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Aim – This empirical study explores the association between competition, business strategy, and the uses of a multiple performance measurement system in Bangladesh manufacturing firms.

Design/methodology – The study uses a questionnaire survey of 50 manufacturing companies. Data were analyzed using multiple regression analysis and other descriptive statistics.

Findings – The results suggest that greater emphasis on multiple measures for performance evaluation is associated with businesses that are facing high competition. The practices of multiple performance measures are also significantly related to the types of business strategy being followed. Specifically, firms pursuing a prospector strategy have relied more on multiple performance measures to rate business performance than the firms pursuing a defender strategy.

Practical implications – The article notes that the designers of performance measurement systems need to consider contingent factors that affect an organizations’ control system.

Originality/value – Substantiating the connection between contingent variables and the use of multiple performance measures in manufacturing firms facilitate a better acceptance of firms’ tendency toward new measurement tools. The study contributes to the performance measurement and contingency literature since it presents empirical evidence of the state of multiple performance measures with organizational contingent variables using a developing country's manufacturing sector data.

In this chapter we develop a new approach, based on the identification of strategy classes, to study how firms face multiple demands. The procedure that we propose (called Relational Class Analysis) stems from an analysis of the similarity of associative patterns across multiple observable outcomes, which reflect the underlying set of choices firms make to similarly address demands. Empirically, the study of 18 financial and extra-financial performance outcomes for 3,655 firms shows the existence of three main strategic classes. Drawing on our analysis, we redefine strategy as the set of committed decisions undertaken to resolve trade-offs between multiple concurrent objectives and discuss the implications of our approach for eight core questions for strategy and organizational theory.

In the growing debate about designing new management control systems (MCS) to include stakeholder values, there has been little discussion about information overload. Stakeholder advocates call for including more environmental and related social disclosures but do not consider how information overload might impair the use and interpretation of corporate performance measures. As we know, shareholders and boards of directors are most concerned with market data such as earnings per share, dividend rates, and market value growth. In this chapter, we assert that management control system designers must consider information overload before expanding the MCS to include social and nonfinancial disclosures.

The paradox in expanding MCS is that demand for sustainability performance measures will likely result in overload for both information preparers and information users. Corporate Social Responsibility (CSR) and similar sustainability disclosures are likely to overload MCS and overwhelm the readers and users by performance reports that include multiple dimensions.

CSR affects the design of companies' annual reports because stakeholders are increasingly concerned with how organizations address their social responsibilities and how they disclose their societal responses. Management accountants are accustomed to providing performance measures within an organization and MCS usually have an internal focus. CFOs are often not accustomed to balancing the needs of stakeholders with those of managers and owners. We suggest that companies and CFOs will face an information overload dilemma in making these determinations, and that users will be overloaded in sifting through the multiple dimensions of information that are increasingly being provided. We suggest that the bias toward financial performance measures will distort both the provision of relevant information and the use of sustainability performance measures. We modified the Epstein and Roy sustainability model (2001) to illustrate some of these potential impacts.

We note that the balanced scorecard (BSC) was developed as one such tool to reflect and communicate multiple measures. We summarize a previous study showing how managers ignored multiple performance measures in a performance scorecard study. We then relate our results to some of the information overload literature to support our suggestion that stakeholders will face many of the same information overload issues and constraints when using and processing social disclosures.

Our summary of the information overload literature results in a call for more interdisciplinary information overload research involving real-world contexts and tasks. We note that most of the extant information overload literature is restricted to discipline-based silo-oriented studies and to simplistic evaluations, brand identification, or forecasting tasks. Our study went into some depth to describe the business, its strategies and objectives, and a comparison of actual results to specific goals. As management control systems evolve or are designed to report sustainability data, the issues surrounding increasing complexity and information overload will become exponentially problematic. We suggest that future research also include consideration of information overload conditions facing preparers and disclosers of sustainability measures.

