Introduction

Globally, many countries utilise sports events to stimulate local economies (Barajas et al. 2016; Chutiphongdech and Kampitak, 2022; Kwiatkowski and Oklevik, 2017). Hosting sports events creates employment opportunities, enhances business prospects, circulates and distributes money within communities, and generates substantial tourism revenue, as participants and attendees of such events are considered high-value tourists (Dixon et al. 2012; Lee and Taylor, 2005). The rapid growth of sports events worldwide has demonstrated their positive impact on the destination image of event-hosting locations (Williams et al. 2021), largely due to the significant media coverage these events attract (Kim et al. 2017).

However, not all sporting events generate profit, produce investment, or bring sufficient revenue to the host countries (Deccio and Baloglu, 2002; Lertwachara et al. 2022; Lin and Lu, 2018). Given the high demand for resources, the economic benefits of hosting a mega sports event can be diminished. The more resources sourced externally, the fewer benefits remain within the host country (Agha and Taks, 2015). Therefore, government or organisational grants are essential to ensure these benefits are retained domestically. Unlike local sporting events, mega sports events require substantial financial and non-financial resources. Consequently, many countries withdraw their bids due to the significant costs and logistical challenges involved. For instance, this phenomenon was evident in the bidding process for the 2026 Winter Olympic Games (Kobierecki & Pierzgalski, 2022).

The question of whether the economic impacts of sports events accrue to host cities remains contentious. Unsurprisingly, studies examining the economic impact of sporting events have garnered scholarly attention for many decades due to their importance in policy-informed decision-making processes (Allmers and Maennig, 2009; Crespo Sogas et al. 2021; Diedering and Kwiatkowski, 2015; Dimitrovski et al. 2022; Kobierecki and Pierzgalski, 2022; Li and Jago, 2013; Pereira et al. 2021; Preuss, 2005; Yüksel and Ön, 2024). This is because information on the economic impact of hosting sports events is crucial for policymakers in shaping sports policies, public budgeting, and sport infrastructure development.

Although several research papers aim to investigate the economic impacts of hosting sport events, most previous studies have focused on estimating these impacts at the national level (Agha and Taks, 2015; Duglio and Beltramo, 2017; Gelan, 2003; Gratton et al. 2000; Kwiatkowski and Oklevik, 2017; Wilson, 2006; Zourgani and Ait-Bihi, 2023). This is possibly due to the availability of aggregate datasets within each country. According to the systematic literature review by Zourgani and Ait-Bihi (2023) and the bibliometric analysis by Yüksel and Ön (2024), approximately 70% of studies concentrated on economic impact assessments for mega and large sporting events, with a focus on specific regions such as North America and Europe. In contrast, very few studies have explored the impacts of local-scale events, which have received significantly less attention compared to major or mega-scale events (Dávid et al. 2018). This is despite the fact that small-scale sport events offer strategic benefits—such as cost efficiency, sustainable infrastructure utilisation, and ongoing community involvement—that often generate more substantial and enduring economic gains for host towns than large-scale events (Agha & Taks, 2015).

Furthermore, previous research on this phenomenon within Asian contexts remains notably scarce, while past studies in similar domains have predominantly employed a single research method, focusing primarily on quantitative analysis rather than qualitative approaches. Understandably, quantitative analysis allows for capturing the economic impact of hosting sport events (Li and Jago, 2013). However, this focus has led to a lack of in-depth exploration in the research domain. Furthermore, the integration of qualitative analysis, such as through a mixed-methods research design, remains highly limited, despite its advantages in providing deeper insights into the subject area. (Bakhsh et al. 2022; Daniels et al. 2004).

Hence, to address existing knowledge gaps and advance the literature on sport event impact assessment, this empirical study aims to answer the research question: What are the long-term economic impacts of hosting a sporting event at the provincial level? Specifically, the objective of this study is to examine the economic effects of sporting events at the provincial scale, using the Bangsaen21 Half Marathon (B21) in Chonburi Province, Thailand, as the contextual focus. This case study evaluates the effects of B21 on the local economy, with a primary focus on tourism-generated income. A mixed-method research design, specifically an explanatory sequential design, was employed to offer methodological insights into how hosting sporting events contributes to economic development within the province.

The organisation of the paper is as follows: the next section outlines the research method employed in this study and details the case study, data collection, data analysis, and research instruments. The subsequent section presents the findings, including the first-stage quantitative analysis of the economic impacts of hosting the B21 event and the second-stage qualitative analysis of runners’ spending behaviours. The discussion section integrates both analyses and contextualises the findings within the existing literature. The final section concludes the study, highlights its limitations, proposes implications for relevant stakeholders, and suggests directions for future research.

Research method

Case setting

The Bangsaen21 Half Marathon (B21) was first hosted on 6 December 2015 by Mice & Communication Co. Ltd., an event management organiser in Thailand owned by Mister Ratt Jirojwannitakarn. It is an annual half marathon held in Chonburi, a province located in the eastern part of Thailand. Chonburi occupies the eastern coast of the Gulf of Thailand, boasting a coastline that stretches up to 160 kilometres. The terrain is mostly flat, interspersed with hills and coastal plains, with mountains extending through the province from the northwest to the southeast. Given its advantageous geography and natural resources, Chonburi benefits from provincial economic development across several sectors, supported by its excellent transportation infrastructure (Chonburi Provincial Administration Organisation, 2022).

