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

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Now showing 1 - 5 of 6
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    Assessing Big Data Analytics Capability and Sustainability in Supply Chains
    ( 2020-01-07) Cetindamar, Dilek ; Shdifat, Baraah ; Erfani, Shadi
    Big data analytics capability (BDAC) is a technology-based capability, which can influence sustainability performance of firms in supply chains. By using BDAC strategically, supply chains could improve their responses to social, environmental, and social changes taking place in uncertain business environments. This paper presents a detailed literature review on the two ends of the equation: BDACs and sustainability in supply chains performance (SSCP). The theoretical perspective of the dynamic capabilities helps us to understand BDAC holistically, a combination of non-human and human capabilities. Then, we adapt the three-bottom-line approach: economic, environmental, and social performance in order to offer a comprehensive measurement of SSCP Based on the overview of the literature, the paper offers metrics to be used in assessing both BDAC and SSCP that can advance the understanding of the relationship between them.
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    Effects of Visualization Techniques on Understanding Inconsistencies in Automated Decision-Making
    ( 2020-01-07) Corea, Carl ; Nagel, Sabine ; Delfmann, Patrick
    The automation of business processes and decision-making have received major interest from practice and academia. As automation allows to execute more processes (cases), monitoring automated decision-making is currently evolving into a big data analytics problem for companies. Thus, not only monitoring insights themselves, but also an effective use of such insights become important. In this context, the speed and ability to interpret data is closely related to the visualization of metrics and data. While various approaches for quantitative insights on automated decision-making have been proposed, there is currently no evidence as to how the specific visualization of such metrics helps companies to create more value from their data. In this report, we therefore present the results of an empirical experiment analyzing the cognitive effects of different visualization techniques for quantitative insights on understanding inconsistencies in automated decision-making data.
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    User Related Challenges of Self-Service Business Intelligence
    ( 2020-01-07) Lennerholt, Christian ; Van Laere, Joeri ; Söderström, Eva
    Self-service Business Intelligence (SSBI) is an upcoming trend that allows non-technical casual users to use Business Intelligence (BI) in a self-reliant manner without the support of technical power users. Many organizations struggle to utilize the potential of SSBI and experience data-related and user-related SSBI implementations challenges. This study aimed at exploring user-related SSBI challenges by conducting and analyzing a total of 30 qualitative interviews with 5 BI consultants and 10 customer representatives involved in 2 SSBI implementation project teams. Analysis of the interviews revealed ten challenges related to “Self-reliant users”, seven challenges related to “creating SSBI reports” and five challenges related to “SSBI education” that differ considerably from SSBI challenges commonly discussed in literature. Awareness of these 22 challenges can help practitioners to avoid unnecessary obstacles when implementing and using SSBI, and guide SSBI researchers in simplifying the implementation process of SSBI.
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    Crowdsourcing Contests: Understanding the Effect of Environment and Organization Specific Factors on Sustained Participation
    ( 2020-01-07) Javadi Khasraghi, Hanieh ; Wang, Xuan ; Li, Yaojie
    Crowdsourcing has increasingly become a recognized problem-solving mechanism for organizations by outsourcing the problem to an undefined crowd of people. The success of crowdsourcing depends on the sustained participation and quality-submissions of the individuals. Yet, little is known about the environment-specific and organization-specific factors that influence individuals’ continued participation in these contests. We address this research gap, by conducting an empirical study using data from an online crowdsourcing contest platform, Kaggle, which delivers data science and machine learning solutions to its clients. The findings show the statistically significant effects of structural capital, familiarity with organization, and experience with the organization on individuals’ sustained participation in crowdsourcing contests. This research contributes to the literature by identifying the environment-specific and organization-specific factors that influence individuals’ sustained participation in crowdsourcing contests. Moreover, this study offers guidance to organizations that host a crowdsourcing platform to design, implement, and operate successful crowdsourcing contest platforms.
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    Extending Loyalty Programs with BI Functionalities
    ( 2020-01-07) Kucklick, Jan-Peter ; Kamm, Michael ; Schneider, Johannes ; Vom Brocke, Jan
    Effective customer loyalty programs are essential for every company. Small and medium sized brick-and-mortar stores, such as bakeries, butcher and flower shops, often share a common overarching loyalty program, organized by a third-party provider. Furthermore, these small shops have limited resources and often cannot afford complex BI tools. Out of these reasons we investigated how traditional brick-and-mortar stores can benefit from an expansion of service functionalities of a loyalty card provider. To answer this question, we cooperated with a cross-industry customer loyalty program in a polycentric region. The loyalty program was transformed from simple card-based solution to a mobile app for customers and a web-application for shop owners. The new solution offers additional BI services for performing data analytics and strengthening the position of brick-and-mortar stores. Participating shops can work together in order to increase sales and align marketing campaigns. Therefore, shopping data from 12 years, 55 shops, and 19,000 customers was analyzed.