Exploring the Interactions between Social Movement Activists and Target Organizations on Social Media

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Bakhshi, Fateme; Faik, Isam

Abstract: Social movements are recognized as significant agents of change in modern socie ... Expand

Abstract: Social movements are recognized as significant agents of change in modern societies. Their influence is increasingly channeled through social media platforms to mobilize support and direct collective action toward targeted organizations. However, targeted organizations also resort to social media channels to counter the actions of social movements that are directed at them. There is little research on organizations' responses to movement's actions on social media. This study endeavors to explore the dynamics of interactions between social movement activists and their target organizations by utilizing narrative network analysis. Drawing on framing theory, this research endeavors to elucidate how social movement actors employ various frames. Specifically, we examine the Twitter accounts of various Canadian banks and activists targeting them for their investments in fossil fuels. We analyze the narrative networks and counter-networks to develop a theoretical understanding of how the social media interactions between activists and target organizations evolve over time. Collapse

Topics: social media Twitter web page design thinking

Methods: narrative network analysis network analysis computational algorithm event log

Theories: framing theory

Governance of Digital Health Data on Cooperatively Organized Platforms – a Design Thinking Approach

2023 | HICSS | Citations: 0

Authors: Burmann, Anja; Langer, Henrike; Bosompem, Jennifer; Clemens, Timo; Herten, Benjamin; Kerstan, Leah; Lauer, Romy; Naeve, Peter; Geller, Simon; Huhnt, Jönne; Merkel, Sebastian

Abstract: More and more stakeholders are collecting data for improving their services: fro ... Expand

Abstract: More and more stakeholders are collecting data for improving their services: from scientific research over public administration to commercial enterprises. Existing data management services offer few rights of co-determination for their users. Data cooperatives aim to provide a democratic alternative to this. Through such a platform cooperative members are supposed to be enabled to share their data in a self-determined way. In this paper, we present a design thinking-based user research with stakeholders of data cooperatives in a health-data context. We provide an overview of motivations, expectations, and interfaces between a cooperative and individuals as cooperative members, organizations, representatives from research, and policy makers. In an iterative process, 34 interviews were conducted with different stakeholder groups, from which 7 personas were subsequently derived. For these, 4 prototypes were developed and tested with potential users. Our results show that all interviewed groups were very interested in the concept of data cooperatives. At the same time, it proves challenging to reconcile the conflicting internal and external requirements and to implement attractive value propositions for all stakeholders. Collapse

Topics: design thinking healthcare data user centered design value creation organization structure

Methods: qualitative interview design methodology design artifact literature sample literature study

From transformation to normalisation: An exploratory study of a large-scale agile transformation

2023 | Journal of Information Technology | Citations: 0

Authors: Carroll, Noel; Conboy, Kieran; Wang, Xiaofeng

Abstract: Following the highly pervasive and effective use of agile methods at the team le ... Expand

Abstract: Following the highly pervasive and effective use of agile methods at the team level, many software organisations now wish to replicate this success at the organisational level, adopting large-scale agile methods. However, an analysis of extant literature reveals (i) a lack of theoretically grounded studies of large-scale agile transformations; (ii) weak assumptions underpinning those that do exist; and (iii) an overly simplistic and often problematic over-reliance on simple adherence to agile methods. In addition, there is a lack of insights on why large-scale agile transformations fail. To explore this, we apply normalisation process theory (NPT) to examine key challenges in normalising (i.e. the process of embedding and sustaining) large-scale agile methods. We present an in-depth case study of large-scale agile transformation and demonstrate how failing to normalise a large-scale agile method can unravel an organisation’s transformation efforts. There are four key contributions from this research. First, this study shows that the standard focus on initial adoption is one of the main reasons for the widespread failure of digital transformations and in this case a large-scale agile transformation. Second, this is the first study to introduce and empirically apply NPT to information system development (ISD) as an illustrative guide for those across information systems field to follow. Third, we present key recommendations based on NPT to guide researchers and practitioners on the normalisation of large-scale transformations. Fourth, we present an agenda for future research on large-scale agile transformations. Collapse

Topics: Spotify digital service agile software development sensemaking digital transformation

Methods: case study design methodology qualitative interview qualitative coding literature study

Theories: information systems theory sociological theory dynamic capabilities theory

THE PROCESS AUGMENTABILITY CANVAS - HOW TO FIND THE SWEET SPOT FOR AUGMENTED REALITY

2023 | European Conference On Information Systems | Citations: 0

Authors: Bräker, Julia; Semmann, Martin

Abstract: The adoption of augmented reality (AR) has been one of the defining technologic ... Expand