In 2023, Chonburi had a population of approximately 1,618,066 people (Department Of Provincial Administration, 2024). The province has made significant progress in regional development, achieving a balance between natural resource preservation, tourism, agriculture, and lifestyle, while maintaining its local cultural heritage. Chonburi has experienced continuous economic growth, as reflected in its Gross Provincial Product (GPP), as shown in Table 1 (Chonburi Provincial Statistical Office, 2024; National Statistical Office 2022; Office of the National Economic and Social Development Council, 2024). It boasts natural tourist attractions and the capacity to support various types of tourism, particularly sport event tourism.

Table 1 Gross Provincial Product of Chonburi (Thai Baht: THB).
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The B21 was launched under the theme ‘The Finest Running Event Ever’. The race covers 21.0975 kilometres, following a beautifully scenic and challenging coastal route, which is one of Bangsaen’s unique highlights. Initially, Bangsaen21 included other distances, such as 5 km, 10 km, and 21.1 km. However, it began exclusively hosting the half marathon distance event in 2019 (Bangsaen21, 2020). The route starts at Bangsaen Road 1, passes several roads and attractions, and then loops back to the starting point on Bangsaen Road (Fig. 1).

Fig. 1: B21 race map.
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Source: Bangsaen21 (2023).

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In 2023, the World Athletics Federation recognised the standards for all 256 road running events. Bangsaen21 was certified as one of the 15 global events to receive the highest standard, the World Athletics Platinum Label, alongside legendary events such as the Boston Marathon, Tokyo Marathon, and Berlin Marathon. According to Bangsaen21 (2024) and World Athletics (2024), Bangsaen21 is the only event among the 15 Platinum Label events to achieve this recognition in the half marathon category. Given its ongoing professional operation in Chonburi and the notable trend of increasing runner participation compared to other local-scale sporting events in the country (Table 2), the B21 event serves as an ideal case study for conducting an economic assessment at the provincial level to address the study’s research objectives.

Table 2 B21 participants during 2015–2023.
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Research design

To investigate the economic impact at the provincial level through the hosting of B21, this study employed mixed research methods, specifically the explanatory sequential design, to provide deeper insights into the research problems (Draucker et al. 2020). This approach is considered appropriate and valuable, particularly when researchers need to clarify quantitative findings (Haynes-Brown, 2023). Using qualitative data helps explain and supplement numerical results, as quantitative findings alone often present limitations in explaining causal relationships (Ghelichkhani et al. 2024; Ivankova et al. 2006). Furthermore, by sequential combining quantitative rigour with qualitative depth, this design enhances the validity and credibility of research findings, reducing the risk of misinterpretation when analysing numerical data (Cameron, 2009). Consequently, qualitative analysis enriches quantitative findings by providing deeper insights and contextual understanding (Creswell and Clark, 2017).

This study divided the design into two sequential phases. In other words, the initial quantitative data provided a foundation for collecting subsequent qualitative data (Cameron, 2009; Isaacs et al. 2019). The first phase, focusing on quantitative analysis, involved statistical analysis using time-series econometric methods to assess the economic impacts of the event hosting from 2015 to 2023. This evaluation primarily examined the effects of B21 on the local economy, with a focus on income generated from tourism. In particular, this study hypothesises that the B21 would increase visitor participation and attract tourists, thereby boosting tourism revenue in the area. Building on the economic impact literature, this research hypothesises that: (1) the B21 event significantly increases tourism-related revenue, (2) the economic benefits are shaped by funding allocation and visitor spending patterns, and (3) inflation and employment dynamics influence the magnitude of these benefits.

Following the completion of the quantitative analysis, the authors conducted a second phase of qualitative analysis to support the findings from the first phase. Recognising that the lack of consistent local database collections in Thailand presents significant limitations, the authors sought to complement the secondary data analysis with primary data collection to enhance the reliability and robustness of the results. This was achieved through the administration of survey questionnaires to participants of the most recent B21 event.

Open-ended questions were developed to explore the spending behaviours of B21 participants during the 2023 event. The online open-ended questionnaire included screening questions, consent permissions, and questions about participants’ experiences at the B21 event in 2023. Additionally, participants were asked about their demographic profiles and the types of expenditure incurred, before and after the event.

By analysing this primary data, this study illustrated the spending patterns of B21 participants and the distribution of income within the local area. Additionally, the survey was structured to capture detailed information on spending behaviour, enabling an analysis of how the event contributed to the local economy. This primary data was instrumental in validating the findings from the secondary data analysis and providing a more holistic view of the event’s economic impact.

Data collection

Phase 1: Quantitative data collection

The quantitative data analysis involved the use of secondary data. The information was collected from the Office of the National Economic and Social Development Council, the Bank of Thailand, the Chonburi Provincial Office of Tourism and Sports, the Chonburi Statistical Office, the Office of Provincial Commercial Affairs Chonburi, Saensuk Municipality, and Mice & Communication.

To operationalise the study, the dependent variable was the income generated from tourism activities within Chonburi, serving as a key indicator of the event’s capacity to attract visitors and deliver economic benefits to local businesses. The independent variables, as detailed in Table 3, were selected to capture the factors influencing the economic dimensions of the event. The primary explanatory variable was the funding allocated for organising the B21 events, along with budget support from the government for other local activities. These investments in local events or activities beyond the B21 event can stimulate tourism by attracting more visitors to the area throughout the year.

Table 3 Dependent and independent variables.
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Additionally, the number of employed individuals in the province, the consumer price index (CPI), the number of tourists, total loans in Chonburi, and total deposits in Chonburi served as control variables. These additional variables accounted for other factors that might influence the dependent variable, aside from the main independent variables under study. Including control variables helps reduce bias and improve the accuracy of the estimated relationships.

