Information Systems Journal最新文献

This study investigates inherent tensions between social media participation and the ways of life in an Indigenous community and subsequent navigation approaches. Relying on an in-depth qualitative study and the notion of two-eyed seeing as a theoretical approach, the study focuses on the complex relationship between social media platform participation and the ways of life in a ‘Guarani’ Indigenous community in South America. This community successfully navigates tensions between participation on social media platforms and preserving their traditional ways of life. We contribute to two streams of literature. First, we contribute to the literature on digital platforms and indigeneity showing that social media use by Indigenous communities leads to specific tensions, as these communities try to balance the use of social media with their desire to preserve their ways of life and protect the natural environment and how they navigate these tensions. Second, we contribute to the literature in relation to digital platforms and non-economic value as we unpack social and environmental value in the context of the Indigenous community and show that non-economic value benefits multiple entities. Overall, we contribute to a deeper understanding of how Indigenous communities navigate tensions between participation on social media and their traditional way of life. Our study also offers practical insights into how policy makers and designers of social media platforms can better meet Indigenous communities' needs.

Algorithms used in data analytics (DA) tools, particularly in high-stakes contexts such as hiring and promotion, may yield unfair recommendations that deviate from merit-based standards and adversely affect individuals. While significant research from fields such as machine learning and human–computer interaction (HCI) has advanced our understanding of algorithmic fairness, less is known about how managers in organisational contexts perceive and respond to unfair algorithmic recommendations, particularly in terms of individual-level distributive fairness. This study focuses on job promotions to uncover how algorithmic unfairness impacts managers' perceived fairness and their subsequent acceptance of DA recommendations. Through an experimental study, we find that (1) algorithmic unfairness (against women) in promotion recommendations reduces managers' perceived distributive fairness, influencing their acceptance of these recommendations; (2) managers' trust in DA competency moderates the relationship between perceived fairness and DA recommendation acceptance; and (3) managers' moral identity moderates the impact of algorithmic unfairness on perceived fairness. These insights contribute to the existing literature by elucidating how perceived distributive fairness plays a critical role in managers' acceptance of unfair algorithmic outputs in job promotion contexts, highlighting the importance of trust and moral identity in these processes.

The natural disaster response efforts are time-constrained, requiring quick and on-the-fly development and the adoption of technological innovations to meet the ever-changing contextual requirements. However, there are limited available insights on implementing and managing those ‘invented-on-the-fly’ innovations. This study draws upon sensemaking and technological frames to examine the adoption process of an on-the-fly developed mobile app in the context of the Gaja cyclone in India. Our findings inform that the adoption of technological innovation in disaster response is linked to its ‘features’ that actors draw upon in their sensemaking process and forming their technological frames. Initial sensemaking and technological framing may involve ‘concrete features’. However, the later sensemaking of evolving contingencies may include discovering various ‘abstract features’ in action. Discoveries of abstract features in action trigger reframing, leading to a congruent technological frame and better exploitation of innovations. Given that natural disasters are occurring more frequently, findings from our study provide critical insights into managing technology innovations in these contexts. The revelation of the role of features in technological (re)framing also enriches the analytical power of the technological frame lens.

Museums are vital cultural and educational institutions that play a key role in heritage preservation. Despite the importance of museums, the interaction between these conventional institutions and advanced technologies remains relatively underexplored in information systems (IS) research. Adopting affordance-actualisation (A–A) theory as the theoretical lens, we conducted an in-depth case study of the Palace Museum in Beijing, China, to investigate its implementation of evolving IS for heritage preservation. We identify three key affordances of these systems and develop a conceptual model illustrating the process of actualising these affordances. Our model extends A–A theory by adding an adaptation phase, wherein the museum responds to the outcomes of the actualisation process by amplifying the achieved outcomes and altering the unintended ones. Additionally, we uncover a hierarchical structure among these affordances, revealing a progressive pattern of actualisation specific to heritage preservation in museums. This research contributes to the literature on A–A theory, heritage preservation in museums, and IS implementation. Furthermore, it provides guidance for practitioners, particularly those in museum contexts, in effectively implementing IS for heritage preservation.

