Supply Chain 4.0 qualifiers for agroindustries - application of fuzzy Delphi method

A sustainable project‐driven supply chain (SPDSC) refers to integrating sustainability into project management to improve the sustainability performance of projects. Integrating sustainability and supply chain management is any project‐based organization's most significant performance‐related challenge. Therefore, the present study explores the drivers that can effectively tackle supply chain issues in managing projects undertaken in construction contracting firms for long‐term sustainability. Sixteen critical drivers were considered through a rigorous literature review and fuzzy Delphi method (FDM) for construction contracting firms. Then, selected drivers were used to analyze established construction contracting firms using a grey relational analysis (GRA) technique. The results highlight that construction contracting firms (CCFs) considered the drivers of sustainable use of resources, energy and eco‐efficiency, and environmental impact assessment; stakeholder engagement and social impact; and supply chain collaboration dimensions need to be improved for enhancing the sustainability of PDSCs. This study's contribution is twofold: It quantifies the identified set of critical drivers relevant to SPDSCs; it offers the CCFs a practical toolkit for sustainable project deliverables.

Sustainable supply chain management towards disruption and organizational ambidexterity: A data driven analysis.

Purpose This study aims to propose a method for measuring lean supply chain management (LSCM) maturity based on the main lean practices and existing waste of a supply chain. Design/methodology/approach A three-stage approach was developed. First, a thorough literature review was performed to raise concepts and previous findings on maturity models (MMs) and LSCM. This review’s outcomes were then validated by experts in the field using the fuzzy Delphi method (FDM). Subsequently, the proposed model was illustrated and assessed based on a multi-case study. Findings All companies attained high outcomes in the elimination of the waste pillar. The pillars of logistics management, continuous improvement and information technology management also stood out in the three organizations’ results. The company with the lowest maturity level operates in a make-to-order production policy, which may harm the lean supply in its supply chain. Practical implications The proposed model can reveal external opportunities and threats and internal strengths and weaknesses in supply chains (SCs). It is also capable of providing a clear roadmap for SC improvement in companies. Originality/value To the best of the authors’ knowledge, no study to date has proposed a MM in the LSCM context using FDM and considering the crucial relationship between lean practices and wastes.

Purpose – The purpose of this article is to identify the critical success factors (CSFs) of knowledge management (KM) adoption in the supply chain (SC) using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) method through an empirical case study. Design/methodology/approach – The paper examines the influencing factors of KM adoption in SC which have been identified through the literature survey and expert opinion. The fuzzy DEMATEL method has been used to evaluate identified influencing factors. Considering the interdependence among factors, the fuzzy DEMATEL method forms a structural model and then visualizes the causal relationships among factors through a cause–effect relationship diagram. On the basis of the cause–effect relationship diagram, CSFs that are extraordinarily essential for KM adoption in SC are identified. Empirical case study of an Indian automobile organization presented to illustrate the fuzzy DEMATEL method and demonstrates its usefulness. Findings – The results gathered from the implementation of the fuzzy DEMATEL method to identify CSFs of KM adoption in SC to the chosen case illustrate that factors such as top management support, employee training and education, integration of knowledge and information flow, communication among the SC members and trustworthy teamwork to exchange knowledge within SC need to be highlighted as critical factors for successful adoption of KM in SC. Practical implications – The finding not only offers a meaningful base to deepen the understanding with regard to KM adoption in SC, but also provides a clue to develop an effective adoption of KM in SC in a stepwise manner. Originality/value – The empirical case study contributes to the literature on KM adoption in SC, suggesting how an organization can identify CSFs of KM adoption in SC and implement them progressively to greatly improve the efficiency of the whole SC performance.

