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Article

An Analysis of the Development Factors of Rail Freight Transport in Thailand: A Structural Equation Modeling Approach

by
Oranicha Buthphorm
*,
Vatcharapol Sukhotu
and
Thammanoon Hengsadeekul
*
Faculty of Logistics and Digital Supply Chain, Naresuan University, Phitsanulok 65000, Thailand
*
Authors to whom correspondence should be addressed.
Infrastructures 2024, 9(7), 102; https://doi.org/10.3390/infrastructures9070102
Submission received: 15 April 2024 / Revised: 26 June 2024 / Accepted: 27 June 2024 / Published: 30 June 2024
(This article belongs to the Section Sustainable Infrastructures)
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Abstract

:
The railway infrastructure projects in Thailand aim to shift transportation from roads to railways. This is crucial for transporting goods in emerging economies and increasing the demand for rail freight transport. However, several dynamic uncertainties hinder sustainable rail freight transport in Thailand. This study aims to identify the key factors and validate their effects on the success of the modal shift from roads to railways in Thailand. A total of 200 participants filled out a questionnaire delivered online and via postal service. The key factors were categorized into the following categories: the rail freight transport system, demand, and development factors in Thailand. The inter-relationship and connection of these factors were analyzed using SEM (structural equation modeling). The SEM results showed that all causal factors in the model had a positive influence on rail freight development in Thailand, which explained 98.3% of the variance in the factors influencing development. This study’s findings underscore the influential significance of rail performance, rail infrastructure, the legal framework, pricing, mode choice, and technology on the expansion of rail freight transport in Thailand. The rail freight transport system, rail performance, rail infrastructure, and Thailand’s rail infrastructure development strategy were significant direct predictors of rail freight expansion. An expansion of the rail freight transport system also leads to rail freight demand. The results of this study have positive implications for the government, railway practitioners, and policymakers to prioritize their focus on achieving rail freight transport as the national target.

1. Introduction

Transport has a distinctive function in bridging space, which is influenced by a variety of human and physical restrictions, including geography, institutional division, time, and geographical distance [1]. As an assessment of the relationships between places, transportation is a crucial component of geography [2]. Despite being widely present worldwide, railroads differ substantially in terms of network length, density, and use (i.e., the ratio of passenger to freight markets) depending on the geographic location [3]. Since the 1820s, railroads have been an important part of the transportation network, contributing to the growth and development of the economy and society [4]. Investing in rail infrastructure is seen as a means to alleviate traffic congestion, mitigate negative environmental impacts, and stimulate economic growth in peripheral areas [5]. Since the transportation of goods via rail is driven by the economic activities of individual companies [6], rail freight transport is a major economic activity that is dependent on many enterprises and individuals [7]. For instance, even transportation uses a substantial amount of the world’s energy and resources. But an estimated 10.4% of the labor force in 2022 was employed in the transportation, warehousing, and related industries in modern industrialized nations like the United States [8]. With these advantages, rail freight transport is widely recognized as a potentially cost-effective and environmentally sustainable option as it enables economies of scale and reduces pollutant emissions [9].
To promote more sustainable transportation modes, the European Union (EU) has set a target of shifting 30% of freight transportation from roads to railways by 2030 and at least 50% by 2050 for shipments that require over 300 km of transportation [10]. The Chinese government implemented the Air Pollution Prevention and Control Action Plan in 2013, which aims to promote the shift of bulk cargo from roadways to railways and waterways, consequently lowering carbon emissions [11]. The proposals for 2020 and 2021, respectively, focus on “carbon dioxide emission peak and carbon neutrality” and “creating green logistics and promoting intermodal transport such as rail–water, road–rail, and road–water”. This indicates that China intends to become carbon neutral by 2060, with establishing a low-carbon, green, circular development economic system being the primary goal. Carbon emissions from road transportation are almost four times higher than those from rail transportation of equivalent distances according to data from the US Federal Railroad Administration [12]. However, the primary barriers to rail freight competitiveness are the increasing complexity and sophistication of supply chains; the growth in transportation and logistics capacity; the improvement in reliability, availability, maintainability, and safety; and the decrease in life cycle costs [13].
Moreover, the current application of modern digital technologies and innovation in rail transportation, which combines state-of-the-art low-carbon technology with automated and connected transport services and smart mobility, will increase the rail efficiency of internal operations in terms of cost, pricing, and safety. Some technologies adopted to overcome those barriers, such as electric trains, are zero emission, so they do not harm the climate and reduce local pollution. Electric trains can accelerate and decelerate at significantly faster speeds, which reduces travel times between stations and allows more trains to be on the line at the same time. An example of efficient technology in rail transport is the pantograph catenary system, which is widely used in high-speed trains. A high-speed rail route intended for traveling faster than 300 km/h is usually reserved solely for passenger trains [14]. Apart from rail efficiency, network, policy, environment, and technology, the other significant instruments or factors that boost rail freight concern cost and pricing, such as the freight rate, rail tariff [15], and pricing strategy.
About half of the world’s operating rail networks are located in emerging economies, and the share of rail freight transport in these countries has declined dramatically. In many countries, the modal share is merely a small percentage of the rapidly increasing number of national freight transport systems [16]. In Thailand, as in other developing countries, freight transport is predominantly reliant on road transportation, accounting for approximately 80% of the total freight volume. In contrast, rail transportation only contributes around 2% to the overall freight transport [17]. As a result, traffic congestion has significant consequences such as gradual delays, increased fuel consumption, and elevated vehicle emissions [18]. To address these issues, the Thai Ministry of Transport has established a policy aimed at shifting freight transportation from roads to railways, with a target of achieving a 10% increase in rail freight transport by 2037 by improving the logistics infrastructure. The development of these rail infrastructure projects began in 2015, with the aim to complete the first seven double-track routes by 2024. Additionally, there are plans for three phases of double-track construction and the introduction of new routes as part of the transport strategy by 2037. Nevertheless, many factors must be considered to successfully accomplish this modal shift. These include the rail freight demand and the railway transport system. Once the logistics service provider (LSP) and shipper deem that the cost, time, and reliability meet their requirements, the modal shift from roads to railways can be achieved. The political, economic, social, technological, and legal factors are exogenous. Therefore, it is crucial to identify the inhibitors that hinder rail freight transport expansion and propose appropriate policies to facilitate the transition from road to rail transportation as planned.
There has been limited research conducted on the factors that contribute to the rail freight expansion in Thailand. This study aims to explore the factors that affect rail infrastructure developments. The limited studies in the literature have provided valuable insights into the barriers and opportunities for a modal shift from roads to railways in Thailand. This study’s primary goal is to fill the gap in the literature by conducting a survey to determine the factors that promote rail freight transport. This study raises the following research question: what are the factors that influence rail freight expansion in Thailand?
Therefore, our objectives are to identify the key factors that drive the rail freight transport demand and development in Thailand, analyze the cause-and-effect relationship among these factors, and provide theoretical and managerial implications to improve the development factors of the modal shift to rail freight transportation. A structural equation model (SEM) is developed to achieved these objectives and aims to examine the relationship between the rail freight transport system, rail freight demand, and the development factors of rail freight transportation in Thailand. The SEM is applied to validate the conceptual model and assess the influence of the rail freight transport system and demand on the development factors of rail freight transportation in Thailand. Analyzing the impact of the development factors of rail freight transport in Thailand is the main objective of this study. By defining a framework of demand and system determinants for rail freight, the research findings will further develop the present theory on the development factors of rail freight transport. Additionally, this study aims to guide government officials in identifying the key development factors and raising awareness on rail transportation. This will enable them to assess the current situation and explore opportunities to promote a shift from roads to railways.
This study is organized as follows: Section 2 provides an overview of the rail freight transport system, rail freight demand, and development factor indicators; Section 3 outlines the proposed methodology; Section 4 presents the results; Section 5 discusses the findings; and finally, Section 6 concludes this article and highlights future research prospects.

