| 1. |
- Alharmoodi, Ahmed Abdulla, et al.
(författare)
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Co-creation and critical factors for the development of an efficient public e-tourism system
- 2024
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Ingår i: Journal of Business Research. - : Elsevier. - 0148-2963 .- 1873-7978. ; 174
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Tidskriftsartikel (refereegranskat)abstract
- This study identifies the factors that guide the adoption of a public e-tourism system resulting in value co-creation in the UAE. Integrating and comparing factors drawn from the third version of the Technology Acceptance Model (TAM3), the Technology-Task-Fit (TTF) theory, and push-to-use, an Analytic Hierarch Process (AHP) model was implemented with data collected using a structured questionnaire from purposively selected UAE e-tourism experts (N = 15) and analyzed using Microsoft Excel. The findings revealed that usefulness, convenience of use, and push-to-use were the most critical aspects for achieving an efficient public e-tourism system that allows for value co-creation in that order of ranking. The findings also suggest that computer self-efficiency is the most critical factor in effectively establishing an e-tourism system followed by government push-to-use. In conclusion, the findings demonstrate that usefulness and ease-of-use backed by computer self-efficiency, result demonstrability, and output quality are vital for the efficient adoption of a public e-tourism system resulting in value co-creation in the UAE.
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| 2. |
- Hjelle, Sara, et al.
(författare)
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Organizational decision making and analytics: An experimental study on dashboard visualizations
- 2024
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Ingår i: Information & Management. - : Elsevier B.V.. - 0378-7206 .- 1872-7530. ; 61:6
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Tidskriftsartikel (refereegranskat)abstract
- Although analytics have become a widespread practice, we still have minimal knowledge about how dashboards influence decision-makers and through what mechanisms they enhance decision making. In this study, we built on an experiment-based approach with mock-up visualizations and recruited 524 participants, who were divided into two groups (A and B) with variations in their visualizations. We found that the format, currency, and completeness of information indirectly affect decision making quality by reducing the perceived task complexity and enhancing information satisfaction. Our results contribute to a better understanding of the role of visual representation of information quality on dashboard visualizations.
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| 3. |
- Löfström, Helena
(författare)
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Trustworthy explanations : Improved decision support through well-calibrated uncertainty quantification
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The use of Artificial Intelligence (AI) has transformed fields like disease diagnosis and defence. Utilising sophisticated Machine Learning (ML) models, AI predicts future events based on historical data, introducing complexity that challenges understanding and decision-making. Previous research emphasizes users’ difficulty discerning when to trust predictions due to model complexity, underscoring addressing model complexity and providing transparent explanations as pivotal for facilitating high-quality decisions.Many ML models offer probability estimates for predictions, commonly used in methods providing explanations to guide users on prediction confidence. However, these probabilities often do not accurately reflect the actual distribution in the data, leading to potential user misinterpretation of prediction trustworthiness. Additionally, most explanation methods fail to convey whether the model’s probability is linked to any uncertainty, further diminishing the reliability of the explanations.Evaluating the quality of explanations for decision support is challenging, and although highlighted as essential in research, there are no benchmark criteria for comparative evaluations.This thesis introduces an innovative explanation method that generates reliable explanations, incorporating uncertainty information supporting users in determining when to trust the model’s predictions. The thesis also outlines strategies for evaluating explanation quality and facilitating comparative evaluations. Through empirical evaluations and user studies, the thesis provides practical insights to support decision-making utilising complex ML models.
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| 4. |
- Madanaguli, Arun, et al.
(författare)
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Artificial intelligence capabilities for circular business models: Research synthesis and future agenda
- 2024
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Ingår i: Technological forecasting & social change. - : Elsevier Inc.. - 0040-1625 .- 1873-5509. ; 200
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Tidskriftsartikel (refereegranskat)abstract
- This study explores the interlink between AI capabilities and circular business models (CBMs) through a literature review. Extant literature reveals that AI can act as efficiency catalyst, empowering firms to implement CBM. However, the journey to harness AI for CBM is fraught with challenges as firms grapple with the lack of sophisticated processes and routines to tap into AI's potential. The fragmented literature leaves a void in understanding the barriers and development pathways for AI capabilities in CBM contexts. Bridging this gap, adopting a capabilities perspective, this review intricately brings together four pivotal capabilities: integrated intelligence capability, process automation and augmentation capability, AI infrastructure and platform capability, and ecosystem orchestration capability as drivers of AI-enabled CBM. These capabilities are vital to navigating the multi-level barriers to utilizing AI for CBM. The key contribution of the study is the synthesis of an AI-enabled CBM framework, which not only summarizes the results but also sets the stage for future explorations in this dynamic field.
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| 5. |
- Mikalef, Patrick, et al.
(författare)
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All eyes on me: Predicting consumer intentions on social commerce platforms using eye-tracking data and ensemble learning
- 2023
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Ingår i: Decision Support Systems. - : Elsevier. - 0167-9236 .- 1873-5797. ; 175
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Tidskriftsartikel (refereegranskat)abstract
- Understanding what information is important for consumers when making a purchase-related decision has been a key question for researchers and practitioners ever since the advent of empirical research in commerce. Nevertheless, our knowledge of what information is important has been formed primarily through post-purchase conscious capturing approaches, such as surveys and questionnaires. To overcome these limitations, we ground this research on an exploratory study that captures eye-tracking data during a decision-making task of product selection. Grounded on the dynamic attention theory, we utilize different information types and formats present on a popular social commerce platform, to identify elements which are important when deciding about online product purchase decision. Specifically, we employ a series of prediction algorithms and use an ensemble learning setup to predict the aspects that contribute to product selection by consumers. Our analysis highlights the most important informational cues to accurately predict product selection among alternatives. In addition, the results showcase how such elements shift in importance during the temporal sequence of comparing different product alternatives. Our results provide insight into how we can understand the journey of decision-making for social commerce customers when navigating through information to select a product. In addition, it opens the discussion about the shifts that eye-tracking in combination with machine learning can create for researchers and marketers.
