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1 – 10 of 121Vineet Jain and Vimlesh Kumar Soni
The purpose of this paper is to identify the flexible manufacturing system performance variables and analyze the interactions among these variables. Interpretive structural…
Abstract
Purpose
The purpose of this paper is to identify the flexible manufacturing system performance variables and analyze the interactions among these variables. Interpretive structural modeling (ISM) has been reported for this but no study has been done regarding the interaction of its variables. Therefore, fuzzy TISM (total ISM) has been applied to deduce the relationship and interactions between the variables and driving and dependence power of these variables are examined by fuzzy MICMAC.
Design/methodology/approach
Fuzzy TISM and fuzzy MICMAC analysis have been applied to deduce the relationship and interactions among the variables and driving and dependence power of these variables are examined by fuzzy MICMAC.
Findings
In total, 15 variables have been identified from the extensive literature review. The result showed that automation, use of automated material handling, an effect of tool life and rework percentage have high driving power and weak dependence power in the fuzzy TISM model and fuzzy MICMAC analysis. These are also at the lowest level in the hierarchy in the fuzzy TISM model.
Originality/value
Fuzzy TISM model has been suggested for manufacturing industries with fuzzy MICMAC analysis. This proposed approach is a novel attempt to integrate TISM approach with the fuzzy sets. The integration of TISM with fuzzy sets provides flexibility to decision-makers to further understand the level of influences of one criterion over another, which was earlier present only in the form of binary (0, 1) numbers; 0 represents no influence and 1 represents influence.
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Nisha Bamel, Sanjay Dhir and Sushil Sushil
The purpose of this paper is to identify the inter-partner dynamics-based enablers of joint venture (JV) competitiveness. In addition, this paper models the interactions among…
Abstract
Purpose
The purpose of this paper is to identify the inter-partner dynamics-based enablers of joint venture (JV) competitiveness. In addition, this paper models the interactions among identified enablers/factors to project the strength of their relationship with JV competitiveness.
Design/methodology/approach
ISM- and total interpretive structural modeling (TISM)-based fuzzy TISM approach has been used to examine the interactions and strength of interactions among identified enablers of JV competitiveness.
Findings
The analysis concludes that inter-partner dynamics-based enablers, such as partner fit, power symmetry and trust, have strong driving power and low dependence power and are at the lowest level of hierarchy in fuzzy TISM model. Variables like collaborative communication, organizational learning and absorptive capacity are linkage variables and they have high dependence as well as driving power and they lie in the second level of fuzzy TISM hierarchy. Strategic flexibility is found to have high dependence power and has weak driving power. The outcome variable JV competitiveness found to have zero driving power and highest dependence power.
Practical implications
The findings have implications for practitioners and policy makers. JVs may achieve competitiveness by managing identified enablers (inter-partner dynamics).
Originality/value
Present paper is one among the few efforts that address the issue of JV competitiveness (post-formation of JV). Methodologically also, this study is one among few initial efforts of using modified fuzzy TISM to explore and understand the linkage among enablers and outcome variables. Modified fuzzy TISM process carries out transitivity checks along with the successive pair-wise comparisons and simplifies the fuzzy TISM approach.
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Sheak Salman, Tazim Ahmed, Hasin Md. Muhtasim Taqi, Guilherme F. Frederico, Amit Sarker Dip and Syed Mithun Ali
The apparel industry of Bangladesh is rethinking lean manufacturing (LM) deployment because of the challenges imposed by the COVID-19 pandemic. Due to COVID-19, LM implementation…
Abstract
Purpose
The apparel industry of Bangladesh is rethinking lean manufacturing (LM) deployment because of the challenges imposed by the COVID-19 pandemic. Due to COVID-19, LM implementation in the apparel industry has become more difficult. Thus, the purpose of this study is to explore the barriers to implementing LM practices in the apparel industry of Bangladesh in the context of COVID-19 pandemic.
Design/methodology/approach
For evaluating the barriers, an integrated framework that combines the Delphi method and fuzzy total interpretive structural modeling (TISM) has been designed. The application of fuzzy TISM has resulted in a structured hierarchical relationship model of the barriers with driving and driven power.
