AIS Electronic Library (AISeL)
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DATAFICATION AT WORK: NAVIGATING AI, PRIVACY CONCERNS, AND EMPLOYEE ENGAGEMENT
Full text linkOur study investigates the opportunities and challenges of increasing workplace datafication from an employee perspective. It focuses on how AI-driven data collection and analysis shape employee perceptions and influence their engagement levels. As AI becomes part of workplace operations, it introduces a complex balance between productivity gains and employee privacy, thereby influencing organizational outcomes. Using a quantitative survey, we will test the relationships between AI-driven datafication, privacy concerns, work-life conflict, productivity, and employee engagement. We specifically examine employee engagement as a key outcome, recognizing it as essential for organizational performance, retention, and job satisfaction. Overall, our study contributes to datafication research by examining the nuanced effects of increasing employee transparency on employee perceptions and attitudes. Our anticipated insights will support organizations as they navigate the complexities of datafication at work, helping them create balanced, employee-centred approaches to AI integration that promote employee engagement
The Hidden Journey: Data-Driven Insights Into E-Commerce Reverse Logistics
No full textAs e-commerce grows, so does the volume of consumer returns. Each return not only incurs costs, but also has negative environmental impacts. However, it has been difficult to quantify these effects as e-tailers withhold reverse logistics information for competitive and reputational reasons. This exploratory research project addresses this gap by leveraging tracking devices as an independent and reliable data source. The collected data provides unprecedented transparency into transportation distances and logistics practices. These insights will allow for a more accurate environmental assessment of returns, empowering consumers to make more informed decisions and incentivizing e-tailers to rethink their business decisions to adopt environmentally friendly strategies and shape greener digital marketplaces. By bridging information systems, logistics, and e-commerce, this work demonstrates the potential of interdisciplinary collaboration to address sustainability challenges and underscores the critical role of Green IS in fostering transparency, accountability, and sustainable development
Adapting to coercive forces: How foreign companies respond to China\u27s data protection regulations
No full textChina’s recent data protection regulations – the Cybersecurity Law, Data Security Law, and Personal Information Protection Law – establish a comprehensive framework for data governance that also encompasses foreign companies operating within or conducting business with China. This study empirically examines how foreign companies perceive and respond to these stringent regulations. Using coercive isomorphism as a theoretical framework and semi-structured interviews as a research methodology, this empirical work analyzes foreign companies’ interpretations of these regulations and their compliance strategies, including data localization, dual IT infrastructures, and administrative restructuring. Our findings show that while these strategies help achieve regulatory compliance, they introduce operational complexity, complicating the balance between local compliance and global cohesion. This work contributes to institutional theory by demonstrating how coercive pressure shapes organizational structures and operational strategies in multinational companies
Responsible Digital Transformation: A Corporate Governance Perspective
No full textFrom chatbot-run customer service to AI-supported decision-making, digital technologies reshape business operations, making digital transformation (DT) a strategic necessity for business preservation. Simultaneously, corporate responsibility (CR) is evolving through changing environmental and social imperatives reinforced by increasing regulations. While DT and CR obligations can align – digital solutions for energy efficiency – they also create tensions, e.g., amplifying the social divide. Here, I argue that balancing the occurring trade-offs has been neglected in previous joint conceptualisations of DT and CR. Through a literature review and synthesis, the study explores a corporate governance perspective, proposing a comprehensive and integrated understanding of Responsible Digital Transformation, contributing to a more balanced approach in IS research
Navigating the Metaverse: A Taxonomy for Metaverse-Driven Business Models
No full textThe metaverse, as an evolving concept that merges aspects of the real and virtual world, offers powerful economic potential for business models in organizations. Immersive experiences and new forms of interaction enable companies to create unique customer experiences and develop new business models through innovative ways of value creation. However, there is a lack of guidance on how metaverse-driven business models are structured and how they can be differentiated. Therefore, this study aims to contribute to a deeper understanding of the anatomy of metaverse-driven business models. To this end, we analyzed 100 start-ups from Crunchbase and developed a taxonomy of metaverse-driven business models consisting of eight dimensions and respective characteristics. Furthermore, we derived business model types through a cluster analysis. Our results provide a classification scheme to assess business models within the metaverse and to create economic value to remain competitive
