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Many researchers have stressed the importance of using the right measures and metrics to manage a supply chain efficiently and effectively and have developed them from different perspectives. The basic purpose of this paper is to consolidate the measures and metrics that have been developed so far, verify the relevance of these measures from the practitioners, produce a usable list with proper classification (database), and demonstrate the use of this database through a case study.

An initial list of metrics and measures is consolidated after analyzing the literature (journals and books) and web sites that deal with supply chains and conducting interviews with industry practitioners. A questionnaire is designed with these measures and metrics and is sent to 300 companies within the electronics industry in Malaysia to obtain feedback from the industry practitioners about the relevance of these measures. A case study is conducted with an electronics manufacturing company to demonstrate the use of the database to identify relevant measures and metrics.

About 838 performance measures form the initial list. From these, the practitioners consider 159 important and very important measures and 135 are in use in the industry. The entire list of measures is classified into the following metrics: Fund flow, Internal process flow, Material flow, Sales and services flow, Information flow, and Partner evaluation. These metrics are further classified into different groups of measures using confirmatory factor analysis.

Only the industry practitioners from electronics industry in Malaysia participate in the study to identify the relevant measures and metrics.

The paper will be valuable to the academicians and practitioners working to develop measures and metrics for manufacturing supply chains.

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.

The purpose of this paper is to explore how to integrate the performance management (PM) process of delivery service in customer/supplier dyads.

The paper is based on a multiple case study of six customer/supplier dyads of manufacturing companies.

The analysis focuses on describing and comparing the activities of the PM process. Most activities show low levels of integration in the dyads studied. Defining metrics and target setting are considered most important to integrate. Lack of common metrics definitions and ERP deficiencies were important obstacles for integration. Research issues related to four areas of supply chain PM are discussed.

The study ends with a number of suggestions for further research on the PM process in supply chains. Proceeding into these studies is necessary for increasing knowledge about PM.

The paper reveals practical problems and outlines practical issues in integrating and handling the PM process in dyads, especially when measuring delivery service using the on‐time delivery metric. It also presents a model for describing and integrating the PM process and its activities.

Practical implications and generation of multiple issues for further research applying a dyadic approach in supply chain PM, a research approach that is quite uncommon.

The purpose of this article is to propose a common framework for the empirical analysis of supply chain performance measurement systems used in different supply chain contexts.

This is a conceptual paper, which includes an extensive literature review and an illustrative case study. The content, context, process framework is applied to structure the body of knowledge and the case study.

Supply chain performance measurement is a context‐dependent process, tailored to specific supply chain requirements. To understand how a performance measurement system in a supply chain has developed and is used there is a need to capture its context, process and content.

The framework is illustrated by a single case study. Further empirical research is required to fully appreciate the breadth of application of this framework.

The proposed framework can help to develop performance measurement systems that are suitable for certain organisational and supply chain contexts in which a company operates, as well as to compare different systems used across different supply chains.

The paper demonstrates an approach for analysing existing supply chain performance measurement systems that can be applied across different supply chains and sectors. This will create an opportunity to use a consistent data collection process across a variety of supply chain situations and thus generate data for further theory development.

The relationship between supply chain management (SCM) competency and firm performance is not well established empirically. This is largely because proven metrics for quantifying the effects of SCM are scarce. Drawing on the strategic managerial concept of supply chain orientation as a source of competitive advantage, this paper aims to apply three independent sources of secondary data to examine the influence of SCM competency on two important firm performance metrics: customer satisfaction and shareholder value.

SCM competency is assessed with data from the expert opinion element of Gartner Supply Chain Group's (formerly AMR Research) supply chain top 25 rankings; the American Customer Satisfaction Index (ACSI) database and the recently developed Economic Value Added (EVA) Momentum financial metric are utilized as outcome measures.

Firms recognized by peers and experts for superior SCM competency exhibit higher levels of customer satisfaction and shareholder value than their respective industry averages.

Further evidence is required to prove causality does exist between these variables. Limitations associated with the use of secondary data restricted the number of top performer firms available for this analysis. Nevertheless, the strong correlations found between SCM competency and two critical firm performance metrics may help senior managers and managers from other functional areas to better understand potential advantages associated with developing greater SCM competency.

The assessment of two metrics that differentiate top SCM performers from their industry competitors may also help SCM professionals to better convey the impact of SCM competency to non‐supply chain managers and external participants in the supply chain whose support and cooperation are critical to the success of process improvement initiatives.

In addition to the study findings, blending qualitative expert opinion, formal customer satisfaction and quantitative financial performance secondary data represents a relatively novel and informative method that responds to contentions that different approaches should be employed to develop a more holistic understanding of SCM.

The purpose of this paper is to set the benchmark for finished goods consumer supply chain companies in terms of financial metrics driven from best performing supply chains in the world.

The paper used a financial data collected from 25 large industries in Ethiopia and 25 companies from the best performing supply chains in the world as ranked by Gartner® to identify the gaps in financial metrics. This method helps in setting benchmarks for the case companies.

The result shows that the Ethiopian supply chains are performing well under revenue growth and insufficient under revenue per employee metrics. The result shows us these supply chains are accumulating inventories and are also seen inefficient and ineffective in their performances.