Findings
The findings reveal that “lack of synchronization of lean planning with strategic planning”, “lack of proper understanding of lean concept” and “low priority from the top management” are the three top most important barriers of LM implementation in apparel industry.
Practical implications
These findings will help the apparel industry to formulate strategy for implementing the LM practices successfully. The proposed model is expected to contribute to the sustainable development goals (SDGs) such as Responsible Consumption and Production (SDG 12); Decent Work and Economic Growth (SDG 8); Industry, Innovation and Infrastructure (SDG 9) via resilient strategies.
Originality/value
This study is one of few initial efforts to investigate LM implementation barriers during the COVID-19 epidemic in a real-world setting.
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Kuldeep Lamba and Surya Prakash Singh
The purpose of this paper is to identify and analyse the interactions among various enablers which are critical to the success of big data initiatives in operations and supply…
Abstract
Purpose
The purpose of this paper is to identify and analyse the interactions among various enablers which are critical to the success of big data initiatives in operations and supply chain management (OSCM).
Design/methodology/approach
Fourteen enablers of big data in OSCM have been selected from literature and consequent deliberations with experts from industry. Three different multi criteria decision-making (MCDM) techniques, namely, interpretive structural modeling (ISM), fuzzy total interpretive structural modeling (fuzzy-TISM) and decision-making trial and evaluation laboratory (DEMATEL) have been used to identify driving enablers. Further, common enablers from each technique, their hierarchies and inter-relationships have been established.
Findings
The enabler modelings using ISM, Fuzzy-TISM and DEMATEL shows that the top management commitment, financial support for big data initiatives, big data/data science skills, organizational structure and change management program are the most influential/driving enablers. Across all three different techniques, these five different enablers has been identified as the most promising ones to implement big data in OSCM. On the other hand, interpretability of analysis, big data quality management, data capture and storage and data security and privacy have been commonly identified across all three different modeling techniques as the most dependent big data enablers for OSCM.
Research limitations/implications
The MCDM models of big data enablers have been formulated based on the inputs from few domain experts and may not reflect the opinion of whole practitioners community.
Practical implications
The findings enable the decision makers to appropriately choose the desired and drop undesired enablers in implementing the big data initiatives to improve the performance of OSCM. The most common driving big data enablers can be given high priority over others and can significantly enhance the performance of OSCM.
Originality/value
MCDM-based hierarchical models and causal diagram for big data enablers depicting contextual inter-relationships has been proposed which is a new effort for implementation of big data in OSCM.
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Gopal Krushna Gouda and Binita Tiwari
Smart HR 4.0 is a new concept characterized by adopting innovative technologies of Industry 4.0 (I4.0) in the HR domain. This study attempts to identify the key factors of Smart…
Abstract
Purpose
Smart HR 4.0 is a new concept characterized by adopting innovative technologies of Industry 4.0 (I4.0) in the HR domain. This study attempts to identify the key factors of Smart HR 4.0 to foster organizational innovation ambidexterity.
Design/methodology/approach
Based on review of literature and survey from expert opinions by using the Delphi method, 12 factors were found most suitable for this study. Further, the fuzzy-TISM technique was used to establish contextual relationships and develop a hierarchical model on the identified factors. Subsequently, the MICMAC analysis was applied to classify these factors according to their driving and dependence power.
Findings
This study framed a conceptual hierarchical model of Smart HR 4.0 and established contextual relationships among identified factors. Result shows that smart organic structure, industry–institute interface, IT-enabled system and ambidextrous leadership are important factors as they have the highest driving power. Further, knowledge management, learning culture and psychological empowerment are the linkage factors having both driving as well as dependency power in the whole system.
Practical implications
This study can guide the managers in smoothly implementing these practices to manage their human capital amidst digital disruption, ensuring innovation competitiveness of the firm. The structural hierarchical framework of Smart HR 4.0 may serve as a blueprint for HR professionals and business leaders to attain organizational innovation ambidexterity in the current wave of digital disruptions (Industry 4.0).
