Advances in Accounting Behavioral Research

Khondkar E. Karim

• Publisher: Emerald Publishing Limited
• Year: 2018
• ISBN:
  9781787565456
• Topic: Commerce
• Subtopic: Commerce Général

Advances in Accounting Behavioral Research promotes research across all areas of accounting, incorporating theory from, and contributing knowledge to, the fields of applied psychology, sociology, management science, ethics and economics. Focusing on research that examines both individual and organizational behavior relative to accounting, the series provides a unique opportunity for the exchange of peer reviewed knowledge across all areas of accounting behavioral research and the development, discussion and expansion of theories from psychology, sociology and related disciplines. Advances in Accounting Behavioral Research encourages research that tests theory, explains theory, and develops theory that can be applied to better understand accounting domains. Accordingly, reviews of established theory and how that theory has and could be used in accounting are also strongly encouraged. Coverage includes, but is not restricted to:

• Individual judgement/decision making
• Group decision making
• Organizational behavior
• Inter-organizational relationships
• Technology integration
• Strategic management/organizational theory
• Theory development
• Theory review

This volume includes chapters on emerging theory, methods, and applications towards behavioral research in accounting and audit.

STRATEGY EVALUATION WHEN USING A STRATEGIC PERFORMANCE MEASUREMENT SYSTEM: AN EXAMINATION OF MOTIVATIONAL AND COGNITIVE BIASES

Lan Guo, Theresa Libby, Bernard Wong-On-Wing and Dan Yang

ABSTRACT

The multiple performance measures in strategic performance measurement systems should be selected to represent a set of causally linked strategic drivers and outcomes. The pattern of results thus can provide information concerning the proper execution of the strategy (i.e., the performance evaluation role) and the strength of the cause-and-effect linkages assumed by the strategy (i.e., the strategy evaluation role). Unfortunately, managers’ tendency to re-evaluate the strategy when performance falls short of target is low in practice. Possible explanations include motivational and cognitive biases. We experimentally examine two decision aids, an attribution aid, and a decomposition aid, designed to help managers ease these challenges. Study 1 shows the decision aids, individually and in combination, increase managers’ tendency to re-examine a problematic strategy. Study 2 demonstrates the effectiveness of the two decision aids, when used together, under a different pattern of results and among a sample of more experienced managers.

Keywords: Strategic performance; performance measurement; motivation; cognitive bias; balance scorecard; judgment and decision-making

INTRODUCTION

Strategic performance measurement systems (SPMS) such as the balanced scorecard (BSC) can serve as both a comprehensive performance measurement system and a strategic management tool (Chenhall, 2005; Ittner & Larcker, 2005; Kaplan & Norton, 2001, 1996). Organizations can use an SPMS to clarify and communicate strategy throughout the organization, set performance targets that align unit and individual objectives with the selected strategy, and periodically evaluate the strategy and identify whether a change in strategy is required. Unfortunately, managers’ use of SPMS results to assess the effectiveness of their strategy, particularly when performance falls short of target, is relatively low in practice (Campbell, Datar, Kulp, & Narayanan, 2015; Ittner & Larcker, 2005). In the current chapter, we propose and test two decision aids intended to increase managers’ tendency to use a firm’s SPMS to evaluate the quality of its strategy.¹

Much prior research has examined the use of an SPMS for performance evaluation (e.g., Banker, Chang, & Pizzini, 2004; Libby, Salterio, & Webb, 2004; Lipe & Salterio, 2000; Wong-On-Wing, Guo, Li, & Yang, 2007), while research on the strategic management function of the SPMS is relatively scarce. Studies that have examined the use of SPMS to evaluate strategy are of two main types: those that use field data to test the assumed causal relations in the business model underlying the SPMS (e.g., Campbell et al. 2015; Dikolli & Sedatole, 2007; Huelsbeck, Merchant, & Sandino, 2010) and those that examine how individual managers make strategy-related judgments and decisions using SPMS results (Cheng & Humphreys, 2012; Choi, Hecht, & Tayler, 2013; Tayler, 2010). Our study falls within this second stream of research by examining managers’ ability to interpret SPMS results from a strategic perspective and to use this information to evaluate the appropriateness of their division’s strategy.

Prior research indicates that evaluating the validity of strategy based on SPMS performance patterns may be subject to motivational and cognitive biases.² First, since upper-level managers are often involved in strategy design, self-serving attributional bias (Heider, 1958; Zuckerman, 1979) may prevent them from attributing poor outcome performance to inappropriate strategies that are (partly) designed by them. This is because external (vs internal) attribution can protect one’s self-esteem in times of failure (Pyszczynski & Greenberg, 1987; Zuckerman, 1979). Consistent with this view, Tayler (2010) finds that managers who are involved in choosing strategic initiatives view those initiatives to be more successful than those who are not involved in the selection process. Like the “attribution therapy” used by psychologists to reduce individuals’ self-serving attributional bias (e.g., Noel, Forsyth, & Kelley, 1987), we introduce a simple decision aid that directs managers’ re-attribution of poor outcome performance. We consider whether this decision aid that is similar to that used by Wong-On-Wing et al. (2007) to improve performance evaluation judgments will also improve manager’s ability to recognize they may be pursuing a failing strategy when faced with negative SPMS results. We label this our “attribution” decision aid.

