Business Intelligence and Big Data for Innovative and Sustainable Development of Organizations

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    Toward a unified model of mobile Business Intelligence (m-BI) acceptance and use
    ( 2022-01-04) Weichbroth, Paweł ; Kowal, Jolanta ; Kalinowski, Marcin
    Factors affecting mobile business intelligence (m-BI) acceptance and use have become an increasingly important topic in practice due to the growing complexity of organizations, and their underlying information systems (IS). Since, one can notice considerable interest in m-BI, however, to the best of our knowledge few studies (if any) aim to synthesize the existing body of knowledge with regards to the factors affecting m-BI acceptance and use. To fill this gap, we conducted a systematic literature review and summarized the current state of the art. By addressing research questions, we identified a set of five factors, namely: Perceived Value, Perceived Ease of Use, Managerial Attitudes, Facilitating Conditions and Quality of Information, and specified their inter-relationships. Moreover, we introduce an acceptance model (m-BIAM) on behavioral intention and use mobile Business Intelligence solutions. The contribution of this study lies in these evidence-based findings, which lay a solid foundation for further studies in the extent of testing and evaluating the m-BIAM model, targeted at delivering more evidence to confirm its validity and predictive power.
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    Public Procurement, Big Data Analytics Capabilities, and Healthcare Supply Chain Sustainability
    ( 2022-01-04) Kozanoglu, Dilek ; Chakraborty, Subrata ; Murad, Md. Ahsan Uddin
    Big data analytics (BDA) is considered the most critical supply chain activity for organizations. Implementing BDA requires specialized infrastructure coupled with specialized analytical expertise. Most of the existing research focuses on building BDA capabilities or perceived benefits of organizations' BDA capabilities. However, the benefits of having BDA capabilities, neither immediately visible nor straightforward. Optimizing procurement is one of the many intermediate factors that influence BDA capabilities' impact on the supply chain's sustainability performance. This paper has analyzed the existing literature to develop a conceptual framework to investigate the relationships among procurement optimization, BDA capabilities, and healthcare sustainable supply chain.
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    Leveraging BI Systems to Overcome Infobesity: A Comparative Analysis of Incumbent and New Entrant firms
    ( 2022-01-04) Malik, Ojaswi ; Jaiswal, Ankur ; Kathuria, Abhishek ; Karhade, Prasanna
    Infobesity is a condition whereby firms collect more information than they need or more information than they can efficiently use. As both incumbent firms and new entrant firms face different information-rich technological and economic environments, they are at a greater risk of infobesity which can compromise their innovation outcomes. In this study we leverage a research design that integrates inductive analytics and abductive discovery to uncover how incumbent and new-entrant firms leverage Business Intelligence systems and digital collaboration activities to innovate in the face of infobesity. We find that new entrant firms encounter a threshold effect governed by the use of BI systems to filter information from their customer network. On the other hand, we found that while most incumbents are able to innovate, there are uninventive incumbents that are unable to develop new products when they deploy only moderate levels of BI systems to filter their supplier data.
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    Dashboard Framework. A Tool for Threat Monitoring on the Example of Covid-19
    ( 2022-01-04) Olszak, Celina ; Kisołek, Arkadiusz
    The aim of the study is to create a dashboard framework to monitor the spread of the Covid-19 pandemic based on quantitative and qualitative data processing. The theoretical part propounds the basic assumptions underlying the concept of the dashboard framework. The paper presents the most important functions of the dashboard framework and examples of its adoption. The limitations related to the dashboard framework development are also indicated. As part of empirical research, an original model of the Dash-Cov framework was designed, enabling the acquisition and processing of quantitative and qualitative data on the spread of the SARS-CoV-2 virus. The developed model was pre-validated. Over 25,000 records and around 100,000 tweets were analyzed. The adopted research methods included statistical analysis and text analysis methods, in particular the sentiment analysis and the topic modeling.
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    ADA-CMM: A Capability Maturity Model for Advanced Data Analytics
    ( 2022-01-04) Korsten, Ginger ; Aysolmaz, Banu ; Turetken, Oktay ; Edel, Diederick ; Ozkan, Baris
    Despite the rising importance of advanced data analytics, there is limited guidance on how organizations should leverage it. The benefits that an organization can gain through advanced data analytics depends on the organization’s ability to gain and use relevant capabilities. This study introduces a capability maturity model (ADA-CMM) for advanced data analytics to help organizations assess their current state of capabilities for managing advanced data analytics. We used the Delphi method to develop the maturity model and performed a survey to evaluate its validity. The results confirm that the maturity level of the advanced data analytics capabilities of organizations is positively related to the business value that they can capture from their use, which in turn found positively related to organizational performance. ADA-CMM can be used by organizations as a self-assessment tool and to create a roadmap for improving their relevant capabilities.