Review Article
Supply Chain Analytics, Definitions, Characteristics and Applications: A Systematic Literature Review
Desmond Mwangi Wairimu*
Issue:
Volume 10, Issue 5, October 2024
Pages:
76-84
Received:
11 August 2024
Accepted:
2 September 2024
Published:
26 November 2024
Abstract: While there is a high uptake of BDA in the realm of supply chain management, in the view of automation supply chains and improving their value proposition by providing more accurate data for demand forecasting. There are material knowledge gaps on the SC-specific analytics applied to match demand, albeit the existing knowledge could be more amorphous. From this backdrop, the study endeavored to analyze extant literature within the ambit of BDA to unpack the current trends and possible future research directions to foster the application of BDA in SC contexts. The study adopted a systematic literature review of the extant literature published between 2014-2023. The study adopted the five-stage iterative procedure used in the systematic review methodology. The review's findings depict extensive use of big data analytics in matching demand and supply and supply chain optimization. The findings of this study adduce almost non-rebuttable evidence that big data analytics can be applied in procurement, inventory control, logistics, and order processing. Under the auspices of BDA is the SCA. Arguably, extant research has demonstrated the capability of SCA in mitigating contemporary SC risks such as mismatches between demand and supply, sub-optimal SCs, and underutilization of the supply chain infrastructures at the cusps of various echelons.
Abstract: While there is a high uptake of BDA in the realm of supply chain management, in the view of automation supply chains and improving their value proposition by providing more accurate data for demand forecasting. There are material knowledge gaps on the SC-specific analytics applied to match demand, albeit the existing knowledge could be more amorpho...
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Research Article
Fostering Innovation and Entrepreneurship for Sustainable Development in African Communities
Edward Lambert,
Kanbiro Orkaido Deyganto*
Issue:
Volume 10, Issue 5, October 2024
Pages:
85-96
Received:
23 September 2024
Accepted:
28 October 2024
Published:
28 November 2024
Abstract: This research explores the influence of Innovation and Entrepreneurship on Sustainable Development within African communities, utilizing a quantitative methodology characterized by an explanatory framework. A total of 370 participants provided data through structured questionnaires, which were analyzed using multiple regression analysis. The findings indicate an adjusted R-squared value of 96.0 percent, suggesting that96.0 percent of the variation in Sustainable Development can be accounted for by the factors examined. Significant results demonstrate that Entrepreneurial Education and Training, Investment in Research and Development, Collaborative Partnerships, and Intellectual Property Rights have a positive impact on Sustainable Development. However, Access to Finance and Access to Market present challenges, illustrated by their negative coefficients, and R&D Investment and the Innovation Ecosystem were deemed insignificant. The study acknowledges that the model does not account for the remaining 0.04 percent of variation, suggesting further investigation is needed. Practical implications point to the necessity for strategic planning in areas with significant positive impacts and the importance of improving Access to Finance and Market conditions. The research highlights the need for a supportive Regulatory Environment and networks to foster Sustainable Development, offering valuable insights and paving the way for future studies in this domain.
Abstract: This research explores the influence of Innovation and Entrepreneurship on Sustainable Development within African communities, utilizing a quantitative methodology characterized by an explanatory framework. A total of 370 participants provided data through structured questionnaires, which were analyzed using multiple regression analysis. The findin...
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