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1 – 10 of 480Gopal Krushna Gouda and Binita Tiwari
This study aims to identify the key enablers for the adoption of Industry 4.0 (I4.0) in the automobile industry of India, which has been severely impacted by COVID-19. Adopting…
Abstract
Purpose
This study aims to identify the key enablers for the adoption of Industry 4.0 (I4.0) in the automobile industry of India, which has been severely impacted by COVID-19. Adopting I4.0 will provide organizations greater flexibility and resilience during the COVID-19 pandemic.
Design/methodology/approach
Based on the literature review and experts’ opinions, 21 enablers were identified. Further, contextual relationships among the identified factors and a hierarchical digraph was developed by using the total interpretive structural modelling (TISM) technique. Finally, fuzzy cross-impact matrix multiplication applied to classification (MICMAC) analysis was conducted to classify the enablers into different categories based on their dependence and driving power.
Findings
The results indicate that top management support, clarity on government policy, strategic vision on I4.0 and development of new industrial policy are the most influential factors, with the highest driving power placed at the bottom of the TISM hierarchical model. Furthermore, agile workforce, smart HR practices and IT standardization and security are identified as linkage enablers with the most driving and dependency power.
Practical implications
The hierarchical TISM model and fuzzy MICMAC approach provide a comprehensive understanding of the I4.0 implementation process through a visual, logical structure to the managers. It will help the researchers and practitioners understand the contextual relationship among various enablers in fostering the I4.0 adoption process and digital reorganization in the automobile industry during the COVID-19 pandemic.
Originality/value
This study provides a holistic TISM hierarchical framework on I4.0 adoption that will elevate the next maturity level of innovation adoption and may act as a blueprint for automobile industries during the COVID-19 pandemic.
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Sucheta Agarwal, Kuldeep Kumar Saxena, Vivek Agrawal, Jitendra Kumar Dixit, Chander Prakash, Dharam Buddhi and Kahtan A. Mohammed
Manufacturing companies are increasingly using green smart production (GSM) as a tactic to boost productivity since it has a number of advantages over conventional manufacturing…
Abstract
Purpose
Manufacturing companies are increasingly using green smart production (GSM) as a tactic to boost productivity since it has a number of advantages over conventional manufacturing methods. It costs a lot of money and takes a lot of work to create an SMS since it combines a lot of different technologies, including automation, data exchanges, cyber-physical systems (CPS), artificial intelligence, the Internet of things (IoT) and semi-autonomous industrial systems. Green smart manufacturing (GSM) activities provide the foundation for creating ecologically friendly and green products. However, there are a number of other significant barriers obstacles to GSM deployment. As a result, removing this identification of these hurdles in a systematic manner should be a top focus of this study.
Design/methodology/approach
This article seeks to identify and prioritize the nine barriers based on research and expert viewpoints on GSM challenges. The analytical hierarchy process (AHP) is used to prioritize the barriers.
Findings
The result depicts that, financial constraints is the most important barrier that followed by scarcity of dedicated suppliers, concern to data security lack of understanding of the surroundings, inadequate top management commitment, proper handling of data interfaces lack of support by government, employees' lack of training, concern to data security lack of environment knowledge, fear of change/resistance and constraints of technology.
Research limitations/implications
The current research will help the manufacturing industry in Industry 4.0 to identify potential barriers to GSM implementation.
Originality/value
Green manufacturing (GM) entails the implementation of renewable production methods and eco-friendly procedures in manufacturing businesses. This study helps manufacturers come up with recycling and creative products, and manufacturers can give back to the environment by protecting natural areas by getting rid of the obstacles that get in the way.
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Maharshi Samanta, Naveen Virmani, Rajesh Kumar Singh, Syed Nadimul Haque and Mohammed Jamshed
Manufacturing industries are facing dynamic challenges in today’s highly competitive world. In the recent past, integrating Industry 4.0 with the lean six sigma improvement…
Abstract
Purpose
Manufacturing industries are facing dynamic challenges in today’s highly competitive world. In the recent past, integrating Industry 4.0 with the lean six sigma improvement methodologies has emerged as a popular approach for organizational excellence. The research aims to explore and analyze critical success factors of lean six sigma integrated Industry 4.0 (LSSI).