Second, Kaplan and Norton (2008) argue the pattern of SPMS results should reflect the strength of the cause-and-effect linkages assumed by the firm’s strategy. If the expected correlations between driver (e.g., learning and growth and/or internal business process measures) and outcome measures (e.g., customer and financial performance measures) included in the SPMS are not observed, the existing strategy should be re-evaluated for its effectiveness. Even so, a few factors can make this apparently straightforward evaluation task cognitively challenging: (1) the SPMS usually includes a large set of measures and managers may not attend to all measures and their results simultaneously (which may result in pattern recognition difficulties), (2) the underlying business model being invalid is usually an obscure or unavailable hypothesis for managers (which may result in hypothesis generation difficulties), and (3) many managers are unfamiliar with the strategy evaluation function of the SPMS (which results in an inappropriate match between the strategy evaluation tool and manager’s level of expertise). To facilitate managers’ information processing in strategy evaluation, we design a second decision aid that decomposes this complex evaluation task into three smaller judgment components. We label this our “decomposition” decision aid.

To examine the potential effectiveness of our decision aids, we report the results of two case-based experiments where participants act as strategic business unit (SBU) managers of a chain of specialty clothing stores targeting professional women. Participants learn that the SBU manager together with corporate management designed and adopted the new growth strategy three years ago, under the assumption that most target customers are not price-sensitive. Within three years, this strategy should yield increased profits, but SPMS results indicate performance on driver measures is greater than target while performance on outcome measures is lower than target (labeled the “good driver-poor outcome pattern”), a pattern that Kaplan and Norton (2008) argue is highly indicative of a need to reconsider firm strategy due to a possible invalid strategic assumption (i.e., customers may be more price sensitive than assumed).

In Study 1, we utilize a 2 (attribution aid present/absent) × 2 (decomposition aid present/absent) experimental design. Participants are 78 MBA students with an average of 5.67 years of full-time work experience.³ Our dependent variable is the participants’ perceived need to re-examine the current strategy after considering the SPMS results. Although the case material clearly suggests potential problems with the strategy, results of Study 1 indicate that without the help of the decision aids, participants do not always consider the need to re-examine the strategy. We find that both the attribution and decomposition decision aids significantly raise the participants’ tendency to re-examine the strategy as predicted. This implies that both the self-serving attributional bias and information processing difficulties to some degree affect managers’ strategy evaluation.

In Study 2, we use a 2 (joint decision aids present/absent) × 2 (poor driver, poor outcome pattern/good driver, and poor outcome pattern) experimental design to further explore the most effective condition from Study 1 (i.e., when both decision aids are present) while adding a “poor driver-poor outcome performance pattern.” This pattern suggests a positive rather than a negative or no relationship between driver and outcome performance. If the decision aids work as theory suggests, we expect that participants using the joint decision aids will recognize the need to place less emphasis on re-examining the strategy under this poor driver-poor outcome performance pattern than under the good driver-poor outcome pattern (the pattern presented in Study 1).

Participants are 57 middle managers from 2 public companies who were participating in an executive education session. Results indicate that, similar to findings of Study 1, the use of the joint decision aids increases these more experienced managers’ tendencies to re-examine the strategy under the good driver-poor outcome performance. We also find that only with the use of the joint decision aids are managers able to place more emphasis on re-visiting the strategy under the good driver-poor outcome pattern than under the poor driver-poor outcome pattern, indicating further evidence of the effectiveness of the decision aids.

The results of the two studies reported here contribute to both research and practice. First, our results suggest that managers may suffer from both motivational biases and information processing difficulties when using an SPMS for strategy evaluation purposes. Our experiments document that even when SPMS results clearly indicate a disconnect between driver and outcome performance, managers do not always recognize the need to reassess the strategy. We also find that with the help of the attribution and/or decomposition decision aids, managers perceive a significantly higher need to re-evaluate the invalid strategy. Based on these results, we can infer that while using the SPMS to make strategy evaluation decisions, managers (both novice and more experienced ones) may encounter biases that the two decision aids were designed to overcome, that is, self-serving attributional bias, and information-processing difficulties. Although many studies (e.g., Banker et al. 2004, Libby et al. 2004, Lipe & Salterio, 2000) have examined judgment challenges in using the SPMS for performance evaluation, few studies have been conducted to understand challenges managers face when using an SPMS to evaluate strategy.

Second, from a practical standpoint, our results are important because features specific to an SPMS are expected to facilitate strategy evaluation and strategic learning (Kaplan & Norton, 2000, 2001, 2008). To obtain this intended benefit, it is important to investigate ways in which managers’ judgment biases can be addressed. Our results suggest that the attribution decision aid can reduce upper-level managers’ self-serving attributional bias while the decomposition decision aid can reduce the complexity of the strategy evaluation task, both of which help (independently and when used in tandem) to improve the quality of the manager’s strategy evaluation judgment.

The remainder of this chapter is organized as follows. The next section provides the theoretical background, which leads to the...

Table of contents

• Cover
• Editorial Advisory Board
• The Effect of Mutual Monitoring and Need for Achievement on Budgetary Slack in a Team-based Environment
• An Empirical Assessment of Employee vs Independent Contractor Status in Taxation and the Effects of Judges’ Gender, Political Affiliation, and Industry on Those Decisions
• Are Non-professional Investors’ Attitudes toward Earnings Management Consistent with Their Investing Behavior?
• Do Consulting Services Performed by Internal Auditors Influence Their Subsequent Assessments when Performing Assurance Services?
• Strategy Evaluation When Using a Strategic Performance Measurement System: An Examination of Motivational and Cognitive Biases
• Stories vs Statistics: The Impact of Anecdotal Data on Managerial Decision Making
• Index