Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS)

Sustainable supplier selection: A multi-criteria intuitionistic fuzzy TOPSIS method

Sustainable supplier selection: A novel integrated fuzzy best worst method (F-BWM) and fuzzy CoCoSo with Bonferroni (CoCoSo’B) multi-criteria model

Sustainability has emerged as an important industrial strategic outlook expanding beyond organizational boundaries to include the supply chain. Simultaneously, the industry has also been faced with supply chain resilience concerns. Research on the intersection of supply chain sustainability and resilience is nascent and is a consequence of their observed mutual influences. However, confusion about concepts, implementation methods, and measurements of sustainable and resilient supply chains remains. This study completes a systematic literature review that critically examines several major observations and directions. We find the concept of sustainable supply chains is more established, and general agreement on its theoretical foundations exists. Supply chain resilience is relatively less mature. The nexus and relationships between the two topics are often incoherent: there is confusion on sustainable and resilient supply chains establishment; there is no clarity on what practices could jointly advance both areas. A major conflict exists since sustainability generally focuses on efficiency, while resilience seeks effectiveness. We recommend studies to analyze implementation relationships and impact. We also observe that performance measurement systems should be developed to assess supply chain sustainability and resilience performance taking with explicit consideration time horizons considered in these measures.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/bse.2776

Integrating sustainability and resilience in the supply chain: A systematic literature review and a research agenda

Organisational and managerial decisions are influenced by corporate sustainability pressures. Organisations need to consider economic, environmental and social sustainability dimensions in their de...

/pdf/social-sustainable-supplier-evaluation-and-selection-a-group-49jwn1fip0.pdf

Social sustainable supplier evaluation and selection: a group decision-support approach

Purpose




The purpose of this paper is to attempt supplier selection considering economic, environmental and social sustainability issues.




Design/methodology/approach




Subjective human judgment bears some kind of vagueness and ambiguity; fuzzy set theory has immense potential to overcome this. Owing to the advantage of intuitionistic fuzzy numbers set over classical fuzzy numbers set; three decision-making approaches have been applied here in intuitionistic fuzzy setting (namely, intuitionistic-TOPSIS, intuitionistic-MOORA and intuitionistic-GRA) to facilitate supplier selection in sustainable supply chain.




Findings




The stated objective of this research “to verify application potential of different decision support systems (in intuitionistic fuzzy setting) in the context of sustainable supplier selection” has been carried out successfully. A case empirical research has been conducted by applying three different decision-making approaches: intuitionistic fuzzy-TOPSIS, intuitionistic fuzzy-MOORA and intuitionistic fuzzy-GRA to an empirical data set of sustainable supplier selection problem. The ranking orders thus obtained through exploration of aforesaid three approaches have been explored and compared.




Originality/value




As compared to generalized fuzzy numbers, intuitionistic fuzzy numbers exhibit a membership degree, a non-membership degree and the extent of hesitation; a better way to capture inconsistency, incompleteness and imprecision of human judgment. Application potential of aforesaid three decision support approaches has been demonstrated in this reporting for a case sustainable supplier selection.

Sustainable supplier selection in intuitionistic fuzzy environment: a decision-making perspective

Purpose – Robot selection is basically a task of choosing appropriate robot among available alternatives with respect to some evaluation criteria. The task becomes much more complicated since apart from objective criteria a number of subjective criteria need to be evaluated simultaneously. Plenty of decision support systems have been well documented in existing literature which considers either objective or subjective data set; however, decision support module with simultaneous consideration of objective as well as subjective data has rarely been attempted before. The paper aims to discuss these issues. Design/methodology/approach – Motivated by this, present work exhibits application potential of preference ranking organization method for enrichment evaluations (extended to operate under fuzzy environment) to solve decision-making problems which encounter both objective as well as subjective evaluation data. Findings – An empirical case study has been demonstrated in the context of robot selection proble...

