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Provides a multi‐criteria performance measurement model to measure the profitability performance of a manufacturing system. In developing the model, analytic hierarchy process (AHP) and its extension system‐with‐feedback (SWF) approaches are used. The SWF approach, an extension of the AHP method, is recommended when independence among different elements of a system assumption is violated. In a manufacturing system, the system’s performance criteria are interrelated. When the level of a single system criterion is changed, other criteria must be considered simultaneously. Also, the relative importance of these criteria with respect to each other and their contribution to the overall profitability is directly affected by the competitive strategy applied by the manufacturing system. The performance evaluation model developed in this study includes the competitive strategy and interdependence between the system criteria in its hierarchical structure and achieves a more realistic and accurate representation of a manufacturing system.

Existing supply chain (SC) performance models are not able to cope with the potential of intensive SC digitalisation and establish a relationship between decisions and decision criteria. The purpose of this paper is to develop an integrated knowledge-based system (KBS) that creates a link between decisions and decision criteria (attributes) and evaluates the overall SC performance.

The proposed KBS is grounded on the fuzzy analytic hierarchy process (fuzzy AHP), which establishes a relationship between short-term and long-term decisions and SC performance criteria (short-term and long-term) for accurate and integrated Overall SC performance evaluation.

The proposed KBS evaluates the overall SC performance, establishes a relationship between decisions (long-term and short-term) and decision criteria of SC functions and provides decision makers with a view of the impact of their short-term or long-term decisions on overall SC performance. The proposed system was implemented in a case company where the authors were able to develop a SC performance monitoring dashboard for the company’s top managers and operational managers.

The proposed KBS assists organisations and decision makers in evaluating their overall SC performance and helps in identifying underperforming SC functions and their associated criteria. It may also be considered as a tool for benchmarking SC performance against competitors. It can efficiently point to improvement directions and help decision makers improve overall SC performance.

The proposed KBS provides a holistic and integrated approach, establishes a relationship between decisions and decision criteria and evaluates overall SC performance, which is one of the main limitations in existing supply chain performance measurement systems.

Understanding the significance of supply chain, demands need of multiple criteria for its performance evaluation. The aim of this paper is to propose an approach to evaluate the performance of supply chain using multiple criteria.

A multi‐criteria decision making tool, like analytic hierarchy process is used to develop an eight step methodology for performance evaluation. The proposed methodology is also elucidated with an illustration and a case from Indian chemical company.

Supply chain performance number is computed, suggesting the present performance status of the supply chain. The methodology also helps rank the various links according to its performance. The analysis leads in computation of supply chain performance number (SCPN): the value lies between 0 and 1.

The methodology can be suitably modified to accommodate any number of criteria and supply links, given the structure of the supply chain.

A case from an Indian chemical industry is presented in this paper. The findings of which, are encouraging and have benefited the practicing mangers in various ways.

This paper presents a unique approach for supply chain performance evaluation considering multiple criteria, with a flexibility to modify and analyze using the available data sets.

The purpose of this paper is to provide a framework for designing a multiple performance measurement tool for evaluating, comparing and benchmarking the working of engineering educational institutes in a group based on total quality management (TQM) criteria and performance measurement criterion, respectively.

Proposed framework is based on fuzzy analytic hierarchy process (FAHP) which takes in to account the fuzziness of human opinion for realistic outcome and generalization of the results. Based on the proposed framework a case study was conducted on engineering institutes of central India for collecting data and analyzing the current practices followed in these institutes. A relationship among TQM implementation criterion was developed, their respective weights derived and then institutes were ranked.

It was found that the rank of institutions based on both the criterion is same, which indicates that the institutes having better TQM implementation have better performance.

The research in this paper is limited to Indian scenario; studies in other countries and sectors may be conducted to compare the results obtained.

The results will help policy makers in identifying institutions having poor performance in the region.

The paper is navel in its attempt to provide a model based on TQM criteria for evaluating the working of engineering educational institutes in a group in terms of their relative weightage and benchmark.

The aim of this study is to develop a framework for measuring of service supply chain (SSC) maturity process.

The main framework of the SSC maturity was developed by reviewing the concepts and models of SSC, business excellence, maturity and supply chain performance evaluation. Then, the maturity level of each excellence criterion was defined in the proposed model by using the excellence criteria for SSC and the concept of Plan, Do, Check and Act (PDCA) cycle in combination with the process survey tools maturity model. Based on the excellence criteria and their maturity levels, a questionnaire was designed to practically measure the proposed framework.

