Providing an interpretive structural model of agile supply chain practices

An integrated Industry 4.0-Sustainable Lean Six Sigma framework to improve supply chain performance: a decision support study from COVID-19 lessons

Purpose

The COVID-19 pandemic era has severely hampered the economy over the globe. However, the manufacturing organizations across all the countries have struggled heavily, as they were among the least who worked on online mode. The organizations are adopting various innovative quality methodologies to improve their performance. In this regard, they are adopting the Sustainable Lean Six Sigma (SLSS) concept and Industry 4.0 technologies to develop products at a faster rate. The use of Industry 4.0 technologies may reduce material movement and supply chain disruptions with the help of smart intelligent systems. There is a strong synergy between SLSS and Industry 4.0 technologies, resulting in an integrated approach for adoption. This study aims to develop a framework that practitioners can use to adopt Industry 4.0-SLSS practices effectively.

Design/methodology/approach

This study portrays 31 Industry 4.0-SLSS practices and 22 performance metrics identified through a literature review to improve the manufacturing supply chain performance. To compute the weights of these practices, the Robust Best–Worst Method (RBWM) is used. The Pythagorean fuzzy combined compromise solution (PF-CoCoSo) method is used to rank performance metrics.

Findings

According to the RBWM results, “Process Development Practices (PDP)” are first among the major criteria, followed by “Organizational Management Practices (OMP)” at second, “Technology Adoption Practices (TAP)” at third, “Strategy Management Practices (SMP)” at fourth and “Executive Management Practices (EMP)” at fifth, whereas the PF-CoCoSo method resulted in the performance metric “On time product delivery” ranking first.

Research limitations/implications

The identified practices have the potential to significantly improve the performance of the manufacturing supply chain. Practices that encourage a sustainable manufacturing supply chain and the usage of emerging technology will benefit organizational effectiveness. Managers can assess performance using prioritized performance metrics.

Originality/value

During the COVID-19 pandemic era, this is one of the unique attempts to provide a framework to improve the manufacturing supply chain performance. This study integrates and identifies Industry 4.0-SLSS practices and performance metrics for enhancing overall performance.

Triggering sustainable firm performance, supply chain competitive advantage, and green innovation through lean, green, and agile supply chain practices

Due to extensive industrial activities, many environmental challenges have devastated human beings and environmental integrity. Therefore, sustainable supply chain (SC) practices (lean, green, and agile - LGA) gained momentum in the manufacturing industry. Considering the importance of LGA-SC, this study investigates the impact of LGA-SC practices on green innovation (GI), supply chain competitive advantage (SCPA), supply chain responsiveness (SCR), and sustainable firm performance (SFP). Data were collected from employees of the manufacturing industry in China. The proposed conceptual framework was verified by using structural equation modeling. The empirical results indicate that LGA-SC practices are statistically associated with GI, SCR, SCPA, and SFP. Moreover, this research finds that GI and SCR play mediating roles between LGA-SC practices and SCPA. GC positively moderates the relationship between LGA-SC practices and GI, and IP also acts as a strong moderator between GI and SCPA. To the authors' best knowledge, this study is the pioneer to provide insights about a novel framework combing LGA-SC practices, SCPA, and SFP with mediating role of GI and moderating role of GI and IP. This study supports managers of the Chinese manufacturing sector to further extend strong roots for LGA-SC adoption.

