Value Implications of Sourcing Electronic Health Records: The Role of Physician Practice Integration

2023 | Information Systems Research | Citations: 0

Authors: Bardhan, Indranil R.; Bao, Chenzhang; Ayabakan, Sezgin

Abstract: Should hospitals source electronic health records (EHR) systems from a single ve ... Expand

Abstract: Should hospitals source electronic health records (EHR) systems from a single vendor or multiple vendors to deliver high-value care? We study hospitals’ EHR sourcing strategies based on their degree of integration with physician practices and its impact on the value of healthcare delivered. We propose a novel framework to define healthcare value as the extent to which a hospital effectively expends clinical resources to deliver services that improve patient outcomes. Drawing on modular systems and transaction cost economics theories, we propose a moderated-mediation model that explores the pathways through which EHR sourcing strategies can create value in healthcare. We test our research hypotheses on a large, longitudinal sample of U.S. hospitals and observe that hospitals with EHR configurations closer to single sourcing strategies exhibit greater health information sharing compared with hospitals with multisourced EHR systems. Furthermore, we find that hospital-physician practice integration moderates the impact of single sourcing on health information sharing, which in turn, improves value. Specifically, tighter integration between hospitals and physician practices can create greater value if it is aligned with hospitals’ EHR sourcing strategies. As the healthcare industry moves toward value-based payment reform, our findings provide a useful roadmap to practitioners and policy makers to improve the performance of hospitals and healthcare providers. History: Rajiv Kohli, Senior Editor; Sunil Wattal, Associate Editor. Funding: I.R. Bardhan thanks the Foster Parker Centennial Professorship and the Dean’s Research Excellence Grant at the McCombs School of Business at UT Austin for generous financial support. C. Bao thanks the Spears Fellowship at Oklahoma State University for financial support. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1183. Collapse

Topics: information exchange healthcare data health information system accounting database system

Methods: longitudinal research survey robustness check econometric modeling design artifact

Theories: transaction cost economics general systems theory institutional theory

Selecting the Optimal Number of Crowd Workers for Forecasting Tasks

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Carvalho, Arthur; Karimi, Majid

Abstract: Crowdsourcing platforms enable requesters to elicit information from thousands ... Expand

Abstract: Crowdsourcing platforms enable requesters to elicit information from thousands of workers worldwide. A question that arises when outsourcing a task to a crowd is how many crowd workers a requester should hire. Focusing on forecasting tasks, we provide a methodological way of answering that question by formally describing how the number of crowd workers relates to the expected forecast error. Specifically, we discuss how an error curve associates a number of hired crowd workers with a fixed and a variable error. We then suggest an optimality concept that enables requesters to select an optimal number of crowd workers based on the tolerable variable error. In an illustrative study on Amazon Mechanical Turk, we demonstrate how highly prescriptive our approach is. In particular, we show how requesters can perform ex-ante and ex-post analyses by determining the optimal number of workers before running a task and by determining the fixed error after running the task and collecting forecasts. Collapse

Topics: crowdsourcing decision support system

Methods: computational algorithm post analysis optimization model experiment mathematical model

Explanation matters: An experimental study on explainable AI

2023 | Electronic Markets | Citations: 0

Authors: Hamm, Pascal; Klesel, Michael; Coberger, Patricia; Wittmann, H. Felix

Abstract: Explainable artificial intelligence (XAI) is an important advance in the field o ... Expand

Abstract: Explainable artificial intelligence (XAI) is an important advance in the field of machine learning to shed light on black box algorithms and thus a promising approach to improving artificial intelligence (AI) adoption. While previous literature has already addressed the technological benefits of XAI, there has been little research on XAI from the user’s perspective. Building upon the theory of trust, we propose a model that hypothesizes that post hoc explainability (using Shapley Additive Explanations) has a significant impact on use-related variables in this context. To test our model, we designed an experiment using a randomized controlled trial design where participants compare signatures and detect forged signatures. Surprisingly, our study shows that XAI only has a small but significant impact on perceived explainability. Nevertheless, we demonstrate that a high level of perceived explainability has a strong impact on important constructs including trust and perceived usefulness. A post hoc analysis shows that hedonic factors are significantly related to perceived explainability and require more attention in future research. We conclude with important directions for academia and for organizations. Collapse

