Information Systems Research Community Research Articles

Looking beyond the hype: The challenges of blockchain adoption in accounting

Blockchain has been hyped and considered a potential game-changer for the recording of accounting transactions as it enables triple-entry accounting and real-time reporting. However, there is very little knowledge of the uptake of blockchain in accounting, and most blockchain accounting research is conceptual, lacking empirical evidence. This study addresses this gap and examines the organisational factors that drive and hinder the adoption of blockchain in accounting, as well as the perceived benefits. Using the technology-organisation-environment (TOE) framework, we analyse interview data collected from blockchain experts and accountants (N = 19). The findings confirm the influence of nine context-specific factors, highlighting the challenges and lack of knowledge in understanding the usage and benefits of blockchain in accounting, its complex integration with existing accounting systems, and the increased costs associated with the adoption intention. This study provides novel empirical evidence of the factors by adequately contextualising an established theoretical framework in the context of accounting. The findings are useful for practitioners and the broader accounting information systems research community as they provide empirical insights into how context-specific factors influence blockchain adoption in accounting.

What is digital transformation? A survey on the perceptions of decision-makers in business

AbstractIn the past years we have observed enormous adoption and use of digital technologies in almost all domains of human life. In this context, researchers and practitioners have been using the term “digital transformation” (DT) to characterize phenomena related to the changes caused by increased use of digital technologies. The progression and contributions of corresponding discussions significantly depend on a common understanding and conceptualization of DT. Accordingly, the information systems research community has started working toward conceptual clarity. Importantly, the current debate focuses on theoretical contributions by academic researchers. Hence, data on the practitioners’ perspective on DT is missing. Against this background, we investigated general understandings of DT in practice. Our analysis comprises data of N = 529 business decision-makers in the UK. Our results show a significant discrepancy between science (i.e., conceptualizations and definitions of DT in the academic literature) and practice (i.e., business decision-makers’ perceptions and corresponding survey responses). Specifically, for a large proportion of the respondents their decision to classify concrete digitalization examples from the literature as DT or no DT was largely independent of the degree of organizational change caused by the use of digital technologies. This is a surprising result, as high-caliber academic literature proposes this degree to be a critical factor to characterize DT. Another key finding is that a remarkable number of practitioners consider a digitalization initiative as DT based on the mere occurrence of specific buzzwords related to digital technologies in the corresponding descriptions. In particular, the buzzword “digital technology” led the survey participants to classify a definition as instance for DT. We discuss implications of our results and limitations.

Blockchain from the information systems perspective: Literature review, synthesis, and directions for future research

This paper profiled blockchain studies in information systems (IS) journals from 2016 to 2022. Drawing on the 443 selected articles from 77 IS journals, we proposed a classification scheme from the IS perspective. Current blockchain articles are highly skewed, focusing on research agendas and system design. We proposed a theoretical framework by summarizing the current status of the blockchain literature and highlighting 15 future research questions for the IS research community. We are optimistic that the proposed framework and future research questions can guide blockchain research and advance its scale and impact.

Can knowledge based systems be designed to counteract deskilling effects?

Recent calls in the information systems research community argue that we know intelligent systems deskill users, and future research should focus on how to design systems that do not deskill, rather than continue to examine whether the phenomenon occurs. This should be a wakeup call for public accounting firms focused on implementing restrictive audit support systems, which leads to de-skilling of novice accounting professionals. Our research focuses on redesigning knowledge-based systems to facilitate expertise development and counteract the de-skilling effects that result from use of such systems. Specifically, we manipulate the design of the system interface by providing information cues in a screen format consistent with expert knowledge representations and manipulate automatic provision versus voluntary use of explanations for users during task completion. Results show that after using the knowledge-based system to complete a series of reenacted client engagements over a three-day period, both the interface design manipulation and automatic provision of explanations had a positive effect on novice accounting professionals’ development of expert-like knowledge structures. The results of the study have important implications for the development of knowledge-based systems intended to support accounting professionals’ (and other knowledge workers’) expertise development processes.

