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Inductive Empiricism, Theory Specialization and Scientific Idealization in IS Theory Building
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2023 | Communications of the Association for Information Systems | Citations: 0
Authors: Iivari, Juhani

Abstract: This paper distinguishes and discusses three strategies for theory building in ... Expand

Abstract: This paper distinguishes and discusses three strategies for theory building in Information Systems (IS) -inductive empiricism, theory specialization, and scientific idealization -and contrasts them in terms of three desiderata of theories -realism, generality, and precision -and the tradeoffs between them. Inductive empiricism, emphasizing realism and generality, represents the received view with the classic Grounded Theory Methodology as a prime example. This paper argues for openness to theory specialization in practical disciplines such as IS. Theory specialization implies sacrificing a generality of theories for their realism and precision. The distinctive attention of the paper lies in scientific idealization, sacrificing the realism of theories for their precision and generality. It has almost been completely omitted in the literature on IS theory building. The special focus of this paper lies in IT applications as a category of IT artifacts and in design-oriented theories that provide knowledge of how to design "better" IT applications. This paper illustrates its points using TAM/UTAUT research. Collapse

Semantic filters: technology acceptance model

Topics: technology adoption ease of use affordance

Methods: theory development design artifact kernel theory design theory

Theories: technology acceptance model unified theory of acceptance and use of technology
Doing Well by Doing Fair? Investigating the Effect of Users’ Fairness Perceptions on Adoption Intentions of Services

2023 | International Conference on Information Systems | Citations: 0
Authors: Waltermann, Hubertus; Ziegler, Anika; Engert, Simon; Hess, Thomas

Abstract: Within the IS discipline, the concept of fairness as a determinant for social g ... Expand

Abstract: Within the IS discipline, the concept of fairness as a determinant for social good recently gained attention. However, a comprehensive understanding of the influence of different fairness dimensions on user perceptions and their adoption intention of new technologies is missing. Based on fairness research, the FAIRSERV model, and the technology acceptance model, we derived a research model to study how users' fairness perceptions along different dimensions influence their adoption intentions in the context of online services. We tested our model in an online experiment with 407 participants. Our results show that perceived distributive, procedural, and interactional fairness positively influence users' perceived overall fairness regarding an online service, which, in return, positively influences their adoption intentions. We contribute to IS research by shedding light on the societal impact of fairness in the context of adopting new digital services. Practitioners can utilize our findings to improve their service offerings. Collapse

Semantic filters: technology acceptance model

Topics: privacy societal evaluation criteria digital service user acceptance information system use

Methods: experiment factor analysis partial least squares path modeling survey chi squared test

Theories: technology acceptance model equity theory
Paths to open government data reuse: A three-dimensional framework of information need, data and government preparation
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2023 | Information & Management | Citations: 0
Authors: Wang, Fang; Zhang, Zhaoqi; Ma, Xin; Zhang, Yichen; Li, Xuguang; Zhang, Xiaofei

Abstract: With the increase of open government data (OGD) supply in many countries, promot ... Expand

Abstract: With the increase of open government data (OGD) supply in many countries, promoting its reuse becomes an important issue to a variety of stakeholders. Considering that most citizens have never used OGD, this study adopted a mixed methods design that includes an experiment and a survey to explore the factors that affect OGD reuse intention. The findings include: (1) user information need, significantly affected by user digital capability, triggers OGD reuse intention. (2) Perceived data value, affected by perceived data quality, information need, and government preparation, is the core influencing factor of OGD reuse intention and user satisfaction. (3) Gov ernment preparation has a significant effect on perceived data value, perceived data quality, and user satisfac tion. (4) Different from previous studies on other products, perceived data quality and user satisfaction have no direct significant effects on user reuse intention, revealing the dual attributes of OGD as technical products and monopolistic public goods. This study reveals the mechanism of OGD value co-creation by integrating factors related to data, user, and the government, providing novel empirical evidence and theoretical insights to the literature of Customer Satisfaction Index, Technology Acceptance Model, and data reuse. Collapse

Semantic filters: technology acceptance model

Topics: information technology capability data quality user satisfaction public good website

Methods: experiment survey mixed method qualitative coding data transformation

Theories: technology acceptance model
A Theory of Information Compression: When Judgments Are Costly
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2023 | Information Systems Research | Citations: 0
Authors: Watson, Richard Thomas; Plangger, Kirk; Pitt, Leyland; Tiwana, Amrit

Abstract: A theory of information compression (TIC) conceptualizes how anticipated judgmen ... Expand

