Abhishek Dixit, Ashish Mani and Rohit Bansal
Feature selection is an important step for data pre-processing specially in the case of high dimensional data set. Performance of the data model is reduced if the model is trained…
Abstract
Purpose
Feature selection is an important step for data pre-processing specially in the case of high dimensional data set. Performance of the data model is reduced if the model is trained with high dimensional data set, and it results in poor classification accuracy. Therefore, before training the model an important step to apply is the feature selection on the dataset to improve the performance and classification accuracy.
Design/methodology/approach
A novel optimization approach that hybridizes binary particle swarm optimization (BPSO) and differential evolution (DE) for fine tuning of SVM classifier is presented. The name of the implemented classifier is given as DEPSOSVM.
Findings
This approach is evaluated using 20 UCI benchmark text data classification data set. Further, the performance of the proposed technique is also evaluated on UCI benchmark image data set of cancer images. From the results, it can be observed that the proposed DEPSOSVM techniques have significant improvement in performance over other algorithms in the literature for feature selection. The proposed technique shows better classification accuracy as well.
Originality/value
The proposed approach is different from the previous work, as in all the previous work DE/(rand/1) mutation strategy is used whereas in this study DE/(rand/2) is used and the mutation strategy with BPSO is updated. Another difference is on the crossover approach in our case as we have used a novel approach of comparing best particle with sigmoid function. The core contribution of this paper is to hybridize DE with BPSO combined with SVM classifier (DEPSOSVM) to handle the feature selection problems.
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Abhishek Dixit, Pooja Agrawal and Ajay Misra
The requirement of robust cooperative control is essential to achieve consensus between unmanned aerial vehicles (UAVs) operating in swarm formation. Often the performance of…
Abstract
Purpose
The requirement of robust cooperative control is essential to achieve consensus between unmanned aerial vehicles (UAVs) operating in swarm formation. Often the performance of these swarm formations is affected by wind gust disturbances. This study proposes an effective robust consensus protocol, which will ensure the UAVs in swam formation to collectively meet the desired objective in real-time scenario.
Design/methodology/approach
In this work, the swarm of UAVs are modeled as multiagent systems by using the concepts of algebraic graph theory. To address the challenges of a complex and dynamic environment, an adaptive sliding mode control (SMC)-based consensus protocol is proposed. The closed loop stability analysis is established through Lyapunov theory.
Findings
The efficacy of the discussed robust consensus controller is analyzed through numerical simulations. Further, the quantitative analysis using Monte-Carlo simulations validates performance of the proposed robust consensus protocol. The presented consensus protocol can be easily implementable as robust flight controller for swarm of UAVs. Also, as the consensus theory is based on the algebraic graph theory, the proposed design is scalable for a large number of UAVs in swarm formation.
Originality/value
The proposed adaptive SMC achieves robust consensus of longitudinal dynamics states between all the UAVs by mitigating the effects of wind gust disturbances. Also, the adaptive SMC offers chattering-free control efforts.
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Rahul Sindhwani, Rajender Kumar, Abhishek Behl, Punj Lata Singh, Anil Kumar and Tanmay Gupta
It would not be an exaggeration to say that healthcare is the most crucial one in today's perspective. The healthcare sector, in general, is engaged in working on various…
Abstract
Purpose
It would not be an exaggeration to say that healthcare is the most crucial one in today's perspective. The healthcare sector, in general, is engaged in working on various dimensions simultaneously like the safety, care, quality and cost of services, etc. Still, the desired outcomes from this sector are far away, and it becomes pertinent to address all such issues associated with healthcare on a priority basis for sustaining the outcomes in a long-term perspective. The present study aims to explore the healthcare sector and list out the directly associated enablers contributing to increasing the viability of the healthcare sector. Besides, the interrelationship among the enlisted enablers needs to be studied, which further helps in setting-out the priority to deal with individual enablers based on their impedance in the contribution towards viability increment.
