IDEAS home Printed from https://ideas.repec.org/a/rom/bemann/v15y2025i1p97-113.html
   My bibliography  Save this article

A Reference Model For Business Analytics-Based Decision-Making Processes In Rail Transport Manufacturing Companies In South Africa

Author

Listed:
  • Genevieve BAKAM

    (Tshwane University of Technology, Pretoria, South Africa)

  • Khumbulani MPOFU

    (Tshwane University of Technology, Pretoria, South Africa)

  • Charles MBOHWA

    (Tshwane University of Technology, Pretoria, South Africa)

Abstract

In addition to digital transformation, businesses have reviewed their business strategies and decision-making techniques to develop a competitive advantage in the transport manufacturing sector. It happens that innovative business approaches face some limitations compromising business survival in the long term. This study investigates the importance of adopting a reference model for business analytics-based decision-making processes in rail transport manufacturing companies. This study follows a qualitative research design using secondary data published in various annual reports to define the thematic analysis around descriptive, prescriptive, and predictive analytics for enhanced business analytics-based decision-making solutions. Results indicate that improved business decisions should be based on the combination of company strategies, technology innovation and business analytics techniques for goals alignment, innovative solutions and data visualisation. Additionally, descriptive, prescriptive, and predictive analytics are generated in a predefined format to suit business, socioeconomic and environmental requirements like product localisation, company equity, financial support of black businesses, skills development, local community empowerment, and environmental protection. Business analytics-based decisions enable cost control, differentiated business decisions for competitive advantage, and strategy upgrades in addition to customer satisfaction, profitability growth and long-term sustainability. The proposed reference model shows the link between company strategies, data analysis, and technology impact in generating enhanced analytics powering the decision-making process in transport manufacturing to ensure the revitalisation of future transport in South Africa. Recommendations highlight that the South African government should improve technology infrastructure and skills development to limit resistance to digital transformation enabling business analytics.

Suggested Citation

  • Genevieve BAKAM & Khumbulani MPOFU & Charles MBOHWA, 2025. "A Reference Model For Business Analytics-Based Decision-Making Processes In Rail Transport Manufacturing Companies In South Africa," Business Excellence and Management, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 15(1), pages 97-113, March.
    • Handle: RePEc:rom:bemann:v:15:y:2025:i:1:p:97-113
    as

