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Reverse logistics services are designed to move goods from their point of consumption to an endpoint to capture value or properly dispose of products and materials. Artificial intelligence (AI)-based reverse logistics will help Micro, Small, and medium Enterprises (MSMEs) adequately recycle and reuse the materials in the firms. This research aims to measure the adoption of AI-based reverse logistics to improve circular economy (CE) performance.

In this study, we proposed ten hypotheses using the theory of natural resource-based view and technology, organizational and environmental framework. Data are collected from 363 Indian MSMEs as they are the backbone of the Indian economy, and there is a need for digital transformation in MSMEs. A structural equation modeling approach is applied to analyze and test the hypothesis.

Nine of the ten proposed hypotheses were accepted, and one was rejected. The results revealed that the relative advantage (RA), trust (TR), top management support (TMS), environmental regulations, industry dynamism (ID), compatibility, technology readiness and government support (GS) positively relate to AI-based reverse logistics adoption. AI-based reverse logistics indicated a positive relationship with CE performance. For mediation analysis, the results revealed that RA, TR, TMS and technological readiness are complementary mediation. Still, GS, ID, organizational flexibility, environmental uncertainty and technical capability have no mediation.

The study contributed to the CE performance and AI-based reverse logistics literature. The study will help managers understand the importance of AI-based reverse logistics for improving the performance of the CE in MSMEs. This study will help firms reduce their carbon footprint and achieve sustainable development goals.

Few studies focused on CE performance, but none measured the adoption of AI-based reverse logistics to enhance MSMEs’ CE performance.

Agriculture is the backbone of a country, contributing more than half of the sector of economy throughout the world. The need for precision agriculture is essential in evaluating the conditions of the crops with the aim of determining the proper selection of pesticides. The conventional method of pest detection fails to be stable and provides limited accuracy in the prediction. This paper aims to propose an automatic pest detection module for the accurate detection of pests using the hybrid optimization controlled deep learning model.

The paper proposes an advanced pest detection strategy based on deep learning strategy through wireless sensor network (WSN) in the agricultural fields. Initially, the WSN consisting of number of nodes and a sink are clustered as number of clusters. Each cluster comprises a cluster head (CH) and a number of nodes, where the CH involves in the transfer of data to the sink node of the WSN and the CH is selected using the fractional ant bee colony optimization (FABC) algorithm. The routing process is executed using the protruder optimization algorithm that helps in the transfer of image data to the sink node through the optimal CH. The sink node acts as the data aggregator and the collection of image data thus obtained acts as the input database to be processed to find the type of pest in the agricultural field. The image data is pre-processed to remove the artifacts present in the image and the pre-processed image is then subjected to feature extraction process, through which the significant local directional pattern, local binary pattern, local optimal-oriented pattern (LOOP) and local ternary pattern (LTP) features are extracted. The extracted features are then fed to the deep-convolutional neural network (CNN) in such a way to detect the type of pests in the agricultural field. The weights of the deep-CNN are tuned optimally using the proposed MFGHO optimization algorithm that is developed with the combined characteristics of navigating search agents and the swarming search agents.

The analysis using insect identification from habitus image Database based on the performance metrics, such as accuracy, specificity and sensitivity, reveals the effectiveness of the proposed MFGHO-based deep-CNN in detecting the pests in crops. The analysis proves that the proposed classifier using the FABC+protruder optimization-based data aggregation strategy obtains an accuracy of 94.3482%, sensitivity of 93.3247% and the specificity of 94.5263%, which is high as compared to the existing methods.

The proposed MFGHO optimization-based deep-CNN is used for the detection of pest in the crop fields to ensure the better selection of proper cost-effective pesticides for the crop fields in such a way to increase the production. The proposed MFGHO algorithm is developed with the integrated characteristic features of navigating search agents and the swarming search agents in such a way to facilitate the optimal tuning of the hyperparameters in the deep-CNN classifier for the detection of pests in the crop fields.

