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For an enterprise, the competence of human resource is more important than the intellect or the basic quality of human resource. This paper aims to present a competence appraisement model of human resource in an enterprise.

The paper puts forward the appraisement index architecture of enterprise human resource competence on the foundation of adopting the concept and models of competence, and establishes a general model of the enterprise human resource competence appraisement.

The results obtained in this paper provide a foundation to establish a relatively reasonable and efficient enterprise appraisement system of human resources.

The research offers information about the enterprise appraisement information processing system of human resources.

In recent years, stimulated environmental awareness (green consciousness) has favored the emergence of the green supply chain paradigm. Therefore, apart from traditional supplier selection criterions, green criteria are necessarily to be incorporated in the supplier selection problem. In this context, the present study aims to highlight an efficient supplier appraisement platform by considering green performance criteria, in fuzzy environment.

The present work exhibits an efficient fuzzy-based supplier performance assessment system using generalized trapezoidal fuzzy numbers set. A fuzzy overall evaluation index has been estimated towards assessing suppliers' green performance extent, thus facilitating supplier appraisement cum selection decision-making.

The proposed method has been found efficient for solving the group decision-making problem under uncertain environment due to vagueness, ambiguity associated with decision-makers' subjective judgment. The proposed appraisement platform has been explored by an Indian automobile part manufacturing company at eastern part of India. Suppliers have been evaluated individually to check their performance level with respect to green attributes. Apart from estimating overall performance metric, the model presented here can identify ill-performing areas that necessitate future attention.

The major contributions of this work have been summarized as follows: Development and implementation of an efficient decision-making procedural hierarchy to support suppliers' green performance extent evaluation. An overall performance metric has been introduced. Concept of generalized trapezoidal fuzzy numbers has been efficiently explored to facilitate such an appraisement cum selection decision-making. The appraisement index system has been extended with the capability to search ill-performing areas that require future progress.

This paper aims to develop an efficient measurement index evaluation system towards assessing suppliers' green performance practices. Apart from estimating overall performance index, the paper also aims to highlight application of decision‐support tools for selection of appropriate candidate supplier in green supply chain management context.

In order to tackle incompleteness and imprecision arising from assigning appropriateness rating as well as priority weights against subjective performance criteria‐attributes, use of grey numbers was proposed. An efficient grey‐based supplier appraisement platform was established. Application of Grey‐Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and COPRAS‐G method were reported to solve the supplier selection decision‐making problem. The theory of grey numbers was utilized here to facilitate such decision modeling.

Over the last two decades, growing concerns about ecosystem quality have stimulated to a renewed interest in environmentalism. Purchasing professionals should also be concerned and need to rethink purchasing strategies which have traditionally neglected environmental impacts. The “green” purchasing‐packaging in reducing and eliminating waste is a major concern in recent days. In order to help foster environmentally concerned purchasing strategies, this paper presents the findings of supplier evaluation strategy in an enterprise with enhanced degree of awareness and frequent applications of “green” purchasing. Environmental factors are identified that may reshape supplier evaluation decisions. The concept of grey numbers set has been adopted in this work. A case study reflects effectiveness of exploring grey relation theory in the context of green supplier evaluation.

The major contributions of this work have been summarized as follows: development and implementation of an efficient decision‐making tool to support green supplier evaluation; an overall green performance index evaluation platform has been introduced; concept of grey numbers has been efficiently explored to facilitate this decision‐making; the appraisement index system has been extended with the capability to search ill‐performing areas which require future progress; and the proposed appraisement system is capable of reducing the number of green attributes towards computing grey appropriateness index thereby transforming into lesser number of green capabilities, thus, facilitating applying decision‐making tools like grey‐TOPSIS and COPRAS‐grey method for appropriate supplier selection from a set of candidate suppliers.