Abstract: A theory of information compression (TIC) conceptualizes how anticipated judgment costs can affect decision quality. We theorize—inductively from decision making in medicine, energy pricing, auditing, and financial analytics—how judgment networks can exacerbate financial and nonfinancial judgment costs that compress information. Information compression occurs when a process intended to inform decision making generates information that has little variation. This can reduce decision quality and market efficiency. We offer potential remedies to mitigate its adverse societal consequences. We use complementary theoretical perspectives to nomologically contextualize how information compression arises. We introduce an information compression measure based on information entropy. TIC’s theoretical crux is that the expansion of a judgment network’s publicness exacerbates information compression by increasing judgment costs for some entities in a judgment network. We close with future research ideas on TIC’s core propositions and its broader theoretical implications for information systems research. History: Yulin Fang, Senior Editor; Robert Gregory, Associate Editor. Collapse

Semantic filters: technology acceptance model

Topics: social media societal evaluation criteria social influence price management decision making

Methods: theory development theoretical contribution econometric modeling

Theories: punctuated equilibrium theory agency theory technology acceptance model mathematical theory of communication theory of information
CARING ABOUT EMPLOYEES’ HEALTH@WORK – UNDERSTANDING HEALTH BELIEFS AND THE USE OF DIGITAL HEALTH INTERVENTIONS

2023 | European Conference On Information Systems | Citations: 0
Authors: Weißenfels, Silke; Kappler, Karolin; Smolnik, Stefan

Abstract: Employees find contemporary ways of working very demanding. Blurred boundaries ... Expand

Abstract: Employees find contemporary ways of working very demanding. Blurred boundaries between life and work cause technostress and considerable mental strain. To overcome these shortcomings, digital health interventions (DHIs) possess the power to prevent employees from suffering health-related issues at and due to their work. We developed a theoretically sound instrument employing a unified conceptualization of health beliefs, technology acceptance, privacy concerns, and autonomy to predict preventive health and technology use behavior at work. Accordingly, we conducted a survey-based study to investigate the factors influencing DHIs use for preventive health behavior at work. Our empirical results emphasize that employees undertake a cost-benefit analysis, valuing the benefits of reducing health threats and the perceived usefulness of DHIs for taking preventive actions at work. We confirm that privacy concerns and autonomy play a vital role. Our research outlines new avenues in DHIs use by contributing a valid theoretical framework for healthier work environments. through behavior change approaches (Pagoto and Bennett, 2013). For instance, wearables for selftracking (Giddens et al., 2017) that enable self-care and autonomy at work, enhance employees' health and well-being (Lupton, 2016). Against this background, we ask which beliefs and perceptions are important in evaluating the outcome of a particular behavior (Agarwal and Karahanna, 2000) as, for example, using DHIs for preventive health behavior at work. Surprisingly, despite the radical challenges of work practices with severe implications for employees, and the grown work around health interventions, the discourse on research referring to DHIs as facilitators of preventive health behavior in organizations is still in its infancy (Melzner et al., 2014;Yassaee and Mettler, 2019;Oesterle et al., 2019;Howarth et al., 2018). We shift our attention from technology use only and move toward an understanding of preventive health and technology use behavior, supported by DHIs in occupational settings. To address our research objectives, we refer to and extend previous research on preventive health behavior and technology use with multiple technological options beyond a narrow focus on which technology to use. Our work is rooted in research on health beliefs, based on the health belief model (HBM) (Rosenstock, 1974) considering the potential to initiate and change health behavior patterns (Abraham and Sheeran, 2005), and assuming that individuals attempt to avoid perceived health threats (Abraham and Sheeran, 2005;Rosenstock, 1974;Champion and Skinner, 2008). Additionally, we investigate employees' behavior in DHIs use at work. Interestingly, the decision-making process regarding technology use for health-related reasons differs from similar processes in other contexts (Sun et al., 2013). Hence, to understand employees' preventive health behavior supported by technology use, we expect that they intend to use DHIs, which, according to the technology acceptance model (TAM) (Davis, 1989;Venkatesh et al., 2003), is a result of systemrelated characteristics that we combine with health-related variables. Further, in offering voluntary DHIs use at work to encourage employees' empowerment, we have to consider their privacy concerns and autonomy, to engage them in healthy behavior at work (Roossien et al., 2021). As it is not clear whether or how health beliefs influence preventive health and technology use behavior at work, nor whether there is a link in-between, this paper seeks to answer the following research question: What impact do health beliefs, privacy concerns, and autonomy have on employees' DHIs use for preventive health behavior at work? More specifically, our research objectives are (1) to explore whether health beliefs influence employees' preventive health behavior at work, (2) to predict employees' technology use behavior of DHIs, (3) to empirically validate the link between health beliefs, DHIs use, and preventive health behavior, and (4) to theorize the influence of privacy concerns and autonomy on DHIs use at work. Our study follows the call to unfold and predict preventive health behavior through complex causal models (Champion and Skinner, 2008) and to demonstrate the interventions' effectiveness (Abraham and Sheeran, 2005). While DHIs have the potential to intervene in unhealthy (working) behavior, we suggest an analysis of the health-related beliefs and factors related to technology use. Therefore, our theoretical framework is to develop a deeper understanding of HBM and TAM as theoretical lenses and their interplay and to offer new perspectives that could ensure healthier work environments. In a quantitative research setting, we use an online-based survey to evaluate our hypothesized relations empirically. Our findings provide compelling evidence that technology use and preventive health behavior do not emerge in isolation. More precisely, our study demonstrates the relationship between health beliefs and system-related characteristics in DHIs use at work. These results help organizations to understand the conditions under which DHIs are likely to have an impact on employees' preventive health behavior and well-being in occupational settings, which can in turn develop into a meaningful quality of work (Rongen et al., 2013). The paper is structured as follows: Section 2 introduces the theoretical background for research on preventive health and technology use behavior and the development of our theoretical conceptualization for the quantitative analysis. Section 3 introduces our survey-based approach to address the research question. We present our analysis in Section 4. Our results and implications are summarized in Section 5 together with a discussion of related literature. Section 6 concludes the paper. Collapse

