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

Exploring Internet of Things Adoption Challenges in Manufacturing Firms: A Fuzzy Analytical Hierarchy Process Approach

Innovation is crucial for sustainable success in today's fiercely competitive global manufacturing landscape. Bangladesh's manufacturing sector must embrace transformative technologies like the Internet of Things (IoT) to thrive in this environment. This article addresses the vital task of identifying and evaluating barriers to IoT adoption in Bangladesh's manufacturing industry. Through synthesizing expert insights and carefully reviewing contemporary literature, we explore the intricate landscape of IoT adoption challenges. Our methodology combines the Delphi and Fuzzy Analytical Hierarchy Process, systematically analyzing and prioritizing these challenges. This approach harnesses expert knowledge and uses fuzzy logic to handle uncertainties. Our findings highlight key obstacles, with "Lack of top management commitment to new technology" (B10), "High initial implementation costs" (B9), and "Risks in adopting a new business model" (B7) standing out as significant challenges that demand immediate attention. These insights extend beyond academia, offering practical guidance to industry leaders. With the knowledge gained from this study, managers can develop tailored strategies, set informed priorities, and embark on a transformative journey toward leveraging IoT's potential in Bangladesh's industrial sector. This article provides a comprehensive understanding of IoT adoption challenges and equips industry leaders to navigate them effectively. This strategic navigation, in turn, enhances the competitiveness and sustainability of Bangladesh's manufacturing sector in the IoT era

Fuzzy Analytic Hierarchy Process Utilization in Government Projects : A Systematic Review of Implementation Processes

Uncertain assessments challenge the aggregation of expert knowledge in the field of decision-making. Valuable, yet sometimes hesitant, insight of expert decision makers needs to be converted into numerically comparative form in the age of information management. . Fuzzy Analytic Hierarchy Process (FAHP) enables the comparison of decision elements through expert judgements, even when the information at hand is uncertain. The present study explores Fuzzy Analytic Hierarchy Process (FAHP) implementation in government projects in a systematic literature review. Theoretical framework for Analytic Hierarchy Process (AHP), Fuzzy Set Theory (FST) and their combination, namely Fuzzy Analytic Hierarchy Process (FAHP) is provided. The systematic literature review categorizes research results under three categories and examines each paper by utilizing review questions. Three main application purposes rise from the literature review; policy planning and assessment, project selection and project and performance evaluation. Overall implementation processes of the three application areas are discussed. The conclusion provides comprehensive evaluation of the approach and considerations for practitioners.Asiantuntijanäkemysten epävarmuus vaikeuttaa tiedon keräämistä päätöksenteossa. Päätöksentekoprosessin kannalta arvokkaat, vaikkakin joskus epävarmat, asiantuntijanäkemykset tulee voida muuttaa numerollisesti vertailtavaan muotoon tietojohtamisen aikakautena. Sumea Analyyttinen Hierarkiaprosessi mahdollistaa päätöksenteossa käytettävien elementtien vertailun asiantuntija-arviointien avulla, jopa silloin kun käytettävissä oleva tieto on epävarmaa. Opinnäytetyössä tutkitaan systemaattisen kirjallisuuskatsauksen keinoin Sumean Analyyttisen Hierarkiaprosessin, eng. Fuzzy Analytic Hierarchy Process (FAHP), implementointia julkishallinnon hankkeissa. Tutkimus sisältää teoreettisen viitekehyksen Analyyttisen Hierarkiaprosessin, Sumean joukko-opin, eng. Fuzzy Set Theory (FST) ja niiden yhdistelmän, Sumean Analyyttisen Hierarkiaprosessin, eng. Fuzzy Analytic Hierarchy Process (FAHP), ymmärtämisen tueksi. Systemaattisen kirjallisuuskatsauksen myötä valittu aineisto luokitellaan kolmeen kategoriaan ja jokaista tutkimusta tarkastellaan ennalta määrättyjen kysymysten avulla. Systemaattisen kirjallisuuskatsaukseen myötä valittujen tutkimusten kolme olennaisinta käyttötarkoitusta ovat; käytännön suunnittelu ja arviointi, hankevalinta sekä hankkeiden ja suoritusten arviointi. Aineiston luokittelun jälkeen tutkimus etenee tarkastelemaan erilaisiin käyttötarkoituksiin suunnattujen Sumean Analyyttisen Hierarkiaprosessi -metodin implementointiprosesseja. Johtopäätös -osio tarjoaa pohdintaa ja huomioita siitä, miten päätöksentekijät voivat suhtautua Sumean Analyyttisen Hierarkiaprosessin hyödyntämiseen julkishankkeiden yhteydessä