In the rapidly changing business environment, companies must align with suppliers to streamline operations, as well as working together to achieve a level of agility beyond individual companies (Lin et al., 2006). Today’s more dynamic business environment increases the need for greater agility in supply chains, which increases both the importance and frequency of supplier/partner evaluation and benchmarking decision making. The purpose of this paper is to develop a multiple criterion appraisement index (model/module) for supplier/partner alternative firm benchmarking perspective under similar agile supply chain architecture.

In this reporting, evaluation information against subjectivity (uncertain environment) indices has been transformed mathematical dimensionless numbers by fuzzy-based computation module. A new interval-valued fuzzy number set conjunction with modified “technique for order preference by similarity to ideal solution” methodology has been explored from benchmarking (ranking order of firm under similar criterion) point of view of supplier firms.

In this context, a novel “fuzzy mathematical equation” has been developed in perceptive to compute the priority weights and appropriateness ratings of first-level measures which reduced the acquisition of supplementary priority weights and appropriateness ratings assessment in linguistic terms from group decision makers (DMs) for first-level indices. An empirical case study has been carried to ranking order the candidate partner/supplier alternative via collective index (CI) value. Lower value of “CI” reflected higher degree of performance extent. The authors found out the effectiveness and validity of proposed methodology for constructed appraisement module.

This research work shall be valuable for that organization which volunteer to obtain the ranking order of partner/supplier alternative (benchmark) under similar agile supply chain architecture in accordance to group DMs’ comprehensive information for select best one supplier for own firm. In this reporting, a novel fuzzy mathematical equation has been developed in order to compute the important weights as well as priority rating of first-level indices/measure which reduced the supplementary important weights and priority rating assessment from group DMs in linguistic terms in order to obtain the measures rating and weights.

Lean manufacturing is a production practice that considers the expenditure of resources for any goal other than the creation of value for the end customer to be wasteful, and thus a target for elimination. In today's competitive global marketplace the concept of lean manufacturing has gained vital consciousness to all manufacturing sectors, their supply chains and hence a logical measurement index system is indeed required in implementing leanness in practice. The paper aims to discuss these issues.

The present work exhibits an efficient grey-based leanness assessment system using concept of grey numbers theory.

Such leanness estimation can help the enterprises to assess their existing leanness level; can compare different industries who are adapting this lean concept. The methodology described here has been found fruitful while applying for a particular industry, in India, as a case study.

Lean extent evaluation module (lean index appraisement system) exploring grey numbers theory is quite new and not documented in literature before.

Supplier evaluation is a part of logistic management. In the present era, resilient supply chain performance (RSCP) assessment of the vendor enterprise is respected as a hot topic. The purpose of this paper is to enable the managers to map the performance in percentage system and also enabling managers for identifying the weak indices-metrics, which need to be improved up to ideal or standard level and strong indices-metrics.

The authors found two research gaps via a literature survey. The first research gap revealed that the performance of a resilient supplier is computed solely in terms of a fuzzy mathematical scale. The articles are not yet published, which could measure the RSCP in percentage. The second research gap argued about the mitigation of the multi-level hierarchical resilient vendor/supplier evaluation framework for materializing RSCP and identifying weak and strong performing indices-metrics. To compensate the both research gaps, the authors developed a novel fuzzy gain-loss evolutionary computational approach to assess the performance of a firm in percentage. Next, a revised ranking technique coupled with trapezoidal fuzzy set based fuzzy performance importance index is implemented on the framework to seek weak and strong indices-metrics. The performance loss of each metric using the ideal solution concept considering the attitude of decision makers is also revealed.

The authors found the RSC performance of supplier firm 74 per cent, whereas performance loss 26 per cent, while actual performance is compared with standard fuzzy performance index (SFPI). Performance loss 26 per cent can be compensated by improving the performance of weak indices-metrics.

The novelty of the paper is that the authors used the ideal solution concept to compute the SFPI and compare it with actual FPI for evaluating the gain and loss of resilient supplier firm in percentage and identify weak and strong indices so that managers can improve the performance of weak indices. The work possesses the significant for all organizations, as research work enables the managers to map and improve the RSC performance of any vendor firm in future. The presented work considers the case of an automobile parts supplier industry to validate the developed approach.