Editorial: Continuing on an Inclusive Path to Scholarly Excellence with Renewed Vigor

Editorial: Continuing on an Inclusive Path to Scholarly Excellence with Renewed Vigor

Human-Centered Design for Individual and Social Well- being: Editorial Preface

As digital technology use becomes widespread, its unintended consequences ranging from personal health to societal righteousness are under more scrutiny. Increasingly, digital designers are accused of not being considerate enough of the depth of their creations, and their impacts on our well-being. In this special issue, we explore an alternative, genuinely human-centered approach to technology design focusing on well-being and making our interactions with digital technology more meaningful, purposeful, and sustainable. To this end, the editorial starts with a brief review of the history of research that led to the growing field of digital well-being. We then introduce the Digital Well-being Design Framework, which goes beyond the ego-centric approach in human-centered design, and is multi-layered with self (intrapersonal), social (interpersonal), and transcendent (extra-personal) levels. Similar topics in related AIS journals are summarized, followed by the application of our framework to introduce and position the papers in this special issue. Our special issue aims to bring the topic of digital well-being to the forefront of the information systems research community and launch a new era of genuinely human-centered design.

Editorial: There Are Promises to Keep and Miles to Go Before I Leave…

Editorial: There Are Promises to Keep and Miles to Go Before I Leave…

Artificial Intelligence in Information Systems: State of the Art and Research Roadmap

Many would argue that artificial intelligence (AI) is not only technology but also a paradigmatic shift in the relationship between humans and machines. Much literature assumes that AI-powered practices substantially differ from and profoundly change organizational structures, communication, affordances, and ecosystems. However, AI research remains fragmented and often lacks clarity. While the information systems (IS) discipline can play a pivotal role in AI’s emergence and use, the discipline needs a clear direction that specifies how it can contribute and its key research themes and questions. This paper draws on a professional development workshop that we organized at the 2020 International Conference on Information Systems and the discussions that followed. We summarize and synthesize how AI has impacted organizational practices over five decades and provide views from various perspectives. We identify weaknesses in the current AI literature as measured against conceptual clarity, theoretical glue, cumulative tradition, parsimony, and applicability. We also identify direct actions that the IS research community can undertake to address these issues. Finally, we propose a next-step research agenda to guide AI research in the coming years.

Artificial intelligence in information systems research: A systematic literature review and research agenda

AI has received increased attention from the information systems (IS) research community in recent years. There is, however, a growing concern that research on AI could experience a lack of cumulative building of knowledge, which has overshadowed IS research previously. This study addresses this concern, by conducting a systematic literature review of AI research in IS between 2005 and 2020. The search strategy resulted in 1877 studies, of which 98 were identified as primary studies and a synthesise of key themes that are pertinent to this study is presented. In doing so, this study makes important contributions, namely (i) an identification of the current reported business value and contributions of AI, (ii) research and practical implications on the use of AI and (iii) opportunities for future AI research in the form of a research agenda.

Examining Assumptions: Provocations on the Nature, Impact, and Implications of IS Theory

The Information Systems research community has a complex relationship with theory and theorizing. As a community of scholars, our assumptions about theory and theorizing affect every aspect of our intellectual lives. Ideas about what theory is, who theo

How to Conduct Rigorous Supervised Machine Learning in Information Systems Research: The Supervised Machine Learning Report Card