This study aims to identify the key drivers of consumer engagement in e-commerce among young consumers at bottom-of-pyramid (BoP) markets and their impact on continued usage intention.

A cross-sectional research design was used to understand low-income customers’ engagement in e-commerce, specifically online shopping. The data for this study were collected from BoP customers in the Indian market. A conceptual model was proposed, and hypotheses were developed using the stimulus–organism–response (S-O-R) framework. For analysis, structural equation modeling was performed using AMOS 20.0 software to test the structural model.

The results of the study highlight that perceived importance, technology and infrastructure and social influence are key drivers of e-commerce at BoP customers. Key drivers have shown a significant positive impact on customer engagement which leads to continue usage intention of e-commerce. Furthermore, customer engagement has shown a strong relationship with continue usage intention of e-commerce.

This study indicates that young consumers’ engagement is important for e-commerce service providers to gain a market share. BoP markets offer immense opportunities to create, develop and sustain e-commerce firms for a long time, especially in India. Managers should recognize the potential of BoP markets, which can generate a huge demand for products and services on e-commerce platforms.

This study contributes both theoretically and empirically. Theoretically, this adds to the existing knowledge of customer engagement, especially in e-commerce and BoP market segment. Empirically, it tested the conceptual research model of low-income customer engagement in the e-commerce marketplace using the S-O-R framework. The study recommended practical implications for e-retailers/e-commerce service providers engaging BoP customers in a digitally connected and intensively competitive era.

The purpose of this paper is to conduct a structured literature review using advanced bibliometric tools to understand the existing knowledge base, understand the trends in omni-channel (OC) research and identify emerging research topics.

More than 500 articles selected through a keyword combination search from reputed databases of peer-reviewed academic sources from period 2009–19 are analyzed for the purposes of this study. The study first presents an exploratory analysis to determine influential authors, sources and regions, among other key aspects. Second, several network analyses including co-citation and dynamic co-citation network analyses are conducted to identify themes. These allow identifying research clusters and emerging research topics algorithmically. Both centrality and modularity-based clustering are employed. A content analysis of the most influential groups within OC literature for each cluster is included.

The findings of this paper make unique contributions by using advanced tools from network analysis along with the standard bibliometric analysis tools to explore the current status of OC research, identify existing themes and the guidance for potential areas of future research interest in OC.

This research provides a comprehensive view of the range of topics of importance that have been discussed in the literature of OC management. These research trends can serve as a quick guide to researchers and practitioners to improve decision making and also develop strategies.

The paper employs advanced tools for the first time to review the literature of OC retailing. The sophisticated tools include co-citation and dynamic co-citation network analysis.

This study seeks to investigate the ability of blockchain technology (BCT) to increase circular economy (CE) practices in the electronics industry, emphasising India and Taiwan.

The study adopts a mixed-methods approach. Initial qualitative semi-structured interviews examined how BCT could inform CE practice. The qualitative aspects were followed by the Analytical Hierarchy Process (AHP), integrating qualitative and quantitative approaches, and fuzzy-set Qualitative Comparative Analysis (fsQCA), to analyse data from 391 industry experts surveyed.

The results show that the BCT has great potential to promote CE processes by improving the aspects of security, transparency and traceability. BCT adoption is driven by a conducive regulatory regime, stakeholder collaboration, and the availability of required technology.

By identifying key drivers and requisite requirements for successful BCT adoption in CE practices, this research offers critical guidance for policymakers, practitioners and researchers. It adds to the wider conversation about how emerging technologies can support sustainability and efficiency in industry.

This study contributes to the literature by providing a new lens to study BCT and CE practices intersectionality, particularly in the context of the emerging electronics industry and in countries such as India and Taiwan. Unlike previous research that studied either BCT or CE independently, this study uniquely illustrates how the principles underpinning these concepts, when implemented together, can positively impact sustainability outcomes within a resource-intensive industry notorious for generating highly significant waste streams.

