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This study aims to propose a collaborative knowledge-based ontological research model for designing a collaborative product development process (PDP) while considering different design for X techniques.

This study follows a thematic literature analysis to identify the key design concepts needed to assess environmental, service, safety, manufacture and assembly, supply chain and quality concerns in developing a collaborative PDP.

The proposed model provides a guide for methodology, engineering and ontology evaluation metrics (verification, assessment and validation). The findings benefit both practitioners and managers because they address the key knowledge taxonomy needed to assist them in storing information, promoting teamwork and making decisions in a collaborative PDP while incorporating various design for X approaches and product life cycles.

This study introduces a novel knowledge-based collaborative ontological research model, which is specifically designed to tackle the challenges of developing collaborative products in the contemporary landscape. The model presents a significant and valuable contribution to the field by introducing an ontological approach for acquiring, representing and leveraging knowledge in a computer-interpretable format to support the design of collaborative products. In addition, it provides a comprehensive guide for evaluating the effectiveness and efficacy of the ontology developed.

Blockchain technology (BT) is creating a new standard for all business operations. It can assist businesses in handling the complexity of circular digital supply chain (DCM) management. Despite this optimistic view, several barriers hinder its implementation. In this regard, this study contributes to Industry 4.0, circular economy (CE), the viability with a critical emphasis on its potential ramifications and influence on the future agenda while using BT technology in the supply chain (SC). In addition, the research reduces the knowledge gap by investigating and ranking the key barriers to the deployment of BT in viable circular digital supply chains (VCDSCs) and studies their interdependencies and causal relationships. The purpose of this paper is to address these issues.

The barriers to BT adoption in the VCDSC are identified through a thorough literature review and considering viability performance. These barriers are then classified using the analytical hierarchy process (AHP) method. Decision-making trial and evaluation laboratory (DEMATEL) is then employed to examine the cause/effect, correlation, and connection among the 14 barriers selected barriers from the AHP classification to estimate each barrier's overall degree of impact over the others.

This paper identifies and analyzes the BT adoption barriers in the VCDSC as well as examines how the key barriers interact. As a result, according to the AHP/DEMATEL method, the most prominent influencing barriers to the BT implementation in the VCDSC are “Data transparency,” “Market competition,” “Missing infrastructure,” “Lack of standardization,” “Complex protocol,” “Lack of industry involvement,” “Financial constraints,” “Missing infrastructure,” “Data transparency” and “Interoperability.” The outcomes offer a potential path for identifying important barriers as well as insight into the implementation of BT in the SC while integrating different capabilities such as viability, sustainability and CE principles.

Managers and researchers will benefit from this research by gaining an understanding of the challenges that must be prioritized and examined for BT to be implemented successfully in the VCDSC.

The use and implementation of blockchain-enabled VCDSC continue to face challenges despite an increase in relevant practice and research. Despite the benefits of BT, managers struggle to apply such technology in the context of their company. In this respect, this paper uses an integrated AHP–DEMATEL for categorizing the BT barriers as well as the interrelationship between them. In this respect, this paper presents the BT barriers studied are those related to the use of BT in the SC while integrating different paradigms such as viability, digitalization and CE. While many studies look at the barriers to BT adoption; none of them has ever included the viable capability, which means the ability to “react agilely to positive changes, be resilient to absorb negative events and re-cover after disruptions and survive at long-term periods.” The study concludes with insightful comments based on the findings and suggestions for eradicating those obstacles and their associated effects.

This article aims to assess risks related to the supply chain 5.0 digitalization. It aims to analyze interdependencies and causal relationships between critical digital supply chain 5.0 risks, emphasizing the need for proactive management to address emerging challenges.

Through an extensive literature review and expert judgment, risks related to supply chain 5.0 digitalization are identified. An integrated approach for risk assessment is employed, where the Analytic Hierarchy Process (AHP) is utilized to prioritize these risks. Subsequently, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is employed to investigate cause-and-effect relationships among the identified top 10 risks. This comprehensive analysis forms the basis for informed strategic management decision-making.

