert and some are not. Through its quantitative foundations, conjoint with theory-guiding hypotheses, meta-analysis offers statistical means of analyzing disparate research designs and conflicting results and discovering consistencies in a seemingly inconsistent literature. Research conclusions reached by a theory-driven, well-conducted meta-analysis are almost certainly more accurate and reliable than those from any single study.

Article

Regulatory Shocks: Forms, Dynamics, and Consequences  

Nydia MacGregor and Tammy L. Madsen

Regulatory shocks, either by imposing regulations or easing them (deregulation), yield abrupt and fundamental changes to the institutional rules governing competition and, in turn, the opportunity sets available to firms. Formally, a regulatory shock occurs when jurisdictions replace one regulatory system for another. General forms of regulation include economic and social regulation but recent work offers a more fine-grained classification based on the content of regulations: regulation for competition, regulation of cap and trade, regulation by information, and soft law or experimental governance. These categories shed light on the types of rules and policies that change at the moment of a regulatory shock. As a result, they advance our understanding of the nature, scope, magnitude, and consequences of transformative shifts in rules systems governing industries. In addition to differences in the content of reforms, the assorted forms of regulatory change vary in the extent to which they disrupt an industry’s state of equilibrium or semi-equilibrium. These differences contribute to diverse temporal patterns or dynamics, an area ripe for further study. For example, a regulatory shock to an industry may be followed by rapid adjustment and, in turn, a new equilibrium state. Alternatively, the effects of a regulatory shock may be more enduring, contributing to ongoing dynamics and prolonging an industry’s convergence to new equilibrium state. As such, regulatory shocks can both stimulate ongoing heterogeneity or promote coherence within and among industries, sectors, organizational fields, and nation states. It follows that examining the content, scope, and magnitude of regulatory shocks is key to understanding their impact. Since conforming to industry regulation (deregulation) increases economic returns, firms attempt to align their policies and behaviors with the institutional rules governing an industry. Thus, regulatory shocks stimulate the evaluation of strategic choices and, in turn, impact the competitive positions of firms and the composition of industries. Following a shock, at least two generic cohorts of firms emerge: incumbents, which are firms that operated in the industry before the change, and entrants, which start up after the change. To sustain a position, entrants must build capabilities from scratch whereas incumbents must replace or modify the practices they developed in the prior regulatory era. Not surprisingly, the ensuing competitive dynamics strongly influence the distribution of profits observed in an industry and the duration of firms’ profit advantages. Our review highlights some of the prominent areas of research inquiry regarding regulatory shocks but many areas remain underexplored. Future work may benefit by considering regulatory shocks as embedded in a self-reinforcing system rather than simply an exogenous inflection in an industry’s evolutionary trajectory. Opportunities also exist for studying how the interplay of industry actors with actors external to an industry (political, social) affects the temporal and competitive consequences of regulatory shocks.