CEO performance-based grants’ vesting provisions and debt contracts: Evidence from GAAP,Non-GAAP and KPI metrics

We examine the influence of CEOs’ equity and cash grants’ vesting provisions that are based on (i) accounting performance metrics prepared under US generally accepted principles (GAAP), (ii) non-GAAP performance metrics and (iii) key performance indicators (KPIs) on debt contracts. We find that grants with vesting provisions based on GAAP metrics and KPIs lead to a lower cost of debt, a lower likelihood of collateral requirements and less restrictive covenant terms. In contrast, performance-based grants with non-GAAP vesting provisions lead to a higher cost of debt, a higher likelihood of collateral requirements and more restrictive covenant terms. Supplementary analyses reveal that our results are incremental to other debtholder-friendly features in the CEO contracts, such as grants with debt-related performance measures and CEOs’ inside debt holdings, and robust to alternative variable definitions and specifications. Overall, our results suggest that debtholders understand the differing incentives associated with GAAP, non-GAAP and KPI-based performance measures, and incorporate these differences into debt contracts.     

Exploring the role of data enclosure in the digital political economy

This exploratory research analyzes the impact of data enclosure initiatives on market competition. Data enclosure is the process by which the information about user activity generated by digital operations are withdrawn from an open or shared arrangement with other operators and made more exclusive to the service providers whose operations generate the data. We make the case that data enclosure is emerging as a significant feature of the multi-sided markets of digital platform providers, by looking empirically at, 1) the encryption of DNS query data using the DNS over HTTPS (DoH) protocol, and 2) the enclosure of Apple and Google's mobile identifiers used in digital advertising and cross-app user tracking. These efforts are not only privacy-enhancing moves, but also a means by which service providers compete with each other over the value and security of data. We assess the degree to which exclusivity of data fosters or forecloses competition in the relevant markets, and find mixed results. DoH, apparently a more disruptive form of data enclosure, has had little impact on industry shares so far, primarily because it was embraced by a small-share, declining actor, but the growing use of DoH and other encrypted DNS protocols does indicate a market-driven response to privacy-enhancement. In mobile identifiers in adtech, the shift in the default from opt-out permission to opt-in permission had both strong privacy effects and major effects on the distribution of revenues in the industry. But the changes are recent and the situation remains unsettled.     

Privacy assurances and social sharing in social commerce: The mediating role of threat-coping appraisals

The social sharing of consumers (e.g., posting about a shopping experience) is the basis for the flourishing of social commerce; however, it conflicts with consumers’ psychological need for privacy. This study attempts to investigate the comprehensive effect of privacy assurances from different institutions on social sharing, involving privacy policy and privacy-protective technology provided by social media companies as well as government regulation and industry self-regulation. We conducted a large-scale empirical survey with 1,311 users of Xiaohongshu in China. The results show that all the four privacy assurances have a positive effect on social sharing that is almost equal. The results also reveal that threat appraisal and coping appraisal jointly mediate the relationship of privacy assurances and social sharing. Our results provide operable implications for stakeholders on how to facilitate social sharing and thus the flourishing of s-commerce through fostering privacy assurances.     

Behavioural intention to use a contact tracing application: The case of StopCovid in France

This research aims to study citizens' intention to download and use the COVID-19 tracing app in France. The theoretical framework considered the theory of technology acceptance model, the theory of goal-directed behaviour, and the theory of privacy to explain the intention to use the COVID-19 tracing app. The methodology included an online survey to examine the theoretical model, which was tested using structural equation modelling. The results show that anticipated emotions, perceived usefulness, privacy concerns, and perceived permission sensitivity significantly contribute towards the intention to adopt the StopCovid app. Subjective norms and goal desire do not exert a direct impact. These findings provide both theoretical and practical implications by adding the extrinsic social value dimension to the analyses of the StopCovid app and presenting antecedents for enhancing its design and safety.     