The concepts and features of maturity levels defined for each of the excellence criteria were used to implement and operationalize the proposed framework and evaluate the SSC processes.

Through the assessment of the existing status of SSC processes, the findings allow managers to reach a better understanding of the strengths and weaknesses of such processes. Then, some opportunities are provided for improving each excellence criterion to enhance the performance of each process.

In fact, this study provides guidelines for organizations to measure their progress and performance and improve their management systems. The main advantages of the proposed SSC measurement framework include self-assessment facilitation, calculation of criteria scores and development of uses. The proposed model, like quality and productivity awards, can pave the way for increased competitiveness of the service industry.

Supply chain performance (SCP) extent can be attributed as a function of multiple criteria/attributes. Most of the criterions/attributes being intangible in nature; SCP appraisement relies on the subjective judgment of the decision makers. Moreover, quantitative appraisement of SCP appears to be very difficult due to involvement of ill-defined (vague) performance measures as well as metrics. The purpose of this paper is to develop an efficient decision support system (DSS) to facilitate SCP appraisement, benchmarking and related decision making.

This study explores the concept of fuzzy logic in order to tackle incomplete and inconsistent subjective judgment of the decision makers’ whilst evaluating supply chain’s overall performance. Grey relational analysis has been adopted in the later stage to derive appropriate ranking of alternative companies/enterprises (in the same industry) in view of ongoing SCP extent.

In this work, a performance appraisement index system has been postulated to gather evaluation information (weights and ratings) in relation to SCP measures and metrics. Combining the concepts of fuzzy set theory, entropy, ideal and grey relation analysis, a fuzzy grey relation method for SCP benchmarking problem has been presented. First, triangular fuzzy numbers and linguistic evaluation information characterized by triangular fuzzy numbers have been used to evaluate the importance weights of all criteria and the superiority of all alternatives vs various criteria above the alternative level. Then, the concept of entropy has been utilized to solve the adjusted integration weight of all objective criteria above the alternative level. Moreover, using the concept of the grey ration grades, various alternatives have been ranked accordingly.

Finally, an empirical example of selecting most appropriate company has been used to demonstrate the ease of applicability of the aforesaid approach. The study results showed that this method appears to be an effective means for tackling multi-criteria decision-making problems in uncertain environments. Empirical data have been analysed and results obtained thereof, have been reported to exhibit application potential of the said fuzzy grey relation based DSS in appropriate situation.

Many argue that the design of compensation contracts for public company chief executive officers (CEOs) is often not guided by a goal of value maximization. Yet, there is limited direct empirical evidence on the negative consequences of the proposed inefficient contracting between shareholders and CEOs. Using data on CEO bonus contracts of the S&P 500 firms, we investigate potential firm performance implications of the use of qualitative criteria such as leadership and mentoring in those contracts. We maintain that unlike quantitative criteria, qualitative criteria are difficult to define and measure on an objective basis, possibly resulting in an inefficient and biased incentive structure. Twenty-five percent of the sample observations have CEO bonus contracts that include a qualitative criterion for bonus payment determination. Our results show that employee productivity, asset productivity, capital expenditures, and future abnormal stock returns are lower for firms that use a qualitative criterion in CEO bonus contracts than those that do not. Further, contrary to the argument in prior literature that earnings management decreases with the use of subjective performance indicators in incentive contracts, we find that income-increasing accruals are actually higher when the CEO bonus contract includes a qualitative criterion. We recommend that compensation committees set concrete, measurable performance goals for CEOs, providing CEOs with better guidance and helping improve their corporate decision making.

COVID-19 is a global event affecting supply chain operations and human health. With COVID-19, many issues in business models, business processes and supply chains, especially in the manufacturing industry, have had to change. The ability to analyze supply chain performances and ensure circularity in supply chains has become one of the factors whose importance has increased rapidly with COVID-19. Therefore, it aims to determine which supply chain performance criteria come to the fore for the company under consideration to accelerate the transformation into high performance and circularity in supply chains.

In this study, a new circular-SCOR model is proposed, and 17 supply chain performance measurement criteria are prioritized for a manufacturing company in the context of circular economy principles during COVID-19 by using stepwise weight assessment ratio analysis and analytical hierarchy process method, separately.

As a result, for both methods, in the case study discussed, the demand fulfillment rate is determined as the most prominent criterion in line with the circular economy principles in the COVID-19 period in manufacturing supply chains.

It is expected that this study will contribute to managers and policy makers as it addresses the “new normal” that started after COVID-19 and the criteria to be considered in supply chain performance measurement and emphasizes the need to adopt circular supply chains, especially in manufacturing industries.