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The purpose of this paper is to present supply chain metrics and to propose a fuzzy-based performance evaluation method for lean supply chain.

To understand the overall performance of cost competitive supply chain the paper investigates the alignment of market strategy and position of the supply chain. Since lean is applicable in many supply chains, the authors propose a set of metrics to evaluate supply chain performance. Moreover, the paper uses a fuzzy model to evaluate the performance of cost competitive supply chains. Fuzzy is an appropriate model method when uncertainty is present. It also allows modelling of a significant number of performance metrics across multiple supply chain elements and processes. Competitive strategy can be achieved by using a different weight calculation for different supply chain situations.

Research provides optimal metrics for lean supply chains. The proposed method can measure the performance of lean supply chains using a fuzzy approach and competitive strategies.

The metrics which have been selected to measure the performance of lean supply chains is particularly applicable for high volume, low-price products.

By identifying optimal performance metrics and applying performance evaluation methods, managers can predict the overall supply chain performance under lean strategy. By identifying performance for each metric they can also categorize the existing performance and optimise them accordingly.

This study provides a performance evaluation method for supply chain managers to assess the effects of lean tools and competitive strategies.

This study examines whether different strategy archetypes deploy specific performance metrics to support their strategic goals and priorities. If so, does alignment of strategy and metrics positively impact organisational performance?

The conceptual framework and hypotheses are couched in Contingency Theory. The role of business strategy as a moderating variable is tested using MANOVA, followed by post hoc pairwise comparisons. The results are based on cross-sectional survey data from 372 manufacturing and service organisations in Italy.

The overall contingency effect of business strategy in selecting and deploying performance metrics and their effect on organisational performance is supported. However, the group-wise post hoc analyses show support only for Prospectors but not for Defenders and Analysers.

This research lends further support in favour of the Contingency Theory from a new geographic context (Italy) that there are no universally best performance metrics that drive organisational performance. However, more research is needed to understand why the theory only holds for certain strategic archetypes and not across all archetypes.

Managers can direct resources and effort towards designing and deploying the “right” type of performance metrics suitable for their strategic orientation and thus optimise organisational performance.

This is a rare study that tests the moderating role of business strategy using all four strategic archetypes of the Miles and Snow typology. It deploys both financial and non-financial measures and uses a very large sample of both manufacturing and service organisations from a relatively unexplored region of the world. The study provides additional evidence in favour of the Contingency Theory whilst advocating for more research to refine our understanding of why the contingency perspective is not so important for firms that are not the first-in.

Despite all the attempts developed so far to measure corporate social performance in the last decades, a standard metric for it is still missing. In this work, the author tries to understand why is this the case. To do so, the author has reviewed 69 relevant metrics developed in the literature since the 1970s until today, covering approaches based on social, reputational, and environmental ratings, as well as several others constructed ad hoc by reputated scholars. The author analyzes each of them through a double optics, checking if they meet the minimum requirements to be considered standard and truly social. The research reveals that the main factor that prevents such a standard is the lack of truly social orientation of the existing metrics.

The purpose of this study is to evaluate whether the classification of the equity mutual fund depends on the performance measure used.

The sample for this study includes stock mutual funds for the USA, Europe and emerging market economies covering the period 2010 to 2020. Using more than 20 performance measures the results are compared using the Sharpe ratio as the reference.

The results show that performance measures based on absolute reward–risk ratios like Sortino, Treynor, etc. have similar rankings, because in general the numerator (mean excess return) is the same. However, when the authors employ other types of performance measures, results may be significantly different, especially in the case of metrics for “incremental returns”, i.e. alphas. Focussing on markets, their results show that choosing performance measures is more relevant for emerging markets.

The sample is only limited to the USA, Europe and the emerging market, and there are other performance metrics in the literature which have not been covered in this work.

The ordering of equity mutual funds depends on the measure used, specially if investors employ factor models to measure excess returns (alphas). Hence, policy formulation on disclosure of mutual fund performance should encourage the use of several metrics from different families. Investors must be aware of the different rankings made and the most appropriate metrics based on their preferences.

This paper focusses specifically on the effect that performance metrics have on relative fund performance. Previous studies have ignored alpha metrics to rank funds, which are commonly employed by investors. The authors’ study performs an analysis for three different markets considering the two main developed ones (the American and European equity markets), as well as the emerging one, largely ignored until now.

This paper aims to focus on the use of qualitative research methods to gain a better understanding of the performance management system (PMS) of one of the largest retailers in North America. The motivation for the research was to assess whether the PMS at one of the world’s largest retail companies was congruent with the most recent thinking and research in the management accounting literature.

Using open-ended interviews, the paper seeks to develop relevant hypotheses emerging from the dimensions of the Strauss and Corbin’s qualitative research methodology (1998). A qualitative methodology was used because it provides a structured approach and analytical techniques that can build upon existing theory and literature.

The qualitative evidence collected during the course of the research indicates that financial measures were predominantly used by the company in its PMS, and that this reliance on financial measures may be an artifact of the industry in which the company operates. The retail industry is highly competitive, and it is very sensitive to changes in customer tastes and behavior, as well as shareholder and financial market pressures. In addition to financial measures, it was found that operational management developed certain non-financial performance measures and that this development may have been a response by operational managers to wider stakeholder pressures and external influences. However, these performance measures appear to be not fully integrated in the PMS and are therefore de-coupled and relatively unimportant in, or entirely absent from, top-level decision-making.

The conclusions of the paper provide support for the concepts of isomorphism and de-coupling as found in the literature of new institutional theory.

