Of Journal Editors and Editorial Boards: Who Are the Trailblazers in Increasing Editorial Board Gender Equality?

Female academics continue to be under‐represented on the editorial boards of many, but not all, management journals. This variability is intriguing, because it is reasonable to assume that the size of the pool of female faculty available and willing to serve on editorial boards is similar for all management journals. This paper therefore focuses on the characteristics of the journal editors to explain this variability; journal editors or editors‐in‐chief are the most influential people in the selection of editorial board members. The authors draw on social identity and homosocial reproduction theories, and on the gender and careers literature to examine the relationship between an editor's academic performance, professional age and gender, and editorial board gender equality. Longitudinal data are collected at five points in time, using five‐year intervals, from 52 management journals. To account for the nested structure of the data, a three‐level multilevel model was estimated. Overall, it is found that the prospects of board membership improve for women when editors are high‐performing, professionally young or female. The authors discuss these findings and their implications for management journals with low, stagnant or declining representation of women in their boards.     

Amplifying a Relational Ethic: A Contribution to PRME Praxis

Western economically driven instrumental ethics fuel the dominant institutional logic in many business schools and are associated with the negative social and environmental situation widely linked to the mode of global development. Other ethical framings have been subordinated, marginalized, or denied. Through the explicit commitment of prominent international certifying bodies of management education, educators, researchers, and practitioners will be encouraged to give increasing effect to the Principles for Responsible Management Education (PRME). The PRME is a United Nations‐led, institution‐level mechanism for reorienting the direction of business schools and for increasing both educator and student capacities to contribute to a more inclusive and sustainable mode of development globally. We propose greater emphasis be given to various forms of relational ethics from which to guide the functional aspirations of institutions. We explore the creative opportunity for institutional change by contrasting the prevailing Western economically driven instrumental institutional logic with indigenous ethical framings. We draw upon Seo and Creed's conceptual framework of institutional change to discuss two films—Mann v. Ford and Waste = Food—to bring greater attention to the generative potential of indigenous perspectives in institutional praxis. Our examples could equally invite an application of other systems of relational ethics that have been overshadowed by the current domination of economic instrumentalism in almost all realms of decision making. We conclude by providing some teaching resources that can be used or adapted for geographical‐ or disciplinary‐specific attention to the issues we raise.     

Improving Flood Risk Communication by Focusing on Prevention‐Focused Motivation

This article proposes an approach to flood risk communication that gives particular emphasis to the distinction between prevention and promotion motivation. According to E. Tory Higgins, the promotion system and the prevention system are assumed to coexist in every person, but one or the other may be temporarily or chronically more accessible. These insights have far‐reaching implications for our understanding of people's reasoning about risks. Flood risk communication framed in terms of prevention involves the notions of chance and harm, woven into a story about particular events that necessitate decisions to be more careful about safety issues and protect one's family and oneself from danger. The article describes how the insights worked out in practice, using a flood risk communication experiment among a sample from the general population in a highly populated river delta of the Netherlands. It had a posttest‐only control group design (n = 2,302). The results showed that risk communication had a large effect on the participants’ responses and that this effect was higher among chronic prevention‐focused people than among others. Any information that increased the fit between a prevention‐framed message and a person's chronic prevention motivation produced stronger situationally induced, prevention‐focused responses. This may significantly improve communication about risks. In contrast, the notion of water city projects, featuring waterside living, had more appeal to promotion‐focused people.     

10 Sociomateriality: Challenging the Separation of Technology,Work and Organization

Abstract

We begin by juxtaposing the pervasive presence of technology in organizational work with its absence from the organization studies literature. Our analysis of four leading journals in the field confirms that over 95% of the articles published in top management research outlets do not take into account the role of technology in organizational life. We then examine the research that has been done on technology, and categorize this literature into two research streams according to their view of technology: discrete entities or mutually dependent ensembles. For each stream, we discuss three existing reviews spanning the last three decades of scholarship to highlight that while there have been many studies and approaches to studying organizational interactions and implications of technology, empirical research has produced mixed and often‐conflicting results. Going forward, we suggest that further work is needed to theorize the fusion of technology and work in organizations, and that additional perspectives are needed to add to the palette of concepts in use. To this end, we identify a promising emerging genre of research that we refer to under the umbrella term: sociomateriality. Research framed according to the tenets of a sociomaterial approach challenges the deeply taken‐for‐granted assumption that technology, work, and organizations should be conceptualized separately, and advances the view that there is an inherent inseparability between the technical and the social. We discuss the intellectual motivation for proposing a sociomaterial research approach and point to some common themes evident in recent studies. We conclude by suggesting that a reconsideration of conventional views of technology may help us more effectively study and understand the multiple, emergent, and dynamic sociomaterial configurations that constitute contemporary organizational practices.     

