ABSTRACT
The topic of study is multi-modal connectivity on logistics performance for trade in Uganda, objectives of study include; to examine the influence of Road Transport on logistics performance, to investigate the influence of railway transport on logistics performance and to investigate the influence of Inland Waterways on logistics performance. Uganda still faces challenges with road network and its one of the major bottlenecks the country is facing while expanding through projects such as the Kampala–Entebbe Expressway and ongoing rehabilitation of the Northern Corridor, still suffers from chronic under-maintenance, especially on secondary and feeder roads (Stewart, 2024). In most Africa countries the road-related logistics costs account for 25–35% of the value of Ugandan exports, significantly higher than in comparable landlocked countries, Poor Road conditions also contribute to high accident rates, frequent breakdowns, negatively affecting tracking and tracing capabilities and unpredictable delivery schedules and Recent attempts at digitalization have shown modest improvements, but implementation remains fragmented due to limited interoperability and weak enforcement (Stewart, 2024). The population of the study is 469 respondents, this will include respondents from Uganda Railways Corporation (URC), Ministry of Works and Transport and Freight and logistics companies.
Background of study
Multi-modal transport refers to the use of two or more different modes of transportation such as rail, road, and sea rail, air, or sea within a single journey from origin to destination (Makarova et al., 2023), The key advantage of this approach lies in its flexibility, that is each mode is used where it performs best, making the entire supply chain more efficient, faster, and often more sustainable (Kostadinov, 2025). A specific type of multi-modal transport is intermodal transportation, where cargo remains in the same container or transport unit throughout the journey (Dzemydienė, Burinskienė, & Miliauskas, 2021). There is no need to unload and reload the goods when switching between modes such as from rail to truck, this system relies on standardized containers that can be easily moved using cranes, forklifts, or other handling equipment (Tenkir, 2021).
Multi-modal connectivity seamless integrates different modes of transport such as rail, inland water ways, air transport which has become a cornerstone of efficient global logistics and trade (Qixu, 2024). In an increasingly interconnected world, the ability to shift goods smoothly between modes reduces transit times, enhances supply chain resilience and lowers cost (Umrigar, & Pitroda, 2023).
In the global logistics industry, the containers play a crucial role in intermodal logistics, they allow for reduced handling times, smooth transfers and better cargo protection, modern intermodal transportation does not just mean moving goods (Vasheghani, & Abtahi, 2023). It’s a technological process involving specialized vehicles, digital tracking systems, and well-equipped terminals, the whole system is designed to maximize the efficiency and also minimize delays of cargo further ensure a seamless flow of cargo across borders and infrastructure types (Ahmadinejad, & Tabbakhpour Langeroodi, 2023).
Most countries world wide with very strong multi modal systems consistently rank higher in, international shipments, timeliness and infrastructure quality, there has been global initiatives like China’s belt and road initiative and the European union’s Trans-European network have demonstrated that coordinated multi-modal connectivity can significantly boost trade volumes and economic competitiveness, many developing economies still suffer from fragmented transport systems, leading to high logistics costs that can account for 15–30% of the value of traded goods (Bevrani, 2018).
There is no single transportation mode that can cover long distances more to that handle large volume of goods and deliver with speed all at once, combining them allows logistics operators to balance cost, time, and convenience, rail is ideal for carrying heavy cargo across long distances, while trucks are better for short distances and flexible delivery, Air freight is the fastest option for urgent or high-value shipments, though it is also the most expensive, when integrated into a multi-modal system, these modes complement each other and improve overall delivery performance (Wei et al., 2025).
In many African countries multi-modal connectivity remains underdeveloped though it has strategic advantages for intra-African trade and global integration (Wasswa, et al.,2023). Africa’s average LPI score of 2.5 is well below the global average of 3.2, largely due to heavy reliance on road transport, in efficient port and rail road interfaces, due to this the African continental free trade area which was launched in 2021 has placed multi-modal connectivity as one of its major priorities (Baluch, 2024).