    Download full text from publisher

    File URL: https://beman.ase.ro/no151/7.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Irina Bogdana Pugna & Adriana Duțescu & Oana Georgiana Stănilă, 2019. "Corporate Attitudes towards Big Data and Its Impact on Performance Management: A Qualitative Study," Sustainability, MDPI, vol. 11(3), pages 1-26, January.
    2. Dignity Paradza & Olawande Daramola, 2021. "Business Intelligence and Business Value in Organisations: A Systematic Literature Review," Sustainability, MDPI, vol. 13(20), pages 1-27, October.
    3. Venkatesh Mani & Catarina Delgado & Benjamin T. Hazen & Purvishkumar Patel, 2017. "Mitigating Supply Chain Risk via Sustainability Using Big Data Analytics: Evidence from the Manufacturing Supply Chain," Sustainability, MDPI, vol. 9(4), pages 1-21, April.
    4. Yili Chen & Congdong Li & Han Wang, 2022. "Big Data and Predictive Analytics for Business Intelligence: A Bibliographic Study (2000–2021)," Forecasting, MDPI, vol. 4(4), pages 1-20, September.
    5. Etleva LESKAJ & Vasilika KUME & Eglantina ZYKA, 2015. "The Skills For Effective Decision Making Of Public Administrators," Business Excellence and Management, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 5(1), pages 33-43, March.
    6. Cristian VIZITIU & Vlad VALEANU & Adrian TANTAU & Ruxandra VIZITIU & Mihaela MARIN & Alexandru NISTORESCU, 2014. "Decision Making And Innovation Diagnosis Within Aero-Space Sector," Business Excellence and Management, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 4(3), pages 5-23, September.
    7. Martin Potančok & Jan Pour & Wui Ip, 2021. "Factors Influencing Business Analytics Solutions and Views on Business Problems," Data, MDPI, vol. 6(8), pages 1-12, August.
    8. Ruxandra DINULESCU & Alexandru-Mihai BUGHEANU & Adina-Liliana PRIOTEASA, 2020. "Assesing The Bucharest’S Public Transport Network By Using The Quality Function Deployment Tool," Business Excellence and Management, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 10(1), pages 31-40, March.
    9. Manuela Nocker & Vania Sena, 2019. "Big Data and Human Resources Management: The Rise of Talent Analytics," Social Sciences, MDPI, vol. 8(10), pages 1-19, September.
    10. Vlad BALANESCU & Paul SOARE & Vlad BELICIU & Cristina ALPOPI, 2013. "The Impact Of Business Process Management On Organizational Strategy," Business Excellence and Management, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 3(2), pages 21-28, June.
    11. Mladen Pancić & Dražen Ćućić & Hrvoje Serdarušić, 2023. "Business Intelligence (BI) in Firm Performance: Role of Big Data Analytics and Blockchain Technology," Economies, MDPI, vol. 11(3), pages 1-19, March.
    12. Ravneet Kaur & Rajesh Singh & Anita Gehlot & Neeraj Priyadarshi & Bhekisipho Twala, 2022. "Marketing Strategies 4.0: Recent Trends and Technologies in Marketing," Sustainability, MDPI, vol. 14(24), pages 1-17, December.
    13. Gerda Žigienė & Egidijus Rybakovas & Rimgailė Vaitkienė & Vaidas Gaidelys, 2022. "Setting the Grounds for the Transition from Business Analytics to Artificial Intelligence in Solving Supply Chain Risk," Sustainability, MDPI, vol. 14(19), pages 1-23, September.
    14. Wullianallur Raghupathi & Viju Raghupathi, 2021. "Contemporary Business Analytics: An Overview," Data, MDPI, vol. 6(8), pages 1-11, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Russell Tatenda Munodawafa & Satirenjit Kaur Johl, 2019. "Big Data Analytics Capabilities and Eco-Innovation: A Study of Energy Companies," Sustainability, MDPI, vol. 11(15), pages 1-21, August.
    2. Leonardo de Assis Santos & Leonardo Marques, 2022. "Big data analytics for supply chain risk management: research opportunities at process crossroads," Post-Print hal-03766121, HAL.
    3. Dr. Zahra Ishtiaq Paul & Hafiz Muhammad Sohail Khan, 2024. "Reshaping the future of HR: Human Resource Analytics and Talent Management," Bulletin of Business and Economics (BBE), Research Foundation for Humanity (RFH), vol. 13(2), pages 332-340.
    4. Mohammadreza Akbari & John L. Hopkins, 2022. "Digital technologies as enablers of supply chain sustainability in an emerging economy," Operations Management Research, Springer, vol. 15(3), pages 689-710, December.