The number of employed persons reflects the employment level within the local economy, offering insights into both economic vitality and tourism-generated revenue. When considering tourism income, increased employment in the target area can be viewed in two ways: first, as a benefit to the local economy, where higher employment levels mean more income is retained within the community; and second, as a cost component for tourism businesses. Employment data thus captures both an operational expense for the tourism sector and a measure of local labour market conditions. Additionally, it serves as a tool for identifying economic trends and supporting policies that foster sustainable local economic growth (Vuković et al. 2023).

The consumer price index reflects inflationary trends and the cost of living in Chonburi. An increase in the consumer price index may indicate rising costs of goods and services, potentially affecting both the spending behaviour of tourists and the profitability of local businesses. The number of tourists is directly related to tourism income, as an influx of visitors increases demand for local goods, services, accommodations, and hospitality.

The total volume of loans in the region serves as an indicator of local business activity and investment. A higher volume of loans suggests that local businesses—such as hotels, restaurants, and other service providers—are investing in capacity expansion or improvements to meet the growing demand from tourists. Lastly, total deposits provide an indication of the financial health and savings of both individuals and businesses in the region.

All variables in this study were presented as time-series data, collected monthly from January 2015 to December 2023, covering a total of 108 months.

Phase 2: Qualitative data collection

Qualitative data were purposively collected using multiple approaches from the end of September to November 2024 to investigate runners’ pre- and post-event spending behaviours. To be eligible for participation in the study, individuals needed to be over 20 years old, have attended the B21 event as a runner in 2023, and provide consent to participate in the research project. Ethical approval for the open-ended questionnaire was granted by the research ethics committee of the first author’s institution in September 2024.

In the initial attempt at data collection, participants in the 2023-B21 event were directly invited to complete the open-ended questionnaire via a Microsoft Form link. They were contacted through the event’s social media platforms, Instagram and Facebook, where researchers observed engagement between participants and the event organiser. A total of 99 participants were contacted, but the response rate was only 9.09%, with just nine questionnaires returned. This low response rate may be attributed to the high prevalence of financial scams in the country (Bangkok Post, 2024), which led many 2023-B21 participants to decline clicking on the link and avoid engaging in the conversation.

The second method involved directly contacting 2023-B21 runners via their social media accounts on Instagram and Facebook, using hashtags such as #Bangsaen21 and #Bangsaen21_2023. Data collection through hashtags enables the identification and utilisation of personal information for analysis, allowing researchers to examine public discourse related to specific themes on social media platforms (Chutiphongdech and Phengkona, 2024; La Rocca and Boccia Artieri, 2022). Hashtags serve as an effective tool for directly contacting individuals and evaluating consumer interaction with a company’s social media content (Omena et al. 2020). The response rate for this method was 28%, with 28 out of 100 individuals contacted responding. However, the data obtained lacked sufficient depth and contextual richness to construct meaningful research findings. Consequently, a third method of qualitative data collection was conducted with the assistance of the B21 event organiser.

As Mice & Communication Company Limited has its own direct communication channels with 2023-B21 runners, the questionnaire link was distributed through these channels. This approach yielded 618 responses. In total, 655 participants submitted questionnaires, of which 622 were deemed usable for further analysis. Thirty-three questionnaires were excluded because they did not pass the screening criteria, which included a lack of consent, non-attendance at the event, or incomplete responses.

Data analysis

Phase 1: Quantitative analysis

This study employed econometric time-series data analysis as its estimation method. This approach enabled researchers to identify trends, patterns, and causal relationships over an extended period. Each data point corresponded to the provincial level, specifically focusing on Chonburi, ensuring that the analysis remained localised and relevant to the specific economic context of the area. Before conducting econometric time-series data analysis, the authors performed statistical analysis to examine the causality, trends, and impacts of the event on each dependent variable, including the control variables. This preliminary analysis helped to uncover the underlying relationships and provides guidance for the subsequent econometric modelling.

However, the authors acknowledged that the event takes place only once a year in December, meaning the primary explanatory variable—the monetary budget invested in the event—had only nine data points within the 108-month time series. This created a potential limitation in the model due to the small number of data points for the event-specific variable. To address this issue, the study employed econometric methods to minimise potential estimation errors, including data transformation techniques to ensure model robustness. One key assumption of the least squares method is the variation in the independent variable (Gujarati, 2009). The authors aggregated the data from monthly to quarterly intervals to better capture the relationship between the explanatory and dependent variables. This approach helped to smooth out fluctuations and improve the reliability of the model’s estimations.

Phase 2: Qualitative analysis

This study employed descriptive analysis to provide an overview of the B21-2023 runners who participated in the study and adopted the thematic analysis framework outlined by Braun and Clarke (2006). This approach, later refined and labelled as reflexive thematic analysis (Braun and Clarke, 2019; Braun et al. 2019; Braun and Clarke, 2024), was used to guide the data analysis process. Reflexive thematic analysis allows researchers to engage reflectively with the collected data and the analytic process (Braun et al. 2019). This method emphasises the researcher’s active role in constructing knowledge (Braun and Clarke, 2019). Owing to its flexible nature, it enables the extraction of in-depth and intricate insights from the data (Chutiphongdech et al. 2024; Hallett and Lamont, 2015).

