Cross-cultural and Institutional Perspectives on Information Technology Governance

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Fernandes, Pedro; Pereira, Ruben; Wiedenhoft, Guilherme

Abstract: Nowadays, over 20% of organizations' worldwide capital expenditure goes toward ... Expand

Abstract: Nowadays, over 20% of organizations' worldwide capital expenditure goes toward Information Technology (IT). Hence IT Governance (ITG) is essential to establish a mutually beneficial connection between IT and the business. To deploy ITG, some factors, such as Organizational Culture (OC), should be considered. This study focuses on how the different cultures in the OCAI model affect employees' perception of ITG institutionalization. A survey was conducted on 513 workers from over 150 companies worldwide. Our model was validated using the Kruskal-Wallis H test. Although the results were not as anticipated, the general hypothesis was validated, demonstrating that individuals' perceptions of ITG institutionalization are influenced by their predominant OC type. Market and Hierarchy cultures show higher levels of individual perception of ITG. Organizations will learn how various cultures affect employees' perceptions of ITG, which will help them create a more ITG-oriented culture, greater alignment between business and IT, and more IT-enabled value. Collapse

Topics: organizational culture missing data national culture anonymity

Methods: survey Kruskal Wallis test nonparametric test factor analysis data transformation

Theories: institutional theory

What ails physician review websites? A study of information needs of patients

2023 | Decision Support Systems | Citations: 0

Authors: Ghosh, Soham; Chakraborty, Soumyakanti; Gupta, Narain; Basu, Sumanta

Abstract: Physician Review Websites (PRWs) help users select physicians by providing both ... Expand

Abstract: Physician Review Websites (PRWs) help users select physicians by providing both structured and unstructured data on physicians and patients' experiences with physicians. In this paper, the adequacy of the available in­ formation on PRWs is investigated. An empirical study is conducted to understand the information that patients seek from PRWs through a survey instrument administered to 344 patients. A topic modelling approach is then employed on 666,551 text reviews of patients using data from a popular PRW in India to discover information available on the PRWs. Combining both approaches, it is found that 12 out of 25 topics are either unavailable or only partially available, indicating an information gap. Two topics which constitute the information gap are then utilised to conduct a full factorial experiment on 153 respondents using a Latin Square design. Experimental results demonstrate that adding relevant information improves the physician selection process. Our work con­ tributes to the healthcare IS literature on online physician selection and the role of information availability. The results will help PRWs and hospitals decide how to restructure information on their websites and devise stra­ tegies to nudge patients to write reviews highlighting the desired information. Collapse

Topics: website service quality IS success video conference web page

Methods: experiment survey design survey latin square design factorial experiment

Theories: SERVQUAL

Collateral Damage: The Relationship Between High-Salience Events and Variation in Racial Discrimination

2023 | Organization Science | Citations: 0

Authors: Gorbatai, Andreea; Younkin, Peter; Burtch, Gordon

Abstract: To what extent are individual or organizational biases affected by racially sali ... Expand

Abstract: To what extent are individual or organizational biases affected by racially salient events? We propose that acts of discrimination and the individual biases that undergird them are sensitive to high-salience events and will oscillate with the salience of the focal attribute. In short, that the propensity to discriminate reflects both individual and environmental differences, and therefore a given person may become more prone to discriminate in the aftermath of a high-salience event. We test our hypothesis in three online experiments that examine how varying the salience of race affects the evaluation of in-group or out-group founders. We find that respondents evaluate their in-group members more favorably, and out-group members less favorably, when exposed to a high-salience event, which translates into a significant disadvantage for the minority (African American) group. We complement these studies with an assessment of how police shootings affect fundraising outcomes on Kickstarter to confirm the external validity of our findings. Together, these studies indicate that racially salient events depress the quality evaluations and success odds of African American entrepreneurs relative to others. Hence, discrimination levels can be affected by salient yet unrelated events, and such events are consequential for the economic fortunes of individuals belonging to minority and disadvantaged groups.History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory.Supplemental Material: The online appendices are available at https://doi.org/10.1287/orsc.2021.1527. Collapse

Topics: crowdfunding crowdsourcing website criminality application programming interface

Methods: experiment parametric test statistical hypothesis test survey facial recognition system

IMPACT OF EXPLAINABLE AI ON COGNITIVE LOAD: INSIGHTS FROM AN EMPIRICAL STUDY

2023 | European Conference On Information Systems | Citations: 0

Authors: Herm, Lukas-Valentin

Abstract: While the emerging research field of explainable artificial intelligence (XAI) ... Expand

