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

Value Creation Tradeoff in Business Ecosystems: Leveraging Complementarities While Managing Interdependencies

2023 | Organization Science | Citations: 0

Authors: Agarwal, Shiva; Kapoor, Rahul

Abstract: Complementary assets play an important role in shaping an innovation’s commercia ... Expand

Abstract: Complementary assets play an important role in shaping an innovation’s commercialization success. In this paper, we broaden the locus of complementarities to examine the role of complementary technologies residing in the business ecosystems that are becoming an important source of value creation for innovating firms. We argue that, on one hand, complementary technologies help innovations create more value for their users. On the other hand, they can also limit the focal innovation’s value creation by exposing them to performance bottlenecks as the underlying technological architecture of the ecosystem evolves. We further extend the notion of specialization of complementary assets to ecosystems by considering complementary technologies that are specialized to a focal ecosystem and those that are available across multiple ecosystems. We highlight that, although the complementary technologies that are specialized to an ecosystem facilitate greater value creation, they are more likely to subject the focal innovation to performance bottlenecks. Evidence from 244,034 apps launched by software developers for Apple’s iPhone ecosystem during 2008–2015 offers strong support for our framework. In summary, the study sheds light on the value creation tradeoff for firms innovating in business ecosystems—the opportunities associated with leveraging complementarities and the challenges associated with managing technological interdependencies. Funding: S. Agarwal was funded by the McCombs School of Business at The University of Texas at Austin [Research Excellence Grant]. Collapse

Topics: mobile application innovation management value creation Apple iPhone iOS

Methods: statistical hypothesis test instrumental variables estimation cross sectional research proportional hazards model robustness check

ETHICAL GUIDELINES FOR BLOCKCHAIN SYSTEMS

2023 | European Conference On Information Systems | Citations: 0

Authors: Agerskov, Signe; Pedersen, Asger; Beck, Roman

Abstract: Enterprise architects and IT systems developers must often decide ad hoc how to ... Expand

Abstract: Enterprise architects and IT systems developers must often decide ad hoc how to identify, assess and mitigate ethical issues of autonomous, rule-based systems based on blockchain technology. As blockchain systems are decentralized and immutable, developers must assess ethical risks, not only on an individual level but also on a network level along the life-cycle stages of a blockchain system. These ethical issues should be addressed and ideally mitigated by clearly defined norms and values that are intentionally incorporated in a blockchain system. As a reference for a normative system, we have chosen the European Union and its ethical values to discuss them in the context of ethical issues emerging from blockchain systems. This paper presents a top-down approach that establishes ethical guidelines for blockchain systems based on ethical issues mapped against European values. Collapse

Topics: blockchain smart contract data encryption privacy supply chain management

Methods: literature sample literature study case study computational algorithm triangulation

How Review Quality and Source Credibility Interacts to Affect Review Usefulness: An Expansion of the Elaboration Likelihood Model

2023 | Information Systems Frontiers | Citations: 0

Authors: Aghakhani, Navid; Oh, Onook; Gregg, Dawn; Jain, Hemant

Abstract: This study extends our understanding of what makes an online review useful by ex ... Expand

Abstract: This study extends our understanding of what makes an online review useful by examining the effects of review quality (i.e., as a composite variable of review comprehensiveness and review topic consistency) on review usefulness, and the moderating effects of source credibility on the relationship between review quality and review usefulness. The Elaboration Likelihood Model, convergence theory, and cueing effect literature are used to define the variables of review comprehensiveness and review topic consistency. Analyses of 27,517 restaurant reviews from Yelp show that review topic consistency has a positive effect on review usefulness, but, contrary to our hypothesis, review comprehensiveness has a negative effect on review usefulness. We also found source credibility positively moderates the effect of review comprehensiveness on review usefulness, but negatively moderates the effect of review topic consistency on review usefulness. Theoretical and practical implications are discussed. Collapse

Topics: online review user-generated content Python website data breach

Methods: topic model term frequency–inverse document frequency NLTK statistical hypothesis test robustness check

Theories: elaboration likelihood model

Design Science Research: Progression, Schools of Thought and Research Themes

2023 | DESRIST | Citations: 0

Authors: Akoka, Jacky; Comyn-Wattiau, Isabelle; Storey, Veda C.

Abstract: Design science research, a well-established research approach to solving complex ... Expand

Abstract: Design science research, a well-established research approach to solving complex real-world problems, has evolved over time. This research characterizes design science research in information systems. By performing a bibliometric analysis, we show that design science research has progressed in the information systems field through three main phases, which we call periods of inquiry. A co-citation analysis shows that the progression has been largely influenced by a few main pioneering studies, leading to three schools of thought. Bibliographic coupling analysis suggests that research in design science can be classified into several distinct intellectual areas corresponding to different research themes. This bibliometric analysis proposes a broad viewpoint of design science and design research, serving as a basis for shaping further research. Collapse

Topics: blockchain database system

Methods: design science co-citation analysis literature sample bibliometric analysis cluster analysis

Self-Building Artificial Intelligence and Machine Learning to Empower Big Data Analytics in Smart Cities

2023 | Information Systems Frontiers | Citations: 0

Authors: Alahakoon, Damminda; Nawaratne, Rashmika; Xu, Yan; De Silva, Daswin; Sivarajah, Uthayasankar; Gupta, Bhumika

Abstract: The emerging information revolution makes it necessary to manage vast amounts of ... Expand