Supply chain resilience during the COVID-19 pandemic

The COVID-19 pandemic has challenged supply chains more seriously challenged than ever before. During this prolonged global health crisis, supply chain managers were forced to rely primarily on solutions developed for limited and foreseeable crises. This study aimed to understand how well existing solutions facilitated supply chain resilience in the UK perishable goods market. Consistent with this aim, we developed a research model based on the supply chain resilience literature and tested it with covariance-based structural equation modelling. Data were collected from 282 retail employees. Supply chain velocity was the preferred measure of resilience. The findings demonstrate that pandemic-related disruptions have affected resilience-building activities. While both proactive and reactive approaches have promoted resilience building during the pandemic, they have not been sufficient to ameliorate all the pandemic's negative effects. Innovation featured as the most effective factor, followed by robustness, empowerment, and risk management via reduced risk. The effect of firm size was significant only on supply chain risk management, with larger companies more efficiently applying risk management practices. The results emphasise the importance of innovation for supply chain resilience. Regardless of firm size, innovation works for every company. Empowerment is another costless and effective tool. Therefore, it is safe to conclude that innovation and empowerment can help organisations to manage their supply chains effectively during crises. Companies can strengthen their supply chain resilience by developing strong relationships with their supplier and employees.

Assessing the factors affecting implementation of unmanned aerial vehicles in Indian humanitarian logistics: a g-DANP approach

Purpose

The purpose of this paper is to analyze the factors affecting the implementation of unmanned aerial vehicles (UAVs) in Indian humanitarian logistics. The factors listed are significant as they are hindering the incorporation of this new technology into the humanitarian supply chain, thus creating inefficiencies in the humanitarian logistics sector.

Design/methodology/approach

This research is approached using a two-step process. In the first step, the particular barriers for UAV implementation are determined by a literature review and consultation with experts. Next, the proposed framework, a combination of grey-decision-making trial and evaluation laboratory (grey-DEMATEL) and analytic network process (ANP), i.e. g-DANP, is used to determine a hierarchical structure for the factors and sub-factors. The grey hypothesis provides sufficient analytical data to an otherwise lacking DEMATEL technique. Also, the use of ANP gives weightage to each factor, allowing us to categorize their importance further.

Findings

This study reveals that factors like expensive commercial solutions and high transport energy costs are significant factors of the “cause” group, whereas the uncertain cost for maintenance and repair and deficiency of high-level computing are crucial factors of the “effect” category. The mentioned factors, along with many others, are the main reasons for the delayed incorporation of UAVs in humanitarian logistics.

Practical implications

The results of this study present insights for humanitarian supply chain managers, UAV producers and policymakers. Those in the humanitarian logistics sector can use the findings of this study to plan for various challenges faced as they try and implement UAVs in their supply chain.

Originality/value

This research is unique as it analyses the general factors hindering the implementation of UAVs in Indian humanitarian logistics. The study enriches existing literature by providing an analytic approach to determine the weightage of various interrelations between the identified factors affecting UAV incorporation in the humanitarian supply chain.

Lean and agile metrics. Literature review and framework for measuring leagile supply chain

Purpose

The aim of this paper is to review metrics and develop a framework for measuring leagile supply chain. Metrics that are applicable in the lean, agile and leagile strategies are identified in the literature and are then combined into a framework that can reflect both agile and lean strategies – the leagile supply strategy.

Design/methodology/approach

This work is based on the systematic literature review. Literature was collected, then lean and agile metrics were extracted, analysed, counted and grouped into the framework. Findings are compared against literature on leagile supply chain.

Findings

Findings indicate that there are sets of metrics specific to lean strategy, such as are process-focused, cost, productivity, inventory and delivery-based metrics, and specific to agile such as flexibility, responsiveness, information sharing and cooperation. There are also metrics common for both strategies; they are related to time, quality and customer satisfaction. Lean measures are tangible and focused on internal processes and products, while agile measures are targeted at external environment.

Practical implications

The framework could be used by practitioners as a starting point for performance system design.

Originality/value

There is a need to stop looking at lean and agile as separate and distinct supply strategies. Results of this research indicate that lean and agile are interlinked, both are focusing on customer satisfaction and quality. Applying a proposed set of metrics enables to design supply chain measurement system that reflects both strategies to measure leagile supply chain. The framework could be used by practitioners as a starting point for performance system design.

A systematic literature review on supply chain approaches

Purpose

The purpose of this paper is to present green supply chain, resilient supply chain, agile supply chain, cold supply chain and lean supply chain (GRACL SC) procedures based on a detailed perspective, analyzing subjects in the past 19 years with a systematic literature review (SLR) of the papers reported from 2000 to 2019, and offering information and guidelines for further studies.

