Available online at www.HighTechJournal.org HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 210 ISSN: 2723-9535 Consumer’s Personality Traits and Knowledge-sharing Behavior on Shoppertainment Platforms: The Mediating Role of Subjective Well-being and Trust Thadathibesra Phuthong 1* 1 Department of Logistics Management, Faculty of Management Science, Silpakorn University, Phetchaburi, 76120, Thailand. Received 27 December 2022; Revised 21 February 2023; Accepted 25 February 2023; Published 01 March 2023 Abstract Objectives: This research analyzed the direct and indirect influences of consumer personality on knowledge-sharing behavior through shoppertainment platforms using subjective well-being and trust as mediators. Methods/Analysis: A questionnaire survey was developed and distributed to 320 consumers with familiarity and experience in purchasing products from the TikTok shop and sharing knowledge, information, news, and purchasing experiences with the Thai TikTok community. This study adopted non-probability and purposive sampling techniques, with measurements and structural model assessments performed before hypothesis testing using the partial least squares structural equation model (PLS-SEM) with SmartPLS statistical software. Findings: Extraversion and openness to experience had a direct positive influence on trust, while neuroticism showed a direct negative influence on trust. Extraversion had a direct positive influence on subjective well-being, while neuroticism showed a direct negative influence on subjective well-being. Both trust and subjective well-being directly influenced knowledge-sharing behavior on the shoppertainment platform. Extraversion and openness to experience positively influenced knowledge-sharing behavior on the shoppertainment platform via trust, while neuroticism negatively influenced knowledge-sharing behavior on the shoppertainment platform through trust. Importantly, extraversion, openness to experience, and agreeableness positively influenced knowledge- sharing behavior on the shoppertainment platform via subjective well-being, with neuroticism negatively influencing knowledge-sharing behavior on the platform through subjective well-being in the same manner. Novelty/Improvement: Results contribute to an improved understanding of the mechanisms of a robust and competitive online retail business model in the digital era that can best deliver business sustainability by elevating consumers’ knowledge-sharing behaviors to facilitate purchasing decisions on goods or services via shoppertainment platforms. Keywords: Personality Traits; Knowledge-Sharing Behavior; Shoppertainment Platform; Subjective Well-Being; Trust; TikTok. 1. Introduction Technology is an important factor in the economic and social foundation, with changes in technology inevitably leading to changes in both the economic and social system formats. Digital and internet technology development has rapidly decreased the cost of acquiring information and communication, affecting people’s economic behavior worldwide. Acquisitions, exchanges, and sharing of resources are now increasingly conducted through online platforms [1], opening windows of opportunity for people to earn income from the different types of assets available. The COVID- 19 pandemic necessitated the transition of consumers’ main activities to a "new normal", with working life and business operating on digital platforms as powerful tools for developing products, innovation, and technological services, and * Corresponding author: phuthong_t@su.ac.th http://dx.doi.org/10.28991/HIJ-2023-04-01-014  This is an open access article under the CC-BY license (https://creativecommons.org/licenses/by/4.0/). © Authors retain all copyrights. https://creativecommons.org/licenses/by/4.0/ https://orcid.org/0000-0002-7385-2808 HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 211 also stimulating business sector growth. Digital platforms can efficiently match the needs of product and service providers with the on-demand economy, creating the opportunity to exchange goods and services with lower transaction costs and increased convenience [2]. Examples of successful digital platforms include Facebook, Yahoo, YouTube, and Uber as social media, informative media sharing, and service platforms. In business terms, a digital platform is a structural unit that connects stakeholders in the value chain and facilitates cooperation or benefit sharing without a long-term commitment. This arrangement leads to a new type of economy, the sharing economy, where companies and entrepreneurs reduce prices, investment, and long-term employment. These business strategies build, attract, and retain customers to use products and services through the platforms by building an ecosystem to develop products, services, and environments to satisfy customers through lower transaction costs [3, 4]. Digital platforms have now become the primary modus operandi for organizing economic and social activities and political interactions [5, 6], and transforming different industries such as the shipping industry (Uber and Grab), hotel services industry (Airbnb and Couch surfing), food service industry (Grubhub and Hungry Hub), and software development (Apple iOS and Google Android). Organizations successfully benefit from digital platforms by offering affordable prices to large numbers of users [7], with digital platforms becoming attractive business models and strategies as potential drivers of economic growth in diverse sectors. Shoppertainment is the concept of making a website more entertaining. The decision to buy or sell is driven by website content that combines entertainment while providing knowledge to customers. A shoppertainment website combines and creates content to suit the online community through impressive buying experiences. Shoppertainment is a perfect way for brands to develop customer involvement through videos with audio. In 2022, TikTok and Boston Consulting Group (BCG) surveyed countries in the Asia-Pacific market, including Thailand, Indonesia, Vietnam, Australia, South Korea, and Japan. They determined that ‘shoppertainment, or the buying experience from entertainment, was an essential driving factor for success in entering the e-commerce era. In Thailand, the fast-growing e-commerce market has now become a part of people’s daily lives and businesses; shoppertainment has become a trend in purchasing products and services via entertaining content, which is more easily accessible, engaging, and exciting. Shoppertainment also builds users’ trust and creates online or virtual communities, with various important driving factors including content creators, users, and brands. Previous research results suggested that shoppertainment had the potential to create business opportunities of around one billion US dollars (USD) for different brands in the Asia-Pacific region by 2025, while the market share of Indonesia, Japan, and South Korea was anticipated to be 67 percent of shoppertainment’s gross market value, with market share continuing to grow at 63 percent each year compared to the compound annual growth rate [8]. Research results concerning APAC’s Trillion-Dollar Opportunity project by TikTok and Boston Consulting Group (BCG) indicated that shoppertainment grew rapidly in Southeast Asian markets, primarily Thailand, Vietnam, and Indonesia, as countries with the largest market share of e-commerce. This region was also driven by entertainment, demand, and supply-stimulating factors, with shoppertainment immensely affecting daily lifestyles and Thailand among the top countries using shoppertainment. This finding concurred with the Electronic Transactions Development Agency survey of internet user behavior in Thailand in 2022. Results determined that Thai people used the internet for an average of seven minutes and four seconds daily, with the top five popular activities being consulting and receiving medical services, communicating, watching TV clips and movies, listening to music, watching live broadcasts for purchasing products and services, and completing financial transactions. Watching live broadcasts to purchase products and services was surveyed for the first time and ranked fourth on the list, reflecting a growing trend in Thailand. A popular shoppertainment platform that later extended to businesses is TikTok. Selling and purchasing through the TikTok community creates infinite loops; users watching the content on social media might discover a product they were unaware of and consider whether it was interesting. If they bought the product and were satisfied, they then told others about it. On average, Thai people visit the TikTok website 12 times daily for a total time of 100 minutes [9, 10]. The data above indicates a business opportunity for retailers to adjust to online business platforms and attract consumers who watch live broadcasts to purchase products and services. The "big five" personality traits suggested by Costa and McCrae [11] have been widely accepted as an accurate overall personality assessment, covering broad dimensions for every country and language. These traits can be adapted to study people of different ages, ranging from young to old [12]. Each component of personality relates to an individual’s ideas, feelings, and behavior. For example, extraversion is a personality trait that can predict social behavior, while neuroticism shows an individual’s ability to adjust their mood and tolerate external stimuli. Openness to experience is related to personal feelings, indicating an adjustment to ideas, beliefs, and actions, while agreeableness is related to behavior between individuals and how they listen to others, and conscientiousness indicates an individual’s goals and achievement ability. Previous studies showed that people with extraversion, openness to new experiences, and agreeableness personality traits tended to trust others [11, 13, 14], while those who displayed neuroticism and conscientiousness personality traits tended not to trust others [13, 14, 15]. Furthermore, people with