Prior to data analysis, key definitions and theoretical assumptions must be addressed to achieve theoretical sufficiency (Braun and Clarke, 2019; Byrne, 2022). This study was conceptualised within an interpretivist and constructivist paradigmatic framework, which has specific implications for thematic analysis (Byrne, 2022). This approach enables researchers to interpret qualitative data gathered from research participants, linking lived experiences to research phenomena (Oruh et al. 2021). By adopting this methodology, the study ensures that the interview data are both comprehensive and in-depth, thereby enhancing the trustworthiness of the data analysis process. While saturation may be beneficial for certain forms of thematic analysis, it holds limited utility and theoretical coherence in reflexive thematic analysis (Chutiphongdech et al. 2024; Vasileiou et al. 2018).

In this study, themes—defined as patterns of shared meaning (Braun and Clarke, 2021)—were developed from codes created through an inductive, data-driven process. This approach aimed to create codes that accurately reflect the substance of the data while also capturing an experiential orientation, prioritising the meaningfulness conveyed by research participants (Byrne, 2022). After assigning identification numbers to the research participants and familiarising them with the data, the authors identified and developed themes based on explicit codes articulated by participants at a semantic level. The coding process was conducted using Microsoft Excel, selected as a cost-effective data analysis tool. This approach facilitated the extraction of rich contextual insights directly from the participants (Hallett and Lamont, 2015).

Findings

Quantitative analysis

Since this study used time-series data, which is typically non-stationary and may have autocorrelation issues, the authors began by testing for autocorrelation using the Durbin-Watson d-statistic (equal to 1.782575), which indicated no autocorrelation problem. Next, the authors assessed stationarity, as non-stationary data can lead to spurious regression results and analytical errors. Determining stationarity was crucial for obtaining accurate results (Paparoditis and Politis, 2018; Singh et al. 2024).

The results of the stationarity test using the Augmented Dickey-Fuller (ADF) test are presented in Table 4. The test results indicated that several variables rejected the null hypothesis, confirming that they were stationary. These stationary variables included total funding used to organise the event, budget support from the government for other local activities, employment in Chonburi, and the consumer price index in Chonburi. Since these variables exhibited stationarity, they were directly used in further analysis.

Table 4 The results of Augmented Dickey-Fuller test.
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However, the test results failed to reject the null hypothesis for several other variables, indicating that they were non-stationary. These variables included tourism in Chonburi, the number of tourists in Chonburi, loans in Chonburi, and deposits in Chonburi. For the non-stationary variables, the researchers applied the first difference method to transform them into stationary variables. The first difference method is a common technique in time-series analysis to achieve stationarity by transforming non-stationary variables into ones with a constant mean and variance over time (Shumway et al. 2000). Once the variables became stationary, they were included in the subsequent analysis to ensure accurate and reliable results.

After adjusting all variables to achieve stationarity, the researchers applied a natural logarithm transformation to the variables to estimate the relationships using a double-log model, addressing cases where the relationship is nonlinear in parameters. Subsequently, the relationships were analysed using the method of minimising the sum of squared residuals, following the adjustment of the data to stationary variables. The results of the study are presented as follows:

The analysis began with testing for economic shocks by creating a dummy variable to indicate the presence of the B21 event (with the absence of the event as the baseline). The B21 event was coded as a dummy variable (1 = event occurs, 0 = event absent) to isolate its economic effect. This approach is commonly used in event impact studies to measure exogenous shocks in time-series models. This was followed by examining its impact on tourism in Chonburi, where the dependent variable was measured by income generated from tourism activities within Chonburi (in Thai baht: THB). The study found that the presence of the event significantly increased income from tourism in Chonburi, with statistical significance at the 99% confidence level. This indicates that the event acts as an effective economic shock, stimulating the flow of money in the tourism sector in the area. To elaborate, the B21 event functions as a localised economic shock by not only increasing tourism-related income but also stimulating multiple economic sectors. Beyond direct spending on accommodation and food services, the event drives demand for transportation, retail, and leisure activities, creating spillover effects that extend throughout the local economy. The result is presented in Table 5.

Table 5 The results of the economic shock from the B21 event.
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After determining that the B21 event can significantly impact the local economy, the next step was to examine how the budget invested in the event generated a flow of money in the tourism sector in the area. The budget investment was categorised into two variables: (1) total funding used to organise the event, which included investment from the B21 organiser, budget support from the government for B21, and budget support from B21 sponsors; and (2) budget support from the government for other local activities. These two variables were classified as key independent variables.

Additionally, this study included control variables in the model that were critical to the economic system in the Chonburi area, including employment, the consumer price index, the number of tourists, loans, and deposits. The results of the analysis are presented in Table 6.

Table 6 The results of the B21 event on tourism.
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The results revealed that all key independent variables have a positive and statistically significant relationship with the flow of money in the tourism sector in the area. This indicates that an increase in the budget allocated for organising the running event leads to greater circulation of money within the tourism sector.

When considering each key factor individually, it was found that a 1% increase in the total funding used to organise the event results in a 0.0468% increase in the flow of money in the tourism sector in the province, with statistical significance at the 90% confidence level. Conversely, a 1% increase in budget support from the government for other local activities leads to a 0.000000133% increase in the flow of money in the tourism sector in the area, with statistical significance at the 95% confidence level.

Additionally, when considering the influence from two perspectives—the magnitude of the effect and the level of statistical significance—it was found that the total funding used to organise the event has a larger impact, but a lower level of statistical significance compared to budget support from the government for other local activities.

Regarding the control variables that are significant economic factors, each can be explained as follows:

Starting with employment in Chonburi, it was found that employment in the area has an inverse relationship with income generated from tourism activities. This is due to the dynamics of total costs and total revenue, where businesses may face challenges in balancing labour costs with revenue generation. As a result, high employment does not necessarily equate to high income for the local economy.

