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Blockchain innovation for consent self-management in health information exchanges
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2023 | Decision Support Systems | Citations: 0
Authors: Anderson, Chad; Carvalho, Arthur; Kaul, Mala; Merhout, Jeffrey W.

Abstract: With the increasing digitalization of health data, patients need to make informe ... Expand

Abstract: With the increasing digitalization of health data, patients need to make informed decisions about the online sharing of their protected health information. This necessitates a robust technical infrastructure that enables patients to self-manage consent and the trusted exchange of this information across sharing entities. Unfortu nately, current health information exchange systems in the U.S. are limited in both these regards. While there is recent work on digital patient consent management, there is limited work that provides effective solutions for patient self-management of consent. Further, interoperability issues in the way health information exchanges are currently architected and differences in regulations across localities exacerbate the challenges of consent man agement. In this research, we survey potential patients' willingness to self-manage healthcare-related consent. Having established the desire for consent self-management, we propose a solution that enables the seamless sharing of patient consent across different healthcare providers and health information exchanges. Specifically, we use a rigorous design science approach to create a blockchain-based, self-managed patient consent system and we evaluate the design through an instantiated prototype. The results of our study should be useful to researchers in healthcare information management as well as to practitioners designing consent management systems. Our research contributes to design science research with an innovative, rigorously evaluated, design principles-based artifact that addresses a critical problem of sharing protected health information. Collapse

Semantic filters: evidence-based design

Topics: blockchain mobile application information exchange privacy Ethereum

Methods: survey design artifact design science design process design principle

Theories: evidence-based design
ARTIFICIAL INTELLIGENCE-AUGMENTED DECISION MAKING IN SUPPLY CHAIN MONITORING: AN ACTION DESIGN RESEARCH STUDY

2023 | European Conference On Information Systems | Citations: 0
Authors: Herath Pathirannehelage, Savindu; Jóhannsson, Jóhann; Shrestha, Yash; Krogh, Georg von

Abstract: Organizations are progressively adopting hybrid human-artificial intelligence ( ... Expand

Abstract: Organizations are progressively adopting hybrid human-artificial intelligence (AI) systems in decisionmaking processes, with human decisions being augmented by AI insights. Among the promising AI applications in supply chain monitoring (SCMo) are predictive maintenance systems that predict potential device failures and augment maintenance decisions, allowing for timely and efficient interventions. Despite the growing proliferation of such systems, prescriptive knowledge encompassing technical, business, and organizational aspects on how to design, develop, and deploy them in actual operational environments remains limited. To address this shortcoming of evidence-based design principles in practice, our action design research developed a predictive maintenance system that predicts SCMo device failures and augments the maintenance decisions about those devices. By doing so, we outline generalizable design principles to guide prospective predictive maintenance systems in SCMo. Collapse

Semantic filters: evidence-based design

Topics: artificial intelligence predictive maintenance organizational context decision making systems evaluation

Methods: machine learning design principle design artifact artificial neural network random forest classification

Theories: evidence-based design
Do You Really Know if It’s True? How Asking Users to Rate Stories Affects Belief in Fake News on Social Media
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2022 | Information Systems Research | Citations: 0
Authors: Moravec, Patricia L.; Kim, Antino; Dennis, Alan R.; Minas, Randall K.

Abstract: Research has shown that consuming ratings influences purchase decisions in e-com ... Expand

Abstract: Research has shown that consuming ratings influences purchase decisions in e-commerce and also has modest effects on belief in news articles on social media. However, we do not know if the act of creating a rating influences belief in online news stories. Unlike e-commerce settings in which ratings typically come from those who have personally used the product or service, social media users who submit their ratings for news articles typically lack firsthand knowledge of the events reported in the news, making it difficult for most users to rate news articles accurately. We propose that one key benefit of user ratings in the context of news on social media lies in triggering users who create the ratings (as opposed to consume the ratings) to realize that they lack this firsthand knowledge, thus inducing them to become more skeptical of articles they see. We asked 68 social media users to assess the believability of 42 social media articles and measured their cognitive activity using electroencephalography. We found that asking users to rate articles using a self-referential question induced them to think more critically—as indicated by increased activation in the medial prefrontal cortex and dorsolateral prefrontal cortex—and made them less likely to believe the articles. The effect extended to subsequent articles; after being asked to rate an article, users were less likely to believe other articles that followed it whether they were asked to rate them or not. Overall, our findings suggest that asking users to evaluate the truthfulness of articles using self-referential rating questions may not only produce rating information that could be used by others later in time, but also has an immediate benefit of inducing users to think more critically about all articles they see. Collapse

Semantic filters: evidence-based design

Topics: social media Facebook fake news misinformation crowdsourcing

Methods: theory development electroencephalography experiment hierarchical linear modeling statistical hypothesis test

Theories: evidence-based design
Iterative uncertainty reduction in multi-actor smart service innovation
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2022 | Electronic Markets | Citations: 0
Authors: Poeppelbuss, Jens; Ebel, Martin; Anke, Jürgen