Design/methodology/approach
This research study explores and analyzes the critical success factors (CSFs) of LSSI. A three-phase study framework is employed. At first, the CSFs are identified through an extensive literature review and validated through experts’ feedback. Then, in the second phase, the initial list of CSFs is finalized using the fuzzy DELPHI technique. In the third phase, the cause-effect relationship among CFSs is established using the fuzzy DEMATEL technique.
Findings
A dyadic relationship among cause-and-effect category CSFs is established. Under the cause category, top management commitment toward integrating LSSI, systematic methodology for LSSI and organizational culture for adopting changes while adopting LSSI are found to be topmost CSFs. Also, under the effect category, organizational readiness toward LSSI and adaptability and agility are found to be the uppermost CSFs.
Practical implications
The study offers a framework to understand the significant CSFs for LSSI implementation. Insights from the study will help industry managers and practitioners to implement LSSI and achieve organizational excellence.
Originality/value
To the best of the authors’ knowledge, CSFs of LSSI are not much explored in the past by researchers. Findings will be of great value for professionals in developing long-term operations strategies.
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Madhuri Prabhala and Indranil Bose
While there has been extensive research on understanding the effects of online reviews on product sales, there is not enough investigation of the inter-relationships between…
Abstract
Purpose
While there has been extensive research on understanding the effects of online reviews on product sales, there is not enough investigation of the inter-relationships between online reviews, online search and product sales. The study attempts to address this gap in the context of the Indian car market.
Design/methodology/approach
The research uses text mining and considers six important review features volume, valence, length, deviation of valence, sentiment and readability within the heuristic and systematic model of information processing. Panel data regression is used along with mediation analysis to study the inter-relationships between features of reviews, online search and sales.
Findings
The study finds that numerical heuristic features significantly affect sales and online search, numerical systematic feature affects sales and the textual heuristic and systematic features do not affect sales or online search in the Indian car market. Further, online search mediates the association between features of reviews and sales of cars.
Research limitations/implications
Although only car sales data from India is considered in this research, similar relationships between review features, online search and sales could exist for the car market of other countries as well.
Originality/value
This research uncovers the unique role of online search as a mediator between review features and sales, whereas prior literature has considered review features and online search as independent variables that affect sales.
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Manh-Hoang Do, Yung-Fu Huang and Vu-Dung-Van Phan
This research study aims to identify and rank the most substantial barriers to implementing green supply chain management (GSCM) in the Vietnamese agriculture industry.
Abstract
Purpose
This research study aims to identify and rank the most substantial barriers to implementing green supply chain management (GSCM) in the Vietnamese agriculture industry.
Design/methodology/approach
The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) techniques have been employed for this work to rank the critical GSCM barriers. The rankings were determined based on the expertise and input of ten experts from Vietnamese agriculture firms who participated as respondents.
Findings
This study has identified seven clusters of barriers, which encompass a total of 19 sub-barriers. Among these obstacles, the categories of financial costs and external stakeholders have emerged as the top priority barriers that require immediate attention and resolution. Meanwhile, the technology and strategic management clusters have a relatively weaker impact on GSCM implementation.
Practical implications
These findings provide valuable guidelines for the top managers in this sector to consider before systematically deciding on the GSCM implementation problems to improve performance and competitive advantage.
Originality/value
This work focuses on considering GSCM barriers for the Vietnamese agriculture industry; hence, it enriches the GSCM literature by offering perspectives from a transitional market, which results in variations in the barriers, categorization and importance ranking.
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Oscar F. Briones, Segundo M. Camino-Mogro and Veronica J. Navas
The purpose of this research is to examine Micro-, small- and medium-sized enterprises (MSMEs). Which have limited access to financial resources from financial intermediaries…
Abstract
Purpose
The purpose of this research is to examine Micro-, small- and medium-sized enterprises (MSMEs). Which have limited access to financial resources from financial intermediaries. Thus, resource allocation is a primary concern for them.