Most studies show studies in East and southern Africa indicates that that effective multi-modal connectivity can reduce transportation times by at least 30–50% and it can also reduce costs in logistics by 20–25% and yet majority of the corridors remain dominated by single modes, resulting in congestion, delays, and high informal payments at borders (Zajontz et al.,2023).
Currently Uganda being a land locked country is heavily dependent on the northern corridor and central which is via, Kenya and Tanzania, it is therefore necessary to adopt multi-modal connectivity for reducing high logistics costs and improving performance of the organization, logistical costs in Uganda often exceed 30% of the export value mainly because of over-reliance on road transport and limited integration with rail and inland water ways (Lugada, 2022).
Most studies in Uganda shows that poor multi-modal integration contributes to an extended clearance, reduced competitiveness, higher freight costs, this particularly applies to agricultural competitiveness were higher costs raises the prices significantly affecting the vulnerable farmers, It is against this background that this study intends to investigate into multi-modal connectivity on logistics performance for trade.
Statement of the problem
Uganda is a land locked developing country that relies heavily an efficient multimodal transport connectivity and the seamless integration of rail, road, and inland waterways, air, and pipeline systems to access international markets through the Northern Corridor and Central Corridor, Kenya and Tanzania respectively.
Uganda railway system is very old though there has been talks of an ongoing infrastructure investment such as the Standard Gauge Railway (SGR) and revival of Lake Victoria ferry services, and improvements at inland ports logistics performance remains poor, with logistics costs accounting for 25–35% of the value of imports and exports among the highest in East Africa (Uganda Bureau of Statistics, 2024). The high cost of structure in logistics in Uganda raises the costs of goods making Uganda uncompetitive in business when compared to other countries across the region, this also further limits small and medium enterprises in Uganda participation in regional and global value chains and constraints. Currently the existing studies tend to focus on single-mode analysis which is mainly road to rail or macro-level trade facilitation with little attention to the to the integrated, multi-modal dimension in the Ugandan context. This study therefore seeks to investigate the influence of multi-modal connectivity on logistics performance for trade in Uganda.
Objectives of the study
- To examine the influence of Road Transport on logistics performance.
- To investigate the influence of railway transport on logistics performance.
- To investigate the influence of Inland Waterways on logistics performance.
Conceptual frame work
MULTI-MODAL CONNECTIVITY (IV) LOGISTICS PERFORMANCE (DV)
| · Road Transport
· Rail Transport · Inland Waterways
|
| Customs clearance efficiency
· Infrastructure quality · Timeliness of shipments · Cost of logistics · Tracking & tracing capability · Reliability & competence of logistics services
|
| · Reduced transit time
· Lower freight & trade costs · Improved predictability · Enhanced supply chain visibility
|
| · Political stability
· Level of infrastructure investment · Institutional quality · Regional integration
|
Mediating variables
LITERATURE REVIEW
This section indicates the literature review in line with; to examine the influence of Road Transport on logistics performance, to investigate the influence of railway transport on logistics performance and to investigate the influence of Inland Waterways on logistics performance.
2.1 Road Transport on logistics performance
Uganda still faces challenges with road network and its one of the major bottlenecks the country is facing while expanding through projects such as the Kampala–Entebbe Expressway and ongoing rehabilitation of the Northern Corridor, still suffers from chronic under-maintenance, especially on secondary and feeder roads (Stewart, 2024).
In most Africa countries the road-related logistics costs account for 25–35% of the value of Ugandan exports, significantly higher than in comparable landlocked countries, Poor Road conditions also contribute to high accident rates, frequent breakdowns, negatively affecting tracking and tracing capabilities and unpredictable delivery schedules and Recent attempts at digitalization have shown modest improvements, but implementation remains fragmented due to limited interoperability and weak enforcement (Stewart, 2024).