Prior studies in sustainable supply chain management (SSCM) fail to address collaboration in the supply chain and lean management in conjunction with economic benefits. Collaboration in the supply chain and lean management have to integrate into SSCM, which involves social, economic and environmental aspects. This study aims to establish a framework to understand the seafood industry in Vietnam and to enhance its performance. This framework proposes 5 aspects and 21 criteria, and these aspects involve qualitative information. Fuzzy set theory is applied to deal with the complexity of and uncertainty in the linguistic preferences. The fuzzy Delphi method is employed to test the reliability and validity attributes. A decision-making trial and evaluation laboratory is to assess the interrelationships among the attributes. Sensitivity analysis is adopted to address subjective robustness and objective perceptions. The results show that the aspects of collaboration in the supply chain and lean management drive economic benefits.

This study provides insights into digitalization in sustainable supply chain management by establishing a structural set of attributes with causal interrelationships among them, as well as by reporting empirical findings on successful criteria for footwear supply chain practices in Indonesia. Sustainable supply chain management and digitalization are mutual benefits. However, there are unclear cause and effect interrelationships. This study aims to critically pinpoint digitalization to approach sustainability and is designed to help firms achieve supply chain competitiveness. The fuzzy Delphi method and fuzzy decision-making trial and evaluation laboratory are utilized, due to the fuzziness associated with human decision making and the complexity and uncertainty in the supply chain. Five aspects and seventeen criteria are validated. The findings indicate that four aspects, including digital platform effectiveness, digital communication belonging to the supply chain digitalization perspective, labour conditions, and manufacturing processes, are important to sustainable supply chain management. The top causal criteria, including logistics integration, logistics optimization, delivery speed, proactive action, and real-time inventory, are considered to assist firms in implementing better practices.

PurposeThe supply chain (SC) model is commonly utilized in manufacturing and has also been adapted to a variety of service industries with similar goals. However, in a few service industries, most notably academic libraries, the SC model is rarely implemented, despite the fact that SC management best practises have been shown to boost stakeholder satisfaction, revenue and decrease total expenses. This research aims to discuss the development of the entities of an academic library SC model and present the verifying/validation process of the model.Design/methodology/approachIn this research, both qualitative and quantitative approaches have been used. System thinking method used to develop the conceptual SC model of the academic library and fuzzy Delphi method (FDM) used to validate the developed model.FindingsThis research explores the functions and components that need to develop and validate the academic library SC model.Originality/valueThe outcome of this research is to construct a valid SC model of an academic library which could be a strategical tool for ensuring a quality service for the library users and the stakeholders because this model shows a holistic view of all entities of the academic library SC.

By emphasizing the principles of recycling, refurbishing, and reusing materials, circularity in supply chain management plays a pivotal role in waste reduction and resource efficiency enhancement. However, the adoption and implementation of circular supply chains (CSCs) remain limited due to the substantial associated risks. Research in Circular Supply Chain Management (CSCM) suggests that integrating Fourth Industrial Revolution technologies and big data analytics may offer a viable solution. Despite growing interest in CSCM, the lack of field-specific data and a predominant focus on macro-level studies have resulted in insufficient exploration of circularity barriers within Iran’s food supply chain. This study seeks to address this gap by prioritizing big data-driven solutions to overcome these barriers. The research objectives include identifying and validating key obstacles within Iran’s food industry through an extensive literature review and content validity ratio analysis. The barriers were classified into five primary categories, with their respective weights determined using the fuzzy SWARA (Step-wise Weight Assessment Ratio Analysis) method. The most critical barriers identified were the absence of organizational infrastructure to support circular supply chain initiatives and the lack of essential systems for product traceability. Subsequently, big data-based techniques were evaluated and prioritized using Einstein’s fuzzy WASPAS (Weighted Aggregated Sum Product Assessment) method. Combining the robustness of fuzzy logic with MCDM (Multi-Criteria Decision-Making) techniques, this approach offers an effective framework for weighting circular supply chain barriers and prioritizing big data techniques under conditions of uncertainty. Notably, this study represents the first application of Einstein’s fuzzy WASPAS method in circular supply chain management. The findings reveal that SNA (social network analysis) and optimization models exert the most significant influence in mitigating implementation barriers. These insights can guide food industry managers in strategically adopting smart technologies to address key challenges in circular supply chain adoption.

