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Article
Publication date: 16 January 2023

Mahesh H. Prabhu and Amit Kumar Srivastava

The competitive rivalry, rapid change and high business volatility necessitate inter-organizational collaboration, including the supply chain (SC). This paper develops an…

Abstract

Purpose

The competitive rivalry, rapid change and high business volatility necessitate inter-organizational collaboration, including the supply chain (SC). This paper develops an interpretive model of the effect of the chief executive officers’ (CEO's) transformational leadership (TL) style on SC collaboration and, consequently, on the firm's performance.

Design/methodology/approach

Total interpretive structural modeling (TISM) is adopted to develop a hierarchical model to delineate the association between the elements of TL, SC collaboration and firm performance. Furthermore, the model has been validated statistically.

Findings

The TISM analysis results suggest that the TL style elements require maximum attention and are strategic. These elements drive factors of SC collaboration leading to improved firm performance. Therefore, CEO leadership is critical for SC collaboration to effectively affect firm performance.

Research limitations/implications

The TISM framework in this paper preferred the majority approach over the fuzzy one, which requires a much larger data set. However, the bias of the majority approach can be eliminated by having multiple consultations with participants. Further, the development and validation of the paper was limited to manufacturing small and medium enterprises (SMEs) in India. The model can also be tested in large organizations to garner additional insights.

Originality/value

This study uniquely integrates TL and SC collaboration elements to explain firm performance. The TISM framework explains not only the “what” and “how” but also the “why” of theory building. This study also adds methodological value by combining triangulation with the interpretive tool.

Details

International Journal of Emerging Markets, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-8809

Keywords

Open Access
Article
Publication date: 5 October 2022

Stratos Moschidis, Angelos Markos and Athanasios C. Thanopoulos

The purpose of this paper is to create an automatic interpretation of the results of the method of multiple correspondence analysis (MCA) for categorical variables, so that the…

2686

Abstract

Purpose

The purpose of this paper is to create an automatic interpretation of the results of the method of multiple correspondence analysis (MCA) for categorical variables, so that the nonexpert user can immediately and safely interpret the results, which concern, as the authors know, the categories of variables that strongly interact and determine the trends of the subject under investigation.

Design/methodology/approach

This study is a novel theoretical approach to interpreting the results of the MCA method. The classical interpretation of MCA results is based on three indicators: the projection (F) of the category points of the variables in factorial axes, the point contribution to axis creation (CTR) and the correlation (COR) of a point with an axis. The synthetic use of the aforementioned indicators is arduous, particularly for nonexpert users, and frequently results in misinterpretations. The current study has achieved a synthesis of the aforementioned indicators, so that the interpretation of the results is based on a new indicator, as correspondingly on an index, the well-known method principal component analysis (PCA) for continuous variables is based.

Findings

Two (2) concepts were proposed in the new theoretical approach. The interpretative axis corresponding to the classical factorial axis and the interpretative plane corresponding to the factorial plane that as it will be seen offer clear and safe interpretative results in MCA.

Research limitations/implications

It is obvious that in the development of the proposed automatic interpretation of the MCA results, the authors do not have in the interpretative axes the actual projections of the points as is the case in the original factorial axes, but this is not of interest to the simple user who is only interested in being able to distinguish the categories of variables that determine the interpretation of the most pronounced trends of the phenomenon being examined.

Practical implications

The results of this research can have positive implications for the dissemination of MCA as a method and its use as an integrated exploratory data analysis approach.

Originality/value

Interpreting the MCA results presents difficulties for the nonexpert user and sometimes lead to misinterpretations. The interpretative difficulty persists in the MCA's other interpretative proposals. The proposed method of interpreting the MCA results clearly and accurately allows for the interpretation of its results and thus contributes to the dissemination of the MCA as an integrated method of categorical data analysis and exploration.

Details

Applied Computing and Informatics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2634-1964

Keywords

Article
Publication date: 1 September 2022

Rinu Sathyan, Parthiban Palanisamy, Suresh G. and Navin M.