A taxonomy of critical factors towards Sustainable Operations and Supply Chain Management 4.0 in developing countries– A systematic review and fuzzy group decision-making

Supply chain disruptions, intensified by black swan events such as the COVID-19 pandemic and the Russia-Ukraine war, have increased the interest in resilient supply chains, which can be achieved by adopting sustainable Industry 4.0 (I4.0) practices. However, the critical success factors (CSFs) for sustainable I4.0 in operations and supply chain management (S-OSCM4.0) are unclear, and there is a lack of a holistic and empirically validated taxonomy of CSFs from multiple stakeholders' perspectives to guide organizations in this transition. Moreover, developing countries face specific challenges that require prioritizing the proper set of CSFs for sustainable digitalization. Therefore, this paper aims to develop a CSFs-based taxonomy for S-OSCM4.0 to help organizations stay current in I4.0 adoption and integrate sustainability in OSCM. We first conducted a systematic literature review (SLR) of 131 papers using bibliometric and content analyses and synthesized the theoretical findings into an alpha taxonomy of CSFs following an inductive approach. Then, we employed a Delphi survey technique combining fuzzy logic to solicit experts' perceptions from a developing country to analyze and validate the taxonomy and determine the most pertinent CSFs, resulting in a beta taxonomy of CSFs for S-OSCM4.0. The developed taxonomy represents a pioneering managerial artefact that can guide sustainable development through an inclusive digital transformation with less environmental impact, contributing to decision-making in S-OSCM4.0, especially for operations in developing countries

Blockchain Technology for Enhancing Supply Chain Performance and Reducing the Threats Arising from the COVID-19 Pandemic

A rigorous examination of the most recent advancements in blockchain technology (BCT) and artificial intelligence (AI)-enabled supply chain networks is provided in this book. The edited book brings together the perspectives of a number of authors who have presented their most recent views on blockchain technology and its applications in a variety of disciplines. The submitted papers contribute to a better understanding of how blockchain technology can improve the efficacy of human activities during a pandemic, improve traceability and visibility in the automotive supply chain, support food safety and reliability through digitalisation of the food supply chain, and increase the performance of next-generation digital supply chains, among other things. The book attempts to address and prepare a way to address the complicated issues that supply chains are encountering as a result of the global pandemic

Circular economy and fuzzy set theory: a bibliometric and systematic review based on Industry 4.0 technologies perspective

The Circular Economy (CE) is receiving more attention, especially in Industry 4.0 (I4.0). In the face of several ambiguous and uncertain information, fuzzy techniques based on Fuzzy Set Theory (FST) are essential for developing CE strategies. This paper uses bibliometric methods to analyze the characteristics of the authors, nations/regions, institutions of the literature of FST and CE, and the collaborations relations between them, and then summarize the literature on fuzzy techniques in the CE and identify the specific role that FST can play in each stage of CE, its primary effects on the CE’s pre-preparation stage, design and production stage, and recycling and reuse stage. Meanwhile, the paper explores the advantages of I4.0 technologies for CE and analyzes the research on the role of fuzzy techniques based on FST for CE and I4.0 technologies. Last but not least, this paper is concluded by summarizing the knowledge gained from the bibliometric and content analyses of the literature and suggesting further research directions of investigation. This research will draw attention to FST’s contribution and encourage its advancement in CE and I4.0 technologies