2. Literature Review

2.1. Rail Freight Transport System

Railway Infrastructure
The rail transport system components consist of the rail infrastructure, rolling stock, and railway operation [19]. Rail freight transport is a method of transportation where goods are transported on land via rail cars that travel along tracks. Shipments can be arranged in a single rail car or a full train, depending on the type of commodities and the shipper’s needs [20]. The significance of the railway network and other modes of transportation has been highlighted in earlier research, as shown in [21], as crucial predictors of future developments. For instance, based on the use of geographic information system (GIS) technology, research conducted in China showed that improvements to the rail system could contribute to the elevation of territorial polarizing patterns within counties [22]. According to Woodburn [23], potential rail freight consumers consider two important factors when choosing a mode of transportation: lower costs and better service quality. In this sense, the new Ferrogro railway line’s efficiency can reduce transportation costs, and a geographic model can predict port regionalization, shorter, less costly routes, and competitiveness in relation to the geographical characteristics of the Brazilian supply chain [24]. Although the main focus of transportation geography is accessibility, the amount of contact opportunities that exist between nodes in an attraction network is also important [25].
The World Economic Forum [26] has available reports from 2009 to 2019 and assigns a ranking to 141 countries based on several parameters. In one of the questions, the train performance system was evaluated in terms of cost, speed, frequency, and punctuality. A score ranging from one for highly inefficient to seven for highly efficient was assigned. In seven Southeast Asian countries (Table 1), Singapore had the highest score of 5.8 points, while the Philippines had the lowest score of 2.4 points. Singapore’s railway transportation consists primarily of a passenger urban railway transit system that runs around the city state. However, operating services have deteriorated in other countries, such as the Philippines, partially due to the deteriorating infrastructure and lack of maintenance, and an improved highway system has given trucks a competitive advantage over railways. Clearly, these statistics show that Thailand has one of the least efficient train services in Southeast Asia, ranking 75 out of 141.
Railway Performance
It is difficult to properly measure rail performance and efficiency using other railways as a benchmark, as railways are subject to exogenous factors. Railways can be classified as public or private; vertically integrated or separated; passenger- or freight-dominated or mixed; and subsidy-supported or fully self-sufficient. Railway services are offered in various ways. From an economic standpoint, railway firms are multi-product corporations. This very capital-intensive business may be relevant for economies of scale and density and has some inherent monopolistic characteristics. It is not easy to comprehend the concept of a competitive railway market [27]. A disciplined process for systematic validation and verification that manages the reliability, availability, maintainability, and safety (RAMS) parameters throughout the life of a railway system is described in the EN50126 standard [28]. Regarding the implementation of various rail performance indicators, organizations such as Railnet Europe (RNE) [29] have stated that the key performance indicators (KPIs) to measure rail freight corridor (RFC) performance are capacity management, operations, and market development. However, in the market sector, KPI development for the rail freight market will function as a basis for the migration strategy and a source of input, as stated in [30]. Given the perspective of shippers and logistics providers, who refer to SMART-RAIL as a dependable transportation infrastructure, and the goal of greater competitiveness, the lead time, costs and income, effectiveness, flexibility, visibility, and overall satisfaction are all considered in this plan.
In contrast to product quality, which is easier for customers to understand and quantify, service quality refers to an assessment of a third-party service (such as a rail service provider) [31]. The SERVQUAL model [32] can be used to define the service quality gap between customer expectations and perception of the service. It has five generic dimensions: reliability, assurance, tangibility, empathy, and responsiveness. This model is commonly used for evaluating various services, including passenger rail service. Regarding rail freight services, India [33] created an extensive tool known as RAILQUAL to ascertain the parameters that clients employed to evaluate the quality of the railway freight service. They were given 50 questionnaire items to determine the performance of railway freight services such as the availability of observed sheds, safe transit of goods, etc.
In the Thai context, punctuality is a key part of the quality of service. Speed, economy, safety, convenience, and reliability are KPIs that were applied to measure the rail freight efficiency of bulk cargoes such as crude oil [34]. Railways, especially state-owned railways, are powerful institutions; they are typically the largest single employer in a country and generally have a long institutional lifespan. Thailand has a railway line network that is connected to 47 out of 77 provinces and comprises 4044 km of meter-gauge railway tracks. The railway lines are single-track (3687 km or 91.17%), double-track (250 km or 6.18%), and triple-track (107 km or 2.65%) [35]. The connectivity of the domestic economy is ensured through the five main lines: the Northern (781 km), Northeastern (1094 km), Eastern (534 km), Southern (1570 km), and Mae Klong (65 km) lines. Converting the country’s long-distance railway network from single- to dual-track is an important policy change that the State Railways of Thailand (SRT) is enforcing to aid the country’s long-term growth [35]. The railway tracks have width of 1.00 m and a speed limit of 80 km/h and can carry cargo weight of 15–18 tons. Most trains and wheels experience wear and have a long service life, influencing service life, service operation, and delays. As a result, the proportion of locomotives that are available for use (i.e., availability) is only about 64.1%. Since 2004, there have been many available locomotives, and the number available has always been lower than the SRT’s demand. The main central links between railway and road transport are Bangkok Port, Laem Chabang Port, and the ICD (inland container depot) Ladkrabang. While Thai railways transport both bulk (primarily oil products and construction materials) and containerized freight, most of the freight transportation is between Bangkok and sea ports (particularly between the Laem Chabang deep-water port and the Lad Krabang container terminal in Bangkok’s eastern suburbs).