The cost of poor transport infrastructure and weak multimodal connectivity further erodes Uganda’s trade competitiveness, Uganda ranks near the bottom for trade-transport infrastructure, only 17% of Uganda’s national roads are paved, and only about 25% of its existing railway network is operational, these challenges indicate that despite bold reforms, Uganda struggles to convert trade policy gains into sustainable, efficient, and inclusive intra-African trade growth the persistence of; trade imbalances and Poor transport infrastructure (Julius, Nicholas, & Kazaara, 2024).
A substantial portion of Uganda’s trade with its African neighbors remains informal, creating both economic leakage and under-realized tax revenue, the UBOS indicates that in 2023 Kenya accounted for 63.5% of Uganda’s informal imports, valued at US$ 78.7 million, while the DRC accounted for 21.4% of those informal flows, the same report estimates that informal cross-border trade exceeds US$ 500 million, pointing to significant under-documentation.
Railway transport on logistics performance
Multimodal transportation is widely acknowledged, the implementation process remains fraught with numerous challenges, particularly when aligning disparate transport modes within a cohesive framework, the influence of synchromodal logistics, which builds upon multimodal systems by allowing for flexible, real-time switching between transport modes based on operational conditions (Makarova et al., 2023). Though there has been different technological advances and the persistent issues such as incompatible information systems, policy fragmentation, uneven way of adopting the ICT solutions which continue to impede optimal integration (Rentschler et al., 2022).
Recent global disruptions have led to the rise in demand for new ways to reconfigure supply chain network to build agility and enhance resilience to absorb short-term shocks (Singh, & Modgil, 2025). The outbreak of COVID-19 in 2020 and the resulted consequences have severely disrupted the global supply chains due to the lack of reliable supply of parts and restricted deployment of skilled workforce, among others (Timotius et al. 2022).
Railway transport plays a strategic role in logistics performance, particularly for bulk cargo, long-distance haulage, and landlocked or transit-dependent economies (Cohen, & Kouvelis, 2021). Unlike road transport, railways offer lower unit costs per ton-kilometre, higher energy efficiency, greater capacity, and reduced environmental impact, making them a critical component of sustainable logistics systems, rail connectivity and efficiency as key determinants of overall logistics performance, especially in the sub-indicators of infrastructure quality, international shipments, and cost competitiveness (Alzate et al., 2024).
Inland Waterways on logistics performance
Inland waterways including navigable rivers, lakes, canals, and man-made channels represent one of the most cost-effective and environmentally sustainable modes of freight transport for bulk and non-time-sensitive cargo, Despite their potential, inland waterways remain underutilized in many developing economies, particularly in Africa, where road transport dominates logistics systems, that effective inland waterway transport can significantly improve logistics performance by reducing freight costs, decongesting roads, lowering carbon emissions, and enhancing supply chain reliability for commodities such as grains, fertilizers, minerals, and petroleum products (Makarova et al., 2023). .
Inland waterways contribute substantially to logistics efficiency in countries with well-developed networks. In Europe, the Rhine Main–Danube Canal and the Dutch canal system handle over 40% of inland freight, achieving unit costs 50–70% lower than road transport and reducing congestion in parallel road corridors, using gravity models show that countries with operational inland waterways record 15–30% lower logistics costs and higher LPI scores in timeliness and infrastructure quality (Hoekman & Shepherd, 2023).
RESEARCH METHODOLOGY
The multi-modal connectivity on logistics performance for trade in Uganda, that can be explained using different theoretical frames. However, for purpose of answering the research question, a pragmatic philosophical stance is adopted. This is concerned with what works and provides solutions to an identified problem (Creswell, 2013; Patton, 2002. Pragmatism allows the researcher to emphasize the research problem and use all approaches available to address the problem. It is an approach that uses mixed methods. Thus, pragmatism will give the researcher the freedom of choice of methods, techniques, and procedures of research that best meets the needs and purpose of the study (Creswell, 2013b.).
