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

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

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

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

Input control and its signalling effects for complementors' intention to join digital platforms

2023 | Information Systems Journal | Citations: 2

Authors: Adam, Martin; Croitor, Evgheni; Werner, Dominick; Benlian, Alexander; Wiener, Martin

Abstract: Existing information systems (IS) research on platform control has largely focus ... Expand

Abstract: Existing information systems (IS) research on platform control has largely focused on examining how input control (i.e., the mechanisms used to control platform access) affects complementors' intentions and behaviours after their decision to join a digital platform. Yet, our understanding of how input control is perceived before this decision and how such perceptions influence prospective complementors' intention to join a platform is still nascent. In this regard, our study views input control as a salient signal that shapes prospective complementors' expected benefits and costs (i.e., their performance and effort expectancy), and ultimately their decision to join a digital platform. Drawing on signalling theory and the antecedent-benefit-cost (ABC) framework, we conducted a randomized online experiment in the context of donation-based crowdfunding. The experiment results offer empirical support for this view by showing that input control has distinct and complex signalling effects for prospective complementors. In particular, our findings reveal curvilinear and competing signalling effects, with perceived input control increasing both performance expectancy (at a decreasing rate) and effort expectancy (at an increasing rate). Also, we find that performance expectancy linearly increases prospective complementors' intention to join a platform, whereas effort expectancy linearly decreases their intention to do so. These findings imply that the overall relationship between perceived input control and intention to join follows an inverted U-shape curve, which means that neither a low nor a high, but a moderate degree of perceived input control maximizes prospective complementors' intention to join. In sum, the results of our study provide novel and important insights into the signalling role that perceived input control plays in shaping prospective complementors' decision to join a digital platform. Collapse

Topics: digital platform crowdsourcing crowdfunding behavioral intention digital ecosystem

Methods: experiment mediation analysis survey survey design theory development

Theories: signaling theory

Gamified monetary reward designs: Offering certain versus chance-based rewards

2023 | Information Systems Journal | Citations: 0

Authors: Adam, Martin; Reinelt, Annika; Roethke, Konstantin

Abstract: To motivate visitors to engage with websites, e-tailers widely employ monetary r ... Expand

Abstract: To motivate visitors to engage with websites, e-tailers widely employ monetary rewards (e.g., vouchers, discounts) in their website designs. With advances in user interface technologies, many e-tailers have started to offer gamified monetary reward designs (MRDs), which require visitors to earn the monetary reward by playing a game, rather than simply claiming the reward. However, little is known about whether and why gamified MRDs engage visitors compared to their non-gamified counterpart. Even less is known about the effectiveness of gamified MRDs when providing certain or chance-based rewards, in that visitors do or do not know what reward they will gain for successfully performing in the game. Drawing on cognitive evaluation theory, we investigate gamified MRDs with certain or chance-based rewards and contrast them to non-gamified MRDs with certain rewards in user registration systems. Our results from a multi-method approach encompassing the complementary features of a randomised field experiment (N = 651) and a randomised online experiment (N = 330) demonstrate differential effects of the three investigated MRDs on user registration. Visitors encountering either type of gamified MRD are more likely to register than those encountering a non-gamified MRD. Moreover, gamified MRDs with chance-based rewards have the highest likelihood of user registrations. We also show that MRDs have distinct indirect effects on user registration via anticipated experiences of competence and sensation. Overall, the paper offers theoretical insights and practical guidance on how and why gamified MRDs are effective for e-tailers. Collapse

Topics: website electronic mail electronic commerce gamification website design

Methods: experiment randomized field experiment survey experimental task mixed method

Theories: cognitive evaluation theory self determination theory

Online Labor Platforms and the Role of Job Security and Compensation (Mis)Fits for Gig Workers

2023 | International Conference on Information Systems | Citations: 1

Authors: Adam, Martin; Wiener, Martin; Benlian, Alexander

Abstract: Online labor platforms (OLPs) use algorithms to manage their workers. Prior res ... Expand

Abstract: Online labor platforms (OLPs) use algorithms to manage their workers. Prior research has examined how OLP management shapes workers' attitudes, implicitly assuming that workers have the same preferences. However, research has largely neglected the role of (mis)fits between what workers need and what they receive from OLPs. Therefore, we conducted a survey with 121 Mechanical Turk workers and used polynomial regression analysis of workers' actual needs and perceived OLP supplies. Our results suggest that higher job security fit decreases perceived exploitation and increases system satisfaction, whereas higher compensation fit decreases perceived exploitation. In addition, we find that job security misfit has decreasing marginal effects on perceived exploitation and increasing marginal effects on system satisfaction. Overall, we contribute to a more nuanced understanding of workers' reactions to the design of OLPs by shedding light on the interplay between what gig workers need and what they perceive to receive from such platforms. Collapse

Topics: IS satisfaction platform worker algorithmic management digital platform ride sharing platform

Methods: survey regression analysis method cross sectional research polynomial regression theoretical contribution

Human-in-Control: A Human-Centered Model of Adaptation to AI Augmentation

2023 | International Conference on Information Systems | Citations: 0

Authors: Afiouni, Rania; Pinsonneault, Alain

Abstract: Artificial Intelligence's (AI) potential to augment knowledge workers' jobs bri ... Expand

Abstract: Artificial Intelligence's (AI) potential to augment knowledge workers' jobs brings about significant transformation in their work, permeating their entire job beyond the automated tasks. Consequently, their established control perceptions can be disrupted. We therefore propose a model of worker adaptation to the AI work environment via personal control processes aimed at aligning the environment and the self. The Humanin-Control (HiC) model is a dialectical process of trust in AI's task execution ability and direct control over tasks that synthesizes in an expectation of delegation success leading to one of four control processes-expansive, opportunistic, investigative, preventive, and disengaging. The reached control state ranges from augmenting to reducing or, in extreme cases, slides down to uncontrollability. These states are transient, with feedback potentially prompting adaptive recalibration and state changes. Our study introduces personal control as an adaptive process in augmentation, expanding adaptation's scope and guiding human-centered empirical investigations of job-wide adaptation. Collapse

Topics: artificial intelligence knowledge work organizational context accounting

Methods: theory development synthesis

Remote Workers’ Privacy Concerns, Psychological Climate for Face Time, and Organizational Affective Commitment

2023 | HICSS | Citations: 0

Authors: Afota, Marie-Colombe; Cañibano, Almudena; Ollier-Malaterre, Ariane; Provost Savard, Yanick; Léon, Emmanuelle

Abstract: During the Covid-19 pandemic, the shift to high-intensity remote work—three days ... Expand

Abstract: During the Covid-19 pandemic, the shift to high-intensity remote work—three days or more a week—accelerated the digitalization of work processes on platforms such as Slack or Teams and the blurring of boundaries between work and personal life through videoconferencing and the use of personal devices for work. This paper explores the relationships between high-intensity remote workers’ information and communication technologies (ICT) privacy concerns, psychological climate for face time, and organizational affective commitment. Building on organizational support and social information processing theories, we argue that ICT privacy concerns and perceptions that an organization values physical presence in-office may undermine commitment to the organization. Based on a two-wave study of 1065 remote workers in a large multinational bank, we find that ICT privacy concerns and psychological climate for face time reinforce one another and are negatively associated with subsequent affective organizational commitment. Collapse

Topics: information privacy concern organizational commitment remote work IT supported collaboration privacy

Methods: statistical hypothesis test chi squared test longitudinal research SEM tool structural equation modeling

Theories: social information processing theory