Search results

Over the years, the fruit and vegetable supply chain has encountered several challenges. From the harvesting stage until it reaches the consumer, a significant portion of fruits and vegetables gets wasted in the supply chain. As a result, the present study attempts to identify and analyze the growth barriers in the fresh produce supply chain (FPSC) in the Indian context.

An integrated grey theory and DEMATEL based approach is used to analyze growth barriers in the FPSC. The growth barriers were analyzed and sorted based on their influence and importance relations.

The results emphasize that the most critical growth barriers in the FPSC that should be addressed to ensure food waste reduction are as follows: Lack of cold chain facilities (B2), lack of transportation or logistic facilities (B1), lack of collaboration and information sharing between supply chain partners (B3), lack of proper quality and safety protocols (B15), a lack of processing and packaging facilities (B14), and poor productivity and efficiency (B13). Results are also verified by conducting a sensitivity analysis.

The results are highly useful for policymakers to exploit growth barriers within the FPSC that require more attention. The obtained results show that the managers and policymakers need to utilize more funds to develop the cold chain facilities and logistics facilities to develop the FPSC. By improving the cold chain facilities, it is possible to improve the quality of food, make the food safe for human consumption, reduce waste, and increase the efficiency and productivity of the supply chain. Also, this study may encourage policymakers and industrial managers to adopt the most influential SCM practices for food waste reduction.

Many researchers have attempted to analyze the causes of food waste and growth barriers in the FPSC using various decision-making methods. Still, no attempts are made to explore the causal relations among various growth barriers in FPSC through the integrated Grey-DEMATEL technique. Also, we devise policy implications in the light of the new farm bills or the Indian agricultural acts of 2020. Lack of cold chain facilities (B2) was found to be the critical driving barrier in the FPSC, as it influences multiple barriers. Also, there is a dire need for cold chain facilities and transportation systems to enhance productivity and efficiency.

This research paper aims to analyze the critical barriers to implementing digitalization in the Indian construction industry as Indian construction companies are lagging in the implementation of digital technologies in the work environment.

In this research paper, a qualitative research approach is adopted, and multiple detailed interviews are conducted with industry and academic experts. Further, multi-criteria decision-making (MCDM) techniques are used to finalize the prioritization among various alternatives. The fuzzy-decision-making trial and evaluation laboratory (Fuzzy-DEMATEL) and interpretive structural modeling (ISM) techniques are employed to find the exact relationship among the identified alternatives.

This study identifies 14 critical barriers from an extensive literature review and multiple interviews with industry professionals, and further driving and critical barriers are identified.

In this research paper, an exploratory study with a limited number of respondents from a large Indian construction company is carried out. Further, a detailed longitudinal analysis can be done to assess the subjectivity of the participants with more advanced statistical tools. However, this research discusses several points pertaining to the implementation of digitalization in the construction industry. The research further identifies the critical barriers to digitalization in the Indian construction industry.

The finding of the study has two-pronged implications. First, it provides a road-map to the construction industry by highlighting the engagement of top management as the key focus area for successful digitalization. Second, the finding also shows similarity of the digitalization process to the adoption of process improvement techniques like lean and total quality management (TQM), wherein the top management plays a crucial role in ushering in the implementation of a disruptive change.

The research is unique in two ways. First, this is one of the very few attempts to understand digitalization in the Indian context. Second, the research also demonstrates that the combination of fuzzy DEMATEL and ISM techniques can be successfully employed in the emerging field of construction digitalization research.

The purpose of this paper is to examine Philip B. Crosby’s 14 quality principles and analyze the interaction between them. Hitherto no research has been published on the implementation of total quality management (TQM) using Crosby’s 14 principles. To fill this gap, interpretive structural modeling (ISM) and Matrix Impact Cross-Reference Multiplication Applied to a Classification (MICMAC) analysis have been designed to prioritize, sequence and categorize variables to find both the dependence and driving power of these variables.

At the initial stage experts from industry as well as from academia were contacted to provide an input for ISM methodology and examine interactions between identified variables. In this approach, interpretations of the interrelationships among variables have been discussed, whereas MICMAC analysis is used to discover dependence and driving power.

The results of the investigation revealed that “Management Commitment,” “Quality Improvement Team,” “Quality Awareness,” “Supervisor Training,” “Goal Setting” and “Cost of Quality Evaluation” are strategic requirements; “Corrective Action,” “Zero Defects Day” and “Error Cause Removal” are tactical requirements. “Recognition,” “Quality Measurement,” “Quality Councils” and “Do It Over Again” are operational requirements for TQM applications.

ISM is used as a part of this research to provide valuable insights into interrelationships among Crosby’s quality principles through a systematic framework. The research opens up a new focus area on the implementation of TQM for services as well as for the manufacturing industry.

It is always of great importance for managers in organizations to evaluate their staff members and create incentive systems, using instruments such as Data Envelopment Analysis (DEA) and DEA-R (DEA models based on ratio analysis). The purpose of this paper is to propose a two-stage network incentives system for commercial banks.

Centralized Resource Allocation (CRA) models make it possible to project all decision-making units (DMUs) onto the efficient frontier by solving a single linear programming model. In this paper, we use our proposed DEA-R-based CRA models to evaluate commercial banks in a two-stage case when the only ratios available are the assets-to-costs and income-to-assets vectors.

Thirteen commercial banks modeled as two-stage networks were evaluated by the models proposed in two different cases of ratio data. Results suggest that the proposed methodology yields more accurate efficiency scores, thus allowing better discrimination among DMUs. Furthermore, evaluating the DMUs when they are structured as two-stage (or even three-stage) networks makes it possible to examine the incentives system in more detail. Therefore, the use of incentive systems by managers would allow a better focus on the priority activities of commercial banks and a faster movement toward the frontier of best practices.