This study examines the impact of buyer pressure and competition pressure on supplier manufacturing automation (MA) implementation and the influence of supplier MA implementation on workforce upskilling. This study also investigates the moderating role of top management support on the association between buyer pressure-supplier MA implementation, competition pressure-supplier MA implementation and supplier MA implementation workforce upskilling.

Grounded in stakeholder theory and a resource-based view, this study uses structural equation modeling and hierarchical regression analysis to test the hypotheses. A close-ended questionnaire was used to collect data from 201 readymade garment firms in Bangladesh.

Results indicate that buyer and competition pressure influence supplier MA implementation. Supplier MA implementation provides opportunities to enhance workforce skill levels. Additionally, firms with top management support deal better with buyers and competition pressures on MA implementation. However, top management support does not boost workforce skill levels as influenced by MA implementation.

To the authors’ knowledge, ours is the first investigation linking buyer pressure and competition pressures to supplier MA implementation. Supplier MA implementation influencing workforce upskilling is also a novel aspect of this investigation. This study found a moderating effect of top management support on the association between buyer pressure-supplier MA implementation and competition pressure-supplier MA implementation. Moreover, stakeholder theory has been extended by including competitors and top management as crucial stakeholders. This study also contributed to the resource-based view by categorizing MA implementation as a capability and workforce upskilling as a resource.

The Internet has changed the nature of purchasing, proof of this being the proliferation of e-commerce sites which have seen their activity grow more quickly due to the COVID-19 pandemic. Therefore, the authors aim to investigate the impact of the consumer's hedonic motivations, price, access to information and trust on the online purchase intention.

A quantitative, transversal study of a conclusive nature was carried out. Based on information gathered through a questionnaire administered to a sample of 750 online purchasers, a structural equation model was estimated.

The results showed that the intention to continue purchasing in online shops is partly explained by access to information online, hedonic motivations and trust in e-commerce sites. It stands out that online information generates trust, and the perception of online prices does not influence loyalty but has a positive influence on hedonic motivations.

Although some constructs were ignored, for example, the integration of channels, experiential marketing and the fear of fraud, including unauthorised use of personal details, the study shows that easy access to useful information about products, prices, promotions is an important antecedent of online purchase.

Online shop managers should pay special attention to e-commerce websites, and the information provided there should explore consumer's hedonic motivations for adventure. Furthermore, it is fundamental to create trust in order to maintain the interest in online shopping.

The estimation of the structural model in the context of online shopping includes the influence of utilitarian motivations (price and access to information), which offer a rational experience and also include emotional motivations (hedonic adventure motivations) on the intention to buy online. The results also revealed that it plays an important role to promote online trust and online loyalty.

The purpose of this study is to analyze the existing literature on the application of the Internet of Things (IoT) and to give an overview of how libraries are adopting this emerging technology to make users feel more engaging with the library resources and service provision.

The basic architecture of IoT with its functionality has been enumerated and its different layers have been depicted.

A conceptual library IoT model, working on Message Queuing Telemetry Transport protocol, based on the fog-cloud computing layer of architecture has been proposed. This study also highlights the sensor-based current library services.

This study focuses on the existing practices of adoption of library IoT and discusses the possibilities of its future expansion in different areas.

This research paper examines the transformative impact of technological integration on the governance of tourist destinations, focusing particularly on the smart destination governance paradigm. It researches into the specific context of India’s adoption of smart tourism technologies, addressing the significant challenges posed by cybersecurity concerns. The study aims to explore how technological integration, innovation, accessibility and the use of social media collectively influence the governance mechanisms of smart destinations, contributing to their sustainability, efficiency and attractiveness to tourists.

The study employed purposive sampling to collect data from tourists visiting key attractions across India, including Hampi, Mysore Palace, Coorg, Udupi, Jog Falls, Gokarna, Badami Caves, Bandipur National Park and Dandeli. To overcome initial hesitations from participants, targeted questionnaires were administered to 50 tourists at each location, total of 450 participants. The collected data were then analysed using statistical software packages SPSS and AMOS to examine the relationships between technological integration, innovation, accessibility, social media and smart destination governance.

