Becoming a blockchain user: understanding consumers’ benefits realisation to use blockchain-based applications

2023 | European Journal of Information Systems | Citations: 0

Authors: Raddatz, Nirmalee; Coyne, Joshua; Menard, Philip; Crossler, Robert E

Abstract: Data breaches and cyber incidents are on the rise, and companies continually res ... Expand

Abstract: Data breaches and cyber incidents are on the rise, and companies continually research new technologies to defend against attacks and protect customer data. The blockchain is a data store designed to promote data privacy, as well as transaction integrity. Enterprises in several industries, especially banking, have investigated the implementation of blockchain-based databases to replace centralised databases as one mechanism for protecting customers’ data by separating transactional data from personally identifiable information. Despite the blockchain’s privacy protections, consumers remain largely unaware of these benefits. Building on the Health Belief Model (HBM), we include privacy concerns and inertia as critical factors that influence consumers’ perceptions of blockchain-based databases’ benefits. Using a sample of 304 respondents, we test a theoretical model incorporating these factors. Our study results indicate threat severity, threat susceptibility, awareness, and inertia significantly influence the perceived benefits of blockchain, which has a significant positive influence on consumers’ intention to switch to blockchain-based applications. Although consumers’ comfort with the status quo of traditional banking mechanisms is a significant barrier to the realisation of blockchain banking applications benefits, additional awareness of consumer privacy protections can persuade customers to use the blockchain-based applications, especially if they exhibit heightened privacy concerns. Collapse

Topics: blockchain database system information privacy concern privacy banking sytem

Methods: survey survey design chi squared test structural equation modeling expert panel

Theories: health belief model loss aversion

Giving to Get Well: Patients’ Willingness to Manage and Share Health Information on AI-Driven Platforms

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

Authors: Raddatz, Nirmalee; Kettinger, William; Coyne, Joshua

Abstract: The digitalization of healthcare makes for the widespread availability of patie ... Expand