Topics: explainable artificial intelligence artificial intelligence perceived ease of use perceived usefulness digital dashboard

Methods: experimental group experiment parametric test experimental task ANOVA

Theories: information systems theory trust theory

Social informedness and investor sentiment in the GameStop short squeeze

2023 | Electronic Markets | Citations: 2

Authors: Kim, Kwansoo; Lee, Sang-Yong Tom; Kauffman, Robert J.

Abstract: We examine investor behavior on social media platforms related to the GameStop ( ... Expand

Abstract: We examine investor behavior on social media platforms related to the GameStop (GME) short squeeze in early 2021. Individual investors stimulated the stock market via Reddit social posts in the presence of institutional investors who bet against GME’s success as short sellers. We analyzed r/WallStreetBets subreddit posts related to GME’s trading patterns. We performed text-based sentiment analysis and compared the social informedness of posting users for GME trading on two social media platforms. The short squeeze occurred due to coordinated trading by individual investors, who discussed trading strategies on the platforms and drove collective social informedness-based trading behavior. Our findings suggest that the valence and number of submissions influenced GME’s intraday transaction volumes and precursors for irrational trading behavior patterns to have emerged. We provide a theoretical interpretation of what occurred and call for tighter monitoring of social news platforms. We also encourage effort to create an in-depth understanding of the observed patterns and the linkages between them and the larger equity markets. Collapse

Topics: Reddit social media Twitter analytical information system Python

Methods: Student's t-test sentiment analysis longitudinal research econometric modeling case study

Theories: cognitive dissonance theory

Positive Demand Spillover of Popular App Adoption: Implications for Platform Owners’ Management of Complements

2023 | Information Systems Research | Citations: 0

Authors: Lee, Mi Hyun; Han, Sang Pil; Park, Sungho; Oh, Wonseok

Abstract: As platform owners interact with end users and complementors, their demand-side ... Expand

Abstract: As platform owners interact with end users and complementors, their demand-side characteristics and performance affect the overall value creation of ecosystems. This research investigated how the emergence of popular complements on a mobile communication platform impacts the usage of other complementary products by the platform’s end users and how platform owners can benefit from such demand spillovers. We identified two different forms of demand spillovers (i.e., backward and forward) and conceptualized how each subsequently affects platform expansion. On the basis of individual user-level app usage data, we empirically demonstrated how the presence of a popular app alters the demand structure of a platform through changes in the usage of other apps operating within it. The findings reveal that popular app adoption by users increases the number of apps used and the duration of app usage, excluding the usage of popular apps, only within the platform offering a popular app. These results support the existence of positive spillovers from popular complement adoption on a platform. Such positive within-platform spillovers are derived from both backward spillovers onto existing apps adopted before popular app adoption and forward spillovers onto new apps to be adopted after the uptake of favored apps. These patterns suggest that positive spillovers of popular app adoption occur through both the increased retrieval of existing apps and reduced uncertainty about newly released apps. Furthermore, forward spillover is considerably stronger than backward spillover, implying that platform owners can reap benefits by coordinating the launch of new complements and the promotion of less-known counterparts to end users with the emergence of a popular app. These results shed light on how platform owners can manage their complements and create value beyond direct contributions from popular complements. History: Yulin Fang, Senior Editor; Yan Huang, Associate Editor. Collapse

Topics: mobile application mobile game Android mobile platform operating system

Methods: experimental group regression analysis method propensity score method longitudinal research propensity score matching