In the last decade, applying supervised machine learning (SML) has become increasingly popular in the information systems (IS) field. However, SML results rely on many different data-preprocessing techniques, algorithms, and ways to implement them, which has contributed to an inconsistency in the way researchers have documented their SML efforts and, thus, the degree to which others can reproduce their results. In one sense, we can understand this inconsistency given the goals and motivations for SML applications vary and the research area’s rapid evolution. However, for the IS research community, the inconsistency poses a big challenge because, even with full access to the data, researchers can neither completely evaluate the SML approaches that previous research has adopted or replicate previous research results. Therefore, in this paper, we provide the IS community with guidelines for comprehensively and rigorously conducting and documenting SML research. First, we review the literature concerning steps and SML process frameworks to extract relevant problem characteristics that researchers should report and relevant choices that they should make in applying SML. Second, we integrate these characteristics and choices into a comprehensive “Supervised Machine Learning Report Card (SMLR)” that researchers can use in future SML endeavors. Third, we apply this report card to a set of 121 relevant papers published in renowned IS outlets between 2010 and 2018 and demonstrate how and where these papers’ authors could have improved their documentation and, thus, how and where researchers can better document their SML approaches in the future. Thus, with this work, we help researchers more completely and rigorously apply and document SML approaches and, thereby, enable researchers to more deeply evaluate and reproduce/replicate results in the IS field.

A Dual-Identity Perspective of Obsessive Online Social Gaming

Obsessive online social gaming has become a worldwide societal challenge that deserves more scholarly investigation. However, this issue has not received much attention in the information systems (IS) research community. Guided by dual-system theory, we theoretically derive a typology of obsessive technology use and contextually adapt it to conceptualize obsessive online social gaming. We also build upon identity theory to develop a dual-identity perspective (i.e., IT identity and social identity) of obsessive online social gaming. We test our research model using a longitudinal survey of 627 online social game users. Our results demonstrate that the typology of obsessive technology use comprises four interrelated types: impulsive use, compulsive use, excessive use, and addictive use. IT identity positively affects the four obsessive online social gaming archetypes and fully mediates the effect of social identity on obsessive online social gaming. The results also show that IT identity is predicted by embeddedness, self-efficacy, and instant gratification, whereas social identity is determined by group similarity, group familiarity, and intragroup communication. Our study contributes to the IS literature by proposing a typology of obsessive technology use, incorporating identity theory to provide a contextualized explanation of obsessive online social gaming and offering implications for addressing the societal challenge.

Motivation and sustained participation in the online crowdsourcing community: the moderating role of community commitment

PurposeCrowdworkers' sustained participation is critical to the success and sustainability of the online crowdsourcing community. However, this issue has not received adequate attention in the information systems research community. This study seeks to understand the formation of crowdworker sustained participation in the online crowdsourcing community.Design/methodology/approachThe research model was empirically tested using online survey data from 212 crowdworkers in a leading online crowdsourcing community in China.FindingsThe empirical results provide several key findings. First, there are two different types of sustained participation: continuous participation intention (CPI) and increased participation intention (IPI). Second, extrinsic motivation and intrinsic motivation positively influence crowdworker CPI and IPI. Third, community commitment negatively moderates the effects of extrinsic motivation on CPI and IPI, while it positively moderates the effects of intrinsic motivation on CPI and IPI.Originality/valueThis study has significant implications for research on online crowdsourcing community and provides practical guidance for formulating persuasive measures to promote crowdworker sustained participation in the community.

An Exploration of the Drivers of Non- Adoption Behavior

While there has been a substantial amount of attention within the information systems research community towards understanding the phenomenon of adoption, much less is known about non-adoption. This study examines the factors surrounding the decision to not adopt a technology and whether certain factors exert differing effects on individuals in particular ways such that concurrent factors could be identified to develop a classification of the specific types of non-adoption behavior. Utilizing inhibitor theory and the symbolic adoption model as a foundational framework for the different types of non-adoption, we posit that different types of non-adoption exist which is demonstrated by determining the perceptions towards technology that coalesce around different types of non-adoption. We conducted a two-phase investigation into nonadoption with two goals in mind: 1) identify and explore specific factors of the IT that are associated with the rejection decision and are distinct from the adoption decision; and 2) determine the extent to which these factors (along with traditional enablers) differentiate between different types of non-adoption. The results from a discriminant function analysis (DFA) indicate the coalescence of specific perceptual variables according to the types of non-adoption behavior, specifically, the discriminatory power of differing perceptions of IT between trial rejecters, symbolic rejecters, trial accepters, symbolic adopters, and adopters. The implications for research and implications for practice are discussed.