The case study approach has enabled to explore and gain further understanding of management accounting practices, particularly performance measurement and management, in their natural setting. Strauss and Corbin’s (1998) grounded theory methodology was adopted because it provides a structured set of analytical steps and systematic analytical techniques for handling and interpreting data and theory building.

The purpose of this paper is to develop and describe the implementation of a novel method for creating interval-level metrics for objectively assessing police officer behaviors during an encounter with the public. These behaviors constitute officer performance and affect the probability of desirable encounter outcomes. The metrics measure concrete, micro-level performance in the common types of complex, dynamic, and low-information police-public encounters that often require immediate action using “naturalistic” decision making. Difficulty metrics also were developed to control for situational variability. The utility of measuring what officers do vs probabilistic outcomes is explored with regard to informing policymaking, field practice, and training.

Metric sets were developed separately for three types of police-public encounters: deadly force judgment and decision making, cross-cultural tactical social interaction, and crisis intervention. In each, “reverse concept mapping” was used with a different diverse focus group of “true experts” to authoritatively deconstruct implicit concepts and derive important variables. Variables then were scaled with Thurstone’s method using 198 diverse expert trainers to create interval-level metrics for performance and situational difficulty. Metric utility was explored during two experimental laboratory studies and in response to a problematic police encounter.

Objective, interval-level metric sets were developed for measuring micro-level police performance and encounter difficulty. Validation and further refinement are required.

This novel method provides a practical way to rapidly develop metrics that measure micro-level performance during police-public encounters much more precisely than was previously possible.

The metrics developed provide a foundation for measuring officers’ performance as they exercise discretion, engage people, and affect perceptions of police legitimacy.

Intense competition forces companies to become involved in supply chain collaboration with their upstream and downstream partners. The key to ensuring that the participating members are progressing on the right track of creating the best‐in‐class practice is to conduct benchmarking. Benchmarking stimulates collective learning for performance improvement that brings benefits to all participating members. However, previous research has focused mainly on supply chain benchmarking at the intra‐company ‐‐ rather than the inter‐company ‐‐ level. Inter‐company benchmarking requires a new perspective for understanding collaborative learning amongst the participating members that encourages them to improve supply chain performance as a whole. This research aims to develop a benchmarking scheme for supply chain collaboration that links collaborative performance metrics and collaborative enablers. The proposed benchmarking scheme can be used to examine the current status of supply chain collaboration among the participating members, identify performance gaps and systematize improvement initiatives.

Competitive sourcing is the government’s term for transferring the operation of an internal process or function to either an external supplier or a reengineered government team. The competitively sourced function is managed through performance metrics. These metrics must be thorough, appropriate and well designed to ensure the government is receiving the level of service required to fulfill its various missions. This research effort develops a performance metric evaluation system that was synthesized from metric design literature, Total Quality Management concepts, and the Government Performance Results Act. Use of the system in a case study is discussed along with how to evaluate the results. Results indicate that some Air Force performance metrics have insufficient and improperly designed metrics.

The purpose of this paper is to explore a host of issues related to the use of marketing metrics and firm performance in the context of the Middle East. Specifically, it seeks to explore which marketing metrics relate to perceived performance, to understand how frequency of metric reporting impacts perceived performance, to identify the impact that marketing dashboards have on perceived firm performance and to analyze how measurement ability relates to perceived performance.

This paper used an online survey administered to marketing managers at firms located in the Middle East. A total of 55 participants provided usable data. Participants provided the frequency at which 71 different marketing metrics are reported by their firms and their assessments of the firm’s performance with respect to sales growth, market share growth, and profitability. In addition, they indicated whether or not a marketing dashboard was used to report these metrics, and if so, how long ago the dashboard had been implemented. They also assessed their firm’s holistic ability to measure and use metrics compared to their competition.

As expected, marketers in the Middle East found the marketing metrics examined to vary in their usefulness as judged by their relationship to perceived performance. For those metrics that were perceived to be useful, their utility tended to peak at a moderate level of reporting frequency. These findings also varied by the type of performance considered. The use a marketing metric dashboard did not relate to perceived performance, but the frequency with which the dashboards were reported was found to have a negative linear relationship to perceived performance. Overall, the more capable respondents judged their firms to be with respect to measuring and reporting metrics, the higher their perceived performance.

This paper offers new insights into the usefulness of a wide variety of marketing metrics to marketers in the Middle East. It also provides guidance on the ideal reporting frequency for those metrics. The findings suggest that marketers in the Middle East should focus on reporting key metrics at an appropriate frequency, regardless of whether or not a dashboard format is used. If a dashboard is used, the results of this paper suggest that care should be taken that it not be reported too frequently.

This paper contributes to our understanding of how marketing metrics relate to performance. As the first such study undertaken in the context of Middle Eastern marketers, it represents an important replication and extension of previous findings in other contexts.

The purpose of this study is to provide a framework to identify performance metrics for evaluating research and development collaborations.

The framework is developed through a review of similar centres and academic studies, followed by surveys and interviews of researchers and industry practitioners for the case of the Construction Innovation Centre (CIC). The proposed framework consists of identification of existing industry research and development needs, development of a research roadmap representing top research priorities, and identification of the most important services to provide to industry partners, which form the context for defining performance evaluation metrics.

A research roadmap is presented, outlining top research areas and methods and a list of the most in-demand services including research, practical and training and outreach services. Metrics for evaluating the performance of proposed projects, completed projects and a collaborative research centre are also identified.

This study presents a novel approach to defining performance metrics for the evaluation of research and development collaborations. The approach and findings of this study can be adopted by other collaborative research centres and initiatives around the world to develop effective metrics for performance measurement. The proposed framework provides a platform for defining performance metrics in the context of the research roadmap and top-priority services applicable to the research and development collaboration.