extraversion, openness to experience, agreeableness, and conscientiousness personality traits were more likely to show their subjective well-being [16]. By contrast, those with neuroticism usually shared negative expressions regarding their subjective well-being or personal satisfaction [16]. HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 212 Lönnqvist & große Deters [17] and Tang et al. [18] also found that people who embraced extraversion, openness to experience, and neuroticism personality traits tended to share on social media, while Correa et al. [19] indicated that those with extraversion regularly used social media platforms and tended to exhibit knowledge-sharing behavior more often than users with other personality traits. By contrast, people with agreeableness and conscientiousness personality traits used online social media platforms carefully and avoided negative relationships or sharing knowledge. Ahn & Shin [20], Cho et al. [21], Ma & Chan [22], and Wei & Gao [23] found that users’ subjective well-being increasingly affected knowledge-sharing behavior on online social media, while Gang & Ravichandran [24] and Hung et al. [25] suggested that trust was an essential concept in knowledge management that created positivity and stimulated knowledge-sharing behavior. This finding correlated with a study by Gang and Ravichandran [24], who demonstrated that trust was an important factor related to knowledge-sharing behavior in a virtual community. Their results revealed a connection between openness to experience, extraversion, neuroticism, agreeableness, and conscientiousness personality traits, which affected subjective well-being, trust, and knowledge-sharing behavior on online social media platforms in a virtual community. A literature review showed that studies investigating the effect of people’s different personalities and knowledge- sharing behaviors showed that personality traits related to how they searched for information and followed such information or recommendations. Many researchers found that trust and subjective well-being were important factors in promoting knowledge-sharing behavior [24, 25, 26], with positive relationships between individuals also important in different situations to promote knowledge-sharing behavior [20–23, 26, 27]. The relationship between subjective well- being and trust as mediators for personality traits and knowledge-sharing behavior was also investigated in the online social media context. Correa et al. [19], Jami Pour & Taheri [28], and Ross et al. [29] indicated that subjective well- being and trust were mediators for a positive relationship between extraversion and knowledge-sharing behavior on online social media platforms, while Gerson et al. [30], Jami Pour & Taheri [28], and Steel et al. [31] found that subjective well-being and trust were mediators for a positive relationship between openness to experience and knowledge-sharing behavior on online social media platforms. In the same vein, DeNeve & Cooper [32], Jami & Taheri [28], and Steel et al. [31] reported that subjective well-being and trust were mediators for a positive relationship between agreeableness and knowledge-sharing behavior on online social media platforms, while conversely, Jami Pour and Taheri [28] found that subjective well-being and trust mediated a negative relationship between neuroticism, conscientiousness, and knowledge-sharing behavior on social media platforms. However, previous research did not consider the mediating role of subjective well-being and trust in the context of popular social e-commerce platforms, with buying or selling driven by content that combined entertainment and knowledge. Therefore, to fill this research lacuna and extend the knowledge and understanding of knowledge-sharing behavior in the context of the shoppertainment platform, this study investigated the relationship between personality traits and knowledge-sharing behaviors by considering the mediating role of trust and subjective well-being among shoppertainment platform consumers. A research model and framework were developed to determine connections between the factors using the Big Five Inventory (BFI-S) Assessment [33], trust [24, 34], subjective well-being [17, 35], and knowledge-sharing behavior [21, 25, 36]. This quantitative study gathered information from a questionnaire sent to 320 consumers with experience purchasing products through the TikTok shop who had shared knowledge, information, news, and at least one purchase experience with Thailand’s TikTok community. The direct and indirect effects of consumers’ personality traits and knowledge-sharing behavior on shoppertainment platforms were assessed using subjective well-being and trust as mediator variables. Results will benefit entrepreneurs of online retail businesses that use shoppertainment platforms and can also be applied by stakeholders to improve applications in their businesses. This information can be used to promote consumers’ knowledge-sharing behaviors in online retail businesses that lead to online purchasing decision-making of products or services through the shoppertainment platform and also create a sustainable higher competitive ability for online retail business entrepreneurs in the digital platform business era. 2. Literature Review The literature review part reviews the relationship among variables to explain the connection and correlation among factors in the related literature. The details are as follows. 2.1. The Relationship between Personality and Trust Extraversion is a quality that indicates a person’s fondness for communication; such people are generally lively and energetic. In contrast, introversion indicates a person’s inclination to detach themselves from society, ignorance, and nervousness [11]. These behavior patterns are consistent with Jami Pour and Taheri [28], McCrae and Costa [37], and Li et al. [38], who indicated that people with extraversion are more likely to have a high level of trust in others, which would increase the tendency to create social interactions and relationships. Based on the aforementioned data, the first research hypothesis can be presented as follows. HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 213  H1(+): Extraversion has a positive direct effect on trust Openness to experience suggests a person’s quality of favoring openness to novel opinions, ideas, and experiences [39], including tolerance to deviations, interest in different cultures, and search for innovation. Costa and McCrae [11], Jami Pour and Taheri [28], and Li et al. [38] found that people who were highly open to new experiences were curious, had new ideas, and were full of imagination; in contrast, those who had a low level of openness to new experiences were cautious and conservative. Furthermore, Dinesen et al. [13] found that people who were more open to experience tended to trust others at a high level. Typically, this group of people was patient and open to everything they encountered. Based on the aforementioned data, the second research hypothesis can be formulated as follows.  H2 (+): Openness to experience has a positive direct effect on trust Neuroticism is a personality trait that shows a person’s tendency to experience unpleasant and unexpected emotions and to have disturbing thoughts and respected actions [15]. People with neurotic personality traits likely feel stressed, restless, and anxious, so they tend to worry and think about things that might go wrong. Such people always have a higher level of worry; as a result, they might trust others less than other people with different personality traits. People with neuroticism also tend to understand or interpret situations negatively, as they are likely to recognize dishonesty, which might result from discrepancies in distributing or sharing benefits. Consequently, there is less chance for these people to trust others [28], which correlates with Tang et al. [40], who indicated that people with neuroticism had a negative relationship with the trust of consumers who used mobile applications. Based on the above data, the third research hypothesis can be postulated as follows.  H3(-): Neuroticism has a negative direct effect on trust People with agreeableness personality traits are always friendly, believe in others’ goodness, and nearly have no hidden intention [11]. Agreeableness also specifies a person’s character when interacting with others more than other types of personalities [14]. People with agreeableness personality traits are willing to cooperate, warm, friendly, and avoid creating conflicts. Studies by Costa and McCrae [11], Deng et al. [41], and Tang et al. [40] showed that people who have a high level of friendliness and agreeableness always have a high level of trust with others as those who are friendly and have agreeableness always easily trust and have confidence in others. Based on the data above, the fourth research hypothesis can be posited as follows.  H4(+): Agreeableness has a positive direct effect on trust The personality of conscientiousness indicates people who are conscious, logical, and knowledgeable. Generally, this group considers themselves more capable than others [11]. People with high conscientiousness are always ambitious, disciplined, accurate, well-planned, and considerate before any actions; however, people with low conscientiousness are generally immature, hot-tempered, weak, reckless, and unstable [11]. Jami Pour and Taheri [28], McCrae and Costa [37], Mondak [14], Tulin et al. [42], and Li et al. [38] revealed that people who have high conscientiousness are always cautious and do not trust information or news they receive from people they consider to have lower conscientiousness. Dinesen et al. [13] also found that people with conscientious personality traits are also determined in decision-making and always try to control situations to be as planned with cautiousness and consciousness. Such people do not immediately trust information from others’ actions or intentions, reflecting their tendency to have low trust in others. Based on the data above, the fifth research hypothesis can be presented as follows.  