An Exploration of the Drivers of Non-Adoption Behavior

While there has been a substantial amount of attention within the information systems research community towards understanding the phenomenon of adoption, much less is known about non-adoption. This study examines the factors surrounding the decision to not adopt a technology and whether certain factors exert differing effects on individuals in particular ways such that concurrent factors could be identified to develop a classification of the specific types of non-adoption behavior. Utilizing inhibitor theory and the symbolic adoption model as a foundational framework for the different types of non-adoption, we posit that different types of non-adoption exist which is demonstrated by determining the perceptions towards technology that coalesce around different types of non-adoption. We conducted a two-phase investigation into non-adoption with two goals in mind: 1) identify and explore specific factors of the IT that are associated with the rejection decision and are distinct from the adoption decision, and 2) determine the extent to which these factors (along with traditional enablers) differentiate between different types of non-adoption. The results from a discriminant function analysis (DFA) indicate the coalescence of specific perceptual variables according to the types of non-adoption behavior, specifically, the discriminatory power of differing perceptions of IT between trial rejecters, symbolic rejecters, trial accepters, symbolic adopters, and adopters. The implications for research and implications for practice are discussed.

Qualitative and Critical Research in Information Systems and Human Computer Interaction: Divergent and Convergent Paths

Qualitative and Critical Research in Information Systems and Human Computer Interaction explores the history and adoption of qualitative and critical research in Information Systems (IS) and contrasts it with the growth of similar methods/theories in Human Computer Interaction (HCI) and, to a lesser, extent Computer Supported Collaborative Work (CSCW). The supposition behind the comparison was that the areas overlap in subject matter and would overlap in methods and authors. However, marked differences were observed in the structure of publications, conferences, and on social media that led to questions about the extent to which the fields shared a common framework. The authors find that the history of each discipline reflects institutional factors that affected the respective timelines for the use of these approaches. This leads them to consider a sociological epistemic framework, which explains the differences quite well. It also supports characterizations of the culture of IS made by members, as having open paradigm and high collegiality, described as an adhocracy. The authors propose that qualitative and critical research developed interdependently in IS. Aside from institutional factors, a further difference in uptake of methods and critical framework comes from the US/Europe divide in research traditions and the political/epistemic climates affecting research in the respective regions. Research from beyond the transatlantic traditions postdates the developments covered here but is touched on at the end of the monograph. The primary goal of Qualitative and Critical Research in Information Systems and Human Computer Interaction is to better understand the ways the IS research community differentiates itself into diverse constituencies, and how these constituencies interact in the field's complex processes of knowledge creation and dissemination. Another goal is to create cross-disciplinary discussion and build on related work in the fields. This is important in the era of platforms with global reach, and the concurrent development of powerful AI and analytics capabilities that both intrude on daily life and try to emulate human intelligence.

Assessing the long-term fragmentation of information systems research with a longitudinal multi-network analysis

ABSTRACTOver the decades, the evolving information systems (IS) research community and its academic output has greatly expanded. This paper offers an integrated analysis of multiple dimensions of network interconnectedness of the growing IS discipline. In line with the social and intellectual dimensions of the underlying theory of science, we synthesise multiple network views on authors, institutions, journal outlets, citations, and themes into a multi-dimensional knowledge network infrastructure analysis of collaborative networks of IS researchers and their academic output. We further introduce two fragmentation types to better address the dynamics of the IS discourse discussed in previous research. Based on a corpus of all 3587 AIS basket of 8 journal articles over 20 years, we use the analytical framework to study whether the fast growth of the IS discipline resulted in a reduced coherence of the overall academic collaboration and the research themes. The analysis reveals that the sampled IS researcher community developed a large core component with influential bridging people who mitigate fragmentation and centralisation. This IS community structure constitutes a valuable asset to cope with fragmentation tendencies in the intellectual dimension (research topics) resulting from many short-term topic bursts and from centralisation of conceptual terms.