Abstract: Smart service innovation is the process of reconfiguring resources, structures, ... Expand

Abstract: Smart service innovation is the process of reconfiguring resources, structures, and value co-creation processes in service systems that result in novel data-driven service offerings. The nature of such offerings requires the involvement of multiple actors, which has been investigated by a few studies only. In particular, little is known about the multiple actors’ efforts to manage uncertainty in the process of establishing smart service systems. Empirically grounded in data from 25 interviews with industry experts, we explore how organizations act and interact in smart service innovation processes. For our data analysis, we adopt a microfoundational view to derive a theoretical model that conceptualizes actor engagement as a microfoundation for iterative uncertainty reduction in the actor-to-actor network of the smart service system. Our study contributes to information systems research on service systems engineering and digital transformation by explaining smart service innovation from both a multi-actor and a multi-level perspective, drawing on service-dominant (S-D) logic and microfoundations as well-established theoretical lenses. Collapse

Semantic filters: evidence-based design

Topics: innovation management business process innovation digital transformation participatory design value creation

Methods: qualitative interview design methodology theory development design science design artifact

Theories: service-dominant logic socio technical theory evidence-based design
A Microservice-Based Reference Architecture for Digital Platforms in the Proteomics Domain
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2021 | DESRIST | Citations: 0
Authors: Shraideh, Marwin; Samaras, Patroklos; Schreieck, Maximilian; Krcmar, Helmut

Abstract: Proteomics holds huge innovations for healthcare such as personalized medicine t ... Expand

Abstract: Proteomics holds huge innovations for healthcare such as personalized medicine to tremendously increase people’s health. Due to its rapid growth, its multidimensional data sets and the related need for the latest technologies and huge computing capacities, a diverse and scattered tool and repository landscape evolved in an uncontrolled manner. Therefore, tool usage is complicated, time consuming and almost impossible without expert IT skills. To create the conditions for new innovations in the proteomics domain and making first steps towards personalized medicine, digital platforms are needed. However, designing such a system is complex and was not yet supported by information systems. Consequently, we will design and implement a sustainable microservice-based reference architecture for digital platforms in the proteomics domain based on the example of ProteomicsDB that focuses on maintainability, extendibility, and reusability by following the design science requirements. With our reference architecture, we extend evidence-based design knowledge in real-world information systems contributing to information systems research and provide proteomics researchers, but also practitioners a foundation for establishing new business models and enhancing existing or developing new services or platforms. Collapse

Semantic filters: evidence-based design

Topics: microservice architecture digital platform authorization electronic authentication user requirement

Methods: design science design artifact qualitative interview design theory literature study

Theories: evidence-based design
Designing Effective Privacy Nudges in Digital Environments: A Design Science Research Approach
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2020 | DESRIST | Citations: 0
Authors: Barev, Torben Jan; Janson, Andreas; Leimeister, Jan Marco

Abstract: When using digital technologies, various data traces are left behind for collect ... Expand

Abstract: When using digital technologies, various data traces are left behind for collection, storage and analysis. Innovative solutions for information systems are needed that mitigate privacy risks and foster information privacy. One mechanism to achieve this is using privacy nudges. Nudges are a concept from behavioral economics to influence individual’s decisions. However, many nudges show low or at least less effects than choice architects hope for and expect. Therefore, this design science research (DSR) project focusses on developing evidence-based design principles for privacy nudges to improve their effectiveness and pave the way for more privacy sensitive IT systems. In this context, we adopt a DSR approach from Vaishnavi & Kuechler. From a theoretical perspective, we are contributing to the discussion of what drives privacy sensitive behavior. We extend generic nudge design models, making them applicable in the context of data disclosure. For practitioners, we provide guidance on how to design and implement effective privacy nudges in the user interface of digital work systems. Collapse

Semantic filters: evidence-based design

Topics: privacy IT work user interface usability

Methods: design principle design theory design science design requirement design artifact

Theories: evidence-based design
Combating Fake News on Social Media with Source Ratings: The Effects of User and Expert Reputation Ratings
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2019 | Journal of Management Information Systems | Citations: 75
Authors: Kim, Antino; Moravec, Patricia L.; Dennis, Alan R.

Abstract: As a remedy against fake news on social media, we examine the effectiveness of t ... Expand

Abstract: As a remedy against fake news on social media, we examine the effectiveness of three different mechanisms for source ratings that can be applied to articles when they are initially published: expert rating (where expert reviewers fact-check articles, which are aggregated to provide a source rating), user article rating (where users rate articles, which are aggregated to provide a source rating), and user source rating (where users rate the sources themselves). We conducted two experiments and found that source ratings influenced social media users' beliefs in the articles and that the rating mechanisms behind the ratings mattered. Low ratings, which would mark the usual culprits in spreading fake news, had stronger effects than did high ratings. When the ratings were low, users paid more attention to the rating mechanism, and, overall, expert ratings and user article ratings had stronger effects than did user source ratings. We also noticed a second-order effect, where ratings on some sources led users to be more skeptical of sources without ratings, even with instructions to the contrary. A user's belief in an article, in turn, influenced the extent to which users would engage with the article (e.g., read, like, comment and share). Lastly, we found confirmation bias to be prominent; users were more likely to believe — and spread — articles that aligned with their beliefs. Overall, our results show that source rating is a viable measure against fake news and propose how the rating mechanism should be designed. Collapse