Abstract: The digitalization of healthcare makes for the widespread availability of patient-provided data. Artificial Intelligence (AI) relies on this data. In this information-intensive environment, it is imperative to understand the contributing factors of an individual's willingness to manage and share personal health information (PHI). Drawing from the health belief model, we identify the factors that motivate individuals to manage and share their PHI in an AI-driven health platform to obtain its intended benefits. We recognize security risks and present the use of a blockchain database as a representative means of securely managing and controlling an individual's PHI. Data collected from a nationally representative sample of allergy sufferers indicate that the health belief model strongly predicts willingness to share PHI on a personalized AI-supported platform. Our study makes significant contributions by investigating the factors that motivate patients to use an AI-driven health platform to manage their health.Artificial intelligence (AI) advances are taking shape and promising to transform the healthcare industry. According to a study by Accenture, AI in the U.S. healthcare industry is expected to have a compound annual growth rate of 46.1% and reach $95.65 billion by 2028 (Vantage Market Research, 2022). AI can offer a more personalized healthcare experience that optimizes the time it takes to gather information for more efficient decision-making, ultimately allowing better patient care. AI is making its presence known across the medical profession, and medical professionals, researchers, patients, and healthcare providers that do not embrace this technology could be left behind.Ultimately, the success of AI-based platforms for medical purposes depends heavily on individual willingness to use the technology. 1 AI can collect, combine, and analyze large amounts of data from various sources, increasing information-gathering and processing capabilities tremendously (Deane, 2018). This capability offers numerous benefits but also potential risks. For example, according to Rocher, Hendrickx, and de Montjoye (2019), AI can profile, identify, and track individuals by de-anonymizing once anonymized information. Some AI only needs 15 data points about an individual to identify the person. Because of security risks, people may be reluctant to share their personal health information (PHI) with AIbased platforms (Deane, 2018).Achieving the potential benefits of AI from patient platforms will depend on (1) the development of intelligent systems that can collect and analyze vast datasets and (2) the willingness of data owners to share and manage their data with these intelligent systems (Agarwal & Khuntia, 2009). Within healthcare, these conditions are (1) the development of systems that can collect and process PHI and provide or augment diagnostics as/more efficiently and effectively than a traditional doctor-patient profile and (2) patients' ability and willingness to manage and share their own PHI. AI developers work to satisfy the first condition but often take the second condition for granted with the attitude, "If we build it, they will come." However, the first condition is certainly not sufficient to satisfy the second. Without convincing many individuals to share their PHI, an AI-driven health platform cannot serve its purpose. As a result, the question arises as to how to increase individuals' willingness and ability to manage and share their PHI with AI-powered health platforms. Thus, the purpose of our investigation is to discover how to begin to satisfy this second condition by addressing the following questions:Are patients willing to share their PHI with AI-driven health platforms despite security risks? Are patients empowered and ready to manage their PHI, thus, in large part, bringing the control of information to the individual?While numerous studies focus on the design aspects of AI-based predictive models, a significant lack of studies investigate the behavioral aspects pertaining to the usability of these models by patients and clinicians. We adapt Rosenstock's (1974) health belief model (HBM) and expand it to identify the determinants of our test subjects' willingness to share PHI with an AI-driven health platform that uses a blockchain-based database. We apply the HBM to a patient profile in which patients do not solely rely on traditional healthcare provider information channels to get diagnostic and treatment information. Instead, they are empowered to use their PHI to get diagnostic and treatment information from an AI platform. As a result, our application of the HBM moves beyond a patient's willingness to follow a proactive health behavior to considering how patients might proactively use (manage and share) their personal health information to help them receive health-related guidance and insights. This patient information management and information sharing behavior represent a future path of the healthcare industry, and we wish to determine whether this well-regarded health-centered model explains behavior under this new "informationally empowered" patient health profile.Because we care about the practical usability of AI-driven health platforms rather than purely hypothetical usability, we model our research instrument on an actual AI-driven health platform (i.e., doc.ai). 2 This platform uses AI for diagnostic and treatment information and a blockchain-based database to store PHI in 1 We define an AI-based healthcare platform as a software application that (1) collects and stores data for analysis by artificial intelligence (e.g., machine learning) and (2) makes the results of that data analysis available to patients and healthcare professionals in order to guide diagnostic and treatment decisions. We base this definition on an actual AI-based healthcare platform (doc.ai) that we describe in section 2. 2 We provide more specific information regarding this health platform in sections 2 and 3. Collapse

Topics: artificial intelligence self efficacy healthcare data blockchain database system

Methods: survey survey design SEM tool chi squared test machine learning

Theories: health belief model technology acceptance model

Data Marketplaces: Value Drivers and Pricing Approaches of Data

2023 | European Conference On Information Systems | Citations: 0

Authors: Radic, Marija; Herrmann, Philipp; Stein, Theresa; Kleine, Simon

Abstract: Although the data monetization market continues to grow, many data marketplaces ... Expand

Abstract: Although the data monetization market continues to grow, many data marketplaces have failed and withdrawn from the market. Particularly the pricing of data remains a challenge. Research to date cannot provide satisfactory recommendations for practitioners. The objective of this paper is to contribute to closing this gap by addressing two research questions: (1) Which price setting mechanisms are chosen in practice? (2) Which value drivers contribute to assessing the value of a dataset? Our results show that data marketplaces dominantly choose cost-based pricing approaches or hand over pricing responsibilities to data providers and buyers. At the same time, they prioritize value drivers outside the cost category. One explanation is that data marketplaces are striving for a value-based pricing approach, but currently fail to implement it. We suggest a pragmatic pricing approach that calculates the base price based on the costs and considers value drivers for margin calculation. Collapse

Topics: price management data quality accounting database system marketing management

Methods: qualitative interview structured literature research literature sample personal interview survey

A Matter of Transition: Authenticity Judgments and Attracting Employees to Hybridized Organizations

