10 research outputs found
Identifying Factors Influencing Consumers Not to Skip TrueView Advertising on YouTube
No full textIdentifying new factors driving customers to skip advertising has called into question the applicability of attention advertising approaches in the digital environment. This study aims to identify the factors that affect skipping advertising on YouTube, discussing the extent of advertising avoidance behavior. The total sample consisted of 478 individuals with experience watching TrueView advertising on YouTube; data were collected via an online questionnaire. The validity and reliability of the results were tested using a set of statistical measures. Data analysis was carried out using GSCA Pro 1.1.8 for the structural equation model analysis. The conceptual frameworks outline use and gratification under the theory of planned behavior. In favor of an advertising avoidance effect, the findings show that attitude towards advertising value is a serious concern. Theoretical and managerial implications of these results are discussed, and alternative solutions for planning advertising are provided as a guideline for creating suitable advertisements for viewers, hopefully leading to a reduction in skipping advertising
Examining the Influences of Satisfaction and Trust on the Behavioral Intentions of Customers Who Dined in Casual Dining Restaurants: A Mixed-Methods Approach
No full textThe restaurant business is very competitive, such that managers must identify appropriate components of their restaurant attributes to better satisfy the needs and wants of their customers. Studies have long investigated restaurant attributes but treated such attributes using a common factor analysis technique; these should be analyzed as components. This paper aims to demonstrate how researchers can conduct a mixed-methods study to investigate the effects of restaurant attributes on customer behaviors and how a component-based analysis method is used. A sequential unequal research design was undertaken, including three steps: (1) identifying a set of restaurant attributes from the restaurant literature (Step-1), (2) conducting a field study to propose a refined set of restaurant attributes that fit with the context of the study (Step-2), and (3) collecting survey data for further analysis with the Generalized Structured Component Analysis (GSCA) technique (Step-3). The results of Step-1 revealed 10 restaurant attributes entailing many components. The results of Step-2 revealed only seven attributes (food, price, services, atmosphere, facilities, cleanliness, and location), entailing different sets of components specific to each attribute. In Step-3, a conceptual model was developed, including three constructs treated as components: satisfaction (encapsulated all seven restaurant attributes), trust, and behavioral intentions. The results of Step-3 indicated that satisfaction was found to influence trust, while satisfaction and trust were found to influence behavioral intentions. In addition, the indirect effect of satisfaction on behavioral intentions through trust was indicated as only a partial mediator. Overall discussions suggest further studies that may adapt various methods to improve research quality. Thus, this paper offers a specific procedure for researchers who desire to conduct a mixed-methods research design through the context of the restaurant business and for those interested in using GSCA. Demonstrating the research processes employed is the primary contribution of this paper. This may be helpful for novices interested in replicating our steps in their specific study context
Social Marketing Strategy to Promote Traditional Thai Medicines during COVID-19: KAP and DoI Two-Step Theory Application Process
No full textIntroduction: Recently, the Thai government has been promoting the innovation of finished forms of traditional Thai medicine (TTM) products (e.g., tablets and capsules). According to the existing literature, most consumers are unaware of the finished forms of TTMs because of conflicting knowledge, information, and communication. Therefore, the consumers have poor perceptions about TTMs and their benefits. Purpose: This qualitative study explores the current perceptions about TTMs and the modes of promotion that are being utilized to develop a strategic communication plan for the finished forms of TTMs. Design/methodology/approach: Utilising thematic analysis, focus groups were conducted with thirty experienced consumers. Findings: Using KAP and DoI theory, the following three themes emerged in this study: (i) the current KAP of Thai consumers toward the finished forms of TTM; (ii) factors influencing the use of finished forms of TTM; and (iii) integrated marketing communication as a promotion strategy to rapidly disseminate knowledge. Research limitations/implications: Given Thailand’s large population, the findings of this study are substantially limited and cannot be generalized. Therefore, the findings herein may not reflect the experiences and opinions of the Thai consumers residing in other regions or the opinions of the entire country. Originality/value: This study utilises interdisciplinary methods and two-step theory application to explain the current knowledge and perceptions about the finished forms of TTM and develop proper communication and media strategies that can promote the finished forms of traditional Thai medicines, helping to widen their usage significantly
The Role of Retail Mix Elements in Enhancing Customer Engagement: Evidence from Thai Fast-Moving Consumer Goods Retail Sector
No full textThe current understanding of the effect of the retail mix elements on customer engagement is limited. This study aims to investigate these relationships using a case study of Thai FMCG retail. A review of the relevant literature was conducted to propose a conceptual model consisting of the five retail mix elements (product, service, store, experience, and sales promotions) and customer engagement. A survey methodology was used to empirically validate the proposed conceptual model. Eight-hundred customers who had experience in shopping at two FMCG retail stores located in Khon Kean City participated in the survey. Obtained data were analyzed using generalized structured component analysis. Results show that four retail mix elements, all except the product aspect, significantly affected customer engagement. A multiple-group analysis was conducted using R package lavaan to further investigate the differences between the two retail stores, revealing the shortfalls of one retailer in respect of the other. This paper theoretically contributes to the retail literature by answering a call for investigation of the impact of FMCG’s retail mix elements on customer engagement. In addition, the study’s results lead to a proposition of strategies that form a pratical contribution, and which may be useful for the retailers under investigation and other retail businesses