Originality/value
This study provides a holistic model of smart HR 4.0 integrating innovation ambidexterity in I4.0.
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Mohd Imran Khan, Shahbaz Khan and Abid Haleem
Multiplicity and conflicting Halal standards involve unnecessary repetition of testing for demonstrating the Halal integrity of the process and the product, thus making it…
Abstract
Purpose
Multiplicity and conflicting Halal standards involve unnecessary repetition of testing for demonstrating the Halal integrity of the process and the product, thus making it difficult for the Halal commodities to get traction in international markets. The purpose of this paper is to suggest initiatives to facilitate harmonisation of Halal standards as to eliminate trade barrier of Halal and to assure the availability of Halal consumables to larger masses.
Design/methodology/approach
Ranking of the initiatives for the harmonisation of Halal standards taking in consideration the costs of accomplishment and associated benefits obtained has been done through the application of integrated Interpretive Ranking Process (IRP) and Fuzzy Total Interpretive Structural Modelling (Fuzzy TISM). This integrated methodology with the weighted criteria have refined the value of the net dominance of different variables, thereby increasing the efficacy of IRP in decision making.
Findings
Findings suggest that strengthening the strategic coordination and collaboration among competent HCBs is a significant initiative. This initiative needs to be undertaken to mitigate the conflict between HCBs. This necessitates to develop a common platform in making the collective decision for effectively controlling Halal businesses. Moreover, recognising competent HCBs will prompt the effective implementation and execution of Halal standards across the supply chain, and ease the global trading of Halal products. A framework has been conceptualised to enable harmonisation of Halal standards which intimates to develop globally agreed protocols for Halal practices.
Practical implications
The framework presented may act as a prelude to harmonise Halal standards and may positively affect the international trade of Halal commodities by phasing out the discriminatory and market-impeding standards.
Originality/value
A harmonised system may provide correct information to the stakeholders and may help in making an informed decision.
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This paper aims to identify the big data analytics (BDAs) based enablers of supply chain capabilities (SCCs) and competitiveness of firms. This paper also models the interaction…
Abstract
Purpose
This paper aims to identify the big data analytics (BDAs) based enablers of supply chain capabilities (SCCs) and competitiveness of firms. This paper also models the interaction among identified enablers and thus projects the relationship strength of these enablers with SCC and a firm's competitiveness.
Design/methodology/approach
In order to achieve the research objectives of this paper, we employed fuzzy total interpretive structural modeling (TISM), an integrated approach of an interpretive structural model and TISM.
Findings
Results suggest that BDA-based enablers namely, IT infrastructure for BDA; leadership commitment; people skills for use of BDA and financial support for BDA significantly enable SCC and enhance firm competitiveness.
Practical implications
Results of the present study have implications for researchers and practitioners; the results will enable them to design policies around identified enablers of BDA initiatives.
Originality/value
The present paper is one of a few early efforts that address the role of BDA in augmenting SCC and subsequently a firm's competitiveness from a resource-dynamic capability perspective.
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Surajit Bag, Sunil Luthra, V.G. Venkatesh and Gunjan Yadav
Humanitarian supply chains (HSCs) by their very nature require urgent reaction to unforeseeable needs, making it difficult to properly plan for the support of actual demands. As…
Abstract
Purpose
Humanitarian supply chains (HSCs) by their very nature require urgent reaction to unforeseeable needs, making it difficult to properly plan for the support of actual demands. As such, integrating sustainability into traditional HSC practices continues to present a challenge to governments, nongovernmental organizations (NGOs) and other humanitarian-related agencies. This study focuses on identifying and categorizing the leading enablers to green humanitarian supply chains (GHSCs) and proposes a model for improving the responsiveness based upon a fuzzy total interpretive structural modelling approach.
Design/methodology/approach
Total interpretive structural modelling (TISM) uses group decision-making to identify contextual relationships among each pair of enablers and elucidates the nature of each underlying relationship. The fuzzy TISM shows the level of strength (very high influence, high influence, low influence and very low influence) of each enabler in relation to other enablers, which can help to inform management decision-making.
