Digital supplier selection reinforcing supply chain quality management systems to enhance firm's performance

Key determinants to supply chain resilience to face pandemic disruption: An interpretive triple helix framework

Today, supply chain (SC) networks are facing more disruptions compared to the past. While disruptions are rare, they can have catastrophic long-term economic or societal repercussions, and the recovery processes can be lengthy. These can tremendously affect the SC and make it vulnerable, as observed during the COVID-19 pandemic. The identification of these concerns has prompted the demand for improved disruption management by developing resilient, agile, and adaptive SC. The aim of this study is to introduce an assessment framework for prioritizing and evaluating the determinants to supply chain resilience (SCR). To analyze the empirical data, fuzzy criteria importance through intercriteria correlation (fuzzy CRITIC) and fuzzy technique for order of preference by similarity to ideal solution (fuzzy TOPSIS) have been incorporated. Fuzzy CRITIC method was used to identify the critical determinants and fuzzy TOPSIS method was applied for determining relative ranking of some real-world companies. Finally, by developing propositions an interpretive triple helix framework was proposed to achieve SCR. This research stands out for its originality in both methodology and implications. By introducing the novel combination of Fuzzy CRITIC and Fuzzy TOPSIS in the assessment of determinants to SCR and applying these determinants with the help of interpretive triple helix framework to establish a resilient SC, this study offers a unique and valuable contribution to the field of SCR. The key findings suggest that 'Responsiveness' followed by 'Managerial coordination and information integration' are the most significant determinant to achieve SCR. The outcome of this work can assist the managers to achieve SCR with improved agility and adaptivity.

A Markovian-based fuzzy decision-making approach for the customer-based sustainable-resilient supplier selection problem

The supplier selection problem is one of the most important issues in supply chain management. So, many papers have investigated the mentioned problem. However, the related literature shows that researchers had less attention to the sustainability and resilience aspects based on the customer preferences in supplier selection problem. To cover this gap, this research tries to investigate the customer-based sustainable-resilient supplier selection problem. In this way, a Markovian-based fuzzy decision-making method is proposed. At the outset, the customer preferences are evaluated using a combination of the quality function deployment and the Markov transition matrix. Then, by combining the transition matrix and the fuzzy best-worst method, the weights of the indicators are calculated. Finally, the decision matrix is formed and the performance of suppliers is measured based on the multiplication of the decision matrix and vector of sub-criteria weights. Regarding the recent pandemic disruption (COVID-19), the importance of online marketplaces is highlighted more than the past. Hence, this study considers an online marketplace as a case study. Results show that in a pandemic situation, the preferences of customers when they cannot go shopping normally will change after a while. Based on the Markov steady state, these changes are from the priority of price, availability, and performance in initial time to serviceability, reliability, and availability in the future. Finally, based on the FBWM results, from the customer point of view, the top five sub-criteria for sustainable-resilient supplier selection include cost, quality, delivery, responsiveness, and service. So, based on these priorities, the case study potential suppliers are prioritized, respectively.

Interval valued intuitionistic fuzzy analytic hierarchy process-based green supply chain resilience evaluation methodology in post COVID-19 era

Supply chain organizations should calmly and cautiously take the most accurate and sustainable decisions quickly and put them into practice. It is obvious that traditional time series-based demand and supply planning approaches are insufficient to meet current business needs due to factors such as sharp changes in market and commercial dynamics, pandemics, and natural disasters on the management of green supply chains, especially these days. In the near future, there will be a need for more resilient supply chains with a flexible business models that are not affected by sudden changes and that can make sustainable decisions dynamically. Additionally, all stakeholders must act with a green supply chain approach to conduct production and service activities in a way that causes the least damage to nature. Companies must build more resilient supply chains by considering environmental sensitivities to compete in the market and ensure their continuity. In this context, the green supply chains should be evaluated according to their resilience. For this purpose, Supply Chain Operations Reference (SCOR) model is extended with novel performance attributes to evaluate resilience of green supply chains in this study. The SCOR-embedded novel green supply chain resilience evaluation model is structured as a three-level performance attribute hierarchical structure. Then, the model is handled as a multi-criteria decision-making problem to determine importance of the performance attributes. Best Worst Method integrated Interval Valued Intuitionistic Fuzzy Analytic Hierarchy Process is used to determine the importance of performance attributes. Most important performance attributes are determined in each level of hierarchy. According to results, organizational factors play a key role to build more resilient supply chains. Especially, integrated systems are required for supply chain resilience.