Abstract: The adoption of augmented reality (AR) has been one of the defining technological trends of the past decade. While AR has experienced significant growth in consumer electronics, its potential for professional use still needs to be explored. Despite the growing interest in AR, determining its feasibility and potential to satisfy business needs remains challenging. To address this gap, we used a mixedmethod research approach to create a guiding framework called the process augmentability canvas. Drawing on a comprehensive case study of a major European maintenance, repair, and overhaul service provider, as well as state-of-the literature, we present a canvas that allows scholars and practitioners to evaluate AR's applicability for a given process thoroughly. By providing a structured approach to analyzing AR solutions, the process augmentability canvas contributes to a better understanding of how AR can be used efficiently in organizational settings. Collapse

Topics: logistics management usability technology adoption human computer interaction innovation management

Methods: literature study qualitative interview case study design artifact cluster analysis

Theories: unified theory of acceptance and use of technology technology acceptance model theory of task technology fit

Prototyping AI-Powered Social Innovation in an Undergraduate MIS course

2023 | International Conference on Information Systems | Citations: 0

Authors: Chen, Yu; Albert, Leslie; Macias, Heather

Abstract: While implementing with caution, Artificial Intelligence (AI) holds potential t ... Expand

Abstract: While implementing with caution, Artificial Intelligence (AI) holds potential to help nations address pressing social issues, such as homelessness, climate change, and healthcare accessibility. With the existing and potential economic and social benefits of AI, it is crucial to integrate AI learning in undergraduate education. This paper presents the preliminary findings of a course project that engages students to learn AI by prototyping solutions to address important social issues in their communities among 120 undergraduate MIS students. Students worked in groups and developed chatbots that addressed a variety of community issues during . A survey study shows students' enhanced understanding and mastery of AI concepts and applications, empowerment of contributing to their communities through AI innovation, and an emerging awareness of diversity, equity, and ethical issues in the community and AI technologies. We conclude with implications of learning AI, innovation, and ethics through the lens of AI for social good. Collapse

Topics: artificial intelligence design thinking societal evaluation criteria innovation management responsible artificial intelligence

Methods: design methodology survey chatbot personal interview design artifact

AI for Social Good (AI4SG) Education in an Undergraduate Introductory MIS Course

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Chen, Yu; Hill, Timothy

Abstract: We describe a pedagogical study in which we designed and implemented a module f ... Expand

Abstract: We describe a pedagogical study in which we designed and implemented a module for undergraduate Management Information Systems (MIS) students, aimed at preparing them for an increasingly AIimpacted business environment and society. We developed a learning module that taps their inherent motivation to make a meaningful difference, challenging them to ideate applications of AI for social good (AI4SG), focused specifically on sustainability. We piloted the module in an existing introductory MIS course, first establishing a range of fundamental AI capabilities through hands-on demos and study cases. Then, with instructor guidance, the student teams, working in a social entrepreneurship "start-up" context, identified sustainability challenges impacting their own communities and worked together to propose and pitch AI-powered solutions. The results suggest that students find this approach deepened their understanding of sustainability issues in their communities, improved their knowledge of how AI could address social issues, and improved their confidence in their ability to innovate. Collapse

Topics: artificial intelligence anonymity IT career entrepreneurship innovation management

Methods: survey Student's t-test parametric test personal interview design methodology

Theories: self determination theory

How can Blockchain technology support patent management? A systematic literature review

2023 | International Journal of Information Management | Citations: 0

Authors: Denter, Nils M.; Seeger, Fabian; Moehrle, Martin G.

Abstract: Patent management tasks involve many stakeholders from diverse disciplines and h ... Expand

Abstract: Patent management tasks involve many stakeholders from diverse disciplines and hierarchies as well as from inside and outside the organization. By drawing on the transaction cost and stakeholder theories, Blockchain technology offers new opportunities to rethink the way in which stakeholders are organized and collaborate. Although Blockchain technology receives considerable attention from both the public and academia, the question of how Blockchain technology leverages patent management in particular has so far been neglected, although it holds great promise. Consequently, this is what we choose to be our basic research question. In response to it, we conduct a systematic literature review, following a procedure in three steps. Out of an initial sample of 714 articles, we select 52 as being particularly relevant, and classify them in accordance with the dimensions of the 7D Patent Management Maturity Model. Three main foci regarding the use of Blockchain technology emerge – i. e. for the generation, the enforcement, and the exploitation of patents. This study contributes to scholarship and management by showing that Blockchain technology mitigates environmental and behavioral uncertainty, while stimulating new governance forms and business models by reorganizing or discarding stakeholders. Collapse

Topics: blockchain database system Bitcoin anonymity design thinking

Methods: literature sample literature study structured literature research topic model qualitative content analysis

Theories: transaction cost economics stakeholder theory

Critical Success Factors for AI-driven Smart Energy Services

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Gerlach, Jana; Lier, Sarah; Hoppe, Paul; Breitner, Michael H.

