As algorithmic control (AC)—broadly defined as the managerial use of algorithms to direct, evaluate, and discipline workers—is increasingly implemented across a wide range of organisations, understanding how workers judge the legitimacy of AC becomes ever more critical. While prior research in this area often remains fixated on the effects of individual AC mechanisms, our study adopts a system-level perspective on AC. Specifically, we propose a three-layered conceptual framework for AC systems—consisting of (1) a control layer, (2) a data layer, and (3) an organisational embedding layer—and identify key design choices within each layer. Based on this framework, we conducted an experimental vignette study with 329 workers to assess how these design choices affect workers’ perceptions of autonomy and exploitation and, ultimately, their legitimacy judgments of AC systems. Our study advances research by shifting the focus beyond the level of individual control mechanisms to the system level and by providing empirical evidence that workers’ legitimacy judgments are highly sensitive to managerial design choices along all three layers. In particular, our results suggest that design choices within the data and organisational embedding layers are at least as critical as the AC mechanisms themselves in shaping workers’ judgments.

1. There has been a very significant number of paper submissions to EJIS in recent years on the topic of artificial intelligence (AI), with many of these focusing in some way on responsibility. Thi...

While the management of traditional, plan-based information systems development (ISD) projects lies with the information technology project manager (ITPM), this role is challenged in agile ISD team settings, characterised by self-managed and autonomous teams. Driven by the potential for individual, project, and organisational benefits through a deeper comprehension of these challenges, our study draws upon role identity theories to uncover identity tensions that this role creates and ways in which ITPMs engage in identity work to resolve these tensions. We conducted an in-depth, qualitative study involving interviews with ITPMs operating within agile ISD teams embedded in traditionally-managed organisations. A central contribution of our paper lies in the development of a theoretical model that unpacks how ITPMs navigate identity work tensions by engaging in specific identity work activities. By revealing the interplay between ITPMs’ role identity tensions, identity work activities, and contextual factors, our study moves beyond purely descriptive accounts and offers a nuanced understanding of the emotional and behavioural dimensions of ITPMs in their liminal position. Additionally, our work underscores the pivotal role of ITPMs as boundary spanners, bridging the gap between traditional and agile governance structures to drive digital transformation. For practitioners, we provide agile ISD team design recommendations.

Web seals have recently been subject to increasing skepticism from consumers. This study develops and tests a theoretical model of web seal skepticism by integrating multiple theoretical perspectives. We explore how web seal skepticism emerges and harms consumers’ perceptions. The results of an online experiment with 757 participants demonstrate that consumer skepticism increases consumers’ mistrust in information system providers and makes them feel less protected. Our findings also indicate that situational factors (web seal unreliability and seal authority incredibility) are significant antecedents of web seal skepticism and that consumers’ inferences of providers’ manipulative intent mediate the relationships.

Organisations increasingly rely on algorithms to exert automated managerial control over workers, referred to as algorithmic control (AC). The use of AC is already commonplace with platform-based work in the gig economy, where independent workers are paid for completing a given task (or “gig”). The combination of independent work alongside intensive managerial monitoring and guidance via AC raises questions about how gig workers perceive AC practices and judge their legitimacy, which could help explain critical worker behaviours such as turnover and non-compliance. Based on a three-dimensional conceptualisation of micro-level legitimacy tailored to the gig work context (autonomy, fairness, and privacy), we develop a research model that links workers’ perceptions of two predominant forms of AC (gatekeeping and guiding) to their legitimacy judgements and behavioural reactions. Using survey data from 621 Uber drivers, we find empirical support for the central role of micro-level legitimacy judgements in mediating the relationships between gig workers’ perceptions of different AC forms and their continuance intention and workaround use. Contrasting prior work, our study results show that workers do not perceive AC as a universally “bad thing” and that guiding AC is in fact positively related to micro-level legitimacy judgements. Theoretical and practical implications are discussed.

With the rise of COVID-19, decision support systems (DSS) increasingly display crowding information (CI) (e.g. how crowded a medical practice is) to encourage physical distancing when users select locations. Despite important implications for containing COVID-19, little is known about the causal effect of CI on user selection behaviour and how the immediacy of CI (e.g. “updated 2 minutes ago“) as well as users’ health anxiety further influence the effect of CI. Drawing on literature on digital choice environments and construal level theory, we conducted a multi-national online experiment to investigate the effect of CI on selecting differently crowded medical practices. Our results demonstrate that present (vs. absent) CI in DSS increases the likelihood of users selecting less crowded medical practices, while the effect is strongest when employed with real-time (vs. historical average) CI and, surprisingly, when users’ health anxiety is low (vs. high). Overall, our study adds to the growing body of research on IS in the age of pandemics and provides actionable insights for DSS providers and policymakers to endow users with information to identify and select less crowded locations, thus containing COVID-19 through improved physical distancing without paternalistically restricting users’ freedom of choice.

Until recently, organizations planning to acquire application software (AS) have had no choice but to adopt proprietary, on-premises software. With the advent of open-source and on-demand solutions, new models for developing and distributing software have entered the stage providing IS managers with more options in AS selection. On the basis of an Analytic Hierarchy Process model, we propose a framework including software package and implementation attributes on different hierarchy levels to examine how IS managers evaluate the relative fulfilment of key selection criteria by traditional, open-source, and on-demand office suites. By testing the framework with a random sample of 254 IS managers of 166 smaller and 88 mid-sized/larger firms, we validate its validity and usefulness in evaluating different software delivery models. Our empirical results show that open-source office suites were consistently perceived to be superior in meeting ease of customization (i.e., extensibility and adaptability) and cost criteria (i.e., acquisition and maintenance cost), whereas traditional software models were superior in fulfilling functionality, ease of use, and support requirements. On-demand office suites excelled in the fulfilment of time-to-value and data recoverability. We discuss further results of the comparison of the three software models, and derive practical and research implications for office suite selection.