H5(-): Conscientiousness has a negative direct effect on trust 2.2. Relationship between Personality and Subjective Well-Being Subjective well-being refers to a good mental state, which is an individual assessment of life regarding positive and negative feelings through each person’s lifestyle experience. An assessment of subjective well-being can be divided into three aspects: life evaluation, affection, and eudaimonia [43]. Furthermore, despite uncertainties in behaviors and activities guaranteeing a person’s happiness, studies over the past 50 years have broadly indicated 2 variables related to continuous life satisfaction: subjective well-being and personality. Good health, social relationship, community involvement, psychological needs, or an individual’s personality traits can explain the variance or predict subjective well-being at approximately 50 percent from all the related factors [44]. A review of previous literature showed the research results that personality plays a vital role in an individual’s perception of subjective well-being [16, 31, 32, 45]. DeNeve & Cooper [32] examined the effect of five personality traits on subjective well-being; they differentiated subjective well-being into two dimensions, which were positive and negative effects, and the balance between positive and negative effects and understanding, such as satisfaction in life. Furthermore, the meta-analysis results by Hayes and Joseph [16] also suggested that neuroticism was the most crucial predicting variable explaining adverse effects and satisfaction in life. Nevertheless, extraversion and agreeableness were perceived as the most accurate predicting variables for positive effects on an individual’s subjective well-being. Moreover, some researchers indicated that conscientiousness was a variable related to the dimensions of the effects and satisfaction in life. For example, Costa et al. [46] found that HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 214 agreeableness and conscientiousness could increase the probability of predicting positive experiences in the context of social situations and an individual’s success, respectively. The findings could conclude that agreeableness and conscientiousness are directly related to an individual’s subjective well-being. Therefore, openness to experience should lead to an individual’s additional encounters with positive and negative emotions. Furthermore, Costa et al. [46] also suggested that extraversion positively affected subjective well-being, whereas neuroticism negatively affected subjective well-being. Based on the data above, the following research hypotheses can be concluded.  H6(+): Extraversion has positive direct effects on subjective well-being.  H7(+): Openness to experience has positive direct effects on subjective well-being.  H8(-): Neuroticism has negative direct effects on subjective well-being.  H9(+): Agreeableness has positive direct effects on subjective well-being.  H10(+): Conscientiousness has positive direct effects on subjective well-being. 2.3. Relationship between Personality and Knowledge-Sharing Behavior A review of previous literature shows studies confirming the effect of people’s different personalities on knowledge- sharing behavior; personality traits are related to methods or means a person uses to search for information and follow such information or recommendations. Moreover, many studies have examined the relationship between the five personality traits in different contexts. These include the study of relationships between personality traits and employees’ job performance [47], the study of relationships between personality traits and job satisfaction [48], the study of relationships between personality traits and continuous attention in job and assigned tasks [49], and the study of relationships between personality traits and career success across the employees’ lifespan [48]. The extant literature indicates that no comprehensive framework and assessment for personality traits have been determined; however, researchers empirically agree that, in psychology, the big five personality traits model is an appropriate and widely popular model to assess an individual’s personality traits and behavior [14, 50-52]. Millions of social media users are currently active worldwide, and the question of “which type of person relies on social media platform tools to interact with others” has been asked; thus, many researchers are interested in and have studied the possible relationship between personality traits and using online social media platforms [18, 19, 30, 53-55]. However, research on the relationship between knowledge-sharing behavior on online social media platforms and personality is still limited. For example, Tang et al. [18] showed that agreeableness, conscientiousness, and neuroticism have a negative relationship with addiction to the Facebook online social community. In contrast, Lönnqvist and große Deters [17] investigated the relationship between the size of the Facebook online social community, subjective well- being, social support, and an individual’s personality traits. They found that the size of Facebook’s online social community had a positive relationship with subjective well-being but had no relationship with the perception of social support. Moreover, extraversion was related to the size of Facebook’s online social community and an individual’s subjective well-being. Furthermore, Correa et al. [19] indicated that personality trait was important in developing interaction among social media platform users. People with extraversion were regular users of social media platforms and were more active than people with other personality traits. Additionally, Tang et al. [18] demonstrated that online social media platform users with a low level of conscientiousness in personality traits usually used online social media platforms cautiously and with a negative relationship. In contrast, users with extraversion, neuroticism, and openness to experience personality traits had a positive relationship with online social media platforms. Based on this information, the following research hypotheses can be presented.  H11(+): Extraversion has a positive direct effect on knowledge-sharing behavior on the shoppertainment platform.  H12(+): Openness to experience has a positive direct effect on knowledge-sharing behavior on the shoppertainment platform.  H13(+): Neuroticism has a positive direct effect on knowledge-sharing behavior on the shoppertainment platform.  H14(-): Agreeableness has a negative direct effect on knowledge-sharing behavior on the shoppertainment platform.  H15(-): Conscientiousness has a negative direct effect on knowledge-sharing behavior on shoppertainment platforms. 2.4. Relationship between Trust and Knowledge-Sharing Behavior Trust is essential in knowledge management as it can create positive reliability and stimulate knowledge-sharing behavior [25]. Many researchers indicate that trust is an important factor in promoting knowledge-sharing behavior [24- HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 215 26]. It is also important for positive relationships between individuals in different situations and can promote knowledge- sharing behavior [26]. From the review of different factors relating to knowledge-sharing behavior in virtual communities [24], trust is an important factor relating to knowledge-sharing behavior [24]. It is defined as the ability of virtual community members and empathy, kindness, and honesty of friends in the virtual community. This research defines trust following Hung et al. [25], who proposed that the intention of members in social communities is good and that they are capable and reliable when sharing and using knowledge in the community. From the aforementioned data, the following research hypothesis is presented.  H16(+): Trust has a positive direct effect on knowledge-sharing behavior on the shoppertainment platform. 2.5. Relationship between Subjective Well-Being and Knowledge-Sharing Behavior The previous literature review shows several studies investigating the relationship between using online social media platforms and subjective well-being. An important finding was that the use of online social media platforms was related to an individual’s higher subjective well-being [56-59]. Furthermore, other studies have indicated that the use of online social media platforms is related to an individual’s lower subjective well-being [60]. For example, Ding et al. [56, 59] investigated “whether the use of online social media platforms is related to an individual’s subjective well-being.” They found that prolonged continuous use of online social media platforms negatively affected an individual’s subjective well- being. Furthermore, Ding et al. [56, 59] studied the role of jealousy as a mediator between effect and sexuality in the relationship between the use of online social media platforms and subjective well-being. They determined that most research has been interested in studying the effect of online social media platforms on an individual’s subjective well- being [20, 61-63]. In contrast, limited studies have investigated the relationship between the effect of an individual’s subjective well-being on online social media platforms using behavior [64]. Therefore, to fill this apparent gap, this present study was interested in examining the effect of subjective well-being on the users’ knowledge-sharing behavior on online social media platforms, especially shoppertainment platforms. The relationship between subjective well-being and knowledge-sharing behavior was specified based on Ahn & Shin [20], Cho et al. [21], Ma & Chan [22], Panahi et al. [27], and Wei & Gao [23]. From the information presented above, the following research hypothesis can be posited.  H17(+): Subjective well-being positively affects knowledge-sharing behavior on the shoppertainment platform. 