The automotive industry appears to overcome much of its obstacles, despite the constant struggle facing COVID-19. The pandemic has resulted in significant improvements in the…

Abstract

Purpose

The automotive industry appears to overcome much of its obstacles, despite the constant struggle facing COVID-19. The pandemic has resulted in significant improvements in the habits and conduct of consumers. There is an increased preference for personal mobility. In this dynamic environment with unexpected changes and high market rivalry, automotive supply chains focus more on executing responsive strategies with minimum costs. This paper aims to identify and model the drivers to the responsiveness of automotive supply chain.

Design/methodology/approach

Seventeen drivers for supply chain responsiveness have been identified from the extensive literature, expert interview. An integrated methodology of fuzzy decision-making trial and evaluation laboratory–interpretive structural modelling (DEMATEL–ISM) is developed to establish the interrelationship between the drivers. The cause–effect relationship between the drivers was obtained through fuzzy DEMATEL technique, and a hierarchical structure of the drivers was developed using the ISM technique.

Findings

The result of the integrated methodology revealed that strategic decision-making of management, accurate forecasting of demand, advanced manufacturing system in the organisation and data integration tools are the critical drivers.

Research limitations/implications

This study has conceptual and analytical limitations. In this study, a limited number of drivers are examined for supply chain responsiveness. Further research may examine the role of other key performance indicators in the broad field of responsiveness in the automotive supply chain or other industry sectors. Future study can uncover the interrelationships and relative relevance of indicators using advanced multi-criteria decision-making methodologies.

Originality/value

The authors proposed an integrated methodology that will be benefitted to the supply chain practitioners and automotive manufacturers to develop management strategies to improve responsiveness. This study further helps to compare the responsiveness of the supply chain between various automotive manufacturers.

Details

Journal of Global Operations and Strategic Sourcing, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2398-5364

Keywords

Article
Publication date: 12 December 2023

Mustafizur Rahman, Sifat Ajmeer Haque and Andrea Trianni

This study aims to recognize the significant barriers of small and medium-sized enterprises (SMEs) in Bangladesh, hindering the adoption of total quality management (TQM)…

Abstract

Purpose

This study aims to recognize the significant barriers of small and medium-sized enterprises (SMEs) in Bangladesh, hindering the adoption of total quality management (TQM). Additionally, this research intends to explore the interrelations among these barriers to develop essential managerial insights for promoting TQM implementation in SMEs.

Design/methodology/approach

The interpretive structural modeling (ISM) approach and Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) a cross-impact matrix multiplication applied to classification show the relationship among the barriers and classification of the barriers to TQM implementation respectively, and partial least squares structural equation modeling (PLS-SEM) is applied for ISM model validation.

Findings

This study examined previous literature and conducted interviews with professionals to identify 17 barriers. The study then develops and investigates a model that outlines the relationships and priorities among these barriers and categorizes them based on their impact and interdependence. This analysis can assist SMEs in implementing TQM during their operations successfully.

Practical implications

This research emphasizes the crucial obstacles that greatly affect other barriers and require immediate attention. Furthermore, this study provides valuable information for SMEs to effectively prioritize their resources and efforts to overcome these obstacles.

Originality/value

This study delves into the primary obstacles impeding the integration of TQM in SMEs through a novel approach. Additionally, this study constructs a verified contextual framework that depicts the hierarchies and interconnections among these barriers.

Details

The TQM Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1754-2731

Keywords

Article
Publication date: 26 December 2023

Eyyub Can Odacioglu, Lihong Zhang, Richard Allmendinger and Azar Shahgholian

There is a growing need for methodological plurality in advancing operations management (OM), especially with the emergence of machine learning (ML) techniques for analysing…

259

Abstract

Purpose

There is a growing need for methodological plurality in advancing operations management (OM), especially with the emergence of machine learning (ML) techniques for analysing extensive textual data. To bridge this knowledge gap, this paper introduces a new methodology that combines ML techniques with traditional qualitative approaches, aiming to reconstruct knowledge from existing publications.

