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Virtual wine experiences (VWEs) replaced in-person wine experiences during the Covid-19 pandemic and continue to be offered by some actors. This study aims to investigate the factors driving interest in VWEs and identify relevant traits of potential consumers to help assess VWEs long-term potential.

A representative sample of 399 Oregon and California wine consumers answered a structured online survey. The authors combine ordered logistic regression and qualitative techniques to analyze the data.

VWEs may effectively attract potential wine consumers and tourists. High interest in VWEs is associated with strong wine involvement and intentions to visit wine regions. Digitization, aversion to travel-related risk and convenience are other relevant drivers of VWE interest. The segmentation analysis revealed that consumers with a potentially higher interest in VWE have distinct traits.

Wineries and wine tourism destinations could leverage VWEs to attract wine tourists and consumers. The authors discuss specific characteristics of high-interest consumers.

Participants in VWEs interact with hosts and explore products in real time. This engagement has long-term marketing potential for attracting them as customers or visitors. The study provides strategic information for practitioners and academics on VWE interest drivers and potential demand, which is currently missing from the literature.

Railways are a well-known example of complex critical infrastructure, incorporating socio-technical systems with humans such as drivers, signallers, maintainers and passengers at the core. The technological evolution including interconnectedness and new ways of interaction lead to new security and safety risks that can be realised, both in terms of human error, and malicious and non-malicious behaviour. This study aims to identify the human factors (HF) and cyber-security risks relating to the role of signallers on the railways and explores strategies for the improvement of “Digital Resilience” – for the concept of a resilient railway.

Overall, 26 interviews were conducted with 21 participants from industry and academia.

The results showed that due to increased automation, both cyber-related threats and human error can impact signallers’ day-to-day operations – directly or indirectly (e.g. workload and safety-critical communications) – which could disrupt the railway services and potentially lead to safety-related catastrophic consequences. This study identifies cyber-related problems, including external threats; engineers not considering the human element in designs when specifying security controls; lack of security awareness among the rail industry; training gaps; organisational issues; and many unknown “unknowns”.

The authors discuss socio-technical principles through a hexagonal socio-technical framework and training needs analysis to mitigate against cyber-security issues and identify the predictive training needs of the signallers. This is supported by a systematic approach which considers both, safety and security factors, rather than waiting to learn from a cyber-attack retrospectively.

It has become increasingly clear that the objectives of privacy and competition policy are in conflict with one another with regard to platform data. While privacy policies aim at limiting the use of platform data for purposes other than those for which the data were collected in order to protect the privacy of platform users, competition policy aims at making such data widely available in order to curb the power of platforms.

We draw on Commons' Institutional Economics to contrast the current control-based approaches to ensuring the protection as well as the sharing of platform data with an ownership approach. We also propose the novel category of platform use data and contrast this with the dichotomy of personal/non-personal data which underlies current regulatory initiatives.

We find that current control- and ownership-based approaches are ineffective with regard to their capacity to balance these conflicting objectives and propose an alternative approach which makes platform data saleable. We discuss this approach in view of its capacity to balance the conflicting objectives of privacy and competition policy and its effectiveness in supporting each separately.

Our approach clarifies the fundamental difference between data markets and other concepts such as data exchanges.

The study directs attention to the psychological conditions experienced and knowledge management practices leveraged by faculty in higher education institutes (HEIs) to cope with the shift to emergency remote teaching caused by the COVID-19 pandemic. By focusing attention on faculty experiences during this transition, this study aims to examine an under-investigated effect of the pandemic in the Indian context.

Interpretative phenomenological analysis is used to analyze the data gathered in two waves through 40 in-depth interviews with 20 faculty members based in India over a year. The data were analyzed deductively using Kahn’s framework of engagement and robust coding protocols.

Eight subthemes across three psychological conditions (meaningfulness, availability and safety) were developed to discourse faculty experiences and challenges with emergency remote teaching related to their learning, identity, leveraged resources and support received from their employing educational institutes. The findings also present the coping strategies and knowledge management-related practices that the faculty used to adjust to each discussed challenge.

The study uses a longitudinal design and phenomenology as the analytical method, which offers a significant methodological contribution to the extant literature. Further, the study’s use of Kahn’s model to examine the faculty members’ transitions to emergency remote teaching in India offers novel insights into the COVID-19 pandemic’s effect on educational institutes in an under-investigated context.

This study explores the work practices of managers who increased working from home during the pandemic to determine what, if any, impact there was on the conditions for vertical leadership development.

The project utilized a survey approach. Each of the participants completed an anonymous online questionnaire using Google Forms. The questionnaire included four sections. The first section included informed consent and required participants to agree before completing the questionnaire. Participants provided general demographic information in the second section, including gender, age, race, job title, company size, average project team size and industry. The third section asked if there had been any change in their work location following the pandemic. The last section asked participants about their work practices.

This study demonstrates that managers continued to be engaged in vertical leadership development activities while working from home. It also suggests that managers faced challenges working from home following the COVID-19 pandemic, which were prime vertical leadership development opportunities.

To capitalize on these opportunities, organizations can more intentionally support the development of their remote staff.