In this study, we examine the reflexivity modes of information systems (IS) professionals and integrate the IS context—including structural, technological, and social properties—with IS professionals' biographical, inner dialogues to theorise about the role of reflexivity modes in their experiences of psychological empowerment. Through the lens of Archer's (2007) three-stage model of reflexivity and different modes of reflexivity (communicative, autonomous, meta, and fractured), we investigate the experiences of psychological empowerment and project dynamics among IS professionals in IS development work by zooming in on 6 years of three IS professionals' work lives. Our findings make several contributions to theory and practice. First, we elucidate the interplay between reflexivity and psychological empowerment. Second, we show how different IS professionals' approach similar structural, technological, or social circumstances differently (such as agile work practices), depending on their reflexive inner dialogues. This includes showing how different reflexivity modes, focused on various properties of the IS context (structural, technological, and social), becomes entangled with interpersonal dynamics and IS project dynamics.

As a junior scholar, I used to be petrified of reviewers. Perhaps you are too. Reviewers, it appeared, were the ultimate arbiters of whether my paper could be published. Consequently, satisfying the reviewers became the be-all and end-all of the publication process. This fear of reviewers is not limited to junior scholars. As Allen Lee (cited in Davison, 2019) noted: ‘I believe that many or most seasoned researchers write with reviewers in mind, if not for the first submission, then certainly by the third revision. In fact, the exasperation is so great by the third or fourth revision that the general audience has completely disappeared from the author's mind and the author is left just wanting to address what the reviewers and editor want’. Even now, as I cross the 30-year mark as an academic who is both an editor and an author, reviewers can exert a baneful influence.

Although this is an editorial, I am conscious that I am writing it from both editorial and authorial perspectives. As an author, I am shielded by tenure to some degree, but my dean still hopes that I will publish in what he deems to be the top journals in the field (I may not agree about that) and has the carrots to induce compliance. Deans apart, I also enjoy conducting research and the writing process, so I can say that I write for my own pleasure. However, my papers also witness the sharp end of reviewers' tongues (or fingers) with comments that can be disheartening, destructive or ridiculous. What should I make of the reviewer who suggested that in future I should not bother with ethnographies because they are too subjective and instead collect survey data? Or the reviewer who advised that collecting data in China is of little value because it cannot be generalised to anywhere else, whereas data collected in the USA is universally generalisable. Honestly, I am not making this up; I could not! These perspectives are so far beyond the pale of reasonable human thinking as to be in the category of ‘truth is stranger than fiction’.

Meanwhile, as editor, I see the best and the worst of reviewers (and of course everything in between). Reviewers can be polite and constructive to a fault, but they can also be vicious, self-serving and/or just plain nasty, seeming to revel in their power to determine the fate of a manuscript. As editor, can I ‘edit’ the reviews before I send them to authors? Strictly speaking, this depends on publisher policy. At some journals, such editing is allowed, whereas at others it is not. I know one editor who routinely edits all reviewer comments for style and readability. But there are many editors who don't. Personally, I try not to micromanage the process unless it is really critical. Reviewers who are offensive will find their reviews rescinded, that is, returned with a request that they moderate their language or tone; some comply, others do not.

Nevertheless, conversations with my colleagues have reinforced that sense tha

Artificial intelligence (AI) platforms face distinct orchestration challenges in industry-specific settings, such as the need for specialised resources, data-sharing concerns, heterogeneous users and context-sensitive applications. This study investigates how these platforms can effectively orchestrate autonomous actors in developing and consuming AI applications despite these challenges. Through an analysis of five AI platforms for medical imaging, we identify four orchestration logics: platform resourcing, data-centric collaboration, distributed refinement and application brokering. These logics illustrate how platform owners can verticalize the AI development process by orchestrating actors who co-create, share and refine data and AI models, ultimately producing industry-specific applications capable of generalisation. Our findings extend research on platform orchestration logics and change our perspective from boundary resources to a process of boundary processing. These insights provide a theoretical foundation and practical strategies to build effective industry-specific AI platforms.