Abstract: Artificial Intelligence (AI) can significantly contribute to decentralizing and ... Expand

Abstract: Artificial Intelligence (AI) can significantly contribute to decentralizing and digitalizing the energy sector and environmental sustainability. Integrating AI-driven smart energy services (SES), such as energy production forecasting, building energy management, and predictive maintenance, remain in an early phase for plant providers or energy utilities. However, the knowledge regarding key factors determining the design of AI-driven SES is limited in the literature. Therefore, we derive critical success factors (CSFs) for the design of AI-driven SES in a design science research (DSR) approach in connection with the design thinking process. We identified ten CSFs and 31 CSF categories by iteratively combining the knowledge of interviewed AI business experts, scientific literature, and results of AI programming projects with students. Based on this, we developed a further research agenda containing six research demands and direct further research questions. KeywordsArtificial intelligence, energy sector, critical success factors, design thinking, design science research. Research Needs and MotivationAI solutions in the energy sector can be deployed for various tasks, such as energy generation forecasting, demand side management, building energy management, weather forecasting, predictive maintenance, plant and storage management, and energy price forecasting (Li et al. 2022). A forecast for the year 2025 predicts that the AI software market will generate annual revenue of 126 billion US dollars (Omdia 2020). Reasons for the increasing integration are the development of technologies for the collection and storage of big data and the constantly evolving computing power (Haenlein and Kaplan 2019). According to Nishant et al. (2020) AI systems in the energy sector contribute threefold: to task automation, gaining insights from data, e.g., documents, videos, and e-mails, and solving complex problems through computing capabilities. Automation tasks include the automated usage of drones for inspection and safety purposes. Gaining insights from data involves image analysis to provide predictive maintenance for power lines or energy production forecasting for energy planning. Solving complex problems includes planning efficient and multiple usages of battery storage (Nishant et al. 2020;Quest et al. 2022). Therefore, AI solutions, here AIdriven SES, can significantly impact energy efficiency and contribute to environmental sustainability, decarbonization, and decentralization of the energy sector (Antonopoulos et al. 2020;Nishant et al. 2020). Environmental sustainability, one of the three dimensions of sustainable development, concerns climate change and the measures required to quantify and reduce its impacts. Sustainability must be understood as consuming natural resources only so that future generations are not exposed to natural resource depletion (Purvis et al. 2019). Current literature on AI-driven SES addresses AI and Machine Learning (ML) models (Li et al. 2022), application areas and business models (Antonopoulos et al. 2020;Li et al. 2022;Quest et al. 2022), and advantages and disadvantages (Ahmad et al. 2021;Benbya et al. 2020). However, knowledge CSFs for AI-driven Smart Energy Services Collapse

Topics: artificial intelligence design thinking critical success factor user interface explainable artificial intelligence

Methods: design methodology qualitative interview literature study personal interview computational algorithm

Data Product Canvas: A Visual Inquiry Tool Supporting Data Product Design

2023 | DESRIST | Citations: 0

Authors: Hasan, M. Redwan; Legner, Christine

Abstract: Data products (DP) are considered a key enabler of data-driven innovation. Howev ... Expand

Abstract: Data products (DP) are considered a key enabler of data-driven innovation. However, suitable methodologies and tools supporting DP design are still scarce. The emerging body of practitioner literature mostly focuses on analytics-based products and their technical design and architecture but lacks a more comprehensive product perspective on data. To address this gap, we propose the Data Product Canvas (DPC) as a visual inquiry tool that supports cross-functional teams in understanding, designing, and analyzing DPs. The DPC was developed in an iterative design science process involving focus groups with 15 global companies and was demonstrated for selected DPs. Building on the core ideas of the Business Model Canvas, the DPC outlines the critical elements for designing DPs focusing on three key themes: desirability from the customer perspective, feasibility from the technical perspective, and viability from an economic perspective. The DPC instantiates the design principles for visual inquiry tools and comprises a conceptual model, shared visualization, and directions for use. The DPC is the first step toward a systematic approach and shared language in designing DPs in ways that technical experts and business users understand. Collapse

Topics: innovation management design thinking new product development data management ease of use

Methods: expert evaluation design principle focus group conceptual modelling design methodology

Interview with Samuel Tschepe on “Quo Vadis Design Thinking?”

2023 | Business & Information Systems Engineering | Citations: 0

Authors: Hawlitschek, Florian

Abstract: ... Expand

Abstract: Collapse

Topics: problem solving design thinking

Methods: design methodology