The analysis identifies significant influences of “Dependence on technology,” “Complexity”, “Potential system failures”, and “Cyber security” while “Environmental impact” and “Socio-economic disparities” emerge as prominent risks in supply chain 5.0 digitalization. These findings offer actionable insights for management decision-making, guiding the formulation of strategies to address and mitigate critical risks.

The proposed integrated approach (AHP-DEMATEL) provides valuable insights for managers to effectively mitigate digital supply chain 5.0 risks and strategically respond to disruptions. By prioritizing risks, organizations can allocate resources efficiently and address the most critical challenges first, minimizing long-term damage to resilience. Embracing this approach enables practitioners to enhance overall supply chain resilience, guiding key management decisions for the development of sustainable and adaptive strategies.

This paper marks the first comprehensive attempt to assess supply chain 5.0 digitalization risks using decision-making methods like AHP and DEMATEL. The integrated approach contributes novel insights to the field of supply chain risk management, specifically aiding management decision-making in the face of digitalization challenges.

Under the current untrusted business environment, digital technologies, such as blockchain technology (BT), show the potential to digitally transform SC processes particularly the sourcing process (SP). Indeed, this process suffers from a lack of digitalization, a lack of trust and a high workload in the automotive supply chain (ASC). Therefore, BT coupled with smart contracts can deal with such issues by fostering trust, transparency, reliability and traceability as a digital solution.

This paper conducts multiple case studies in the automotive sector and interviews 11 managers from two firms. It follows the managers’ perspective to identify and analyze the main issues that occurred while conducting this process using the existing technology.

It proposes a new architecture for the smart sourcing process (SSP) that uses BT & smart contracts to mitigate the identified issues, enable traceability, improve resilience, eliminate intermediaries, automate tasks, and enhance trust and data management. Also, the paper provides a decision tree to help determine which blockchain platform is needed for adopting the SSP solution.

This study is useful for both academics and practitioners as it demonstrates the digitalization of one of the SC processes using BT and smart contracts, as well as develops a roadmap for digitalizing the SP of the ASC, and solves its vulnerabilities.

BT has been used by researchers to digitalize the sourcing process only in the public procurement area. Considering all the faced challenges by the private procurement area, this paper aims to present a new architecture for the digitalization of the SP using BT and smart contracts in the ASC as a private SC.

As the global focus on supply chain management has shifted toward the importance of digitalization, resilience and sustainability to ensure viability, this paradigm merits special consideration in the industrial supplier selection process in a VUCA (Volatile, Uncertain, Complex and Ambiguous) world. Additionally, the increasing geopolitical challenges further complicate the industrial supplier selection process, necessitating robust decision-making frameworks. Thus, this paper aims to present a decision-making system using a fuzzy inference system (FIS) for industrial supplier evaluation and selection, considering a new criterion: viability.

Fuzzy set theory, particularly a FIS, is used to address the subjectivity of decision-makers’ preferences. The suggested method’s validity is evaluated using a real automotive case study for industrial supplier selection situations.

Seventeen key criteria for viable industrial supplier selection were identified and used to evaluate and select the case study firm’s industrial supplier. The chosen supplier (B) demonstrated superior resilience, sustainability and digitalization capabilities, making it preferable to others. Specifically, supplier (B) exhibited exceptional adaptability to disruptions, a strong commitment to sustainable practices and advanced digital integration that enhances operational efficiency.

This study provides valuable insights for researchers and professionals by proposing a comprehensive industrial supplier selection system. Integrating diverse criteria is essential for viable performance in supply chains that enhances robustness and adaptability, supporting more strategic decision-making in supplier evaluation amid global and network-related challenges.

This novel paper introduces a new criterion, i.e. viability, in the industrial supplier selection process in the VUCA environment. In addition, it proposes a decision-making system for viable supplier performance evaluation. Furthermore, it validates the proposed FIS in an automotive case study.