Abstract: The emerging information revolution makes it necessary to manage vast amounts of unstructured data rapidly. As the world is increasingly populated by IoT devices and sensors that can sense their surroundings and communicate with each other, a digital environment has been created with vast volumes of volatile and diverse data. Traditional AI and machine learning techniques designed for deterministic situations are not suitable for such environments. With a large number of parameters required by each device in this digital environment, it is desirable that the AI is able to be adaptive and self-build (i.e. self-structure, self-configure, self-learn), rather than be structurally and parameter-wise pre-defined. This study explores the benefits of self-building AI and machine learning with unsupervised learning for empowering big data analytics for smart city environments. By using the growing self-organizing map, a new suite of self-building AI is proposed. The self-building AI overcomes the limitations of traditional AI and enables data processing in dynamic smart city environments. With cloud computing platforms, the self-building AI can integrate the data analytics applications that currently work in silos. The new paradigm of the self-building AI and its value are demonstrated using the IoT, video surveillance, and action recognition applications. Collapse

Topics: artificial intelligence smart city big data cloud computing distributed system

Methods: computational algorithm experiment unsupervised learning machine learning longitudinal research

Explaining Explainable Artificial Intelligence: An integrative model of objective and subjective influences on XAI

2023 | HICSS | Citations: 0

Authors: Alarcon, G.; Willis, S.

Abstract: Explainable artificial intelligence (XAI) is a new field within artificial inte ... Expand

Abstract: Explainable artificial intelligence (XAI) is a new field within artificial intelligence (AI) and machine learning (ML). XAI offers transparency of AI and ML that can bridge the gap in information that has been absent from "black-box" models. Given its nascency, there are several taxonomies of XAI in the literature. The current paper incorporates the taxonomies in the literature into one unifying framework, which defines the types of explanations, types of transparency, and model methods that together inform the user's processes towards developing trust in AI and ML systems. Collapse

Topics: artificial intelligence explainable artificial intelligence usability human computer interaction

Methods: computational algorithm theory development artificial neural network

Social media platforms and social enterprise: Bibliometric analysis and systematic review

2023 | International Journal of Information Management | Citations: 0

Authors: Ali, Imran; Balta, Maria; Papadopoulos, Thanos

Abstract: A considerable number of contributions at the intersection of social media platf ... Expand

Abstract: A considerable number of contributions at the intersection of social media platforms and social entrepreneurship has been witnessed over the past decade. The multi-disciplinary nature of current literature necessitates inte­ grative insights on the topic. We thus undertake a two-pronged approach – bibliometric analysis followed by systematic review – to map the extant literature in a structured, objective, and quantitative way. We contribute to the literature as we (i) offer a classification of the literature in three clusters, namely ‘social media platforms, social collaboration and social marketing’, ‘social media platforms and crowdfunding, and ‘social media plat­ forms and crowdsourcing’; (ii) analyze recent research development in each cluster, methodological develop­ ment, countries co-authorship and evolution of research in the area; and (iii) propose a conceptual framework -accompanied by research propositions- that provides an overview of the literature at the intersection of social media platforms, various social entrepreneurial practices and their influence on the social enterprise perfor­ mance. Our review culminates with numerous impactful research avenues for scholarly progression in the area. From a practical standpoint, this review integrates scattered findings into one body, allowing the practitioners and policymakers to discern the role of social media platforms in dealing with emerging societal problems and increasing operational efficiencies of social enterprises (SEs). To the best of our knowledge, this is the first review of its kind, offering unique perspectives at the nexus of social media platforms and SE’s performance. Collapse

Topics: social media crowdsourcing marketing management crowdfunding digital platform

Methods: literature sample bibliometric analysis literature study structured literature research co-citation analysis

Theories: structuration theory dynamic capabilities theory

Measuring Workers’ Perceptions of Algorithmic Control: Item Development and Content Validity Assessment

2023 | HICSS | Citations: 0

Authors: Alizadeh, Armin; Hirsch, Felix; Benlian, Alexander; Wiener, Martin; Cram, W. Alec

Abstract: Algorithmic control (AC) refers to organizations’ use of increasingly intelligen ... Expand

Abstract: Algorithmic control (AC) refers to organizations’ use of increasingly intelligent algorithms and related digital technology to steer worker behavior. While previous studies have identified and conceptualized various forms of AC in both platform and traditional work contexts, the presented conceptualizations lack measurability. This key shortcoming hampers further empirical research on the current use of AC and its manifold consequences. In this study, we report on the item development process for a scale for measuring perceived AC from a workers’ perspective. Following well-established approaches, an initial item pool was developed. The items were discussed and refined with the support of five academic experts and three AC workers. A subsequent rating study with 98 workers was conducted to ensure the content validity of all items. On this basis, the study at hand presents a comprehensive set of items for both AC in general and its seven sub-dimensions. Collapse

Topics: platform worker organizational context technostress database system ride sharing platform

Methods: qualitative interview survey design card sorting computational algorithm survey

Perceived Algorithmic Control: Conceptualization and Scale Development

2023 | European Conference On Information Systems | Citations: 1

Authors: Alizadeh, Armin; Hirsch, Felix; Benlian, Alexander; Wiener, Martin; Cram, W.

Abstract: Organizations today leverage big data analytics combined with modern informatio ... Expand

Abstract: Organizations today leverage big data analytics combined with modern information and communication technology (ICT) to control workers in a largely automated manner. This phenomenon is commonly referred to as algorithmic control (AC). Research has shown that worker perceptions of AC applications can impact critical outcomes such as worker resistance, continuance intention, and well-being. Despite recent efforts to better understand these worker-level effects of AC, no systematic measures of workers' perceptions of AC exist to date. In this study, we develop and present a scale to empirically measure AC at the worker level. In particular, following established scale development guidelines, we conceptualize AC in terms of seven distinct forms, and derive, evaluate, and validate a final set of 33 measurement items. In doing so, our study paves the way for a much-needed, more systematic investigation of AC and its worker-level implications. Collapse

Topics: database system video conference social media

Methods: qualitative interview survey design psychometrics card sorting descriptive statistic