Developing infrastructure and supporting factors are a gateway for trade, investment, and the important economic base of the region. Railways can connect with regional and sub-regional logistics networks to reduce logistics costs, enabling convenient access to China and countries in the Mekong sub-region by supporting connectivity between Thailand, Laos, and China in Nong Khai and Chiang Rai provinces, Cambodia at Aranyaprathet station, and Malaysia at Padang Besar and Sungai Kolok stations (Figure 1). Thai railways transport both mass (mostly oil items and industrial products) and containerized cargo. The transportation cost of double-track railways can be lowered as much as reasonably possible through collaboration services, and customers can direct their sole focus on railway cargo. The railway framework can be significantly improved to the country’s advantage via public arrangements. While freight trains can travel between Thailand and neighboring countries (Malaysia and Laos), the number of international railway freight systems currently constitutes only a minuscule portion of Thailand’s foreign trade.
Domestic freight transport development in Thailand
Figure 2 shows between 2004 and 2022, road transportation accounted for around 80% of the total amount of freight transit in Thailand. Water transportation, which includes coastal and river transportation, came in second with about 18% of the total. In contrast, the share of railway and air freight transport is relatively small, at 2.07% and 0.2%, respectively [37].
Railway Infrastructure Development Strategy and Policy
The railway sector is of great public interest to nations that have the necessary markets and corridors to support it. Public policies are based on public interests. According to Rodrigue [38], transportation policies comprise ideas intended to achieve specific targets for the social, economic, and environmental conditions and the efficacy and efficiency of the transportation infrastructure. However, along with the need to reduce harmful environmental impacts from the transportation system, other possible effects should be evaluated and considered for improvement. Developing a railway would be hampered initially by the physical topography of any given nation. The two main adverse constraints are water and relief. The cost of new infrastructure and repair will undoubtedly increase due to the presence of waterways, bridges, and tunnels [3]. Addressing transportation-related inequities and their effects requires reforming transportation systems to distribute the costs and benefits more evenly [39]. Then, the railway development strategies and policies of Europe, China, the United States, and Thailand may be implemented.
The creation of the Common Transport Policy in the 1950s marked the beginning of the EU’s Trans-European transport network (TEN-T), which was subsequently established in 1992. TEN-T projects exist in every EU member state and include all aspects of transport: road, rail, maritime, inland waterways, air, logistics, co-modality, and innovation [40]. TEN-T is intended to establish and develop the key links and interconnections needed to eliminate existing roadblocks to mobility, complete missing sections on major routes (especially across borders), cross natural barriers, and improve interoperability [41]. The European Union has set a goal for the rail industry that includes modernizing and deploying the European Rail Traffic Management System (ERTMS) on six corridors by 2020. These corridors encompass numerous significant freight routes. About 5% of all rail freight traffic in Europe uses these six lines for travel [42].
China proposed the Belt and Road Initiative (BRI) in 2013 during President Xi Jinping’s visits to Kazakhstan in September and Indonesia in October, which has brought new ideas to ongoing trends in China’s trade relations. Official data from China state that 125 countries had signed collaboration agreements with China as of March 2019, to improve connectivity and cooperation on a transcontinental scale. The scope of the BRI involves two main components, the Silk Road Economic Belt (the “Belt”) and the New Maritime Silk Road (the “Road”). The Belt links China to Europe through Central and South Asia, and the “Road” links to Southeast Asia, East and North Africa, Europe, and the Gulf States [43]. Building new, quicker trains and more direct lines is projected to boost the Chinese economy, especially in delivery times. Along with implementing the Silk Road Economic Belt, the government has also announced other infrastructure projects aimed at promoting prosperity in the region, such as the construction of a high-speed railway in western China. The New Silk Road, a network of intercontinental railroads, aims to boost trade between China and its trading partners that are connected by rail [44]. Fallon [45] also pointed out that the transportation infrastructure along this route is meant to play a major role in establishing a Eurasian “economic corridor”.
The Fixing America’s Surface Transportation (FAST) Act mandates that the U.S. Department of Transportation (DOT) should create a National Freight Strategic Plan to carry out the objectives of the country’s multimodal freight policy. A multi-agency effort involving extensive engagement with public and private sector freight stakeholders helped develop a nationwide multimodal freight plan to direct the freight efforts and policies of the US DOT [46]. Mostly privately owned, freight railroads in the US operate on either their own or another private railroad’s maintained infrastructure. With operating revenues of at least USD 490 million, 584 local railroads, 22 regional railroads, and 7 class I railroads operate across the 140,000 miles of the US freight rail network. Approximately 69% of the entire mileage in the business comprises class I railroads [47].
Previously, Thailand’s first national logistics development plan (2006–2010) outlined its goal of being the primary transportation and logistical hub for ASEAN, given its advantageous geographical position in the middle of the continent of Southeast Asia [48]. According to Thailand’s Transport Infrastructure Development for 2015–2022, Kinsukon and Suwanpot [49] examined the preferences for double-track railroads when transporting northeastern agrarian items. This approach meets three important requirements. First, it decreases the transportation time and increases the unwavering quality of commodity conveyance because the preparations are no longer delayed and left waiting. Moreover, the rail organization covers more locales and there are more accessible operating offices, including a capacity yard to prepare the agricultural products that were recently delivered by ship to a port in advance. Nevertheless, the fundamentals of this transportation infrastructure themselves also have an impact on the physical layout of railways. Numerous lines that are in use now are the result of several development procedures, including the following: The railway system was developed through gradual growth rather than in one go [3]. The railroad transport infrastructure strategy is of great significant for Thailand given the economic and geographical position of the nation and its strategic position on the regional stage, as well as for long-term international trade development.
However, no previous study has tested this relationship in Thailand. Therefore, railway infrastructure, railway performance, and Thailand’s Railway Infrastructure Development Strategy are the first three components of the rail freight transport system described in this study. These three components, in our opinion, will strengthen the shift from roads to railways and increase rail freight traffic in Thailand. Therefore, the researchers propose the following hypotheses for this study:
H1: 
The rail freight transportation system has a direct effect on rail freight demand.
H2: 
The rail freight transportation system has a direct effect on the development factors of rail freight transport in Thailand.