The next factor is the consumer price index, which reflects the area’s inflation rate and is inversely related to income generated from tourism activities. According to standard macroeconomic theory (Mankiw, 2022), rising inflation erodes real purchasing power, subsequently reducing both domestic and inbound tourist spending. Higher prices for accommodation, food, and services may discourage travel and, in turn, lower total tourism revenue.

The number of tourists in Chonburi is positively correlated with income generated from tourism activities. This aligns with demand-side tourism economics, whereby an increase in visitor numbers typically drives aggregate spending in the local economy (Matias et al., 2011). A higher volume of tourists results in increased occupancy rates, restaurant patronage, shopping, and participation in recreational activities, all of which directly contribute to tourism revenue.

As for loans, they show a positive relationship with income generated from tourism activities. From a Keynesian investment perspective (Dillard, 2018; Keynes, 1937), an increase in loans may indicate improved access to capital for businesses, enabling expansion and enhancing service capacity and quality. Furthermore, greater credit availability can stimulate consumer spending, both among local residents and visiting tourists, thereby further boosting tourism revenue.

Finally, the number of deposits, which constitutes part of the local money supply, is positively correlated with income generated from tourism activities. An increase in deposits reflects stronger household and business savings and liquidity, which can enhance consumer confidence and support future spending. From a monetary transmission perspective, higher deposit levels may also expand lending capacity, thereby reinforcing investment and stimulating economic activity, particularly in service-oriented sectors such as tourism.

Qualitative analysis

To further supplement the quantitative findings, this section presents the qualitative data analysis collected from the 2023-B21 runners. It includes a descriptive analysis of the demographic profiles of research participants and the spending patterns of B21 runners. This section provides supporting evidence and insights into B21 participants’ spending behaviours and their financial contributions to the local area, enabling an analysis of the event’s economic impact.

Demographic profiles of participants

As seen in Table 7, the B21 event attracts a diverse group of participants with varying demographic characteristics, geographical origins, and experiences. The demographic profile of the participants is particularly noteworthy, reflecting significant variation in terms of gender, age, education, income, geographical distribution, and event experience.

Table 7 Demographic profiles of 2023-B21 participants.
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Nearly three-quarters of the participants were male, accounting for 71.22% (443 participants), while approximately 27.33% were female. A very small proportion, 0.48%, identified as LGBTQ or non-binary. Participants ranged in age from 22 to 72 years, with an average age of 52.38, indicating broad generational representation with a notable concentration among older age groups.

In terms of educational background and income levels, the most common qualification among attendees was a bachelor’s degree, held by 56.43% of participants, while those with postgraduate qualifications accounted for 25.72%. This finding indicates that the majority of participants are well-educated. Participants’ income levels displayed significant variation. The largest groups reported earning between 20,001–30,000 THB (16.40%) and 40,001–50,000 THB (15.27%), while 10.77% of participants reported earning over 100,000 THB per month, highlighting the event’s strong appeal among middle- to high-income participants.

Table 8 and Fig. 2 illustrate the geographic distribution of the 2023-B21 runners. As shown in Fig. 2, a deeper colour intensity indicates a higher concentration of participants from a given province. The majority of participants were based in the Central region, accounting for 58.36%, with most residing in Bangkok (33.76%). A significant proportion of participants also came from the Eastern region (32.64%), with Chonburi contributing 21.70%. Other regions, such as the North (1.45%) and the Northeast (4.34%), made relatively smaller contributions.

Table 8 Distribution of participants’ location across regions of Thailand.
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Fig. 2
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Distribution of participants’ location across regions of Thailand.

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Finally, in terms of event involvement, the majority of participants were returning attendees, with 57.88% having joined on 1–3 occasions and 31.67% having participated in 4–6 events. Only 3.38% were new participants, as seen in Table 9. This finding reflects a strong retention rate and a loyal participant base.

Table 9 Participants’ experience with Bangsaen21.
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The demographic profile of B21 runners indicates that most participants in the 2023 event had previously taken part in earlier editions. The event attracted runners from various regions across Thailand, spanning a wide age range. Most participants were well-educated and belonged to middle- to high-income groups, reflecting the presence of quality tourists likely to contribute economically to the area.

Spending behaviours of B21 runners

The findings from the descriptive analysis revealed that the majority of 2023-B21 runners, approximately 62.7%, travelled while participating in the event. Conversely, 37.3% indicated that they did not travel while attending the event. However, most of the 37.3% reported incurring expenses related to accommodation and transportation, while 2.57% reported not spending anything, as shown in Fig. 3.

Fig. 3
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Spending patterns of 2023-B21 runners.

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The findings from most research participants revealed that 62.06% stayed at least one night in Chonburi, as shown in Table 10. Accommodation expenses ranged from a maximum of 8000 THB per night to zero, the latter reflecting participants who stayed with friends, parents, or relatives or opted to sleep in their cars. The longest recorded stay was 7 days, while 16.72% of participants did not stay overnight at the destination.

Table 10 Overnight patterns of 2023-B21 runners.
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To provide insight into runner spending behaviours, the reflexive thematic analysis identified four themes that represented different types of runners with diverse spending behaviours and patterns, as presented in Table 11. The majority, accounting for 66.27%, were classified as ‘Run-Life-Balance Runners.’ This category reflected individuals such as accommodation, food, souvenirs, and other goods and services. Some of these runners spent money before the event, while others incurred expenses both before and after their participation.