2.6. Relationship between Subjective Well-Being and Trust as Mediators for Personality Traits and Knowledge- Sharing Behavior This study investigated the consumers’ personality traits and knowledge-sharing behavior on shoppertainment platforms, using subjective well-being and trust as mediators. A review of previous literature revealed studies on the relationship between subjective well-being and trust as mediators for personality traits and knowledge-sharing behavior in the online social media context. Examples include Correa et al. [19], Jami Pour & Taheri [28], and Ross et al. [29], which indicated that subjective well-being and trust were mediators for a positive relationship between extraversion and knowledge-sharing behavior for online social media platforms. Gerson et al. [30], Jami Pour & Taheri [28], and Steel et al. [31] found that subjective well-being and trust were mediators for a positive relationship between openness to experience and knowledge-sharing behavior on online social media platforms. DeNeve & Cooper [32], Jami Pour & Taheri [28], and Steel et al. [31] reported that subjective well-being and trust were mediators for a positive relationship between agreeableness and knowledge-sharing behavior for online social media platforms. Conversely, Jami Pour & Taheri [28] found that subjective well-being and trust mediate a negative relationship between neuroticism, conscientiousness, and knowledge-sharing behavior on online social media platforms. The literature review, however, reflected that there is still limited research studying the relationship between subjective well-being and trust as mediators for personality traits and knowledge-sharing behavior, especially for shoppertainment platforms. Therefore, to fill this gap, the present study examines the relationship between subjective well-being and trust as mediators passing the personality traits to knowledge-sharing behavior on the shoppertainment platform. From the literature review, the research hypotheses are proposed as follows.  H18: Extraversion has a positive indirect effect on knowledge-sharing behavior on the shoppertainment platform through trust.  H19: Openness to experience has a positive indirect effect on knowledge-sharing behavior on the shoppertainment platform through trust.  H20: Neuroticism has a negative indirect effect on knowledge-sharing behavior on the shoppertainment platform through trust. HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 216  H21: Agreeableness has a positive indirect effect on knowledge-sharing behavior on the shoppertainment platform through trust.  H22: Conscientiousness has a negative indirect effect on knowledge-sharing behavior on the shoppertainment platform through trust.  H23: Extraversion has a positive indirect effect on knowledge-sharing behavior on the shoppertainment platform through subjective well-being.  H24: Openness to experience has a positive indirect effect on knowledge-sharing behavior on the shoppertainment platform through subjective well-being.  H25: Neuroticism has a negative indirect effect on knowledge-sharing behavior on the shoppertainment platform through subjective well-being.  H26: Agreeableness has a positive indirect effect on knowledge-sharing behavior on the shoppertainment platform through subjective well-being.  H27: Conscientiousness has a positive indirect effect on knowledge-sharing behavior on the shoppertainment platform through subjective well-being. Based on the literature review, Figure 1 presents the research model. Figure 1. Research model entitled consumers’ personality traits and knowledge-sharing behavior on shoppertainment platforms: The mediating roles of subjective well-being and trust 3. Research Methods This quantitative examination used a questionnaire to collect data. A flowchart of the research methodology is shown in Figure 2. 3.1. Population and Sample Group The population and sample group included consumers with experience purchasing products through the TikTok shop and shared knowledge, information, news, and at least one purchase experience in Thailand’s TikTok community. The sample group was calculated by specifying the ratio between the sample units according to the parameters or variables based on the formula by Hair et al. [65], which specified that the number of the sample group was appropriate for the multivariate analysis and should have at least 5–10 times that of the indicator. There were 32 questions in this study, so the minimum number of the sample group should have been 320 samples. Therefore, this study used a minimum of 320 samples, which were selected using the non-probability and purposive sampling methods. HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 217 Figure 2. Flowchart of research methodology 3.2. Research Instruments The research instrument was an online questionnaire divided into two parts (Appendix I). Part 1 was the respondents’ answers to four general information questions, and Part 2 included the data about the relationship between the consumers’ personality traits and knowledge-sharing behavior on the shoppertainment platform, using subjective well-being and trust as mediators. There are two questions on extraversion, two on openness to experience, three on neuroticism, two on conscientiousness, and two on agreeableness. This study adapted 11 questions for consumers’ personality traits mentioned above [33], 5 questions on knowledge sharing on the shoppertainment platform [21, 25, 36], 10 questions on subjective well-being [17, 35], and 5 questions on trust [24, 34]. Questions were scored on a 5-point Likert scale. 3.3. Validity and Reliability of the Research Instruments The appropriateness of language used in the research instrument was tested with 10 participants to assess their understanding and ease of the questions. After the questionnaire was adjusted, its quality was examined by three experts to determine the content validity using the index of item objective congruence; an acceptance rate of more than 0.50 was used to show that the questions were consistent with the objectives and content [65]. The analysis showed that every question passed the minimum requirements with values between 0.67–1.00. The data were then collected to test the confidence level with the sample group of 30 participants. Cronbach’s Alpha was analyzed with an acceptance rate of more than 0.70 to show that this questionnaire was reliable and that the reliability values of all variables in the present study were acceptable [66]. The results from the analysis showed that all questions passed the minimum requirements with a confidence level between 0.716–0.904 and 0.909. The questions were revised a final time to ensure that the questionnaire covered all the objectives and factors before the data collection. HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 218 3.4. Data Collection The present study used an online questionnaire to collect data. Google Forms and Google Sheets were used to create and distribute the questionnaire through different channels, including social network sites, such as Line, Facebook, Twitter, and email, using non-probability and purposive sampling methods. The inclusion criteria were that the participants or volunteers were consumers who had experience purchasing products through TikTok Shop and had shared knowledge, information, news, and experience in purchasing products through the TikTok community. The researcher did not include limitations on age, educational level, and experience using the TikTok shop application. The exclusion criteria were data from the sample group who responded but could not answer every question in the questionnaire; a replacement sample group was then found using the same inclusion criteria. Question filtered the sample group by asking whether they had bought products through the TikTok shop and determined shared knowledge, information, news, and experience in purchasing products from the TikTok community. 3.5. Data Analysis After the responses were received, the basic statistical assumptions were tested using the data collected from the sample group to consider the completeness of the questionnaire answers to test the missing data, outliers, normal distribution, linearity, multicollinearity, and singularity. The test showed no missing data; linearity was found, but no multicollinearity or singularity. The data passed all the criteria with a negatively skewed distribution of more than +3 or less than −3 [67]; therefore, this study used the data for statistical analysis. The descriptive statistics were analyzed, and the hypothesis testing was tested using the partial least square (PLS) method. 4. Results The study results were divided into three main parts: 1) descriptive statistics for the demographic data of the sample group, 2) the results of structural equation modeling analysis to assess the assessment and structural equation models, and 3) hypothesis testing and effect path. The details are presented as follows. 