    5. Wonhyuk Cho & Seeyoung Choi & Hemin Choi, 2023. "Human Resources Analytics for Public Personnel Management: Concepts, Cases, and Caveats," Administrative Sciences, MDPI, vol. 13(2), pages 1-22, January.
    6. Ammar AL-Ashmori & P. D. D. Dominic & Narinderjit Singh Sawaran Singh, 2022. "Items and Constructs of Blockchain Adoption in Software Development Industry: Experts Perspective," Sustainability, MDPI, vol. 14(16), pages 1-18, August.
    7. Gholamreza Dehdasht & Rosli Mohamad Zin & M. Salim Ferwati & Mu’azu Mohammed Abdullahi & Ali Keyvanfar & Ronald McCaffer, 2017. "DEMATEL-ANP Risk Assessment in Oil and Gas Construction Projects," Sustainability, MDPI, vol. 9(8), pages 1-24, August.
    8. Fahim ul Amin & Qian-Li Dong & Katarzyna Grzybowska & Zahid Ahmed & Bo-Rui Yan, 2022. "A Novel Fuzzy-Based VIKOR–CRITIC Soft Computing Method for Evaluation of Sustainable Supply Chain Risk Management," Sustainability, MDPI, vol. 14(5), pages 1-15, February.
    9. Ana-Maria Ionescu & Flavius Aurelian Sârbu, 2024. "Exploring the Impact of Smart Technologies on the Tourism Industry," Sustainability, MDPI, vol. 16(8), pages 1-23, April.
    10. Showimy Aldossari & Umi Asma’ Mokhtar & Ahmad Tarmizi Abdul Ghani, 2023. "Factor Influencing the Adoption of Big Data Analytics: A Systematic Literature and Experts Review," SAGE Open, , vol. 13(4), pages 21582440231, December.
    11. Dutescu Adriana & Pugna Irina Bogdana & Stanila Georgiana Oana, 2019. "Reframing business reporting in a Big Data world," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 13(1), pages 696-706, May.
    12. Carolyn Axtell & Mark Taylor & Bridgette Wessels, 2019. "Big Data and Employee Wellbeing: Walking the Tightrope between Utopia and Dystopia," Social Sciences, MDPI, vol. 8(12), pages 1-5, November.
    13. Vaibhav S. Narwane & Rakesh D. Raut & Sachin Kumar Mangla & Manoj Dora & Balkrishna E. Narkhede, 2023. "Risks to Big Data Analytics and Blockchain Technology Adoption in Supply Chains," Annals of Operations Research, Springer, vol. 327(1), pages 339-374, August.
    14. Ionica Oncioiu & Ovidiu Constantin Bunget & Mirela Cătălina Türkeș & Sorinel Căpușneanu & Dan Ioan Topor & Attila Szora Tamaș & Ileana-Sorina Rakoș & Mihaela Ștefan Hint, 2019. "The Impact of Big Data Analytics on Company Performance in Supply Chain Management," Sustainability, MDPI, vol. 11(18), pages 1-22, September.
    15. Jiguang Wang & Bing Ran, 2018. "Sustainable Collaborative Governance in Supply Chain," Sustainability, MDPI, vol. 10(1), pages 1-17, January.
    16. Aysu Göçer & Yao Henry Jin & Stanley E. Fawcett, 2019. "How Does the Contingent Sustainability–Risk–Cost Relationship Affect the Viability of CSR? An Emerging Economy Perspective," Sustainability, MDPI, vol. 11(19), pages 1-25, September.
    17. Joash Mageto, 2021. "Big Data Analytics in Sustainable Supply Chain Management: A Focus on Manufacturing Supply Chains," Sustainability, MDPI, vol. 13(13), pages 1-22, June.
    18. Uzair Bhatti & Noralfishah Sulaiman, 2022. "The Impact of Sustainability Practices on Share Performance with Mediation of Board Members Experience: A Study on Malaysian Listed Companies," IJFS, MDPI, vol. 11(1), pages 1-22, December.
    19. Xiaole Han & Leong-Mow Gooi, 2025. "Multi-Level Determinants of Sustainable Blockchain Technology Adoption in SCM: Individual, Organisational, and Societal Perspectives," Sustainability, MDPI, vol. 17(6), pages 1-56, March.
    20. Marta Negri & Enrico Cagno & Claudia Colicchia & Joseph Sarkis, 2021. "Integrating sustainability and resilience in the supply chain: A systematic literature review and a research agenda," Business Strategy and the Environment, Wiley Blackwell, vol. 30(7), pages 2858-2886, November.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rom:bemann:v:15:y:2025:i:1:p:97-113. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Zamfir Andreea (email available below). General contact details of provider: https://edirc.repec.org/data/mnasero.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.