The super-efficiency scores of a number of commercial banks are evaluated based on the CRA model, as a cornerstone criterion for the two-stage evaluation in DEA-R, thus allowing the rank of each commercial bank in terms of the incentives system rather on the performance of the productive process.

The COVID-19 outbreak disrupted the business environment and severely affected the morale and performance of the employees. Further, the Indian automobile industry witnessed major setbacks and drastically impacted sector in COVID-19. Talent agility is an emerging concept in the field of HRM that will foster innovations and productivity in the automobile industry. Thus, this study aims to explore the barriers to building in-house agile talents in the Indian automobile industry in the new normal.

The barriers of talent agility were identified through a literature review and validated through experts’ opinions. This study used a hybrid approach, which combines Interpretive Structural Modelling-Polarity (ISM-P) and decision-making trial and evaluation laboratory (DEMATEL) to develop a hierarchical structural model of the barriers, followed by classification into cause and effect groups.

The result of the multi-method approach identified that shortage of skills and competencies, lack of IT infrastructure, lack of ambidextrous leaders, lack of smart HRM technologies and practices, lack of attractive reward system/career management, poor advanced T&D, poor industry, institute interface and financial constraints are the critical barriers.

It can provide a strategic roadmap for automobile manufacturers to promote talent agility in the current wave of digitalization (Industry 4.0). This study can help the managers to address and overcome the barrier and hurdles in building talent agility.

This study is unique in that it addresses the contemporary issues related to talent agility in the context of the Indian automobile industry in the current rapidly changing environment. This study developed a holistic integrated ISM(P)-DEMATEL hierarchical framework on the barriers of talent agility indicating inner dependency weights, i.e., the strength of interrelationship between the barriers.

This study aims to identify 3D-printed medical model (3DPMM) supply chain barriers that affect the supply chain of 3DPMM in the Indian context and investigate the interdependencies between the barriers to establish hierarchical relations between them to improve the supply chain.

The methodology used interpretive structural modeling (ISM) and a decision-making trial and evaluation laboratory (DEMATEL) to identify the hierarchical and contextual relations among the barriers to the 3DPMM supply chain.

A total of 15 3DPMM supply chain barriers were identified in this study. The analysis identified limited materials options, slow production speed, manual post-processing, high-skilled data analyst, design and customization expert and simulation accuracy as the significant driving barriers for the medical models supply chain for hospitals. In addition, the authors identified linkage and dependent barriers. The present study findings would help to improve the 3DPMM supply chain.

There were no experts from other nations, so this study might have missed a few 3DPMM supply chain barriers that would have been significant from another nation’s perspective.

ISM would help practitioners minimize 3DPMM supply chain barriers, while DEMATEL allows practitioners to emphasize the causal effects of 3DPMM supply chain barriers.

This study minimizes the 3DPMM supply chain barriers for medical applications through a hybrid ISM and DEMATEL methodology that has not been investigated in the literature.

Many types of research have already investigated the lean, green or agile manufacturing systems in a discrete manner or as combinations of two of them. In today’s competitive scenario, if industry wants to perpetuate its name in the market, then it has to supervene proper thinking and smart approach. Therefore, the combination of lean, green and agile manufacturing systems can provide better and beneficial results. The purpose of this paper is to discern the barriers to the combined lean green agile manufacturing system (LGAMS), understand their interdependence and develop a framework to enhance LGAMS by using total interpretive structural modeling (TISM) and MICMAC (Matriced’ Impacts Croise’s Multiplication Appliquée a UN Classement) Analysis.

This paper uses TISM methodology and MICMAC analysis to deduce the interrelationships between the barriers and rank them accordingly. A total of 13 barriers have been identified through extensive literature review and discussion with experts.

An integrated LGAMS has been presented that balances the lean, green and agile paradigms and can help supply chains become more efficient, streamlined and sustainable. Barriers are identified while referring to all three strategies to showcase the clear relevance. TISM models the barriers in different levels showcasing direct and important transitive relations. Further, MICMAC analysis distributes the barriers in four clusters in accordance with their driving and dependence power.

The inferences have been drawn from a model developed on the basis of inputs from a small fraction of the industry and academia and may show variations when considering the whole industry.

The outcome of this research can contribute to bringing the change to the manufacturing systems used in most developing nations. Also, top managers considering adoption of LGAMS can be cautious of the most influential barriers.

A TISM-based model of the barriers to an integrated LGAMS has been proposed with evaluation of the influence of the barriers.

Textile and Apparel (T&A) sector significantly influences socio-economic and environmental dimensions of the sustainability. The purpose of this paper is proposed to establish the interrelationship among the critical barriers to the sustainable development of T&A supply chains by using a multi-criteria decision-making approach and to obtain a ranking of the barriers.

In the present investigation through literature review and from expert opinions, 14 significant challenges to the sustainable growth of T&A sector have identified. For establishing the interrelationship and for developing a structural model of the identified challenges, interpretive structural modelling (ISM) methodology is employed.

The results of the investigation revealed that lack of effective governmental policies (B8), poor infrastructure (B4), lack of effective level of integration (B6), low foreign investment (B13) and demonetization (B12) are the top most significant challenges.

The model development based on the expert inputs from the industry and academia, these inputs could be biased influencing the accuracy of the model. Also, inclusion more factors for the analysis will improve the reliability of the model.

This research is intended to guide the policy and decision makers for improving overall the growth of the T&A supply chain.