Using real-time support systems may help operators in road construction to improve paving and compaction operations. Nowadays, these systems transform from descriptive to prescriptive systems. Prescriptive or operator guidance systems propose operators actionable compaction strategies and guidance, based on the data collected. It is investigated how these systems mediate the perceptions and actions of operators in road pavement practice.

A case study is conducted on the specific application of an operator guidance system in a road pavement project. In this case study, comprehensive information is presented regarding the process of converting input in the form of data from cameras and sensors into useful output. The ways in which the operator guidance systems translate data into actionable guidance for operators are analyzed from the technological mediation perspective.

Operator guidance systems mediate actions of operators physically, cognitively and contextually. These different types of action mediation are related to preconditions for successful implementation and use of these systems. Coercive interventions only succeed if there is widespread agreement among the operators. Persuasive interventions are most effective when collective and individual interests align. Contextual influence relates to designs of the operator guidance systems that determine human-technology interactions when using them.

This is the first study that analyzes the functioning of an operator guidance system using the technological mediation approach. It adds a new perspective on the interaction between this system and its users in road pavement practice.

Prior research has extensively examined how bringing technology from work into the non-work life domain creates conflict, yet the reverse pathway has rarely been studied. The purpose of this study is to bridge this gap and examine how the non-work use of smartphones in the workplace affects work–life conflict.

Drawing from three literature streams: technostress, work–life conflict and role boundary theory, the authors theorise on how limiting employees' ability to integrate the personal life domain into work, by means of technology use policy, contributes to stress and work–life conflict. To test this model, the authors employ a natural experiment in a company that changed its policy from fully restricting to open smartphone access for non-work purposes in the workplace. The insights gained from the experiment were explored further through qualitative interviews.

Work–life conflict declines when a ban on using smartphones for non-work purposes in the workplace is revoked. This study's results show that the relationship between smartphone use in the workplace and work–life conflict is mediated by sensed stress. Additionally, a post-hoc analysis reveals that work performance was unchanged when the smartphone ban was revoked.

First, this study advances the authors' understanding of how smartphone use policies in the workplace spill over to affect non-work life. Second, this work contributes to the technostress literature by revealing how, in specific situations, engagement with ICT can reduce distress and strain.

Recent evidence from a linear econometric framework infers that housing search activity, captured from Google Trends data, can predict housing returns for the USA at a national and regional (metropolitan statistical area [MSA]) level. Based on search theory, the authors, however, postulate that search activity can also predict housing returns volatility. This study aims to explore the possibility of using online search activity to predict both housing returns and volatility.

Using a k-th order non-parametric causality-in-quantiles test allows us to test for predictability in a robust manner over the entire conditional distribution of both housing price returns and its volatility (i.e. squared returns) by controlling for nonlinearity and structural breaks that exist in the data.

The analysis over the monthly period of 2004:01 to 2021:01 produces results indicating that while housing search activity continues to predict aggregate US house price returns, barring the extreme ends of the conditional distribution, volatility is relatively strongly predicted over the entire quantile range considered. The results carry over to an alternative (the generalized autoregressive conditional heteroskedasticity-based) metric of volatility, higher (weekly)-frequency data (over January 2018–March 2021) and to over 84% of the 77 MSAs considered.

To the best of the authors’ knowledge, this is the first study regarding predictability of overall and regional US housing price returns and volatility using search activity, based on a non-parametric higher-order causality-in-quantiles framework, which is insightful to investors, policymakers and academics.

This study aims to assess the spread of environmental literacy graduation requirements at public universities in the USA, and to highlight factors that mediate the adoption of this curriculum innovation.

The author analyzed the undergraduate general education curriculum requirements at all 549 public BA-granting higher education institutions in the USA between 2020 and 2022.

The study found that only 27 US public universities out of 540 have an environmental literacy graduation requirement, which represents 5% of universities and is substantially lower than previous estimates.

First, this study provides a more complete, more reliable and more current assessment of the graduation requirement’s presence at US tertiary institutions, and shows the number of universities that have implemented this innovation is lower than was estimated a decade ago. Second, it draws from the scholarship on the infusion of sustainability into the university curriculum to provide a comprehensive discussion of factors that mediate the pursuit and implementation of the graduation requirement. As well, it identifies factors that played a key role in one pertinent case.

Researchers looking for ways to change the insecure behaviour that results in phishing have considered multiple possible reasons for such behaviour. Therefore, the purpose of this paper is to understand the role of optimism bias (OB – defined as a cognitive bias), which characterises overly optimistic or unrealistic individuals, to ensure secure behaviour. Research that focused on issues such as personality traits, trust, attitude and Security, Education, Training and Awareness (SETA) was considered.

This study built on a recontextualized version of the theory of planned behaviour to evaluate the influence that optimism bias has on phishing susceptibility. To model the data, an analysis was performed on 226 survey responses from a South African financial services organisation using partial least squares (PLS) path modelling.

This study found that overly optimistic employees were inclined to behave insecurely, while factors such as attitude and trust significantly influenced the intention to behave securely.

Our contribution to practice seeks to enhance the effectiveness of SETA by identifying and addressing the optimism bias weakness to deliver a more successful training outcome.

Our study enriches the Information Systems literature by evaluating the effect of a cognitive bias on phishing susceptibility and offers a contextual explanation of the resultant behaviour.