Measuring the flexibility index for a supply chain using graph theory matrix approach

Improving supplier performance and strategic sourcing decisions by integrating jobshop scheduling, inventory management and agile new product development

Purpose

The purpose of this study is to improve supplier performance and strategic sourcing decisions by integrating jobshop scheduling, inventory management and agile new product development. During the COVID-19 pandemic, the organizations have struggled a lot to maintain the supplier performance and strategic sourcing decisions in the organizational benefit. However, in this context, the organization’s agile new product development (ANPD) process must be aligned with this requirement by maintaining the inventory and jobshop scheduling. As a result, identifying ANPD indicators, performance metrics and developing a structural framework to guide practitioners at various stages for smooth adoption is essential to improve the overall performance.

Design/methodology/approach

A comprehensive literature review is conducted to identify jobshop scheduling, inventory management and ANPD indicators along with the performance metrics, and the hierarchical structure is developed with the help of expert opinion. The modified stepwise weight assessment ratio analysis (SWARA) and weighted aggregated sum product assurance (WASPAS) techniques, along with expert judgement, are used in this study to calculate the weights of the indicators and the ranking of the performance metrics.

Findings

As per the weight computation by SWARA method, the strategy indicators have the highest relative weight, followed by the product design indicators, management indicators, technical indicators, supply chain indicators and organization culture indicators. According to the ranking of performance metrics obtained through WASPAS, the “frequency of new product development is at the top”, followed by “advances in product design and development” and “estimated versus actual time to market”.

Research limitations/implications

It is believed that the framework developed will help industrial practitioners to plan effectively to improve supplier performance. The indicators identified may guide the ANPD penetration, and performance metrics may be useful for evaluation and comparison.

Practical implications

The outcomes of the present study will be extremely beneficial for the industry practitioners to improve the supplier performance. The indicators identified may guide the ANPD penetration, and performance metrics may be useful for evaluation and comparison.

Originality/value

A unique combination of modified SWARA–WASPAS technique has been used in this study which would be beneficial for organizations willing to adopt the jobshop scheduling and inventory management and ANPD for improving supply chain performance.

Medical supply chain integrated with blockchain and IoT to track the logistics of medical products

Nowadays blockchain technology plays a vital role in creative developments and important discoveries in the world. Blockchain develops secure and trustworthy platforms for data sharing in various application areas such as secure sharing of medical data, Anti-money laundering, tracking systems, Supply chain, and logistics monitoring, Crypto-currency exchange, etc. Today's Supply chain in the healthcare sector faces many problems like security, transparency, tampering with medical products, counterfeit drugs, more paperwork, high cost, and more time-consuming process while transporting medical equipment from manufacture to end-users. To overcome these problems, we introduce Novel Approach for Integrated IoT (Internet of Things) With Blockchain in Health Supply Chain (NAIBHSC) approach. By using this approach, we can eliminate all supply chain-related issues between suppliers and end-users. The goal of this research is by combining Blockchain technology with IoT to develop a smart health supply chain management system. This approach provides security, privacy, trust, visibility, decentralized tracking and tracing of the medical product, avoids counterfeit drugs, avoids the damage to medical components, authentication, reduces the cost, and provides the status of the products during the shipment process between manufacturers to end-user. In this approach, we conduct a series of experiments on a different group of users. The experimental results show that compare to existing approaches our proposed NAIBHSC approach gives better response time that is the average Transaction Per Second (TPS) for a group of 500 users is 100 milliseconds, reduces the latency time that is average latency time for 500 users group has 403 milliseconds, and improves the overall performance of the smart health supply chain management system.

Valuation of inter-boundary inefficiencies accounting IoT based monitoring system in processed food supply chain

Nowadays, demand for processed food items is escalating towards the record consumption volume, which resulted in the surging of the Food Supply Chain (FSCs) network. But, the flow of the commodities through the various channels of the FSC is hampered by the various inefficiencies, which persist due to a lack of monitoring. This results in the widening of the gap between the supply and demand patterns allied with it. To tackle the same, and cater to the upwelling shares of the consumer demand, the dynamics of the Food Supply Chain Performance System (FSCPS) need to be tuned with the avenues of Industry 4.0 practices. Presented work clusters the various attributes of the inefficiencies, which hampers the processed FSCs dynamics and maintenance-related activities, elaborated by their sub-attributes based upon their events of occurrences. A model comprising the various attributes and sub-attributes of inefficiencies constrained outside the organizational boundaries of a firm’s FSC is rendered in this study. For effective handling of the mutual interdependencies persisting between the attributes, the methodology of the Graph Theory and Matrix Approach (GTMA) is exercised for the analysis of the developed model. Outcomes of the presented work felicitate the managers of industries, its allied corporates and numerous stakeholders of the FSC to ground a robust decisional framework, governing policies and managing the process permutations.