Table 11 Overview of different types of 2023-B21 runners according to reflexive thematic analysis.
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Some insights from the Run-Life-Balance Runners highlighted their enjoyment of the event and their travel experience:

‘It was a big running event close to home, with a great atmosphere along the route. In December, the weather started to cool down, making it was not too hot. We can also take the kids to play in the sea while we ran.’ (ID.111)

‘Before the event, I looked for delicious restaurants to try. After the event, I searched for seafood restaurants, as it’s a national running event and a great opportunity to enjoy local cuisine.’ (ID.152)

‘Booked accommodation the day before the run and stayed after the run to continue travelling. Accommodation for 3 nights, souvenirs, and meals for 4 days. Planned to buy souvenirs to bring back. 2100 THB per night for accommodation, with daily expenses ranging from about 1000–1500 THB for 2 people, possibly reaching 2000 THB per day. Bought many souvenirs, such as clothes, running gear, and items from tourist spots and cafés. […] You can continue to relax, with plenty of food options available in Bangsaen.’ (ID.185)

The second category consisted of runners who indicated that they did not travel, accounting for 37.3% of the total. This category could be further divided into three sub-groups: the No-Travel-But-Stay Runners, the No-Travel-No-Stay-But-Pay Runners, and the I-Come-Here-For-Run Runners.

The No-Travel-But-Stay Runners represented individuals who reported no tourism-related activities but incurred other expenses within the province, such as accommodation and food. This group accounted for 25.4% of all runners who participated in the survey. Some insights from participants revealed their activities after the event:

‘I came to run because the event had a good standard of organisation and high safety. It was easy to find accommodation, and you can visit the beach before and after the run.’ (ID.18)

‘I didn’t go on a trip. I just walked around the dolphin roundabout and the area near Bangsaen Beach. That was already very nice.’ (ID. 65)

‘Got to eat seafood, relax after running, bored with Bangkok, came to drive along the seaside.’ (ID.539)

While the No-Travel-No-Stay-But-Pay Runners included those who reported no tourism or accommodation expenses, they did incur some costs related to food or goods within the province. This group made up 9.32% of runners who reported no tourism. Some insights from participant highlighted their spending on food, transportation, and souvenirs:

‘After finishing the Bangsaen21 event, I didn’t go out, but I had a meal with friends and went to a café.’ (ID.17)

‘I liked this event […]. The cost of purchasing items at the running event and travel expenses was about 300 baht.’(ID.555)

‘I liked the Bangsaen21 event because of its management standards, it was not far from home, and I got food souvenirs after the run.’ (ID.560)

Finally, the I-Come-Here-For-Run Runners comprised 2.57% of participants. This group consisted of individuals who reported no tourism-related activities and no spending before or after the event. Unsurprisingly, most of the runners in this category resided in Chonburi and noted that the B21 event was conveniently located near their homes. Some participants shared their insights for participating in the event:

‘No travel. If I didn’t go to the Bangsaen21 event, there was no reason to go to Chonburi province.’ (ID.7)

‘I came here because I wanted to run. The event was close to home, the atmosphere was good, and it was fun.’ (ID.194)

‘I wanted to run for health and participate in a well-organised running event in a residential area.’ (ID.618)

In terms of attractions and tourism activities, the word cloud analysis based on keywords provided by the runners identified Bangsaen Beach, Ang Sila, Khao, Wonnapha Beach, Pattaya, the Fish Market, and Sriracha as the most popular attractions that runners intended to visit as seen in Fig. 4. The associated tourism activities included visiting cafés at these destinations, dining at seafood restaurants, going to the beaches, and shopping at local markets. Some participants shared additional insights about their experiences:

‘B21 was conveniently located near Bangkok. There were many restaurants and cafés, and all the food was delicious.’ (ID.66)

‘I really liked the Bangsaen21 because, after running many marathons, none can compare to Bangsaen21. After the run, you can also continue your trip to Pattaya.’ (ID.164)

‘[…]. I also came to try the food at various restaurants, visit cafés, go to coffee shops, buy pet food, and get souvenirs to take home.’ (ID.425)

Fig. 4
figure 4

The most common attractions and activities among 2023-B21 runners.

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Discussion

This empirical study contributes to the impact assessment literature in sport event management research. While the majority of past studies have predominantly employed quantitative analyses at the national or macroeconomic scale (Zourgani and Ait-Bihi, 2023; Yüksel and Ön, 2024), this study supplements these findings by evaluating the economic impact at the micro level—specifically, in terms of provincial economic development using the B21 at Chonburi, Thailand, as a case study. An explanatory sequential mixed-methods approach was utilised to provide qualitative insights that support the quantitative analysis.

In the first stage of quantitative analysis employing econometric time-series techniques, this study revealed statistically significant effects of hosting the event on the local economy. This was evidenced by an influx of money into the province’s tourism sector, driven by both the budget allocated for hosting the event and other factors contributing to increased tourism revenue in the province. As seen in Fig. 5, it illustrates the income generated from tourism activities in Chonburi alongside quarterly time data. Notably, during the fourth quarter—when the event occurs (indicated by red dots on the graph)—a slight increase in income is observed compared to the third quarter. While the fourth quarter is typically a high season for tourism, this period also coincides with Thailand’s winter season (Chen and Pearce, 2012; Fakfare et al. 2022; Tangtammaruk et al. 2024), during which many Thais prefer visiting the mountainous regions in northern Thailand rather than seaside destinations like Chonburi (Chen and Pearce, 2012). Despite this, the B21 event stimulates travel to Chonburi, drawing participants to the area and boosting monetary circulation within the local tourism sector.

