Industry competition and firm conduct: Joint determinants of risk–return relations

• Author: Thorbjørn Knudsen,Michael Christensen,Nils Stieglitz,Ulrik W. Nash
• Date: 01 December 2020
• Published date: 01 December 2020
• DOI: http://doi.org/10.1002/smj.3184

RESEARCH ARTICLE

Industry competition and firm conduct: Joint

determinants of risk–return relations

Michael Christensen

1

| Thorbjørn Knudsen

1

|

Ulrik W. Nash

1

| Nils Stieglitz

2

1

Department of Marketing and

Management, Strategic Organization

Design Unit (SOD), Danish Institute for

Advanced Study (DIAS), University of

Southern Denmark, Odense M, Denmark

2

Frankfurt School of Finance and

Management, Frankfurt am Main,

Germany

Correspondence

Thorbjørn Knudsen, Department of

Marketing and Management, Strategic

Organization Design Unit (SOD), Danish

Institute for Advanced Study (DIAS),

University of Southern Denmark,

Campusvej 55, DK-5230 Odense M,

Denmark.

Email: tok@sam.sdu.dk

Funding information

Danish Council for Independent Research

Abstract

Research Summary: In this study, we offer a novel

approach, establishing how firm conduct and competi-

tive interactions among firms jointly provide micro-

foundations of risk–return relations. Firms influence

each other, and the way they reciprocate these influ-

ences to cause mutual adjustments is a core feature of

industry dynamics. This core feature fundamentally

influences risk–return relations. Based on our

approach, we develop models that allow us to trace

how, at the microlevel, firm conduct in conjunction

with competitive interactions generate risk–return rela-

tions, and how these are associated with macrolevel

measures of industry concentration. That translates

into an approach that affords fine-grained predictions

of risk–return relations based on the nature of competi-

tion in an industry—for example, Cournot or

Bertrand—and observations of the industry's competi-

tive intensity and concentration.

Managerial Summary: The risk-return trade-off is of

critical importance for strategic management. Yet, the

relation between industry conditions and the shape of

risk-return relations is often unclear. We develop a

framework that allows managers to understand how

industry conditions generate risk-return relations, and

how these can be inferred from macro-level measures

of industry concentration. At the micro-level, we show

that low variation in operational implementation of

strategies may, under some conditions, be associated

Received: 23 August 2016 Revised: 27 March 2020 Accepted: 28 April 2020 Published on: 6 July 2020

DOI: 10.1002/smj.3184

Strat Mgmt J. 2020;41:2315–2338. wileyonlinelibrary.com/journal/smj © 2020 John Wiley & Sons, Ltd. 2315

with high variation as well as high means in financial

returns. Our primary insight is that the risk-return

trade-off changes with competitive intensity: Starting

from industries with two or three firms, we show that

increasing competitive intensity –higher number of

firms, higher entry and exit barriers –gives rise to a

predictable sequence of risk-return relations that

change over the life-cycle of industries. Overall, we

contribute a framework that allows managers to infer

the risk-return trade-off for the industry that their busi-

ness units are located in.

KEYWORDS

Bertrand, Bowman paradox, Cournot, firm conduct, industry

competition, reflection effect, risk–return

1|INTRODUCTION

Over more than three decades after Bowman (1980) observed negative correlations between the

mean (return) and variance (risk) of accounting-based measures, numerous studies have inves-

tigated risk–return relations (e.g., Andersen, Denrell, & Bettis, 2007; Bromiley, 1991;

Fiegenbaum and Thomas 1985, 1986; Gooding, Goel, & Wiseman, 1996; Patel, Li, & Park, 2017).

The literature is extensive, and the facts are well known. To reiterate the facts, empirical studies

continue to find negative risk–return relations, but also continue to report positive and

U-shaped risk–return. Some scholars have raised concerns that these empirical findings are

artifacts of spurious correlations (e.g., Henkel, 2009). Yet, even when correcting for spurious

correlations, recent empirical studies continue to find evidence for negative and U-shaped risk–

return relations (see, e.g.. Holder, Petkevich, & Moore, 2016; Patel et al., 2017).

As this summary of the literature highlights, risk–return relations vary across industries.

But why are risk–return relations negative in some industries, positive in others, and why

do we sometimes see U-shaped risk–return relations? The contingent nature of this phe-

nomenon suggests that risk–return relationships vary with industry settings, but how do we

explain this? Facing up to this challenging problem, Andersen et al. (2007) introduced a

theoretical explanation and a “strategic fit model”that can explain and predict how risk–

return relationships will play out under specific environmental conditions in different set-

tings. They showed that heterogeneity in strategic responsiveness—a firm's ability to obtain

strategic fit to environmental conditions—leads to a negative correlation between mean and

variance of performance and that the magnitude of this negative correlation varies with the

level of dynamism in the environment. The strategic fit model convincingly demonstrated

that variation in firms' strategic conduct is a possible driver of risk–return relations. This

model also has elements relating to competition, but it does not explicitly capture competi-

tive interactions. Thus, a deeper understanding of competition—and how competition in

different industry settings shapes associations between risk and return—remains an impor-

tant missing piece in the Bowman puzzle.

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