4.1. Demographic Characteristics of the Sample Group Most of the questionnaire respondents were female, accounting for 70.94 percent. Their ages were primarily between 18 and 25, comprising 50.31 percent. Most received a bachelor’s degree as their highest education level, which accounted for 68.75 percent, and 47.19 percent had 3–5 years of experience using the TikTok shop. 4.2. Results of Structural Equation Modeling Analysis 4.2.1. Results of Structural Model Assessment Multicollinearity must be tested in any structural equation modeling analysis, and no statistically significant interrelationships should exist. The variance inflation factor (VIF) indicates whether multicollinearity is problematic. In this model, the highest VIF value of 2.398 was below the critical threshold of 5.00 [68]. Hence, multicollinearity was not a critical issue in this study, as shown in Table 1. Table 1. Results of Multicollinearity Testing Constructs VIF Extraversion (EXT) 1.328 Openness to experience (OPE) 1.320 Neuroticism (NEU) 1.531 Agreeableness (AGR) 1.373 Consciousness (CON) 1.307 Trust (TRT) 2.398 Subjective Well-Being (SWB) 2.371 Knowledge sharing behavior on the shoppertainment platform (KLS) 1.716 4.2.2. Results of the Measurement Model Evaluation The structural equation measurement modeling assessment analyzed the internal consistency reliability, determining that every latent variable had a composite reliability value of more than 0.70, ranging from 0.842 to 0.925, and the Cronbach’s Alpha had a value of more than 0.70, between 0.742 and 0.899. Thus, all measurement model evaluations of all the model’s latent variables were reliable [67, 69]. The convergent validity analysis showed that every latent variable had an AVE value of more than 0.50, between 0.589 and 0.764. Therefore, a convergent validity exists between HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 219 observed variables under the same latent variables in each of the model’s latent variables [67, 69]. For the analysis of indicator reliability, every observed variable had an outer loading value of more than 0.70 at between 0.746 and 0.935. Hence, all the observed variables were reliable [67, 69], as shown in Table 2. Table 2. Construct Reliability and Validity Constructs Items Outer Loadings Composite Reliability Cronbach’s Alpha AVE Agreeableness (AGR) AGR1 0.904 0.866 0.794 0.764 AGR2 0.842 Consciousness (CON) CON1 0.764 0.842 0.753 0.729 CON2 0.935 Extraversion (EXT) EXT1 0.825 0.854 0.764 0.746 EXT2 0.900 Knowledge sharing behavior on the shoppertainment platform (KLS) KLS1 0.760 0.877 0.825 0.589 KLS2 0.783 KLS3 0.755 KLS4 0.777 KLS5 0.762 Neuroticism (NEU) NEU1 0.834 0.853 0.742 0.660 NEU2 0.854 NEU3 0.746 Openness to experience (OPE) OPE1 0.850 0.854 0.760 0.746 OPE2 0.877 Subjective well-being (SWB) SWB3 0.842 0.879 0.816 0.646 SWB4 0.847 SWB5 0.764 SWB6 0.759 Trust (TRT) TRT1 0.806 0.925 0.899 0.712 TRT2 0.849 TRT3 0.869 TRT4 0.846 TRT5 0.848 For the discriminant validity analysis, the square root of the AVE value of each latent variable was higher than the correlation between the latent variable and the others in the model. The cross-loading value of each observed variable and their latent variables had the highest value compared to the cross-loading value of such observed variables and other latent variables in the model. Therefore, all the latent variables of the model had discriminant validity and were measured with the correct observed variable [70], as presented in Table 3. Table 3. Fornell–Lacker Criterion (Discriminant Validity) Constructs AGR CON EXT KLS NEU OPE SWB TRT Agreeableness (AGR) 0.874 Consciousness (CON) 0.692 0.854 Extraversion (EXT) 0.450 0.486 0.864 Knowledge sharing behavior on the shoppertainment platform (KLS) 0.344 0.343 0.465 0.767 Neuroticism (NEU) 0.517 0.428 0.534 0.410 0.813 Openness to experience (OPE) 0.504 0.439 0.582 0.422 0.632 0.864 Subjective Well-Being (SWB) 0.427 0.445 0.617 0.525 0.575 0.508 0.804 Trust (TRT) 0.233 0.176 0.472 0.613 0.434 0.448 0.432 0.844 HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 220 4.3. Results of the Analysis of Direct and Indirect Effects of Personality Traits on Knowledge-Sharing Behavior on the Shoppertainment Platform with Subjective Well-Being and Trust as Mediators to Test the Hypotheses 4.3.1. Path Coefficient and T-Statistic (Bootstrapping) The structural model was evaluated. after validating the adequate convergent and discriminant criteria of the measurement model. The primary focus concerned the model’s capability to explain and predict the effect of exogenous latent variables on the endogenous dependent latent variables [69]. Several measures were used to determine the model’s goodness of fit (GoF). The minimum acceptable R2 score for a suitable model fit was stated as 0.10 [67]. According to Henseler et al. [71], R2 represents the model’s explanatory power, with values of 0.02, 0.13, and 0.26 regarded as weak, moderate, and substantial, respectively [72]. In this study, all R2 values exceeded 0.26, with TRT 0.303, SWB 0.477, and KLS 0.478, indicating that the model had sufficient explanatory power. Furthermore, The Stone-Geisser Q2 criteria displayed the value of TRT, 0.273, SWB 0.455, and KLS, 0.241 that were all higher than zero, further supporting the predictive ability of the study model [71], as shown in Figure 3. Figure 3. Research model after hypothesis testing In the final step of the SmartPLS statistical software calculations, the statistical significance of parameters was tested using the bootstrapping process [67] and random sampling technique with 5,000 sets [67]. Two-tailed hypothesis testing was used to show that the coefficient effect value supported the research hypotheses, with a significant coefficient of 0.05 or p < 0.05 and a t-statistics value of more than or equal to 1.96. It was found that extraversion (EXT) (ß = 0.323, t = 4.779, p = 0.000) and openness to experience (OPE) (ß = 0.204, t = 2.771, p = 0.006) had a positive direct effect on trust (TRT), while neuroticism (NEU) had a negative direct effect on TRT (ß = 0.205, t = 2.855, p = 0.004). EXT (ß = 0.374, t = 6.336, p = 0.000) also positively affected subjective well-being (SWB); however, NEU had a negative direct effect on SWB (ß = 0.290, t = 4.885, p = 0.000). Furthermore, TRT (ß = 0.247, t = 4.113, p = 0.000) and SWB (ß = 0.471, t = 9.000, p = 0.000) had a positive direct effect on knowledge-sharing behavior on the shoppertainment platform (KLS). Agreeableness (AGR) (ß = −0.024, t = 0.290, p = 0.772) and conscientiousness (CON) (ß = −0.142, t = 1.913, p = 0.056) had no positive direct effect on TRT whereas OPE (ß = 0.057, t = 0.969, p = 0.332), AGR (ß = 0.003, t = 0.049, p = 0.961), and CON (ß = 0.112, t = 1.726, p = 0.084) had no positive direct effect on SWB. Furthermore, EXT (ß = 0.018, t = 0.296, p = 0.767), OPE (ß = 0.022, t = 0.350, p = 0.726), AGR (ß = 0.048, t = 0.784, p = 0.0.433), and CON (ß = 0.113, t = 1.907, p = 0.057) had no direct effect on KLS. NEU (ß = −0.033, t = 0.584, p = 0.559) had no negative direct effect on KLS. Table 4 presents the results of the analysis, showing that hypotheses H1, H2, H3, H6, H8, H16, and H17 were accepted, whereas hypotheses H4, H5, H7, H9, H10, H11, H12, H13, H14, and H15 were rejected. HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 221 Table 4. Structural model result for direct relationships Hypotheses t-Statistics Results H1 Extraversion has a positive direct effect on trust. 4.779*** Accepted H2 Openness to experience has a positive direct effect on trust. 2.771** Accepted H3 Neuroticism has a negative direct effect on trust. 2.855** Accepted H4 Agreeableness has a positive direct effect on trust. 0.290ns Rejected H5 Conscientiousness has a negative direct effect on trust. 1.913ns Rejected H6 Extraversion has a positive direct effect on subjective well-being. 6.336*** Accepted H7 Openness to experience has a positive direct effect on subjective well-being. 0.969ns Rejected H8 Neuroticism has a negative direct effect on subjective well-being. 4.885*** Accepted H9 Agreeableness has a positive direct effect on subjective well-being. 0.049ns Rejected H10 Conscientiousness has a positive direct effect on subjective well-being. 1.726ns Rejected H11 Extraversion has a positive direct effect on knowledge-sharing behavior on the shoppertainment platform. 0.296ns Rejected H12 Openness to experience has a positive direct effect on knowledge-sharing behavior on the shoppertainment platform. 0.350ns Rejected H13 Neuroticism has a positive direct effect on knowledge-sharing behavior on the shoppertainment platform. 0.584ns Rejected H14 Agreeableness has a negative direct effect on knowledge-sharing behavior on the shoppertainment platform. 0.784ns Rejected H15 Conscientiousness has a negative direct effect on knowledge-sharing behavior on the shoppertainment platform. 1.907ns Rejected H16 Trust has a positive direct effect on knowledge-sharing behavior on the shoppertainment platform. 9.000*** Accepted H17 Subjective well-being has a positive direct effect on knowledge-sharing behavior on the shoppertainment platform. 4.113*** Accepted Notes *** p < 0.01, ** p < 0.05, and ns = No statistical significance 4.3.2. SEM Analysis using Mediating Variables This study employed the bootstrapping method Preacher and Hayes [73] suggested to test the mediating effects. Table 5 shows that EXT (ß = 0.152, t = 4.490, p = 0.000) and OPE (ß = 0.096, t = 2.637, p = 0.008) had a positive indirect effect on KLS through TRT; however, NEU (ß = 0.097, t = 2.717, p = 0.007) had a negative indirect effect on KLS through TRT. EXT (ß = 0.092, t = 3.420, p = 0.001) had a positive indirect effect on KLS through SWB, whereas NEU (ß = 0.071, t = 2.912, p = 0.004) had a negative indirect effect on KLS through SWB. This study used a widely accepted and recommended test called the variance accounted for (VAF) test to analyze the mediating effects. According to Hair et al. [74], a VAF value less than 20% suggests no mediation, a value between 20 and 80% suggests partial mediation and a value greater than 80% suggests full mediation. In this study, the VAF value was calculated using the equation: VAF = Indirect effect / total effect The VAF value was 57.79% for the mediation effect of TRT in the relationship between EXT and KLS, 72.73% for the mediation effect of TRT in the relationship between OPE and KLS, and 71.85% for the mediation effect of TRT in the relationship between NEU and KLS. These results indicated that TRT partially mediated the relationship between EXT, OPE, NEU and KLS. Moreover, the VAF value was 34.98% for the mediation effect of SWB in the relationship between EXT and KLS, and 52.59% for the mediation effect of SWB in the relationship between the NEU and KLS. These results indicated that SWB partially mediated the relationship between EXT, NEU and KLS. Nevertheless, AGR (ß = −0.011, t = 0.291, p = 0.771) and CON (ß = −0.067, t = 1.869, p = 0.062) had no positive indirect effect on KLS through TRT and OPE (ß = 0.014, t = 0.912, p = 0.362). AGR (ß = 0.001, t = 0.048, p = 0.961) and CON (ß = 0.028, t = 1.543, p = 0.123) have no positive indirect effect on KLS through SWB. Table 5 indicates that hypotheses H18, H19, H20, H23, H24, H25, and H26 were accepted, whereas the hypotheses H21, H22, and H27 were rejected. HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 222 Table 5. Structural model result for the indirect effect Hypotheses t-Statistics Results H18 Extraversion has a positive indirect effect on knowledge-sharing behavior on the shoppertainment platform through trust. 