2.2. Rail Freight Demand

Demand represents the needs of customers—individuals, societies, businesses, and the economy—for a particular product or service and their willingness to pay for it. As the population or economy grows, demand also grows [21]. The theory of rail freight demand aims to acquire and encourage rail freight traffic. Numerous researchers have identified the demand for rail freight from various perspectives. In this study, we will only focus on six major factors related to rail freight.
Firstly, railroad construction is mostly driven by economic concerns, particularly the expansion of plantations [25]. In addition, the potential influence of transportation infrastructure on local economic development is significant as it affects the relocation of businesses and households. The primary drivers of this influence are local economic factors. For instance, introducing high-speed rail services can bring about changes in the local income composition, resulting in cumulative multiplier effects on the local economy [50]. On the other hand, there are geographical variations along the Guangdong–Guangxi–Guizhou high-speed train network in China. These variations are more pronounced in less developed areas and in locations that are distant from the regional center city. Furthermore, the primary mechanisms through which HSR propels less developed areas are the “industrial layout effect” and the “funds invested effect” [51].
Secondly, demographic factors also play a role. For example, Berger [52] discovered that the existence of a trunk railway line within a parish in Sweden leads to augmented secondary occupational shares. Furthermore, nearly all of the municipalities in Peninsular Spain studied for high-speed rail (HSR) coverage are the most densely populated according to geographic information systems (GISs) [25].
Thirdly, it is important to consider the impact on commodities. For instance, Luathep et al. [53] highlighted that rail infrastructure developments can affect the transportation of sugar products, potentially shifting freight transport from road to rail systems.
Fourthly, mode choice is another crucial factor to consider. Distances between locations and the resulting travel time, as well as associated intermodal competition, have an impact on the geography and usage of railway lines. When medium- and long-distance accessibility is acknowledged as an essential element of a city’s or region’s appeal, intermodal rivalry considers infrastructure and travel times in addition to services (routes, frequencies, and timetables) [3]. It is essential to understand the effects of shippers’ mode choices to increase the mode share of railways in hinterland leg container transportation. Therefore, it is recommended that railway demand forecasting and project appraisals consider mode-specific willingness-to-pay factors [54].
Fifthly, pricing also plays a significant role. According to the Asian Development Bank (ADB) [55], low-cost or fare-reduced freight services for bulky cargoes over long distances can stimulate rail freight demand in Thailand, ensuring cost reduction and maintaining physical interconnectivity with logistics hubs, production centers, ports, and consumers. Similarly, in China, recent studies on the modal shift from road to rail freight to reduce CO2 emissions stated that market-oriented railway pricing and operation planning are the two most significant factors that increase railway freight competitiveness. Revenue management is widely employed in many industries, such as the sales of perishable goods, hotel management, and air transportation, and depends heavily on market-based pricing [56]. Furthermore, one of the factors influencing the transportation rate in a spatial interface is undoubtedly the cost of transporting freight, together with any changes in rate and associated charges. In general, freight rates are directly correlated with distance itself. Because of their tremendous complexity, it is very difficult to translate the rates’ structure into meaningful spatial patterns [57]. The freight rate and total economic activity are the most important factors influencing rail freight demand in Pakistan, according to a study conducted in the same year that used annual time series data from 1972 to 2017 to analyze the rail freight transport demand and make management and planning decisions [58]. Furthermore, a recent study conducted in Italy uncovered the cost function of the new rail line connecting the hinterland of Leghorn port, which included wages, the cost of using rail tracks, operation costs, the amortization of costs, and maintenance and insurance costs of locomotives and wagons [59].
Finally, fuel prices have an effect on rail freight demand, so governments should encourage the transition from energy-inefficient to energy-efficient modes of transportation to achieve sustainable freight transportation, according to [60]. Therefore, the researchers formulated the following hypotheses:
H3: 
The rail freight demand has a direct effect on the development factors of rail freight transport in Thailand.
H4: 
The rail freight transportation system has an indirect effect on the development factors of rail freight transport in Thailand via the rail freight demand.

2.3. The Development Factors of Rail Freight Transport

The railway system and other modes of transportation play a crucial role in shaping future developments. When the time frame is short, the environment, including the economy, societies, technologies, and financing, remains relatively stable and changes predictably [21]. For instance, the heavily regulated railroads in the United States underwent significant deregulation in 1980 through the 4R Act and Staggers Rail Act. This shift made the railroads more reliant on the free market to enhance profitability, as highlighted in [61]. In Thailand, the “Guidelines for Developing Thailand’s State Railway (SRT)” study examined the current state and administrative challenges of the SRT and potential growth opportunities. The study suggests that factors such as approach and governmental issues, the economy, society and culture, innovation and advancement, the climate, and regulations should be considered in the analysis [62]. Furthermore, Peetawan and Suthiwartnarueput [63] found that the rail development master plan is crucial to the achievement of Thailand’s rail infrastructure project. Kelly [64] emphasized the significant impact of railroads on the political, economic, and geographical future of the United States, as they facilitate suburban living and influence the physical development of cities and towns.
This study aims to identify the determinants of these factors to assess the importance of the development factors of rail freight transport in Thailand. Based on an extensive review of the existing literature, which includes nearly 100 studies, 33 of them were deemed highly relevant. Ultimately, a comprehensive analysis reveals a total of 15 factors specific to Thailand’s rail freight industry that can be categorized into three distinct groups, as illustrated in Table 2: the rail freight transport system, rail freight demand, and development factors.
After the classification of the 15 factors, related studies also helped identify the potential relationship between the following three characteristics: the rail freight transport system, rail freight demand, and development factors specific to Thailand’s rail freight industry. Within this path model, there are two types of paths. The first path involves the relationship between the rail freight transport system and the development factors, which in turn affects rail freight demand and the system itself. The second path focuses on the rail freight demand, which plays a significant role in the development factors of rail freight transport according to various literature sources. Building upon these two paths, a path model framework was proposed, supported by the literature, as shown in Figure 3.

