Suman Choudhary and Kirti Mishra
This paper aims to explore the implications of virtual work arrangements on employee knowledge hiding (KH) behaviour and the different strategies of KH used by employees in these…
Abstract
Purpose
This paper aims to explore the implications of virtual work arrangements on employee knowledge hiding (KH) behaviour and the different strategies of KH used by employees in these arrangements.
Design/methodology/approach
Following a grounded theory approach to understanding KH, 21 semi-structured in-depth interviews were conducted with employees engaged in virtual working setups. The data collected from these informants were then analysed using qualitative methods.
Findings
The study revealed that virtual work arrangements increase employee KH behaviour because of three reasons: ease of hiding, digital burnout and loss of control. Further, the study found that rationalized hiding is the most commonly adopted strategy by employees engaged in virtual work arrangements, while inclinations towards evasive hiding strategy decrease in this arrangement.
Originality/value
This is the first study in knowledge management literature that seeks to explain KH in the virtual work context.
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Kavita Choudhary and Suman Pant
This paper aims to present comfort properties of bamboo-silk and cotton-silk Kota Doria fabrics.
Abstract
Purpose
This paper aims to present comfort properties of bamboo-silk and cotton-silk Kota Doria fabrics.
Design/methodology/approach
Two types of Kota Doria fabrics were manufactured: one from the mixture of silk and bamboo yarns and the other from the mixture of cotton and silk yarns. Air permeability, thermal resistance and moisture management properties were determined.
Findings
Air permeability of bamboo-silk fabric was higher than that of cotton-silk fabric, whereas thermal resistance was less. Moisture management of both the fabrics was almost the same.
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Under the carbon tax policy, the authors examine the operational decisions of the low-carbon supply chain with the triple bottom line.
Abstract
Purpose
Under the carbon tax policy, the authors examine the operational decisions of the low-carbon supply chain with the triple bottom line.
Design/methodology/approach
This paper uses the Stackelberg game theory to obtain the optimal wholesale prices, retail prices, sales quantities and carbon emissions in different cases, and investigates the effect of the carbon tax policy.
Findings
This study’s main results are as follows: (1) the optimal retail price of the centralized supply chain is the lowest, while that of the decentralized supply chain where the manufacturer undertakes the carbon emission reduction (CER) responsibility and the corporate social responsibility (CSR) is the highest under certain conditions. (2) The sales quantity when the retailer undertakes the CER responsibility and the CSR is the largest. (3) The supply chain obtains the highest profits when the retailer undertakes the CER responsibility and the CSR. (4) The environmental performance impact decreases with the carbon tax.
Practical implications
The results of this study can provide decision-making suggestions for low-carbon supply chains. Besides, this paper provides implications for the government to promote the low-carbon market.
Originality/value
Most of the existing studies only consider economic responsibility and social responsibility or only consider economic responsibility and environmental responsibility. This paper is the first study that examines the operational decisions of low-carbon supply chains with the triple bottom line under the carbon tax policy.
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The purpose of this paper is to investigate the manufacturer’s production, pricing and green technology investment decision problem when strategic customer behavior and carbon…
Abstract
Purpose
The purpose of this paper is to investigate the manufacturer’s production, pricing and green technology investment decision problem when strategic customer behavior and carbon emissions-sensitive random demand is taken into consideration and discuss the impact of carbon emissions-sensitive demand on the manufacturer’s operation strategies, total carbon emissions and maximum expected profit.
Design/methodology/approach
The authors formulate a model to introduce carbon emissions-sensitive demand into the newsvendor framework with strategic customer behavior. The authors characterize the rational expectations equilibrium to derive the optimal solutions to the manufacturer. The authors analyze the effects of carbon emissions-sensitive demand on the manufacturer’s optimal strategies, total carbon emissions and maximum expected profit by comparative analysis.
Findings
The authors obtain the manufacturer’s optimal production, pricing and green technology investment strategies under rational expectations equilibrium in scenario of price-sensitive demand and that of carbon emissions-sensitive demand, respectively. The authors find that as customer demand changes from price-sensitive demand to carbon emissions-sensitive demand, the manufacturer’s optimal prices are the same but optimal production quantity, optimal unit carbon emissions and maximum expected profit go down. Though the total emissions decrease, the carbon emissions reduction would not increase as the demand is more carbon emissions-sensitive. Whether it increases or decreases depends on the model parameters.
Originality/value
Carbon emissions-sensitive demand and strategic customer behavior are considered simultaneously in an integrated model. The result can guide the manufacturer decision-making. The proposed model are hoped to shed light to the future works in the field of sustainable supply chain management.
