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Corporate Social Responsibility and Financial Performance in the Chinese Pharmaceutical Sector: The Roles of Technological Innovation and Media Coverage
(2025-04-01)
Wang, Jin
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Chaveesuk, Singha
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Keerativutisest, Vasu
The pharmaceutical industry has been developing rapidly in recent years, and concerns have been widely raised about social responsibility for the safety of people’s lives. This research aims to investigate the impact of CSR on CFP of listed pharmaceutical companies in China. This study was based on the data of pharmaceutical listed companies from 2010 to 2020 as a sample and built regression models for the effects of pharmaceutical corporate social responsibility (CSR) on corporate financial performance (CFP) based on the indirect effects of technological innovation and media coverage. The two-way fixed effect method, the systematic generalized method of moments estimation (SYS-GMM), and the Bootstrap method are adopted for the regression analysis of the model. The research found that (1) CSR positively affected CFP; (2) CSR positively affected technological innovation, while technological innovation partially mediated between CSR and CFP; and (3) both positive and negative media coverage negatively moderated the relationship between CSR and CFP as well as the relationship between CSR and technological innovation. In addition, both positive and negative media coverage negatively moderates the mediation path of “CSR–corporate innovation–CFP”.
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Enhancing Chatbot Service User Satisfaction
(2025-01-01)
Promsiri, Triyuth
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Wuittipappinyo, Naruemol
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Keerativutisest, Vasu
Chatbots play an essential role in enhancing automated customer support experiences, with the global chatbot market estimated to reach $142 billion in 2024. Despite this growth, limited research addresses the factors influencing user satisfaction with chatbot services. Drawing from the literature on service and information quality, this study investigates how these factors impact chatbot service user satisfaction (CSUS). It hypothesizes that service quality (SQ) and information quality (IQ) are significant predictors of CSUS and that demographic variables like age may influence satisfaction levels. A survey of 385 Thai chatbot users were surveyed concerning their online service opinions, from which the data were analyzed using ANOVA and multiple regression. Results confirmed that both SQ and IQ significantly enhance CSUS. Additionally, age was a significant factor, with younger users (21-30 years) reporting higher satisfaction than older groups. These findings highlight the importance of delivering timely, accurate, and reliable information while ensuring visually appealing and user-friendly chatbot designs. The study underscores the need for businesses to adapt chatbot communication strategies to demographic preferences and to prioritize continuous updates and personalization. Future research should explore other potential influences, such as chatbot personality traits, perceived benefits, and cultural variations.
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DETERMINANTS OF AI-BASED APPLICATIONS ADOPTION IN THE AGRICULTURAL SECTOR – MULTI-GROUP ANALYSIS
(2024-01-01)
Keerativutisest, Vasu
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Chaiyasoonthorn, Wornchanok
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Khalid, Bilal
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Ślusarczyk, Beata
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Chaveesuk, Singha
This research investigated the factors determining the adoption of AI-based applications in Thailand and Poland’s agricultural sectors. The study explored the sector’s adoption of AI technology and its contributions to driving the market and business performance. Despite the potential of AI in the agricultural sector, its adoption rate still needs to be clarified, and its potential needs to be better understood, hence the need for the study. The research applied primary data collected from respondents working in the agricultural sector in Thailand and Poland using a structured questionnaire. A sample of 356 and 377 respondents were representative samples in Thailand and Poland, respectively. The research was driven by the hypotheses evaluated using the Structural Equation Model (SEM). The findings indicated that organizational size was the most influential determinant of AI-based applications in both countries. Another significant determinant was technological competence in both countries. Additionally, social influence was a significant determinant in Thailand, while facilitating conditions and effort expectancy were significant determinants in Poland. The multi-group analysis revealed that the two countries were not invariant; hence, the effect of independent variables on behavioral intention to adopt AI between the two countries was different. The research recommended that each country’s policymakers consider its contexts differently in AI-based application adoption policies. However, improving the organizational size and technological competence would enhance the adoption of AI-based applications across the board.
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Exploring determinants influencing the selection of geriatric nursing care services in Thailand Bangkok metropolitan area
(2024-01-01)
Promsiri, Triyuth
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Arunyik, Budsara
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Keerativutisest, Vasu
The global population structure is undergoing a significant transformation, marked by an increasing number of elderly individuals. Thailand, in particular, is transitioning into an aging society and exhibits the third-highest growth rate in Asia, following Japan and Singapore. This phenomenon is driven by various factors, including economic and social conditions, technological advancements, family dynamics, and evolving lifestyles. Consequently, a growing number of elderly individuals are either living alone or require caregivers and elderly care facilities if they are dependent. This study is prompted by a keen interest in the elderly care service industry, which demonstrates significant potential both currently and in the future. The primary objective of this research is to explore the determinants influencing the selection of Geriatric nursing care and to identify the challenges encountered in delivering these services. The study investigated demographic and social factors, the necessity for elderly care, and the decision-making process in selecting geriatric nursing care. Data was collected through online questionnaires and analyzed, employing both descriptive and inferential statistics, including factor analysis, reliability analysis, and correlations between variables. The target population comprises Thai individuals aged 50 and above residing in Bangkok and its metropolitan areas with a sample size of 426 participants. Findings suggest that demographic factors, excluding occupation, along with social factors, the necessity for dependency, and the decision-making process, affect the selection of Geriatric nursing care in the studied regions.