Towards measuring SMEs performance amid the COVID-19 outbreak: exploring the impact of integrated supply chain drivers

Purpose

This study aims to explore supply chain disruptions during the COVID-19 pandemic in the small and medium enterprise (SME) sector in Oman. This study analyzes the impact on selected supply chain drivers – facilities, inventory, transportation and sourcing. It further intends to explore whether the supply chain challenges faced by the SME sector in Oman impact their overall performance.

Design/methodology/approach

This study follows the quantitative technique of structural equation modeling to examine the proposed hypotheses. Data were collected electronically from SME managers/owners/entrepreneurs. All items were adopted and measured using a five-point Likert scale. One hundred and four complete and usable responses were received and considered.

Findings

The data was analyzed using SPSS and PLS statistical software. The model has been supported empirically, and the results showed a significant relationship between supply chain drivers and SMEs’ overall performance in Oman, except for supply chain inventory. The results have demonstrated that the COVID-19 pandemic has affected the SMEs’ supply chain drivers in Oman and, consequently, their overall performance.

Practical implications

The results of this research can drive the development and implementation of a supply chain management strategy. This research will help policymakers induce the performance of SMEs affected by the COVID-19 pandemic. It would further enhance strategic sourcing and supplier performance considering the developed practices associated with the resource-based view.

Originality/value

The originality of the current study lies in its ability to empirically test two models within the Omani SMEs context while considering the supply chain drivers as a single variable or dividing it into four separate independent variables. This study would provide a preview for scholars for such empirical investigation and serve as a reference for policymakers and practitioners to maintain a management system of crises that may protect the SME supply chain drivers.

Fuzzy DEMATEL-QFD for Designing Supply Chain of Shipbuilding Materials Based on Flexible Strategies

Shipbuilding materials are characterized by diverse kinds, large quantities and wide distribution of suppliers, which make the supply network complicated. Complex networks have led to increasing uncertainties that may cause disruptions in the supply chain. Flexibility is an effective measure to cope with uncertainty, thus this paper aims to integrate flexibility into the supply chain of shipbuilding materials and explore supply, logistics, organization and quality flexibility by focusing on the requirements of shipbuilding enterprises. This paper combines Quality Function Deployment (QFD), fuzzy theory and Decision Making Trial and Evaluation Laboratory (DEMATEL) methods to guide practical design. After determining five customer requirements (CRs) and 24 design requirements (DRs), QFD links CRs and DRs to determine the most important feasible DRs for improvement of supply chain flexibility. Research results reveal that the most important design requirements can be summarized into four aspects, namely domestic procurement, supply chain member cooperation, supplier supervision, and emergency response construction. Moreover, it is found that long-term strategic partnerships with suppliers and strategic logistics outsourcing are effective strategies. This paper provides insight into implications for strategic decisions of shipbuilding enterprises.

Analysis of barriers intensity for investment in big data analytics for sustainable manufacturing operations in post-COVID-19 pandemic era

Purpose

The study presents various barriers to adopt big data analytics (BDA) for sustainable manufacturing operations (SMOs) post-coronavirus disease (COVID-19) pandemics. In this study, 17 barriers are identified through extensive literature review and experts’ opinions for investing in BDA implementation. A questionnaire-based survey is conducted to collect responses from experts. The identified barriers are grouped into three categories with the help of factor analysis. These are organizational barriers, data management barriers and human barriers. For the quantification of barriers, the graph theory matrix approach (GTMA) is applied.

Design/methodology/approach

The study presents various barriers to adopt BDA for the SMOs post-COVID-19 pandemic. In this study, 17 barriers are identified through extensive literature review and experts’ opinions for investing in BDA implementation. A questionnaire-based survey is conducted to collect responses from experts. The identified barriers are grouped into three categories with the help of factor analysis. These are organizational barriers, data management barriers and human barriers. For the quantification of barriers, the GTMA is applied.

Findings

The study identifies barriers to investment in BDA implementation. It categorizes the barriers based on factor analysis and computes the intensity for each category of a barrier for BDA investment for SMOs. It is observed that the organizational barriers have the highest intensity whereas the human barriers have the smallest intensity.

Practical implications

This study may help organizations to take strategic decisions for investing in BDA applications for achieving one of the sustainable development goals. Organizations should prioritize their efforts first to counter the barriers under the category of organizational barriers followed by barriers in data management and human barriers.

Originality/value

The novelty of this paper is that barriers to BDA investment for SMOs in the context of Indian manufacturing organizations have been analyzed. The findings of the study will assist the professionals and practitioners in formulating policies based on the actual nature and intensity of the barriers.