3. Methodology

3.1. Survey Instrument

A measure was adopted from an extensive literature review and in-depth interviews to create the research instruments. The instrument used in this study was a questionnaire, divided into four parts: Part 1 collected demographic data, including business type, location, commodities, and modes of transportation; Part 2 collected information about rail freight transportation system data, including railroad infrastructure, railroad performance, and Thailand’s infrastructure development strategy; Part 3 collected information about rail freight demand data, including local economics, demographics, commodities, mode choice, pricing, and fuel price; Part 4 collected information about the development factors of rail freight transport in Thailand, including political, economic, socio-cultural, technological, environmental, and legal factors. Parts 2 to 4 consisted of questionnaires related to measurement variables, as shown in Table 2. Furthermore, a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree) was applied. This scale effectively captured a wide range of possible responses and allowed for a comprehensive evaluation of individual perspectives.
Five academic logistics and supply chain professionals reviewed the content validity of the research instrument using the Item-Objective Congruence (IOC) index. All items were rated higher than 0.50 on the IOC index, indicating that they were acceptably congruent with the set objectives. A pilot test was conducted to ensure the reliability of the instrument. Cronbach’s alpha was used to test the internal consistency of the measurements. The results indicated that the Cronbach’s alpha for the different measurements ranged from 0.70 to 0.92. Furthermore, the instrument design examined various issues, such as language that was easy to understand and user-friendly.

3.2. Data Collection and Data Analysis

The target participants of this study were manufacturing and logistics service providers. The former included agricultural (cassava, palm, para rubber, rice, and sugar) and industrial economic manufacturing (cement, fertilizer, and steel) providers. The latter consisted of railway customers and members of the Thai Transportation and Logistics Association and the Thai International Freight Forwarders Association. Data collection was carried out from May to October 2023; the questionnaires was distributed via “Google Forms” and postal mail, and a total of 203 responses were obtained. However, three incomplete responses were excluded. Therefore, only 200 responses were included in the total sample, which was deemed sufficient for the analysis, as presented in Table 3.
Statistical Package for the Social Sciences (SPSS) 24 was used for the descriptive analysis and reliability testing, while the analysis of moment structures (AMOS) 24 was used for confirmatory factor analysis (CFA) and SEM. The questionnaire was designed to capture the development factors of rail freight transport, rail freight transportation systems, and rail freight demand in Thailand.

4. Results

4.1. The Demographic Characteristics of the Respondents

In total, 65% of the 200 respondents were from the manufacturing sector, while 35% were from the logistics service provider (LSP) sector. Nearly one-third of the overall respondents (27.5%) were from central Thailand, with Bangkok coming in second at 22%. Many respondents (41.50%) were involved in general product transportation, while 35.50% were involved in dry bulk cargo transportation. Liquid bulk and other industrial product categories made up 9% and 14% of the total, respectively. Regarding the domestic mode of transport, most respondents (86.14%) said that their primary mode of transportation would be via road, with rail transportation second at 9.96%; 2.60% selected coastal shipping or inland waterways and 1.33% selected pipe transportation (Table 3).

4.2. The Measurement Analysis of Construct Validity

As shown in Table 3, the number of latent variables is directly related to degrees of freedom (df) for the fit indices. The values of the three indices (CFI, GFI, and RMSEA) include the df term that penalizes their values. The value is 0.900 or above for CFI and GFI and 0.05 or below for RMSEA (Table 4).
Internal consistency was evaluated using composite reliability (CR) and Cronbach’s alpha (α) to ensure the reliability and validity of the constructs. As shown in Table 5, CR ranges from 0.814 to 0.887, while the α values range from 0.950 to 0.960, both of which exceed the acceptance thresholds.
The construct validity was evaluated using convergent and discriminant validity techniques, the CFA factor loading ranged from 0.431 to 0.881, and the average variance extracted (AVE) ranged from 0.539 to 0.724, with both being greater than 0.5 [79]. Additionally, the factor loading (λ) for all constructs in the measurement model was found to be highly significant (p < 0.001) and surpassed 0.3 (as a general rule of thumb, the value should be >0.3). The coefficient of determination (R2) represents the effect size, which reflects the strength of the relationship between the dependent and independent variables. Therefore, the strength of the model was further established, with R2 values of 0.113 to 0.758. Concerning the model, all the coefficients of the variables were statistically significant at the 95% confidence level.
The heterotrait–monotrait ratio of correlation (HTMT) analysis, an emerging and robust technique, was applied to assess the confidence of discriminant validity, and all constructs possessed HTMT values of less than one and were significant, as recommended in [80] (Table 6). Thus, discriminant validity was confirmed for all constructs.

4.3. The Structural Analysis Model and Hypothesis Testing

We used AMOS 24 to investigate the relationships between the RFTS, RFD, and DFRF. The model fit indices indicate a strong fit, with Chi-square = 36.525, df = 29, p-value = 0.159, Chi-square/df = 1.259, CFI = 0.998, GFI = 0.976, AGFI = 0.902, TLI = 0.992, RMR = 0.024, and RMSEA = 0.036. The CFI, GFI, AGFI, and TLI were highly suitable for our research model because their fit values were very close to 1.0, which denotes a perfect fit. RMR and RMSEA were the other fit indices used; a value < 0.10 indicates a good model fit. Our results show that the estimated model fits these criteria and attests to the construct validity for model measurement. The statistical results showed that the empirical data were in good agreement with the model. The SEM results related to hypotheses 1–4 are shown in Figure 3 and Table 7. The results from testing the hypotheses are outlined below.
A key metric of a model’s quality is its predictive capacity. According to Hair et al. [81], a data set is considered to have a good predictive capacity if its coefficient of determination (R2) is larger than 0.6. In this model, the fit index indicates a strong fit, with R2 = 0.983 for the DFRF. The strong R2 value demonstrates that the variance in the DFRF could be predicted using the RFTS and the RFD as independent constructs. Furthermore, there is an indirect effect of the RFTS on the DFRF through the RFD, with an R2 = 0.875 for this path.
Table 7 shows the correlation coefficients. All paths were significant at p < 0.05, and the test results showed that the RFTS had a positive and statistically significant RFD (β = 0.936). The RFTS and RFD were positive and statistically significant for the DFRF (β = 0.363 and β = 0.643, respectively). However, the RFTS had a significant direct effect on the DFRF and an indirect effect on the RFD (β = 0.602). Thus, hypotheses H1 to H4 were supported.

