The investigation of established drivers of online purchase behavior is of great relevance during the COVID-19 pandemic, as companies must anticipate consumer behavior during this global crisis to maintain a competitive edge. This study investigates online shopping motives of generation Y and Z during the COVID-19 shutdown in April 2020. We use survey data from 451 German consumers to examine the relations between normative, utilitarian and hedonic motives, and purchase intentions employing structural equation modeling. The results show that normative determinants such as media reports on the economic situation are related to consumers’ purchase intentions, whereas the normative influence of close social networks is not. Furthermore, we find that hedonic motivation is a better predictor of purchase intentions than utilitarian motives and that individuals practicing social distancing, generation Z, and women show higher levels of hedonic motivation. We provide recommendations for e-commerce companies on ways to address consumers’ purchase motives and strategically harness normative influences.

Background: Contact tracing apps are an essential component of an effective COVID-19 testing strategy to counteract the spread of the pandemic and thereby avoid overburdening the health care system. As the adoption rates in several regions are undesirable, governments must increase the acceptance of COVID-19 tracing apps in these times of uncertainty. Objective: Building on the Uncertainty Reduction Theory (URT), this study aims to investigate how uncertainty reduction measures foster the adoption of COVID-19 tracing apps and how their use affects the perception of different risks. Methods: Representative survey data were gathered at two measurement points (before and after the app’s release) and analyzed by performing covariance-based structural equation modeling (n=1003). Results: We found that uncertainty reduction measures in the form of the transparency dimensions disclosure and accuracy, as well as social influence and trust in government, foster the adoption process. The use of the COVID-19 tracing app in turn reduced the perceived privacy and performance risks but did not reduce social risks and health-related COVID-19 concerns. Conclusions: This study contributes to the mass adoption of health care technology and URT research by integrating interactive communication measures and transparency as a multidimensional concept to reduce different types of uncertainty over time. Furthermore, our results help to derive communication strategies to promote the mass adoption of COVID-19 tracing apps, thus detecting infection chains and allowing intelligent COVID-19 testing.

Background: Hospitals have been one of the major targets for phishing attacks. Despite efforts to improve information security compliance, hospitals still significantly suffer from such attacks, impacting the quality of care and the safety of patients. Objective: This study aimed to investigate why hospital employees decide to click on phishing emails by analyzing actual clicking data. Methods: We first gauged the factors that influence clicking behavior using the theory of planned behavior (TPB) and integrating trust theories. We then conducted a survey in hospitals and used structural equation modeling to investigate the components of compliance intention. We matched employees’ survey results with their actual clicking data from phishing campaigns. Results: Our analysis (N=397) reveals that TPB factors (attitude, subjective norms, and perceived behavioral control), as well as collective felt trust and trust in information security technology, are positively related to compliance intention. However, compliance intention is not significantly related to compliance behavior. Only the level of employees’ workload is positively associated with the likelihood of employees clicking on a phishing link. Conclusions: This is one of the few studies in information security and decision making that observed compliance behavior by analyzing clicking data rather than using self-reported data. We show that, in the context of phishing emails, intention and compliance might not be as strongly linked as previously assumed; hence, hospitals must remain vigilant with vulnerabilities that cannot be easily managed. Importantly, given the significant association between workload and noncompliance behavior (ie, clicking on phishing links), hospitals should better manage employees’ workload to increase information security. Our findings can help health care organizations augment employees’ compliance with their cybersecurity policies and reduce the likelihood of clicking on phishing links.

Due to the high risk of COVID-19 transmission, many sport events, including organised cycling competitions, have been cancelled. Nevertheless, staying active is important for individual well-being and professional athletes need to compete to earn their living. We propose that mixed-reality applications like ZWIFT allow to conduct virtually mediated sports competitions, which resemble traditional sport realistically and could serve as a remedy for this contradiction. To test this proposition, we compare professional cyclists’ performance data from virtual competitions with data obtained from traditional cycling races and find that the physical activities are comparable. Thus, we contribute to the discussion on the distinctiveness of sports and eSport. Moreover, we interview 11 professional cyclists, who participated in virtual race series regarding their evaluation of the virtualisation of cycling events. Accordingly, we contribute to the literature on mixed-reality applications by focusing on user perceptions of a novel and physical dimension of virtually mediated interaction. Thereby, we apply the sports digitalisation framework proposed by Xiao et al. (2017). Professional athletes mainly perceive the virtualisation of sport as positive, but also mention some specific risks. Consequently, we derive implications for practice that include the supportive role of virtual sport to help master pandemics such as COVID-19.

Trust has been identified as inevitable for technology acceptance and might further gain importance as technologies become increasingly complex. However, previous research on trust in online environments lacks a systematic configuration of trust entities in research models; some studies include either trust in technology or trust in provider, others both. In combination with inconsistent results, this leads to a lack of in-depth knowledge about the trust entities’ relationship to each other, to their antecedents, and intention to use. Therefore, this study aims at clarifying these relationships and examining how they vary for different configurations. We performed pairwise meta-analyses to generate summary effects for the individual trust entities and examined four different trust configurations by applying meta-analytic structural equation modeling (MASEM). Our findings advance technology acceptance and trust research and highlight the necessity to carefully configure trust. More specifically, the results from pairwise meta-analysis support a strong relationship between the trust entities that is, however, countered by the effects of antecedents in MASEM. Institution-based trust and reputation are found stronger predictors for trust in provider and familiarity a stronger determinant of trust in technology. Furthermore, the trust entities show comparable paths to intention to use when either trust entity is included in the research model, but when both are integrated, trust in technology is more important than trust in provider.