Findings
GHSC management requires strategic planning of inventory and logistics management. The importance of collaborative relationship building with HSC partners for developing capability and the effective use of available resources are keys to success. These improved relationships also help to promote postponement and similar speculation-based logistics strategies, as well as advanced purchasing and pre-positioning strategies. Finally, the speed and quality of response is found to be the top enabler in GHSC management.
Research limitations/implications
One noted shortcoming of the chosen research method is its reliance on subjective expert judgement. However, collecting judgements is at the basis of many research methods, and the research team took utmost care throughout the research process to allay biases. Future empirical research can further examine the relationships suggested herein. Managers can use the model developed in this research to consider impactful ways to design and execute sustainable HSCs.
Originality/value
To the best of the authors' knowledge, this is a novel attempt to identify enablers to GHSC management. Secondly, the research team has used an advanced methodology (fuzzy TISM) to develop the contextual inter-relationships among the enablers which has not been used earlier in this direction before and thus advances the GHSC literature.
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The purpose of this paper is to model the sustainable food security system using various technologies driving internet of things (IoT). The right to food is a fundamental right of…
Abstract
Purpose
The purpose of this paper is to model the sustainable food security system using various technologies driving internet of things (IoT). The right to food is a fundamental right of humans. With increasing population and urbanization, less land is being used for agricultural purposes. In addition, the climate change due to global warming often leads to frequent disasters such as droughts and floods, adversely affecting the food production. This leads to increased levels of poverty and hunger. Ensuring food security has become the prime agenda for all the policymakers and government bodies across the world. With changing global dynamics, traditional ways of ensuring food security will not be sufficient alone.
Design/methodology/approach
There is a need to develop a sustainable food security system that not only focusses on food production but also equally emphasizes on the efficacy of food distribution and reducing food wastage. In this digital age, the emerging disruptive technologies like Block chain, robotics, big data analytics, and cloud computations, etc., are increasingly changing the functioning of various sectors, giving rise to IoT-based working environment. The policymakers are also exploring these technologies to maximize their outreach so as to benefit the larger set of population and to gain visualization and control over policy implementation using IoT. This paper attempts to model the sustainable food security system using various technologies driving IoT. It also studies the interrelationship among various technologies and their application in various levels of policy implementation. The methodology used in the paper is fuzzy-TISM, which not only provides the causal relationship among two technologies but also provides the magnitude of the cause–effect relationship and the hierarchical framework for the complex problem.
Findings
The paper is addressed to the design of sustainable food security system in the Indian context wherein government ensures food security for all, using public distribution system (PDS).
Social implications
The paper is addressed to the design of sustainable food security system in Indian context wherein government ensures food security for all, using PDS.
Originality/value
This study is a novel attempt to integrate the IoT into the design of the PDS to ensure food security. The enabling factors for IOT are modelled using Fuzzy-TISM.
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Yesim Deniz Ozkan-Ozen and Yigit Kazancoglu
The aim of this paper is to identify and analyse workforce development challenges in the digital age by first, presenting these challenges and relationship between them, and then…
Abstract
Purpose
The aim of this paper is to identify and analyse workforce development challenges in the digital age by first, presenting these challenges and relationship between them, and then proposing a structural model that categorizes these challenges and proposes suggestions for managers to improve human resources practices and firm performance.
Design/methodology/approach
Fuzzy total interpretive structural modelling (TISM) is used as the methodology, which gives an interpretive structural model by presenting direct and transitive relationship between workforce development challenges and categorizes them under autonomous, dependent, independent and linkage groups.
Findings
In total, 13 different workforce development challenges are presented in this study. Results showed that lack of IT/digital skills has a critical role in workforce development in terms of affecting other challenges. Dependent group includes requirements for longer learning time and specialized training, lack of analytical thinking and dealing with complexity, and lack of interdisciplinary thinking and acting. On the other hand, lack of ability in decentralized decision-making and shortage of workforce with adequate skillset within the labour market have more macro-impacts on others. Most of the challenges located in the linkage group, which means that most of the challenges are interrelated with each other.
Originality/value
Originality of this paper is presenting a systematic structure for workforce development in Industry 4.0 that considers challenges systematically.
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