Knowledge contributions in design science research: Paths of knowledge types

2023 | Decision Support Systems | Citations: 0

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

Abstract: Design science research addresses important, complex real-world problems. Althou ... Expand

Abstract: Design science research addresses important, complex real-world problems. Although well-accepted as part of research in information systems, initiating or progressing a design science research project still requires effort to describe how knowledge creation emerges and its underlying dynamics. Given the existing body of knowledge on design science research, it should be possible to learn from that knowledge to progress future work. This paper analyzes design science research projects to identify and make explicit their knowledge contributions while recognizing the plurality of a project's knowledge contributions with respect to a project's knowledge scope and knowledge goals. The construct of a path of knowledge types is introduced that represents how knowledge con­ tributions are dynamically created throughout a project. These paths form the basis for the derivation of seven design science research strategies, which lead to guidelines for initiating or progressing a project. This effort is compared to other research that analyzes the growing body of work in design science with respect to knowledge contributions and project classifications. Collapse

Topics: knowledge type decision support system IT project management innovation management anonymity

Methods: design science literature sample literature study design artifact design principle

The role of system-use practices for sustaining motivation in crowdsourcing: A technology-in-practice perspective

2023 | Information Systems Journal | Citations: 0

Authors: Alam, Sultana Lubna; Sun, Ruonan

Abstract: The success of crowdsourcing (CS) systems depends on sustained participation, wh ... Expand

Abstract: The success of crowdsourcing (CS) systems depends on sustained participation, which is an ongoing challenge for the majority of CS providers. Unfortunately, participants are frequently demotivated by technical difficulties and the incorrect use of CS systems, which can result in CS failure. Although the literature generally assumes that sustained participation in CS is determined by a shift between intrinsic and extrinsic motivation, the role of system-use practices in facilitating such a shift remains unknown. We explore how CS system-use practices influence participants' sustained motivation, evolving from initiation to progression to sustention. Using the notion of technology-in-practice as a lens, we develop and examine a process model using an in-depth case study of a large-scale ongoing CS project, the Australian Newspaper Digitisation Program. The findings suggest that CS participants' motivation is shaped by an evolving combination of three basic components (i.e., contextual condition, outcome and action intensity) and mediated by two types of system-use practice (i.e., passive and active). Passive-use practices facilitate sustaining motivation from initiation to progression, whereas active-use practices have a key role in sustention. Our study contributes to the emerging literature on the substantial role of system-use practices in sustaining motivation, resulting in sustained participation. The findings also offer actionable insights into improving the viability of CS systems in retaining and motivating continuous and increased contributions from participants. Collapse

Topics: information system use strategic management intrinsic motivation

Methods: qualitative interview case study business process modeling theory development synthesis

Theories: technology acceptance 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

Dynamics of Trust: Unpacking Trust in Human-AI Collaboration in Decision-Making

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Baduna, Maryam; Hylving, Lena

Abstract: This literature review examines trust in AI-augmented decision-making systems i ... Expand

Abstract: This literature review examines trust in AI-augmented decision-making systems in collaborative settings. The analysis suggests that human characteristics, AI characteristics, the decision-making environment, and the collaboration setting are antecedents of human trust in AI. This literature review contributes to the theoretical knowledge of trust with a dynamic learned trust framework, which represents an integrated understanding of trust in AI in human-AI collaborative decision-making. The review also provides practical implications for AI designers and implementors for improving the trustworthiness and adoption of AI for human-AI collaboration. By providing insight for researchers and audiences in information systems, organization and management, this paper can serve as a starting point for investigating the nuances, complexities and dynamics of trust in human-AI relationships. Collapse

Topics: decision making artificial intelligence human AI collaboration human computer interaction expert system

Methods: literature study literature sample computational algorithm synthesis machine learning

What Makes Digital Technology? A Categorization Based on Purpose

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

Authors: Baier, Marie-Sophie; Berger, Stephan; Kreuzer, Thomas; Oberländer, Anna; Röglinger, Maximilian

Abstract: Digital technology (DT) is creating and shaping today's world. Building on its ... Expand

