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Africa has been identified as an area where higher mortality happens due to un-accessibility to health care, drugs and other health facilities. Nigeria, as one of the African countries, is not excluded from such difficulties. This study aims to examine the determinants of efficient last-mile delivery at selected health facilities and the Kaduna State Health Supplies Management Agency (KADSHMA).

The study sourced data from KADSHMA and the health facilities’ staff, with a total of 261 observations used. Likewise, the respondents were picked from warehouses of each health facility and KADSHMA. The data was analysed using the partial least square structural equation modelling analysis to estimate the relationship among the variables of the study.

The study’s findings revealed that all five variables of the study (i.e. determinants) were significantly affecting the efficient last-mile delivery. Four constructs (delivery cost [DC], delivery time [DT], mode of delivery [MD] and facilities technology [FT]) have shown a positive and significant association with efficient last-mile delivery, whereas one variable (product mix [PM]) indicated a negative and significant association with efficient last-mile delivery. The study concludes that DC, DT, MD, FT and PM played significant roles in efficient last-mile delivery.

The study provides that specific means of transportation should always be on standby to transport health supplies. Time schedules should always be prepared and adhered to when transporting health supplies to the facilities, and each facility should network with robust technology to ease communication in terms of order and order planning. Additionally, facilities should try as much as possible to reduce the varieties of products when ordering health supplies, as it will increase the efficiency of the delivery.

To the best of the authors’ knowledge, this study is the first of its kind that considered these five variables (DC, DT, MD, FT and PM) with impact on the last-mile delivery in one model, especially in the Nigerian case. This is a great contribution to knowledge, more importantly, to the last-mile delivery of the health sector. The result confirmed the importance of these determinants (DC, DT, FT and PM) of last-mile delivery efficiency in saving lives.

The purpose of this study is to solve the problem of healthcare waste management in developing countries. The buildup of medical waste has attracted the attention of all spheres of society due to the expanding population and developing economy. Timely collection and processing of medical waste are extremely important due to its potential hazards. Although the problem of planning medical waste management has been addressed in developed countries, it persists in several developing countries. This research is motivated by an example of a city in India characterized by a dense population, abundant health-care facilities and a lack of planning for managing large medical waste generated daily.

The authors address the problem of designing the network of collection and processing facilities for medical waste and optimizing the vehicle route that collects and transfers the waste between facilities. Due to distinct topographic restrictions in the considered city, the collection and transfer process needs to be conducted in two echelons – from hospitals to collection centers using smaller vehicles and then to the processing facilities using trucks. This work addresses these two problems as a two-echelon location-routing problem.

A mixed-integer programming model is developed to minimize the cost of opening the facilities and transporting medical waste. Several managerial insights are drawn up to assist planners and decision-makers.

This study follows a case study approach to provide a descriptive and prescriptive approach to hospital waste management in the ancient city of Varanasi. The city has witnessed unplanned growth over the years and is densely populated. The health-care facilities in the city have a large catchment area and attract patients from neighboring districts. The situation analysis based on secondary data and unstructured interviews of the stakeholders suggests that the ad hoc approach prevails in present hospital waste management in the city.

This study aims to minimize the cost and time of blood delivery in the whole blood supply chain network (BSCN) in disaster conditions. In other words, integrating all strategic, tactical and operational decisions of three levels of blood collection, processing and distribution leads to satisfying the demand at the right time.

This paper proposes an integrated BSCN in disaster conditions to consider four categories of facilities, including temporary blood collection centers, field hospitals, main blood processing centers and medical centers, to optimize demand response time appropriately. The proposed model applies the location of all permanent and emergency facilities in three levels: blood collection, processing and distribution. Other essential decisions, including multipurpose facilities, emergency transportation, inventory and allocation, were also used in the model. The LP metric method is applied to solve the proposed bi-objective mathematical model for the BSCN.

The findings show that this model clarifies its efficiency in the total cost and blood delivery time reduction, which results in a low carbon transmission of the blood supply chain.

The researchers proposed an integrated BSCN in disaster conditions to minimize the cost and time of blood delivery. They considered multipurpose capabilities for facilities (e.g. field hospitals are responsible for the three purposes of blood collection, processing and distribution), and so locating permanent and emergency facilities at three levels of blood collection, processing and distribution, support facilities, emergency transportation and traffic on the route with pollution were used to present a new model.

