A normative theory of luck

Psychologists have identified heuristics and biases that can cause people to make assumptions about factors that contribute to the success of individuals and firms, whose outcomes may have actually resulted primarily from randomness. Yet the interpretation of these biases becomes ambiguous when they represent reasonable cognitive shortcuts that offer certain advantages. This paper addresses this ambiguity by presenting four versions (weak, semi-weak, semi-strong, strong) of a normative theory of luck that integrates insights from psychology with the chance model approach to predict the circumstances under which performance non-monotonicity occurs: higher performance may not only indicate greater luck, but also lower expected merit or quality. The semi-strong version is illustrated by examining the decoupling of citations of academic publications and their impact, illuminating when higher citations indicate lower quality. We conclude by discussing the broader implications of a normative theory of luck, emphasizing strategies to address situations where people mistake luck for skill.

A Noisy Theory of Asking for Help That Explains why Many Feel Underwhelmed With the Help They Receive

Employees often feel that the help they receive at work is inadequate. Whereas previous research explains this empirical finding by referencing stereotypes or poor communication, we suggest an alternative that does not rely on biased agents: disappointment with received help may arise due to self-selection and regression to the mean. Before asking for help, employees assess whether their co-workers have the time and ability to respond. Consistent with regression to the mean, extreme beliefs are often followed by less extreme outcomes. However, employees with inflated beliefs are more likely to ask for help than employees with low or modest beliefs. Therefore, the subset of employees who act will have overly optimistic expectations, expectations that are unlikely to be met once co-workers respond. Apart from challenging conventional wisdom, this article also integrates chance and self-selection perspectives into the ongoing dialogue of help-seeking. Implications for future research, theory, and practice are discussed.

Plain Language Summary

This article presents a theory explaining the following empirical regularity: employees often feel let down with the help they receive at work. Prior research explains this effect by referencing errors in communication or cognition. We propose a simple, alternative mechanism, such that cognitive biases or communication mishaps need not be present for the pattern to emerge. Suppose employees ask for help based on a noisy signal of colleague potential—that is, a perception of whether co-workers have the motivation and ability to resolve the issue. Employees who believe potential is high will be more likely to ask for help than employees who believe potential is low. Due to regression to the mean, extreme beliefs will likely be followed by less extreme received help (in either direction). But not every employee asks for help. Only those with sufficiently high beliefs send a request—and it is those employees who have a greater chance of holding inflated assessments. Among those who ask, then, received help will appear underwhelming. Apart from challenging conventional wisdom, this article also integrates chance and self-selection perspectives into the ongoing dialogue of help-seeking. Implications for future research, theory, and practice are discussed.

Econometrics and the Growth of Firms: Perspectives from Evolutionary Economics

This article discusses recent results and future research possibilities in the areas of econometrics and firm growth, drawing on Dosi and Marengo’s “10 building blocks” of evolutionary theory. These 10 building blocks are: dynamics first!, microfoundations, realism is a virtue, bounded rationality, persistent heterogeneity, novelty in the system, selection mechanisms, emergent properties at the aggregate level, emergence of organizational forms and institutions, and coevolution across levels of analysis and timescales. As it happens, many of our comments relate to the theme of “realism is a virtue.” We also suggest, in some cases, which econometric techniques might be more appropriate for research into firm growth and performance, given these 10 building blocks.

Why Do Firms Fail to Engage Diversity? A Behavioral Strategy Perspective

The persistent failure of organizations to engage diversity—to employ a diverse workforce and fully realize its potential—is puzzling, as it creates labor-market inefficiencies and untapped opportunities. Addressing this puzzle from a behavioral strategy as arbitrage perspective, this paper argues that attractive opportunities tend to be protected by strong behavioral and social limits to arbitrage. I outline four limits—cognizing, searching, reconfiguring, and legitimizing (CSRL)—that deter firms from sensing, seizing, integrating, and justifying valuable diversity. The case of Moneyball is used to illustrate how these CSRL limits prevented mispriced human resources from being arbitraged away sooner, with implications for engaging cognitive diversity that go beyond sports. This perspective describes why behavioral failures as arbitrage opportunities can persist and prescribes strategists, as contrarian theorists, a framework for formulating relevant behavioral and social problems to solve in order to search for and exploit these untapped opportunities.