Abstract: Digital technology (DT) is creating and shaping today's world. Building on its identity and history of technology research, the Information Systems discipline is at the forefront of understanding the nature of DT and related phenomena. Understanding the nature of DT requires understanding its purposes. Because of the growing number of DTs, these purposes are diversifying, and further examination is needed. To that end, we followed an organizational systematics paradigm and present a taxonomic theory for DT that enables its classification through its diverse purposes. The taxonomic theory comprises a multi-layer taxonomy of DT and purpose-related archetypes, which we inferred from a sample of 92 real-world DTs. In our empirical evaluation, we assessed the reliability, validity, and usefulness of the taxonomy and archetypes. The taxonomic theory exceeds existing technology classifications by being the first that (1) has been rigorously developed, (2) considers the nature of DT, (3) is sufficiently concrete to reflect the diverse purposes of DT, and (4) is sufficiently abstract to be persistent. Our findings add to the descriptive knowledge on DT, advance our understanding of the diverse purposes of DT, and lay the ground for further theorizing. Our work also supports practitioners in managing and designing DTs. Collapse

Topics: knowledge base perceived usefulness competitive advantage decision making technology adoption

Methods: cluster analysis theory development longitudinal data analysis focus group computational algorithm

Theories: information systems theory sociomaterialism theory

Self-reporting Limitations in Information Systems Design Science Research

2023 | Business & Information Systems Engineering | Citations: 0

Authors: Barata, João; da Cunha, Paulo Rupino; de Figueiredo, António Dias

Abstract: Besides increasing transparency and demonstrating awareness of the author, self- ... Expand

Abstract: Besides increasing transparency and demonstrating awareness of the author, self-reported limitations enable other researchers to effectively learn from, build on, validate, and extend the original work. However, this topic is understudied in information systems design science research (IS DSR). The study has assessed 243 IS DSR papers published in the period 2013–2022 and built a typology of the 19 most relevant limitations, organized into four categories: (1) Input Knowledge and Technology, (2) Research Process, (3) Resulting Artifact, and (4) Design Knowledge. Further, the contribution suggests actions to mitigate each type of limitation throughout the entire IS DSR project lifecycle. The authors have also created guidelines to report the limitations in a useful way for knowledge accumulation. The proposed typology and guidelines enable reviewers and editors to better frame self-reported limitations, assess rigor and relevance more systematically, and provide more precise feedback. Moreover, the contribution may help design researchers identify, mitigate, and effectively communicate the uncertainties inherent to all scientific advances. Collapse

Methods: literature sample literature study design science theory development synthesis

Digital Transformation: From Traditional IS Theories to Emerging Assemblage

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Aryal, arun; AMRANI, REDOUANE EL; Wu, Crystal

Abstract: Digital transformation (DT) is a complex and dynamic phenomenon that requires a ... Expand

Abstract: Digital transformation (DT) is a complex and dynamic phenomenon that requires a significant shift in organizational culture and mindset, necessitating new theoretical perspectives to understand the interactions between technology and people. This article conducts a critical literature review of the extant literature on DT, contrasting traditional Information Systems (IS) theories with assemblage theory. Assemblage theory provides a dynamic framework to analyze the various components of DT and their interactions, acknowledging the significance of power dynamics and politics in shaping the direction and outcomes of DT initiatives. This paper provides different theoretical perspectives in digital transformation literature by analyzing 70 articles published in premier IS journals. This article is helpful for scholars and practitioners interested in understanding the complexities of DT through assemblage theory perspectives. Collapse

Topics: digital transformation database system diffusion of innovation innovation management

Methods: literature study literature sample qualitative coding cross sectional research theory development

Theories: information systems theory institutional theory dynamic capabilities theory diffusion of innovations theory knowledge management theory

Algorithmic Transparency: Concepts, Antecedents, and Consequences – A Review and Research Framework

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

Authors: Bitzer, Tobias; Wiener, Martin; Cram, W. Alec

Abstract: The widespread and growing use of algorithm-enabled technologies across many as ... Expand

