Choice Of Performance Measures Research Articles

Measuring the Performance of Corporate Acquisitions: An Empirical Comparison of Alternative Metrics*

The choice of performance measure has long been a difficult issue facing researchers. This article investigates the comparability of four common measures of acquisition performance: cumulative abnormal returns, managers' assessments, divestment data and expert informants' assessments. Independently each of these measures indicated a mean acquisition success rate of between 44–56%, within a sample of British cross‐border acquisitions. However, with the exception of a positive relationship between managers' and expert informants' subjective assessments, no significant correlation was found between the performance data generated by the alternative metrics. In particular, ex‐ante capital market reactions to an acquisition announcement exhibited little relation to corporate managers' ex‐post assessment. This is seen to reflect the information asymmetry that can exist between investors and company management, particularly regarding implementation aspects. Overall, the results suggest that future acquisitions studies should consider employing multiple performance measures in order to gain a holistic view of outcome, while in the longer term, opportunities remain to identify and refine improved metrics.

Strategy, Choice of Performance Measures, and Performance

We examine the relationship between quality-based manufacturing strategy and the use of different types of performance measures, as well as their separate and joint effects on performance. A key part of our investigation is the distinction between financial and both objective and subjective nonfinancial measures. Our results support the view that performance measurement diversity benefits performance as we find that, regardless of strategy, firms with more extensive performance measurement systems—especially those that include objective and subjective nonfinancial measures—have higher performance. But our findings also partly support the view that the strategy-measurement “fit” affects performance. We find that firms that emphasize quality in manufacturing use more of both objective and subjective nonfinancial measures. However, there is only a positive effect on performance from pairing a qualitybased manufacturing strategy with extensive use of subjective measures, but not with objective nonfinancial measures.

Disparate Measures: Public Managers and Performance-Measurement Strategies

Over the past two decades, many studies have investigated the scope and significance of performance measurement in public organizations. Nonetheless, there is more to learn about the challenges facing public managers who want to measure organizational outputs and use the feedback to improve performance. Specifically, managers are often faced with redundant measures of the same output, each of which may be preferred by a different political principal or stakeholder. Furthermore, a manager's choice of measures can have serious consequences for both the estimation of agency problems and the success of programmatic solutions. We test these assertions in an analysis of educational organizations in Texas. We find that managers’ assessments of organizational performance and decisions regarding solutions depend on the choice of performance measures.

Analysis and Comparison of Microscopic Traffic Flow Models with Real Traffic Microscopic Data

The evermore widespread use of microscopic traffic simulation in the analysis of road systems has refocused attention on submodels, including car-following models. The difficulties of microscopic-level simulation models in the accurate reproduction of real traffic phenomena stem not only from the complexity of calibration and validation operations but also from the structural inadequacies of the submodels themselves. Both of these drawbacks originate from the scant information available on real phenomena because of the difficulty with the gathering of accurate field data. In this study, the use of kinematic differential Global Positioning System instruments allowed the trajectories of four vehicles in a platoon to be accurately monitored under real traffic conditions on both urban and extraurban roads. Some of these data were used to analyze the behaviors of four microscopic traffic flow models that differed greatly in both approach and complexity. The effect of the choice of performance measures on the m...

Analysis and Comparison of Microscopic Traffic Flow Models with Real Traffic Microscopic Data

The evermore widespread use of microscopic traffic simulation in the analysis of road systems has refocused attention on submodels, including car-following models. The difficulties of microscopic-level simulation models in the accurate reproduction of real traffic phenomena stem not only from the complexity of calibration and validation operations but also from the structural inadequacies of the submodels themselves. Both of these drawbacks originate from the scant information available on real phenomena because of the difficulty with the gathering of accurate field data. In this study, the use of kinematic differential Global Positioning System instruments allowed the trajectories of four vehicles in a platoon to be accurately monitored under real traffic conditions on both urban and extraurban roads. Some of these data were used to analyze the behaviors of four microscopic traffic flow models that differed greatly in both approach and complexity. The effect of the choice of performance measures on the model calibration results was first investigated, and intervehicle spacing was shown to be the most reliable measure. Model calibrations showed results similar to those obtained in other studies that used test track data. Instead, validations resulted in higher deviations compared with those from previous studies (with peaks in cross validations between urban and extraurban experiments). This confirms the need for real traffic data. On comparison of the models, all models showed similar performances (i.e., similar deviations in validation). Surprisingly, however, the simplest model performed on average better than the others, but the most complex one was the most robust, never reaching particularly high deviations.

