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

Information technology as a resource to counter domestic sex trafficking in the United States

2023 | Information Systems Journal | Citations: 2

Authors: Giddens, Laurie; Petter, Stacie; Fullilove, Michael H.

Abstract: Globally, millions of individuals are victims of sex trafficking and are compell ... Expand

Abstract: Globally, millions of individuals are victims of sex trafficking and are compelled to perform sexual acts through force, fraud, or coercion. Law enforcement agencies, non-profit organisations, and social entrepreneurs increasingly are using information technology as a resource to locate, identify, and rescue victims and find, arrest, and convict traffickers. In this qualitative case study, we partnered with a non-profit organisation that trains law enforcement officers to use information technology to counter sex trafficking. For this research study, we observed training courses, interviewed law enforcement officers and non-profit staff, and reviewed technology usage logs and other data sources. Some officers readily used the new information technology post-training, while others failed to use the new technology. Using conservation of resources theory as a sensitising lens, we identify two factors affecting the use of new technology post-training: the level of organisational resources available to individuals and the individual's perceptions of the new information technology as a resource. With these findings, we develop the Resources Model of Information Technology Use to explain how perceptions of organisational and technology resources affect information technology usage patterns and outcomes. Collapse

Topics: information system use system support societal evaluation criteria perceived usefulness information exchange

Methods: qualitative interview qualitative coding theory development case study personal interview

Theories: conservation of resources theory

Identifying the patterns: Towards a systematic approach to digital platform regulation

2023 | Journal of Information Technology | Citations: 3

Authors: Gleiss, Alexander; Degen, Konrad; Pousttchi, Key

Abstract: Digital platforms have proven to be efficient matchmakers in our networked econo ... Expand

Abstract: Digital platforms have proven to be efficient matchmakers in our networked economy and society. However, their tremendous potential is a double-edged sword, and concerns about their malpractices and negative impact have risen remarkably. In the light of practical relevance, research on digital platform regulation (DPR) did not contribute very much. Especially information systems (IS) which, as a discipline, seems predestined to explain the problems at the confluence of technology–economy–society, has barely grazed the issue of DPR. Particularly, a contribution is missing that at least explores the problems with digital platforms systematically and comprehensively. In response to this aim, we pursue a two-step approach: First, we apply qualitative meta-analysis of 211 cases as well as a number of regulation papers and actual regulation endeavors to identify and conceptualize the problem scope and potential regulatory approaches for platform problems. Second, we condense our findings into a conceptual model. Our findings show that digital platforms exploit both platform- and monopoly-related problems to assert themselves in different markets. Through their impactful platform governance, they even have become serious challengers to the regulator in controlling market access, key conditions, and resources. At this, they rely on the efficient use of data and digital technologies to effectively orchestrate platform agents and their transactions. The outcome of the paper is a set of two structured instruments that fill a void in interdisciplinary research and provide support to DPR practitioners for a systematic approach to regulation. Collapse

Topics: digital platform electronic market innovation management business model Google+

Methods: meta analysis theory development ontological modelling case study conceptual modelling

Theories: lemon market theory

Designing Digital Platforms: A Synthetization of Relevant Design Topics for Business Models from a Literature Review

2023 | HICSS | Citations: 0

Authors: Goertler, Thomas; Papert, Marcel; Schmidt, Malou

Abstract: Digital platforms (DPs) represent a challenging research object. In this context ... Expand

Abstract: Digital platforms (DPs) represent a challenging research object. In this context, scientific literature has produced a large number of publications studying DPs. Given the importance of designing DPs in both academia and practice, the purpose of this study is to synthesize the current research findings on DPs and provide a framework with possible design topics under consideration from a business model perspective. A systematic literature review (SLR) was conducted to identify and synthesize the relevant findings. We analyzed 22 publications published before May 2021. The analysis shows that, in terms of "Value Propositions", most design topics were identified. In contrast, only one design topic was identified for "Customer Relationships", "Customer Segments", and "Cost Structure". In sum, our results present a framework with design topics for DPs and support the alignment of further research. Practitioners receive an overview of design topics for DPs that encourage today`s digital transformation projects. Collapse

