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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.

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.

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.

Although the impostor phenomenon is attributed to childhood experiences, theory on achievement motivation indicates that achievement-related fears can also be elicited by the context. Using achievement goal theory as a base, the authors investigate the effect of context-dependent predictors, job-fit, career stage and organisational tenure, on impostor fears. The authors also examined gender and the achievement-related traits, self-efficacy and locus of control, as predictors of impostor fears to advance knowledge on antecedents to impostor fears.

Two studies were conducted with 270 and 280 participants, each. In Study 1, a subset of 12 respondents participated in follow-up interviews.

Impostor fears tended to be predicted by organisational tenure and career stage in both studies and job-fit in Study 1. Self-efficacy and locus of control predicted impostor fears. Men and women reported similar levels of impostor fears.

The authors demonstrate the importance of context in eliciting impostor fears and partially support initial descriptions of antecedents to impostor fears. The findings contribute to the development of targeted managerial practices that can help with the development of interventions, such as orientation programmes, that will enhance socialisation processes and mitigate impostor fears.

The literature on imposter fears has not addressed their situational predictors, which the authors argue are important elements in the genesis and maintenance of impostor fears. The authors draw on achievement goal theory to explain the pattern of findings related to key situational characteristics and their influence on imposter fears. The findings for Sri Lanka, on personality predictors, are similar to those reported in studies focused on North America providing evidence of cross-cultural applicability of the concept.

The study aimed to understand the significance of how employee personhood and the act of speaking up is shaped by factors such as employees' professional status, length of employment within their hospital sites, age, gender and their ongoing exposure to unprofessional behaviours.

Responses to a survey by 4,851 staff across seven sites within a hospital network in Australia were analysed to interrogate whether speaking up by hospital employees is influenced by employees' symbolic capital and situated subjecthood (SS). The authors utilised a Bourdieusian lens to interrogate the relationship between the symbolic capital afforded to employees as a function of their professional, personal and psycho-social resources and their self-reported capacity to speak up.

The findings indicate that employee speaking up behaviours appear to be influenced profoundly by whether they feel empowered or disempowered by ongoing and pre-existing personal and interpersonal factors such as their functional roles, work-based peer and supervisory support and ongoing exposure to discriminatory behaviours.

The findings from this interdisciplinary study provide empirical insights around why culture change interventions within healthcare organisations may be successful in certain contexts for certain staff groups and fail within others.

This study investigated the crossover of work–family conflict (WFC) from supervisors to subordinates employed in conventional work settings. The authors hypothesized that the supervisor’s WFC would impact the subordinate’s level of WFC, and the level of crossover would vary with relationship quality or LMX.

The authors surveyed a matched set of 150 supervisors and 193 subordinates from several services organizations who were recruited using a snowballing technique. Data were analysed using hierarchical regression analyses and moderation testing.

Results confirmed a significant direct crossover path. Further, the crossover was found to be lowered in the event of higher LMX quality.

The findings provide significant insights into the conditions under which transmission of WFC takes place by broadening crossover research in the work–family area. Future studies must explore the crossover of work–family enrichment and the role of leadership styles, empathy and perspective taking of subordinates in the crossover.

Supervisors must endeavour to reduce the level of WFC of subordinates by trying to build high-quality LMX by regularly interacting with them and by providing them a supportive climate. Employees in turn must support supervisors in various means, which will help them gaining manager’s trust and support.

Examination of the potential mitigating effect of high-quality LMX in the crossover of WFC in supervisor–subordinate dyads has rarely been investigated in the past.