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This study addresses the impact of aesthetics and formality in Food Delivery Applications (FDAs) in evoking emotions, and how these influence the intention to reuse and compulsive usage, providing critical insights for designing responsible and effective marketing strategies.

A quantitative analysis of data collected from 1,029 FDA users was employed, using the PAD (Pleasure, Arousal, Dominance) theory to investigate how aesthetic design and formality affect emotions and consumer behaviour towards the applications.

The study reveals that aesthetic appeal and formality significantly impact emotions of dominance, arousal, and pleasure, which are decisive in users' decisions to continue using FDAs and in the manifestation of compulsive usage behaviours.

This study presents inherent limitations due to its cross-sectional design, which prevents offering a longitudinal perspective on the evolution of consumer behaviour regarding FDAs. The actual purchasing behaviour is not examined, but rather the suggested experiences. Future research could be enriched by considering cultural, social, and demographic factors, the influence of sustainability on the perception and use of FDAs, and the importance of specific sustainable practices. Adopting a longitudinal approach and utilising actual usage data would allow for a deeper and more nuanced understanding of consumer behaviour towards FDAs, taking into account both personal factors and functional attributes of FDAs along with their aesthetic appeal and emotional reactions.

The findings provide guidelines for FDA companies to optimise their interfaces to enhance user experience, foster loyalty, and prevent compulsive usage. They emphasise balancing aesthetics and functionality to induce more conscious and sustainable consumption behaviours.

This study highlights significant social implications stemming from the integration of aesthetic appeal and formality in Food Delivery Apps (FDAs) and their effect on consumer emotions, which in turn influences reuse intention and compulsive use. Amidst the COVID-19 pandemic, consumer behaviours have shifted towards increased electronic transactions and hedonic consumption as responses to stress, anxiety, and boredom, leading to a reevaluation of life experiences through technological means. The research underlines the critical role of emotions, particularly pleasure, dominance, and arousal, in promoting the intention to reuse FDAs, which has far-reaching implications for consumer engagement, compulsive usage patterns, and the need for responsible, sustainable consumption practices. It suggests a new avenue for businesses and policymakers to consider emotional impacts and consumer satisfaction in the design and regulation of FDAs, aiming to mitigate potential adverse effects of compulsive usage and to encourage sustainable, responsible consumption behaviours.

The research offers a novel perspective by exploring how aesthetic and emotional dimensions affect consumer loyalty and compulsivity. These areas are still to be examined in depth in the marketing literature. The findings enhance the theoretical and practical understanding of FDA marketing, demonstrating how design can influence consumer well-being and the sustainability of purchasing behaviour.

1. Novel use of PAD theory to analyse FDA’s aesthetic appeal and formality on user emotions.

2. FDA’s aesthetic appeal significantly influences reuse intentions and compulsive usage.

3. Emotions of pleasure, dominance, and arousal are directly linked to FDA reuse intention.

4. Pleasure and reuse intention influence the compulsive use of FDAs.

Novel use of PAD theory to analyse FDA’s aesthetic appeal and formality on user emotions.

FDA’s aesthetic appeal significantly influences reuse intentions and compulsive usage.

Emotions of pleasure, dominance, and arousal are directly linked to FDA reuse intention.

Pleasure and reuse intention influence the compulsive use of FDAs.

This paper aims to enrich the 3D urban models with data contributed by citizens to support data-driven decision-making in urban infrastructure projects. We introduced a new application domain extension to CityGML (social – input ADE) to enable citizens to store, classify and exchange comments generated by citizens regarding infrastructure elements. The main goal of social – input ADE is to add citizens’ feedback as semantic objects to the CityGML model.

Firstly, we identified the key functionalities of the suggested ADE and how to integrate them with existing 3D urban models. Next, we developed a high-level conceptual design outlining the main components and interactions within the social-input ADE. Then we proposed a package diagram for the social – input ADE to illustrate the organization of model elements and their dependencies. We also provide a detailed discussion of the functionality of different modules in the social-input ADE.

As a result of this research, it has seen that informative streams of information are generated via mining the stored data. The proposed ADE links the information of the built environment to the knowledge of end-users and enables an endless number of socially driven innovative solutions.