Design/methodology/approach
The authors have done an extensive review to list out the enablers of the healthcare sector to perform efficiently and effectively. Further, the attempt has been made on the enablers to rank them by using the modified Total Interpretative Structure Modelling (m-TISM) approach. The validation of the study reveals the importance of enablers based on their position in the hierarchical structure. Further, the MICMAC analysis on the identified enabler is performed to categorize the identified enablers in the different clusters based on their driving power and dependence.
Findings
The research tries to envisage the importance of the healthcare sector and its contribution towards national development. The outcomes of the m-TISM model in the present study reveal the noteworthy contribution of the organizational structure in managing the healthcare facilities and represented it as the perspective of future growth. The well-designed organizational structure in the healthcare industry helps in establishing better employee–employer cooperation, workforce coordination and inter-department cooperation.
Research limitations/implications
Every research work has limitations. Likewise, the present research work also has limitations, i.e. input taken for developing the models are from very few experts that may not reflect the opinion of the whole sector.
Practical implications
The healthcare sector is the growing sector in the present-day scenario, and it is essential to keep the quality of treatment in check along with the quantity. The present study has laid down the practical foundations for improvement in the healthcare sector viability. Besides, the study emphasized on accountability of the healthcare sector officials to go with the enablers having the strong driving power for effective utilization of all the resources. This would further help them in customer (patients) satisfaction.
Originality/value
Despite an increase in demand for good quality healthcare facilities worldwide, the growth of this sector is bounded by the economic, demographic, cultural and environmental concerns, etc. The present study proposed a unique framework that provides a better understanding of the enablers. It would further help in playing a key role in increasing the viability of the healthcare sector. The hierarchy developed with the help of m-TISM and MICMAC analysis will help the viewers to recognize the important enablers based on their contribution to the viability improvement of the healthcare sector.
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Kavya Satish, Abhishek Venkatesh and Anand Shankar Raja Manivannan
This research aims to study the recent changes in consumer behaviour and purchase pattern during the Covid-19 pandemic. Covid-19 pandemic has forced consumers to stockpile, which…
Abstract
Purpose
This research aims to study the recent changes in consumer behaviour and purchase pattern during the Covid-19 pandemic. Covid-19 pandemic has forced consumers to stockpile, which has its own consequences. The article proposes the importance of “minimalism in consumption” to avoid greed in consumer behaviour.
Design/methodology/approach
The data are collected from consumers across India using an online survey during the first lockdown from March 2020 to May 2020. A simple random sampling technique is used for data collection, and the collected data are analysed using SPSS version 26.
Findings
The study states that there will be a shift in the purchase pattern of the consumers if lockdowns are imposed in the future or during any other crisis. However, at present, consumers have developed a stockpiling mentality fearing the unavailability of essentials.
Research limitations/implications
Pandemic has stimulated a drastic change in consumer behaviour, which is a situational effect. Each crisis affects consumer behaviour in a different way. In this research, we have considered only fear, greed and anxiety in the light of Covid-19. On the other hand, the research intends to draw realistic conclusions based on consumers' experiences during the lockdown.
Practical implications
The study proposes solutions that will help marketers frame exclusive strategies for a future crisis. Analysing the change in consumer behaviour and the shift in purchase patterns will emphasize the importance of market research to know consumer expectations during a crisis situation in order to cater to their new demands.
Social implications
Consumers who stockpile should realize the unavailability of goods to other consumers who are in need. They also have to understand the importance of “minimalism in consumption” during a crisis.
Originality/value
The data are collected during the most taxing crisis, the Covid-19 pandemic. Data are collected at the peak time of the first wave of Covid-19 in India, during a major shift in consumers' behaviour and purchase pattern. The article brings to the larger consciousness and also preaches a life lesson to all consumers to execute their responsibilities in consumption without over-demands and expectations.
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Abhishek N., Neethu Suraj, Keyur Kumar M. Nayak, Hardik Bhadeshiya, Abhinandan Kulal and M.S. Divyashree
This study aims to examine the factors driving the adoption of carbon management accounting (CMA) and various considerations that mediate its effectiveness in accounting and…
Abstract
Purpose
This study aims to examine the factors driving the adoption of carbon management accounting (CMA) and various considerations that mediate its effectiveness in accounting and disclosure practices.