Abstract: While the emerging research field of explainable artificial intelligence (XAI) claims to address the lack of explainability in high-performance machine learning models, in practice, XAI targets developers rather than actual end-users. Unsurprisingly, end-users are often unwilling to use XAI-based decision support systems. Similarly, there is limited interdisciplinary research on end-users' behavior during XAI explanations usage, rendering it unknown how explanations may impact cognitive load and further affect end-user performance. Therefore, we conducted an empirical study with 271 prospective physicians, measuring their cognitive load, task performance, and task time for distinct implementationindependent XAI explanation types using a COVID-19 use case. We found that these explanation types strongly influence end-users' cognitive load, task performance, and task time. Further, we contextualized a mental efficiency metric, ranking local XAI explanation types best, to provide recommendations for future applications and implications for sociotechnical XAI research. Collapse

Topics: explainable artificial intelligence task productivity artificial intelligence decision support system shapley additive explanation

Methods: descriptive statistic statistical hypothesis test literature study machine learning survey

Theories: theory of abduction

The social dilemma of big data: Donating personal data to promote social welfare

2023 | Information and Organization | Citations: 0

Authors: Hillebrand, Kirsten; Hornuf, Lars; Müller, Benjamin; Vrankar, Daniel

Abstract: When using digital devices and services, individuals provide their personal data ... Expand

Abstract: When using digital devices and services, individuals provide their personal data to organizations in exchange for gains in various domains of life. Organizations use these data to run technologies such as smart assistants, augmented reality, and robotics. Most often, these organizations seek to make a profit. Individuals can, however, also provide personal data to public databases that enable nonprofit organizations to promote social welfare if sufficient data are contributed. Reg­ ulators have therefore called for efficient ways to help the public collectively benefit from its own data. By implementing an online experiment among 1696 US citizens, we find that individuals would donate their data even when at risk of getting leaked. The willingness to provide personal data depends on the perceived risk level of a data leak but not on a realistic impact of the data on social welfare. Individuals are less willing to donate their data to the private industry than to academia or the government. Finally, individuals are not sensitive to whether the data are pro­ cessed by a human-supervised or a self-learning smart assistant. Collapse

Topics: database system economic surplus IS economics health information system data breach

Methods: archival research experiment nonparametric test Kruskal Wallis test computational algorithm

Theories: prospect theory privacy calculus theory

Consumer Preferences for Privacy Management Systems

2023 | International Conference on Information Systems | Citations: 0

Authors: Hanneke, Björn; Baum, Lorenz; Schlereth, Christian; Hinz, Oliver

Abstract: This work presents insights into consumer preferences regarding Privacy Managem ... Expand

Abstract: This work presents insights into consumer preferences regarding Privacy ManagementSystems in the context of the General Data Protection Regulation (GDPR). The authors perform a Choice-Based Conjoint experiment with consumers (n = 589) to elicit preferences over four attributes and compute usage likelihoods for all product configurations. Results show that data sharing for marketing purposes and discounts are the most important attributes for consumers. Furthermore, consumers prefer digital access to privacy-related information, detailed rights management for data sharing and no data sharing for marketing purposes. Moreover, a cluster analysis reveals differing importance weights across clusters. The study concludes that incorporating consumer preferences into the design and development process of Privacy Management Systems could increase their use and effectiveness, ultimately strengthening consumers' privacy rights and companies' legal compliance. The authors suggest researching legal, business, and consumer requirements more holistically to converge these perspectives to improve Privacy Management Systems adoptions. Collapse

Topics: privacy legal context General Data Protection Regulation marketing management digital dashboard

Methods: experiment cluster analysis survey literature study computational algorithm

EXPLORING THREAT-SPECIFIC PRIVACY ASSURANCES IN THE CONTEXT OF CONNECTED VEHICLE APPLICATIONS

2023 | European Conference On Information Systems | Citations: 0

Authors: Lechte, Henrik; Menck, Jannes; Stocker, Alexander; Lembcke, Tim-Benjamin; Kolbe, Lutz

Abstract: Connected vehicles enable a wide range of use cases, often facilitated by smart ... Expand