4.490*** Accepted H19 Openness to experience has a positive indirect effect on knowledge-sharing behavior on the shoppertainment platform through trust. 2.637** Accepted H20 Neuroticism has a negative indirect effect on knowledge-sharing behavior on the shoppertainment platform through trust. 2.717** Accepted H21 Agreeableness has a positive indirect effect on knowledge-sharing behavior on the shoppertainment platform through trust. 0.291ns Rejected H22 Conscientiousness has a negative indirect effect on knowledge-sharing behavior on the shoppertainment platform through trust. 1.869ns Rejected H23 Extraversion has a positive indirect effect on knowledge-sharing behavior on the shoppertainment platform through subjective well-being. 3.420** Accepted H24 Openness to experience has a positive indirect effect on knowledge-sharing behavior on the shoppertainment platform through subjective well-being. 0.912ns Accepted H25 Neuroticism has a negative indirect effect on knowledge-sharing behavior on the shoppertainment platform through subjective well-being. 2.912** Accepted H26 Agreeableness has a positive indirect effect on knowledge-sharing behavior on the shoppertainment platform through subjective well-being. 0.048ns Accepted H27 Conscientiousness has a positive indirect effect on knowledge-sharing behavior on the shoppertainment platform through subjective well-being. 1.543ns Rejected Notes*** p < 0.01, ** p < 0.05, ns = No statistical significance 5. Discussions According to the objectives, the research results showed that extraversion and openness to experience personality traits had a positive direct effect on trust, while neuroticism had a negative direct effect on trust. These reflected that the consumers had extraversion and openness to experiencing personality traits. The respondents also had experience purchasing, sharing knowledge, information, and news related to purchasing experiences from the shoppertainment platform, and their decisions to buy or sell products were stimulated and driven through entertaining and informative content. The content was also put together and created to suit the online community, which trusted their friends on the platform or others they were not highly acquainted with. The respondents also liked to talk and share knowledge, information, news, and experience about purchasing products with members of the virtual community on the shoppertainment platform or other people to let them know their stories and purchasing experiences. The findings support Jami Pour & Taheri [28], Li et al. [38], and Flavián et al. [75], who found that a person with extraversion personality traits always trusted others at a high level, which would lead to a tendency to develop a behavior of building social interactions and good relationships later. Jami Pour and Taheri [28] and Li et al. [38] indicated that people who were highly open to new things were curious, creative, and imaginative, whereas people with low openness to new things were cautious and blocked public access to their accounts in the online social community. Furthermore, Deng et al. [41] reported that groups of people who were always open to new experiences tended to trust others at a high level because the nature of this group of people was always patient and open to everything they encountered; however, a neurotic personality trait had a negative direct effect on trust. This result reflected low levels of trust from consumers who had neurotic personality traits when using the shoppertainment platform to purchase products and share knowledge, information, news, and their purchasing experience. Such consumers also tended to interpret what they encountered more negatively than positively. There was also a minimal chance that these people would trust other people or other members of the online social community that they had not known before. This finding was consistent with studies by Tang et al. [40], Kraus et al. [76], Sharan & Romano [77], and Zhang et al. [78], who found that neuroticism had a negative relationship with consumers’ trust in using new online commercial platform services. Extraversion had a positive direct effect on SWB, indicating that consumers with extraversion personality traits who used to purchase products from shoppertainment platforms and shared knowledge, information, news, and experience purchasing products from the shoppertainment platform of which they were members with other members perceived that they had a better quality of life and a good mental state. Moreover, they were continuously satisfied with their lives, consistent with studies by Abdullahi et al. [79] and Han [80], which indicated that extraversion was an important factor positively affecting an individual’s perception of life satisfaction. Conversely, neuroticism had a negative direct effect on SWB, suggesting that consumers with neurotic personality traits who used to purchase products from the shoppertainment platform would have a poor psychological condition and a perception of a worse quality of life. This negative perception would lead to more dissatisfaction in these consumers’ lives when sharing knowledge, information, news, and experiences purchasing products from the shoppertainment platform with other members. This finding was in line with studies by Abdullahi et al. [79] and Han [80], which suggested that neuroticism was an essential factor negatively affecting an individual’s perception of dissatisfaction in life. HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 223 Furthermore, trust and SWB positively affected knowledge-sharing behavior on the shoppertainment platform, indicating the consumers’ belief that the shoppertainment platform could provide quality services and facilitate consumers or users with what they needed. These users also believed that the platform could be used to share knowledge, information, news, and experience purchasing products from the community on the shoppertainment platform with other members. These actions would improve their psychological status and perception of quality of life. If the consumers trusted and perceived SWB toward the shoppertainment platform at a higher level, the knowledge-sharing behavior of sharing information about the products or online services with friends and members of the online community would be promoted. An example was the experience of purchasing or using the shoppertainment platform through knowledge sharing and the presentation of products or services, which also included sharing information about the products or services with other consumers at a higher level. The findings supported the studies by Kmieciak [81], Mutahar et al. [82], Renqiang & Wende [83], and Wen & Wang [84], who found that trust was an important driving factor promoting an individual’s knowledge-sharing behavior, especially knowledge-sharing behavior in a virtual community. Wei & Gao [23], Yen [85], and Yen & Valentine [86] indicated that SWB was positively related to knowledge-sharing behavior on the social media platform. Likewise, extraversion and openness to experience personality traits had a positive indirect effect on knowledge- sharing behavior on the shoppertainment platform through trust. This finding reflected that consumers with extraversion and openness to experience personality traits who had experience purchasing and sharing knowledge, information, news, and experience purchasing products from the shoppertainment platform would have the behavior of communicating and sharing information about products or online services on the shoppertainment platform with other members of the online social community. This behavior included sharing information or news about experiences in purchasing products or using services on the shoppertainment platform, presenting information about products or services, and distributing information about products or services to other consumers at a higher rate. These would occur when the consumers trusted and were satisfied with the services they received and felt that members of the shoppertainment platform community were sincere and helped one another. These would lead to the behavior of sharing knowledge, information, news, and experience purchasing products from the shoppertainment platform that they used with other consumers at a higher level. This finding was consistent with the studies by Jami Pour & Taheri [28] and Li et al. [38], who indicated that trust is a mediator in the positive relationship between extraversion and knowledge-sharing behavior on social media. Jami Pour & Taheri [28], Li et al. [38], and Gerson et al. [30] reported that trust was a mediator in the positive relationship between openness to experience and knowledge-sharing behavior on social media; however, neuroticism negatively and directly affected knowledge-sharing behavior on the shoppertainment platform through trust. This result suggests that neurotic consumers would share information about online products or services on the shoppertainment platform by sharing news and presentations of products or services, including distributing the information about the products or services to other consumers at a lower or contrasting rate when the consumers did not trust or felt unsatisfied with the services. Furthermore, when these users felt that friends who were members of the shoppertainment platform were not sincere and were unwilling to help one another, the behavior of sharing knowledge, information, news, and experience purchasing products from the shoppertainment platform of which they were members with other members would decrease. This finding was consistent with Hamza et al. [87], who found that trust was a mediator for the negative relationship between neuroticism and knowledge-sharing