Fig. 5
figure 5

The income generated from tourism activities within Chon Buri per quarter (Million THB).

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The current results align with previous studies on the economic impacts of small-scale sporting events. For instance, Davies (2002) examined the economic impact of sporting events at the local level in Sheffield and highlighted the value added by sporting events. Similarly, Gelan (2003) estimated the local impacts of the 1999 British Open held at Carnoustie, reporting that local goods purchased by visitors significantly contributed to the local economy. Wilson (2006) explored the economic impact of local swimming events in the UK and found that the additional spending at such events was largely determined by the number of attendees.

Furthermore, the findings of this research indicate that an increase in the budget allocated for organising the running event leads to a greater circulation of money within the tourism sector. These results are consistent with studies by Duglio and Beltramo (2017), Salgado-Barandela et al. (2021), and Solberg and Preuss (2007). Additionally, they align with the concept of the expenditure multiplier in macroeconomic theory, as discussed by Wang et al. (2010).

Although the current findings report that the impact of the budget allocated for organising the B21 event is modest compared to other contributing factors, the results further indicate that the total funding for the event provides a slight stimulation to tourism income. This demonstrates that investment in such events can serve as an effective policy tool for boosting local economies. Hosting a running event acts as a financial injection into the area, increasing the circulation of money within the economic system, particularly in the tourism sector in Chonburi. Nonetheless, other factors—such as the overall number of tourists, loan availability, and regional deposits—play a more significant role in driving tourism income.

The economic impact of the B21 event can be categorised into short-term and long-term effects. In the short term, the event provides a financial boost by attracting tourists and increasing spending on accommodation, food, and local businesses. This immediate surge in economic activity is reflected in the rise in tourism-generated income during the event period. However, sustaining these benefits requires ongoing investment in event infrastructure and marketing.

The long-term economic effects of the B21 event depend on its ability to enhance Chonburi’s appeal as a destination, attracting repeat visitors beyond the event period. When leveraged strategically, the event can contribute to sustained tourism growth and local business development, similar to the long-term benefits observed in other globally recognised sporting events (Wilson, 2006; Gelan, 2003).

A key challenge in isolating the event’s impact is the influence of seasonal tourism patterns. The B21 event takes place in December, a peak tourism season in Thailand. While the data indicate a direct positive effect on local tourism revenue, part of this increase may be attributed to the natural rise in tourist numbers during this period. Future research could employ counterfactual analysis to better distinguish the event’s specific contribution from broader seasonal trends.

The second stage, a qualitative analysis, corroborated the quantitative findings. While the first-stage quantitative analysis confirmed that hosting the B21 event significantly impacts Chonburi’s local economy by injecting money into the province’s tourism sector, the second-stage qualitative analysis reinforced these findings. It confirmed that nearly all participants spent their money in the area, contributing to local economic development.

In particular, the data revealed that the event attracted runners who were predominantly well-educated and represented diverse income ranges. These participants significantly contributed to the local economy through their spending. A survey using open-ended questions found that approximately 97.43% of participants spent money in the area. Of these, 67.2% reported expenditures on tourism-related activities, identifying as sport event tourists—a segment considered to be high-quality tourists (Dixon et al. 2012; Jeong and Kim, 2020; Mortazavi, 2021; Roche et al. 2013). Meanwhile, 34.72% mentioned spending on items such as food and beverages, sports-related products, and souvenirs. Only 2.57% of participants reported spending no money in the area beyond the event participation fees.

As highlighted in previous literature (Duglio and Beltramo, 2017; Kwiatkowski and Oklevik, 2017; Walo et al. 1996), event participants are a crucial component in generating additional expenditure for the host economy, particularly at the local level. Therefore, these qualitative insights strongly support the quantitative findings, affirming that hosting the B21 event plays a pivotal role in fostering local economic development.

Furthermore, the analysis highlights the significant negative impact of the consumer price index (CPI), emphasising the detrimental effect of inflation on tourism spending. Inflation poses a key limitation to the net economic benefits of the event, as the increased demand for goods and services during the event may drive up local prices, offsetting gains in tourism revenue. The CPI analysis in this study confirms this effect, showing a negative correlation between rising inflation and tourism income. Consequently, it is crucial for policymakers to implement price stabilisation or inflation-targeting strategies to mitigate these challenges, addressing concerns not only at the macroeconomic level but also within the local economy.

Additionally, the quantitative analysis also reveals a negative relationship between employment and tourism income, which can be interpreted from two perspectives:

  • Cost-revenue perspective: While increased local employment boosts household income and stimulates economic activity, it also raises operational costs for businesses, as labour is a key component of production (Pindyck and Rubinfeld, 2018). These higher costs may offset revenue gains in the tourism sector, potentially leading to a decline in overall tourism income (Liu and Wall, 2006).

  • Seasonality in tourism employment: Tourism jobs are often seasonal or part-time, meaning that revenue peaks during high-demand seasons do not necessarily lead to sustained employment growth (Ashworth and Thomas, 1999; Jolliffe and Farnsworth, 2003). This seasonality results in revenue fluctuations driven by tourist demand, while consistent employment growth may not follow, leading to inconsistencies in the relationship between employment and income levels throughout the year.