Extension of PROMETHEE for robot selection decision making

Purpose




Recently, in turbulent and highly competitive marketplace, organizational sustainability in the long run necessitates the adaptation of appropriate supply chain (SC) strategies. Hence, traditional SC philosophies are being restructured nowadays to fulfill different business goals. Articulation of lean, agile, green and resilient SC strategies could amply be found in the literature; however, integration of those in various modes may definitely improve overall SC’s performance. Past researchers have focused on the integration of lean, agile and green paradigms together to ensure an efficient SC construct. But the integration of green and resilient paradigm has been rarely reported in the literature. To deal with the unexpected situations/disturbances in the SC management along with embedded environmental consciousness, the purpose of this paper is to integrate the resilient SC and green SC philosophies; thereof to evaluate of an overall SC “g-resilient”/“ecosilient” index for a case automotive company.




Design/methodology/approach




A consolidated list consisting of supply chain practices (combining green and resilient performance indices) have been articulated in this study. A decision-making group has been assumed; where, the role of the decision makers is to provide individuals’ judgment (subjective opinion) toward determining the weight and the rating (performance extent) of various performance indices. The overall g-resilient SC performance has been determined by computing a unique ecosilient (g-resilient) index. The concepts of fuzzy performance importance index along with Degree of Similarity (DOS) adapted from fuzzy set theory (FST) have been applied to rank various performance indicators. In addition to that, the interrelationships amongst various g-resilient indices (performance indicators) have also been established through interpretive structural modeling.




Findings




By exploring the concept of fuzzy DOS, outlined in the trapezoidal fuzzy numbers set theory, various SC performance indicators have been classified into three distinct performance categories/levels (namely regretful, tolerable, and satisfactory). Such categorization has been found helpful in order to determine ill (poor) performing SC areas, which need future improvement toward boosting up the overall g-resilient index of the company’s SC.




Originality/value




The study bears significant managerial implications. The decision support framework suggested in this paper is found capable enough to determine a unique index known as “ecosilient (g-resilient) index” toward exploring “greenness” as well as “resiliency” for the case automotive company. Application potential of the proposed ecosilient (g-resilient) index evaluation system has been explored in this reporting. The recommended framework enables the managers to cope up with unexpected disruptions and found helpful in order to reduce the environmental impacts.

On evaluation of supply chain’s ecosilient (g-resilient) performance index: A fuzzy embedded decision support framework

Purpose – Decision making is the task of selecting the most appropriate alternative among a finite set of possible alternatives with respect to some attributes. The attributes may be subjective or objective (or combination of both), depending upon the situation; requirements may also be conflicting. In practice, most of the real-world decision-making problems are based on subjective evaluation criteria which are basically ill-defined and vague. Since subjective human judgment bears ambiguity and vagueness in the decision making; application of grey numbers set theory may be proved fruitful in this context. The paper aims to discuss these issues. Design/methodology/approach – Owing to the advantages of grey numbers set theory in tackling subjectivity in decision making; the crisp-TODIM needs to be extended by integrating with grey numbers set theory in order to facilitate decision making consisting of subjective data. Hence, the unified objective of this paper is to propose a grey-based TODIM approach in t...

Extension of TODIM combined with grey numbers: an integrated decision making module

Green supply chain management has become an important avenue in current business scenario. The concept of GSCM is to integrate environmental thinking into traditional supply chain management. A firm's sustainability performance is greatly influenced by appropriate supplier selection in the green supply chain context. In selecting appropriate green supplier, various green criteria need to be considered along with traditional supplier selection criteria. The decision making in the context of green supplier selection becomes much more complex due to involvement of subjective selection criteria. Subjective human judgment often bears ambiguity and vagueness in the decision making; whilst fuzzy set theory overcomes the challenges of imprecise and inconsistent human judgment in ambiguous decision environment. In this context, a decision making scenario in relation to green supplier selection has been articulated in this paper aiming to investigate the applicability of MULTIMOORA in fuzzy setting (F-MULTIMOORA). The ranking order of candidate suppliers has been compared to that of fuzzy-TOPSIS. Finally, an attempt has been made to determine a unique quantitative performance index for each of the green suppliers; based on which a ranking order has also been arrived.

Green supplier selection in fuzzy context: a decision-making scenario on application of fuzzy-MULTIMOORA

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