5. Discussion

We examined the factors that promote rail freight expansion in Thailand. In Figure 4 and Table 8, the performance of the model proves that the model aligns well with the data gathered via surveys, as depicted in Figure 2. The RFTS characteristics include rail performance (0.908), which is the most relevant in this study, followed by the rail infrastructure (0.900) and Thailand’s rail strategy development infrastructure (0.784). Regarding RFD characteristics, the indicators of pricing (0.833) and mode choice (0.830) are more significant than fuel price (0.743), commodity (0.510), demographics (0.477), and local economics (0.410). Regarding DFRF characteristics, the legal indicator (0.890) was the most significant, followed by technology (0.802), political (0.749), environmental (0.704), and socio-cultural (0.497), while the economy was the least significant (0.384).
Indicators such as rail performance, rail infrastructure, legal factors, pricing, mode choice, and technology are crucial and should be paid close attention to boost rail freight traffic and establish a resilience model. Even in this study, the respondents were not concerned much about the environment. However, the environment is the main issue raised in the present day. The Green Deal for Europe aims to compete and have zero greenhouse gas emissions by 2050. European member states are working hard to accomplish this goal and seek the appropriate policy and strategy to implement. One notable contribution from Cempirek et al. [82] suggested Lean + Green initiatives in the Czech Republic to promote sustainability and profitability in the transportation sector. The train operator must suggest multimodal transportation via the Modalohr system to decrease negative environmental effects of railroads. The simulation of the discrete choice high-speed train model found that high-speed rail freight transport in Europe is roughly 70% more expensive than traditional lorries, but it generates 80% less CO2 emissions [83].
However, in many countries, railways are considered the second most important source of ambient noise pollution, immediately after urban traffic. It is unlikely that nearby residents find train noise to be disruptive [84]. Freight trains create additional environmental problems with their noise and vibrations because of their larger axle weights and longer pass-by lengths [76].
The results of the path coefficient analysis are shown in Table 5, and the results from testing the hypotheses via AMOS 24 established that all four hypotheses were supported. Moreover, the casual variable analysis of the model also established that all variables positively affected the DFRF, which had a coefficient of determination (R2) of 98.3%. The following section explores the hypotheses, testing both strengths and weaknesses and their inter-relationships.

5.1. Rail Freight Transportation System

Table 6 and Figure 2 demonstrate that the test results of the three hypotheses for the RFTS were all positive, while H1 and H2 were direct and H4 was indirect. The H1 relationship between the RFTS and RFD was strong (r = 0.936). Furthermore, the correlation between the RFTS and DFRF was very high (r = 0.965) (encompassing the total effect). The RFTS was shown to have a very positive impact on RFD and DFRF, which proves H1, H2, and H4, respectively.
This finding is consistent with prior studies in different contexts [20], which mention that railway networks and other means of transportation are key deterministic factors in future developments. The three main criteria that define future systems are demand, accessibility, and affordability. In addition, some transportation demands cannot be met due to insufficient railway freight capacity. Rail transportation requires high-capacity transportation infrastructure that can promote sustainable development in a competitive economy [55]. Rail infrastructure is generally defined as tracks, stations, locomotives, and freight cars; however, rail transportation systems have the disadvantage of first-mile delivery and require logistics facilities such as container stations and inland container terminals. A study in Nigeria revealed that developing rail links, optimal rail freight corridors, and rail freight services between inland container depots (ICDs) and container freight stations (CFSs) is necessary to ensure the viability and functionality of ICDs and CFSs. Creating these corridors between the hub, seaports, and regional ICDs will considerably lower domestic prices and increase the competitiveness of exports from ICD regions in global markets [85]. The authors of [22] supported this idea, stating that improvements to infrastructure could lower prices and boost service quality, which are two factors that are important to prospective rail freight customers when considering a mode of transportation. The data point to the likelihood that the infrastructure, performance, strategy, and policies of the rail transport system may boost rail freight demand in the future.
The RFTS positively affected the elements that supported the rail freight transport system, thereby supporting hypothesis 2 in turn. This was in line with Brazilian data showing that the rail freight sector in Brazil accounted for over 20 percent of the total volume transported, an increase of 20 percent throughout the country’s 15 years of railway concessions [86]. Moreover, it was shown that a more directly targeted policy on infrastructure investment is required to loosen the existing limitations on rail share in Central and Eastern European (CEE) countries. This policy could come in the form of higher subsidies or different strategies to entice private investment in infrastructure [87]. The findings also indicate that rail freight transport systems have a substantial impact on the outcomes of increased rail freight traffic.
The acceptance of H4 in this study was facilitated via RFTS, which positively impacted factors for rail freight traffic via RFD. This is in line with past studies conducted in China, where the production and consumption of commodities had an impact on freight transportation. The rail freight demand is influenced by a wide range of factors, including the location of the demand, fuel pricing, infrastructure constraints, and economic progress. Railway networks are seeing an increase in traffic as the number of freight transport systems increases. Significant improvements in rail infrastructure are needed to accommodate the demand for freight transport [88]. Many anticipate that rail freight traffic may rise from the influence that RFD has on rail transportation networks.

5.2. Rail Freight Demand

RFD has a positive effect on DFRF, as supported by H3, which shows a moderate correlation of r = 0.643. As mentioned earlier, the variables that affect the total volume of rail traffic can be categorized into four interconnected groups: demand for commodities, supply and production of commodities, modal competition, and rail services [89]. Like previous research on the Turkish Rail System, the demand characteristics for city- and station-based production and attraction trips were identified to determine key load centers and corridors for rail freight demand. Typically, the most industrialized locations, including ports and cities, that generate mineral resources serve as the starting and ending points for significant rail freight transport systems [90]. Rail freight pricing is a significant factor in boosting the freight modal shift from roads to railways [57]. Low costs can induce rail freight demand [54] and provide additional evidence by suggesting that a subsidy policy is considered to promote rail freight, and that dynamic freight pricing enhances the competitiveness of rail freight transport [55].
These findings indicate that the demand for commodities transported by rail freight, pricing, the choice of mode, and fuel prices all play a significant role in determining the total number of rail freight transport systems.