Gestão de Recursos Finitos em Empresas

The present work has as goal aiding decision makers, researchers, enterprises and practitioners by developing a proper literature review as a base for comparison among multiple-criteria decision making methods in finite resources management according to each of the most important areas of a business environment. Efficient resource management decision making in companies impacts its value creation capability and, therefore, its competitiveness and ultimate success. The methodology for paper research follows the PRISMA flow diagram, for correct paper filtrations according to the set of criteria stablished in alignment with the thesis goal. The papers included in the study are any that employ multiple-criteria decision making methods in their pure forms, in combination with each other forming hybrids, or in combination with other mathematical techniques for solving decision making problems across five major areas of a company’s body. The five major areas are: (1) Supply Chain Management and Logistics; (2) Environmental Management; (3) Business and Marketing Management; (4) Design, Engineering and Manufacturing Systems; and (5) Human Resources Management. The 204 final papers are presented separated by their corresponding application areas, ordered by number of citations, which is used as a measure of their scientific community relevance. They are also classified by, author, nationality, journal, year, type of research and methods used. All collected data is used for quantitative statistical analysis, with which is possible to collect more in-depth information on the literature research. Focused comments on the main methods are also present in this work, with observations made on the many applications and variations each of them had throughout the articles in the research. The AHP and TOPSIS approaches, either with their fuzzy set variations are by far the most popular methods in the referred applications. However, besides them other 51 MCDM or other mathematical techniques are employed in many different combinations and approaches, bringing a very interesting diversity to the study that is very useful for it to be used as a base for comparison among methods. A total number of 111 journals and authors and co-authors of 41 nationalities are involved in the publications between 2012 and 2018, with more than half of papers coming from either India, Turkey or Iran. Many other results are obtained, bringing the readers different perspectives on the subject. This paper contributes to the body of knowledge with a great and insightful overview on MCDM methods application in aiding in challenges part of a business environment, so that companies can better manage their resources and be more prosperous. It is a vast database that allows many comparisons and evaluations, offering more analysis than the standard literature review articles.O presente trabalho tem como objetivo auxiliar os tomadores de decisão, pesquisadores e profissionais, ao desenvolver uma revisão bibliográfica adequada como base para comparação entre os métodos de decisão multicritério na gestão de recursos finitos de acordo com cada uma das áreas mais importantes de um ambiente de negócios. A tomada eficiente de decisões de gestão de recursos nas empresas afeta sua capacidade de criação de valor e, portanto, sua competitividade e sucesso finais. A metodologia da investigação baseou-se na metodologia PRISMA, para a correta filtração das publicações de acordo com o conjunto de critérios estabelecidos, em alinhamento com o objetivo da tese. Os artigos incluídos no estudo são aqueles que apresentam métodos de decisão com critérios múltiplos em suas formas puras, em combinação uns com os outros ao formar híbridos, ou com outras técnicas matemáticas para resolver problemas em cinco áreas principais das empresas. As cinco áreas são: (1) Gestão da Cadeia de Suprimentos e Logística; (2) Gestão Ambiental; (3) Gestão de Negócios e Marketing; (4) Sistemas de Projeto, Engenharia e Manufatura; e (5) Gestão de Recursos Humanos. Os 204 artigos finais são apresentados de acordo com as áreas de aplicação correspondentes, ordenadas por número de citações, que são usadas como uma medida de sua relevância na comunidade científica. Eles são, ainda, classificados por autor, nacionalidade, revista, ano, tipo de pesquisa e métodos utilizados. Todos os dados coletados são utilizados para análise estatística quantitativa, com a qual é possível recolher informações mais aprofundadas sobre a pesquisa bibliográfica. São realizados comentários sobre os principais métodos e as maneiras que foram apresentados ao longo do estudo de todos os artigos durante a pesquisa. As abordagens AHP e TOPSIS, com suas variações em conjuntos difusos ou fuzzy, são de longe os métodos mais populares nas aplicações referidas. No entanto, além destes, outros 51 MCDM e outras técnicas são utilizadas em muitas combinações e abordagens, trazendo uma diversidade muito interessante para o estudo, servindo de base para comparação dos métodos. Um total de 111 revistas e autores e coautores de 41 nacionalidades estão envolvidos nas publicações entre 2012 e 2018, com mais de metade dos artigos provenientes da Índia, Turquia ou Irão. Estes e outros resultados levam aos leitores diferentes perspectivas sobre o assunto. Este documento contribui para o estado da arte, com um conhecimento geral excelente e perspicaz sobre a aplicação de métodos MCDM para ajudar nos desafios de um ambiente de negócios, para que as empresas possam melhor gerenciar seus recursos e serem mais prósperas. É um vasto banco de dados que permite muitas comparações e avaliações, oferecendo mais análises do que os artigos de revisão de literatura padrão