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Reza Kiani Mavi, Neda Kiani Mavi, Doina Olaru, Sharon Biermann and Sae Chi
This paper systematically evaluates the existing literature of innovations in freight transport, including all modes, to uncover the key research themes and methodologies employed…
Abstract
Purpose
This paper systematically evaluates the existing literature of innovations in freight transport, including all modes, to uncover the key research themes and methodologies employed by researchers to study innovations and their implications in this industry. It analyses the role of transport and the impact of innovations during crises, such as COVID-19.
Design/methodology/approach
Qualitative and quantitative analysis of the innovations in freight transport unravels the pre-requisites of such endeavours in achieving a resilient and sustainable transport network that effectively and efficiently operates during a crisis. The authors performed keyword co-occurrence network (KCON) analysis and research focus parallelship network (RFPN) analysis using BibExcel and Gephi to determine the major resulting research streams in freight transport.
Findings
The RFPN identified five emerging themes: transport operations, technological innovation, transport economics, transport policy and resilience and disaster management. Optimisation and simulation techniques, and more recently, artificial intelligence and machine learning (ML) approaches, have been used to model and solve freight transport problems. Automation innovations have also penetrated freight and supply chains. Information and communication technology (ICT)-based innovations have also been found to be effective in building resilient supply chains.
Research limitations/implications
Given the growth of e-commerce during COVID-19 and the resulting logistics demand, along with the need for transporting food and medical emergency products, the role of automation, optimisation, monitoring systems and risk management in the transport industry has become more salient. Transport companies need to improve their operational efficiency using innovative technologies and data science for informed decision-making.
Originality/value
This paper advises researchers and practitioners involved in freight transport and innovation about main directions and gaps in the field through an integrated approach for evaluating research undertaken in the area. This paper also highlights the role of crisis, e.g. COVID-19, and its impacts on freight transport. Major contributions of this paper are as follows: (1) a qualitative and quantitative, systematic and effective assessment of the literature on freight transport through a network analysis of keywords supplemented by a review of the text of 148 papers; (2) unravelling major research areas; (3) identifying innovations in freight transport and their classification as technological and non-technological and (4) investigating the impact of crises and disruptions in freight transport.
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The chapter aims to empirically explore trends and issues concerning Indian wellness services being taken internationally for commercial use by wellness service providers and…
Abstract
The chapter aims to empirically explore trends and issues concerning Indian wellness services being taken internationally for commercial use by wellness service providers and tourists. The text also highlights how their authenticity gets compromised in place of profitability. The enquiry is approached through a conceptual framework of wellness tourism and subsequent tourism concerns. While scholars have recently turned their attention to tourism challenges during the COVID-19 pandemic, the perspective of digitalization within tourism can help to nuance this area of concern. Some recommendations for the Indian wellness tourism sector include digital solutions, screen-induced tourism, measures towards tourists' safety, regulations concerning certifications and targeting new client segments. Furthermore, raising greater awareness about the philosophical backdrop of Indian wellness services amongst international tourists would contribute to practice and theory while resurrecting the wellness tourism industry in India.
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Mohd Javaid, Ibrahim Haleem Khan, Ravi Pratap Singh, Shanay Rab and Rajiv Suman
Unmanned aerial vehicles are commonly known as UAVs and drones. Nowadays, industries have begun to realise the operational and economic benefits of drone-enabled tasks. The…
Abstract
Purpose
Unmanned aerial vehicles are commonly known as UAVs and drones. Nowadays, industries have begun to realise the operational and economic benefits of drone-enabled tasks. The Internet of Things (IoT), Big Data, drones, etc., represent implementable advanced technologies intended to accomplish Industry 4.0. The purpose of this study is to discuss the significant contributions of drones for Industry 4.0.
Design/methodology/approach
Nowadays, drones are used for inspections, mapping and surveying in difficult or hazardous locations. For writing this paper, relevant research papers on drone for Industry 4.0 are identified from various research platforms such as Scopus, Google Scholar, ResearchGate and ScienceDirect. Given the enormous extent of the topic, this work analyses many papers, reports and news stories in an attempt to comprehend and clarify Industry 4.0.
Findings
Drones are being implemented in manufacturing, entertainment industries (cinematography, etc.) and machinery across the world. Thermal-imaging devices attached to drones can detect variable heat levels emanating from a facility, trigger the sprinkler system and inform emergency authorities. Due partly to their utility and adaptability in industrial areas such as energy, transportation, engineering and more, autonomous drones significantly impact Industry 4.0. This paper discusses drones and their types. Several technological advances and primary extents of drones for Industry 4.0 are diagrammatically elaborated. Further, the authors identified and discussed 19 major applications of drones for Industry 4.0.
Originality/value
This paper’s originality lies in its discussion and exploration of the capabilities of drones for Industry 4.0, especially in manufacturing organisations. In addition to improving efficiency and site productivity, drones can easily undertake routine inspections and check streamlines operations and maintenance procedures. This work contributes to creating a common foundation for comprehending Industry 4.0 outcomes from many disciplinary viewpoints, allowing for more research and development for industrial innovation and technological progress.