Design/methodology/approach
This research studies the determinants of cash conversion cycle components and cash flow of MSMEs operating in Ecuador. This study examined a robust sample of 19,680 firms from 2000 to 2020, using the two-step generalized methods of moments to control for endogeneity and multicollinearity of independent variables issues.
Findings
The sample was divided into working capital intensive and fixed capital intensive firms. It was found that in every segment (micro-, small- and medium-sized), the majority of firms are working capital intensive and their average return is higher. This implies that small business owners assign the majority of their resources to current assets, which thus far have enabled them to achieve higher profitability.
Originality/value
Research investigated Ecuadorian MSMEs in a dollarized developing environment. Scrutinizing working capital intensive vs fixed capital intensive.
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Gopal Krushna Gouda and Binita Tiwari
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Practical implications
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.
Originality/value
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.
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Karthik Bajar, Aditya Kamat, Saket Shanker and Akhilesh Barve
In recent times, reverse logistics (RL) is gaining significant traction in various automobile industries to recapture returned vehicles’ value. A good RL program can lower…
Abstract
Purpose
In recent times, reverse logistics (RL) is gaining significant traction in various automobile industries to recapture returned vehicles’ value. A good RL program can lower manufacturing costs, establish a green supply chain, enhance customer satisfaction and provide a competitive advantage. However, reducing disruptions and increasing operational efficiency in the automobile RL requires implementing innovative technology to improve information flow and security. Thus, this manuscript aims to examine the hurdles in automobile RL activities and how they can be effectively tackled by blockchain technology (BCT). Merging BCT and RL provides the entire automobile industry a chance to generate value for its consumers through effective vehicle return policies, manufacturing cost reduction, maintenance records tracking, administration of vehicle information and a clear payment record of insurance contracts.
Design/methodology/approach
This research is presented in three stages to accomplish the task. First, previous literature and experts' opinions are examined to highlight certain factors that are an aggravation to BCT implementation. Next, this study proposed an interval-valued intuitionistic fuzzy set (IVIFS) – decision-making trial and evaluation laboratory (DEMATEL) with Choquet integral framework for computing and analyzing the comparative results of factor interrelationships. Finally, the causal outline diagrams are plotted to determine the influence of factors on one another for BCT implementation in automobile RL.
Findings
This study has categorized the barriers to BCT implementation into five major factors – operational and strategical, technical, knowledge and behavioral, financial and infrastructural, and government rules and regulations. The results revealed that disreputable technology, low-bearing capacity of IT systems and operational inefficiency are the most significant factors to be dealt with by automobile industry professionals for finer and enhanced RL processes utilizing BCT. The most noticeable advantage of BCT is its enormous amount of data, permitting automobile RL to develop client experience through real-time data insights.
Practical implications
This study reveals several factors that are hindering the implementation of BCT in RL activities of the automobile industry. The results can assist experts and policymakers improve their existing decision-making systems while making an effort to implement BCT into the automobile industry's RL activities.
Originality/value
Although there are several studies on the benefits of BCT in RL and the adoption of BCT in the automobile industry, individually, none have explicated the use of BCT in automobile RL. This is also the first kind of study that has used IVIFS-DEMATEL with the Choquet integral framework for computing and analyzing the comparative results of factor interrelationships hindering BCT implementation in automobile RL activities.
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This study aims to develop the alleviating bullwhip effects framework (ABEF) replenishment rules, and bullwhip, inventory fluctuations and customer service fulfilment rates were…
Abstract
Purpose
This study aims to develop the alleviating bullwhip effects framework (ABEF) replenishment rules, and bullwhip, inventory fluctuations and customer service fulfilment rates were examined. In addition, automated smoothing and replenishment rules can alleviate supply chain bullwhip effects. This study aims to understand the current artificial intelligence (AI) implementation practice in alleviating bullwhip effects in supply chain management. This study aimed to develop a system for writing reviews using a systematic approach.