COVID-19 as External Enabler of entrepreneurship practice and research

For decades, entrepreneurship and strategy research has been dominated by agent-centric and inward-looking theoretical perspectives. The ongoing COVID-19 pandemic demonstrates the limits of this stance, as its influence on business has been both enormous and palpable. For the most part, the effects of the pandemic are no doubt negative. Business research—and presumably business practice—typically address such influence in terms of failure, resilience, and crisis management among existing businesses. Contrasting this prevalent discourse, we focus instead on positive influence of the pandemic for some emerging and new ventures. We analyze the many possible positive effects on entrepreneurship practice and highlight also positive effects on entrepreneurship research. We illustrate both positives by applying the External Enabler framework.

JEL CLASSIFICATION: L26, M13, O3, R11

From Data to Causes I: Building A General Cross-Lagged Panel Model (GCLM)

This is the first paper in a series of two that synthesizes, compares, and extends methods for causal inference with longitudinal panel data in a structural equation modeling (SEM) framework. Starting with a cross-lagged approach, this paper builds a general cross-lagged panel model (GCLM) with parameters to account for stable factors while increasing the range of dynamic processes that can be modeled. We illustrate the GCLM by examining the relationship between national income and subjective well-being (SWB), showing how to examine hypotheses about short-run (via Granger-Sims tests) versus long-run effects (via impulse responses). When controlling for stable factors, we find no short-run or long-run effects among these variables, showing national SWB to be relatively stable, whereas income is less so. Our second paper addresses the differences between the GCLM and other methods. Online Supplementary Materials offer an Excel file automating GCLM input for Mplus (with an example also for Lavaan in R) and analyses using additional data sets and all program input/output. We also offer an introductory GCLM presentation at https://youtu.be/tHnnaRNPbXs . We conclude with a discussion of issues surrounding causal inference.

Predicting the growth of high-growth SMEs: evidence from family business firms

Purpose

The purpose of this paper is to arrive at high-growth firm (HGF) and predict the growth of rapid-growth firms using the set of balance-sheet ratios.

Design/methodology/approach

The source of data came from the AIDA database, a commercial database provided by Bureau van Dijk. A total of 45,000 family business small- and medium-scale enterprises of Italy were selected for the study. Liquidity ratio, solvency ratio, firm age, cash flow, and working capital are considered as predictors of the firm growth. Probit regression is used for predicting the growth of the firms.

Findings

The result of the study indicated that the most important financial indicators were the liquidity ratio, solvency ratio, firm age, cash flow, and working capital are most important predictors of firm growth. The ROC of the model is 70.78, which shows that the model is fair.

Originality/value

The present study considers an innovative approach that considers balance sheet issued the year prior to the observation of rapid growth as predictors of firm growth (similar to the credit-scoring models, i.e. the Z-score model, to measure the probability of default).

Toward a Chance Management View of Organizational Change

Chance serves as the gate to organizational change. Based on a relational view of chance, we propose that in an organizational context, the chance to change is affected by the perceptions of change agents and the affordance of situational momentum, and that different time points of change are associated with different degrees of chance favorability. We develop a theoretical model to represent how change agents can assess the favorability of current and future momentum and how they can benefit from identifying a perceived chance by employing chance grasping, entraining, creating, or riding strategy to promote organizational change. We generate theoretical propositions to illustrate the four timing strategies of chance management. The overall contribution of this study is a chance management view of organizational change that considers change agents and situational momentum as two interdependent factors in the process of managing the chance to change.