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As globalization continues to reshape the business landscape, the use of Business process outsourcing services and activities is gaining significant popularity among businesses. The exact services and activities that benefits and create a sustainable competitive advantage to organizations remain underexplored and few studies have been conducted in the Southern Africa developing countries including South African mobile operators. The main purpose of this study was to redress the existing knowledge gap by ascertaining the actual services and activities that the mobile telecom operators are outsourcing for sustainable competitive advantage. A structured closed-ended questionnaire was used to collect raw data from 210 employees. Overall, the results indicate that some of the key services and activities outsourced for sustainable competitive advantage included building and managing network infrastructure, network roll-out and management, manufacturing of mobile network equipment, monitoring the mobile network on capacity overload and breakdowns and assembly operations, maintenance of the base stations of mobile network, manufacturing of hard software components and resolving software problems and fleet management. The practical implications of the findings, assist organizational management in making informed and structured decisions through the identification of critical activities and services that contribute to the attainment of a sustainable competitive advantage and performance improvement of the mobile telecom operators.

Financial markets are a system of complex price dynamics that are often influenced by various nonlinear factors. Traditional linear models often do not capture the inherent nonlinearities that exist between them. The aim of this study was to examine the interconnectedness of global financial markets using a multivariate Granger causality framework, focusing the United States, Europe, Asia, and emerging markets. Daily closing share prices spanning 13 years were utilised (January 2010 to December 2023) to analyze the shock transmission dynamics. The findings revealed unidirectional causality from the U.S. to European, Japanese, and Emerging markets, underscoring its dominant role in global financial networks. Conversely, European and Asian markets exhibit no reverse causality on the United States, highlighting asymmetrical interdependence. Notably, China’s Shanghai Composite Granger-causes Emerging market returns, reflecting its rising influence. These insights challenge conventional models that underestimate multilateral linkages, demonstrating that financial integration has intensified bidirectional interactions between Emerging markets and developed markets. By implication, investors should reassess exposure to dominant markets like the U.S. and China’s growing sway over Emerging economies while policymakers should prioritize cross-border spillover monitoring and systemic risk frameworks to address asymmetrical dependencies. Also, institutions must adopt nonlinear models to better capture shock transmission and evolving interdependencies, enhancing resilience against contagion.

The increasing inter relationship between financial markets have led to the discovery of new risk dynamics particularly when considering downside risk. Recent advances in econometric modelling have prompted the search for new insights into the intertemporal dynamics between downside risks and expected stock returns. Therefore, the aim of this study was to investigate this relationship in the S&P 500, the FTSE 100, the DAX, the Nikkei 225, and the TSX Composite, covering the period from January 2000 to December 2023. Using a time-varying transition probability model, the findings revealed consistent negative correlations between downside risk measures and expected returns across all markets, with CVaR exhibiting stronger inverse relationships compared to VaR. These findings challenge the classical risk-return trade-off but align with behavioural explanations where heightened risk aversion during downturns suppresses returns. The regime-switching analysis further uncovers asymmetry in transition probabilities where high-risk regimes persist with a 74% probability, while low-risk regimes show greater stability. By implication, this study provides empirical support for regulatory frameworks prioritizing tail risk mitigation, particularly in volatile markets.

The aim of this study was to investigate phase distribution and phase correlation dynamics across international financial markets to uncover cyclical patterns, synchronization, and contagion effects. The sample financial markets were the S&P 500, DAX, Nikkei 225, FTSE 100, Shanghai Composite, BSE Sensex with daily closing prices ranging from 2018–2023. Using the Hilbert-Huang Transform complemented by Phase Concentration Index, Kuiper tests, and Granger causality, the results reveal distinct phase clustering in the Shanghai and BSE Sensex. Developed markets exhibit lower volatility clustering (S&P 500: 28% high-volatility phases) but stronger cross-market synchronization (S&P-DAX: 0.82 correlation), underscoring their interconnectedness. The S&P 500 emerges as a global anchor, Granger-causing European and Asian markets with 1.8–3.5-day lags. Crisis periods, particularly COVID-19, amplify synchronization (average correlation=0.92), while non-crisis phases show market-specific volatility (correlation=0.65). Emerging markets demonstrate regional co-movement (Shanghai-BSE: 0.73), offering diversification opportunities. The findings highlight the hierarchical structure of global markets, where developed economies drive cycles, while emerging markets remain prone to instability. This study advances phase-based methodologies as tools for systemic risk monitoring, providing insights into crisis contagion and investor strategies balancing short-term synchronization with long-term diversification.