Conclusion

Theoretical contributions

Given the economic advantages of sporting events at both national and local scales, many countries opt to host such events. However, much of the existing literature focuses on large-scale events with the aim of assessing their economic impact at the macro level. In contrast, sporting events that contribute to local economies have received comparatively less attention, and there remains a lack of in-depth research to inform policymakers. This gap is largely due to the predominant reliance on quantitative research designs in past studies, limiting a comprehensive understanding of localised economic impacts.

This study bridges this gap and provides methodological insights by examining provincial economic growth using the Bangsaen21 Half Marathon in Chonburi, Thailand, as a case study. Employing an explanatory sequential mixed-methods approach, the study demonstrates that the event plays a significant role in fostering local economic development. This stems from budgeting invested in the area, the spending behaviours of event participants as sport event tourists, and other factors that generate tourism revenue in the region. This study concludes that organising events like the Bangsaen 21 significantly boosts tourism-related income in the area.

Practical implications

To provide actionable insights for policymakers and stakeholders in sport event management, the findings suggest that government expenditure on organising local sporting events can serve as an effective mechanism for stimulating tourism-related income. Policymakers should therefore support and promote such events as valuable economic drivers, particularly in diverse contextual settings where the potential exists to attract sport tourists. Furthermore, regularly hosting specific types of sporting events that align with the local environment during off-peak seasons may help balance income flows and mitigate seasonal fluctuations in tourism demand.

By providing financial support for events such as mid-year endurance races or adventure sports, governments can help distribute tourism income more evenly throughout the year. This diversification would reduce economic dependence on a single annual event and create a more consistent revenue stream. Additionally, fostering partnerships between event organisers and local businesses—such as hotels, restaurants, and retail outlets—through discount programmes or official sponsorship agreements can promote more equitable revenue distribution and support small business growth.

Based on the empirical findings, this study recommends that local authorities support tourism-related businesses through financial incentives, including low-interest loans and tax relief measures. Marketing strategies should prioritise targeted digital campaigns aimed at attracting health-conscious and international tourists. Additionally, extending the event into a multi-day festival featuring local markets and cultural showcases could encourage greater tourist spending. Public-private partnerships should also be fostered to finance infrastructure and service enhancements. Finally, price monitoring during the event period is essential to mitigate inflationary pressures and preserve affordability for visitors.

The analysis also highlights the significant negative impact of the consumer price index. While events such as the Bangsaen21 Half Marathon generate clear economic benefits, tourism policies should prioritise maintaining price stability, encouraging financial investment, and attracting more tourists to maximise Chonburi’s economic advantages. To mitigate inflationary effects, temporary price regulations or subsidised incentives for local businesses—such as capped hotel pricing agreements and transportation vouchers—could be introduced.

While this study confirms the short-term economic benefits of hosting the Bangsaen21 event, its long-term impact on tourism and local development must also be considered. The B21 event has the potential to position Chonburi as a key sport tourism destination, attracting repeat visitors beyond race day. When leveraged strategically, it can enhance destination branding, leading to increased annual visitor numbers and higher long-term tourism revenue. The economic benefits of the event could justify greater public and private investment in tourism-related infrastructure. Enhancements in transportation networks, accommodation facilities, and public amenities would not only improve the event experience but also contribute to long-term regional development, benefiting both residents and future visitors. As evidenced by several studies (as in Chutiphongdech and Kampitak, 2022; Jeong and Kim, 2020; Kim et al. 2014; Wilson, 2006), sporting events play a significant role in building a destination’s image. Well-managed events that balance stakeholder benefits can enhance the value and legacy of the host location, creating long-term positive impacts for the community.

Furthermore, policymakers should address societal and environmental issues associated with event hosting. Effective event planning, supported by public policies, is essential for balancing the benefits and challenges of such events and ensuring sustainable development for the province. A strategic approach to event management can help navigate these competing priorities. This includes ensuring that investments in event-related infrastructure serve long-term community needs, implementing sustainable practices to minimise environmental impact, and ensuring that local communities benefit from sporting events to foster social cohesion and minimise societal disruptions. However, successful policy implementation requires active engagement with stakeholders across the event ecosystem. A comprehensive strategic approach to event management will not only leave a lasting legacy but also create long-term benefits and value.

Although this study makes notable academic contributions to the sport event management literature, several limitations should be acknowledged. First, the availability of data in Chonburi was limited and may not fully capture all relevant variables, potentially leading to omitted variable bias. Much of the data provided by government agencies is available only at the national level, with limited granularity at the provincial level, which constrained the ability to obtain comprehensive local data. Second, future research should consider employing monthly rather than quarterly data to better detect potential lagged effects of the event. In this study, such lag effects could not be tested due to data and model constraints, and this has been recognised as a limitation.

Specifically, this study lacks empirical data on individual visitor spending, pre- and post-event economic activity, and changes in business revenue during the event period. Moreover, the study covers only a limited period, potentially overlooking the long-term effects of the event on tourism. Additionally, the prevalence of scammers in the country posed challenges for qualitative data collection, limiting opportunities for two-way communication between researchers and participants. To address this data limitation in future investigations, it is recommended to implement structured surveys to collect primary data on individual visitor spending, categorised by sectors such as accommodation, food, and shopping during the event. Additionally, conducting in-depth analyses of local business financial records can help quantify changes in revenue and employment levels associated with the event.

To advance this research domain, the study encourages scholars in the field to investigate local sporting events further and elaborate on qualitative findings, addressing the current scarcity of in-depth research in event impact assessment, which has predominantly relied on quantitative analyses. Incorporating qualitative data collection methods involving interactive conversations with participants could yield more insightful and nuanced results, enriching the research field.