A contingency model of the association between strategy, environmental uncertainty and performance measurement: impact on organizational performance

From a contingency framework, this paper attempts to contribute to a stream of literature that investigates determinants and consequences of performance measures. In general, it investigates the role of the choice of performance measures on the relationship between (a) strategic priorities and performance and (b) environmental uncertainty and performance. Two hypotheses are developed concerning this general relationship, predicting, respectively, a positive relationship between business unit strategy and performance through management’s choice of non-financial measures of performance ( H1) and a positive relationship between environmental uncertainty and performance through management’s choice of non-financial measures of performance ( H2). To test these hypotheses, a path analytical model is applied to questionnaire survey data from 52 manufacturing companies. As hypothesized, the results revealed the existence of a significant and positive association between management’s strategic choice and performance acting through management’s high use of non-financial measures for performance evaluation. On the other hand, the study found no evidence of a significant relationship between environmental uncertainty and performance through management’s use of non-financial performance measures.

The Measurement Gap in Paying for Performance: Actual and Preferred Measures

What is measured gets managed – especially if rewards depend on it. For this reason many companies (over 70% in this survey) have upgraded their performance measurement systems so as to include a mix of financial and non-financial metrics. This study compares how companies currently measure performance for compensation purposes with how their managers think performance should be measured. We find significant measurement gaps between actual and preferred measures, and we find that larger measurement gaps are related to lower overall performance. The choice of performance measures for compensation purposes is also related to the attitudes of managers towards manipulation of reported results.

Determinants of Control System Design in Divisionalized Firms

We investigate two determinants of two choices in the control system of divisionalized firms, namely decentralization and use of performance measures. The two determinants are those identified in the literature as important to control system design: (1) information asymmetries between corporate and divisional managers and (2) division interdependencies. We treat decentralization and performance measurement choices as endogenous variables and examine the interrelation among these choices using a simultaneous equation model. Using data from 78 divisions, our results indicate that decentralization is positively related to the level of information asymmetries and negatively to intrafirm interdependencies, while the use of performance measures is affected by the level of interdependencies among divisions within the firm, but not by information asymmetries. We find some evidence that decentralization choice and use of performance measures are complementary.

Assessing workforce perception of total quality-based performance measurement: A case study of a customer equipment servicing organization

Performance measurement has been identified as a key agent in attempts to manage organizational learning and business strategic change. The introduction of total quality (TQ)-based management frequently requires a change in organizational culture and management style, and performance measurement can be seen either to inhibit or facilitate this. A case study analysis is reported for performance measurement in the Division of Customer Equipment Services (CES) at Company K International, including a survey of workforce perception of the effectiveness of the existing approach to performance measurement and a 5-step model of performance measurement process. These steps are: TQM strategy development and goal deployment, performance information received, process management measurement, key results extraction, and reward and recognition of performance. Organizational learning and teamwork are also involved. The workforce survey found generally positive attitudes to performance measurement but there were some perceived problems, including a generally perceived over-emphasis on financial measures, and under-emphasis on Customer Satisfaction, Quality, and Employee Relations. There were perceived deficiencies in personal performance measurement and, by implication, in the linkage to Reward and Recognition. These may reflect the exclusion of 58% of the respondent sample from the company's formal appraisal system, which only extends down as far as middle management. The reports by Field Engineers are likely to be the main customer-facing contact and, at the operational "sharp end', their potential alienation from the TQM process should be of special concern. Involvement of the workforce in the choice of performance measures is generally regarded as critical for effective performance measurement design and implementation. It could be expected that employees would have a greater regard for the use of performance information within CES if they were part of the measurement design process.

