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Drawing on COR theory and based on a person-centered approach, this study aims to explore profiles of both leadership behavior (transformational leadership, abusive supervision) and well-being indicators (cognitive irritation, emotional exhaustion). Additionally, we consider whether certain resource-draining (work intensification) and resource-creating factors (leader autonomy, psychological contract fulfillment) from the leaders' work context are related to profile membership.

The profiles are built using LPA on data from 153 leaders and their 1,077 followers. The relationship between profile membership and correlates from the leaders' work context is examined using multinomial logistic regression analyses.

LPA results in an interpretable four-profile solution with the profiles named (1) Good health – constructive leading, (2) Average health – inconsistent leading, (3) Impaired health – constructive leading and (4) Impaired health – destructive leading. The two groups with the highest sample share – Profiles 1 and 3 – both show highly constructive leadership behavior but differ significantly in their well-being indicators. The regression analyses show that work intensification and psychological contract fulfillment are significantly related to profile membership.

The person-centered approach provides a more nuanced view of the leadership behavior – leader well-being relationship, which can address inconsistencies in previous research. In terms of practical relevance, the person-centered approach allows for the identification of risk groups among leaders for whom organizations can provide additional resources and health-promoting interventions.

The rapid advancement of technology has transformed the health-care industry and enabled the emergence of m-Health solutions such as health apps. The viability and success of these apps depends on the definition of a monetization model appropriate to their specificities. In this sense, the purpose of this paper is to study the mechanisms of monetization of health apps, to stablish how alternative revenues determine if a health app is to be free or paid.

Probability models are used to identify the factors that explain if a health app is free or paid.

Results show that the presence of alternative monetization mechanisms negatively impacts the likelihood of a health app being paid for. The use of personal data to customize advertising (the monetization of “privacy capital”) or the inclusion of ads on the app are alternative means of monetization with potential to decrease the likelihood of a health app being paid for. The possibility of in-app purchases has a lower negative impact on the probability of a health app being paid for. The choice of platform to commercialize an app is also a strategic decision that influences the likelihood of an app being paid for.

This work stands out for bringing together the two largest platforms present in Portugal and for focusing on the perspective of revenue and monetization of health apps and not on the perspective of downloads.

The existing literature offers various perspectives on integrating cryptocurrencies into investment portfolios; yet, there is a gap in understanding the behaviours, attitudes and cross-investment links of individual investors. This study, grounded in the modern portfolio theory and the random walk theory, aims to add empirical insights that are specific to the UK context. It explores four hypotheses related to the influence of socio-demographics, digital adoption, cross-investment behaviours and financial attitudes on cryptocurrency owners.

This study uses a logistic regression model with secondary data from the Financial Lives Survey 2020 to assess the factors impacting cryptocurrency ownership. A total of 29 variables are used, categorized into four groups aligned with the hypotheses. Additionally, hierarchical clustering analysis was conducted to further explore the cross-investment links.

The study reveals a significant lack of diversification among UK cryptocurrency investors, a pronounced inclination towards high-risk investments such as peer-to-peer lending and crowdfunding, and parallels with gambling behaviours, including financial dissatisfaction and a propensity for risk-taking. It highlights the influence of demographic traits, risk tolerance, technological literacy and emotional attitudes on cryptocurrency investment decisions.

This study provides valuable insights into cryptocurrency regulation and retail investor protection, underscoring the necessity for tailored financial education and a holistic regulatory approach for investment products with comparable risk levels, with the aim of minimizing regulatory arbitrage. It significantly enhances our understanding of the unique dynamics of cryptocurrency investments within the evolving financial landscape.

The purpose of this paper is to identify the practices that owners of public profiles in social networking sites can leverage to actively build online reputation and to evaluate the impact of the adoption of such practices on the initial formation of trust toward these individuals when they are presented as new virtual work partners.

A theoretical model was developed and an experiment with 233 participants was utilized to assess the model using partial least squares structural equation modeling.

The results suggest that individuals can build their online reputations in public profiles of social networking sites via a series of practices of self-disclosure of information and that the adoption of these practices has significant effects on the initial formation of trust toward the profile owner in virtual work contexts. Categorization mechanisms such as stereotyping, unit grouping and reputation categorization have been found to contribute to the initial formation of trust, both from an affect and cognition-based perspectives.