Institutional ontology for Conceptual Modeling

Conceptual models are intended to capture knowledge about the world. Hence, the design of conceptual models could be informed by theories about what entities exist in the world and how they are constituted. Further, a common assumption within the field of conceptual modeling is that conceptual models and information systems describe entities in the real world, outside the systems. An alternative view is provided by an ontological commitment that recognizes that the institutional world is constructed through language use and the creation of institutional facts. Such an ontological commitment implies that there is an institutional reality, which, to a great extent, is constructed using information infrastructures. Accordingly, conceptual models have not only a descriptive role but also a prescriptive one, meaning that modelers set up a framework of rules that restrict and enable people to construct institutional reality using information infrastructures. Understanding the prescriptive role of conceptual models may revive the area of conceptual modeling in the information systems research community. Reviving conceptual modeling through institutional modeling is motivated by the effect that implemented conceptual models have on information infrastructures and institutions. The purpose of this article is to propose an institutional ontology that can support the design of information infrastructures. The ontology is theoretically informed by institutional theory and a communicative perspective on information systems design, as well as being empirically based on several case studies. It is illustrated using a case study in the welfare sector. A number of guidelines for modeling institutional reality are also proposed.

Uma Análise sobre a Produção de Conhecimento Científico nas Pesquisas Publicadas nos Primeiros 10 anos da iSys (2008-2017)

Um dos desafios da comunidade científica brasileira de Sistemas de Informação (SI) ligada à Computação tem sido endereçar a pesquisa em SI, que vai além da construção de tecnologias computacionais. O avanço da produção do conhecimento científico em SI passa pelo domínio e aplicação de teorias, multiplicidade de paradigmas e métodos de pesquisa que ainda são pouco explorados. Realizamos uma análise das pesquisas publicadas na iSys, ao longo dos primeiros 10 anos, com o intuito de refletir sobre possíveis caminhos teóricos, epistemológicos e metodológicos para as pesquisas de SI. A análise se baseou em tipologias empregadas pela literatura internacional, compreendendo quatro eixos de análise: i) concepção do artefato TI, ii) paradigma de pesquisa, iii) teorização, e iv) métodos de pesquisa. Como principais conclusões desta análise, observamos por parte da comunidade de pesquisa em SI na iSys, a produção de conhecimento científico com forte ênfase positivista e experimental. A análise aponta para caminhos e oportunidades para robustecer a produção de conhecimento nacional que incluem a abertura a paradigmas epistemológicos que compreendam a complexidade e a multiplicidade do mundo real e a formulação de um campo teórico consistente para a área.

Turning the Spotlight on the Consequences of Individual IT Turnover

Among the many aspects of IT personnel studied by the information systems (IS) research community, individual voluntary IT turnover is one of the most-examined phenomena. However, research into this phenomenon concentrates mainly on antecedents and cognitive precursors such as turnover intention. Antecedents are essential to understanding the turnover behavior of IT personnel, but they do not represent the complete IT turnover research. The consequences of individual voluntary IT turnover behavior, an important topic, have faded from the spotlight of the IS community. We investigate this by conducting a multidisciplinary scoping literature review of individual voluntary IT turnover behavior, with the focus on the consequences. The purpose of this review is to determine what is known about voluntary IT turnover behavior consequences and what research gaps exist in this research context. To make our review as rigorous as possible, we followed a systematic review approach, accompanied with transparent reporting of all steps of the review process. Our search strategy yielded 153 IT turnover studies, 14 of which consider IT turnover behavior consequences, concentrated primarily on IT project management. Drawing on the scoping review, our study also specifies a research agenda for future IT turnover behavior consequences research by highlighting knowledge gaps for potentially fruitful research directions.