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The purpose of this paper is to validate the theoretical finding that digital MNEs avoid physical presence norms of permanent establishment and royalty characterization rules for business and royalty taxation, respectively, to escape tax incidence in the market economy, using information, communication and technology features and transfer pricing (TP) manipulations.

Multiple case studies of MNEs from technology sector, based on judicial decisions in 141 cases, over taxability of profits earned from Indian economic activities. Additional in-depth case study of the Uber Group to study the tax avoidance structures under platform economy, by routing of Indian profits through The Netherlands, a tax haven.

The study finds a significant number of digital MNEs earning profits from India and avoiding tax by defying physical presence and royalty characterization. In majority of the cases, demand-side business activities are discharged through incorporating and remunerating affiliates at cost plus low markup, thus avoiding tax incidence, using TP manipulations under the arm’s length principle applied by governments for benchmarking the intragroup transactions of the MNEs.

The research findings validate the view that digital features promote tax avoidance in the market economy.

The originality of the study lies in the validation of profit shifting through digital features from the developing market economy and portending that digital MNEs defy physical presence to avoid business taxation through TP manipulations.

An undergraduate civil engineering programme is assessed for its relevance to the building construction sector. Its contrast from the existing curriculum structure is also highlighted.

The curriculum is clustered into 15 groups based on disciplines. A pairwise comparison of groups is conducted by experts from the building construction sector. Expert judgements are analysed using Fuzzy Analytical Hierarchy Process (Fuzzy AHP) to determine the groups' order based on their importance in preparing students for a career in the building construction sector.

Concrete Technology, Structural Design and Analysis, and Building Technology and Town Planning emerged as the three most essential course groups, followed by Construction and Project Management, Surveying, and Geotechnical and Allied. Foundational Science and Math, Hydrology/Water Resource Engineering, and Computing and Programming came last in the order.

Relying on a curriculum from a specific region, generalizability to other geographical areas is limited. The perspective of building construction sector professionals excludes the views of other stakeholder groups within the sector.

The study allows universities in general to enhance students' job prospects in construction by calibrating course group priorities and aligning skills with industry needs, thereby potentially improving employability, and boosting the industry-academia relationship.

Fuzzy AHP has been utilized by building construction industry experts to assess the relevance of an undergraduate civil engineering curriculum. Findings serve as a valuable reference for implementing positive curriculum changes to potentially enhance student employability.

This paper aims to present a literature review on the emerging field of employee moonlighting, which refers to holding more than one job at a time. It also attempts to integrate the literature on employee moonlighting and present the related research themes.

This is a systematic literature review (SLR) using the basic guidelines of SLR. A search string is designed, and the prominent database is searched. The results are screened based on self-designed inclusion and exclusion criteria. The qualitative analysis of selected 89 research studies uses inductive thematic analysis and proposes a framework.

The outcome of the present study consists of a conceptual framework, themes and sub-themes related to employee moonlighting, propositions, and the pictorial representation of the overall outcome. The four key themes that emerged are determinants and traits of moonlighting intentions, the impact of moonlighting on employer and employee, policy, and economic implications, respectively.

The study provides insight into the factors that lead to moonlighting intentions and activity. The managers can understand and analyze these factors and can formulate policies to streamline the moonlighting activity with the organizational goals and for the company’s benefit. Academic scholars can adopt some research ideas from the themes and gaps suggested and can work on them in the near future.

The study aims to enhance the detection and classification of conjunctival eye diseases' severity through the development of ConjunctiveNet, an innovative deep learning framework. This model incorporates advanced preprocessing techniques and utilizes a modified Otsu’s method for improved image segmentation, aiming to improve diagnostic accuracy and efficiency in healthcare settings.

ConjunctiveNet employs a convolutional neural network (CNN) enhanced through transfer learning. The methodology integrates rescaling, normalization, Gaussian blur filtering and contrast-limited adaptive histogram equalization (CLAHE) for preprocessing. The segmentation employs a novel modified Otsu’s method. The framework’s effectiveness is compared against five pretrained CNN architectures including AlexNet, ResNet-50, ResNet-152, VGG-19 and DenseNet-201.

The study finds that ConjunctiveNet significantly outperforms existing models in accuracy for detecting various severity stages of conjunctival eye conditions. The model demonstrated superior performance in classifying four distinct severity stages – initial, moderate, high, severe and a healthy stage – offering a reliable tool for enhancing screening and diagnosis processes in ophthalmology.

ConjunctiveNet represents a significant advancement in the automated diagnosis of eye diseases, particularly conjunctivitis. Its originality lies in the integration of modified Otsu’s method for segmentation and its comprehensive preprocessing approach, which collectively enhance its diagnostic capabilities. This framework offers substantial value to the field by improving the accuracy and efficiency of conjunctival disease severity classification, thus aiding in better healthcare delivery.

The present study uses a meta-analysis technique to explore the association between corporate governance and dividend policy. The extant literature delivers inconclusive findings on the relationship between corporate governance and dividend policy. Therefore, this study aims to resolve the issues and deliver comprehensive results.

The study involves a meta-analysis of 53 research studies using preferred reporting items for systematic reviews and meta-analyses and population, intervention, comparison, outcome and study design approaches. The paper examines the impact of moderators: corporate governance structure (Anglo-American, communitarian or emerging system) and dividend distribution metrics (dividend over net income, dividend over total assets and absolute amount of dividend/dividend per share). The study involves subgroup analysis and meta-regression analysis to examine the impact of moderators.

The study’s results specify that board size and percentage of female directors significantly impact the dividend decisions of the company. In addition, subgroup analysis and meta-regression results demonstrate that dividend measurement proxy moderates the association between corporate governance and dividend policy.