Topics: price management business model value creation database system information system use

Methods: synthesis literature study design framework structured literature research literature sample

Law, Economics, and Privacy: Implications of Government Policies on Website and Third-Party Information Sharing

2023 | Information Systems Research | Citations: 0

Authors: Gopal, Ram D.; Hidaji, Hooman; Kutlu, Sule Nur; Patterson, Raymond A.; Yaraghi, Niam

Abstract: Widespread abuse of internet users’ privacy online has prompted user advocacy gr ... Expand

Abstract: Widespread abuse of internet users’ privacy online has prompted user advocacy groups to implore governments to intervene and protect consumer rights. To study such interventions’ effects, we examine data-protection policies that policy makers and governments can enforce on websites, including consent-based user information sharing and subsidizing competing websites. We use a stylized analytical model to examine such policies’ impact on the decisions and outcomes of websites, users, and third-parties. Interestingly, we find that even though a consent-based policy may improve user surplus, in the absence of market entry and exit (static market), it has the unintended consequence of increasing the number of third-parties and, thus, sharing of user information. We also determine that both consent-based and website subsidization policies may reduce competition by driving websites out of the market—to the detriment of user surplus and social welfare. To validate our analytical model’s findings, we empirically investigated the impact of a consent-based policy on third-parties in a natural experiment of the California Consumer Privacy Act. These findings raise significant implications for policy making surrounding online privacy. History: Giri Kumar Tayi, Senior Editor; Nachiketa Sahoo, Associate Editor. Funding: Financial support from the Social Sciences and Humanities Research Council of Canada is gratefully acknowledged. R. D. Gopal gratefully acknowledges support by the Gillmore Centre for Financial Technology at the Warwick Business School. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1178. Collapse

Topics: website information privacy concern data protection privacy legal context

Methods: mathematical model natural experiment experimental group longitudinal research time series analysis

What do growing early-stage digital start-ups look like? A mixed-methods approach

2023 | International Journal of Information Management | Citations: 0

Authors: Griva, Anastasia; Kotsopoulos, Dimosthenis; Karagiannaki, Angeliki; Zamani, Efpraxia D.

Abstract: Digital entrepreneurship is one of the most important and impactful forms of ent ... Expand

Abstract: Digital entrepreneurship is one of the most important and impactful forms of entrepreneurship. However, the majority of digital start-ups fail to scale, despite their potential to achieve growth. Moreover, what constitutes growth is significantly different for start-ups as compared with established firms: they have limited financial performance, and their growth cannot be accurately measured by metrics such as customers, revenues, profits, and turnover at the early stages of the new venture creation process or before the start-up has reached sus­ tainability. Therefore, the first objective of this research is to contribute to the definition of growth by examining less tangible dimensions of growth. Moreover, the second objective is to identify the characteristics of early-stage digital start-ups experiencing growth. Based on a mixed-methods approach, which combines an adapted Delphi study, a questionnaire-based survey, and a comparative case study, our results suggest that growing digital startups exhibit a set of characteristics that include: an agile culture combining clan with adhocracy; the ability to nurture their absorptive, innovative, and adaptive capabilities effectively; and a human capital with adequate entrepreneurial skills, emotional attachment to and fitness with the start-up. Collapse

Topics: digital entrepreneurship human resource management entrepreneurship innovation management absorptive capacity

Methods: survey delphi study mixed method qualitative interview case study

Theories: dynamic capabilities theory

A Configurational Set-Theoretic Approach to an Innovation Capability Maturity Model

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Gräubig, Dix; Bley, Katja

Abstract: Constantly evolving economic demands caused by phenomena such as digital transf ... Expand