Abstract: The widespread and growing use of algorithm-enabled technologies across many aspects of public and private life is increasingly sparking concerns about the lack of transparency regarding the inner workings of algorithms. This has led to calls for (more) algorithmic transparency (AT), which refers to the disclosure of information about algorithms to enable understanding, critical review, and adjustment. To set the stage for future research on AT, our study draws on previous work to provide a more nuanced conceptualization of AT, including the explicit distinction between AT as action and AT as perception. On this conceptual basis, we set forth to conduct a comprehensive and systematic review of the literature on AT antecedents and consequences. Subsequently, we develop an integrative framework to organize the existing literature and guide future work. Our framework consists of seven central relationships: (1) AT as action versus AT as perception; factors (2) triggering and (3) shaping AT as action; (4) factors shaping AT as perception; as well as AT as perception leading to (5) rational-cognitive and (6) affective-emotional responses, and to (7) (un-)intended behavioral effects. Building on the review insights, we identify and discuss notable research gaps and inconsistencies, along with resulting opportunities for future research. review of the literature on AT. Not only has such an endeavor, to our knowledge, not yet been undertaken; but more importantly, we expect that such a review will reveal critical research gaps and inconsistencies and inform future research in the area. In particular, we aim to extend past work and contribute to the extant body of knowledge by (1) strengthening the conceptual foundations of AT; (2) reviewing the AT literature in a systematic manner; and (3) deriving a research framework. In doing so, our study offers a more nuanced conceptualization of AT, including the explicit distinction between AT as action and AT as perception, and delineates AT from related concepts. Moreover, following established guidelines (e.g., vom Brocke et al., 2015;Okoli & Schabram, 2010;Paré et al., 2015;Webster & Watson, 2002) and drawing on a review sample of 50 studies (published between 2002 and 2021), our study offers a comprehensive review and synthesis of prior research on the antecedents and consequences of AT. Finally, we propose an integrative framework to organize existing and guide future work. Collapse

Topics: database system algorithmic transparency artificial intelligence website digital service

Methods: computational algorithm literature study synthesis mixed method archival research

Explainable artificial intelligence in information systems: A review of the status quo and future research directions

2023 | Electronic Markets | Citations: 4

Authors: Brasse, Julia; Broder, Hanna Rebecca; Förster, Maximilian; Klier, Mathias; Sigler, Irina

Abstract: The quest to open black box artificial intelligence (AI) systems evolved into an ... Expand

Abstract: The quest to open black box artificial intelligence (AI) systems evolved into an emerging phenomenon of global interest for academia, business, and society and brought about the rise of the research field of explainable artificial intelligence (XAI). With its pluralistic view, information systems (IS) research is predestined to contribute to this emerging field; thus, it is not surprising that the number of publications on XAI has been rising significantly in IS research. This paper aims to provide a comprehensive overview of XAI research in IS in general and electronic markets in particular using a structured literature review. Based on a literature search resulting in 180 research papers, this work provides an overview of the most receptive outlets, the development of the academic discussion, and the most relevant underlying concepts and methodologies. Furthermore, eight research areas with varying maturity in electronic markets are carved out. Finally, directions for a research agenda of XAI in IS are presented. Collapse

Topics: explainable artificial intelligence artificial intelligence user requirement electronic market user experience

Methods: literature study literature sample cluster analysis synthesis machine learning

Theories: information systems theory activity theory agency theory attribution theory cognitive fit theory

An immodest proposal – going “All in” on replication research in information systems

2023 | European Journal of Information Systems | Citations: 0

Authors: Brendel, Alfred Benedikt; Diederich, Stephan; Niederman, Fred

Abstract: Genuine theory testing, also under the term “replication research”, is rarely fo ... Expand

Abstract: Genuine theory testing, also under the term “replication research”, is rarely found in Information Systems (IS) research. Based on a replication’s results, our understanding or representation of the original theory is updated. This function of replication is integral to a scientific discipline to accumulate confidence in the explanatory power of a theory and to weed out theories that did not withstand scrutiny. However, many new theories are only tested once in the original study, while subsequent studies reference it without explicitly questioning the original theory. Against this background, we examine three aspects of the current state of replication studies in IS: (1) how many explicit replication studies in key IS research outlets have been published; (2) the attitudes of senior scholars, mostly prestigious IS journals’ editors, towards publishing replication research in their journals; and (3) a new policy proposal towards replication research broadly across all journals. We propose that all journals should take responsibility for publishing replications of theory or empirical results that have formerly been presented in that journal. Collapse

Topics: unintended consequence innovation management

Methods: literature study qualitative interview theory development literature sample