Towards a Deployment-Aware Machine Learning Lifecycle
No full textArtificial intelligence (AI) and machine learning (ML) are transforming industries by enabling automation, optimization, and co-creation of business value. However, the deployment of ML models into production ecosystems and enterprise-wide information systems remains a significant challenge, partly due to the lack of standardized frameworks addressing the full ML lifecycle. While existing lifecycle models focus heavily on pre-deployment phases like data preparation and model training, critical post-deployment tasks such as monitoring, maintenance, and governance are often overlooked. To address this gap, we conduct a systematic mapping study to analyze existing ML lifecycle frameworks, identifying their limitations in post-deployment coverage. Building on these findings, we propose a research design to create a deployment-aware ML lifecycle, integrating empirical insights from multiple case studies across industries. This comprehensive framework aims to support practitioners in managing the complexities of real-world ML deployments and ensuring the sustainability of ML systems within dynamic organizational contexts
DECOMPOSING DEPRESSION: A COMPARATIVE STUDY ON SELF-DISCLOSURE USING WEB-SURVEYS AND CONVERSATIONAL AGENTS
No full textData quality has been a major challenge in precision healthcare. In this study, we used two data-gathering modalities, conversational agents (like chatbots) and web surveys, to explore how social structures, like genre rules associated with each modality, influence the content and structure of collected data, especially on sensitive topics such as depression. In general, these genre rules influence how participants interact and shape the information they disclose. Our results showed that the content and structure of self-disclosed information differ between modalities and that each modality also influences the depth and style of the information reported. We believe that these findings highlight the importance of carefully considering different data-gathering methods in precision healthcare and clinical research, particularly in experiment design
Opening Pandora’s Dox: Investigating Dynamics Among Doxing Actors Within Online Environments
No full textDoxing describes the malicious disclosure of individuals’ personal information on the internet. While existing literature recognizes that online platforms greatly facilitate the aggregation, disclosure, and dissemination of personal information, the specific mechanisms through which these platforms influence interactions among doxing actors, and consequently the progression of doxing incidents, remain unclear. To explore the dynamics—i.e., patterns of activities among actors—shaping doxing events in online environments, we conducted a qualitative multi-case study analyzing six real-world doxing incidents. Our findings reveal complex interaction patterns among human (doxers, doxees, and human audiences) and institutional actors (online platform operators and affiliated organizations). Additionally, we delineate the distinct roles of online platform types in facilitating doxing activities, including information research, communication, collaboration, and auxiliary functions. Our study holds significant implications for researchers investigating online platform-empowered adversarial social movements like doxing and offers valuable insights for practitioners aiming to mitigate its impacts
DETERMINANTS OF BLOCKCHAIN TECHNOLOGY ADOPTION AND ITS IMPACT ON FINANCIAL PERFORMANCE: AN EMPIRICAL STUDY OF JORDANIAN SMES
No full textThis paper explores the key factors influencing blockchain adoption and its impact on financial performance among small and medium sized enterprises (SMEs) in Jordan. Using survey data collected from 438 SMEs, we test a set of research hypotheses on adoption and performance. The findings review that adoption is positively influenced by relative advantage, compatibility, top management support, and organizational readiness, while complexity negatively impacts adoption. However, competitive pressures do not significantly influence adoption. Additionally, blockchain adoption is positively associated with improved financial performance in these enterprises
PLATFORM FEDERATIONS: AN ANALYSIS OF INTEGRATION USING GRAPH THEORY
No full textPlatform federations represent an emerging model in which independent host platforms selectively integrate functionalities from source platforms through specialized federation modules, creating a networked architecture that differs from traditional platform approaches. Through an empirical analysis of browser extensions that integrate AI source platforms across Chrome, Firefox, and Edge this study investigates the structural characteristics and governance dynamics of platform federations. Our analysis reveals that platform federations create double vertical complementarities and exhibit decentralized governance structures that balance integration with autonomy. These findings extend platform theory by conceptualizing federation-specific externalities and providing practitioners with strategic insights into operating in increasingly interconnected digital ecosystems. This study introduces a heterogeneous graph-based framework for analyzing platform federations, offering both theoretical and methodological contributions to understanding this emerging phenomenon