6. Conclusions

This study examined the endogenous factors of the rail freight transportation system in Thailand and the effect of rail freight demand on rail freight expansion. This aligns with the government’s goal of achieving a 10% conversion from roads to railways by 2037. This study presents a theoretical framework that identifies the key factors driving the expansion of rail freight traffic in Thailand. A survey with manufacturing and LSP from various regions of Thailand was conducted, and questionnaires were used to gather data. A total of 200 valid and complete survey responses—130 from manufacturing and 70 from LSP—were used for the analysis. The results showed that all models’ casual variables positively affected the development factors of rail freight transport with an R2 = 98.3%. The analysis also revealed that the rail freight transport system was the most significant when ranked by the total effect values. The key factors that influence rail freight development in Thailand included rail performance, rail infrastructure, legal factors, pricing, mode choice, and technology. This implies that improving railway performance—such as trip time reliability and carriage availability—can help boost rail freight transport. A robust railway network and tracking system will also result in increased customer satisfaction. The lesson for changing laws and regulations and stabilizing rail freight transport is best illustrated by the example of the United States. Creating a price that corresponds with commodity attributes and distance will draw in an increased number of prospective clients. The benefit of environmental friendliness will assist the business in developing its social responsibility. In conclusion, utilizing technology for both operation and service will improve rail freight traffic.
As a result, both the government and railway operators will greatly benefit from the valuable recommendations provided in this study, which can be applied in real-life scenarios to launch campaigns supporting rail freight transport. The government should prioritize enhancing the quality of rail services and the development of the rail infrastructure; implement rail network, rail station, and logistics facilities, such as container yards and inland container depot; implement deregulation measures; establish a reasonable pricing strategy; encourage the transition from roads to railways; and allocate funds for technological improvements.

6.1. Theoretical Implications

Our results contribute to the body of knowledge on the domestic variables for rail freight transport development. The implications are as follows:
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There is a broad variety of inter-related rail freight development elements to support the modal shift from road to rail.
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The analysis of the components’ relationships from the point of view of the key stakeholders is novel, and substantially contributes to the body of knowledge on stakeholders’ theories.
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The framework of this study can serve as a basis for future advancements in rail freight transportation.

6.2. Managerial and Policy Implications

This study has significant managerial and policy perspective implications for rail freight transport development in Thailand. The present study involves the primary stakeholders’ views on rail freight transport development in Thailand. This study highlights the following implications:
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The findings place strong emphasis on rail performance, whereby the SRT can increase freight volume by enhancing rail performance through accelerated transit times and increasing train capacity through double stacking, improved train maintenance, increased availability of wagons, customized services, and increased safety.
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The findings show that the requirements for rail framework improvement prevent rail cargo advancement in Thailand. Accordingly, government policymakers at SRT can propose sufficient engineering and innovation to draw in new clients in the SRT cargo transport business.
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By approving new laws to liberalize services, we would allow competitors and newcomers to freely participate in the railway freight transport industry. New rail freight operators could be made possible by the prompt separation of the functions within the state’s monopolies into infrastructure management and railway undertakings.
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To maintain competitiveness, especially in road freight, it is important to adopt a tariff policy and a truck CO2 emission tax to promote rail freight traffic.
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A pricing dynamic strategy should be developed. To set prices for rail freight transport, it is necessary to fully liberalize the market, ensure fair competition, and conduct more successful acquisitions using incentives based on price origin and destination.
The factors that have been identified as contributing to rail freight expansion in Thailand can serve as a practical guide for rail freight organizers to optimize their policies, strategies, and practices. This study highlights the importance of investing in improving facilities to develop rail operator services that meet the increasing rail freight demand. These factors play a significant role in attracting new customers, retaining existing ones, and maintaining a competitive edge in the rail freight sector for both the State Railway of Thailand (SRT) and policymakers such as the government and the Department of Rail (DRT).
Furthermore, this study emphasizes the need for the SRT, government, and DRT to focus on strengthening the demand for a modal shift among manufacturing and logistics service providers. This can be achieved by improving the quality of rail services in terms of logistics facilities, the network, liberalization, competitive pricing, and mode choice. Given the relatively low number of rail freight transport systems in Thailand, it is crucial to take practical steps to support rail freight customers, practitioners, and policymakers, especially as the industry begins to recover. This study recommends SRT and DRT to carefully plan and implement these measures in their operations. Additionally, SRT and DRT should prioritize rail freight pricing, as this significantly encourages a shift from road to rail transportation. They should incorporate pricing policies and legal considerations into their rail freight strategies to attract existing customers and tap into new potential markets. Moreover, this study suggests that SRT and the government should embrace technology and innovation to improve rail performance and promote sustainable rail freight transportation in Thailand. Successfully increasing the rail freight demand relies on achieving a sustainable competitive advantage, which stems from both financial and marketing success.

6.3. Future Research

Our study demonstrated that rail performance is the main factor of timeliness in intercity and regional services to improve rail freight performance in Thailand and the frequency and length of train service delays, especially during station pauses. As more consumers switch from roads to railways, future research will assist railway operators in developing strategies for effective train operations that will reduce costs, boost earnings, and expand their market shares.

Author Contributions

Conceptualization, O.B. and T.H.; methodology, O.B., V.S. and T.H.; writing—original draft preparation, O.B.; writing—review and editing, O.B., V.S. and T.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The data used to support the findings of this study are available from the corresponding author upon request.

Acknowledgments

The authors express their gratitude to all manufacturing and logistics service providers who participated in the survey and to the experts who offered insightful comments and suggestions that helped to refine this paper’s structure and content.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

αCronbach’s alpha
X2Chi-square distributions
R2coefficient of determination
Dfdegree of freedom
pp-value
λlambda, factor loading
βbeta
rPearson Product Moment Correlation Coefficient
AMOSanalysis of moment structures
ADBAsian Development Bank
AGFIadjusted goodness of fit index
AVEaverage variance extracted
BRIBelt and Road Initiative
CEECentral and Eastern Europe
CFAconfirmatory factor analysis
CFIcomparative fit index
CFSscontainer freight stations
CMIN/dfrelative chi-square
CRcomposite reliability
DFRFDevelopment Factors to Rail Freight in Thailand
DEdirect effect
ERTMSEuropean Rail Traffic Management System
EUEuropean Union
FASTFixing America’s Surface Transportation
GFIgoodness of fit I
HTMTheterotrait–monotrait ratio of correlations
ICDinland container depot
IEindirect effect
IOCitem-objective congruence
KPIskey performance indicators
LSPlogistics service provider
RAILQUALrail quality
RAMSreliability, availability, maintainability, and safety
RFCsrail freight corridors
RFTSrail freight transport system
RFDrail freight demand
RMRroot mean square residual
RMSEAroot mean square error of approximation
RNERailnet Europe
SEMstructural equation modeling
SERVQUALservice quality
SPSSStatistical Package for the Social Sciences
SRTState Railways of Thailand
TEtotal effect
TEN-TTrans-European Transport Network
TLITucker–Lewis Index