The supply chain inherently possesses a high degree of complexity, which has become increasingly exacerbated due to globalization, market expansion, and the continuous evolution of customer preferences. This growing complexity may lead to asset invisibility, inefficient inventory management, or logistical mismanagement. These complications often culminate in the well-known phenomenon of the "Bullwhip Effect" (BE) within supply chains. The aim of this study is to identify the key enablers that effectively reduce the Bullwhip Effect in the automotive supply chain sector. This research is descriptive in methodology and applied in purpose. To determine the importance of critical enablers influencing the mitigation of the Bullwhip Effect, a thorough review of the literature was first conducted to identify a preliminary list of significant enablers. Subsequently, using the Fuzzy Delphi Method, the final set of influential enablers for minimizing the Bullwhip Effect in the automotive supply chain was identified. To analyze the interrelationships among the 13 foundational enablers—based on literature and data collected through questionnaires—the study employed Fuzzy Cognitive Mapping (FCM) and Interpretive Structural Modeling (ISM) to determine the most impactful enablers. FCMapper software was used for the FCM method, while Excel software facilitated the ISM approach. Based on centrality metrics within the Fuzzy Cognitive Mapping approach, five enablers were found to be critically important: information quality in the supply chain, big data, supply chain flexibility, customer relationship management, and trust in the supply chain. Additionally, business intelligence, visibility capability, supply chain agility, order volume, information sharing capability, coordination and collaboration in the supply chain, supply chain integration and transparency, and delivery time were ranked sixth to thirteenth, respectively. According to the ISM results, the following enablers were identified in order of significance as the primary factors in reducing the Bullwhip Effect in the automotive supply chain: big data, business intelligence, information sharing capability, integration and transparency, trust in the supply chain, delivery time, coordination and collaboration, visibility capability, information quality, customer relationship management, order volume, supply chain agility, and flexibility.

Supply chain (SC) is assumed as a leading operations strategy in both manufacturing and service organisations. Knowledge is recognised as an important source of competitive advantage in SC. However, evidence suggests that there are several SC knowledge flow barriers (SCKFBs) which obstruct knowledge flow in SC. The purpose of this research is to identify SCKFBs and propose solutions to overcome the SCKFBs. The weight of major SCKFBs is calculated by fuzzy Delphi (FD) method and ranking of the solutions of SCKFBs is evaluated using the fuzzy inference system (FIS) method. To overcome SCKFBs, the top rank solutions obtained are visible technologies that offer real-time customer and demand knowledge, building strategic relationships with SC partners and induce mutual trust with SC partners. This study may be one of the first to bring together a large range of SCKFBs on the same platform, and an attempt to give solutions for SCKFBs.

Sustainable supply chain management trends in world regions: A data-driven analysis

PurposeThe purpose of this study was to identify the excellence criteria of services supply chain (SSC) in Iran and the relationship between them and the importance of each criterion.Design/methodology/approachIn this paper, after reviewing the principles and evaluating models of SSCs, using the fuzzy Delphi method, the criteria for excellence in the supply chain processes were identified. Then, the relationships between these criteria and their significance were evaluated using decision-making trial and evaluation laboratory (DEMATEL) and DEMATEL-based analytic network process methods.FindingsThe results show that 19 evaluation criteria have been identified in Iran in accordance with the SSC process. These criteria were classified according to their nature and based on the Deming Excellence Model and ISO 9004 standards in four areas: Plan, Do, Check and Act. In addition, the Act dimension with the weight of 0.275 has the highest importance and the Plan dimension with the weight of 0.219 has the lowest importance.Practical implicationsThis study attempted to identify appropriate criteria for SSC processes in management consulting firms by examining supply chain assessment models to provide the managers with the right understanding of this industry for performance assessment so that they have a better knowledge of supply chain processes.Originality/valueThe results will be useful for managers to understand the SSC and the ways of SSC excellence in a service organization. This research is a first step for evaluating SSC performance of management consultancy institutes. In fact, after the identification of SSC processes and evaluation criteria, designing a mechanism for the evaluation of the performance of SSCs can be a subject for future research.

