Data Science for Social Good

2023 | Journal of the Association for Information Systems | Citations: 0

Authors: Abbasi, Ahmed; Chiang, Roger; Xu, Jennifer

Abstract: Data science has been described as the fourth paradigm of scientific discovery. ... Expand

Abstract: Data science has been described as the fourth paradigm of scientific discovery. The latest wave of data science research, pertaining to machine learning and artificial intelligence (AI), is growing exponentially and garnering millions of annual citations. However, this growth has been accompanied by a diminishing emphasis on social good challenges-our analysis reveals that the proportion of data science research focusing on social good is less than it has ever been. At the same time, the proliferation of machine learning and generative AI has sparked debates about the sociotechnical prospects and challenges associated with data science for human flourishing, organizations, and society. Against this backdrop, we present a framework for "data science for social good" (DSSG) research that considers the interplay between relevant data science research genres, social good challenges, and different levels of sociotechnical abstraction. We perform an analysis of the literature to empirically demonstrate the paucity of work on DSSG in information systems (and other related disciplines) and highlight current impediments. We then use our proposed framework to introduce the articles appearing in the JAIS special issue on data science for social good. We hope that this editorial and the special issue will spur future DSSG research and help reverse the alarming trend across data science research over the past 30-plus years in which social good challenges are attracting proportionately less attention with each passing day. Collapse

Topics: societal evaluation criteria digital dashboard productivity social media pandemic

Methods: word embedding literature study literature sample longitudinal research design science

Examining the case of French hesitancy toward IDaaS solutions: Technical and social contextual factors of the organizational IDaaS privacy calculus

2023 | Information & Management | Citations: 0

Authors: Abdalla Mikhaeil, Christine; James, Tabitha L.

Abstract: Identity-as-a-service (IDaaS) is a cloud security service to which companies can ... Expand

Abstract: Identity-as-a-service (IDaaS) is a cloud security service to which companies can outsource the identity and access management (IAM) functions that administer their employee’s access to organizational resources. Engaging with the information systems (IS) privacy literature, our qualitative analysis develops a framework for an organiza­ tional privacy calculus that informs French organizational consumers’ decisions to pursue IDaaS solutions. We collect data from employees of a multinational IDaaS provider operating in Europe but headquartered in the US. Our case study reveals the organizational privacy calculus associated with transferring control of a primary security control to a multinational cloud service provider. Collapse

Topics: cloud computing information privacy concern marketing management privacy internet of things

Methods: qualitative interview case study company material single case study personal interview

Theories: privacy calculus theory

How AI-Based Systems Can Induce Reflections: The Case of AI-Augmented Diagnostic Work

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Abdel-Karim, Benjamin; Pfeuffer, Nicolas; Carl, K. Valerie; Hinz, Oliver

Abstract: This paper addresses a thus-far neglected dimension in human-artificial intelli ... Expand

Abstract: This paper addresses a thus-far neglected dimension in human-artificial intelligence (AI) augmentation: machine-induced reflections. By establishing a grounded theoretical-informed model of machine-induced reflection, we contribute to the ongoing discussion in information systems (IS) regarding AI and research on reflection theories. In our multistage study, physicians used a machine learning-based (ML) clinical decision support system (CDSS) to see if and how this interaction can stimulate reflective practice in the context of an X-ray diagnosis task. By analyzing verbal protocols, performance metrics, and survey data, we developed an integrative theoretical foundation to explain how ML-based systems can help stimulate reflective practice. Individuals engage in more critical or shallower modes depending on whether they perceive a conflict or agreement with these CDSS systems, which in turn leads to different levels of reflection depth. By uncovering the process of machine-induced reflections, we offer IS research a different perspective on how such AI-based systems can help individuals become more reflective, and consequently more effective, professionals. This perspective stands in stark contrast to the traditional, efficiency-focused view of MLbased decision support systems and also enriches theories on human-AI augmentation. Collapse

Topics: artificial intelligence decision making decision support system algorithmic transparency recommender system

Methods: cognitive walkthrough survey theory development qualitative interview Student's t-test

Theories: learning theory information systems theory theory of abduction

Maintaining or Altering the Status Quo in the Nonmarket Arena: Theory and Evidence from Government Contract Disputes

2023 | Organization Science | Citations: 0

Authors: Abdurakhmonov, Mirzokhidjon; Hasija, Dinesh; Ridge, Jason W.; Hill, Aaron D.

Abstract: We develop a theory that considers important differences in competition in the p ... Expand

Abstract: We develop a theory that considers important differences in competition in the political arena based on whether firms are attempting to maintain or alter the status quo. Particularly, we argue that although investing resources and time to build relationships with politicians and government officials fosters trust, solidarity, and reciprocity, likely producing desired outcomes for both firms attempting to maintain the status quo and those trying to alter it, such relationships are more strongly positive for firms maintaining the status quo. As the effectiveness of relational strategies may differ based on firms’ political strategies and firm characteristics, we then theorize that the effects of a more relational approach on ”winning” these desired outcomes for firms seeking to maintain or alter the status quo will be moderated by (1) prior targeting in the political arena where the competition unfolds and (2) a firm’s social reputation. Specifically, we argue that knowledge and relationships from prior targeting in a political domain where competition unfolds, and a firm’s better social reputation will strengthen the effect of a more relational approach on securing desired outcomes for both firms seeking to maintain and alter the status quo. We expect the moderating effect for a firm’s targeting and social reputation will be stronger for firms seeking to maintain the status quo compared with firms seeking to alter the status quo. Our study contributes to corporate political activity literature and notably to the research on political markets by advancing a more nuanced but realistic understanding of interfirm rivalry for governmental outcomes. Collapse

Topics: resource allocation database system competitive advantage legal context anonymity

Methods: theory development statistical hypothesis test chi squared test cluster analysis Compustat

Theories: resource based view of the firm

Introduction to the Minitrack on Explainable Artificial Intelligence (XAI)

2023 | HICSS | Citations: 0

Authors: Abedin, B.; Meske, C.; Rabhi, F.; Klier, M.