Leagile and sustainable supplier selection problem in the Industry 4.0 era: a case study of the medical devices using hybrid multi-criteria decision making tool

Given the crucial role of the supplier selection problem (SSP) in today's competitive business environment, the present study investigates the SSP by considering the leagile, sustainability, and Industry 4.0 (I4.0) indicators for the medical devices industry (MDI). In this regard, at the outset, the list of criteria and sub-criteria is provided based on the literature and experts' opinions. Then, the importance of the indicators is measured utilizing the rough best-worst method (RBWM). In the next step, the potential suppliers are ranked employing the multi-attributive border approximation area comparison (IR-MABAC) method. Due to the crucial role of medical devices during the COVID-19 outbreak, the present work selects a project-based organization in this industry as a case study. The obtained results show that agility and sustainability are the most important criteria, and manufacturing flexibility, cost, reliability, smart factory, and quality are the most important sub-criteria. The main theoretical contributions of this study are considering the leagile, sustainability, and I4.0 criteria in the SSP and employing the hybrid RBWM-IR-MABAC method in this area for the first time. On the other side, The results of this research can help supply chain managers to become more familiar with the sustainability, agility, leanness, and I4.0 criteria in the business environment.

A goal programming-based fuzzy best-worst method for the viable supplier selection problem: a case study

Since the COVID-19 outbreak has led to drastic changes in the business environment, researchers attempt to introduce new approaches to improve the capability and flexibility of the industries. In this regard, recently, the concept of the viable supply chain, which tried to incorporate the leagile, resiliency, sustainability, and digitalization aspects into the post-pandemic supply chain, has been introduced by researchers. However, the literature shows that there is lack of study that investigated the viable supplier selection problem, as one of the crucial branches of viable supply chain management. Therefore, to cover this gap, the current work aims to develop a decision-making framework to investigated the viable supplier selection problem. In this regard, owing to the crucial role of the oxygen concentrator device during the COVID-19 outbreak, this research selects the mentioned product as a case study. After determining the indicators and alternatives of the research problem, a novel method named goal programming-based fuzzy best-worst method (GP-FBWM) is proposed to compute the indicators' weights. Then, the potential alternatives are prioritized employing the Fuzzy Vlse Kriterijumsk Optimizacija Kompromisno Resenje method. In general, the main contributions and novelties of the present research are to incorporate the elements of the viability concepts in the supplier selection problem for the medical devices industry and to develop an efficient method GP-FBWM to measure the importance of the criteria. Then, the developed method is implemented and the obtained results are analyzed. Finally, managerial and theoretical implications are provided.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00500-022-07572-0.

Emerging competencies for logistics professionals in the digital era: A literature review

The speed of technology integration among businesses has accelerated during the COVID-19 pandemic due to the work-from-home arrangements and safe distancing regulations, prompting businesses to automate operations and digitalize work environments. These impacts have disrupted work environments and operational processes, and a fresh set of competencies is required to stay competent in this new normal. Consequently, there is a need to develop a state-of-the-art competency framework for logistics professionals during these trying times. This study has adopted the Preferred Reporting Items for Systematic Reviews and Meta-Analyses to review, identify, and update the emerging competencies required by logistics professionals. The relevant academic documents were narrowed down to 81 and were used to identify the emerging competencies relevant to Industry 4.0 and COVID-19. The competencies were subsequently categorized into four key domains i.e., business, logistics, digital, and personal competencies, with a total of 17 sub-domains. This state-of-the-art framework contributes to academic research by updating the existing competency frameworks. Future research can also build upon this holistic list of emerging competencies by utilizing it to reduce the competency gaps faced by those who are less technology savvy i.e., older logistics professionals. Additionally, future research can correlate the competency framework to organizational learning theories to improve the overall performance of logistics companies.

A Conceptual Model Proposal to Assess the Effectiveness of IoT in Sustainability Orientation in Manufacturing Industry: An Environmental and Social Focus

The scientific literature reveals that there is a gap oriented towards empirical study of the relationship between the Internet of Things (IoT) and sustainability in manufacturing industries. This paper aims to fill this gap by proposing a new conceptual model (CM) for evaluating the effectiveness of IoT technologies in relation to their orientation towards socio-environmental sustainability and the circular economy approach. The research methodology for developing the CM follows the PRISMA protocol, and the data are obtained from the Web of Science (WoS) and Elsevier Scopus databases, focusing on the relationship between IoT and sustainable manufacturing. The PRISMA methodology results in six articles whose statements contribute to the development of the CM. The statements are identified, categorized and organized from the selected articles and divided into dimensions, namely: IoT technology and environmental and social context. The CM incorporates these dimensions and their constructs and indicators to support the assessment of the effectiveness of IoT technologies in relation to socio-environmental sustainability and the circular economy approach. The result of this study is a CM whose objective is to guide organizations in the use of IoT technologies applied to the production and supply chain, in order to create advances in the field of sustainability and the circular economy. The CM will be validated and applied in a manufacturing industry in the next publication. The paper contributes to management practices as it explores the knowledge of performance measurement and evaluation in the context of IoT, sustainability and the circular economy approach.