Abstract: Connected vehicles enable a wide range of use cases, often facilitated by smartphone apps and involving extensive processing of driving-related data. Since sensitive information about actual driving behavior or even daily routines can be derived from this data, the issue of privacy arises. We explore the impact of short privacy assurance statements on user perceptions by considering two data-intensive cases, usage-based insurance, and traffic hazard warnings. We conducted two experimental comparisons to investigate whether and how privacy-related perceptions about vehicle data sharing can be altered by different text-based privacy assurances on fictional app store pages. Our results are largely inconclusive, and we found no clear evidence that such short statements can significantly alter privacy concerns and increase download intentions. Furthermore, our results suggest that general and threatspecific privacy assurance statements likely yield no or little benefits to connected vehicle app providers regarding user perceptions. Collapse

Topics: privacy mobile application information privacy concern digital distribution mobile application market

Methods: survey experiment parametric test nonparametric test one-way ANOVA

Theories: protection motivation theory privacy calculus theory

HUMAN-AI COLLABORATION IN CONCEPTUALIZING DESIGN SCIENCE RESEARCH STUDIES: PERCEIVED HELPFULNESS OF GENERATIVE LANGUAGE MODEL'S SUGGESTIONS

2023 | European Conference On Information Systems | Citations: 0

Authors: Memmert, Lucas; Cvetkovic, Izabel; Bittner, Eva

Abstract: Solving complex problems was named a new challenge for research on human-AI col ... Expand

Abstract: Solving complex problems was named a new challenge for research on human-AI collaboration. In our study we focus on a particular means to solving complex problems: design science research (DSR). We investigate whether AI, more specifically, generative language models (GLM), can support an individual in conceptualizing DSR studies by making helpful suggestions. To do so we use extracts of a published DSR study and have GPT-3, a GLM provide suggestions for aspects of this study. These suggestions are then evaluated in a survey (n=33) regarding their helpfulness. Results show that GLM suggestions are perceived to be helpful, with some variation depending on expertise. Reported interest in using such a tool in the future was high. Describing how GLMs can offer helpful suggestions we contribute toward a DSR tool support ecosystem and, more generally, towards knowledge on how humans and (generative) AI systems can team up to solve complex problems. Collapse

Topics: artificial intelligence human computer interaction human AI collaboration generative AI system support

Methods: survey design requirement design principle correlation analysis descriptive statistic

Trusting the trust machine: Evaluating trust signals of blockchain applications

2023 | International Journal of Information Management | Citations: 0

Authors: Völter, Fabiane; Urbach, Nils; Padget, Julian

Abstract: Information systems research emphasizes that blockchain requires trust in the te ... Expand

Abstract: Information systems research emphasizes that blockchain requires trust in the technology itself. However, we lack knowledge on the applicability of established trust cues to blockchain technology. Thus, this paper’s objective is to empirically evaluate the effectiveness of several established IS trust formation factors on end user trust. We do so by conducting a between-groups experiment. While we can validate the applicability of previous IS trust research for blockchain technology to some extent, we find that trust signals emphasizing the technol­ ogy’s underlying trust-building characteristics are most effective. Hence, we highlight the need for contextual­ ization of trust research on blockchain technology. We provide both researchers and practitioners with insights for building trustworthy blockchain applications that enable trust-less interactions not only in theory but in practice. Collapse

Topics: blockchain human computer interaction usability IT work Bitcoin

Methods: experiment experimental group design artifact parametric test survey

Engaging Business Students with “Low-Code” Model Driven Development: Self-Efficacy Beliefs in an Introductory MIS Course

2023 | HICSS | Citations: 0

Authors: Wright, Kathie; Antonucci, Yvonne; Anderson, Laura; Townsend, Andrene

Abstract: “Low-code/no-code” (LC/NC) platforms are designed to empower non-IT business pro ... Expand

Abstract: “Low-code/no-code” (LC/NC) platforms are designed to empower non-IT business professionals to use model driven development to rapidly create sophisticated applications. Organizations are increasingly adding LC/NC platforms to their IT software portfolios. Thus, it is likely that current business students will encounter such tools and be expected to be able to use them. This research assesses the implementation of a low-code app development case within a business management information systems (MIS) course with the aim of identifying whether it promotes student self-efficacy of learning complex technology topics and how this relates to interest in further LC/NC skill development and interest in the MIS major. Collapse

Topics: self efficacy systems development low code development platform mobile application enterprise information system

Methods: survey nonparametric test data transformation factor analysis statistical hypothesis test