RMUTI Journal Humanities and Social Sciences

Impact of Production Factors on the Competitiveness of the Service Industry in Thailand

Pongyooth Glayooth, Pakarat Jumpanoi — Tue, 30 Jun 2026 00:00:00 +0700

This study investigates the impact of production factors on the competitiveness of Thailand’s service industry, aiming to examine the relationships among key inputs and their influence on competitiveness. Multiple regression analysis was employed, with capital (CAP), labor (LAB), average wage (WAGE), and technology (TECH) as independent variables, and competitiveness (COMP) as the dependent variable. This research utilizes secondary time-series data comprising 32 annual observations from 1993 to 2024. The LAB variable was sourced from the Ministry of Labor, CAP and COMP from the National Economic and Social Development Council (NESDC), and WAGE from the Bank of Thailand. TECH was calculated using the Solow residual method based on Total Factor Productivity (TFP), allowing for a more precise estimation of technological impact. The findings indicate that capital and average wage are positively and statistically significantly associated with competitiveness in the service sector. Accordingly, the government should promote capital formation through measures such as tax incentives, low-interest financing, and infrastructure development and oversee the adjustment of the labor compensation structure to ensure appropriateness to enhance sustainable competitiveness over the long term. In contrast, labor exhibits a statistically significant negative effect, which may reflect issues related to low labor productivity or mismatches between workforce skills and market demand. Therefore, policy efforts should prioritize reskilling initiatives, digital skills training, and strengthened vocational education to improve labor quality. Although, technology does not demonstrate a statistically significant relationship with service sector competitiveness in this analysis, it remains theoretically important. Policymakers should thus continue to support technological adoption in the service sector particularly automation, artificial intelligence, and data-driven systems to foster long-term innovation and efficiency.

The Role of Social Media Advertising Value and Technology Acceptance Influence on Purchasing to Supplementary Food Product Through Online Channel of Young Elderly

Wasutida Nurittamont, Sornnarin Leehuad, Kanchanawadee Samleete — Tue, 30 Jun 2026 00:00:00 +0700

The objectives of this study were to investigate the influence of social media advertising value on the purchasing to supplementary food product through online channel of young elderly and to examine the impact of technology acceptance on the purchasing to supplementary food product through online channel of young elderly. Online questionnaires were used to collect data from 395 participants, employing non-probability sampling through convenience sampling method. The data analysis included descriptive statistics such as percentage, frequency, average, and standard deviation. Hypothesis testing was conducted using multiple regression analysis with the Enter method. The results revealed that advertising on social media, particularly in terms of entertainment, informativeness, and credibility, positively influences the intention to purchase online of young elderly. Additionally, technology acceptance, particularly perceived usefulness, has a positive effect on the intention to purchase online of young elderly. Therefore, the findings of this study can serve as guidelines for promoting the development of marketing communications tailored to the needs and behaviors of young elderly using technology.

Participation in Group Management and Product Innovation Affecting the Success of Community Enterprise Operations in Lampang Province

Daoduean Inteacha — Tue, 30 Jun 2026 00:00:00 +0700

This research aims to study the participation in group management and product innovation that affect the success of community enterprise groups in Lampang Province. This is a quantitative research. The sample group is 315 community enterprise groups in Lampang Province. The research method used was probability sampling. The research tools were questionnaires. The statistics used for data analysis were frequency, percentage, mean, standard deviation, and multiple regression analysis. The study results found that 1) group management participation was at a high level, with the greatest importance given to participation in planning to determine development guidelines. Product innovation is at a high level, with the greatest importance given to customer satisfaction surveys. In terms of operational success, it is at a high level, with an emphasis on collaboration and unity. 2) Product innovation has a statistically significant influence on operational success at the 0.05 level. While group management participation does not directly influence the success of community enterprise groups, the success of community enterprises in Lampang Province depends more on product innovation than on group management participation.