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Mohd Javaid, Abid Haleem, Ravi Pratap Singh, Shanay Rab, Rajiv Suman and Shahbaz Khan
Over the past few decades, lean manufacturing has focussed on being customer-centred and now Lean 4.0 technologies have made it possible for manufacturers to have a deeper view of…
Abstract
Purpose
Over the past few decades, lean manufacturing has focussed on being customer-centred and now Lean 4.0 technologies have made it possible for manufacturers to have a deeper view of waste reduction. Technologies such as the internet of things, artificial intelligence, three-dimensional printing, robotics, real-time data, cloud computing, predictive analytics and augmented reality, are helpful to achieve Lean 4.0. This study aims to develop the conceptual understanding of Lean 4.0, related tools and linkage with Industry 4.0. Further, it provides the strategies for implementing Lean 4.0, developing lean culture and highlights the Lean 4.0 application in the manufacturing context.
Design/methodology/approach
This study relates to Lean 4.0 and its technologies. Prominent research is identified through Scopus, Web of Science, ScienceDirect and Google Scholar and studied as per the objective of this study. This lean revolution provides customers desire for personalisation, connectedness, high-quality and valuable products. Lean 4.0 provides valuable information on the value chain and production process. This revolution has significantly impacted refining production processes for a greater level of adaptability and cost reduction.
Findings
This paper is brief about Lean 4.0 and its capabilities for the reduction of waste. The authors discussed different tools used in Lean 4.0 and its relationship with Industry 4.0. The classical strategies and progressive features of Lean 4.0 for overall enhancing the manufacturing sphere are discussed diagrammatically. Finally, it identified and discussed 14 significant applications of Lean 4.0 for manufacturing industries.
Originality/value
This study provides a comprehensive understanding of Lean 4.0 and related tools and strategies that help the upcoming manufacturing industries.
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Shiv Raj, Suman Sharma and Dev Dutt
This study investigates the impact of digital disruption on tourism education in the 21st century.Research problem: Digital disruption is causing a major upheaval in the tourism…
Abstract
This study investigates the impact of digital disruption on tourism education in the 21st century.
Research problem: Digital disruption is causing a major upheaval in the tourism education sector, which is affecting how teachers instruct and how students learn. The purpose of this study is to investigate ways in which educators can adjust to these changes and to comprehend the impact of digital disruption on tourism education.
Research significance: This study is important because it clarifies the opportunities and problems associated with the digital disruption of tourism education. It offers guidance to educators, decision-makers, and industry participants on how to successfully incorporate digital technologies into curricula for tourism education.
Methods: A mixed-methods strategy integrating quantitative and qualitative methods was employed. An online survey and in-depth interviews with 100 participants – students, professionals in the industry, and educators – were used to gather data. For qualitative data, thematic analysis was employed, whereas descriptive statistics were used for quantitative data.
Frameworks: The study is set up in relation to the theory of digital disruption and how it affects education. The literature on digital technologies in education, transformative learning theory, and the necessity of developing 21st-century skills are also consulted.
Results: Participants generally perceived a moderate to high level of disruption, suggesting that there is a significant level of digital disruption in tourism education. The study emphasizes how critical it is to incorporate new technologies into curricula, stress the value of sustainable development, enhance intercultural competency, and promote cooperation between academic institutions and the travel and tourism sector.
Originality/value: Overall similarity 2%.
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Suman Chhabri, Krishnendu Hazra, Amitava Choudhury, Arijit Sinha and Manojit Ghosh
Because of the mechanical properties of aluminium (Al), an accurate prediction of its properties has been challenging. Researchers are seeking reliable models for predicting the…
Abstract
Purpose
Because of the mechanical properties of aluminium (Al), an accurate prediction of its properties has been challenging. Researchers are seeking reliable models for predicting the mechanical strength of Al alloys owing to the continuous emergence of new Al alloys and their applications. There has been widespread use of empirical and statistical models for the prediction of different mechanical properties of Al and Al alloy, such as linear and nonlinear regression. Nevertheless, the development of these models requires laborious experimental work, and they may not produce accurate results depending on the relationship between the Al properties, mix of other compositions and curing conditions.
Design/methodology/approach
Numerous machine learning (ML) models have been proposed as alternative approaches for predicting the strengths of Al and its alloys. The hardness of Al alloys has been predicted by implementing various ML algorithms, such as linear regression, ridge regression, lasso regression and artificial neural network (ANN). This investigation critically analysed and discussed the application and performance of models generated by linear regression, ridge regression, lasso regression and ANN algorithms using different mechanical properties as training parameters.
Findings
Considering the definition of the problem, linear regression has been found to be the most suitable algorithm in predicting the hardness values of AA7XXX alloys as the model generated by it best fits the data set.
Originality/value
The work presented in this paper is original and not submitted anywhere else.