Evaluation of supply chain resilience index: a graph theory based approach

Purpose

The present study aims at developing a model to quantify supply chain resilience as a single numerical value. The numerical value is called resilience index that measures the resilience capability of the case company's supply chain. The model calculates the index value based on the interactions between the enablers of supply chain resilience and its dimensions.

Design/methodology/approach

Graph theoretic approach (GTA) is used to evaluate the resilience index for the case company's supply chain. In GTA, the dimensions of resilience enablers and their interdependencies are modelled through a digraph. The digraph depicting the influence of each dimension is converted into an adjacency matrix. The permanent function value of the adjacency matrix is called the resilience index (RI).

Findings

The proposed approach has been illustrated in context of an Indian automobile organization, and value of the RI is evaluated. The best case and the worst-case values are also obtained with the help of GTA. It is noted from the model that strategic level dimension of enablers is most important in contributing towards supply chain resilience. They are followed by tactical and operational level enablers. The GTA framework proposed will help supply chain practitioners to evaluate and benchmark the supply chain resilience of their respective organizations with the best in the industry.

Originality/value

A firm can compare the RI of its own supply chain with other's supply chain or with the best in the industry for benchmarking purpose. Benchmarking of resilience will help organizations in developing strategies to compete in dynamic market scenario.

Bullwhip effect reduction map for COVID-19 vaccine supply chain

The growing COVID-19 virus pandemic outbreak causes an urgent need to produce its vaccine. Pharmaceutical companies would encounter a massive wave of unforeseen demand for the COVID-19 Vaccine after the vaccine production that could lead to a bullwhip effect in the COVID-19 Vaccine Supply Chain (CVSC). The main objective of this study is to design a cognitive map based on the influential factors on the Bullwhip Effect Reduction (BER) of CVSC. Hence, in the first step, the affecting factors on the BER of CVSC are identified and ranked based on their importance from the pharmaceutical experts using the AHP technique. In the second step, 13 out of 18 identified factors are considered for further analyzing and understanding their relationship by Fuzzy Cognitive Mapping (FCM) technique. Furthermore, three different forward scenarios and three backward scenarios are carefully constructed to find the optimal solution for BER on pharmaceutical organizations. The obtained results show that the flexibility factor is the starting point of the backward scenario, which reduces the bullwhip effect in CVSC. Beside, by improving the inventory management and reliability factor, it would be effectively possible to control the lead-time factor and consequently, overcome the bullwhip effect in CVSC.

An integrated approach to model the blockchain implementation barriers in humanitarian supply chain

Purpose

Block chain technology (BCT) has emerged as a promising solution for the co-ordination and aid mechanism issues in the context of humanitarian supply chain (HSC). However, implementation of BCT in HSC discerns several barriers. Therefore, the purpose of this study is to identify and model the block chain implementation barriers in the context of HSC.

Design/methodology/approach

In the present study, 14 potential barriers to BCT adoption in HSC have been identified through literature survey. The survey comprises white papers, pilot studies, conference proceedings and journal articles. Further, the identified barriers were finalised in consultation with a team of experts. The team comprised experienced stakeholders working in the humanitarian domain and BCT development. The barriers were categorised into four (technological, organisational, exogenous and economic) perspectives adopting the kappa statistics. Further, the barriers were prioritised using fuzzy best worst method (FBWM) approach. Later, sensitivity analysis was performed to check the robustness and viability of the model.

Findings

The findings from the study indicate that the barriers, such as “data privacy, ownership, and security issues” (B1), “funding issues and cost complexity” (B3) and “technological complexities” (B8), are relatively more influential. The HSC stakeholders and BCT developers are required to identify the safety mechanism against the misuse of victim’s data. The funding issues and technological complexities are interrelated and need synergetic cooperation between blockchain developers, donors, humanitarian organisations (HOs) and other HSC stakeholders. Further, “lack of awareness and understanding among stakeholders” (B6) and “interoperability, collaboration and cross-pollination among HOs” (B5) were identified as least influential barriers to BCT adoption in HSC.

Research limitations/implications

In literature, limited study has been observed on determining barriers to BCT implementation. A more systematic method and statistical confirmation is necessary to establish further new confronting barriers. This study is limited to Indian context.

Originality/value

To the best of the authors’ knowledge, this study is first of its kind to use an FBWM approach for prioritising the barriers to BCT adoption in the context of HSC. The study provides potential barriers to BCT and categorises them into four different perspectives, along with their degree of influence.

Determining manufacturing system changes based on new product specifications

Purpose

The purpose of this paper is to investigate how necessary changes in a manufacturing system can be determined based on a new product specification. It proposes a formal modelling approach, enhancing the utilization of changeability of a manufacturing system given a set of changes in a product.

Design/methodology/approach

To develop the proposed modelling approach, a design science research method is used to iteratively frame an issue, develop a solution and evaluate it in a relevant environment. Evaluation is carried out through a case study.