China's Belt and Road Initiative (BRI) is the most ambitious investment strategy for infrastructural development belonging to the significant potential for stimulating regional economic growth in Asia, Europe and Africa. This study aims to investigate the impact of infrastructure on spurring inward foreign direct investment (FDI) within the purview of human capital, GDP per capita, foreign aid, trade, domestic investment, population and institutional quality in BRI countries.

In doing so, the authors analyze panel data from 2000 to 2019 within the framework of the system generalized method of movement (GMM) approach for 66 BRI countries from Europe, Asia, Africa and the Middle East.

The investigated results demonstrate that aggregate and disaggregate infrastructure indices, e.g. transport, telecommunications, financial and energy infrastructures, are the driving forces in attracting foreign direct investment (FDI) in the BRI countries. In addition, control variables (i.e. institutional quality, human capital, trade, domestic investment, foreign aid and GDP per capita) play an essential role in spurring FDI inflows.

The authors’ study uniquely investigates both the pre- (2000–2012) and post- (2013–2019) BRI scenarios using the aggregate and disaggregate infrastructural components from the perspectives of full and clustered sample regions, such as Asia, Europe, Africa and the Middle East. The study provides several policy implications.

Throughout human history, the occurrence of disasters has been inevitable, leading to significant human, financial and emotional consequences. Therefore, it is crucial to establish a well-designed plan to efficiently manage such situations when disaster strikes. The purpose of this study is to develop a comprehensive program that encompasses multiple aspects of postdisaster relief.

A multiobjective model has been developed for postdisaster relief, with the aim of minimizing social dissatisfaction, economic costs and environmental damage. The model has been solved using exact methods for different scenarios. The objective is to achieve the most optimal outcomes in the context of postdisaster relief operations.

A real case study of an earthquake in Haiti has been conducted. The acquired results and subsequent management analysis have effectively assessed the logic of the model. As a result, the model’s performance has been validated and deemed reliable based on the findings and insights obtained.

Ultimately, the model provides the optimal quantities of each product to be shipped and determines the appropriate mode of transportation. Additionally, the application of the epsilon constraint method results in a set of Pareto optimal solutions. Through a comprehensive examination of the presented solutions, valuable insights and analyses can be obtained, contributing to a better understanding of the model’s effectiveness.

This study aims to deepen the understanding of the challenges and implications entailed by deploying mobile clinics in conflict zones to reach populations affected by violence and cut off from health-care services.

This research combines an integrated literature review and an instrumental case study. The literature review comprises two targeted reviews to provide insights: one on conflict zones and one on mobile clinics. The case study describes the process and challenges faced throughout a mobile clinic deployment during and after the Iraq War. The data was gathered using mixed methods over a two-year period (2017–2018).

Armed conflicts directly impact the populations’ health and access to health care. Mobile clinic deployments are often used and recommended to provide health-care access to vulnerable populations cut off from health-care services. However, there is a dearth of peer-reviewed literature documenting decision support tools for mobile clinic deployments.

This study highlights the gaps in the literature and provides direction for future research to support the development of valuable insights and decision support tools for practitioners.

Despite large bodies of research related to the impacts of e-commerce on last-mile logistics and sustainability, there has been limited effort to evaluate urban freight using an equity lens. Therefore, this study proposes a modeling framework that enables researchers and planners to estimate the baseline equity performance of a major e-commerce platform and evaluate equity impacts of possible urban freight management strategies. The study also analyzes the sensitivity of various operational decisions to mitigate bias in the analysis.

The model adapts empirical methodologies from activity-based modeling, transport equity evaluation, and residential freight trip generation (RFTG) to estimate person- and household-level delivery demand and cargo van traffic exposure in 41 U.S. Metropolitan Statistical Areas (MSAs).

Evaluating 12 measurements across varying population segments and spatial units, the study finds robust evidence for racial and socio-economic inequities in last-mile delivery for low-income and, especially, populations of color (POC). By the most conservative measurement, POC are exposed to roughly 35% more cargo van traffic than white populations on average, despite ordering less than half as many packages. The study explores the model’s utility by evaluating a simple scenario that finds marginal equity gains for urban freight management strategies that prioritize line-haul efficiency improvements over those improving intra-neighborhood circulations.