Design/methodology/approach
This study used an exploratory, cross-sectional, quantitative design. Academics, managements/executives, professional accountants, professional auditors and researchers served as the primary units of analysis. This study used a survey method to gather data through a structured online questionnaire. The data were analyzed using descriptive statistics and partial least squares structural equation modeling (PLS-SEM).
Findings
The results revealed that the factors driving the adoption of CMA directly influence the effectiveness of CMA practices, with a significant mediating effect of regulatory and ethical aspects. Furthermore, this study revealed the difficulty of accounting, quantifying and reporting carbon emissions and revenue generation from the trading of carbon credits. This highlights the critical role of standard-setters and academics in deciding the concrete methodology to promote uniformity in carbon disclosures.
Research limitations/implications
The major limitations of this study are that it considered only the perception of experts and did not study the actual practices of CMA by considering companies that have already implemented CMA. Further studies should consider this aspect to validate the results of this study. Furthermore, the findings highlight the insignificant effect of economic, environmental and social aspects in enhancing the overall effectiveness of CMA. This is because of the limited number of factors considered in the study of such metrics. To overcome this limitation, future studies should consider wider aspects to validate the outcomes of this study.
Practical implications
The major contribution of this study is that it serves as a base input for business organizations, academics, researchers and regulatory authorities who are working to implement CMA strategies to reduce carbon emissions and promote net-zero business practices.
Originality/value
The outcome of this study is unique and new, as the subject matter of this study is in the nascent stage. The outcome of this study may become a significant valid input for regulators and policymaking companies to gain knowledge about CMA practices and motivate them to integrate CMA practices as part of their sustainability initiatives.
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Abhishek Kashyap and Om Ji Shukla
The purpose of this paper is to recognize and prioritize the critical drivers (CDs) essential for establishing a sustainable foxnut supply chain (SFNSC) aligned with the…
Abstract
Purpose
The purpose of this paper is to recognize and prioritize the critical drivers (CDs) essential for establishing a sustainable foxnut supply chain (SFNSC) aligned with the sustainable development goals (SDGs) set forth by the United Nations. The objective is to make a meaningful contribution to the longevity and well-rounded sustainability of the foxnut industry by scrutinizing pivotal factors that endorse triple bottom line (TBL) sustainability aspect throughout the supply chain.
Design/methodology/approach
A systematic approach, integrating literature reviews and government reports, identified potential CDs for a sustainable foxnut supply chain. Expert opinions refined the list with the help of fuzzy-Delphi method (FDM), and the final CDs were analyzed with fuzzy decision-making trial and evaluation laboratory (F-DEMATEL) to establish their causal relationships and hierarchical importance.
Findings
The study identifies the top three CDs for a SFNSC: “Branding of the product”, “The Global increase in demand” and “Value addition of the foxnut”. Moreover, “Storage infrastructure”, “Mechanized processing” and “Proper transportation facilities” also contribute to the sustainability of the foxnut supply chain.
Research limitations/implications
The results hold significance for various stakeholders in the foxnut industry, encompassing producers, policymakers and researchers. The identified CDs can guide decision-making and resource allocation to improve the sustainability of the foxnut supply chain. The study's framework and methodology can also be applied to other industries to promote sustainable practices and achieve SDGs.
Originality/value
This study enhances understanding of CDs for an SFNSC. FDM and F-DEMATEL techniques analyze causal relationships and rank key factors. The SFNSC model may help other major foxnut producers to become more sustainable.
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Mukta Srivastava, Neeraj Pandey and Gordhan K. Saini
Reference price is a key input in deciding product/service prices by organizations and has a significant influence on consumer purchase decisions. This study aims to provide a…
Abstract
Purpose
Reference price is a key input in deciding product/service prices by organizations and has a significant influence on consumer purchase decisions. This study aims to provide a deeper understanding of reference pricing literature using bibliometric analysis and offers specific research questions for future research in this domain.