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| 6. |
- Mikalef, Patrick, et al.
(författare)
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Artificial intelligence (AI) competencies for organizational performance: A B2B marketing capabilities perspective
- 2023
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Ingår i: Journal of Business Research. - : Elsevier. - 0148-2963 .- 1873-7978. ; 164
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Tidskriftsartikel (refereegranskat)abstract
- The deployment of Artificial Intelligence (AI) has been accelerating in several fields over the past few years, with much focus placed on its potential in Business-to-Business (B2B) marketing. Early reports highlight promising benefits of AI in B2B marketing such as offering important insights into customer behaviors, identifying critical market insight, and streamlining operational inefficiencies. Nevertheless, there is a lack of understanding concerning how organizations should structure their AI competencies for B2B marketing, and how these ultimately influence organizational performance. Drawing on AI competencies and B2B marketing literature, this study develops a conceptual research model that explores the effect that AI competencies have on B2B marketing capabilities, and in turn on organizational performance. The proposed research model is tested using 155 survey responses from European companies and analyzed using partial least squares structural equation modeling. The results highlight the mechanisms through which AI competencies influence B2B marketing capabilities, as well as how the later impact organizational performance.
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| 7. |
- Mikalef, Patrick, et al.
(författare)
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Thinking responsibly about responsible AI and 'the dark side' of AI
- 2022
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Ingår i: European Journal of Information Systems. - : Taylor & Francis Group. - 0960-085X .- 1476-9344. ; 31:3, s. 257-268
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Artificial Intelligence (AI) has been argued to offer a myriad of improvements in how we work and live. The notion of AI comprises a wide-ranging set of technologies that allow individuals and organizations to integrate and analyze data and use that insight to improve or automate decision-making. While most attention has been placed on the positive aspects companies realize by the adoption by the adoption and use of AI, there is a growing concern around the negative and unintended consequences of such technologies. In this special issue we have made a call for research papers that help us explore the dark side of AI use. By adopting a dark side lens, we aimed to expand our understanding of how AI should be implemented in practice, and how to minimize or avoid negative outcomes. In this editorial, we build on the notion of responsible AI, to highlight the different ways in which AI can potentially produce unintended consequences, as well as to suggest alternative paths future IS research can follow to improve our knowledge about how to mitigate such occurrences. We further expand on dark side theorizing in order to uncover hidden assumptions of current literature as well as to propose other prominent themes that can guide future IS research on AI adoption and use.
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| 8. |
- Peretz-Andersson, Einav, et al.
(författare)
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Artificial intelligence implementation in manufacturing SMEs: A resource orchestration approach
- 2024
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Ingår i: International Journal of Information Management. - : Elsevier Ltd. - 0268-4012 .- 1873-4707. ; 77
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Tidskriftsartikel (refereegranskat)abstract
- Artificial intelligence (AI) is playing a leading role in the digital transformation of enterprises, particularly in the manufacturing industry where it has been responsible for a profound transformation in key business and production operations. Despite the accelerated growth of AI technologies, knowledge of the implementation of AI by small and medium-sized enterprises (SMEs) remains underexplored. Thus, this study seeks to examine how manufacturing SMEs orchestrate resources for AI implementation. Building on the resource orchestration (RO) theory and recent work on AI implementation, we investigate multiple case studies involving manufacturing SMEs in Sweden operating in the packaging, plastic, and metal sectors. Our findings indicate that SMEs structure a portfolio based on acquiring and accumulating AI resources. AI resources are bundled into learning and governance capabilities to leverage configurations for AI implementation. Through a dynamic process of AI resource orchestration, SMEs effectively leverage AI resources and capabilities by mobilising technologies, coordinating manufacturing processes, and empowering skilled people. This research contributes to existing practice and the academic literature on AI implementation, highlighting how SMEs orchestrate AI resources and capabilities to drive an organisation's digital transformation whilst creating a competitive advantage.
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| 9. |
- Ågerfalk, Pär J., 1971-, et al.
(författare)
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Artificial Intelligence in Information Systems : State of the Art and Research Roadmap
- 2022
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Ingår i: Communications of the Association for Information Systems. - : Association for Information Systems. - 1529-3181. ; 50:1, s. 420-438
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Tidskriftsartikel (refereegranskat)abstract
- Many would argue that artificial intelligence (AI) is not only technology but also a paradigmatic shift in the relationship between humans and machines. Much literature assumes that AI-powered practices substantially differ from and profoundly change organizational structures, communication, affordances, and ecosystems. However, AI research remains fragmented and often lacks clarity. While the information systems (IS) discipline can play a pivotal role in AI’s emergence and use, the discipline needs a clear direction that specifies how it can contribute and its key research themes and questions. This paper draws on a professional development workshop that we organized at the 2020 International Conference on Information Systems and the discussions that followed. We summarize and synthesize how AI has impacted organizational practices over five decades and provide views from various perspectives. We identify weaknesses in the current AI literature as measured against conceptual clarity, theoretical glue, cumulative tradition, parsimony, and applicability. We also identify direct actions that the IS research community can undertake to address these issues. Finally, we propose a next-step research agenda to guide AI research in the coming years.
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