Analysis of Decision Support Systems of Industrial Relevance: Application Potential of Fuzzy and Grey Set Theories

The present work articulates few case empirical studies on decision making in industrial context. Development of variety of Decision Support System (DSS) under uncertainty and vague information is attempted herein. The study emphases on five important decision making domains where effective decision making may surely enhance overall performance of the organization. The focused territories of this work are i) robot selection, ii) g-resilient supplier selection, iii) third party logistics (3PL) service provider selection, iv) assessment of supply chain’s g-resilient index and v) risk assessment in e-commerce exercises. Firstly, decision support systems in relation to robot selection are conceptualized through adaptation to fuzzy set theory in integration with TODIM and PROMETHEE approach, Grey set theory is also found useful in this regard; and is combined with TODIM approach to identify the best robot alternative. In this work, an attempt is also made to tackle subjective (qualitative) and objective (quantitative) evaluation information simultaneously, towards effective decision making. Supplier selection is a key strategic concern for the large-scale organizations. In view of this, a novel decision support framework is proposed to address g-resilient (green and resilient) supplier selection issues. Green capability of suppliers’ ensures the pollution free operation; while, resiliency deals with unexpected system disruptions. A comparative analysis of the results is also carried out by applying well-known decision making approaches like Fuzzy- TOPSIS and Fuzzy-VIKOR. In relation to 3PL service provider selection, this dissertation proposes a novel ‘Dominance- Based’ model in combination with grey set theory to deal with 3PL provider selection, considering linguistic preferences of the Decision-Makers (DMs). An empirical case study is articulated to demonstrate application potential of the proposed model. The results, obtained thereof, have been compared to that of grey-TOPSIS approach. Another part of this dissertation is to provide an integrated framework in order to assess gresilient (ecosilient) performance of the supply chain of a case automotive company. The overall g-resilient supply chain performance is determined by computing a unique ecosilient (g-resilient) index. The concepts of Fuzzy Performance Importance Index (FPII) along with Degree of Similarity (DOS) (obtained from fuzzy set theory) are applied to rank different gresilient criteria in accordance to their current status of performance. The study is further extended to analyze, and thereby, to mitigate various risk factors (risk sources) involved in e-commerce exercises. A total forty eight major e-commerce risks are recognized and evaluated in a decision making perspective by utilizing the knowledge acquired from the fuzzy set theory. Risk is evaluated as a product of two risk quantifying parameters viz. (i) Likelihood of occurrence and, (ii) Impact. Aforesaid two risk quantifying parameters are assessed in a subjective manner (linguistic human judgment), rather than exploring probabilistic approach of risk analysis. The ‘crisp risk extent’ corresponding to various risk factors are figured out through the proposed fuzzy risk analysis approach. The risk factor possessing high ‘crisp risk extent’ score is said be more critical for the current problem context (toward e-commerce success). Risks are now categorized into different levels of severity (adverse consequences) (i.e. negligible, minor, marginal, critical and catastrophic). Amongst forty eight risk sources, top five risk sources which are supposed to adversely affect the company’s e-commerce performance are recognized through such categorization. The overall risk extent is determined by aggregating individual risks (under ‘critical’ level of severity) using Fuzzy Inference System (FIS). Interpretive Structural Modeling (ISM) is then used to obtain structural relationship amongst aforementioned five risk sources. An appropriate action requirement plan is also suggested, to control and minimize risks associated with e-commerce exercises

INTERVAL TYPE-2 FUZZY MODEL FOR CUSTOMER COMPLAINT HANDLING

Complaint management system (CMS) has become increasingly important for organizations, businesses, and government in Malaysia. The interaction between customers and business provider based on complaints which referring to perceptions and wording involves uncertainties and not an easy task in complaint handling process to rank the complaint