Design/methodology/approach

In this pragmatist-rooted abductive method where human-machine interactions analyse big data, the authors employ topic modelling (TM), an ML technique, to enable constructivist grounded theory (CGT). A four-step coding process (Raw coding, expert coding, focused coding and theory building) is deployed to strive for procedural and interpretive rigour. To demonstrate the approach, the authors collected data from an open-source professional project management (PM) website and illustrated their research design and data analysis leading to theory development.

Findings

The results show that TM significantly improves the ability of researchers to systematically investigate and interpret codes generated from large textual data, thus contributing to theory building.

Originality/value

This paper presents a novel approach that integrates an ML-based technique with human hermeneutic methods for empirical studies in OM. Using grounded theory, this method reconstructs latent knowledge from massive textual data and uncovers management phenomena hidden from published data, offering a new way for academics to develop potential theories for business and management studies.

Details

International Journal of Operations & Production Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0144-3577

Keywords

Article
Publication date: 16 January 2023

Taslima Nasreen, Ron Baker and Davar Rezania

This review aims to summarize the extent to which sustainability dimensions are covered in the selected qualitative literature, the theoretical and ontological underpinnings that…

Abstract

Purpose

This review aims to summarize the extent to which sustainability dimensions are covered in the selected qualitative literature, the theoretical and ontological underpinnings that have informed sustainability research and the qualitative methodologies used in that literature.

Design/methodology/approach

This study uses a systematic review to examine prior empirical studies in sustainability reporting between 2000 and 2021.

Findings

This review contributes to sustainability research by identifying unexplored and underexplored areas for future studies, such as Indigenous people’s rights, employee health and safety practice, product responsibility, gender and leadership diversity. Institutional and stakeholder theories are widely used in the selected literature, whereas moral legitimacy remains underexplored. The authors suggest that ethnographic and historical research will increase the richness of academic research findings on sustainability reporting.

Research limitations/implications

This review is limited to qualitative studies only because its richness allows researchers to apply various methodological and theoretical approaches to understand engagement in sustainability reporting practice.

Originality/value

This review follows a novel approach of bringing the selected studies’ scopes, theories and methodologies together. This approach permits researchers to formulate a research question coherently using a logical framework for a research problem.

Details

Journal of Financial Reporting and Accounting, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1985-2517

Keywords

Article
Publication date: 23 January 2024

Ranjit Roy Ghatak and Jose Arturo Garza-Reyes

The research explores the shift to Quality 4.0, examining the move towards a data-focussed transformation within organizational frameworks. This transition is characterized by…

Abstract

Purpose

The research explores the shift to Quality 4.0, examining the move towards a data-focussed transformation within organizational frameworks. This transition is characterized by incorporating Industry 4.0 technological innovations into existing quality management frameworks, signifying a significant evolution in quality control systems. Despite the evident advantages, the practical deployment in the Indian manufacturing sector encounters various obstacles. This research is dedicated to a thorough examination of these impediments. It is structured around a set of pivotal research questions: First, it seeks to identify the key barriers that impede the adoption of Quality 4.0. Second, it aims to elucidate these barriers' interrelations and mutual dependencies. Thirdly, the research prioritizes these barriers in terms of their significance to the adoption process. Finally, it contemplates the ramifications of these priorities for the strategic advancement of manufacturing practices and the development of informed policies. By answering these questions, the research provides a detailed understanding of the challenges faced. It offers actionable insights for practitioners and policymakers implementing Quality 4.0 in the Indian manufacturing sector.

Design/methodology/approach

Employing Interpretive Structural Modelling and Matrix Impact of Cross Multiplication Applied to Classification, the authors probe the interdependencies amongst fourteen identified barriers inhibiting Quality 4.0 adoption. These barriers were categorized according to their driving power and dependence, providing a richer understanding of the dynamic obstacles within the Technology–Organization–Environment (TOE) framework.