Purpose The digital sustainable maturity (DSM) is an important component of organizational performance. However, it is a scarce concept and lacks measurement models. Hence, this article aims to develop and validate a conceptual model to measure DSM in supply chains. Design/methodology/approach The DSM dimensions were identified through a literature review, and their relevance was assessed using the fuzzy Delphi method (FDM). FDM combines qualitative evaluation (Delphi) with quantitative analysis (fuzzy logic) to reduce the uncertainty of expert judgments. In this process, 27 experts were consulted. The results were then used to develop a maturity grid for the domain under study. Findings The results indicated that, among the 33 dimensions extracted from literature, five were considered irrelevant for the model, resulting in 28 dimensions grouped into five macro-dimensions: digital, sustainable, organizational, supply chain and external. Based on these results, the proposed maturity grid comprised the selected dimensions, grouped into the macro-dimensions above, and structured across a six-level maturity scale. This model provides a comprehensive evaluation, considering the company’s internal and external aspects and positioning relative to other supply chain members. Practical implications The study enables organizations to assess their maturity level and identify pathways for enhancing performance and competitiveness. Originality/value The study’s novelty lies in presenting a new conceptual maturity model for DSM, a domain that has been scarcely explored in the literature.

The evaluation of supply chain (SC) alliances in a bidding environment has received increasing attention in today’s business environment. This study focuses on developing an evaluation tool to provide an improved method for assuring optimal alliance selection and efficient supply chain management (SCM) using a fuzzy Delphi method and fuzzy analytic hierarchy process and demonstrates how this can be extended from supplier selection to an alliance environment. The main contributions of this paper are the development of an interactive evaluation process for SC alliance in a bidding environment by introducing novel aspects such as a synthetic measurement index and a user-friendly platform. On this platform, the distributed users can work collaboratively using the Internet. Specifically, this paper develops a relatively stable system that employs a supply chain operations reference and a computer-integrated web-based platform (CIWBP) to support implementation. The efficiency and practical implication of the CIWBP are validated with a real-life case study. The developed system assists in the making of reasonable choices and identifies performance improvement objectives, all of which have the possibility of positively influencing future SCM development and assisting a bulk purchase manager in making better decisions. This proposed system could easily be extended to more complex real-world applications.

PurposeThis exploratory study illustrated an integrated academic library supply chain (IALSC) model to design the strategic planning management tool of the academic library. The supply chain (SC) model has been widely used in manufacturing industries and has also been applied in many service industries with the same objectives. However, very few studies for academic libraries, particularly the implementation of the integrated SC model, are being executed, although it has been proven that SC management in practice can enhance stakeholder satisfaction, increase revenues and decrease total costs. The academic library also needs to be successful in providing quality products, services and information to fulfil the library users’ needs within the library budget. This research aims to develop a verified model of the integrated SC for the academic library.Design/methodology/approachThis research used both qualitative and quantitative approaches to achieve its objectives. The proposed conceptual SC model, named as IALSC, for the academic library has been developed using the system thinking method; eventually, it has been validated through the fuzzy Delphi method, an expert judgement technique.FindingsThe research findings could contribute to academic library management in planning and formulating a roadmap for the library to increase its quality services for all stakeholders.Originality/valueThe conceptual model would have a high potential to be proposed as the strategic decision-making tool for an academic library, i.e. the flow of funds through the operations of the library, the library stakeholders’ satisfaction measurement, the decision process currently made by the library management team on the purchase of new library resources, the library resource suppliers, etc.