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This study aims to explore how information technology (IT) professionals perceive work-life balance (WLB) in a work-from-home (WFH) setup. Additionally, it explores what emotions one may associate with such changing work environments, which have high implications for organisational success.

The two primary research questions guided this research. An online questionnaire-based survey was conducted to collect the data so that respondents’ both subjective and objective perceptions were documented. Purposive cum snowball sampling was used to collect data from 262 IT professionals. However, the data was analysed using both qualitative (content analysis) and quantitative (chi-square) techniques.

The findings of this study are interesting in nature and reported the work-life experiences at various socio-demographic levels (age, gender, educational qualification, designation, work experience, income, type of family and the number of children). The comprehensive examination of the data obtained from diverse aspects related to remote work environments has shed light on crucial facets impacting IT professionals. A predominant observation derived from the study reveals a significant disparity in working hours between male and female respondents during remote work. This discrepancy is notable, with male employees tending to work longer hours (i.e. 10 or more hours daily) than their female counterparts. The investigation into respondents’ sleep patterns revealed that the majority slept between 5 h and 7 h daily, underscoring reduced sleep hours for IT professionals during remote work. This comprehensive study thus emphasises the multifaceted nature of gender-associated influences on work patterns, health and well-being during remote work scenarios among IT professionals. As remote work is the new normal, this study has high implications for future work arrangements and organisational success.

The findings of the study will assist managers in dealing with the work conflict issue of remote workers. Importantly, these managers should try eliminating or reducing workplace conflict, emotional exhaustion and social overload associated with remote work.

This study is a humble attempt to highlight the employee’s WLB in the context of WFH in an emerging market (i.e. India). Furthermore, emphasises practical issues associated with changing work paradigms and concludes with interesting recommendations for future work arrangements.

This study aims to examine the perceptions of political figures and campaign strategists in Kuwait regarding the adoption of virtual political campaigns during the COVID-19 pandemic. By using an enhanced version of the technology acceptance model (TAM), it seeks to understand and quantify their attitudes toward these digital campaign methods. This study can be considered as a bold contribution to the discussion on digital transformation of virtual channels for the promotion of bold innovation and social impact in Kuwait.

Data was gathered from 82 participants, comprising 47 politicians and 35 campaign managers in Kuwait. A comprehensive method involving both questionnaires and face-to-face interactions was implemented to ensure a thorough collection of relevant data, aiming to support the research’s objectives effectively.

The results underscore the significant influence of perceived ease of use, perceived usefulness and the newly integrated factor of perceived convenience on the attitudes toward virtual political campaigns. These factors collectively shape the willingness and approach of political entities in embracing digital campaigning avenues. The findings also indicate that digital transformation in the design and implementation of virtual campaigns can be grounded on positive attitudes and perceptions.

The research fills a critical gap in existing literature by examining large-scale attitudes toward virtual political campaigns in Kuwait’s unique context. It offers novel understandings of how political figures and campaign managers perceive and adapt to technological advancements in campaign strategies, mainly during unprecedented crisis times like the COVID-19 pandemic. This study contributes to academic discourse and has practical implications for the evolution of political campaigning strategies in a digital age. A direct implication of our study is also the need to promote further future research on the capacity of digitally transformed channels for political campaigns to be venues of bold innovation. It also highlights the need to provide citizens with training and awareness for this new era of prompt responses to their requirements toward sustainable development and innovation.

Research done to date has produced a wide range of perspectives that center on the junction between the specific function and responsibility of the entrepreneur when applying ethical dimensions to the field of entrepreneurship. By combining a bibliometric analysis with the literature review, the purpose of this paper is to provide an overview of entrepreneurship ethics and its contribution to sustainable development goals, along with future research directions on the topic of entrepreneurship and ethics.

The research looked for literature based on entrepreneurship ethics from the Dimension database. The authors accumulated 2,279 articles for the period of 2002–2022 for analysis. The authors used bibliometric analysis for analyzing the topic with the use of VosViewer and Excel.