Harmonizing regulatory regimes for the governance of patient-generated health data

Patient-generated health data (PGHD), created and captured from patients via wearable devices and mobile apps, are proliferating outside of clinical settings. Examples include sleep trackers, fitness trackers, continuous glucose monitors, and RFID-enabled implants, with many additional biometric or health surveillance applications in development or envisioned. These data are included in growing stockpiles of personal health data (PHI) being mined for insight by health economists, policy analysts, researchers, and health system organizations. Dominant narratives position these highly personal data as valuable resources to transform healthcare, stimulate innovation in medical research, and engage individuals in their health and healthcare. Large tech companies are also increasingly implicated in these areas, through mobile health application sales and data acquisitions. Given the many possible uses and users for PGHD, ensuring privacy, security, and equity of benefits from PGHD will be challenging. This is due in part to disparate regulatory policies and practices across technology firms, health system organizations, and health researchers. Rapid developments with PGHD technologies and the lack of harmonization between regulatory regimes may render existing safeguards to preserve patient privacy and control over their PGHD ineffective, while also failing to guide PGHD-related innovation in socially desirable directions. Using a policy regime lens to explore these challenges, we examine three existing data protection regimes relevant to PGHD in the United States that are currently in tension with one another: federal and state health-sector laws, regulations on data use and reuse for research and innovation, and industry self-regulation of consumer privacy by large tech companies. We argue that harmonization of these regimes is necessary to meet the challenges of PGHD data governance. We next examine emerging governing instruments, identifying three types of structures (organizational, regulatory, technological/algorithmic), which synergistically could help enact needed regulatory oversight while limiting the friction and economic costs of regulation that may hinder innovation. This policy analysis provides a starting point for further discussions and negotiations among stakeholders and regulators to do so.     

Developing design principles for the implementation of AI in PSM: An investigation with expert interviews

The use of artificial intelligence (AI) in purchasing and supply management (PSM) has great potential, e.g. for automating processes and supporting PSM employees. Nevertheless, the number of realized AI use cases in PSM is still limited, and mostly in large companies. This paper examines first requirements for the implementation of AI in PSM. Second, design principles are developed on the basis of the identified requirements. Third, exemplary AI use cases in PSM are presented. For this purpose, a literature analysis is first conducted and followed by interviews with 17 PSM and technology experts. Finally, 40 requirements for the implementation of AI in PSM are developed from the conducted expert interviews. Based on these 40 requirements, ten design principles are developed in the sense of the design science research (DSR) approach to describe the relevant activities for the implementation of AI in PSM. The artifacts developed in this paper will contribute to the implementation of AI in PSM. The applicable research results should facilitate the transfer of knowledge into practice and contribute to the establishment of the DSR method in PSM research.     

When and how consumers are willing to exchange data with retailers: An exploratory segmentation

Consumer data is a crucial resource for retailers. Yet accessing this data increasingly requires consumers to willingly participate in data exchange. This paper draws on social exchange theory and privacy calculus to investigate differences in consumer willingness to exchange data with retailers. Consumers are also profiled on their perceptions of retailer's use and abuse of data, along with the antecedents and outcomes of these perceptions. We employ a cross-sectional quantitative survey and collect data from a sample of 463 US consumers. For statistical analysis, we employ a latent class segmentation and identify six consumer segments which differ in their perceptions of the consumer-retailer data exchange. The key drivers of these segment differences include privacy concerns, technology readiness, and general trust of, and engagement with, retail brands. The segments also differ in their subsequent views towards the use and abuse of their data by retailers, including willingness to exchange data. Hence, when accessing and utilizing consumer data, it is important that brands identify different segments, and adapt their approach accordingly.     

An unrealistic and undesirable alternative to the right to be forgotten

In their “Così fan tutte: A better approach than the right to be forgotten”, Martha Garcia-Murillo and Ian MacInnes (2018) present an alternative to the right to be forgotten. It mainly consists of changing social norms to a more open and transparent society and improving anti-discrimination laws. In this reply, I challenge their suggestions both empirically and normatively, arguing that they cannot achieve what they set-out; that their analysis of privacy and the right to be forgotten misses important aspects that go beyond discrimination; and that we have a shared interest in allowing individuals to live a partly opaque life.