2023 | Organization Science | Citations: 0

Authors: Radoynovska, Nevena; Ruttan, Rachel

Abstract: Category-spanning organizations have been shown to face a number of penalties co ... Expand

Abstract: Category-spanning organizations have been shown to face a number of penalties compared with organizations occupying a single category. The assumption seems to be, however, that organizations spanning the same categories will be evaluated similarly. Yet, this is not always the case. We know far less about why evaluations may differ within category-spanners, largely due to existing studies’ focus on comparing single-category to category-spanning organizations in equilibrium states at a fixed point in time. Instead, this paper investigates audience judgments of organizations as they transition from single to multiple categories. We rely on the empirical setting of social-commercial hybrids—an intriguing context in which to explore category-spanning across market and nonmarket domains associated with distinct values, norms, and expectations. In a series of two experimental studies, we investigate how hybridization affects audience judgments of organizational authenticity and the ability to attract potential employees. We find that across organizational fields associated with nonprofit (communal) and for-profit (market exchange) norms, hybridization—more than hybridity itself—triggers audience cynicism and leads to decreased judgments of authenticity. However, the penalties for hybridizing are only observed when organizations also move away from field-level profit-status norms. The findings contribute to the category-spanning and authenticity literatures by integrating social psychological and organizational theory perspectives to offer a dynamic view of spanning beyond for-profit, market contexts. They also offer empirical support for the theorized multidirectionality of mission drift in hybrid organizations, while suggesting that drifting need not always be detrimental.History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory.Supplemental Material: Supplemental online materials are available at https://doi.org/10.1287/orsc.2021.1495. Collapse

Topics: organizational change database system online labor market

Methods: parametric test experiment statistical power analysis ANOVA statistical hypothesis test

Theories: organizational behavior theory organizational theory

Artificial Intelligence in the Workplace: Implementation Challenges and Opportunities

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Raftopoulos, Marigo; Hamari, Juho

Abstract: This study aims to investigate how firms can prepare for artificial intelligenc ... Expand

Abstract: This study aims to investigate how firms can prepare for artificial intelligence (AI) adoption and how AI creates business values for adopting firms. We propose that, first, leveraging AI for value creation depends on the presence of an enabling resource foundation, consisting of a stack of technological and managerial resources. According to the real options theory, the stronger such a resource foundation is, the more valuable the option it creates for a firm to adopt AI, and consequently the firm is more likely to exercise the option to adopt. Second, we propose that, after adoption, the depth of AI use can have negative impacts on employee productivity, while the breadth of AI use can have positive impacts. We empirically validate these hypotheses based on a sample of 6,854 manufacturing firms in a coastal province in China. Collapse

Topics: artificial intelligence individual productivity organizational value value creation productivity

Methods: survey experiment regression analysis method

Theories: real options theory resource based view of the firm options theory

Psychological factors affecting social media usage: A U&G theory perspective

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Raghavendra, Ananya; Bellary, Sreevatsa; Sengupta, Pooja; Bala, Prof Pradip Kumar; Mukherjee, Arindam

Abstract: ... Expand

Abstract: Collapse

Topics: social media pandemic programming language social media addiction

Methods: qualitative interview cross sectional research cross sectional survey survey mixed method

How is my IT department leading to Digital Innovation Success?

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Rahman, Md. Tuhinur; Palvia, Prashant

Abstract: Digital innovation, driven by IT departments, is a key enabler for success in a ... Expand

Abstract: Digital innovation, driven by IT departments, is a key enabler for success in all types of organizations around the world. Although there are a lot of touted benefits, there is not much scholarly attention as to how digital innovation success can be achieved in organizations. Drawing upon social capital theory, this study plans to examine how functional IT employees' relationship with the Chief Information Officer (CIO) can help organizations in achieving digital innovation success. The study proposes that the social capital of the relationship between CIO and functional IT employees will enhance both external and internal digital innovation success through more closely engaging functional IT employees in the decisionmaking processes of CIO. Furthermore, the study aims to identify the role of environmental turbulence and organizational culture as moderators in the proposed model. Collapse