By combining a bibliometric analysis with a literature review, this study aimed to provide an overview of the ethics and entrepreneurship and contribution to sustainable development goals. The most influential author and journal are Vanessa Ratten and the Journal of Business Ethics, respectively. The top sustainable development goals (SDGs) being contributed by entrepreneurship ethics are SDG4, SDG8, SDG16, SDG11 and SDG3. By contrasting these two interpretations, the authors have demonstrated that the entrepreneurship environment involves various ethical issues connected to personal, organizational and societal sectors.

The current study may serve as a general guideline for future investigation into this topic.

Regarding the practical ramifications, the findings can help entrepreneurs who are preparing to launch a business or are already doing so. The findings provide a comprehensive framework of success variables that must be considered to improve the venture’s performance.

This study’s originality is from presenting a structured and in-depth literature review that describes the current state of entrepreneurship ethics and its contribution to sustainable development goals. A complete analysis of the data gathered on entrepreneurship ethics is offered to establish that it is sustainable.

The purpose of this study is to examine the factors that affect managers’ ethical decision-making in export-oriented readymade garments in Bangladesh.

This is an empirical study based on the quantitative approach undertaking a cross-sectional survey method where a convenience sampling technique was applied. The analysis was done using partial least square structural equation model applying Smart-PLS version 3.0.

This study confirmed that all the components of cognitive appraisal processes, including perceived severity, perceived vulnerability, response efficacy and self-efficacy, have a significant influence on attitude. Attitude, in turn, mediates the relationship between these variables and the behavioural intention of ethical practice, except for perceived vulnerability. Besides, moral obligation is found to mediate the relationship between attitude, self-efficacy and the behavioural intention of ethical decision-making. The study also found that ethical climate and subjective norms have a direct influence on behavioural intention. Furthermore, behavioural intention, ethical climate and self-efficacy are positively related to actual decision-making behaviour. However, this study did not find any direct effect of subjective norms on moral obligation.

The organization should include an emphasis on building ethical culture and setting an ethical code of conduct within the organization to sustain ethical practice within employees. However, the practitioner should work on enhancing self-efficacy to curb unethical practices by individuals.

This research contributes to the management of garments manufacturers by a practical and theoretical understanding of what influences the ethical behavioural decision-making process. Valuable guidelines are provided on the ethical decision-making process in the garments manufacturing companies for future researchers.

This research aims to explore the research data ethics governance framework and collaborative network to optimize research data ethics governance practices, to balance the relationship between data development and utilization, open sharing, data security and to reduce the ethical risks that may arise from data sharing and utilization.

This study explores the framework and collaborative network of research data ethics policies by using the UK as an example. 78 policies from the UK government, university, research institution, funding agency, publisher, database, library and third-party organization are obtained. Adopting grounded theory (GT) and social network analysis (SNA), Nvivo12 is used to analyze these samples and summarize the research data ethics governance framework. Ucinet and Netdraw are used to reveal collaborative networks in policy.

Results indicate that the framework covers governance context, subject and measure. The content of governance context contains context description and data ethics issues analysis. Governance subject consists of defining subjects and facilitating their collaboration. Governance measure includes governance guidance and ethics governance initiatives in the data lifecycle. The collaborative network indicates that research institution plays a central role in ethics governance. The core of the governance content are ethics governance initiatives, governance guidance and governance context description.

This research provides new insights for policy analysis by combining GT and SNA methods. Research data ethics and its governance are conceptualized to complete data governance and research ethics theory.

A research data ethics governance framework and collaborative network are revealed, and actionable guidance for addressing essential aspects of research data ethics and multiple subjects to confer their functions in collaborative governance is provided.

This study analyzes policy text using qualitative and quantitative methods, ensuring fine-grained content profiling and improving policy research. A typical research data ethics governance framework is revealed. Various stakeholders' roles and priorities in collaborative governance are explored. These contribute to improving governance policies and governance levels in both theory and practice.