Based on the existing literature surveyed, to the best of the authors’ knowledge, the current study is the first to conduct a meta-analysis on the relationship between corporate governance and dividend policy. This paper is unique and the first one of its kind (to the best of the authors’ knowledge) to cover all these moderating variables under an umbrella and consolidate the results to understand the existing knowledge and direct future research in the area of corporate governance and dividend decisions.

This study explores the intricate relationship between social media communication, consumer attitude and purchase intention within the context of lifestyle category products. With the rapid proliferation of social media platforms, businesses have turned to these platforms to connect with consumers and influence their purchasing decisions. This study aims to provide an in-depth analysis of how social media communication strategies impact consumer attitudes and, in turn, influence purchase intentions.

The study employs partial least squares structural equation modeling (PLS-SEM) to analyze the data collected from a sample of consumers.

The results of this study present that lack of visibility (LV), low-efficiency levels (LEL) and unpredictable elements (UE) are ranked as the top three major risk hurdles whereas real-time information on a package’s location (LV1), putting a GPS tracking system to track last-mile journey (OT3) and users wants on time location of their package (LV2) are ranked as top three most significant criteria affecting the practices of modern last-mile logistics in e-commerce businesses.

The results of this study contribute to our understanding of how social media influences consumer behavior in the lifestyle product sector, shedding light on the underlying mechanisms that drive consumer purchasing decisions.

By constructing and testing experimentally a research model that reveals a thorough analysis of pertinent literature and identifies multiple important elements influencing consumer behavior in the lifestyle category, this paper adds to the body of knowledge on marketing. Practical ramifications for lifestyle firms are examined, along with suggestions for improving their social media tactics, in light of the findings.

The present study undertakes an extensive review of the causes of service failures in artificial intelligence (AI) technology literature.

A hybrid review has been employed which includes descriptive analysis, and bibliometric analysis with content analysis of the literature approach to synthesizing existing research on a certain topic. The study has followed the SPAR-4-SLR protocol as outlined by Paul et al. (2021). The search period encompasses the progression of service failure in AI from 2001 to 2023.

From identified theories, theoretical implications are derived, and thematic maps direct future research on topics such as data mining, smart factories, and among others. The key themes are being proposed incorporates technological elements, ethical deliberations, and cooperative endeavours.

This research study makes a valuable contribution to understanding and reducing service defects in AI by providing insights that can inform future investigations and practical implementations. Six key future research directions are derived from the thematic and cluster discussions presented in the content analysis.

This study aims to explore the career transition process of women professionals when they return to the workplace after a break and re-integrate with their career aspirations.

This research used a qualitative approach with semi-structured interviews for data collection. All 20 women participants have returned to their careers after a break.

The data analysis reveals women’s career transition and re-integration process into the workplace after a career break. Supervisory support, work–life balance practices, role models, coworker support and career success emerged as factors enabling successful transition. The employing organisations’ diversity, equity and inclusion (DEI) hiring strategy emerged as an important mechanism for re-entry.

Although previous research has studied women professionals returning after a break, the “transition process” that enables re-entry is missing.

This study aims to explore the drivers (i.e. service innovation, service exchange, customer wellbeing and employee wellbeing) and organizational culture in the service ecosystem in the hospitality sector.

This study adopted a quantitative approach by collecting data from employees and customers of the top 10 hotels (identified from three major websites, i.e. Goibibo, Trivago and MakeMyTrip) functional in Jammu city, North India. Exploratory factor analysis, confirmatory factor analysis and partial least square analysis are used to analyse the data.

The study findings reveal that among the four drivers (i.e., service innovation, service exchange, employee wellbeing and customer wellbeing) customer wellbeing shows a strong impact and significant impact on the service ecosystem. Following this, the study also exhibits that organizational culture significantly moderates the relationship between service innovation and the service ecosystem. However, it does not show any moderating influence among the other drivers of the service ecosystem.

This study is conducted only in the top 10 hotels (three and four stars) of Jammu city, North India, which might not represent all Indian hotels.

The study contributes by establishing the role of four service ecosystem drivers, namely service innovation, service exchange, employee wellbeing and customer wellbeing. Following this, the study empirically tested and validated the service ecosystem framework in the context of north Indian hotels. The study also establishes the significant role of organizational culture, particularly group culture and hierarchy culture, in strengthening the service ecosystem.

The purpose of this study is to understand why Gen Z indulges in moonlighting in IT organisations and to help policymakers redefine mutually beneficial policies for improving talent management, which will benefit Gen Z as well as organisations and society at large.

A qualitative technique was adopted by conducting in-depth interviews with Gen Z, who works in the IT sector of metropolitan cities in India. The interviews were transcribed and thematically coded using thematic analysis in NVivo. A model based on themes from the analysis has been proposed.

The themes derived from this study revolve around issues such as ethics, legal, self-satisfaction, money and social causes. These themes will contribute to the body of knowledge by adding new dimensions to moonlighting.

This research has been carried out consider Gen Z moonlighting in the IT sector within India. The study can be further enhanced to other regions and sectors. It will give clarity and help avoid potential conflict situations at the workplace.

This research will clarify and help avoid conflict situations by redefining policies and improving talent management and retention. The results can be further tested in other organisations.

This research draws attention of the policymakers to help create a common framework and guidelines for all stakeholders to follow with respect to moonlighting. It will open work opportunities on other platforms for interested and talented workforce and help them gain financial strength and independence.

Systematic thematic analysis using CAQDAS – NVivo has been carried out to elucidate Gen Z’s numerous motives for moonlighting in the IT sector. A model has been proposed based on the themes that evolved from the study, which policymakers can leverage to improve talent management in IT organisations.