Semantic filters: technology acceptance model

Topics: information system use information privacy concern perceived usefulness decision making technology adoption

Methods: survey partial least squares regression card sorting theory development factor analysis

Theories: technology acceptance model measurement theory health belief model
Human versus automated agents: how user preferences affect future mobility systems

2023 | European Conference On Information Systems | Citations: 0
Authors: Ahadi, Ramin; Taudien, Anna; Ketter, Wolfgang

Abstract: Along with rapid advancements in digital, and physical technologies, shared aut ... Expand

Abstract: Along with rapid advancements in digital, and physical technologies, shared autonomous electric vehicles are forecasted to gradually complement and replace traditional human-based mobility systems. Information systems play a key role in such a deep socio-technical system to pave the path toward a more sustainable future. This study investigates a hybrid ride-hailing platform of automated and human-driven vehicles. Our focus lies on the demand side where we evaluate the influence of user behaviors on economic and environmental system performance. For this, we employ a data-driven agent-based simulation modeling heterogeneous vehicle and user agents calibrated by rental data of a leading vehicle-sharing company. Our findings declare that diverse customer responses to the introduction of shared autonomous electric vehicles yield significantly differing fleet performance and ecological costs. We also observe that the status quo customer communication design of ride-hailing platforms needs adjustments to maximize the potentials of future hybrid shared mobility systems. Collapse

Semantic filters: technology acceptance model

Topics: ride sharing platform user behavior service quality decision making artificial intelligence

Methods: simulation agent based simulation experiment literature study sensitivity analysis

Theories: technology acceptance model general systems theory
Telepresence in live-stream shopping: An experimental study comparing Instagram and the metaverse
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2023 | Electronic Markets | Citations: 0
Authors: Barta, Sergio; Gurrea, Raquel; Flavián, Carlos

Abstract: Advances in digital platforms allow influencers to use live shows to showcase pr ... Expand

Abstract: Advances in digital platforms allow influencers to use live shows to showcase products, which has given rise to live-stream shopping. Moreover, new communication forms have emerged, such as the metaverse. The social interactions that occur in these immersive environments foster influencer-follower interactions. This research compares the impact of live-stream shopping on followers’ experiences and behaviors on two communication channels (live shows on Instagram and in the metaverse) and analyses the moderating role of content involvement in telepresence. Data were collected in a between-subjects quasi-field experiment. Two scenarios that differed in degree of telepresence were created, a live show on Instagram and a live show in the metaverse. The results showed that telepresence is an important part of the user experience and in the success of live shows. Telepresence was seen to have a major influence on experiential value, but not on instrumental value. Both values provided followers with satisfaction with the experience. This satisfaction generated stickiness intention and intention to recommend the influencers’ live shows. The effect of telepresence on experiential value was greater for followers less involved with the influencer’s content. This research is pioneering in comparing an established platform, Instagram, with the metaverse. Despite the greater experiential value provided by the metaverse, to increase its instrumental value metaverse spaces needs to be further developed. Collapse