Design/methodology/approach
Using a sample of 309 articles published between 1977 and 2021, the study conducts bibliographic coupling, citation analysis, cluster analysis, content analysis, keyword analysis and a three-field plot to map the intellectual structure of reference price.
Findings
The content analysis gave seven research clusters: (1) modeling reference price, (2) consumer perceptions of price (un)fairness, (3) price framing, (4) comparative price-based promotion, (5) reference price formulation, (6) pay-what-you-want (PWYW) pricing and (7) range theory and price perceptions. The study also delineates reference price literature across several parameters like authorship, highest cited paper, most popular journal, institutions, region-wise publication trend and author-networks. The emerging research themes for future scholars working in this domain have also been highlighted.
Originality/value
This is the first comprehensive study to explore reference price from a bibliometric lens. The study highlights and discusses the recent themes on reference price, from both academic and managerial perspectives.
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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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Mikhail Vialtsev and Mikhail Komarov
This paper aims to explore the potential impact of smart contracts on the sharing economy through the lens of car-sharing company Delimobil. Despite the growing body of literature…
Abstract
Purpose
This paper aims to explore the potential impact of smart contracts on the sharing economy through the lens of car-sharing company Delimobil. Despite the growing body of literature on smart contracts and the sharing economy, there remains a gap in understanding how these two areas intersect and what implications this could have on sustainability. By reviewing existing literature, analyzing real-world applications of smart contracts within sharing economy platforms and creating a model to quantitatively describe the effect, this study seeks to provide insights into this emerging area of research.
Design/methodology/approach
This study uses a mixed-methods approach to investigate the impact of smart contracts on the sharing economy through the lens of car-sharing company Delimobil. Initially, a literature review was conducted to conceptualize the sharing economy and smart contract technologies. The proposed generalized business model of a sharing economy company was analyzed to identify attributes amenable to smart contract implementation. Qualitative analysis assessed the effects of smart contracts on these attributes. Subsequently, a quantitative revenue and costs models for the car-sharing company were developed, comparing profit margins before and after smart contract adoption. The costs of maintaining smart contracts in the Delimobil company were also evaluated for a comprehensive cost–benefit analysis.
Findings
Smart contracts can enhance the efficiency of governance models, mediating interfaces, review systems, revenue streams and pricing mechanisms through automation, security and transparency. This study’s quantitative model, based on Delimobil’s case, shows that smart contracts could increase revenue by 9.7% and reduce costs by 8.13%, while raising IT infrastructure costs from 301m RUB to 484m RUB. Delimobil’s profit could rise from 6,463m RUB to 9,478m RUB. While this demonstrates the potential of smart contracts in car-sharing, the lack of quantitative data and novelty of the technology present challenges for further research.
Research limitations/implications
This study’s limitations include its focus on a single case study (Delimobil) in the car-sharing industry, which may not be applicable to all sharing economy sectors. Additionally, the static assumption of regulatory and technological environments may not account for future changes that could affect the feasibility of smart contracts. The lack of quantitative research in this field also presents challenges for advancing further studies.
Practical implications
For practitioners, this research provides a comprehensive view of the pros and cons of implementing smart contracts in car-sharing, based on a detailed revenue and cost model. This analysis, using Delimobil as a case study, shows that smart contracts can increase revenue by 9.7% and reduce costs by 8.13%, although IT infrastructure costs rise from 301m RUB to 484m RUB. This leads to a potential profit increase from 6,463m RUB to 9,478m RUB. Despite the potential benefits, the lack of quantitative data and the novelty of the technology present challenges for further exploration.
Originality/value
This paper presents an innovative exploration of the intersection between smart contracts and the sharing economy, addressing a significant gap in existing literature. By combining qualitative and quantitative analyses, it offers a comprehensive evaluation of how smart contracts can enhance efficiency, transparency and trust within sharing economy platforms. The study’s mixed-methods approach and detailed cost–benefit analysis of implementing smart contracts in the car-sharing industry provide unique insights and practical recommendations. This research contributes to the growing body of knowledge on blockchain technology’s potential to revolutionize business models in the sharing economy, offering a foundation for future investigations.