Research Design
Different research designs relate to philosophical assumptions and the research design is associated with a pragmatic paradigm (Creswell, 2013; Kothari, 2004). The research design associated with the pragmatic paradigm involves mixed methods (Creswell, 2012). The current study will adopt a concurrent parallel design combining the survey design applied within a case study. The mixing of the two designs will provide a better understanding of the research problem since it utilizes and it builds upon the strengths of both quantitative and qualitative data (Creswell, 2008; Saunders, et al., 2012).
The case study is a method of study that focuses on in-depth rather than breadth. This research will use a case study design involving Uganda railways. The case study is a design in qualitative research an objective as well as a product of inquiry (Creswell, 2013). It is where the researcher explores real-life multiple bounded systems (cases) over time through detailed in-depth data collection involving multiple sources of information in which inferences can be drawn (Creswell, 2013). The case study design will be a basis to explore role of railway transport on carbon emission reduction(Ritchie, et al., 2013).
Creswell (2012) defines survey research design as procedures in quantitative research in which investigators administer a survey to a sample or to the entire population of people to describe the attitudes, opinions, behaviors, or characteristics of the population. The current study will adopt a cross-sectional survey design since the researcher shall collect data at one point in time and measure the practices, awareness, and readiness then (Creswell, 2012). Furthermore, survey research typically collects data using two basic forms: questionnaire and interview which will be applied in the current study. The questionnaire and interview will be administered to stakeholders such as Uganda Railways Corporation (URC) staff, Ministry of Works and Transport officials, NEMA officers, freight and logistics companies, include climate experts, policy makers and technical personnel
The study area will include; Uganda Railways Corporation (URC) , Ministry of Works and Transport, NEMA, freight and logistics companies. Although each of the selected cases has its history, they are considered to be centers of excellence in their respective line of research within national, regional, and international collaborations
The population is the entire set of respondents from whom the study sample with common observable characteristics (sample) will be drawn (Taherdoost, 2018). The population of the study is 469 respondents, this will include respondents from Uganda Railways Corporation (URC), Ministry of Works and Transport and Freight and logistics companies.
Sample Size and Sampling Strategies
A sample is any part of a fully defined population (Banerjee and Chaudhury, 2010). Here below the sample size and sampling strategies of the study are explained.
The ideal sample size for researchers as respondents will be calculated using the Cochran formula at the desired level of precision, confidence level, and the estimated proportion of the attribute present in the population.
The Cochran formula is:
Where:
- e is the desired level of precision (i.e. the margin of error),
- p is the (estimated) proportion of the population that has the attribute in question,
- q is 1 – p.
- the z-value is found in a Z-table.
This give a sample size of 212 Respondents. However, to allow a representative sample from each study site, Stratified sampling will be used to generate an appropriate sample depending on the population of respondents available in each study site. Consequently, Cochran’s formula is modified to calculate a sample for small (Hypergeometric) populations, applied as shown below:
n=
Where:
n= Sample size
N= Population size
Z=z-score
e= Margin of error
P= Sample proportion (If unknown we use 0.5)
N=469, Z-score at 95% confidence level=1.96, e=5%, P=0.5
Substituting into the formula
n=
Sample size (n) = 212
For each stratum, a proportionate stratification shall be given by the formula below.
Where: =Strata sample size,
=Strata population size,
= strata
However, to attain a balance in response from each of the study sites, the sample for the respondent for the questionnaires shall be as here below derived from the calculation:
Sample for ministry of works ( ) = = 25
Sample for NEMA ( ) = = 16
Sample for URC ( ) = = 171
The sample size for key informants includes: climate experts, policy makers and technical personnel, from each of the selected organizations will be one respondent per category per institute which makes the total of 9 Respondents. Thus the total sample size will be 221 Respondents for both questionnaire and interview.