Presents a first effort in building a modeling framework for more equitable decision-making in last-mile delivery operations and broader city planning.

This study aims to explore the level of independence among persons with disabilities (PWDs) towards their use of public buildings’ facilities, as well as assess the anxiety and relevant challenges regarding such use.

In a cross-sectional survey design, 91 consenting PWDs were recruited via purposive sampling at diverse locations and invited to complete self-report questionnaires on their use of public buildings’ facilities.

Only 19 PWDs (20.9%) were able to independently use such facilities. The participants’ level of anxiety, observed to be mostly severe (41.7%), was significantly associated with sex and affected body region (p < 0.05). Most PWDs identified “lack of amenities” (85.7%), “inconvenience” (78%) and “safety issues” (59.4%) as relevant challenges towards the use of public buildings’ facilities.

This research emphasises the urgent need to universally improve PWDs’ level of independence towards the use of public buildings’ facilities alongside eradicating anxiety and challenges experienced towards such use. Accessibility ought to be promoted among PWDs, with specific attention given to women and those affected in multiple body regions; as such populations are prone to experiencing substantial anxiety. This approach should entail the provision of barrier-free facilities as well as ensuring their safe and convenient use by PWDs.

This study sought and provided key feedback from PWDs on the current built environment, which ought to be considered by relevant stakeholders to improve accessibility, promote well-being and contribute towards meeting the global goals of reducing inequality and making cities/communities inclusive, safe, resilient and sustainable.

This study investigates how asset specificity, relational governance and firm adaptability relate with supply chain integration (SCI), considering selected food processing firms (FPFs) in Uganda.

This study applies a quantitative research methodology. This research draws on a sample of 103 FPFs that have been selected from a population of 345 FPFs located in Kampala district. Hypothesis testing was done using Smart PLS version 3.

Asset specificity has a significant positive relationship with SCI, and firm adaptability partially mediates this relationship. Also, there is a full mediation impact of firm adaptability on the relationship between relational governance and SCI.

This study focused on perceptual measures to get responses from managers on the level of integration with key suppliers and customers, yet firms deal with a number of suppliers and customers.

This study contributes to existing literature on SCI by applying the transaction cost theory. The study focuses on the influence of asset specificity, relational governance and firm adaptability on SCI in the food processing sector. Literature on relational governance in supply chain using the transaction cost theory remains scanty. Few studies have also focused on firm adaptability as a mediator in the FPS with specific focus on Uganda, yet the sector is highly faced with uncertain events. The uncertain events in the sector and in developing countries call for adaptive strategies. Additionally, this study is the first to use firm adaptability to mediate the influence of asset specificity and relational governance on SCI more so in a developing country like Uganda where the FPS is one of the most important in the economy.

Logistics sector is recognized as one of the core enablers of the economic development of a nation. However, inefficiency in logistics operations impedes the achievement of intended targets by increasing the cost of doing business. Also, it is difficult to improve the efficiency of a country’s logistics operations without a metric for evaluating and understanding logistics capabilities and efficiency. Therefore, the present study has developed In-country Logistics Performance Index (ILP Index) to propose a benchmarking tool to measure the in-country logistics competitiveness, particularly in the setting of emerging economies, i.e. India.

This study has developed a unified index using principal component analysis and quintile approach. In addition, the proposed index relies on several dimensions that are developed and illustrated using quantitative secondary panel data.

The findings of this study reveal that the quality of infrastructure, economy, and telecommunications are the three most important dimensions that may significantly support the growth of the transportation and logistics sector. The results reveal that Gujarat, Tamil Nadu, and Maharashtra are the top performers whereas, Bihar, Jharkhand, and Jammu and Kashmir scores the least due to the insufficient logistics infrastructure as compared to other Indian states.

Given the extensive focus on international-level logistics index (like World Bank’s LPI) in the existing literature, this study intends to develop in-country logistics index to evaluate the logistics capabilities at the regional and state level. In addition, unlike prior studies, this study utilizes quantitative secondary data to eliminate cognitive and opinion bias. Moreover, this benchmarking tool would assist decision-makers in idealizing standard practices toward sustainable logistics operations. Additionally, the ILP index could serve the international investors in crucial decision-making, as it provides valuable insights into a country’s logistics readiness, influencing their investment choices and trade preferences. Finally, the proposed approach is adaptable to measuring the overall performance of any other industry/economy.