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Infrastructures 09 00102 g001
Figure 1. The railway network of Thailand. Source: Thai Railway Wiki [36].
Figure 1. The railway network of Thailand. Source: Thai Railway Wiki [36].
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Figure 2. Domestic freight in Thailand. Source: Ministry of Transport [37].
Figure 2. Domestic freight in Thailand. Source: Ministry of Transport [37].
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Figure 3. The theoretical model of the development factors of rail freight in Thailand. Source: authors.
Figure 3. The theoretical model of the development factors of rail freight in Thailand. Source: authors.
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Figure 4. Results of structural equation modeling (SEM). Source: authors.
Figure 4. Results of structural equation modeling (SEM). Source: authors.
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Table 1. Quality of railway infrastructure in Southeast Asia.
Table 1. Quality of railway infrastructure in Southeast Asia.
CountryGlobal RankingScale (1 (Low)–7 (High))
Singapore55.8
Malaysia125.1
Indonesia184.7
India284.4
Vietnam523.6
Thailand752.8
Philippines862.4
Source: World Economic Forum [26].
Table 2. Development factors of rail freight transport.
Table 2. Development factors of rail freight transport.
ConstructsFactorsReferences
Rail Freight Transport System
(RFTS)		RFTS
Rail Infrastructure		[21,23,56]
Rail Performance[27,28,29,34]
Thailand’s Rail Infrastructure Development Strategy[49,63,65]
Rail Freight Demand
(RFD)		RFD
Local Economy
[21,51]
Demographics[53,66,67]
Commodity[51,53,68]
Mode Choice[54,69,70]
Pricing[55,56,58]
Fuel Price[60,71]
Development Factors of Rail Freight in Thailand (DFRF)DFRF
Political
[49,62,72,73]
Economic[21,62,63,64]
Socio-cultural[21,62,63]
Technology[62,74,75]
Environment[62,76,77]
Legal[61,78]
Table 3. Descriptive statistics of demographic data.
Table 3. Descriptive statistics of demographic data.
VariableCategoriesFrequencyPercentage (%)
Business Type (N = 200)Manufacturing13065.00
LSP7035.00
Location (N = 200)
Central5527.50
Bangkok4422.00
Southern4120.50
Northeastern2412.00
Eastern2211.00
Northern147.00
Commodities
General products8341.50
Dry bulk7135.50
Other types of industrial products 2814.00
Liquid bulk189.00
Transportation Modes
Road19986.14
Rail239.96
Coastal shipping or inland waterway62.60
Pipe31.30
Table 4. Confirmatory factor model fit indices.
Table 4. Confirmatory factor model fit indices.
ConstructsChi-SquaredfCFIGFIRMSEA
RFTS0.09411.0001.0000.000
RFD0.10611.0001.0000.000
DFRF1.67641.0001.0000.000
Note: CFI = comparative fit index, GFI = goodness of fit index, and RMSEA = root mean square error of approximation.
Table 5. Analysis results of construct indicator validity.
Table 5. Analysis results of construct indicator validity.
IndicatorsItemsαAVECRR2λ
RFTS 0.9600.7240.887-
Rail InfrastructureX1 0.858
Rail PerformanceX2 0.871
Thailand’s Rail Infrastructure Development Strategy X3 0.823
RFD 0.9500.5390.8140.875
Local EconomicsX4 0.431
Demographic sX5 0.484
CommodityX6 0.493
Mode ChoiceX7 0.820
PricingX8 0.826
Fuel PriceX9 0.785
DFRF 0.9580.5910.8440.983
PoliticalY1 0.568
EconomicY2 0.432
Socio-culturalY3 0.497
TechnologicalY4 0.880
EnvironmentY5 0.881
LegalY6 0.799
Note all values (p < 0.001). X2 = 37.168, df = 27, CMIN/df = 1.377, CFI = 0.997, GFI = 0.976, AGFI = 0.895, TLI = 0.988, RMR = 0.029, and RMSEA = 0.044.
Table 6. Discriminant validity: heterotrait–monotrait ratio of correlations (HTMT).
Table 6. Discriminant validity: heterotrait–monotrait ratio of correlations (HTMT).
RFTSRFDDFRF
RFTS0.851
RFD0.813 ***0.863
DFRF0.865 ***0.855 ***0.901
Note: *** p < 0.001.
Table 7. Test results of the hypotheses.
Table 7. Test results of the hypotheses.
Path/HypothesesPath Coefficients (β)Direct Effect (DE)Indirect Effect (IE)Total Effect (TE)Degree of InfluenceResult
RFTS → RFDH10.9360.936-0.936Very highSupported
RFTS → DFRFH20.3630.363-0.965Very highSupported
RFTS → RFD→ DFRFH40.602 0.602Supported
RFD → DFRFH30.6430.643-0.643ModerateSupported
Table 8. The analysis results of SEM.
Table 8. The analysis results of SEM.
ConstructsItemsIndicatorsλ
RFTS
X1- Rail Infrastructure0.900
X2- Rail Performance0.908
X3- Thailand’s Rail Infrastructure Development Strategy 0.784
RFD
X4- Local Economics0.410
X5- Demographics0.477
X6- Commodity0.510
X7- Mode Choice0.830
X8- Pricing0.833
X9- Fuel Price0.743
DFRF
Y1- Political0.749
Y2- Economic0.384
Y3- Socio-cultural0.497
Y4- Technological0.802
Y5- Environment0.704
Y6- Legal0.890
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Buthphorm, O.; Sukhotu, V.; Hengsadeekul, T. An Analysis of the Development Factors of Rail Freight Transport in Thailand: A Structural Equation Modeling Approach. Infrastructures 2024, 9, 102. https://doi.org/10.3390/infrastructures9070102

AMA Style

Buthphorm O, Sukhotu V, Hengsadeekul T. An Analysis of the Development Factors of Rail Freight Transport in Thailand: A Structural Equation Modeling Approach. Infrastructures. 2024; 9(7):102. https://doi.org/10.3390/infrastructures9070102

Chicago/Turabian Style

Buthphorm, Oranicha, Vatcharapol Sukhotu, and Thammanoon Hengsadeekul. 2024. "An Analysis of the Development Factors of Rail Freight Transport in Thailand: A Structural Equation Modeling Approach" Infrastructures 9, no. 7: 102. https://doi.org/10.3390/infrastructures9070102

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