In today’s’ highly competitive market, outsourcing logistic activities have become a global trend as it offers wide range of services including transportation, distribution, packaging, labeling, warehousing, freight forwarding and order fulfillment. The demand of third-party logistics (3PL) provider becomes an increasingly important issue for corporate seeking improved customer service, operational efficiency, logistics costs as well as capital expenditure reduction. However, choosing a proper 3PL provider is a kind of multi-criteria decision making problem under consideration of complicated criteria hierarchy. Therefore, it seems necessary to develop an efficient appraisement module towards performance evaluation as well as selecting the best 3PL provider. The paper aims to discuss these issues.

The present paper proposes a fuzzy based appraisement platform for evaluation and selection of 3PL providers. The theory behind interval-valued fuzzy numbers (IVFNs) has been utilized to aid the said decision-modeling. Based on two appraisement modules for 3PL evaluation; empirical data have been analyzed to validate case application.

The proposed method has been found efficient for solving the group decision-making problem under uncertain environment due to vagueness, ambiguity associated with decision-makers’ subjective judgment. The proposed appraisement platform has been explored by an Indian automobile part manufacturing company at eastern part of India. 3PL providers have been evaluated individually to check their performance level with respect to various evaluation attributes. Apart from estimating overall performance metric, the model presented here can identify ill-performing areas which necessitate future attention.

The major contributions of this work have been summarized as follows: First, development and implementation of an efficient decision-making procedural hierarchy to support 3PL evaluation and selection. Second, an overall performance metric has been introduced. Third, concept of IVFNs has been efficiently explored to facilitate such a appraisement cum selection decision making. Final, the appraisement index system has been extended with the capability to search ill-performing areas which require future progress.

Around the world, protecting environment and purchasing green products by the manufacturing firms progressively becomes a popular and important issue. Manufacturers are realizing the importance of producing green products under green practices. This study aims to propose an appraisement platform to evaluate the overall performance index of a firm under green practices. Furthermore, the study also helps in identifying ill-performing areas, which necessarily require future attention to augment green supply chain (GSC) of a firm. A case research is conducted to assess the real-life application by the proposed approach.

The authors used fuzzy performance index to measure the overall performance index of a firm. Beside this, they proposed a degree of similarity approach amalgamated with fuzzy performance importance index to classify the ills and strong indices in GSC extent.

The intermittent assessment of green practices and their metrics in the organizational supply chain management (SCM) is indeed necessary. The present study provides an appraisement module to assess overall GSC fuzzy performance index and also helps in identifying the ill-performing areas which require future augmentation toward successful green implementation.

The exposed research work dealt with chains of subjective indices (measure and their interrelated metrics), which are induced into hierarchical appraisement module. To tackle the uncertainty of indices, the subjective indices are transposed into interval-valued fuzzy number set (IVFNS), as IVFNs are preferred to undertake the uncertainty of GSC indices. The proposed approach is demonstrated with a case research to justify its validity and originality.

The purpose of this paper is to develop a multi-level hierarchical framework (evaluation index system) toward evaluating an “appraisement index” from the prospectus of measuring and monitoring resilient performance of the candidate industry.

In this reporting, vagueness, imprecision, as well as inconsistency associated with subjective evaluation information (aligned with ill-defined assessment indices of SC resilience performance), has been tackled by the application of fuzzy theory.

Subjective evaluation information (expressed in linguistic term) acquired from the committee of decision makers (called expert group), against different resilience indices/metrics, has been fruitfully explored through the proposed fuzzy-based resilience performance appraisement module. Finally, a case study from an Indian automobile company has been conducted from the perspective of checking effectiveness of the proposed methodology for evaluation of appraisement index indicating SC resilience extent.

This methodology might be successfully applied to help other decision-making problems from the perspective of performance appraisal and benchmarking of candidate alternatives/choices under predefined criteria and subjective evaluation circumstances.

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.