This work aims to provide a digital platform for aggregating, organizing and filtering the distributed end-users’ inputs and integrating them within the city’s digital twins to enhance city models. To create a data standard for integrating attributes of city physical elements and end-users’ social information and inputs in the same digital ecosystem, the open data model CityGML has been used.

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.

With the advancement of technology, microlearning has emerged as a promising method to improve the efficacy of teaching and learning. This study aims to investigate the document types, volume, growth trajectory, geographic contribution, coauthor relationships, prominent authors, research groups, influential documents and publication outlets in the microlearning literature.

We adapt the PRISMA guidelines to assess the eligibility of 297 Scopus-indexed documents from 2002 to 2021. Each was manually labeled by educational level. Descriptive statistics and science mapping were conducted to highlight relevant objects and their patterns in the knowledge base.

This study confirms the increasing trend of microlearning publications over the last two decades, with conference papers dominating the microlearning literature (178 documents, 59.86%). Despite global contributions, a concentrated effort from scholars in 15 countries (22.39%) yielded 68.8% of all documents, while the remaining papers were dispersed across 52 other nations (77.61%). Another significant finding is that most documents pertain to three educational level categories: lifelong learning, higher education and all educational levels. In addition, this research highlights six key themes in the microlearning domain, encompassing (1) Design and evaluation of mobile learning, (2) Microlearning adaptation in MOOCs, (3) Language teaching and learning, (4) Workflow of a microlearning system, (5) Microlearning content design, (6) Health competence and health behaviors. Other aspects analyzed in this study include the most prominent authors, research groups, documents and references.

The finding represents all topics at various educational levels to offer a comprehensive view of the knowledge base.

The purpose of this study was to analyze importance of artificial intelligence (AI) in education and its emphasis on assessment and adversity quotient (AQ).

The study utilizes a systematic literature review of over 141 journal papers and psychometric tests to evaluate AQ. Thematic analysis of quantitative and qualitative studies explores domains of AI in education.

Results suggest that assessing the AQ of students with the help of AI techniques is necessary. Education is a vital tool to develop and improve natural intelligence, and this survey presents the discourse use of AI techniques and behavioral strategies in the education sector of the recent era. The study proposes a conceptual framework of AQ with the help of assessment style for higher education undergraduates.

Research on AQ evaluation in the Indian context is still emerging, presenting a potential avenue for future research. Investigating the relationship between AQ and academic performance among Indian students is a crucial area of research. This can provide insights into the role of AQ in academic motivation, persistence and success in different academic disciplines and levels of education. AQ evaluation offers valuable insights into how individuals deal with and overcome challenges. The findings of this study have implications for higher education institutions to prepare for future challenges and better equip students with necessary skills for success. The papers reviewed related to AI for education opens research opportunities in the field of psychometrics, educational assessment and the evaluation of AQ.

Social commerce (s-commerce) has gained widespread popularity as a social platform where customers engage in resource-sharing activities such as information exchange, advice-seeking and expressing their opinions on mutual interests. However, existing studies have not fully comprehended the drivers of electronic customer-to-customer interaction (eCCI) and how such behavior contributes to the customer “stick” on s-commerce sites. This study develops the Motivation–Opportunity–Ability (MOA) theory and investigates the impact of MOA factors on eCCI, which in turn affects customer stickiness.

A survey was used to acquire data from 455 valid respondents, and the research employed a combination of fuzzy-set qualitative comparative analysis (fsQCA) and structural equation modeling.

The results revealed associations between perceived self-efficacy, intrinsic motivation, tie strength with other customers, eCCI and customer stickiness.

Considering the limited availability of complete eCCI frameworks in existing scholarly works, the authors present valuable perspectives on the role of consumer characteristics as both antecedents and consequences of eCCI. Additionally, this study proposes a research agenda for the field of eCCI on s-commerce sites.

Businesses are increasingly vulnerable and exposed to physical climate change risks, which can cascade through local, national and international supply chains. Currently, few methodologies can capture how physical risks impact businesses via the supply chains, yet outside the business literature, methodologies such as sustainability assessments can assess cascading impacts.

Adopting a scoping review framework by Arksey and O'Malley (2005) and the PRISMA extension for scoping reviews (PRISMA-ScR), this paper reviews 27 articles that assess climate risk in supply chains.