Findings

The study results highlight the lack of Quality 4.0 standards and Big Data Analytics (BDA) tools as fundamental obstacles to integrating Quality 4.0 within the Indian manufacturing sector. Additionally, the study results contravene dominant academic narratives, suggesting that the cumulative impact of organizational barriers is marginal, contrary to theoretical postulations emphasizing their central significance in Quality 4.0 assimilation.

Practical implications

This research provides concrete strategies, such as developing a collaborative platform for sharing best practices in Quality 4.0 standards, which fosters a synergistic relationship between organizations and policymakers, for instance, by creating a joint task force, comprised of industry leaders and regulatory bodies, dedicated to formulating and disseminating comprehensive guidelines for Quality 4.0 adoption. This initiative could lead to establishing industry-wide standards, benefiting from the pooled expertise of diverse stakeholders. Additionally, the study underscores the necessity for robust, standardized Big Data Analytics tools specifically designed to meet the Quality 4.0 criteria, which can be developed through public-private partnerships. These tools would facilitate the seamless integration of Quality 4.0 processes, demonstrating a direct route for overcoming the barriers of inadequate standards.

Originality/value

This research delineates specific obstacles to Quality 4.0 adoption by applying the TOE framework, detailing how these barriers interact with and influence each other, particularly highlighting the previously overlooked environmental factors. The analysis reveals a critical interdependence between “lack of standards for Quality 4.0” and “lack of standardized BDA tools and solutions,” providing nuanced insights into their conjoined effect on stalling progress in this field. Moreover, the study contributes to the theoretical body of knowledge by mapping out these novel impediments, offering a more comprehensive understanding of the challenges faced in adopting Quality 4.0.

Details

International Journal of Quality & Reliability Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 15 February 2024

Albi Thomas and M. Suresh

Green transformation is more than simply a trend; it is a way of life, a set of habits, a field of knowledge and a dedication to resource conservation. Going green is surely a…

Abstract

Purpose

Green transformation is more than simply a trend; it is a way of life, a set of habits, a field of knowledge and a dedication to resource conservation. Going green is surely a creative and transformative process for both individuals and organizations. This paper aims to “identify,” “analyse” and “categorise” the readiness factors for green transformation process in health care using total interpretive structural modelling (TISM) and neutrosophic-MICMAC.

Design/methodology/approach

To address the study objectives, the study used TISM and neutrosophic-MICMAC analysis. To identify the readiness factors, a literature study was conducted, and the factors were face-validated by the healthcare experts. The factors influence on one another were captured by using a scheduled interview with a closed ended questionnaire. The TISM addressed the identification and analysing of factors and the categorization and ranking the readiness factors is addressed by using neutrosophic-MICMAC analysis.

Findings

This study identified 11 green transformation process readiness factors for healthcare organizations. The study states that the key factors or driving factors are awareness of green governance principle, environment leadership and management, green gap analysis, information and communication technology and innovation dynamics.

Research limitations/implications

The factor ranking is sensitive to the respondents’ ratings. The study relied on the past literature and experts’ opinion may result in the subjective biases. The complex nature of healthcare ecosystem challenges to capture all the factors. The study focussed on Indian hospitals.

Practical implications

Study significantly impacts the healthcare practitioners, academicians and policymakers by providing critical insights into the readiness factors required for the healthcare green transformation process. The study offers a better understanding of the crucial or key or driving factors that aid in embracing green and sustainable practices.

Originality/value

Identifying a gap in conceptual and theoretical frameworks for green transformation readiness factors in healthcare organizations and in Indian context. The study addresses this gap by aiming to create a thorough theoretical framework and highlighted by its focus on Indian hospitals.

Details

Journal of Indian Business Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1755-4195

Keywords

Article
Publication date: 18 April 2022

Prashant Jain, Dhanraj P. Tambuskar and Vaibhav Narwane

The advancements in internet technologies and the use of sophisticated digital devices in supply chain operations incessantly generate enormous amounts of data, which is termed as…

Abstract

Purpose

The advancements in internet technologies and the use of sophisticated digital devices in supply chain operations incessantly generate enormous amounts of data, which is termed as big data (BD). The BD technologies have brought about a paradigm shift in the supply chain decision-making towards profitability and sustainability. The aim of this work is to address the issue of implementation of the big data analytics (BDA) in sustainable supply chain management (SSCM) by identifying the relevant factors and developing a structural model for this purpose.

