Barriers to big data analytics in manufacturing supply chains: A case study from Bangladesh

© 2018 Elsevier Ltd Recently, big data (BD) has attracted researchers and practitioners due to its potential usefulness in decision-making processes. Big data analytics (BDA) is becoming increasingly popular among manufacturing companies as it helps gain insights and make decisions based on BD. However, there many barriers to the adoption of BDA in manufacturing supply chains. It is therefore necessary for manufacturing companies to identify and examine the nature of each barrier. Previous studies have mostly built conceptual frameworks for BDA in a given situation and have ignored examining the nature of the barriers to BDA. Due to the significance of both BD and BDA, this research aims to identify and examine the critical barriers to the adoption of BDA in manufacturing supply chains in the context of Bangladesh. This research explores the existing body of knowledge by examining these barriers using a Delphi-based analytic hierarchy process (AHP). Data were obtained from five Bangladeshi manufacturing companies. The findings of this research are as follows: (i) data-related barriers are most important, (ii) technology-related barriers are second, and (iii) the five most important components of these barriers are (a) lack of infrastructure, (b) complexity of data integration, (c) data privacy, (d) lack of availability of BDA tools and (e) high cost of investment. The findings can assist industrial managers to understand the actual nature of the barriers and potential benefits of using BDA and to make policy regarding BDA adoption in manufacturing supply chains. A sensitivity analysis was carried out to justify the robustness of the barrier rankings

Modeling the interrelationships among barriers to sustainable supply chain management in leather industry

© 2018 Elsevier Ltd The leather industry of Bangladesh is facing considerable amounts of pressure to adopt sustainable supply chain management (SSCM). While there are some studies that have examined barriers to SSCM practices in developed and developing countries in various domains, these are not necessarily applicable to the Bangladeshi leather industry. To bridge this gap, it is crucial to identify most influential barriers to SSCM practices, particularly in the context of developing economies. Therefore, this study identifies such barriers and examines the causal relationships between them with an aim to facilitate the effective implementation of SSCM in the Bangladeshi leather processing industry. Thirty-five barriers to SSCM implementation were identified through a detailed literature review and a survey of leather processing industry experts. Among them, the most common 20 barriers were selected with the help of industry experts. Then, a blended, grey-based Decision Making Trial and Evaluation Laboratory (DEMATEL) approach was utilized to examine their interrelationships. The results demonstrate that nine barriers could be classified as “causal” and eleven as “influenced”. ‘Lack of awareness of local customers in green products’ and ‘lack of commitment from top management’ took high priority in the causal group. ‘Lack of reverse logistics practices’ and ‘Outdated machineries’ were the most influenced barriers. This research uses a leather processing company as a case study for demonstrating the proposed model. The findings aim to support the leather processing industry in a structural way, so that industrial managers can identify the most influential barriers and work to eliminate them. This study may be useful to stakeholders to achieve sustainable development

Drivers to sustainable manufacturing practices and circular economy: A perspective of leather industries in Bangladesh

© 2017 Elsevier Ltd Sustainable manufacturing practices and the circular economy have recently received significant attention in academia and within industries to improve supply chain practices. Manufacturing industries have started adopting sustainable manufacturing practices and a circular economy in their supply chain to mitigate environmental concerns, as sustainable manufacturing practices and a circular economy result in the reduction of waste generation and energy and material usage. The leather industry, in spite of it contributing remarkably to a country's economic growth and stability, does not bear a good image because of its role in polluting the environment. Therefore, the leather industries of Bangladesh are trying to implement sustainable manufacturing practices as a part of undertaking green supply chain initiatives to remedy their image with the buyer and to comply with government rules and regulations. The main contribution of this study is to assess, prioritize and rank the drivers of sustainable manufacturing practices in the leather industries of Bangladesh. We have used graph theory and a matrix approach to examine the drivers. The results show that knowledge of the circular economy is paramount to implementing sustainable manufacturing practices in the leather industry of Bangladesh. This study will assist managers of leather companies to formulate strategies for the optimum utilization of available resources, as well as for the reduction of waste in the context of the circular economy

A case study on strategies to deal with the impacts of COVID-19 pandemic in the food and beverage industry

This research investigates the impacts of the novel coronavirus disease, also referred to as COVID-19 pandemic, on the food and beverage industry. It examines both short-term and medium-to-long-term impacts of the pandemic and outlines strategies to reduce the potential consequences of those impacts. To this end, we use a qualitative, multiple-case-study methodology, collecting data from eight sample companies with fourteen respondents in the food and beverage industry in Bangladesh. The findings show that the short-term impacts of this pandemic, such as product expiry, shortage of working capital, and limited operations of distributors, are severe, while the medium-to-long-term impacts promise to be complex and uncertain. In the longer term, various performance metrics, such as return on investment by the firms, the contribution of the firms to the gross domestic product (GDP), and employee size, are all expected to decrease. Moreover, firms may need to restructure their supply chain and build relationships with new distributors and trade partners. The study proposes several strategies that managers in this sector can adopt to improve resiliency in the changing environment during and after the COVID-19 era. While this research is novel and contributes to both theory and practice, it does not consider small and medium-sized companies in the food and beverage industry. Therefore, the impacts and strategies we identify may not apply to smaller companies