Little is known about the information disclosure practices in public profiles of social networking sites that new work partners can adopt to facilitate the formation of trust between them before they start working together. This study has contributed to the existing body of literature by clarifying these practices and the relative importance of online reputation to the initial formation of trust during the outset of a new virtual work relationship.

This study aims to analyze the capacity of ecotourists to exhibit behavior that aligns with the ecotourist scale using the Rasch model measurement.

The data was gathered using an online survey incorporating the five tenets of ecotourism using a seven-point rating scale on domestic tourists in Indonesia. Descriptive statistics, cross-tabulation and Rasch model measurement were used to analyze the data.

The ecotourist identification scale measurement items were reliable and satisfactory. The most challenging behavior for ecotourists was using the services of a tour guide who was concerned about the environment. Meanwhile, respecting cultural differences around the tourist destination was the most accessible behavior. Most respondents demonstrated a fit response pattern and satisfactorily met the validity and reliability criteria.

This study did not compare ecotourists’ ability to behave by the type of conservation visited as its limitation. However, it provides a significant methodological contribution to developing a measurement of ecotourist behavior implemented in well-established behavioral theories.

Integrating ecotourism into education, incentivizing eco-friendly tourism practices, promoting awareness, supporting local businesses, respecting local values and ensuring safe travels.

To the best of the authors’ knowledge, this study is the first of its kind to be conducted in Indonesia. It uses a unique and innovative method to reveal the unobserved variables in ecotourists’ behavior. The findings confirm that tourists’ behaviors align with the five tenets of ecotourism.

The purpose of this paper is to develop a prototype of a wearable medical device in the form of a bandage with a real-time data monitoring platform, which can be used domestically for diabetic patients to identify the possibility of foot ulceration at the early stage.

The prototype can measure blood volumetric change and temperature variation in the forefoot area simultaneously. The waveform extracted using a pulsatile-blood-flow signal was used to assess blood perfusion-related information, and hence, predict ischemic ulcers. The temperature difference between ulcerated and the reference was used to predict neuropathic ulcers. The medical device can be used as a bandage during the application wherein the sensory module is placed inside the hollow pocket of the bandage. A platform was developed through a mobile application where doctors can extract real-time information, and hence, determine the possibility of ulceration.

The height of the peaks in the pulsatile-blood-flow signal measured from the subject with foot ischemic ulcers is significantly less than that of the subject without ischemic ulcers. In the presence of ischemic ulcers, the captured waveform flattens. Therefore, the blood perfusion from arteries to the tissue of the forefoot is considerably low for the subject with ischemic ulcers. According to the temperature difference data measured over 25 consecutive days, the temperature difference of the subject with neuropathic ulcers occasionally exceeded the 4 °F range but mostly had higher values closer to the 4 °F range. However, the temperature difference of the subject who had no complications of neuropathic ulcers did not exceed the 4 °F range, and the majority of the measurements occupy a narrow range from −2°F to 2 °F.

The proposed prototype of wearable medical apparatus can monitor both temperature variation and pulsatile-blood-flow signal on the forefoot simultaneously and thereby predict both ischemic and neuropathic diabetes using a single device. Most importantly, the wearable medical device can be used domestically without clinical assistance with a real-time data monitoring platform to predict the possibility of ulceration and the course of action thereof.

Research on online user privacy shows that empirical evidence on how privacy literacy relates to users' information privacy empowerment is missing. To fill this gap, this paper investigated the respective influence of two primary dimensions of online privacy literacy – namely declarative and procedural knowledge – on online users' information privacy empowerment.

An empirical analysis is conducted using a dataset collected in Europe. This survey was conducted in 2019 among 27,524 representative respondents of the European population.

The main results show that users' procedural knowledge is positively linked to users' privacy empowerment. The relationship between users' declarative knowledge and users' privacy empowerment is partially supported. While greater awareness about firms and organizations practices in terms of data collections and further uses conditions was found to be significantly associated with increased users' privacy empowerment, unpredictably, results revealed that the awareness about the GDPR and user’s privacy empowerment are negatively associated. The empirical findings reveal also that greater online privacy literacy is associated with heightened users' information privacy empowerment.