Abstract: Artificial Intelligence (AI) already reached or even surpassed the task perform ... Expand

Abstract: Artificial Intelligence (AI) already reached or even surpassed the task performance of humans in various domains. However, most AI systems are still "black boxes" that are difficult to comprehend -not only for developers, but also for users and decision-makers. Explainable Artificial Intelligence (XAI) is aimed at intelligent systems that are highly performant to enable their users to understand, appropriately trust, and scrutinize them. Collapse

Topics: explainable artificial intelligence artificial intelligence

Methods: experiment structured literature research

Responsible Digital Innovation in Dark: Toward Access-Control-Transparency Theory

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Abhari, Kaveh; Xiao, Bo; Eisenberg, David

Abstract: As the world moves ever forward into a digital future, the need for responsible ... Expand

Abstract: As the world moves ever forward into a digital future, the need for responsible digital innovation (RDI) becomes increasingly urgent. This paper presents the access-control-transparency (ACT) theory, a simple yet powerful framework for guiding designers and developers in creating digital artifacts that embody the principles of responsible design. With a focus on promoting access, control, and transparency, this theory aims to address the dark side of digital innovation and ensure that new technologies are developed in a way that considers their impact on individuals, communities, and society. The paper also explores avenues for future research, including the impact of ACT-driven design principles on organizational and societal outcomes, the role of individual and organizational values in the RDI process, and the incorporation of human-centric design and ongoing reflection into the ACT theory. Collapse

Topics: innovation management digital innovation access control

Methods: theory development synthesis design artifact

None

2023 | HICSS | Citations: 0

Authors: Abhari, K.; Xiao, B.

Abstract: ... Expand

Abstract: Collapse

Topics: sharing platform platform worker cryptocurrency communities of practice platform work site

Theories: theory of affordance

A Systematic Review of Blockchain-based Loyalty Programs

2023 | HICSS | Citations: 0

Authors: Abooleet, Saeed; Kinnett, Seth

Abstract: Customer loyalty programs, the incentive structures designed to reward and retai ... Expand

Abstract: Customer loyalty programs, the incentive structures designed to reward and retain customers for purchases and other activities, have struggled to maximize their intended goals. Academics and industry practitioners have advocated for the use of blockchain technology as a vehicle to revolutionize loyalty programs. Despite this hype, we have yet to see an examination of existing blockchain-based loyalty solutions. This paper identifies, reviews, and classifies tokenized loyalty solutions. Using a web-scraping method, we systematically retrieved 9,642 tokens listed on the coinmarketcap.com website. Multiple applications of inclusion/exclusion criteria resulted in 21 active loyalty programs based on blockchain, which we evaluated in depth. Our findings confirm that the domain is nascent yet more actualized than previous research has suggested. This analysis fills a much-needed role in the blockchain-loyalty literature by providing an industry lens into the realities of blockchain as a loyalty solution. Collapse

Topics: blockchain cryptoasset crypto exchange customer loyalty website

Methods: descriptive statistic structured literature research

The Impact of Use of Big Data-Driven Systems on Decision-Makers’ Power

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Abouei, Mahdi; Ansari, Kimia; Ghasemaghaei, Maryam

Abstract: Modern organizations are adopting Big Data-Driven (BDD) systems to obtain and s ... Expand

Abstract: Modern organizations are adopting Big Data-Driven (BDD) systems to obtain and sustain their competitive advantage through improved decisions. However, the changes in the organizational decision structure and processes due to the establishment of these systems raised the question of how becoming data-driven will affect the traditional role of human decision-makers in organizations. Specifically, this research-in-progress study investigates the mechanisms through which the use of BDD systems impacts organizational decisionmakers' power. To address this research question, the study draws on the premises of the strategic contingencies theory of intra-organizational power and the literature on BDD decision-making in organizations and develops a theoretical model to be tested empirically. Ultimately, the potential contributions to theory and practice are also discussed. KeywordsBig data-driven systems, decision-making, strategic contingencies theory of intra-organizational power. Collapse

Topics: decision making IS impact business process management

Methods: survey theory development cross sectional survey structural equation modeling cross sectional research

A taxonomy of data governance decision domains in data marketplaces

2023 | Electronic Markets | Citations: 0

Authors: Abraham, Rene; Schneider, Johannes; vom Brocke, Jan

Abstract: Commercializing data and data-related services has gained in importance in recen ... Expand

Abstract: Commercializing data and data-related services has gained in importance in recent years. Driven by digitalization and the Internet-of-Things (IoT), companies and individuals continuously generate vast amounts of data. Data marketplaces have emerged to support these data providers in selling their data to different data consumers. However, data marketplaces face challenges in different data governance decision domains that inhibit their adoption. To get a better understanding of how data marketplaces counteract these challenges, this paper develops a taxonomy of data governance decision domains in data marketplaces. We used a taxonomy development method to inspect 13 data marketplaces from eight countries. The resulting taxonomy shows an overview of mechanisms concerning data quality, data security, data architecture, metadata, data lifecycle, data storage, and data pricing. We discuss common instantiation patterns, highlight gaps, and propose possible solutions. The taxonomy sets a foundation for further research and theory-building on data marketplaces. Practitioners can use the taxonomy to develop customized data governance strategies for data marketplaces. Collapse

Topics: data governance price management system development method computer data storage website

Methods: design artifact data modeling design methodology design science company material