Design/methodology/approach

This research is based on 17 keywords in the title and topic of the articles and collects data from Web of Science (WOS) databases and objectively chooses 1,190 articles and performs meta-data analyses. Tables and statistical reports are based on the following three filters: publication year, authors and document type. At least, 39 publications from the ISI WOS has been examined for presenting information of categorization of the conducted research with regard to the content analysis, comprising the conceptual development and obstacles, cooperation with the supply chain elements, as well as mathematical and other optimization models.

Findings

Finally, this study answered three main questions in the research and demonstrates that the majority studies in the green supply chain (GSC) and a minimum number of studies on the cold supply chain have been conducted and 27 factors are chosen to achieve the 2000 to 2019 GRACL SCM model which robust and fit for Iranian food industries. The model shows that the agile, resilient and lean supply chain have direct effect on GSC and it can be said that all 27 groups which are selected for the final model of this research can be the main groups in the supply chain.

Originality/value

This paper was actually conducted by authors who reported it. To prevent plagiarized, redoubled efforts have been made and actually this paper is based on SLR methodology and the results are real and the researcher discusses the results appropriately. This investigation can have a positive impact within the field of expanding supply chain flexibility and lessening squander within the Iranian generation framework.

Analysing the critical success factors and the risks associated with third-party logistics in the food supply chain: a case of coffee industry

Purpose

The purpose of this study is to analyse various risks associated with third-party logistics (3PL) in the coffee supply chain and to present a framework that computes the influence of these risks on the critical success factors of the coffee supply chain.

Design/methodology/approach

The risks have been identified through a comprehensive literature review and validation by industry experts. The paper utilises an interpretive structural modelling (ISM) methodology for developing a hierarchical relationship among the CSFs. Furthermore, fuzzy MICMAC analysis is carried out to categorise these CSFs based on their driving power and dependence value. The fuzzy technique for order preferences by the similarity of an ideal solution (fuzzy-TOPSIS) approach has been applied to prioritise the risks associated with 3PL based on their ability to influence the CSFs of the coffee SC. Furthermore, we performed a sensitivity analysis to analyse the stability of the results obtained in this study.

Findings

This study illustrates ten risks associated with 3PL and five CSFs in the coffee supply chain. The analysis revealed that coffee enterprises need to develop a balanced pricing strategy to ensure a sustainable competitive advantage, whereas the lack of direct customer communication is the most dominant 3PL risk affecting the CSFs.

Practical implications

This research provides coffee enterprises with a generalised framework with set parameters that can be used to attain a successful coffee supply chain in any developing nation.

Originality/value

The study contributes to the literature by being the first kind of study, which has used fuzzy ISM-MICMAC to analyse the CSFs of the coffee supply chain and fuzzy-TOPSIS for analysing the impact of various risks associated with the 3PL in the coffee supply chain. Thus, this work can be considered a benchmark for future research and advancement in the coffee business field.

Priority Challenges of University Technology Transfer with Interpretative Structural Modeling and MICMAC Analysis

Translating university technology via the university–industry route faces an array of challenges. Subsequently, understanding the interrelationships of these challenges hopes to provide a better outlook on the complex nature of the university technology transfer (UTT) process. Such an agenda remains a gap in the domain literature. To advance this oversight, this study intends to identify the UTT challenges and determine their complex contextual relationships. The interpretative structural modeling, together with the MICMAC analysis, was sequentially adopted to derive the overarching structure of the challenges of UTT. A case study in a public university in the Philippines was conducted to carry out these objectives. Findings show that time constraints, knowledge being too theoretical, high costs of managing joint research projects, complex organizational structure, institutional bureaucracy, geographic distance, and lack of national benchmark are driving challenges that influence other challenges in impeding UTT in the representative Philippine university. These findings provide policy insights to key decision-makers and stakeholders on the success of technology transfers.