Short Description: Peer-Reviewed, Open-Access, Google Scholar indexed, Cabells WHITE-LISTED journal, publishing scholarly articles in finance, marketing, human resource, Information Technology, along with manuscripts documenting Economics research data and analysis.
E-ISSN: 2469-4339
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Publisher: HATASO - SynergyGlobal
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10.18639/MERJ.2025.9900111
Original Research Article
Jul 25, 2025
This investigation examines the potential of Artificial Intelligence (AI)-enhanced strategies to enhance the resilience of supply chains and logistics in South Africa’s challenging environment. The global disruptions, particularly those emphasised by the COVID-19 pandemic, have rendered the establishment of resilient and sustainable logistics systems an urgent priority. This study examines the impact of AI on improving efficiency, sustainability, and resilience in the logistics sector of South Africa’s supply chain practices. This study uses a systematic review approach that is based on the PRISMA framework. A thorough literature review was performed, concentrating on the convergence of artificial intelligence, sustainable logistics, and South Africa’s environmental issues. Thematic analysis was conducted using Atlas-ti software to identify and organize key themes related to AI applications in logistics and supply chain management. Studies were selected based on predefined criteria. The results highlight the critical role of AI technologies, including machine learning, predictive analytics, and big data analytics, in the advancement of sustainable logistics. AI applications improve transportation efficiency, optimize inventory management, diminish carbon emissions, and augment supply chain transparency. The emergence of AI-driven solutions and GSCM frameworks, which are in alignment with sustainable practices and improve operational resilience, is a noteworthy trend. The synthesis indicates an increasing dependence on AI and big data analytics to improve supply chain capabilities and augment adaptability to environmental disruptions. The study concludes that AI-improved strategies provide significant advantages in the promotion of sustainable logistics and the improvement of resilience in supply chain operations. The implementation of AI solutions improves operational efficiency and aligns logistics practices with environmental sustainability objectives. The findings of this investigation offer valuable advice to academics, policymakers, and industry professionals who are striving to leverage AI for sustainable supply chain management in South Africa.
10.18639/MERJ.2025.9900110
Original Research Article
Apr 17, 2025
The paper discusses how social media, including Instagram, Facebook, and TikTok, play a key role in forming consumers’ attitudes towards offline shopping and their purchasing behavior in physical stores. Influencer endorsements, user-generated content, and targeted ads have become social media marketing strategies that brands have been using to raise visibility and get more foot traffic to their brick-and-mortar locations. The study explores the psychological triggers that lead consumers to engage with social media (FOMO, social proof, online reviews) to act on time-sensitive offers and visit physical stores. Social commerce and AR technologies are also highlighted as a transformative trend that improves the consumer's in-store shopping experience and facilitates virtual preview and integrated buying options. Beyond enhancing online engagement, these innovations help close the digital and offline purchase gap by leading consumers to make purchases in offline channels. The paper concludes that effective social media marketing and innovative technologies are important for offline retailers to survive in the changing retail landscape. For retailers, the integration of AR and social commerce enables future trends that create custom, interactive experiences that drive both online and offline sales.
10.18639/MERJ.2025.9900109
Conceptual Article
Apr 15, 2025
This conceptual paper analyzes the use of dynamic pricing in soccer competitions in the United States, emphasizing the role of business analytics in enabling data-driven ticket pricing methods. Based on economic, marketing, and sports management perspectives, we identify a gap in the literature about dynamic pricing in soccer events, which have traditionally depended on static pricing models. Our research examines how dynamic ticket pricing might enhance income and attendance for soccer competitions while ensuring fairness for fans. Our research reveals that dynamic pricing enables organizers to maximize revenue from high-demand matches by increasing ticket prices to align with real-time market value and to enhance attendance for low-demand matches by strategically reducing prices and providing discounts. These modifications are facilitated by business analytics, encompassing demand forecasts and price optimization algorithms, which guarantee that current data informs pricing decisions on consumer willingness to pay. Our analysis emphasizes that dynamic pricing in sports functions not merely as a mechanism for price augmentation but may also augment consumer value and accessibility, as demonstrated by its capacity to lower ticket prices when warranted. Drawing on existing literature, the paper provides a theoretical framework and practical recommendations, highlighting areas for future empirical research. We offer practical insights into the implementation of dynamic pricing in soccer, emphasizing the significance of analytical models, effective stakeholder engagement, and policy considerations to balance revenue objectives with fan experience. These findings enhance sports management literature by applying dynamic pricing theory to U.S. soccer and providing a framework for utilizing business analytics in the optimization of sports revenue.
