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Business Intelligence Issues for Sustainability Projects

Author

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  • Mihaela Muntean

    (Business Information Systems Department, Faculty of Economics and Business Administration, West University of Timisoara, 300223 Timisoara, Romania)

Abstract

Business intelligence (BI) is an umbrella term for strategies, technologies, and information systems used by the companies to extract from large and various data, according to the value chain, relevant knowledge to support a wide range of operational, tactical, and strategic business decisions. Sustainability, as an integrated part of the corporate business, implies the integration of the new approach at all levels: business model, performance management system, business intelligence project, and data model. Both business intelligence issues presented in this paper represent the contribution of the author in modeling data for supporting further BI approaches in corporate sustainability initiatives. Multi-dimensional modeling has been used to ground the proposals and to introduce the key performance indicators. The démarche is strengthened with implementation aspects and reporting examples. More than ever, in the Big Data era, bringing together business intelligence methods and tools with corporate sustainability is recommended.

Suggested Citation

  • Mihaela Muntean, 2018. "Business Intelligence Issues for Sustainability Projects," Sustainability, MDPI, vol. 10(2), pages 1-10, January.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:2:p:335-:d:129112
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    References listed on IDEAS

    as
    1. Lee, Ki-Hoon & Farzipoor Saen, Reza, 2012. "Measuring corporate sustainability management: A data envelopment analysis approach," International Journal of Production Economics, Elsevier, vol. 140(1), pages 219-226.
    2. Muntean, Mihaela & Cabau, Liviu Gabiel, 2013. "Business Intelligence Support For Project Management," MPRA Paper 48484, University Library of Munich, Germany, revised 20 May 2013.
    3. Muntean, Mihaela & Cabau, Liviu Gabriel, 2011. "Business Intelligence Approach In A Business Performance Context," MPRA Paper 29914, University Library of Munich, Germany.
    4. Muntean, Mihaela, 2012. "Business Intelligence Approaches," MPRA Paper 41139, University Library of Munich, Germany, revised 03 Jun 2012.
    5. Muntean, Mihaela, 2012. "Theory and Practice in Business Intelligence," MPRA Paper 41359, University Library of Munich, Germany, revised 15 Sep 2012.
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    Cited by:

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    2. Aitor Goti & Alberto De la Calle & María José Gil & Ander Errasti & Pedro R. D. Bom & Pablo García-Bringas, 2018. "Development and Application of an Assessment Complement for Production System Audits Based on Data Quality, IT Infrastructure, and Sustainability," Sustainability, MDPI, vol. 10(12), pages 1-18, December.
    3. Mohammad Reza Seddigh & Sajjad Shokouhyar & Fatemeh Loghmani, 2023. "Approaching towards sustainable supply chain under the spotlight of business intelligence," Annals of Operations Research, Springer, vol. 324(1), pages 937-970, May.
    4. Sumera Ahmad & Suraya Miskon & Rana Alabdan & Iskander Tlili, 2020. "Towards Sustainable Textile and Apparel Industry: Exploring the Role of Business Intelligence Systems in the Era of Industry 4.0," Sustainability, MDPI, vol. 12(7), pages 1-23, March.
    5. Mihaela Muntean & Laurenţiu Dijmărescu, 2018. "Sustainable Implementation of Access Control," Sustainability, MDPI, vol. 10(6), pages 1-9, May.
    6. Seunghoon Lee & Young Hoon Lee & Yongho Choi, 2019. "Project Portfolio Selection Considering Total Cost of Ownership in the Automobile Industry," Sustainability, MDPI, vol. 11(17), pages 1-17, August.
    7. Natalia R. Potoczek, 2021. "The use of process benchmarking in the water industry to introduce changes in the digitization of the company’s value chain," Journal of Entrepreneurship, Management and Innovation, Fundacja Upowszechniająca Wiedzę i Naukę "Cognitione", vol. 17(4), pages 51-89.
    8. Simona-Vasilica Oprea & Adela Bâra & Răzvan Cristian Marales & Margareta-Stela Florescu, 2021. "Data Model for Residential and Commercial Buildings. Load Flexibility Assessment in Smart Cities," Sustainability, MDPI, vol. 13(4), pages 1-20, February.
    9. Gabriel Koman & Martin Holubcik & Milan Kubina, 2018. "Descriptive representation about transformation of company by using current technologies and tools for analytical processing and evaluation of diverse data," Managerial Economics, AGH University of Science and Technology, Faculty of Management, vol. 19(1), pages 89-101.
    10. Mihaela Muntean & Doina Dănăiaţă & Luminiţa Hurbean & Cornelia Jude, 2021. "A Business Intelligence & Analytics Framework for Clean and Affordable Energy Data Analysis," Sustainability, MDPI, vol. 13(2), pages 1-25, January.
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