Topics: IT workforce innovation management digital innovation Chief Information Officer social capital

Methods: structural equation modeling survey statistical hypothesis test

Theories: social capital theory

Impact of social influence on continuous use of mobile game applications

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Rahman, Md. Tuhinur; Singh, Rahul

Abstract: Mobile games dominate the mobile application market in terms of the share of ap ... Expand

Abstract: Mobile games dominate the mobile application market in terms of the share of applications and total revenue. Organizations and developers of mobile game applications are challenged to identify factors that influence users' intentions and continuous use of the games. From this perspective, we draw on social identity theory (SIT) and plan to identify the moderating effect of social influence on the relationship between user satisfaction and continuous use of mobile game applications. This study also aims to investigate the direct impact of social influence on continuous use of mobile game applications. We propose that social influence (compliance, internalization, and identification) will positively moderate the transition from initial adoption to continuous use. We will conduct an online survey in two phases to test the research model and hypotheses. Collapse

Topics: social influence mobile game mobile system user satisfaction mobile application

Methods: survey structural equation modeling longitudinal research statistical hypothesis test

Theories: social identity theory

Delays Impair Learning and Can Drive Convergence to Inefficient Strategies

2023 | Organization Science | Citations: 0

Authors: Rahmandad, Hazhir; Gary, Michael Shayne

Abstract: With so many possible choices, why do managers adopt the strategies they do? We ... Expand

Abstract: With so many possible choices, why do managers adopt the strategies they do? We identify delays between adopting a strategy and observing the full implications of that choice as a critical factor influencing strategic choices. Using a simulation of a service firm, we conduct two behavioral experiments to investigate how delays interact with outcome uncertainty to shape learning, strategy adaptation, and performance outcomes. Two mechanisms emerge from how different subject groups perceive, react to, and learn in the presence of delayed feedback and uncertainty. First, when multiple viable strategies exist, longer delays lead both general participants and experienced managers toward alternatives that have rapid returns. When those alternatives are suboptimal, delays may strengthen convergence to inefficient strategies. Second, delays and uncertainty may also induce learners to persist with their a priori strategies. Managers show larger confidence in their priors and thus underperform general participants when the underlying task structure diverges from those priors. Both mechanisms can undermine performance. Moreover, delays and uncertainty may reduce heterogeneity in strategies and performance in more dynamic, uncertain environments, leading to convergence as tasks grow more complex and where decision makers possess similar priors.History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory.Funding: Funding from the Massachusetts Institute of Technology and UNSW Business School supported this research.Supplemental Material: The online appendices are available at https://doi.org/10.1287/orsc.2020.1405. Collapse

Topics: human resource management decision making social influence advertising management

Methods: experiment simulation statistical power analysis statistical hypothesis test experimental task

Theories: behavioral theory

Governance in social media platforms of minority organizations

2023 | HICSS | Citations: 0

Authors: Rahrovani, Y.

Abstract: Social media platforms can offer a sense of social inclusion and equitable acce ... Expand

Abstract: Social media platforms can offer a sense of social inclusion and equitable access to information for minority groups, including minority immigrants to Western countries. However, even as they empower minority community-based organizations (CBOs) to assist their members, these platforms can also create conditions for further exclusion and inequity if they are too exclusive (i.e., drift towards segregation) or too inclusive (i.e., drift towards dilution). This paper aims to extend prior platform governance research to understand how to govern minority CBO platforms featuring both minority and non-minority members in a way that maintains a balance between segregation and dilution, the two paradoxical forces of drifting. By adopting a longitudinal, grounded-theory study of three social media platforms in a minority CBO (one segregated, one balanced, and one diluted), I identify three categories of governing practices (ajar gatekeeping, opportunity manipulating, and output harmonizing), which maintain platform balance against segregational or dilutional drifting. Collapse

Topics: social media platform governance Telegram accounting digital platform

Methods: qualitative interview longitudinal research grounded theory archival research triangulation

Theories: control theory