Findings

A stepwise method is introduced, facilitating the creation of a model describing the relations between product characteristics within a product family and the changeability of a manufacturing system. Limitations of each manufacturing system module are evaluated to determine permittable changes in the product domain. This establishes clear relations between product attributes and manufacturing capabilities. Through this, users receive feedback on which parts of the manufacturing system must change, depending on changes in product attributes.

Research limitations/implications

Testing has been carried out in an academic learning factory setting. Products and processes are thus less complicated than an industrial setting. The system used for validation is highly modular by design.

Practical implications

The proposed approach could be used during product development, when determining characteristics and variety of new products, evaluating the consequences of changing the solution space. This implies a shorter time-to-market and lower product costs.

Social implications

Faster product development and shorter time-to-market would give manufacturers increased agility to track market needs, and ultimately lead to greater fulfilment of customer requirements.

Originality/value

The current body of literature focus on modelling either products or manufacturing systems. Little literature addresses both, but does not touch on identifying changes within parts of the manufacturing system, nor supports the high changeability proposed in this research.

Strategies to Manage the Impacts of the COVID-19 Pandemic in the Supply Chain: Implications for Improving Economic and Social Sustainability

This paper aims to identify the negative impacts of the COVID-19 outbreak on supply chains and propose strategies to deal with the impacts in the context of the readymade garment (RMG) industry supply chain of an emerging economy: Bangladesh. To achieve the aims, a methodological framework is proposed through a literature review, expert inputs, and a decision-aid tool, namely the grey-based digraph-matrix method. A total of 10 types of negative impacts and 22 strategic measures to tackle the impacts were identified based on the literature review and expert inputs. Then, the grey-based digraph-matrix was applied for modeling the strategic measures based on their influence to deal with the impacts. Findings reveal that the strategies “manufacturing flexibility”, “diversify the source of supply”, and “develop backup suppliers” have significant positive consequences for managing the impacts of the COVID-19 pandemic in the RMG supply chain. The findings help industrial managers recover from supply chain disruptions by identifying and classifying the impacts and strategies required to manage the major supply chain disturbances caused by the COVID-19 pandemic. As a theoretical contribution, this study is one of few initial attempts to evaluate the impacts of the COVID-19 outbreak and the strategies to deal with the impacts in the supply chain context.

Study of ethical issues of green procurement in Indian automobile industry using integrated ISM-fuzzy MICMAC – AHP –VIKOR

Purpose

The purpose of this study is the identification and analysis of key ethical issues of green procurement (GP) and the potential solutions to mitigate the issues in the Indian automobile sector.

Design/methodology/approach

Based on the literature review and expert elicitation, 23 ethical issues of GP in the Indian automobile industry and 11 solutions to mitigate these issues were identified. This paper explores the ethical issues based on an integrated method consisting of interpretative structural modelling fuzzy Matrice d'Impacts Croisés-Multiplication Appliquée á un Classement, analytical hierarchy process and the solutions to mitigate these issues using fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje.

Findings

The findings suggest that ethical issues such as favouritism towards suppliers and failure to fulfil business objectives by top management are identified as the most significant variables with the highest importance weights, while top management commitment for ethical behaviour is identified as the most potent solution for mitigating the issues.

Research limitations/implications

This study is limited to the literature review and experts’ opinions.

Practical implications

The results may help practitioners and researchers to focus on major ethical issues of GP to strategize proactive solutions that may help to mitigate or eliminate the ethical issues.

Originality/value

This paper is an original contribution of the analysis of GP and provides an interesting insight into the Indian automotive industry.

Developing a framework for evaluating sustainability index for logistics service providers: graph theory matrix approach

Purpose

The purpose of this study is to identify sustainability practices and to propose a framework for evaluating the sustainability index of logistics service providers (LSPs).

Design/methodology/approach

Sustainable practices followed by LSPs are identified through literature review and analysis of a case study. Thirteen such sustainable practices are identified. Thereafter, with expert inputs, nine sustainable practices are shortlisted and considered for the evaluation of the sustainability index in the proposed framework. Graph Theory Matrix Approach has been applied to evaluate the sustainability index of an LSP.

Findings

Major practices identified for evaluating sustainability index include the use of recyclable packaging, use of renewable energy sources, green procurement, reduction in carbon emissions, use of CNG/electric vehicles, rainwater harvesting and so on. The sustainability index of an LSP is evaluated by using the proposed framework.

Practical implications

LSPs can benchmark their sustainability index with respect to the best in the industry. Based on it, LSPs can also identify potential areas for improvement.

Originality/value

Novelty of the study lies in the proposed framework for evaluation of sustainability index which can be used to develop strategies for green logistics. LSPs can also improve their performance in terms of sustainability measures by adopting green logistics.