Design/methodology/approach

Through a comprehensive literature review and experts’ opinion, the crucial factors are found using the PESTEL framework, which covers political, economic, social, technological, environmental and legal factors. The structural model is developed based on the results of the total interpretive structural modelling (TISM) procedure and MICMAC analysis.

Findings

The policy support regarding IT, culture of data-based decision-making, inappropriate selection of BDA technologies and the laws related to data security and privacy are found to affect most of the other factors. Also, the company’s vision towards environmental performance and willingness for material and energy optimization are found to be crucial for the environmental and social sustainability of the supply chain.

Research limitations/implications

The study is focused on the manufacturing supply chain in emerging economies. It may be extended to other industry sectors and geographical areas. Also, additional factors may be included to make the model more robust.

Practical implications

The proposed model imparts an understanding of the relative importance and interrelationship of factors. This may be useful to managers to assess their strengths and weaknesses and ascertain their priorities in the context of their organization for developing a suitable investment plan.

Social implications

The study establishes the importance of BDA for conservation and management of energy and material. This is crucial to develop strategies for enhancing eco-efficiency of the supply chain, which in turn enhances the economic returns for the society.

Originality/value

This study addresses the implementation of BDA in SSCM in the context of emerging economies. It uses the PESTEL framework for identifying the factors, which is a comprehensive framework for strategic planning and decision-making. This study makes use of the TISM methodology for model development and deliberates on the social and environmental implications too, apart from theoretical and managerial implications.

Details

Journal of Engineering, Design and Technology , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1726-0531

Keywords

Article
Publication date: 12 December 2022

Supratika Samir Banerjee and Arti Chandani

The novel blockchain technology can be leveraged, owing to the growth in computing power and its widespread applications. This study aims to understand the challenges of adopting…

Abstract

Purpose

The novel blockchain technology can be leveraged, owing to the growth in computing power and its widespread applications. This study aims to understand the challenges of adopting blockchain technology in the financial sector, organise them into a model and classify them for systematic address.

Design/methodology/approach

Interpretive Structural Modeling (ISM) has been carried out along with MICMAC (Matrice d’impacts croisés multiplication appliquée á un classment) analysis to hierarchically structure blockchain adoption problems and categorise the challenges into four classes-autonomous, dependent, linkage and independent for better addressing. The study also uses content analysis using NVivo software.

Findings

The digraph depicts the hierarchical challenge model. Vulnerability to financial crimes and glitches, privacy issues and geopolitical tensions due to cross-border transactions are the dependent variables. Complex architecture to comprehend, code and fix, the need for new financial intermediaries, complexity in auditing and the lack of unified governance and coordination among institutions and regulators are the independent variables. The digraph, which is also justified by the qualitative content analysis, is beneficial for stakeholders to systematically address the interdependent challenges associated with blockchain implementations in finance to foster its favourable adoption.

Practical implications

The challenges in the adoption of blockchain should be resolved to allow the implementation of this technology in various finance domains. This study enables organisations to carry out resource planning and systematically address these challenges to leverage the advantages of blockchain.

Social implications

The results of the present study can help in promoting the proliferation of blockchain for faster, cost-effective, transparent and secure financial transactions and foster innovative and new business models for economic growth.

Originality/value

The development of technology has brought about significant changes in the financial sector. Blockchain is a technological advancement that aims to bring security and transparency to transactions. There has been no research leveraging ISM-MICMAC to hierarchically organise and classify the blockchain challenges in the financial sector, a critical one. The research also uses content analysis which is seldom found along with ISM-MICMAC.

Details

Journal of Economic and Administrative Sciences, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1026-4116

Keywords

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