Challenges to agile project management during COVID-19 pandemic: an emerging economy perspective

Globally, COVID-19 pandemic has affected more than 214 countries across the world, creating uncertainty and affecting every institution and individual. The organisations recognise the need of agile projects that may offer several benefits including faster deployments, adaptability and best fit alignment to fulfill the customer needs. Implementing agile projects is the key to survive in the post pandemic situation, but emerging economies have limited scope for implementation. The present study determines the critical factors that restricts implementation of agile projects in emerging economies. The critical factors are identified from literature and validated by experts. The validated critical factors are further assessed to identify the cause-and-effect relationship using Fuzzy Decision-Making Trial and Laboratory (F-DEMATEL) method. The results of the study posit ‘Skepticism towards the new way of working’ is the most significant causal factor affecting other factors. This study is an attempt to help project managers to consider the significant factors for agile project implementation in post pandemic situation. The project managers may be benefitted from this study by considering these factors to manage challenges for agile project implementation in emerging economies. This study contributes to assess the influencing and the influenced challenging factors for agile project implementation.

Assessing Effectiveness of Humanitarian Activities against COVID-19 Disruption: The Role of Blockchain-Enabled Digital Humanitarian Network (BT-DHN)

The COVID-19 pandemic has affected more than 214 countries across the world, disrupting the supply of essential commodities. As the pandemic has spread, humanitarian activities (HAs) have attempted to manage the various situation but appear ineffective due to lack of collaboration and information sharing, inability to respond towards disruption, etc. This study aims to determine and provide insights into the critical factors that may enhance the effectiveness of HAs during the pandemic. A systematic literature review was undertaken to explore critical factors and validated by experts using the fuzzy–Delphi method. These were further assessed to identify the cause-and-effect relationship by means of the fuzzy decision-making trial and laboratory (DEMATEL) method. The results show that building a blockchain-enabled digital humanitarian network (BT-DHN) is the most significant factor during the pandemic. The use of digital platforms for sharing real-time information enhances the effectiveness of HAs. This study offers stakeholders, policymakers, and decision-makers the opportunity to consider these factors in strategic planning to deal with pandemic disruption.

An exploration of organizational readiness factors for Quality 4.0: an intercontinental study and future research directions

Purpose

Quality 4.0 incorporates the role of automation and digitization and provides competitive advantage for organizations by enhancing customer experience and increase profitability. The purpose of this study is to critically examine the organizational readiness factors for the successful implementation of Quality 4.0 implementation and assess their importance.

Design/methodology/approach

This study applies a quantitative research methodology to examine readiness factors of Quality 4.0 in organizations by 147 senior management professionals in various organizations including manufacturing and service companies in America, Asia and Europe participated through an online survey.

Findings

The readiness factors for Quality 4.0 were critically ranked amongst manufacturing and service organizations by senior management professionals from three continents. Five significant reasons for non-adoption of Quality 4.0 were lack of resources, inability to link Quality 4.0 with the corporate strategy and objectives, lack of understanding of benefits, high initial investment and the current quality management strategy and methods are already delivering good results hence unsure of the need for Quality 4.0. The handling of big data in quality management was the most important factor for adopting Quality 4.0, irrespective of the size and nature of the organization. More accuracy and less errors and improved decision-making the factors of adopting Quality 4.0 in service sector were not significant for manufacturing sector. Small and medium-sized enterprises (SMEs) reported that costs and time savings over the long run were not so significant.

Practical implications

This study is focussed on the significance of pros and cons of adopting Quality 4.0 in organizations. Senior managers in both large and SMEs can benefit immensely from understanding before investing heavily towards implementing Quality 4.0. The importance of identified organizational readiness factors for the successful adoption of Quality 4.0 can be used as indicators to understand how ready an organization is to implement Quality 4.0. The top three readiness factors for the successful adoption of Quality 4.0 were identified as: top management commitment, leadership and organizational culture. Improved understanding of the readiness factors can be highly beneficial to senior quality professionals in both manufacturing and service companies in the journey towards successful implementation of Quality 4.0.

Originality/value

This is the first empirical study on assessing Quality 4.0 readiness factors at an intercontinental level and therefore serves as a foundation for many future studies. The study provides a theoretical foundation for the Quality 4.0 in terms of organizational readiness for successful adoption and overcoming implementation challenges. During the planning, implementation and progress review of Quality 4.0, review the readiness factors while planning and resourcing a Quality 4.0 implementation strategy to ensure effective performance.

The Influence of the Digital Supply Chain on Operational Performance: A Study of the Food and Beverage Industry in Indonesia

In this rapidly developing digital era, digital transformations take place within every industry, and they have effects on the management of the supply chains. The aim of this study is to delve into the influence of the digital supply chain on the quality, productivity, and cost reduction aspects of operational performance. This study relies on quantitative methodology and data collected from the food and beverage industry of Indonesia. Data from a survey comprising a total of 209 responses were selected for investigation. PLS-SEM was used to perform the analysis. The investigation reveals that the digital supply chain has significant effects on operational performance in terms of quality, productivity, and cost reduction performance. This study contributes to the understanding of supply chain management by addressing the knowledge gap associated with the digital supply chain. In particular, it has concentrated on the hitherto unresearched effect of operational performance in the context of the Indonesian manufacturing industry.