Modeling drivers to big data analytics in supply chains

The recent emergence of data-driven business markets and the ineligibility of traditional data management systems to trace them have fostered the application of Big Data Analytics (BDA) in supply chains of the present decade. Literature reviews reveal that the successful implication of BDA in a supply chain mainly depends on some key drivers considering the size and operations of an organization. However, collective analysis of all these drivers is still neglected in the existing research field. Therefore, the purpose of this research is to identify and prioritize the most significant drivers of BDA in the supply chains. To this aim, a novel Best-worst method (BWM) based framework has been proposed, which has successfully identified and sequenced the twelve most significant drivers with the help of previous literature and experts’ opinions. Theoretically, this study contributes to the BDA literature by offering some unique drivers to BDA in supply chains. The findings show that ‘sophisticated structure of information technology’ and ‘group collaboration among business partners’ are the top most significant drivers. ‘Digitization of society’ is identified as the least significant driver of BDA in this study. The outcome of this study is expected to assist the industry managers to find out the most and least preferable drivers in their supply chains and then take initiatives to improve the overall efficiency of their organizations accordingly

Key performance indicators for a sustainable recovery strategy in health-care supply chains: COVID-19 pandemic perspective

Purpose: Supply chains’ (SCs’) sustainability practices and recovery strategies are attaining popularity in academia and industries to improve the resilience of the SCs and to manage large-scale disruptions. The global pandemic caused by the COVID-19 has raised the question of the sustainability of essential health-care products’ SCs of Bangladesh. It is an essential avenue for making the life of people safe and secure. Despite its importance, most of the health-care SCs in Bangladesh are struggling to meet the demand of its nation due to capacity shortage, technological backwardness of the manufacturers, delivery capacity shortages and less advanced forecasting capabilities. Therefore, this study aims to investigate the key performance indicators (KPIs) of a sustainable recovery strategy in the context of health-care SCs considering the COVID-19 pandemic. Design/methodology/approach: This study used a dynamic method named graph theory and matrix approach to evaluate the most critical KPIs of a sustainable recovery strategy in the context of Bangladeshi health-care SCs. Findings: The result revealed that dynamic forecasting and planning with a smooth delivery and distribution support system, production capacity diversification and having alternative or multiple suppliers during extraordinary disruptions may aid in the sustainability of the health-care SCs in Bangladesh. Originality/value: This study is unique as no previous study has identified and examined the sustainable recovery strategy perspective KPIs considering the COVID-19 pandemic in the context of Bangladeshi health-care SCs. This study will also add value by guiding decision-makers of the health-care SCs of Bangladesh to adopt strategies toward the sustainability of SCs

An innovative decision-making framework for evaluating transportation service providers based on sustainable criteria

© 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group. Evaluating transportation service providers is an applied and multi-criteria decision-making problem. To ensure supply chain sustainability, it is important to consider all sustainable criteria for assessing and evaluating transport service providers. This paper aims to develop a new decision-making framework to evaluate transport service providers considering sustainable criteria from economic, environmental, social and operational aspects. The decision-making framework integrates both qualitative expert opinion and quantitative best-worst method (BWM) and VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) method. The developed framework contributes to the academic literature by expanding the knowledge in supply chain sustainability by considering all possible sustainable criteria and integrating both qualitative and quantitative methods for evaluating transport service providers. This study also contributes to practice by developing a decision support tool, by which decision-makers can make an accurate, systematic and prompt decision to identify and assess sustainable criteria and to evaluate the priority of different transport service providers

Supply Chain Recovery Challenges in the Wake of COVID-19 Pandemic

The COVID-19 pandemic has revealed the fragility of global supply chains arising from raw material scarcity, production and transportation disruption, and social distancing. Firms need to carefully anticipate the difficulties during recovery and formulate appropriate strategies to ensure the survival of their businesses and supply chains. To enhance awareness of the issues, this research aims to identify and model recovery challenges in the context of the Bangladeshi ready-made garment industry. A Delphi-based grey decision-making trial and evaluation laboratory (DEMATEL) methodology was used to analyze the data. While the Delphi method helped identify the major supply chain recovery challenges from the impacts of the COVID-19 pandemic, the grey DEMATEL approach helped categorize the causal relationships among these challenges. Of the 23 recovery challenges finalized, 12 are causal challenges. The study's findings can assist decision-makers in developing strategic policies to overcome the recovery challenges in the post-COVID-19 era

Analyzing barriers and strategies for implementing Lean Six Sigma in the context of Indian SMEs

PurposeThe purpose of this study is to investigate the barriers for implementing Lean Six Sigma (LSS) in small and medium-sized enterprises (SMEs) and present a framework that provides prioritized strategies to overcome the barriers.Design/methodology/approachThe barriers and strategies are identified via a comprehensive literature review and validated by industry experts. The study uses the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (fuzzy TOPSIS) to analyze the barriers and strategies for determining the prioritized list of strategies.FindingsThe findings reveal that there are sixteen barriers to LSS implementation in Indian SMEs. To overcome these barriers, this study reveals twelve strategies. The analysis shows that “effective management” is the most crucial strategy to overcome the barriers for implementing LSS in Indian SMEs.Research limitations/implicationsThis research guides SMEs practitioners to efficiently and effectively implement LSS, which, in turn, can enhance the performance of SMEs.Originality/valueThis study contributes to the literature by integrating the strategies with the barriers for implementing LSS in Indian SMEs. Besides, this study provides the prioritized list of strategies to overcome the barriers for implementing LSS in Indian SMEs.</jats:sec