While few advanced studies made systematic efforts to measure changes occurred on websites since the GDPR enforcement, it remains unclear, however, how individuals perceive, understand and apply the GDPR rights/guarantees and their likelihood to strengthen users' information privacy control. Therefore, this paper contributes empirically to understanding how online users' privacy literacy shaped by both users' declarative and procedural knowledge is likely to affect users' information privacy empowerment. The study empirically investigates the effectiveness of the GDPR in raising users' information privacy empowerment from user-based perspective. Results stress the importance of greater transparency of data tracking and processing decisions made by online businesses and services to strengthen users' control over information privacy. Study findings also put emphasis on the crucial need for more educational efforts to raise users' awareness about the GDPR rights/guarantees related to data protection. Empirical findings also show that users who are more likely to adopt self-protective approaches to reinforce personal data privacy are more likely to perceive greater control over personal data. A broad implication of this finding for practitioners and E-businesses stresses the need for empowering users with adequate privacy protection tools to ensure more confidential transactions.

Food service establishments and online food delivery companies use a revenue share model based on a commission rate. Because of the asymmetry of bargaining power, many food service establishments are vulnerable to a high commission rate. What is missing in the ongoing discussion about the revenue share model is the perspective of food consumers, who are the third party in the multi-sided market.

Within a willingness-to-pay (WTP) framework, we study if food consumers have preferences for the commission rate charged by food delivery companies to food service establishments. With 456 random consumers in the United States, we conduct a controlled experiment in which information is used as treatment in two groups. In the first group, the provided information only relates to the revenue share model (i.e. economic). In the second group, participants also received information about price control initiatives (i.e. economic and political).

Based on WTP-space mixed logit model results, there is a significant effect of information on preferences for the commission rate. While participants in the control group exhibited no aversion to the commission rate, participants who received treatment had a significant and negative WTP. The magnitude of the effect is estimated at -$1.08 for participants in the first treatment and -$2.28 for participants in the second treatment.

To date there is no applied research on the preferences of consumers in the online food order and delivery industry with respect to upstream conditions (i.e. commission rates).

European Parliament adopted a new directive on gender balance in corporate boards when by 2026, companies must employ 40% of the underrepresented sex into non-executive directors or 33% among all directors. Therefore, this study aims to analyze the impact of gender diversity (GD) on board of directors and the shareholders’ structure and their impact on the likelihood of company bankruptcy during the COVID-19 pandemic.

The data sample consists of 1,351 companies for 2019 and 2020, of which 173 were large, 351 medium-sized companies and 827 small companies. Three bankruptcy indicators were tested for each company size, and extreme gradient boosting (XGBoost) and logistic regression models were developed. These models were then cross-validated by a 10-fold approach.

XGBoost models achieved area under curve (AUC) over 98%, which is 25% higher than AUC achieved by logistic regression. Prediction models with GD features performed slightly better than those without them. Furthermore, this study indicates the existence of critical mass between 30% and 50%, which decreases the probability of bankruptcy for small and medium companies. Furthermore, the representation of women in ownership structures above 50% decreases bankruptcy likelihood.

This is a pioneering study to explore GD topics by application of ensembled machine learning methods. Moreover, the study does analyze not only the GD of boards but also shareholders. A highly innovative approach is GD analysis based on company size performed in one study considering the COVID-19 pandemic perspective.

Online reviewers' identity information is an essential cue by which consumers judge reviews on ecommerce platforms. However, few studies have explored how prior anonymous reviews and focal reviews affect reviewers' preference for anonymity. The purpose of this paper is to investigate why reviewers seek anonymity in terms of prior anonymous reviews and focal reviews.

Based on restaurant reviews collected from meituan.com, one of the largest group-buying ecommerce platforms in China, this study employed logistic regression to examine how prior anonymous reviews and focal reviews are associated with reviewers' preference for anonymity.

Results show that the volume and sequence of prior anonymous review are positively associated with the likelihood of reviewers' preference for anonymity, whereas focal review valence is negatively correlated with this preference. Focal review length is positively correlated with reviewers' preference for anonymity but negatively moderates the roles of review valence and prior anonymous reviews on this preference.

This study expands the information disclosure literature by exploring determinants of user identity disclosure from a reviewer perspective. This research also offers a methodological contribution by employing a more accurate measure to calculate reviewers' preference for anonymity, enhancing the empirical results. Lastly, this work supplements the online review literature on how prior anonymous reviews and focal reviews are associated with reviewers' identity disclosure.