The Relationships between Perceived Value, Tourist Satisfaction, and Intention to Travel of Tourists in Nakhon Phanom, Thailand

Tue, 30 Jun 2026 00:00:00 +0700

This research aims to examine the relationship between perceived value, tourist satisfaction, and intention to travel of tourists visiting Nakhon Phanom. It focuses on analyzing the effects of perceived value on tourist satisfaction, as well as intention to travel in terms of revisit intention and recommendation of tourist attractions to others. The sample group consists of 400 Thai tourists aged 18 years and above who travel to and stay overnight in Nakhon Phanom. The research instrument is a questionnaire developed based on the perceived value framework. This study employs PLS-SEM
statistical analysis to examine causal relationships. The results reveal that perceived value in all dimensions has positive effects on tourist satisfaction. Furthermore, economic value and cultural value have positive effects on intention to travel. In addition, tourist satisfaction has a positive effect on intention to travel. These findings indicate that enhancing the perceived value that tourists can recognize is an important factor for the sustainability of the provincial tourism industry and
serves as in-depth information for formulating policies and strategies to develop tourist attractions that effectively and sustainably meet tourists’ needs.

Service Quality Factors Influencing Passenger Satisfaction and Repeat Usage Behavior: A Case Study of Phra Nakhon Si Ayutthaya Railway Station

Tue, 30 Jun 2026 00:00:00 +0700

This research aims to analyze 1) the influence of service quality on passenger satisfaction, 2) the influence of satisfaction on repeat usage behavior, and 3) the influence of service quality on repeat usage behavior among passengers at Phra Nakhon Si Ayutthaya Railway Station. This quantitative study collected data from 400 railway service users through convenience sampling. The research instrument employed was a questionnaire. Data analysis utilized frequency, percentage, mean, and
standard deviation, along with multiple regression analysis. The research findings revealed that 1) service quality has a positive influence on passenger satisfaction (Adjusted R² = 0.582, p<.001), with tangibility (β = 0.051), reliability (β = 0.039), assurance (β = 0.056), and empathy (β = 0.059) showing significant effects at the 0.01 level, while responsiveness showed no clear influence (p = 0.188); 2) passenger satisfaction positively influences repeat usage behavior (β = 0.029, Adjusted R² = 0.594, p<.001); and 3) all five dimensions of service quality—tangibility (β = 0.043), reliability (β = 0.033), responsiveness (β = 0.033), assurance (β = 0.047), and empathy (β = 0.050)—directly and significantly influence repeat usage behavior (Adjusted R² = 0.663, p<.001). These findings indicate that developing service quality and creating satisfaction are critical strategies for enhancing repeat usage behavior among railway passengers.

The Relationship Between AI Risk and Compliance Disclosure and Firm Value: Evidence from Listed Companies in Thailand’s SET100

Aukkaradej Chaveerug — Tue, 30 Jun 2026 00:00:00 +0700

This research aims to examine the effects of Artificial Intelligence Risk Disclosure (AI Risk Disclosure) and Artificial Intelligence Compliance Disclosure (AI Compliance Disclosure) on the firm value of listed companies in the SET100 of the Stock Exchange of Thailand. The study covers 92 companies with a total of 276 observations between 2022 and 2024, using a quantitative research approach. Data were collected from annual reports and AI disclosure reports and analyzed using descriptive statistics, correlation analysis, and multiple linear regression. The findings indicate that both AI Risk Disclosure and AI Compliance Disclosure have a significant positive relationship with firm value, and the simultaneous disclosure of both aspects leads to the highest increase in firm value. Among the control variables, firm size and profitability positively affect firm value, whereas high leverage has a negative effect. In conclusion, comprehensive, transparent, and balanced AI disclosure enhances investor confidence, reduces uncertainty in investment decisions, and increases firm value, providing clear benefits for managers, investors, and market regulators.