The literature on supply chain risks of climate change using quantitative techniques is limited. Our review confirms that no research adopts sustainability assessment methods to assess climate risk at a business-level.

Alongside the need to quantify physical risks to businesses is the growing awareness that climate change impacts traverse global supply chains. We review the state of the literature on methodological approaches and identify the opportunities for researchers to use sustainability assessment methods to assess climate risk in the supply chains of an individual business.

The impact of technological transformations in all sectors is undeniably significant, especially in fitness family business. The aim is to examine the digital transformation perceptions of fitness centre employees and the effects of perceived empowerment on their job performance in family business in Turkey.

The sample was 334 fitness centre employees. Four variables were evaluated (digital transformation, meaning competence, self-determination and job performance), and PLS-SEM was used.

The digital transformation process in the fitness sector can be considered as an important factor in terms of creating new business ventures. Our results showed that digital transformation perceived by family business employees had a significantly influence on the meaning competence of the employees. Also, the meaning competence of employees was a mediator between the digital transformation and job performance.

Managers of family businesses must take into account that an appropriate digital transformation of their products and/or services has an impact on the meaning competence of their employees. Thus, through increased competence in employee performance, the digitization of family business fitness will lead to higher employee performance and productivity.

This study innovates by linking digital transformation as a factor influencing the coach's own motivation and self-perceived competence in the use of technology to their job performance.

The new customer churn prediction (CCP) utilizing deep learning is developed in this work. Initially, the data are collected from the WSDM-KKBox’s churn prediction challenge dataset. Here, the time-varying data and the static data are aggregated, and then the statistic features and deep features with the aid of statistical measures and “Visual Geometry Group 16 (VGG16)”, accordingly, and the features are considered as feature 1 and feature 2. Further, both features are forwarded to the weighted feature fusion phase, where the modified exploration of driving training-based optimization (ME-DTBO) is used for attaining the fused features. It is then given to the optimized and ensemble-based dilated deep learning (OEDDL) model, which is “Temporal Context Networks (DTCN), Recurrent Neural Networks (RNN), and Long-Short Term Memory (LSTM)”, where the optimization is performed with the aid of ME-DTBO model. Finally, the predicted outcomes are attained and assimilated over other classical models.

The features are forwarded to the weighted feature fusion phase, where the ME-DTBO is used for attaining the fused features. It is then given to the OEDDL model, which is “DTCN, RNN, and LSTM”, where the optimization is performed with the aid of the ME-DTBO model.

The accuracy of the implemented CCP system was raised by 54.5% of RNN, 56.3% of deep neural network (DNN), 58.1% of LSTM and 60% of RNN + DTCN + LSTM correspondingly when the learning percentage is 55.

The proposed CCP framework using the proposed ME-DTBO and OEDDL is accurate and enhances the prediction performance.

Internships are widely used as one of the best learning tools for professional practice. The purpose of this research paper is to comprehend to what extent the LIS interns become competent with practical tasks through this program, current facilities offered by the internship-offering institutions and their plan in this regard.

This study used a mixed-method approach. To examine LIS students’ practical experience, this study conducted a survey. Participants were 110 students having internship experience from the LIS bachelor’s degree offering universities of Bangladesh. For qualitative data, representatives of internship-offering institutions were interviewed.

Results indicate that there is a certain lack of coordination between theoretical knowledge with practical demonstrations. Some essential ICT-based tasks missed out from this program like library automation software (e.g. KOHA); online-based cataloging such as Machine Readable Cataloguing, Resource Description and Access; digital library software (Greenstone); Institutional Repository software (Dspace, EPrint, etc.); virtual library services; radio frequency identification, etc. which should be taken into consideration in internship modules. Including faculty members and practitioners is suggested for a model internship framework ensuring ever-advanced LIS education. There is no significant difference between interns’ gender with their satisfaction level.

The major limitation of this study is the absence of coverage of faculty perceptions regarding Internships. As in the higher education institution, the three stakeholder groups’ subsets, namely, faculty members, practitioners and students are parallelly important to take any initiative.

The input from interns will assist the industries in redesigning their modules in light of interns’ feedback to best prepare interns for the competitive job market.

Internship in LIS education is not a new research area; however, research attempts to show students’ experience along with organizations’ preparedness in offering internships is new in nature.