Three sampling techniques will be used to select the respondents as here below explained
Stratified sampling is where the population is divided into strata (or subgroups) and a random sample is taken from each subgroup. A subgroup is a natural set of items. Subgroups might be based on company size, gender, or occupation (to name but a few). Stratified sampling is often used where there is a great deal of variation within a population. Its purpose is to ensure that every stratum is adequately represented. A sample for each of the study sites as a stratum will be calculated.
At each institution, the respondents for questionnaires will be selected using random sampling. The respondents’ list shall be requested from the Human Resources Office in each institute. The entire population of the respondents at each institute will be given a number code and the numbers will be put together in a bag and randomly select one by one with replacement until all the required sample at each site is selected. All those selected will then be contacted with a request to participate in the study by answering a questionnaire.
Purposive sampling known as judgmental sampling is defined as selecting a relatively small number of respondents who can provide valuable information related to the research questions under examination (Teddlie and Tashakkori, 2009). The rationale for purposive sampling is its ability to enable the selection of informed persons who possess vital information, comprehensive enough to gain a better insight into the problem under study. Purposive sampling will be used to select key informants. These include; climate experts, policy makers and technical personnel. The office-bearers in the identified categories above are assumed to be information-rich on issues related to climate change practices within institutes by virtual of their roles, training, and skills. A list of office holders in those categories will be identified with the help of the Human Resources Office at each institute. Where there is more than one person in each category, the most senior will be selected. The selected respondents will then be contacted requested for an interview.
Data collection methods and tools
Data will be collected using multiple data collection tools. The tools will include: questionnaires, interviews, and document reviews
Questionnaires will be used to collect both quantitative and qualitative data for analyzing the , Uganda Railways Corporation (URC), Ministry of Works and Transport and Freight and logistics companies. Questionnaires will be used to collect data from respondents who are currently knowledgeable on the study topic. These include; climate experts, policy makers and technical personnel. Researchers as respondents in this study are important since they play a critical role in the research data lifecycle. Questionnaires with options for selecting and measuring based on the Likert scale are considered appropriate for the study. The questionnaire will be concurrently distributed to all study institutes. Thereafter all physically completed questionnaires shall be collected and input into the Google forms by the researcher and input into SPSS for analysis.
The interview is a data collection method in qualitative methods. It is where the respondents reply to questions asked by the interviewer verbal communicating and spoken narratives of insights constructing their social world (Ritchie, et al., 2013). This method will be used to collect verbal responses from respondents. Interviews will be conducted with climate experts, policy makers and technical personnel. Interviewing this category of respondents will reveal in-depth personal accounts and explore issues in detail about research data, its management, readiness, challenges experienced, and thereafter interviewees may make suggestions proposing a measure that could enhance the study. Interviews shall be held at the respondents’ place of work or by telephone whatever is convenient to the interviewee. Interviews will be recorded on request and thereafter transcribed into textual data for analysis. The text will be assumed to be a replica of the verbal responses of the respondents.
Written documents are a pervasive socially constructed representation of reality in institutions (Patton, 2002). However, documents pose challenges among which are access to official documents, understanding how and why they were produced, and difficulty to determine their accuracy. Nonetheless, as a data collection method, documents to be reviewed will include: legal and policy documents; strategic and annual plans; statistical and research-related reports of institutes understudy and collaborators, and oversight institutions’ reports. Despite the challenges, documents are an important source of data related to the institutional context that could be useful in understanding the study.
Data will be collected using: Questionnaire, Interview guides and a Document review guide.
Data quality control are measures put in place to ensure data integrity and authenticity and to safeguard the quality of the research output.
