Evaluation of circular supply chains barriers in the era of Industry 4.0 transition using an extended decision-making approach

Assessing educational methods for tomorrow's supply chain leaders with the integration of skill development priorities: a fuzzy decision-making approach

Purpose

Effective educational methods are critical for successfully training future supply chain talent. The paper proposes a fuzzy multi-criteria decision-making model to evaluate and select the best educational method for tomorrow's supply chain leaders integrating skill development priorities in an uncertain environment.

Design/methodology/approach

The Grounded theory scheme is used to identify SC leaders' skillsets criteria and educational method alternatives. Fuzzy step-wise weight assessment ratio analysis sets the priority and determines the weight of 17 criteria. Eight decision-makers evaluate 13 alternatives using fuzzy linguistic terms. Fuzzy technique for order preference by similarity to ideal solution ranks and shows the most effective educational method. Sensitivity analysis presents the applicability of this study.

Findings

Its implementation in a university-industry collaboration case in Brazil, Mentored learning from industry experts is the best educational method. The skill development priorities are data analytics ability, end-to-end supply chain vision and problem-solving. Technical skills are the most important criteria that influence the selection of the optimal option and educational methods related to learning from others rank in the top teaching pool, including multidisciplinary cross-cultural training.

Originality/value

This paper is among the first to evaluate educational methods with skill development priorities integration for supply chain students using fuzzy SWARA–fuzzy TOPSIS. It provides actionable insights: a decision-making procedure for educational method selection, a broad skills profile for supply chain professional success and educational methods that professors can bring to in classroom/virtual environment.

Digitalization of manufacturing for implanting value, configuring circularity and achieving sustainability

Purpose

This paper explores the relationships between Industry 4.0-driven technologies and the circular economy-driven business model (CEDBM) components of value creation, delivery and capture along manufacturing processes.

Design/methodology/approach

Based on the literature, a research model is developed in which the three CEBDM components are represented by five components: product service system (PSS), product design, industrial symbiosis (IS), consumer interaction and pay-per-use/rental. For each of these five components, enabling Industry 4.0 technologies are identified and vague interdependence relationships were assessed using a fuzzy decision-making trial and evaluation laboratory (DEMATEL) method.

Findings

This paper contributes to the literature by exploring the relationships of the CEDBM components of value creation, value delivery and value capture with Industry 4.0-driven technological enablers. In addition, causal relationships between Industry 4.0 technologies and their relevance for facilitating CE-enabled manufacturing processes are identified, and finally, Industry 4.0-driven technological enablers of CE are categorized as base and front-end technologies.

Research limitations/implications

The findings suggest that value delivery-based differentiation provides new avenues for value creation and innovative forms of value capture in CEDBMs.

Practical implications

Practitioners can use the findings to develop a roadmap for Industry 4.0-driven technological solutions for CE.

Social implications

CE-driven processes of manufacturing provide not only opportunities for value capture, creation and delivery but also avenues for customer-centric product and service development and effective resource utilization.

Originality/value

This paper is the first to identify value creation, delivery and capture processes along with Industry 4.0-enabled manufacturing processes.

An Optimization Model for Appraising Intrusion-Detection Systems for Network Security Communications: Applications, Challenges, and Solutions

Cyber-attacks are getting increasingly complex, and as a result, the functional concerns of intrusion-detection systems (IDSs) are becoming increasingly difficult to resolve. The credibility of security services, such as privacy preservation, authenticity, and accessibility, may be jeopardized if breaches are not detected. Different organizations currently utilize a variety of tactics, strategies, and technology to protect the systems’ credibility in order to combat these dangers. Safeguarding approaches include establishing rules and procedures, developing user awareness, deploying firewall and verification systems, regulating system access, and forming computer-issue management groups. The effectiveness of intrusion-detection systems is not sufficiently recognized. IDS is used in businesses to examine possibly harmful tendencies occurring in technological environments. Determining an effective IDS is a complex task for organizations that require consideration of many key criteria and their sub-aspects. To deal with these multiple and interrelated criteria and their sub-aspects, a multi-criteria decision-making (MCMD) approach was applied. These criteria and their sub-aspects can also include some ambiguity and uncertainty, and thus they were treated using q-rung orthopair fuzzy sets (q-ROFS) and q-rung orthopair fuzzy numbers (q-ROFNs). Additionally, the problem of combining expert and specialist opinions was dealt with using the q-rung orthopair fuzzy weighted geometric (q-ROFWG). Initially, the entropy method was applied to assess the priorities of the key criteria and their sub-aspects. Then, the combined compromised solution (CoCoSo) method was applied to evaluate six IDSs according to their effectiveness and reliability. Afterward, comparative and sensitivity analyses were performed to confirm the stability, reliability, and performance of the proposed approach. The findings indicate that most of the IDSs appear to be systems with high potential. According to the results, Suricata is the best IDS that relies on multi-threading performance.