Abstract: Constantly evolving economic demands caused by phenomena such as digital transformation necessitate businesses and their underlying models to adapt. One possible solution for enhancing innovation potential and increasing revenue is implementing an innovation capability maturity model. This research replicates an existing maturity model development approach, which accounts for the unique characteristics of a class of companies based on their size and sector. Thus, by using a data-driven method, we provide an innovation capability maturity model for small industrial companies. We identified 21 combinations of factors that can affect innovation capability maturity, grouped into a knowledge and organizational dimension. Using a set-theoretic approach, we identified configurations of these factors that lead to low, medium, and high levels of innovation capability maturity. Based on these findings, we support an empirically driven, set-theoretic approach for developing a maturity model that can be used for higher applicability and representativity in individual classes of companies. Collapse

Topics: innovation management research and development fuzzy logic business model business process management

Methods: structured literature research descriptive statistic design science longitudinal research maturity model

Theories: fuzzy set theory knowledge based theory of the firm balance theory

How Can the BISE Community Promote Tech Startups?

2023 | Business & Information Systems Engineering | Citations: 0

Authors: Haag, Steffi; Chase, Christina; Miczaika, Gesa; Möslein, Kathrin; Steininger, Dennis; Zarnekow, Rüdiger; van Bohemen, Joris

Abstract: ... Expand

Abstract: Collapse

Topics: social media business model IS education

Digital Innovation of Healthcare Services in Times of Crisis and Beyond

2023 | HICSS | Citations: 0

Authors: Hausvik, G.; Askedal, K.

Abstract: The COVID-19 pandemic has created a worldwide state of emergency, triggering ex ... Expand

Abstract: The COVID-19 pandemic has created a worldwide state of emergency, triggering extensive digital innovation within healthcare institutions to recover from the disrupted services caused by the pandemic. The purpose of this research is to explore the phenomena of digital innovation during these extraordinary conditions and to understand the impacts during the pandemic and beyond. To do so, we conducted a systematic literature review by analyzing 130 research articles across research disciplines that were published during the pandemic. We found that the innovation processes were highly iterative and focused on rapid diffusion to address the urgent need for stabilizing and recovering disrupted services. This short-term perspective may result in adverse impacts beyond the pandemic, such as increased inequity. Moreover, we found that some environmental factors were highly adaptive to the pandemic, whereas others were less so. We suggest that organizations should focus on the latter when building resilience to future pandemics. Collapse

Topics: innovation management digital innovation pandemic business process innovation mobile system

Methods: structured literature research conceptual modelling chatbot literature study qualitative content analysis

Do Early Words from New Ventures Predict Fundraising? A Comparative View of Social Media Narratives

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Havakhor, Taha; Golmohammadi, Alireza; Sabherwal, Rajiv; Gauri, Dinesh

Abstract: Online equity markets have significantly changed the dynamics of connecting ang ... Expand

Abstract: Online equity markets have significantly changed the dynamics of connecting angels and individual equity investors to new ventures that seek early-stage capital. However, for those early-stage investors, information pointing to the success of business-to-business (B2B) new ventures (B2BNVs) is scattered and disconnected. This paper focuses on social media narratives (SMNs) as a source of insight for such investors and proposes that predicting a B2BNV's likelihood of success requires a comparative view, i.e., a comparison of its SMNs with those of its competitors and customers. We expect that higher (lower) lingual similarity between the SMNs of an early-stage B2BNV and those of its prospective customers (competitors) predict its success. Using a longitudinal panel of 574 B2BNVs resulting in more than 2,700 venture-round observations, we find that a comparative view of a venture's SMNs can give early-stage investors reliable predictions about the B2BNV's ability to manage its market presence and its success in later stages. Our models show that a comparative view of SMNs increases the accuracy of predicting a B2BNV's later-stage fundraising success by an average of 15%. Furthermore, predictive models can reliably point to a successful market presence in later stages, including the landing of customers, the winning of awards and competitions, the receiving of endorsements, the generating of revenue, and the successful patenting of products. Our study contributes to existing literature that focuses on the business impacts of social media by demonstrating the usefulness of comparative linguistics in social media analytics, i.e., comparing the firm's social media communications to those of its competitors and business customers in the prediction of the entrepreneurial firm's success. Collapse

Topics: Twitter social media social media analytics social capital website

Methods: machine learning chi squared test latent dirichlet allocation robustness check theoretical contribution

Theories: lemon market theory