Models of value creation that have been proposed for supporting value-based management are described and analyzed, including the Balanced Scorecard, the Baldrige Quality Award Criteria, the Deming Management Method, the Service-Profit Chain, and the Skandia Intellectual Capital Model. These models are compared, their potential for guiding the identification of value drivers and performance measures for value-based management is assessed, and management issues that must be addressed if such models are to contribute to long-run value creation are explored. These issues include causally linking value drivers to each other and to financial outcomes, the extent to which the models take a dynamic, or whole-system, view of value creation, and whether multiple value drivers should be explicitly weighted and combined to form a “value index.” Finally, the substantial body of research evidence linking intangible value drivers to financial outcomes is reviewed, and some directions for further research are offered.

As state funding for public higher education has declined, there is a rising demand for accountability. Past studies have relied on indicator ratios to look at the relationship between funding and performance measures. This approach has some inherent problems that make it difficult to identify inefficiencies. This chapter will study efficiency in state systems of higher education by applying data envelopment analysis (DEA). DEA methodology converts multiple variables into a single comprehensive measure of performance efficiency and has the ability to perform benchmarking for the purpose of establishing performance goals. The advantages of DEA modeling will be shown by comparing results with those from a recent study of higher education finance based on publicly available data. DEA is shown to be feasible and implementable for studying state systems of higher education, and provides useful information in identifying “best practice” state systems and guidance for improvement. The value of DEA modeling to state policy makers and education researchers is discussed.

The increasing use of complex, nonfinancial environmental performance measures in managerial decisions motivates consideration of contextual influences that potentially impact managerial judgments in environmental settings. This study extends general evaluability theory (GET: Hsee & Zhang, 2010) to environmental accounting by investigating the combined effects of evaluation mode and incomplete supplemental evaluability information (SEI; e.g., benchmark data) on management decisions. To elaborate, evaluation mode is the display format in which the accounting information system (AIS) provides available information for analysis; e.g., a manager’s or business unit’s performance is assessed either comparatively (i.e., in joint mode) or individually (i.e., in separate mode). GET suggests more decision weight on measures containing SEI in separate mode because that evaluation mode contains less context in which to analyze information. On the other hand, more decision weight should result for measures that do not contain SEI in joint mode because that mode already contains more context for analysis (e.g., comparing multiple performances with each other). To test these predictions, experimental participants (n = 53) evaluated environmental measures for factories with similar environmental performances. To operationalize the information available in many environmental AIS, some, but not all, performance measures contained benchmark data (incomplete SEI); factories were evaluated either jointly or separately. Participants evidenced decision intransitivity; i.e., in separate evaluation mode, factories rated higher when a favorable measure contained SEI, while in joint evaluation mode, factories rated higher when a favorable measure lacked SEI. The results extend previous AIS and management accounting research by investigating contextual influences, and potential systems design elements, in judgments using environmental AIS.

Empirical evidence indicates that effective management of resources to implement strategy in a balanced scorecard (BSC) system is essential. We present a mathematical model for allocating limited resources in the BSC strategy implementation process.

The proposed facilitated negotiation model provides a systematic approach to prioritizing strategic initiatives in the design and implementation of a BSC.

Our joint decision model prioritizes strategic initiatives and concurrently calculates the optimal (or approximately optimal) set of BSC targets and weights, given multiyear resource restrictions.

The model assumes full, open, and truthful exchange of information between the parties; an assumption that may exclude many organizations.

We address an important gap in the BSC literature on how organizations can effectively link strategy to the potential constraint of resource budgets.

Quantitative models are being used in practice for allocating resources, but we are not aware of their use by organizations for allocating resources in a BSC application.

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.

This experimental study examined whether sustainability performance measures matter in managerial appraisal and bonus decisions. Participants received financial and non-financial information about four branch managers of a commercial bank, with different combinations of sustainability and financial performance. Participants perceived sustainability measures as being less important than financial ones; still, the experiment revealed that sustainability performance had some impact on appraisal and bonus decisions (albeit it mattered less than financial performance). Evaluators seemed to penalize inferior sustainability performance less than they penalized inferior financial performance. They also seemed to reward sustainability success less than financial success. These findings have practical implications for the implementation of sustainability measures in managerial evaluation systems. The experimental results indicated that incorporating these measures in evaluations does not necessarily mean they will have a sizable effect in decision-making. Results from a companion experiment suggested that organizations using a sustainability balanced scorecard for appraisal and bonus purposes might benefit from an increased emphasis on communication and evaluator training, with a focus on how sustainability performance impacts the attainment of strategic objectives.