Corporate strategies, environmental forces, and performance measures: a weighting decision support system using the k-nearest neighbor technique

The choice of performance measures is critical to formulating strategies. This paper investigates the relationship among corporate strategies, environmental forces, and the Balanced Scorecard (BSC) performance measures. Corporate strategies are explored within the framework of Miles and Snow's taxonomy, where they are categorized into prospectors, defenders, analyzers, and reactors. The relative weights for each performance measure are calculated by the use of the Analytic Hierarchy Process. A sample of 219 companies can confirm the link between corporate strategies, environmental forces, and the weights of the BSC performance measures. These weights shift depending on the nature of challenges companies face. In the light of this empirical evidence, a decision support system is proposed to help retrieve the BSC weights of the companies with similar characteristics. In order to measure the proximity between companies, a k-nearest neighbor technique is employed. This system can help find the weights of the performance measures for particular strategies.

Determinants of Performance Measure Choices in Worker Incentive Plans

This study examines the determinants of performance measure choices in worker incentive plans. The results indicate that informativeness issues such as those addressed in economic theories have a significant effect on measurement choices. However, other reasons for adopting the plans, such as upgrading the workforce and linking bonuses to the firm’s ability to pay, also influence measurement choices, as do union representation and management participation in plan design. Moreover, the factors influencing the use of specific measures vary, suggesting that the aggregate performance measure classifications commonly used in compensation research provide somewhat misleading inferences regarding performance measurement choices.

An empirical investigation of project evaluation criteria

In this article, we report on an empirical study conducted in the USA to determine the performance measures project managers commonly use to evaluate the success of their projects. Specifically, we identify project managers’ orientations toward using internal and/or customer driven measures of performance. We also investigate the priority given to these measures at different stages of a project by identifying the primary objective at those stages. In general we find that project managers’ primary success measure is quality and their most important objective is meeting customer needs. The priority given to this objective does not change during various stages of a project regardless of the project type and industry classification. The choice of performance measures, however, is influenced by project type and industry classification.

Determinants Of Performance Measure Choices In Worker Incentive Plans

This study examines some of the factors influencing the choice of performance measures in worker (non-management) incentive plans. Our sample consists of 607 incentive plans covering non-management employees and having a clear, pre-announced performance-payout link. We find that informativeness issues such as those addressed in economic theories are key factors in the selection of performance measures for worker incentive plans. However, we also find that other reasons for adopting the plan (i.e., promoting organizational change, improving the link between pay and firm performance, and upgrading the workforce) also play a role in performance measure choices, as do union representation and management participation in plan design. Moreover, the factors influencing the use of specific measures vary, suggesting that the aggregate performance measure classifications commonly used in compensation research, such as the comparison of financial versus non-financial metrics, provide somewhat misleading inferences regarding performance measurement choices.

The Post-Issue Performance of Initial Public Offering Firms in the People’s Republic of China

ABSTRACT This study seeks to identify issues related to the process of corporatization of the State-owned enterprises (SEO) and to examine the post-issue performance of initial public offering (IPO) firms in the People’s Republic of China (PRC). We have discussed in this paper various incentives and potential opportunities for earnings management during the process of corporatization. These include compliance with listing requirements for profitability, right-issue offerings, issue price and the carving out of assets in financial packaging. Based on a sample of 582 A-share IPO firms, we reject the hypothesis that the performance of IPO firms does not decline subsequent to the IPO year. To see if our results depend on the choice of performance measure, we have conducted the tests using different performance measures. Overall, our findings indicate that performance of the IPO firms in the PRC is not sustainable even after controlling for macroeconomic conditions and that there is evidence leading to possible earnings management.