behavior on social media. Extraversion, openness to experience, and agreeableness also had a positive indirect and direct effect on knowledge-sharing behavior on the shoppertainment platform through SWB. This result reflected that consumers with extraversion, openness to experience, and agreeableness personality traits were always friendly and trusted others’ goodness. These consumers were warm and friendly, willing to cooperate with others; they avoided conflicts, had experience purchasing products, and shared knowledge, information, and news about their experience purchasing products on the shoppertainment platform. The behavior of passing and sharing information about the products or online services on the shoppertainment platform with other members of the social media community, such as experience in purchasing products or using online services on the shoppertainment platform by exchanging information and news, presentation of information and news, and distribution of information about the products or services to other consumers, would be higher when the consumers perceived higher quality of life, satisfaction, and better psychological status from using the shoppertainment platform to buy products or services online. This finding was consistent with a study by Jami Pour & Taheri [28], which indicated that SWB was a mediator for the positive relationship between extraversion and knowledge-sharing behavior on the social media platform. The results were also in line with Jami Pour & Taheri [28] and Gerson et al. [30], who found that SWB is a mediator for the positive relationship between openness to experience and knowledge-sharing behavior on the online social media platform. Moreover, Jami Pour & Taheri [28] indicated that SWB is a mediator for a positive relationship between agreeableness and knowledge-sharing behavior on the online social media platform. Nevertheless, neuroticism negatively affected knowledge-sharing behavior on the shoppertainment platform through SWB, indicating that consumers with neuroticism personality traits would have the behavior of sharing and telling information about products or online services on the shoppertainment platform with other members of the online social community. An example was the experience of purchasing or using products or services on the shoppertainment platform HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 224 by sharing information and presenting information about products or services. Information about products or services was distributed to other consumers at a lower or contrasting level when the consumers felt dissatisfied with their lives, had a bad mental state, and perceived that they had a lower quality of life from using the shoppertainment platform to purchase products or services online. This situation would lead to sharing knowledge, information, news, and experience in purchasing products from the shoppertainment platform with other consumers at a lower level. This finding was in line with the study by Jami Pour & Taheri [28], who found that SWB is a mediator for the negative relationship between neuroticism and knowledge-sharing behavior on social media. 6. Conclusions and Suggestions 6.1. Conclusions According to the objectives, the research results showed that extraversion and openness to experience had a positive direct effect on trust, while neuroticism had a negative direct effect on trust. Extraversion had a positive direct effect on SWB, whereas neuroticism negatively affected SWB. Furthermore, trust and SWB positively affected knowledge- sharing behavior on the shoppertainment platform. In contrast, extraversion and openness to experience had a positive indirect effect on knowledge-sharing behavior on the shoppertainment platform through trust, and neuroticism had a negative indirect effect on knowledge-sharing behavior on the shoppertainment platform. Furthermore, extraversion, openness to experience, and agreeableness had a positive indirect effect on knowledge-sharing behavior on the shoppertainment platform through SWB, and neuroticism had a negative indirect effect on knowledge-sharing behavior on the shoppertainment platform through SWB. The research results led to the development of a framework used to analyze the direct and indirect effects of the consumers’ personality traits on knowledge-sharing behavior on the shoppertainment platform, with SWB and trust as mediators. This study applied the BFI-S assessment [33], trust [24, 34], SWB [17, 35], and knowledge-sharing behavior [21, 25, 36] together with a review of the literature and related previous research. This approach enabled the development of new knowledge to analyze the direct and indirect effects of the consumers’ personality traits on knowledge-sharing behavior on the shoppertainment platform, with SWB and trust as mediators. This approach could be applied as guidelines for further studies and research to correspond to the present situation where e-commerce is driven by entertainment and more factors stimulate consumers’ demands and supplies. Apart from SWB and trust as mediators for the relationship among the big five personality traits and knowledge-sharing behavior on the shoppertainment platform, there is a question of whether other factors are present. This study’s statistical analysis indicates that the direct and indirect effects of the consumers’ personality traits on knowledge-sharing behavior on the shoppertainment platform with SWB and trust as mediators had a predictive coefficient value of 0.478, which could explain the variability of the dependent variable at 47.80 percent. In other words, the other 52.20 percent might be factors or mediators (outside those explored in this study) that explain the direct and indirect effect of the consumers’ personality traits on knowledge- sharing behavior on the shoppertainment platform. The research results showed that extraversion and openness to experience had a positive direct effect on trust, while neuroticism had a negative direct effect on trust. Extraversion had a positive direct effect on SWB, whereas neuroticism negatively affected SWB. Furthermore, trust and SWB positively affected knowledge-sharing behavior on the shoppertainment platform. At the same time, extraversion and openness to experience had a positive indirect and direct effect on knowledge-sharing behavior on the shoppertainment platform through trust. Neuroticism had a negative indirect effect on knowledge-sharing behavior on the shoppertainment platform through trust. Extraversion, openness to experience, and agreeableness had a positive indirect effect on knowledge-sharing behavior on the shoppertainment platform through SWB. Neuroticism had a negative indirect effect on knowledge-sharing behavior on the shoppertainment platform through SWB. Therefore, owners of online retail stores who used the shoppertainment platforms, shoppertainment platform providers, and stakeholders needed to place importance on trust and SWB as they were mediators passing positive and negative effects from extraversion and openness to experience. Agreeableness and neuroticism led to knowledge-sharing behavior on the shoppertainment platform. These could be applied to their own businesses to upgrade the knowledge-sharing behavior of consumers in an online retail business, which would lead to their decisions to purchase products or online services through the shoppertainment platform at the end. It could also create the sustainable competitive ability of online retail business entrepreneurs in the era of the digital platform business. 6.2. Limitation and Future Research 6.2.1. Limitation of the Research This research analyzed the direct and indirect effects of consumers’ personality traits on knowledge-sharing behavior on the shoppertainment platform, with SWB and trust as mediators. The eight variables selected were extraversion, neuroticism, openness to experience, agreeableness, conscientiousness, SWB, trust, and knowledge-sharing behavior on the shoppertainment platform. The variables were selected from four concepts: the BFI-S assessment [33], trust [24, 34], SWB [17, 35], and knowledge-sharing behavior [21, 25, 36]. This approach enabled this study to analyze the direct and HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 225 indirect effects of consumers’ behavior on knowledge-sharing behavior on the shoppertainment platform with SWB and trust as mediators. Future studies might employ other variables from newly discovered or presented concepts or theories to analyze the direct and indirect effects of the consumers’ behavior and knowledge-sharing behavior on the shoppertainment platform with SWB and trust as mediators. Furthermore, this research collected data from a specific group of consumers with experience purchasing products from the TikTok shop and shared knowledge, information, news, and experience purchasing products in the TikTok community in Thailand. This study did not examine the effect of the level of the consumers’ personality traits on knowledge-sharing behavior on the shoppertainment platform, with SWB and trust as mediators. Additionally, data was not collected from other shoppertainment platforms, such as live selling through Facebook Live Shopping, Shopee Live, or LazLive. Moreover, this study was conducted only in Thailand; therefore, the results should be applied carefully, considering different demography and culture, which might affect consumers’ opinions or expectations on different shoppertainment platforms. 6.2.2. Recommendations for Future Studies  This study was conducted cross-sectionally. The data were collected over some time and were the attitudes of consumers with experience purchasing products through the TikTok shop and shared their experience in purchasing products from the TikTok Shop, and shared knowledge, information, news, and experience in purchasing products in the TikTok community at the time of the study. Consumers’ attitudes might change at times; therefore, a longitudinal study can be conducted to investigate the trends and understand consumers’ attitudes at different times.  