A Systematic Literature Review on Recent Lean Research: State‐of‐the‐art and Future Directions

Lean management (LM) has attracted the interest of scientists and practitioners since 1990, when Womack et al. (Womack, J.P., Jones, D.T. and Roos, D. (1990). The Machine that Changed the World. New York, NY: Rawson Associates) popularized the Japanese manufacturing approach aimed at eliminating waste to improve operational performance and customer satisfaction. Over the years, the lean concept has evolved becoming a managerial paradigm applicable to different sectors and processes with impressive results. This heterogeneity of implementations and settings makes the recent LM literature diverse and fragmented, and an extensive analysis of the latest contributions on this field is lacking. To address this gap, the authors propose a systematic literature review (SLR) of 240 articles published in 25 peer‐reviewed academic journals from January 2003 to December 2015. The purpose is to analyse the recent trends in this area and to provide a framework that organizes lean researched issues into mature, intermediate and nascent, based on their position in the research life cycle. Starting from the gaps that the SLR highlights, the authors suggest conducting lean research in the following directions: (a) grounding lean studies on existing managerial theories; (b) addressing service settings such as banking/finance, public sector and education; (c) exploring the role of national culture through cross‐country comparisons; (d) defining and conceptualizing ‘lean‐x’ processes; (e) understanding the relationships between lean and safety/environmental issues, and (f) unveiling the effects on social outcomes. Finally, the proposed framework helps scholars find issues not sufficiently explored that require theory‐building research (to move from nascent to intermediate) or theory‐testing research (to move from intermediate to mature).     

Testing a Parametric Model Against a Nonparametric Alternative with Identification Through Instrumental Variables

This paper is concerned with inference about a function g that is identified by a conditional moment restriction involving instrumental variables. The paper presents a test of the hypothesis that g belongs to a finite‐dimensional parametric family against a nonparametric alternative. The test does not require nonparametric estimation of g and is not subject to the ill‐posed inverse problem of nonparametric instrumental variables estimation. Under mild conditions, the test is consistent against any alternative model. In large samples, its power is arbitrarily close to 1 uniformly over a class of alternatives whose distance from the null hypothesis is O(n^−1/2), where n is the sample size. In Monte Carlo simulations, the finite‐sample power of the new test exceeds that of existing tests.     

Cost‐Effective Sampling and Analysis for Mycotoxins in a Cereal Batch

The presence of hazards (e.g., contaminants, pathogens) in food/feed, water, plants, or animals can lead to major economic losses related to human and animal health or the rejection of batches of food or feed. Monitoring these hazards is important but can lead to high costs. This study aimed to find the most cost‐effective sampling and analysis (S&A) plan in the cases of the mycotoxins deoxynivalenol (DON) in a wheat batch and aflatoxins (AFB₁) in a maize batch. An optimization model was constructed, maximizing the number of correct decisions for accepting/rejecting a batch of cereals, with a budget as major constraint. The decision variables were the choice of the analytical method: instrumental method (e.g., liquid chromatography combined with mass‐spectrometry (LC‐MS/MS)), enzyme‐linked‐immuno‐assay (ELISA), or lateral flow devices (LFD), the number of incremental samples collected from the batch, and the number of aliquots analyzed. S&A plans using ELISA showed to be slightly more cost effective than S&A plans using the other two analytical methods. However, for DON in wheat, the difference between the optimal S&A plans using the three different analytical methods was minimal. For AFB₁ in maize, the cost effectiveness of the S&A plan using instrumental methods or ELISA were comparable whereas the S&A plan considering onsite detection with LFDs was least cost effective. In case of nonofficial controls, which do not have to follow official regulations for sampling and analysis, onsite detection with ELISA for both AFB₁ in maize and DON in wheat, or with LFDs for DON in wheat, could provide cost‐effective alternatives.     

Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain

We develop results for the use of Lasso and post‐Lasso methods to form first‐stage predictions and estimate optimal instruments in linear instrumental variables (IV) models with many instruments, p. Our results apply even when p is much larger than the sample size, n. We show that the IV estimator based on using Lasso or post‐Lasso in the first stage is root‐n consistent and asymptotically normal when the first stage is approximately sparse, that is, when the conditional expectation of the endogenous variables given the instruments can be well‐approximated by a relatively small set of variables whose identities may be unknown. We also show that the estimator is semiparametrically efficient when the structural error is homoscedastic. Notably, our results allow for imperfect model selection, and do not rely upon the unrealistic “beta‐min” conditions that are widely used to establish validity of inference following model selection (see also Belloni, Chernozhukov, and Hansen (2011b)). In simulation experiments, the Lasso‐based IV estimator with a data‐driven penalty performs well compared to recently advocated many‐instrument robust procedures. In an empirical example dealing with the effect of judicial eminent domain decisions on economic outcomes, the Lasso‐based IV estimator outperforms an intuitive benchmark. Optimal instruments are conditional expectations. In developing the IV results, we establish a series of new results for Lasso and post‐Lasso estimators of nonparametric conditional expectation functions which are of independent theoretical and practical interest. We construct a modification of Lasso designed to deal with non‐Gaussian, heteroscedastic disturbances that uses a data‐weighted ℓ₁‐penalty function. By innovatively using moderate deviation theory for self‐normalized sums, we provide convergence rates for the resulting Lasso and post‐Lasso estimators that are as sharp as the corresponding rates in the homoscedastic Gaussian case under the condition that logp = o(n^1/3). We also provide a data‐driven method for choosing the penalty level that must be specified in obtaining Lasso and post‐Lasso estimates and establish its asymptotic validity under non‐Gaussian, heteroscedastic disturbances.     

How Important is Selection? Experimental VS. Non‐Experimental Measures of the Income Gains from Migration

How much do migrants stand to gain in income from moving across borders? Answering this question is complicated by non‐random selection of migrants from the general population, which makes it hard to obtain an appropriate comparison group of non‐migrants. New Zealand allows a quota of Tongans to immigrate each year with a random ballot used to choose among the excess number of applicants. A unique survey conducted by the authors allows experimental estimates of the income gains from migration to be obtained by comparing the incomes of migrants to those who applied to migrate, but whose names were not drawn in the ballot, after allowing for the effect of non‐compliance among some of those whose names were drawn. We also conducted a survey of individuals who did not apply for the ballot. Comparing this non‐applicant group to the migrants enables assessment of the degree to which non‐experimental methods can provide an unbiased estimate of the income gains from migration. We find evidence of migrants being positively selected in terms of both observed and unobserved skills. As a result, non‐experimental methods other than instrumental variables are found to overstate the gains from migration by 20–82%, with difference‐in‐differences and bias‐adjusted matching estimators performing best among the alternatives to instrumental variables. (JEL: J61, F22, C21)     

Lowest Cost May Not Lower Total Cost: Using “Spackling” to Smooth Mass‐Customized Production

Consider a manufacturer who mass customizes variants of a product in make‐to‐order fashion, and also produces standard variants as make‐to‐stock. A traditional manufacturing strategy would be to employ two separate manufacturing facilities: a flexible plant for mass‐customized items and an efficient plant for standard items. We contrast this traditional focus strategy with an alternative that better utilizes capacity by combining production of mass‐customized and standard items in one of two alternate spackling strategies: (1) a pure‐spackling strategy, where the manufacturer produces everything in a (single) flexible plant, first manufacturing custom products as demanded each period, and then filling in the production schedule with make‐to‐stock output of standard products; or (2) a layered‐spackling strategy, which uses an efficient plant to make a portion of its standard items and a separate flexible plant where it spackles. We identify the optimal production strategy considering the tradeoff between the cost premium for flexible (versus efficient) production capacity and the opportunity costs of idle capacity. Spackling amortizes fixed costs of capacity more effectively and thus can increase profits from mass customization vis‐à‐vis a focus strategy, even with higher cost production for the standard goods. We illustrate our framework with data from a messenger bag manufacturer.     