The Influence of Lifestyle Destination Tourism on Tourist Experience: The Mediating Role of Novelty Seeking in Song Wat Road, Bangkok

Tue, 30 Jun 2026 00:00:00 +0700

This study aimed to (1) examine the influence of lifestyle tourism on novelty seeking and tourism experiences, (2) analyze the influence of novelty seeking on tourism experiences, and (3) investigate the mediating role of novelty seeking between lifestyle tourism and tourism experiences. The research was conducted using a case study of Song Wat Road, Bangkok. The sample consisted of 347 tourists who had previously visited the area. Data were collected using a questionnaire verified for content
validity with an item-objective congruence (IOC) index ranging from 0.80 to 1.00, and an overall reliability coefficient of 0.95. The data were analyzed using descriptive statistics, confirmatory factor analysis (CFA), and structural equation modeling (SEM) with JAMOVI software. The results revealed that lifestyle tourism had a significant positive effect on novelty seeking (β = 0.897, p<0.001) and tourism experiences (β = 0.981, p<0.001). Novelty seeking also positively influenced tourism experiences (β = 0.950, p<.001) and partially mediated the relationship between lifestyle tourism and tourism experiences (β = 0.853, p<0.001). These findings indicate that destinations designed to align with tourists’ lifestyles and preferences can stimulate curiosity, enhance engagement, and create more profound and memorable experiences. Such experiences ultimately foster satisfaction and revisit intentions among tourists,
contributing to sustainable destination development.

Lessons Learned from MICE Communities: A Pathway to Sustainable Destinations through the BCG Economy Model

Wisakha Phoochinda, Paron Vongchan, Nicharnan Patitas, Peeraya Vajrodaya — Tue, 30 Jun 2026 00:00:00 +0700

This research aims to draw lessons from the operations of pilot MICE tourism communities and analyze their success factors to propose strategic guidelines for sustainable development based on the BCG Economy Model. This study employs a qualitative approach through documentary research. Ten pilot communities in five designated MICE Cities were selected via purposive sampling as case studies. The researcher utilized Thematic Analysis to synthesize data by coding MICE operations, classifying codes to identify success patterns across areas, and crystallizing them into three main themes: MICE Product, MICE Management, and MICE Marketing Promotion. The findings indicate that while each community possesses distinct product characteristics based on its local context such as Wellness MICE in Chiang Mai or Eco-MICE in Surat Thani, there are three key common success factors: 1) the possession of a unique and distinctive MICE product; 2) a strong management mechanism supported by a mentoring agency; and 3) a clear capability to link with target markets within the MICE industry. Based on these analyses, the researcher proposes four strategic guidelines for sustainable development: developing BCG-driven products, upgrading human capacity with sustainability literacy, creating marketing channels that emphasize sustainability, and building collaborative networks within the BCG ecosystem.

Effects of Psychological Barriers to E-payment on Alternative Attractiveness and Intention to Use: A Conceptual Framework

Tue, 30 Jun 2026 00:00:00 +0700

Despite technological advances in electronic payment (e-payment) systems and their increasing relevance in modern economies, many consumers, especially in countries like Thailand, remain hesitant to adopt these innovations. This conceptual model emphasizes the necessity of addressing these psychological barriers, especially traditional and image barriers to E-payment on alternative attractiveness and intention to use by presenting an innovation resistance theory that interlinks psychological resistance, alternative attractiveness, and intention to use. Finally, the findings are intended to inform not only academic debates but also strategic practices for both fintech innovators and policymakers seeking to drive inclusive digital transformation, and it offers recommendations for research design aimed at facilitating and accelerating the adoption of electronic payments as a mainstream payment modality in the future.

Marketing Strategies for the Transportation Business Driven by Generative AI

Peravich Singkhala, Chalearmkiart Feongkeaw — Tue, 30 Jun 2026 00:00:00 +0700

This article aims to propose marketing strategies for the transportation business driven by Generative AI as transportation business plays a crucial role in economy and life, serving as a key component in connecting people, markets, and resources worldwide. It provides services related to the movement of goods, passengers, and raw materials from one place to another. The challenge for running business nowadays is to adapt and build competitiveness by integrating modern technologies and innovations, such as Generative AI, into its operational processes. However, the competition in the market requires effective marketing strategies, which act as operational plans that businesses deploy to attract customers and increase sales. For these reasons, marketing strategies for the transportation business driven by Generative Artificial Intelligence (Generative AI) encompass four key components: 1) Generative AI Driven Marketing and Business, 2) Customer Segmentation, 3) Personalized Marketing, and 4) Media Optimization. These components are critical variables requiring business to prepare and intelligently adopt Generative AI within the context of evolving challenges and transformations in the modern world. Such readiness will enable business to navigate the increasing influence of this technology on its operations in the future.