Joash Mageto

Background: Population growth and rising healthcare demand increasingly strain public healthcare in emerging economies. Further, poor supply visibility, frequent stock-outs, and medicine expiry weaken healthcare supply chain performance (SCP) and patient outcomes. In response, the Internet of Things (IoT) offers promising ways to improve the monitoring, distribution, and management of medical supplies. However, empirical evidence on how technological, organisational, and environmental factors influence IoT adoption and its effect on public healthcare SCP remains limited. This study examined factors influencing IoT adoption and its effect on supply chain performance in public healthcare facilities. Methods: Data were collected from 102 respondents drawn from 90 public healthcare facilities. Results: Factors associated with technological factors have the most significant influence on the adoption of IoT in public healthcare SCs. The lack of significance of organisational and environmental factors may be attributed to the early stage of IoT adoption in public healthcare SCs. Conclusions: This study contributes to the theoretical understanding of IoT adoption by highlighting the dominant role of technological factors over organisational and environmental considerations in resource-constrained public healthcare settings. From a practical perspective, the findings encourage policymakers and healthcare managers to prioritise investments in relevant ICT infrastructure to accelerate IoT adoption.

Poor service was one of the many reasons why Nigeria's railway transportation, which dates to the 18th century, became obsolete. This article examines the service quality dimensions of Nigeria's standard-gauge rail system. The objective is to identify the key service indicators for service quality dimensions that influence passengers' patronage of standard-gauge railway transport in Nigeria. A questionnaire was administered to 359 train passengers in Abuja, Lagos, and Ibadan using a random sampling technique to gather data for the study. Exploratory Factor Analysis (EFA) was used to analyze the data. The study highlighted departure and arrival times, ease of buying tickets, comfortability, ticket price, and availability of food/snacks on the train as indicators that do not contribute to the major service quality dimensions of the rail transportation in Nigeria. The main dimensions of service quality that affect passengers' experiences with Nigeria's standard rail system are tangibility, responsiveness, reliability, safety and security, and service orientation. The findings underscore the importance of maintaining high-quality services to ensure passenger satisfaction and increase rail transport patronage in Nigeria. The findings suggest creating and implementing policies that will consistently enhance Nigeria's rail transportation service delivery.

Smart mobility is widely promoted as a solution to urban congestion, pollution, and inefficiency. Yet, its adoption remains inconsistent, particularly in developing and small cities. While prior research has examined technological enablers, the structural and systemic barriers that constrain adoption are less understood. This study identifies and analyzes the institutional, political, technological, and socio-cultural barriers that collectively inhibit smart mobility transitions. Using Total Interpretive Structural Modelling (TISM) and MICMAC analysis, the study hierarchically maps 14 interrelated barriers derived from literature and validated through expert consultation. Findings reveal that legacy paradigms in conventional transport planning, fragmented institutional mandates, and regulatory misalignment are the foundational constraints that reinforce downstream challenges such as affordability, limited service coverage, and user resistance. Anchored in Critical Urban Theory, the study reframes smart mobility adoption as a contested and political process shaped by institutional inertia and unequal access to technology. The paper contributes to the literature by offering a theory-informed diagnostic framework for understanding mobility transitions. It also provides practical entry points for policymakers, planners, and mobility innovators seeking to target root cause interventions rather than symptoms, to enable more equitable, scalable, and resilient smart mobility transitions.

Smart mobility is widely promoted as a solution to the urban challenges of congestion, pollution, and inefficient transportation systems. Yet, its adoption remains inconsistent, particularly in developing cities where structural and systemic barriers are dominant. Prior research has examined enabling factors such as digital infrastructure and user perceptions, but has paid limited attention to the institutional, political, and socio-cultural constraints that influence adoption. Moreover, whenever considered, the barriers are studied in isolation, obscuring their systemic interactions. This study addresses this gap using Total Interpretive Structural Modelling (TISM) to hierarchically map the barriers. To complement the analysis, MICMAC classification is used to assess their driving and dependence power. Findings reveal that legacy paradigms in conventional transport planning, fragmented institutional mandates, and regulatory misalignment are the foundational barriers, reinforcing downstream challenges such as affordability constraints, limited service coverage, and persistent car-centric preferences. Anchored in Critical Urban Theory, the study depicts how smart mobility adoption is not a neutral technological process, but one deeply embedded in wider struggles over governance, equity, and urban development. The paper contributes to the literature by offering a theory-building framework that captures the interdependence of institutional, technological, and behavioral barriers. It also provides practical entry points for policymakers, planners, and mobility innovators seeking to target root cause interventions rather than symptoms, thereby enabling more equitable, scalable, and resilient smart mobility transitions.

Background: Ride-hailing services (RHS) offer accessible and affordable transport and are gaining traction in cities globally. However, there is limited research that addresses how perceived risks shape the intention to use RHS in emerging markets.Objectives: This study examined the relationship between perceived risk dimensions and the intention to use RHS.Method: Data from 179 respondents (users and non-users) were analysed using structural equation modelling.Results: Uber and Bolt dominate the RHS landscape in Nairobi. Key risk factors include driver performance, service and/or application (App) performance, and privacy concerns significantly affect users’ perceived risk. Lower perceived risks in these factors are positively associated with the intention to use RHS.Conclusion: The findings highlight the need for policies that ensure service quality and user safety in technology-mediated transport. By applying perceived risk theory (PRT) and digital collaborative consumption (DCC), the study clarifies how risk perceptions influence RHS adoption in emerging urban contexts.Contribution: This study contributes to RHS literature by integrating PRT and DCC frameworks, and identifying critical service-related risks influencing user behaviour in emerging economies.

Over the past several decades, considerable changes have taken place which have not only impacted the economy but have also transformed the supply chain. With the supply chain being revolutionized, demand for products has escalated, leading to a simultaneous increase in production. This has led to an increase in the utilization of raw material, energy and water consumption as well as adverse GHG emission, all resulting in detrimental environmental issues and climate change. The transport and logistics industry are known to account for a significant amount of GHG emissions globally. As such, knowledgeable consumer, together with government, non-government organizations and stakeholder have added pressure on logistics service providers to implement green strategies to mitigate their carbon footprint. However, the extent to which LSPs have heeded the call is unknown. Hence, the objective of this study is to investigate the green strategies implemented by LSPs and their impact on performance. A descriptive survey research design was followed. Data was collected from people working for LSPs in South Africa. Route planning and load consolidation were two most implemented green strategies among LSPs. The implementation of the green strategies was found to be positively correlated with economic, environmental, and operational performance of LSPs. In addition, implementation of the green strategies accrues benefits such as high asset utilization, customer satisfaction and reduced GHG emissions. The study reveals that green strategies implemented by LSPs are in nascent stages in emerging economies compared to those in developed economies.