Semantic filters: evidence-based design

Topics: social media fake news Facebook misinformation electronic commerce

Methods: experiment theory development survey statistical hypothesis test linear regression analysis

Theories: evidence-based design
Do You Really Know If It’s True? How Asking Users to Rate Stories Affects Belief in Fake News on Social Media

2019 | HICSS | Citations: 0
Authors: Moravec, Patricia; Kim, Antino; Dennis, Alan; Minas, Randall

Abstract: The rise of “fake news” has become a major concern for social media platforms. I ... Expand

Abstract: The rise of “fake news” has become a major concern for social media platforms. In response, Facebook has proposed and tested the idea of users flagging and rating news articles and sources, much akin to how consumers rate products and services on the Internet. One obvious challenge with this crowdsourced rating approach is whether the users really know enough to rate news articles and sources. Perhaps, a side benefit of asking users to evaluate an article—and asking about their personal experience with the event described in the article—is making them realize that they do not know enough about the event to make an accurate judgment, thus pushing them to become more skeptical. We asked 68 social media users to assess the believability of 42 social media headlines. We found that, while users were generally more likely to believe articles that agreed with their point of view, asking users to rate pushed them to think more critically about the truthfulness of the articles. Moreover, once users had been asked to rate some articles, they remained critical of other articles as well, even without the rating prompt. Overall, our findings suggest that asking users to evaluate the truthfulness of articles may not only produce rating information that can be a useful reference at a later point in time but also have an immediate benefit of alerting users to think more critically about all articles they see. Collapse

Semantic filters: evidence-based design

Topics: social media Facebook mindfulness fake news

Methods: experiment theory development robustness check statistical hypothesis test experimental design

Theories: evidence-based design
Engaging Users to Co-Create – Implications for Service Systems Design by Evaluating an Engagement Platform

2018 | HICSS | Citations: 0
Authors: Grotherr, Christian; Semmann, Martin; Böhmann, Tilo

Abstract: Far-reaching digitalization affords significantly more opportunities for engagin ... Expand

Abstract: Far-reaching digitalization affords significantly more opportunities for engaging actors and mobilizing resources in service systems. By leveraging these capabilities, digitally enabled service systems can facilitate user-generated services. Traditional service engineering approaches provide for such service systems. This paper presents and discusses the evaluation of a field-based design science research project for designing an engagement platform that facilitates the co-creation of user-generated services. This study reports contributions to the design knowledge of such an engagement platform and their consequences for engagement activities. Based on the evaluation, we propose design propositions for such an engagement platform from a sociotechnical perspective. Collapse

Semantic filters: evidence-based design

Topics: participatory design user behavior embedded system mobile system usability

Methods: design science cognitive walkthrough design methodology qualitative interview design theory

Theories: evidence-based design
Says Who?: How News Presentation Format Influences Perceived Believability and the Engagement Level of Social Media Users

2018 | HICSS | Citations: 0
Authors: Kim, Antino; Dennis, Alan

Abstract: We investigate whether the news presentation format affects the believability of ... Expand

Abstract: We investigate whether the news presentation format affects the believability of a news story and the engagement level of social media users. Specifically, we test to see if highlighting the source delivering the story can nudge the users to think more critically about the truthfulness of the story that they see, and for obscure sources, whether source ratings can affect how the users evaluate the truthfulness. We also test whether the believability can influence the users' engagement level for the presented news post (e.g., read, like, comment, and share). We find that such changes in the news presentation format indeed have significant impacts on how social media users perceive and act on news items. Collapse

Semantic filters: evidence-based design

Topics: social media Facebook usability user interface fake news

Methods: descriptive statistic statistical hypothesis test expert panel theory development survey

Theories: evidence-based design

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Found 16 articles

Blockchain innovation for consent self-management in health information exchanges

ARTIFICIAL INTELLIGENCE-AUGMENTED DECISION MAKING IN SUPPLY CHAIN MONITORING: AN ACTION DESIGN RESEARCH STUDY

Do You Really Know if It’s True? How Asking Users to Rate Stories Affects Belief in Fake News on Social Media

Iterative uncertainty reduction in multi-actor smart service innovation

A Microservice-Based Reference Architecture for Digital Platforms in the Proteomics Domain

Designing Effective Privacy Nudges in Digital Environments: A Design Science Research Approach

Combating Fake News on Social Media with Source Ratings: The Effects of User and Expert Reputation Ratings

Do You Really Know If It’s True? How Asking Users to Rate Stories Affects Belief in Fake News on Social Media

Engaging Users to Co-Create – Implications for Service Systems Design by Evaluating an Engagement Platform

Says Who?: How News Presentation Format Influences Perceived Believability and the Engagement Level of Social Media Users