The COVID-19 pandemic has caused major disruptions and revealed the fragilities in supply chains. This crisis has re-opened the debate on supply chain resilience and sustainability. This paper aims to investigate distinct impacts of COVID-19 on supply chains. It identifies both short- and medium-to-long-term measures taken to mitigate the different effects of the pandemic and highlights potential transformations and their impacts on supply chain sustainability and resilience.

To address the purpose of the study, a qualitative research approach based on case studies and semi-structured interviews with 15 practitioners from various supply chain types and sectors was conducted. Studied organizations included necessary and non-necessary supply chain sectors, which are differently impacted by the COVID-19 pandemic.

This study reveals five main challenges facing supply chains during COVID-19, including uncertain demand and supply, suppliers' concentration in specific regions, globalized supply chains, reduced visibility in the supply network, and limited supplier capacity. To help mitigate these challenges and develop both sustainability and resilience, this paper identifies some mitigating actions focusing on the promotion of the health and wellbeing of employees and supply chain stabilization. Further, in the post-COVID era, sustainable and resilient supply chains should consider regionalization of the supply chain, diversification of the supply network, agility, collaboration, visibility, and transparency; and should accelerate the use of smart technologies and circular economy practices as dynamic capabilities to improve supply chain resilience and sustainability.

This study contributes to exploring the sustainability- and resilience-related challenges posed by the COVID-19 pandemic. Its findings can be used by researchers and supply chains decision-makers to limit disruptions and improve responsiveness, resilience, sustainability, and restoration of supply chains. The results support benchmarking through sharing of the best practices and organizations can also integrate the different capabilities discussed in this study into the processes of selection and auditing of their suppliers.

Selecting the optimal supplier is a challenging managerial decision that involves several dimensions that vary over time. Despite the considerable attention devoted to this issue, knowledge is required to be updated and analyzed in this field. This paper reveals new opportunities to advance supplier selection (SS) research from a multidimensional perspective. Moreover, this study aims to formalise SS knowledge to enable the appropriate selection of sustainable, resilient and circular criteria.

This study is developed in two stages: first, a systematic literature review is conducted to select relevant papers. Descriptive and thematic analyses are employed to analyze criteria, solving approaches and case studies. Second, a criterion knowledge-based framework is developed and validated by experts to be implemented as ontology using Protégé software.

Evaluating the viability of suppliers need further studies to integrate other criteria and to align SS objectives with research advancement. Artificial intelligence tools are needed to revolutionize and optimize the traditional techniques used to solve this problem. Literature lucks frameworks for specific sectors. The proposed ontology provides a consistent criteria knowledge base.

For academics, the results of this study highlight opportunities to improve the viable SS process. From a managerial perspective, the proposed ontology can assist managers in selecting the appropriate criteria. Future works can enrich the proposed ontology and integrate this knowledge base into an information system.

This study contributes to promoting knowledge about viable SS. Capitalizing the knowledge base of criteria in a computer-interpretable manner supports the digitalization of this critical decision.

In the era of industry 4.0, managing the design is a challenging mission. Within a dynamic environment, several disciplines have adopted the complex adaptive system (CAS) perspective. Therefore, this paper aims to explore how we may deepen our understanding of the design process as a CAS. In this respect, the key complexity drivers of the design process are discussed and an organizational decomposition for the simulation of the design process as CAS is conducted.

The proposed methodology comprises three steps. First, the complexity drivers of the design process are presented and are matched with those of CAS. Second, an analysis of over 111 selected papers is presented to choose the appropriate model for the design process from the CAS theory. Third, the paper provides methodological guidelines to develop an organizational decision support system that supports the complexity of the design process.

An analysis of the key drivers of design process complexity shows the need to adopt the CAS theory. In addition to that, a comparative analysis between all the organizational methodologies developed in the literature leads the authors to conclude that agent-oriented Software Process for engineering complex System is the appropriate methodology for simulating the design process. In this respect, a system requirements phase of the decision support system is conducted.

The originality of this paper lies in the fact of analysing the complexity of the design process as a CAS. In doing so, all the richness of the CAS theory can be used to meet the challenges of those already existing in the theory of the design.