Validity is how well an instrument measures what it is supposed to measure (Taherdoost, 2018). The goal of validity is to ensure accurate, objective, and neutral representation of the topic under study (Marwill and Rossman, 2011). A pre-test will be carried out to assess the face validity of the data collection tools to gauge the meaning and attributes of the questions both in interview and questionnaire (Ng ’ Eno, 2018). The pre-test shall also assess whether the data collection tools capture the information required for the study. It will also help to give confidence to the researcher in data collection and eliminate barriers such as resistance to recording and mistrust of the researcher’s agenda which shall consequently strengthen the study (Marwill and Rossman, 2011).
Reliability will be ensured by the data collection tools being subjected to respondents who were identified for the purpose. All researchers shall be subjected to a questionnaire across the study sites and interviews shall be conducted for pre-identified key informants in each institute.
Data presentation and analysis
Data shall be collected from each study site and analyzed. Thereafter, cross-case conclusions shall be made and the report written. However, all collected data shall be under the custody of the researcher. Qualitative data will be presented using the themes derived from the interpretations analyzed by NVIVO software to give deeper research insights. The software will be used to create mind maps to quicken the process of analyzing qualitative data (Godau, 2014). Qualitative data will be presented in form of direct quotations from respondents explaining in detail their experiences and practices. Quantitative data will be analyzed using Statistical Package for Social Scientists (SPSS) and presented using interactive statistical analysis.
This study will strictly adhere to the ethical standards outlined in the Makerere University Research Ethics Guidelines, which emphasize respect for persons, beneficence, justice, and responsible conduct of research. Prior to data collection, the researcher will obtain ethical clearance from the Makerere University Research Ethics Committee (REC) and seek formal authorization from the Ministry of Works and Transport, the National Environment Management Authority (NEMA), and the Uganda Railways Corporation to ensure institutional compliance. Participation in the study will be entirely voluntary, and all selected officials will be provided with detailed information about the purpose of the study, the procedures involved, the potential risks and benefits, and their rights as participants. Written informed consent will be obtained before any interview or data collection activity is conducted.
To uphold confidentiality, all data will be handled in accordance with Makerere University’s data protection and privacy guidelines. Participants’ identities will be protected through the use of codes, pseudonyms, and secure data storage systems, and no personal identifiers will appear in transcripts or the final report unless explicit permission is granted. Data will be stored securely in password-protected digital files and locked cabinets accessible only to the researcher. The researcher will ensure that no participant suffers any form of psychological, social, or professional harm, and questions will be framed sensitively to avoid discomfort or undue pressure. Participants will also be informed of their right to withdraw from the study at any stage without any negative consequences.
The researcher gave equal opportunity for both male and female respondents to participate in the study in the course of collecting data.
The study will adhere to strict ethical standards to protect participants and ensure the integrity of the research. Informed consent will be obtained from all officials of the Uganda Railways Corporation, NEMA, and the Ministry of Works and Transport after clearly explaining the purpose, procedures, benefits, and voluntary nature of their participation. Participants will be assured of their right to withdraw at any stage without consequence, and confidentiality will be maintained by anonymizing identities and securely storing all data. The study will avoid any form of psychological, social, or professional harm by ensuring respectful engagement and asking only relevant, non-threatening questions. Permission will be sought from the respective institutions, and all data collected will be used solely for academic purposes. Ethical approval will be obtained from the appropriate institutional review board to ensure full compliance with national and institutional research guidelines.
This study is delimited to examining the role of railway freight transport in reducing carbon emissions and enhancing environmental sustainability within Uganda. Specifically, the study will focus on three key institutions: the Uganda Railways Corporation (URC), the National Environment Management Authority (NEMA), and the Ministry of Works and Transport. Only officials directly involved in railway operations, environmental regulation, and transport policy will be included. The study is further limited to railway freight transport and does not cover passenger rail services or other modes of transport such as road, air, or water. Geographically, the study is restricted to Kampala and selected operational points where these institutions operate. The study will also rely primarily on self-reported data from interviews and questionnaires, which may limit the depth of operational insights. Time constraints and resource availability additionally restrict the scope to data that can be collected within the study period.
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