Nonparametric Instrumental Regression

The focus of this paper is the nonparametric estimation of an instrumental regression function ϕ defined by conditional moment restrictions that stem from a structural econometric model E[Y−ϕ(Z)|W]=0, and involve endogenous variables Y and Z and instruments W. The function ϕ is the solution of an ill‐posed inverse problem and we propose an estimation procedure based on Tikhonov regularization. The paper analyzes identification and overidentification of this model, and presents asymptotic properties of the estimated nonparametric instrumental regression function.     

Guidelines for Improving the Power Values of Statistical Tests for Nonresponse Bias Assessment in OM Research

The assessment of nonresponse bias in survey‐based empirical studies plays an important role in establishing the credibility of research results. Statistical methods that involve the comparison of responses from two groups (e.g., early vs. late respondents) on multiple characteristics, which are relevant to the study, are frequently utilized in the assessment of nonresponse bias. We consider the concepts of individual and complete statistical power used for multiple testing and show their relevance for determining the number of statistical tests to perform when assessing nonresponse bias. Our analysis of factors that influence both individual and complete power levels, yielded recommendations that can be used by operations management (OM) empirical researchers to improve their assessment of nonresponse bias. A power analysis of 61 survey‐based research papers published in three prestigious academic operations management journals, over the last decade, showed the occurrence of very low (<0.4) power levels in some of the statistical tests used for assessing nonresponse bias. Such low power levels can lead to erroneous conclusions about nonresponse bias, and are indicators of the need for more rigor in the assessment of nonresponse bias in OM research.     

Probability of Exporting Infected Carcasses from Vaccinated Pigs Following a Foot‐and‐Mouth Disease Epidemic

Emergency vaccination is an effective control strategy for foot‐and‐mouth disease (FMD) epidemics in densely populated livestock areas, but results in a six‐month waiting period before exports can be resumed, incurring severe economic consequences for pig exporting countries. In the European Union, a one‐month waiting period has been discussed based on negative test results in a final screening. The objective of this study was to analyze the risk of exporting FMD‐infected pig carcasses from a vaccinated area: (1) directly after final screening and (2) after a six‐month waiting period. A risk model has been developed to estimate the probability that a processed carcass was derived from an FMD‐infected pig (P_carc). Key variables were herd prevalence (P_H), within‐herd prevalence (P_A), and the probability of detection at slaughter (P_SL). P_H and P_A were estimated using Bayesian inference under the assumption that, despite all negative test results, ≥1 infected pigs were present. Model calculations indicated that P_carc was on average 2.0 × 10^?5 directly after final screening, and 1.7 × 10^?5 after a six‐month waiting period. Therefore, the additional waiting time did not substantially reduce P_carc. The estimated values were worst‐case scenarios because only viraemic pigs pose a risk for disease transmission, while seropositive pigs do not. The risk of exporting FMD via pig carcasses from a vaccinated area can further be reduced by heat treatment of pork and/or by excluding high‐risk pork products from export.     

Estimating the causal effect of measured endogenous variables: A tutorial on experimentally randomized instrumental variables

Omitted variables create endogeneity and thus bias the estimation of the causal effect of measured variables on outcomes. Such measured variables are ubiquitous and include perceptions, attitudes, emotions, behaviors, and choices. Even experimental studies are not immune to the endogeneity problem. I propose a solution to this challenge: Experimentally randomized instrumental variables (ERIVs), which can correct for endogeneity bias via instrumental variable estimation. Such ERIVs can be generated in laboratory or field settings. Using perceptions as an example of a measured variable, I examine 74 recent articles from two top-tier management journals. The estimation methods commonly used exposed estimates to potential endogeneity bias; yet, authors incorrectly interpreted the estimated coefficients as causal in all cases. Then I demonstrate the mechanics of the ERIV procedure using simulated data and show how researchers can apply this methodology in a real experimental context.     

Does power corrupt the mind? The influence of power on moral reasoning and self-interested behavior

We test whether leaders' power shapes their reasoning about moral issues and whether such moral reasoning subsequently influences leaders' display of self-interested behavior. We use an incentivized experiment to manipulate two components of leader power: power over more versus fewer followers and power to enforce one's will by having discretion over more versus fewer payout options to allocate between oneself and one's followers. We find that having power over more followers decreased leaders' principled moral reasoning, whereas having higher power to enforce one's will enabled leaders to engage in self-interested behavior. We also find suggestive evidence that power over increases self-interested behavior by decreasing principled moral reasoning; the effect of power to was not mediated by moral reasoning. These results illustrate that power activates self-interest within and outside the context in which power is held. They also show that moral reasoning is not a stable cognitive process, but that it might represent an additional path via which power affects self-interested behavior.     