Even though the research is only one of the few on case considered, it is not without limitation. The strategies to narrow the performance gaps for the respective case companies are not articulated.

It is an ideal for the managers in the case companies to look into their performance gaps and take the necessary actions to stay alive in this fierce competition era. Hence, the paper shows insights to the improvement of the supply chain performances.

The research can be considered the only one of the few in a case country. It is also the first of the type in covering large fast moving consumer goods companies’ metrics at large aligning with the best practicing supply chains in the world within the same industry vertical.

A growing body of literature has begun in the direction of supply chain performance measurement. However, selecting the appropriate set of key performance indicators (KPIs) for measuring supply chain performance have always remained a challenge. The purpose of this paper is to identify the KPIs and categorize them specifically for measuring retail supply chain performance.

A qualitative approach, based on literature has been adopted. Published literature from refereed journals on supply chain performance measurement has been considered and various approaches for developing KPIs have been studied to develop a theoretical framework for performance measurement in retail supply chain.

The paper identifies key indicators for performance measurement and classifies them into four major categories: transport optimization, information technology optimization, inventory optimization and resource optimization. These key indicators are arranged precisely for retail industry. A theoretical framework is proposed to link the performance of these constructs on financial performance of the firm.

Future research can be carried out to validate the relevance and applicability of identified indicators. The study can be further conducted to measure the interrelationships between the KPIs and their impact on financial performance of the firm.

This study proposes a list of indicators for retail industry, which are presented in appropriate categories so that it can be used by the focussed teams for further improvement.

To the best of authors’ knowledge, no other study has categorized the KPIs into groups, specifically for measuring retail supply chain performance. The researcher also intends to carry out further empirical study to test the proposed theoretical framework.

This paper revisits the recent work of Chan and Qi which proposed an innovative performance measurement method for supply chain management. While the measurement method has many advantages, it can be unwieldy in practice. This paper aims to address these limitations and to propose a more user‐friendly alternative performance measurement model.

The performance measurement model described in this paper is a combination of two existing methods: Chan and Qi's model and the supply chain operations reference (SCOR) model. To demonstrate the applicability of the combined approach, actual SCOR level 1 performance data and the measurement information from a case supply chain (SC) are collected and processed by Chan and Qi's measurement algorithm.

These two methods complement each other when measuring SC performance.

This paper develops a practical and efficient measurement model that can resolve SC performance problems by incorporating the strengths of two different measurement models to create a synergistic new model.

Although the importance of establishing sound metrics is often noted in the logistics literature, few research efforts have examined appropriate metrics for reverse logistics (RL) processes. Through the lens of goal-setting theory, the paper identifies and align salient RL goals and metrics, and uncover some of the most common challenges to RL professionals. The paper aims to discuss these issues.

The paper used open-ended questions to gather qualitative data from 84 RL professionals from the defense industry. A content analysis method was employed to extract and categorize the goals, challenges, and metrics for RL processes.

The paper identifies specific categories of goals, challenges and metrics. Several themes emerged from the study, to include customer service, disposition, costs, and process efficiencies. Using these themes, the paper matched goals to metrics and found a lack of uniformity and noted that metrics and goals often were not matched or were misaligned.

This research is limited by the defense industry sample and the research method. Caution should be used when generalizing the results, and further research is required to empirically test the validity of the findings. Nonetheless, in the context of goal-setting theory, the study contributes to the performance metrics literature by aligning RL metrics with goals and addressing challenges faced by RL practitioners. By investigating the topic from multiple perspectives, the study provides more detailed findings and demonstrates the differences between the inbound and outbound RL processes.

This study provides insight into the metrics used to monitor and control RL processes. The findings may help firms to identify shortcomings and choose metrics that they can employ to align RL processes with firm goals.

The study contributes to the performance metrics literature by aligning RL metrics with goals and addressing challenges faced by RL practitioners. By investigating the topic from both an inbound and outbound perspective, the study provides more detailed findings and demonstrates the differences between the inbound and outbound RL processes.

The purpose of this paper is to report the use of performance metrics among 121 Brazilian agribusiness companies, with the aim of helping accountants and academics to understand the actual use of performance metrics in non-integrated supply chains (SCs).

To identify which performance metrics are used among SC partners, four independent clusters representing specific SC roles (input suppliers, farmers, distributors, and retailers) were formed. Data relating to 49 performance metrics were collected by questionnaire and analyzed statistically to isolate common measures.

It was found among suppliers, farmers, distributors, and retailers that the performance metrics for return on investment, responsiveness, and response time to clients are not being used whereas customer satisfaction obtained a usage pattern in all roles in the four groups. Hence, it appears that customer satisfaction rather than financial sustainability is the driver for discussion between SC partners.

Although limited to a sample of firms within Brazil, the findings confirm evidence from similar SCs worldwide.

These findings suggest that the common metrics approach to measure SC performance may be very difficult to achieve in practice and other alternatives should be investigated by management accountants.

A predominance of customer satisfaction metrics to the exclusion of discussions on financial performance between partners in agri-food SC has implications for the sustainability of the industry and the ability of accountants and managers to negotiate when faced with increasing input costs.

This study contributes to the accountants’ understanding of how performance measurement works in fragmented SCs, whereas the majority of the literature is concerned with the integrated SCs.