Decision support for the single‐period inventory problem

The development of a decision support tool for the single‐period inventory problem is presented. The support tool allows a consideration of the following factors: empirical frequency distributions, theoretical probability distribution functions and managerial probability estimates of total demand over the period; piece‐wise linear (possibly discontinuous) cost functions. Such functions allow for the possibility of “fixed cost” elements and/or “economies/diseconomies” of scale and account for most, if not all, of the purchase cost, holding cost, salvage revenue and shortage cost functions that arise in practice; choice of performance measures; and “what‐if” analysis on the problem parameters. The support tool, which uses the Monte Carlo simulation option of Visual IFPS/Plus, is transparent and constructively simple and thus readily facilitates understanding, acceptance and implementation by management. The support tool runs under the Windows operating system and has easy access to appropriate spreadsheet and word‐processing packages for further processing and report presentation.

Interior Systems, Inc.: The Decision to Adopt EVA®

The purpose of the Interior Systems case is to introduce and critique the use of residual income measures for decision making, performance evaluation, and incentive compensation. In this case we focus on Stern Stewart's proprietary measure of residual income, Economic Value Added (EVA®). The case uses the setting of a multidivisional company that is struggling with the decision of what measure to use in performance evaluation. The company recognizes that the choice of performance measures is likely to affect managers' motivations and in turn decision making. The problem the company faces is which measure to use, especially in light of the differing key success drivers of the different divisions. The case has been used successfully at the undergraduate level, in M.B.A. programs, and in executive education programs.

Are EREITs Real Estate?

Executive Summary. This study examines the return properties of securitized real estate investment trusts (EREITs) and unsecuritized real estate for four property types: apartment, industrial, office and retail. Return properties studied include central tendency, normality, autocorrelation, the lead-lag relationship and risk-adjusted performance. The results indicate that private real estate returns display significant levels of autocorrelation, even after lower order effects have been removed. Moreover, both types of real estate exhibit levels of skewness and kurtosis inconsistent with a normal distribution. Concerning risk-adjusted performance, the choice of performance measure does matter, while choice of benchmark makes little difference. Finally, returns on private and public real estate behave differently from one another and should be treated as separate and distinct asset classes from a real estate portfolio manager's perspective.

Design of loading policies for a high-performance computer system

We use a systematic simulation study of computer-system loading policies to design a loading policy for a high-performance system. Our results illustrate the performance advantages of ‘round-robin’ disciplines, the interference caused by finite memory, and how this interference can be mitigated by using carefully selected loading policies that exploit information about job resource requirements. Our choice of performance measures allows us to assess response-time predictability and fairness as well as overall efficiency. Using the insights obtained from our study, we introduce a new type of policy, the NEST policy, which is structured to employ the principles of good scheduling, while avoiding shortcomings of commonly used approaches.

A model for service businesses

Looks at classifying service businesses and how this involves three basic service types: professional services; service shops; and mass service, uses a figure by way of explanation. Gives a further breakdown as a guide, going into a deep explanation of the hybrid types, different measures, choice of performance measures, and closing with an update. Uses easy‐to‐follow tables to give further emphasis and guidance. Closes by way of commenting favourably on the model designed for service business.

Incentives for overhead cost reduction: Setup time and lot size considerations

This paper addresses incentive issues arising in the integration of production control and process improvement on the shop floor. High overhead rate estimates identified by an activity based costing (ABC) system can result in a decision to increase lot sizes, thereby reducing setup related overhead costs. We integrate ABC and EOQ analyses to establish the circumstances under which increasing the lot size becomes a viable alternative. However, while increasing the lot size may be important for short-term competitiveness, long-term control of setup related overhead costs can be achieved only by decreasing setup time. We address the role of incentive systems in simultaneously implementing both short-term and long-term strategies. In particular, we focus on how the choice of performance measures can result in conflicts between production personnel who may be concerned with short-term cost reduction and engineering personnel who are responsible for reducing setup time. Finally, we discuss the value of group incentive systems in mitigating such conflicts.