Leveraging Machine Learning to Enhance Road Safety: A Social Marketing Approach
No full textRoad safety remains a critical concern worldwide. This research aims to investigate the use of Explainable AI (XAI) techniques, particularly SHAP (Shapley Additive Explanations), to identify key factors influencing road accident severity and create a social marketing campaign encouraging people to change their behavior in relation to road safety. Several machine learning models were developed using data from Thailand’s Ministry of Transport. The results show that the Light Gradient Boosting Machine (LGBM) model achieved the highest accuracy of 0.85 and an F1 score of 0.83. SHAP analysis revealed that the most significant contributing factors were the number of motorcycle involvements, road code, and the total number of vehicles and people involved in the accident. A practical framework for promoting sustainable road safety was proposed, focusing on raising awareness, delivering emotionally impactful communication, and fostering immediate behavioral change. This research provides valuable insights for strategic road safety initiatives and demonstrates the effectiveness of integrating machine learning with XAI. The findings can guide government authorities, policymakers, insurance companies, and social marketing planners in improving road safety
Influences of the Promotion Mix on Brand Love, Brand Loyalty, and Word-Of-Mouth: Evidence from Online Fashion Retail in Thailand
No full textThe online fashion industry faces competent competition, while brand love has become the key to winning a competitive advantage. Thus, brand love has become an interesting concept among academia in brand management-related disciplines. Previous research has not investigated the origins of brand love, specifically, its critical connection to the components of the promotion mix. This study employs the Tri-component attitude model as a theoretical foundation to investigate the influences of components of the promotion mix on brand love, brand loyalty, and word-of-mouth. The survey questionnaire was developed from the relevant literature and deployed in Khon Kaen Province, Thailand. Through convenience sampling, 276 individuals from Generation-Z participated in the survey. The Integrated Generalized Structured Component Analysis (IGSCA) was employed using GSCA Pro 1.2.1 software to assess the structural model. Findings show that advertising, personal selling, and sales promotion can predict variance in brand love, which can further predict the variance in brand loyalty and word-of-mouth. Several promotional mix strategies specific to each gender are proposed for practical use with online fashion brands to induce a love for online fashion brands
Enhancing Spectator Engagement in E-sports Events
No full textThis study investigates and measures factors related to the involvement of spectators in e-sports events using a Structural Equation Model (SEM) coupled with a Necessary Condition Analysis (NCA). The researchers conducted the study within a framework of push and pull factors. The findings indicate that both push and pull factors impact commitment, and that commitment has an impact on engagement. The practical implication of this is that management should emphasize pull factors, such as improving the quality of events, strategies for enhancing event attractiveness at the community level, managing event rewards, considering pricing strategies, utilizing promotions, and selecting suitable venues. Regarding the theoretical implications, the significance of three factors, push, pull, and commitment, are underscored as necessary conditions for engagement in this context. This research provides valuable in-depth insights for e-sports event managers to develop strategies which increase interest and participation among spectators, thereby enhancing the overall experience and growth of the industry
Captivating Spectators: Exploring the Influence of Marketing Mix Elements on Sports Event Engagement
No full textThis research study explores the influence of Marketing Mix components on spectator interest and engagement in sports events, with a focus on the traditional rugby football rivalry between Chulalongkorn University and Thammasat University, known as “Rugby Football,” in Thailand. Drawing on the 7Ps marketing mix theory, the study utilizes a composite-based approach to identify key factors within each element that contribute to spectator interest and subsequent engagement. The findings reveal that “Product,” “People,” and “Physical Evidence” significantly influence spectator interest in tracking sports competition results and promoting their involvement. Practical implications emphasize the importance of service quality, staff adequacy, appropriate event timing, engaging halftime shows, and stadium decoration, to enhance spectator interest. Theoretical implications highlight the role of the Marketing Mix elements as stimuli to attract individuals without prior interest in sports. Overall, this research provides valuable insights for sports competition managers to develop targeted strategies that foster increased interest and engagement among spectators, enriching the sports event experience and industry growth
Systematic Literature Review: The Use of SEM in Journal of Travel & Tourism Marketing (JTTM) Between 2020 – 2022
No full textThe aim of this study was to categorize and analyze the patterns of structural equation modeling (SEM) used in research in the travel and tourism industry, published in the journal of travel & tourism marketing (JTTM) between 2020 and 2022. This review seeks to provide an updated literature overview and identify gaps in the literature relevant to future research by employing the systematic literature review (SLR) method. The findings of the study indicate that factor-based SEM has been more frequently used compared to composite-based SEM. However, for future research, there should be more emphasis on composite-based SEM, particularly utilizing techniques such as integrated generalized structured component analysis (IGSCA) and partial least square consistent structural equation modeling (PLSc-SEM). These methods are hybrid techniques that can analyze both factor and composite variables within the same model. Additionally, this study has categorized research in the travel and tourism industry into eight major themes: 1) destination, 2) attraction, 3) hotel/resort, 4) airline, 5) restaurant, 6) social media, 7) festival/event, and 8) travel agency. For future research, there should be a focus on the festival/event and travel agency themes, as there is a relatively limited body of research within these themes