Theories: theory of economic growth

Compete with Me? The Impact of Online Gamified Competition on Exercise Behavior

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

Authors: Yang, Yang; Goh, Khim; Teo, Hock Hai; Tan, Sharon

Abstract: Online gamified competition utilizes competition as a core gamification design ... Expand

Abstract: Online gamified competition utilizes competition as a core gamification design element with affordances from wearables and mobile applications to track competitive activities and visualize information in an integrated way to shape users' exercise behaviors. However, a clear understanding of how online gamified competition cultivates exercise behaviors in different types of individuals is still lacking. We take into account the individual differences in exercise behaviors and categorize exercisers into three groups (active, moderate, and inactive) based on an adapted recency, frequency, and monetary value framework using key exercise behavior metrics. Theorizing online gamified competition as a means of social and temporal self-comparison, we examine the effect of performance feedback from two distinct modes of comparison (performance rankings and performance gap), and participants' relationships with their social comparison referents (i.e., rivalry intensity), on the exercise behaviors of different exerciser groups. Our results reveal that online gamified competition has differential effects on exercise behaviors across different exerciser groups. Specifically, we find that positive performance improvements are more motivational for active and moderate exercisers, while performance deterioration relative to historical exercise performance level is more discouraging for inactive exercisers. Performance rankings exhibit a more salient effect for moderate and inactive exercisers, and rivalry intensity has a stronger positive effect on active exercisers' exercise behavior. The strengthening effect of awareness affordances in mobile fitness apps is more notable with regard to the impact of rivalry intensity on moderate and inactive exercisers. We derive theoretical and practical implications of gamified information systems that use competition as a core design element for shaping the exercise behavior of individuals in different exerciser groups. Collapse

Topics: fitness tracker mobile fitness app mobile system gamification smart wearable device

Methods: theory development cluster analysis k-means clustering descriptive statistic design principle

Theories: social comparison theory theory of economic development

Institutional Disruptions and the Philanthropy of Multinational Firms

2022 | Organization Science | Citations: 0

Authors: Ballesteros, Luis; Magelssen, Catherine

Abstract: This paper studies philanthropy by multinational enterprises (MNEs) during insti ... Expand

Abstract: This paper studies philanthropy by multinational enterprises (MNEs) during institutional disruptions—the sudden and unexpected, temporary, and systemic breakdowns in market-oriented institutions. The central argument is that, under institutional disruptions, MNEs aim to restore factors that are essential for the market to function, such as infrastructure and labor markets, and the strength of the market restoration motive is positively associated with the economic importance of the affected country to the MNE. Analyses of donations from 2,000 MNEs headquartered in 63 countries in the aftermath of 265 major epidemics, natural disasters, and terrorist attacks affecting 129 countries suggest that the economic importance of the country to the firm strongly explains donations. Country market concentration, public aid, and the country’s regulatory quality moderate this effect. These associations are robust to a matching method; a vector of firm-, country-, and event-specific time-varying and -constant variables; and alternative motives, such as reputation, altruism, media salience, market standing, and poverty-gap avoidance. They offer evidence that company philanthropy in the aftermath of institutional disruptions may deviate from predicted behavior under stable conditions. Particularly, the findings contest the expectation that philanthropy rises in market competition. Monopolistic firms are comparatively large donors and may act as an economic stop-loss mechanism during large disruptions. Collapse

Topics: database system terrorist incident pandemic missing data earthquake

Methods: qualitative interview descriptive statistic natural language processing theory development robustness check

Theories: theory of economic fluctuations

Tarzan and chain: exploring the ICO jungle and evaluating design archetypes

2022 | Electronic Markets | Citations: 1

Authors: Bachmann, Nina M.; Drasch, Benedict; Fridgen, Gilbert; Miksch, Michael; Regner, Ferdinand; Schweizer, André; Urbach, Nils

Abstract: The phenomenon of a blockchain use case called initial coin offering (ICO) is dr ... Expand