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Factors Effecting Employees Motivation: A Study of the Ministry of Foreign Affairs in Myanmar
(2023-01-01)
Kyaw, Htet Aung
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Keerativutisest, Vasu
The study aimed to determine the organizational factors that influence employee motivation in the Ministry of Foreign Affairs in Myanmar. Organizational factors as the independent variable were hypothesized to influence the dependent variable. Organizational factors are organization policies, salary, compensation and bonus, working conditions, job security, interpersonal relationships, psychological conditions, and emotional intelligence directly affect employee motivation. This research employed a mixed method that collects the qualitative data first and the results from the qualitative data analysis use the questionnaires for the quantitative data collection. Descriptive statistics of dependent and independent variables are obtained to interpret the responses of participants and draw comparisons of how the responses are distributed. Multiple regression and Pearson correlation coefficient were applied to test hypotheses. Organizational commitment as a moderating variable can strengthen the relationship between organizational factors and employees' motivation. Testing of the hypothesis found that organization factors significantly influence employees' motivation and organizational commitment can modify the relationship between organization factors and employees' motivation
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Sustaining Thai Government Agency Innovation through Design Thinking Learning Effectiveness
(2022-06-01)
Promsiri, Triyuth
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Sukavejworakit, Krisakorn
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Keerativutisest, Vasu
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Virasa, Thanaphol
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Kampanthong, Krischanan
Thailand’s 4.0 strategy intends to achieve prosperity, security, and sustainability for its citizens both today and in the distant future. By focusing on the public sector and its civil servants, the government is driving innovation in the public sector by using design thinking (DT) to train government officials to improve public sector innovation (PSI). However, despite studies being conducted on DT and its increasing popularity among scholars, there is still a gap between knowledge and practice with regard to the learning effectiveness of the DT methodology in terms of fostering public sector innovation. Therefore, the authors’ objective for this study was to explore the effectiveness of DT in the Thai PSI and measure the learning effectiveness of the design thinking method (DTM). The researchers conducted action research through a series of workshops and in-class activities involving both qualitative and quantitative approaches. The sample was made up of government officials participating in the Thai Government Innovation Lab (GIL) project in 2020 and 2021. The results on the effectiveness of the program showed that fostering government innovation through DT education led to highly sustainable and highly effective outcomes. This study contributes to the development of public innovation by implementing the DTM as a core methodology for fostering innovation in public organizations.
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FINANCIAL FEASIBILITY CANVAS (FFC): EXTENDING THE BUSINESS MODEL CANVAS AS A METHOD TO TEACH FINANCIAL FEASIBILITY STUDY IN ENTREPRENEURIAL FINANCE
(2021-01-01)
Keerativutisest, Vasu
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Promsiri, Triyuth
Teaching entrepreneurial finance is a challenge, especially for new ventures. New ventures are facing many uncertainties during the process of business venturing, which leads to difficulties in estimating assumptions and projections to conduct feasibility analysis. Although there are many theories to explain that entrepreneurs always make a decision through bias and self-decision making, Feasibility analysis is still essentially important because it guides entrepreneurs make a decision through data and critical thinking. In this study, we seek to develop an alternative method to help nascent entrepreneurs have a better understanding to be able to conduct the financial feasibility analysis. Therefore, we deploy the existing tool in entrepreneurship, which is business model canvas, as a framework. Business model canvas was selected because it is a visual tool that allows entrepreneurs to see the connection among different components of the business, and it is the main theory which has been used widely in entrepreneurship classrooms; however, the connection between business model canvas and financial feasibility study is still limited. This study filled the gap of financial aspects of the business model canvas by proposing the 6-step analysis through the “Financial Feasibility Canvas (FFC)”. Those six steps including investment rationale, capital investment, assumptions, cashflow, financial returns, and decision, will guide learners and entrepreneurs to follow logical financial consequence until financial return calculation to assist entrepreneur’s decision-making process. The researchers then implemented this teaching method in entrepreneurial finance class. 33 entrepreneurship students participated in a series of 3-week workshop. The researchers further guided them through 6-step analysis, assign team project to come up with their own business idea and verify the possibility of their business idea through FFC. Learners agreed on the effectiveness of this teaching method in comparison with traditional methods. This study fills the void of academic linkage, promote class participation and environment, and raise the awareness of entrepreneurship students focusing on the financial aspects of business in completing the Business Model Canvas.

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