The purpose of this study was to examine consumer data acquired by branded prescription drug websites and the ethics of privacy related to the interconnected web of personal information accessed, packaged and resold by tracker technologies.

The research used the DMI Tracker Tool to collect data on the top 17 branded prescription drug websites, with a specific interest in the tracker technologies embedded in those websites. That data was analyzed using Gephi, an open-source data visualization tool, to map the network of trackers embedded in those branded prescription drug websites.

Findings visualize the interconnections between tracker technologies and prescription drug websites that undergird a system of personal data acquisition and programmatic advertising vehicles that serve the interests of prescription drug marketers and Big Tech. Based on the theory of platform ethics, the study demonstrated the presence of a technostructural ecosystem dominated by Big Tech, a system that goes unseen by consumers and serves the interests of advertisers and resellers of consumer data.

The 17 websites used in this study were limited to the top-selling prescription drugs or those with the highest ad expenditures. As such this study is not based on a random sampling of branded prescription drug websites. The popularity of these prescription drugs or the expanse of advertising associated with the drugs makes them appropriate to study the presence of tracking devices that collect data from consumers and serve advertising to them. It is also noted that websites are dynamic spaces, and some trackers within their infrastructures are apt to change over time.

Branded prescription drug information has over the past three decades become part of consumers’ routine search for information regarding what ails them. As drug promotion moved from print to TV and the Web, searching for drug information has become a part of everyday life. The implications of embedded trackers on branded prescription drug websites are the subject of this research.

This study has significant social implications as consumers who are searching for information regarding prescription medications may not want drug companies tracking them in a way that many perceive to be an invasion of privacy. Yet, as the Web is dominated by Big Tech, web developers have little choice but to remain a part of this technostructural ecosystem.

This study sheds light on branded prescription drug websites, exploring the imbalance between the websites under study, Big Tech and consumers who lack awareness of the system that operates backstage.

Research on artificial intelligence (AI) and its potential effects on the workplace is increasing. How AI and the futures of work are framed in traditional media has been examined in prior studies, but current research has not gone far enough in examining how AI is framed on social media. This paper aims to fill this gap by examining how people frame the futures of work and intelligent machines when they post on social media.

We investigate public interpretations, assumptions and expectations, referring to framing expressed in social media conversations. We also coded the emotions and attitudes expressed in the text data. A corpus consisting of 998 unique Reddit post titles and their corresponding 16,611 comments was analyzed using computer-aided textual analysis comprising a BERTopic model and two BERT text classification models, one for emotion and the other for sentiment analysis, supported by human judgment.

Different interpretations, assumptions and expectations were found in the conversations. Three subframes were analyzed in detail under the overarching frame of the New World of Work: (1) general impacts of intelligent machines on society, (2) undertaking of tasks (augmentation and substitution) and (3) loss of jobs. The general attitude observed in conversations was slightly positive, and the most common emotion category was curiosity.

Findings from this research can uncover public needs and expectations regarding the future of work with intelligent machines. The findings may also help shape research directions about futures of work. Furthermore, firms, organizations or industries may employ framing methods to analyze customers’ or workers’ responses or even influence the responses. Another contribution of this work is the application of framing theory to interpreting how people conceptualize the future of work with intelligent machines.

This study aims to address a systematic literature review (SLR) using bibliometrics on the relationship between academic integrity and artificial intelligence (AI), to bridge the scattering of literature on this topic, given the challenge and opportunity for the educational and academic community.

This review highlights the enormous social influence of COVID-19 by mapping the extensive yet distinct and fragmented literature in AI and academic integrity fields. Based on 163 publications from the Web of Science, this paper offers a framework summarising the balance between AI and academic integrity.

With the rapid advancement of technology, AI tools have exponentially developed that threaten to destroy students' academic integrity in higher education. Despite this significant interest, there is a dearth of academic literature on how AI can help in academic integrity. Therefore, this paper distinguishes two significant thematical patterns: academic integrity and negative predictors of academic integrity.