Developing a Human‐centred and Science‐based Approach to Design: The Knowledge Management Platform Project

The gap between theory and practice is a persistent problem in management and organization research. In this respect, several scholars have suggested that ‘design’ is an ideal‐typical form of mode 2 knowledge production. Design research develops knowledge in the service of action and problem solving in organizational settings. In this paper, we connect two perspectives on design that can be considered to be largely complementary but have hardly been combined and integrated in practice: science‐based design drawing on design propositions grounded in research and human‐centred design emphasizing an active and systematic participation by users and other stakeholders. An integrated approach that builds on both perspectives is developed and subsequently applied to designing and developing a portal for mapping competencies in an information technology cluster. This project involves creating problem awareness and articulating design propositions as well as developing scenarios of use, experimenting with prototypes, and organizational transformation. As such, this methodology addresses the dual challenge of rigour and relevance by producing both scientific and practical knowledge.     

Improving Risk Management: From Lame Excuses to Principled Practice

The three classic pillars of risk analysis are risk assessment (how big is the risk and how sure can we be?), risk management (what shall we do about it?), and risk communication (what shall we say about it, to whom, when, and how?). We propose two complements as important parts of these three bases: risk attribution (who or what addressable conditions actually caused an accident or loss?) and learning from experience about risk reduction (what works, and how well?). Failures in complex systems usually evoke blame, often with insufficient attention to root causes of failure, including some aspects of the situation, design decisions, or social norms and culture. Focusing on blame, however, can inhibit effective learning, instead eliciting excuses to deflect attention and perceived culpability. Productive understanding of what went wrong, and how to do better, thus requires moving past recrimination and excuses. This article identifies common blame‐shifting “lame excuses” for poor risk management. These generally contribute little to effective improvements and may leave real risks and preventable causes unaddressed. We propose principles from risk and decision sciences and organizational design to improve results. These start with organizational leadership. More specifically, they include: deliberate testing and learning—especially from near‐misses and accident precursors; careful causal analysis of accidents; risk quantification; candid expression of uncertainties about costs and benefits of risk‐reduction options; optimization of tradeoffs between gathering additional information and immediate action; promotion of safety culture; and mindful allocation of people, responsibilities, and resources to reduce risks. We propose that these principles provide sound foundations for improving successful risk management.     

Adversarial Risk Analysis with Incomplete Information: A Level‐k Approach

This article proposes, develops, and illustrates the application of level‐k game theory to adversarial risk analysis. Level‐k reasoning, which assumes that players play strategically but have bounded rationality, is useful for operationalizing a Bayesian approach to adversarial risk analysis. It can be applied in a broad class of settings, including settings with asynchronous play and partial but incomplete revelation of early moves. Its computational and elicitation requirements are modest. We illustrate the approach with an application to a simple defend‐attack model in which the defender's countermeasures are revealed with a probability less than one to the attacker before he decides on how or whether to attack.     

Does It Pay to Be Moral? How Indicators of Morality and Competence Enhance Organizational and Work Team Attractiveness

Based on a social identity analysis, the authors argue that people are attracted to teams and organizations with positive features. Such features can refer to the competence and achievements of the organization, or to its moral values and ethical conduct. However, in work contexts, ethics and achievements do not necessarily go together. The paper reports three studies that examine the relative and combined impact of perceived competence vs morality of a team or organization on its attractiveness to individuals. Study 1 (n = 44) reveals that students prefer to seek employment in a moral rather than a competent organization, when forced to choose between these organizational features on a bipolar scale. Study 2 (n = 100) replicates these findings in a design where the competence and morality of a fictitious organization were manipulated orthogonally. Study 3 (n = 89) examines responses to experimental task teams that systematically differed from each other in their competence and morality. Results of all three studies converge to demonstrate that the perceived morality of the team or organization has a greater impact on its attractiveness to individuals than its perceived competence. The authors discuss the theoretical and practical implications of these findings.