The empirical analysis revealed significant and positive relationships between the factors studied and smart destination governance. Specifically, technology (b = 0.538, t = 13.284, p-value = 0.012), innovation (b = 0.713, t = 12.467, p-value = 0.003), accessibility (b = 0.549, t = 9.284, p-value = 0.000) and social media (b = 0.683, t = 10.284, p-value = 0.015) were found to significantly contribute to the governance of smart destinations. Collectively, these factors account for 52.7% of the variance in smart destination governance, indicating a substantial impact on the management and operational aspects of tourist destinations.

The study introduces a Smart Destination Governance Framework emphasizing collaborative structures, user-driven services, social innovation and local community involvement. This framework outlines the importance of stakeholder dynamics, accessibility, social innovation and strategic social media use. While the framework provides valuable theoretical insights and strategies for adapting to various disturbances, the research is limited by its focus on specific tourist destinations in India, which may affect the generalizability of the findings to other contexts. Further research is encouraged to validate the framework in different geographical and cultural settings.

The findings offer actionable strategies for tourism stakeholders aiming to enhance smart destination governance. These include the strategic adoption of technology, addressing cybersecurity issues, integrating technology with sustainability, involving local communities, improving accessibility, leveraging social media for marketing, implementing resilience in smart destinations and prioritizing continuous visitor experience improvement. The study underscores the critical role of stakeholder engagement and social innovation in achieving improved accessibility measures and overall destination attractiveness.

The study emphasizes the role of technological integration, innovation, accessibility and social media in smart destination governance, aiming to improve tourist experiences, promote inclusivity and foster community involvement. It also highlights the need to balance modernization with cultural preservation.

This research contributes to the academic discourse on smart destination governance by providing empirical evidence of the significant impact of technological integration, innovation, accessibility and social media. It offers a novel Smart Destination Governance Framework that highlights the importance of collaborative efforts, social innovation and stakeholder engagement in enhancing the governance of tourist destinations. The study’s findings and proposed strategies provide valuable insights for policymakers, destination managers and tourism practitioners seeking to navigate the complexities of smart destination governance in the digital era.

The purpose of this paper is to study the applicability of a crossover model of work–family conflict (WFC) in the work setting among supervisor–subordinate dyads. It examines the positive association between supervisor’s WFC and subordinate’s WFC and analyses the moderating effect of subordinate’s susceptibility to emotional contagion (SEC).

Data were gathered using a questionnaire survey method and tested in 193 matched supervisor–subordinate dyads from select organisations representing the services sector in India.

The authors found a significant direct crossover path from the supervisor to his/her subordinate’s WFC. The effect of supervisor reported WFC on subordinate reported WFC was found to be strong when the subordinate displayed higher SEC with his/her supervisor.

Examining the crossover of WFC contributes to theory by broadening crossover research to include transmission of negative experiences in the work context. This study significantly adds to emotional contagion theory by substantiating the existence of WFC contagion in supervisor–subordinate dyads. Given the constraints of cross-sectional research design, future research should replicate these findings using a larger sample in other cultural contexts as well to generalise the results. Future research should consider using longitudinal data and including information from both the supervisor and the subordinates collected at different points in time. Crossover of positive work–family experiences (e.g. work–family enrichment) and the role of other individual difference variables such as the personality of the subordinates, empathy, etc., could also be considered.

Supervisors should be advised of the potential adverse effects of their WFC and organisations should be made cognizance of the impact that the WFC of employees can have on their job outcomes. Organisations should provide the required formal and informal support to their employees to deal with their WFC efficiently.

This study has attempted to examine the crossover of WFC in supervisor–subordinate dyads and the potential effect of one of the individual difference variables namely SEC. To the best of the authors knowledge, it has rarely been examined earlier.