Design/methodology/approach
The methodology for the present study consists of three parts: Part 1 deals with the systematic review process. In Part 2, the study applies social network analysis (SNA) to the fourth phase of the systematic review process. In Part 3, the author discusses developing research clusters to analyse the research state more granularly. Systematic literature reviews synthesize scientific evidence through repeatable, transparent and rigorous procedures. By using this approach, you can better interpret and understand the data. The author used two databases (EBSCO and World of Science) for unbiased analysis. In addition, systematic reviews follow preferred reporting items for systematic reviews and meta-analyses.
Findings
The study uses UCINET6 software to analyse the data. The study found that specific topics received high centrality (more attention) from scholars when it came to the study topic. Contrary to this, others experienced low centrality scores when using NETDRAW visualization graphs and dynamic capability clusters. Comprehensive analyses are used for the study’s comparison of clusters.
Research limitations/implications
This study used a journal publication as the only source of information. Peer-reviewed journal papers were eliminated for their lack of rigorousness in evaluating the state of practice. This paper discusses the bullwhip effect of digital technology on supply chain management. Considering the increasing use of “AI” in their publications, other publications dealing with sensor integration could also have been excluded. To discuss the top five and bottom five topics, the author used magazines and tables.
Practical implications
The study explores the practical implications of smoothing the bullwhip effect through AI systems, collaboration, leadership and digital skills. Artificial intelligence is rapidly becoming a preferred tool in the supply chain, so management must understand the opportunities and challenges associated with its implementation. Furthermore, managers should consider how AI can influence supply chain collaboration concerning trust and forecasting to smooth the bullwhip effect.
Social implications
Digital leadership and addressing the digital skills gap are also essential for the success of AI systems. According to the framework, it is necessary to balance AI performance and accountability. As a result of the framework and structured management approach, the author can examine the implications of AI along the supply chain.
Originality/value
The study uses a systematic literature review based on SNA to analyse how AI can alleviate the bullwhip effects of supply chain disruption and identify the focused and the most important AI topics related to the bullwhip phenomena. SNA uses qualitative and quantitative methodologies to identify research trends, strengths, gaps and future directions for research. Salient topics for reviewing papers were identified. Centrality metrics were used to analyse the contemporary topic’s importance, including degree, betweenness and eigenvector centrality. ABEF is presented in the study.
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Amit Rohilla, Neeta Tripathi and Varun Bhandari
In a first of its kind, this paper tries to explore the long-run relationship between investors' sentiment and selected industries' returns over the period January 2010 to…
Abstract
Purpose
In a first of its kind, this paper tries to explore the long-run relationship between investors' sentiment and selected industries' returns over the period January 2010 to December 2021.
Design/methodology/approach
The paper uses 23 market and macroeconomic proxies to measure investor sentiment. Principal component analysis has been used to create sentiment sub-indices that represent investor sentiment. The autoregressive distributed lag (ARDL) model and other sophisticated econometric techniques such as the unit root test, the cumulative sum (CUSUM) stability test, regression, etc. have been used to achieve the objectives of the study.
Findings
The authors find that there is a significant relationship between sentiment sub-indices and industries' returns over the period of study. Market and economic variables, market ratios, advance-decline ratio, high-low index, price-to-book value ratio and liquidity in the economy are some of the significant sub-indices explaining industries' returns.
Research limitations/implications
The study has relevant implications for retail investors, policy-makers and other decision-makers in the Indian stock market. Results are helpful for the investor in improving their decision-making and identifying those sentiment sub-indices and the variables therein that are relevant in explaining the return of a particular industry.
Originality/value
The study contributes to the existing literature by exploring the relationship between sentiment and industries' returns in the Indian stock market and by identifying relevant sentiment sub-indices. Also, the study supports the investors' irrationality, which arises due to a plethora of behavioral biases as enshrined in classical finance.
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