Abstract: The phenomenon of a blockchain use case called initial coin offering (ICO) is drawing increasing attention as a novel funding mechanism. ICO is a crowdfunding type that utilizes blockchain tokens to allow for truly peer-to-peer investments. Although more than $7bn has been raised globally via ICOs as at 2018, the concept and its implications are not yet entirely understood. The research lags behind in providing in-depth analyses of ICO designs and their long-term success. We address this research gap by developing an ICO taxonomy, applying a cluster analysis to identify prevailing ICO archetypes, and providing an outlook on the token value market performance for individual archetypes. We identify five ICO design archetypes and display their secondary market development from both a short-term and a long-term perspective. We contribute to an in-depth understanding of ICOs and their implications. Further, we offer practitioners tangible design and success indications for future ICOs. Collapse

Topics: Ethereum Bitcoin crowdfunding crowdsourcing cryptocurrency

Methods: cluster analysis qualitative interview chi squared test design methodology hierarchical clustering

Theories: auction theory

The Theory and Measurement of Expertise-Based Problem Solving in Organizational Teams: Revisiting Demonstrability

2022 | Organization Science | Citations: 0

Authors: Bonner, Bryan L.; Shannahan, Daniel; Bain, Kristin; Coll, Kathryn; Meikle, Nathan L.

Abstract: The current paper revisits and builds upon task demonstrability, which defines t ... Expand

Abstract: The current paper revisits and builds upon task demonstrability, which defines the criteria necessary for groups to choose a correct response if any member prefers that response. We identify boundary conditions of the current conceptualization of task demonstrability with respect to its use in understanding modern organizational teams. Specifically, we argue that, in its current form, task demonstrability is not optimally suited to studying ongoing teams in which member expertise varies and teams work to complete complex multifaceted tasks. To address this issue, we provide a revisited perspective on demonstrability. We specify the nomological network of revisited demonstrability and recast each of its criteria in a form that preserves the original intent of the construct, but has broader applicability, particularly to organizational contexts. We then discuss theoretical implications and managerial applications of the construct. Finally, noting that there is no standard assessment tool for demonstrability (original or revisited), we develop and validate a measure to facilitate future research. Collapse

Topics: problem solving Near Field Communication team productivity personality task complexity

Methods: factor analysis data transformation chi squared test survey design ordinary least square

Theories: big five model

MEET YOUR NEW COLLE(AI)GUE – EXPLORING THE IMPACT OF HUMAN-AI INTERACTION DESIGNS ON USER PERFORMANCE

2022 | European Conference On Information Systems | Citations: 0

Authors: Braun, Marvin; Greve, Maike; Riquel, Johannes; Brendel, Alfred Benedikt; Kolbe, Lutz

Abstract: Artificial Intelligence (AI) has an increasing impact on industries, establishi ... Expand

Abstract: Artificial Intelligence (AI) has an increasing impact on industries, establishing a new way of solving tasks and automating work routines. While AI-based systems have become new colleagues for some processes, the tasks of some humans have shifted towards supervising AI. Essentially, humans need to adapt to a new form of interaction with AI-based systems because AI functioning is more similar to cognitive processes of humans than traditional information systems, e.g., in terms of their intransparent decision making. Previous research indicates that AI adds new challenges to human-computer interaction, and new frameworks for human-AI interaction are developed. However, current research lacks empirical research on the design of such interactions. We conducted a 2x2x2 experiment of AIsupported information extraction and measured the ability of participants to validate the extracted information by the AI. Our results indicate that the design of human-AI interaction significantly impacts users' supervising performance.interaction and the current state of research. Second, the SDT is explained and applied to derive hypotheses regarding human-AI interaction. Collapse

Topics: artificial intelligence human AI collaboration decision support system human computer interaction human resource management

Methods: experiment ANOVA parametric test information extraction theoretical contribution

Theories: signal detection theory