This study also presents several contributions by showing that tools associated with AI can act as detectors of students who plagiarise. That is, they can be useful in identifying students with fraudulent behaviour. Therefore, it will require a combined effort of public, private academic and educational institutions and the society with affordable policies.

This study proposes a new, innovative framework summarising the balance between AI and academic integrity.

A new triage method, MBCE (Medical Bio Social Ethics), is presented with social justice, bio, and medical ethics for critical resource distribution during a pandemic. Ethical triage is a complex and challenging process that requires careful consideration of medical, social, cultural, and ethical factors to guide the decision-making process and ensure fair and transparent allocation of resources. When assigning priorities to patients, a clinician would evaluate each patient’s medical condition, age, comorbidities, and prognosis, as well as their cultural and social background and ethical factors.

A statistical analysis shows no interactions among the ethical triage factors. It implies the ethical components have no moderation effect; hence, each is independent. The result also points out that medical and bioethics may have an affinity for interactions. In such cases, there seem to be some ethical factors related to bio and medical ethics that are correlated. Therefore, the triage team should be careful in evaluating patient cases. The algorithm is explained with case histories of the selected patient. A group of triage nurses and general medical practitioners assists with the triage.

The MBCE triage algorithm aims to allocate scarce resources fairly and equitably. Another ethical principle in this triage algorithm is the principle of utility. In a pandemic, the principle of utility may require prioritizing patients with a higher likelihood of survival or requiring less medical care. The research presents a sensitivity analysis of a patient’s triage score to show the algorithm’s robustness. A weighted score of ethical factors combined with an assessment of triage factors combines multiple objectives to assign a fair triage score. These distinctive features of the algorithm are reasonably easy to implement and a new direction for the unbiased triage principle.

The idea is to make decisions about distributing and using scarce medical resources. Triage algorithms raise ethical issues, such as discrimination and justice, guiding medical ethics in treating patients with terminal diseases or comorbidity. One of the main ethical principles in triage algorithms is the principle of distributive justice.

This study aims to investigate how living lab (LL) activities align with responsible research and innovation (RRI) principles, particularly in artificial intelligence (AI)-driven digital transformation (DT) processes. The study seeks to define a framework termed “responsible living lab” (RLL), emphasizing transparency, stakeholder engagement, ethics and sustainability. This emerging issue paper also proposes several directions for future researchers in the field.

The research methodology involved a literature review complemented by insights from a workshop on defining RLLs. The literature review followed a concept-centric approach, searching key journals and conferences, yielding 32 relevant articles. Backward and forward citation analysis added 19 more articles. The workshop, conducted in the context of UrbanTestbeds.JR and SynAir-G projects, used a reverse brainstorming approach to explore potential ethical and responsible issues in LL activities. In total, 13 experts engaged in collaborative discussions, highlighting insights into AI’s role in promoting RRI within LL activities. The workshop facilitated knowledge sharing and a deeper understanding of RLL, particularly in the context of DT and AI.

This emerging issue paper highlights ethical considerations in LL activities, emphasizing user voluntariness, user interests and unintended participation. AI in DT introduces challenges like bias, transparency and digital divide, necessitating responsible practices. Workshop insights underscore challenges: AI bias, data privacy and transparency; opportunities: inclusive decision-making and efficient innovation. The synthesis defines RLLs as frameworks ensuring transparency, stakeholder engagement, ethical considerations and sustainability in AI-driven DT within LLs. RLLs aim to align DT with ethical values, fostering inclusivity, responsible resource use and human rights protection.

The proposed definition of RLL introduces a framework prioritizing transparency, stakeholder engagement, ethics and sustainability in LL activities, particularly those involving AI for DT. This definition aligns LL practices with RRI, addressing ethical implications of AI. The value of RLL lies in promoting inclusive and sustainable innovation, prioritizing stakeholder needs, fostering collaboration and ensuring environmental and social responsibility throughout LL activities. This concept serves as a foundational step toward a more responsible and sustainable LL approach in the era of AI-driven technologies.