Semantic filters: technology acceptance model

Topics: video conference virtual reality Instagram social network social media

Methods: survey field experiment statistical power analysis statistical hypothesis test experimental group

Theories: technology acceptance model
Modern Centaurs: How Humans and AI Systems Interact in Sales Forecasting

2023 | European Conference On Information Systems | Citations: 0
Authors: Beese, Jannis; Fahse, Tobias

Abstract: Recent achievements of artificial intelligence (AI) have caused organizations t ... Expand

Abstract: Recent achievements of artificial intelligence (AI) have caused organizations to increasingly bring AI capabilities into their core business processes. Such AI-supported business processes often result in human-AI hybrid systems, which consist of an AI system, which performs most of the execution, and humans, who monitor this execution and occasionally provide additional inputs and overrides. Using sales data from Walmart, we conduct an online study to investigate if human supervision can improve upon state-of-the-art AI forecasts. Furthermore, we analyze the perceptions and behavioral intentions of the human participants over time. We find that human interventions consistently lead to less accurate forecasts and that participants initially underestimate the AI system's accuracy and overestimate their own potential to improve upon AI forecasts. However, perceptions quickly shift over the course of the study, causing the participants to perceive the AI system increasingly favorably, which also leads to behavioral changes and better hybrid system performance. Collapse

Semantic filters: technology acceptance model

Topics: artificial intelligence IT productivity information system use task productivity perceived usefulness

Methods: regression analysis method survey LightGBM conceptual modelling experiment

Theories: technology acceptance model
STAY WITH ME - CONVERSATIONAL CHURN PREVENTION IN DIGITAL SUBSCRIPTION SERVICE

2023 | European Conference On Information Systems | Citations: 0
Authors: Benner, Dennis; Schöbel, Sofia

Abstract: ... Expand

Abstract: Collapse

Semantic filters: technology acceptance model

Topics: digital service usage intention ease of use business-to-consumer business-to-business

Methods: qualitative interview design artifact experimental group survey experiment

Theories: technology acceptance model
The Role of Strong and Weak Ties in the Usage Behaviour of Social Media Apps

2023 | European Conference On Information Systems | Citations: 0
Authors: Beşer, Alper; Erdogan, Aleyna

Abstract: Social media apps like TikTok have influenced the daily lives of billions of us ... Expand

Abstract: Social media apps like TikTok have influenced the daily lives of billions of users. Such apps are forms of network goods and subject to so-called network externalities. They offer a social utility that increases with the number of app users. The social utility can be divided into a strong-tie utility (STU) and weaktie utility (WTU) as it may emerge from strong ties (e.g. close friends) and weak ties (e.g. friends of friends) respectively. To investigate their influence on the usage behaviour more closely, we develop a research model and conduct an online experiment (N=291) for collecting data for seven popular social media apps. The results prove that strong and weak ties can influence users in two ways: providing utility and exerting social pressure. While the level of these effects varies for the tested apps, the utility has a generally greater influence on the intention to use. Collapse

Semantic filters: technology acceptance model

Topics: mobile application social media usage intention information system use YouTube

Methods: survey statistical hypothesis test experiment structural equation modeling partial least squares regression

Theories: technology acceptance model social network theory self determination theory

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Found 1648 articles

Inductive Empiricism, Theory Specialization and Scientific Idealization in IS Theory Building

Doing Well by Doing Fair? Investigating the Effect of Users’ Fairness Perceptions on Adoption Intentions of Services

Paths to open government data reuse: A three-dimensional framework of information need, data and government preparation

A Theory of Information Compression: When Judgments Are Costly

CARING ABOUT EMPLOYEES’ HEALTH@WORK – UNDERSTANDING HEALTH BELIEFS AND THE USE OF DIGITAL HEALTH INTERVENTIONS

Human versus automated agents: how user preferences affect future mobility systems

Telepresence in live-stream shopping: An experimental study comparing Instagram and the metaverse

Modern Centaurs: How Humans and AI Systems Interact in Sales Forecasting

STAY WITH ME - CONVERSATIONAL CHURN PREVENTION IN DIGITAL SUBSCRIPTION SERVICE

The Role of Strong and Weak Ties in the Usage Behaviour of Social Media Apps