Another direction for future work would be studying other variables expected to be mediators for both direct and indirect effects of consumers’ behavior on knowledge-sharing behavior on the shoppertainment platform. A review of previous literature and related and up-to-date research is recommended.  The framework of this research could be further investigated in the context of analyzing the direct and indirect effects of the consumers’ behavior on knowledge-sharing behavior on the shoppertainment platform with SWB and trust as mediators in other shoppertainment platforms in Thailand, such as live selling through Facebook Live Shopping, Shoppe Live, or LazLive. 7. Declarations 7.1. Data Availability Statement The data presented in this study are available in the article. 7.2. Funding and Acknowledgments This research was financially supported by the Silpakorn University Research, Innovation and Creativity Fund, in part from the Faculty of Management Science for the 2023 fiscal year. 7.3. Institutional Review Board Statement This study considered the ethics in research involving human subjects and respected the humanity of the volunteers. The research instrument was approved in the exemption review category by the Human Research Ethics Committee of Silpakorn University Research, Innovation, and Creativity Administration Office. The certificate of research approval number is REC 66.0302-026-1536. 7.4. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. 7.5. Declaration of Competing Interest The author declares that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. 8. References [1] Codagnone, C., & Martens, B. (2017). Scoping the Sharing Economy: Origins, Definitions, Impact and Regulatory Issues. Institute for Prospective Technological Studies Digital Economy Working Paper 2016/01, JRC100369, 1-36. doi:10.2139/ssrn.2783662. [2] Collier, R. B., Dubal, V. B., & Carter, C. (2017). Labor Platforms and Gig Work: The Failure to Regulate. IRLE Working Paper No. 106-17, UC Hastings Research Paper No. 251, 1-32. doi:10.2139/ssrn.3039742. [3] Almahameed, M., & Obidat, A. (2023). Exploring the critical success factors of s-commerce in social media platforms: The case of Jordan. International Journal of Data and Network Science, 7(1), 163–174. doi:10.5267/j.ijdns.2022.11.006. HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 226 [4] Ricardianto, P., Christy, E., Pahala, Y., Abdurachman, E., Soekirman, A., Purba, O. R., Prasetiawan, S. T., Wiguna, E. S., Wibawanti, A. B., & Endri, E. (2023). Digitalization and logistics service quality: Evidence from Indonesia national shipping companies. International Journal of Data and Network Science, 7(2), 781–790. doi:10.5267/j.ijdns.2023.1.011. [5] Fu, W., Sun, J., & Lee, X. (2023). Research on the Openness of Digital Platforms Based on Entropy-Weighted TOPSIS: Evidence from China. Sustainability (Switzerland), 15(4), 3322. doi:10.3390/su15043322. [6] Eisape, D. A. (2022). Transforming Pipelines into Digital Platforms: An Illustrative Case Study Transforming a Traditional Pipeline Business Model in the Standardization Industry into a Digital Platform. Journal of Open Innovation: Technology, Market, and Complexity, 8(4), 183. doi:10.3390/joitmc8040183. [7] Plantin, J. C., & de Seta, G. (2019). WeChat as infrastructure: the techno-nationalist shaping of Chinese digital platforms. Chinese Journal of Communication, 12(3), 257–273. doi:10.1080/17544750.2019.1572633. [8] Newsroom TikTok. (2022). TikTok-BCG study finds Shoppertainment to be the next USD 1 trillion opportunity for Asia Pacific. TikTok, Culver City, United States. Available online: https://newsroom.tiktok.com/en-sg/future-of-commerce-apac (accessed on April 2023). [9] Al-Khasawneh, M., Sharabati, A. A. A., Al-Haddad, S., Tbakhi, R., & Abusaimeh, H. (2022). The adoption of TikTok application using TAM model. International Journal of Data and Network Science, 6(4), 1389–1402. doi:10.5267/j.ijdns.2022.5.012. [10] Electronic Transactions Development Agency. (2022). Thailand Inter User Behavior, Bangkok, Thailand. Available online: https://www.etda.or.th/th/Useful-Resource/publications/iub2022.aspx (accessed on April 2023). (In Thai). [11] Costa, P., & McCrae, R. (2002). Personality in Adulthood: A Five-Factor Theory Perspective. Management Information Systems Quarterly - MISQ. doi: 10.4324/9780203428412. [12] olland, J. P. (2002). The Cross-Cultural Generalizability of the Five-Factor Model of Personality. The Five-Factor Model of Personality Across Cultures. International and Cultural Psychology Series, Springer, Boston, United States. doi:10.1007/978-1- 4615-0763-5_2. [13] Dinesen, P. T., Nørgaard, A. S., & Klemmensen, R. (2013). The Civic Personality: Personality and Democratic Citizenship. Political Studies, 62(1_suppl), 134–152. doi:10.1111/1467-9248.12094. [14] Mondak, J. J. (2010). Personality and the foundations of political behavior. Cambridge University Press, Cambridge, United Kingdom. doi:10.1017/CBO9780511761515. [15] Vestre, N. D. (1984). Irrational beliefs and self-reported depressed mood. Journal of Abnormal Psychology, 93(2), 239–241. doi:10.1037/0021-843X.93.2.239. [16] Hayes, N., & Joseph, S. (2003). Big 5 correlates of three measures of subjective well-being. Personality and Individual Differences, 34(4), 723–727. doi:10.1016/S0191-8869(02)00057-0. [17] Lönnqvist, J. E., & Große Deters, F. (2016). Facebook friends, subjective well-being, social support, and personality. Computers in Human Behavior, 55, 113–120. doi:10.1016/j.chb.2015.09.002. [18] Tang, J. H., Chen, M. C., Yang, C. Y., Chung, T. Y., & Lee, Y. A. (2016). Personality traits, interpersonal relationships, online social support, and Facebook addiction. Telematics and Informatics, 33(1), 102–108. doi:10.1016/j.tele.2015.06.003. [19] Correa, T., Hinsley, A. W., & de Zúñiga, H. G. (2010). Who interacts on the Web?: The intersection of users’ personality and social media use. Computers in Human Behavior, 26(2), 247–253. doi:10.1016/j.chb.2009.09.003. [20] Ahn, D., & Shin, D. H. (2013). Is the social use of media for seeking connectedness or for avoiding social isolation? Mechanisms underlying media use and subjective well-being. Computers in Human Behavior, 29(6), 2453–2462. doi:10.1016/j.chb.2012.12.022. [21] Cho, H., Chen, M., & Chung, S. (2010). Testing an Integrative Theoretical Model of Knowledge-Sharing Behavior in the Context of Wikipedia. Journal of the American Society for Information Science and Technology, 61(6), 1198–1212. doi:10.1002/asi.21316. [22] Ma, W. W. K., & Chan, A. (2014). Knowledge sharing and social media: Altruism, perceived online attachment motivation, and perceived online relationship commitment. Computers in Human Behavior, 39, 51–58. doi:10.1016/j.chb.2014.06.015. [23] Wei, L., & Gao, F. (2017). Social media, social integration and subjective well-being among new urban migrants in China. Telematics and Informatics, 34(3), 786–796. doi:10.1016/j.tele.2016.05.017. [24] Gang, K., & Ravichandran, T. (2015). Exploring the Determinants of Knowledge Exchange in Virtual Communities. IEEE Transactions on Engineering Management, 62(1), 89–99. doi:10.1109/tem.2014.2376521. [25] Hung, S. Y., Lai, H. M., & Chou, Y. C. (2015). Knowledge-sharing intention in professional virtual communities: A comparison between posters and lurkers. Journal of the Association for Information Science and Technology, 66(12), 2494–2510. doi:10.1002/asi.23339. https://www.etda.or.th/th/Useful-Resource/publications/iub2022.aspx HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 227 [26] Jer Yuen, T., & Majid, M. S. (2007). Knowledge-sharing patterns of undergraduate students in Singapore. Library Review, 56(6), 485–494. doi:10.1108/00242530710760382. [27] Panahi, S., Watson, J., & Partridge, H. (2012). Social media and tacit knowledge sharing: Developing a conceptual model. World academy of science, engineering and technology, 64, 1095-1102. [28] Jami Pour, M., & Taheri, F. (2019). Personality traits and knowledge sharing behavior in social media: mediating role of trust and subjective well-being. On the Horizon, 27(2), 98–117. doi:10.1108/OTH-03-2019-0012. [29] Ross, C., Orr, E. S., Sisic, M., Arseneault, J. M., Simmering, M. G., & Orr, R. R. (2009). Personality and motivations associated with Facebook use. Computers in Human Behavior, 25(2), 578–586. doi:10.1016/j.chb.2008.12.024. [30] Gerson, J., Plagnol, A. C., & Corr, P. J. (2016). Subjective well-being and social media use: Do personality traits moderate the impact of social comparison on Facebook? Computers in Human Behavior, 63, 813–822. doi:10.1016/j.chb.2016.06.023. [31] Steel, P., Schmidt, J., & Shultz, J. (2008). Refining the Relationship Between Personality and Subjective Well-Being. Psychological Bulletin, 134(1), 138–161. doi:10.1037/0033-2909.134.1.138. [32] DeNeve, K. M., & Cooper, H. (1998). The Happy Personality: A Meta-Analysis of 137 Personality Traits and Subjective Well- Being. Psychological Bulletin, 124(2), 197–229. doi:10.1037/0033-2909.124.2.197. [33] Gerlitz, J. Y., & Schupp, J. (2005). Assessment of big five personality characteristics in the SOEP. DIW Research Notes, German Institute of Economic Research, Berlin, Germany. (In German). [34] Hashim, K. F., & Tan, F. B. (2015). The mediating role of trust and commitment on members’ continuous knowledge sharing intention: A commitment-trust theory perspective. International Journal of Information Management, 35(2), 145–151. doi:10.1016/j.ijinfomgt.2014.11.001. [35] Diener, E., Emmons, R. A., Larsem, R. J., & Griffin, S. (1985). The Satisfaction With Life Scale. Journal of Personality Assessment, 49(1), 71–75. doi:10.1207/s15327752jpa4901_13. [36] Staples, D. S., & Webster, J. (2008). Exploring the effects of trust, task interdependence and virtualness on knowledge sharing in teams. Information Systems Journal, 18(6), 617–640. doi:10.1111/j.1365-2575.2007.00244.x. [37] McCrae, R. R., & Costa, P. T. (2003). Personality in adulthood: A five-factor theory perspective. Guilford Press. doi:10.4324/9780203428412. [38] Li, Z., Lin, Z., & Nie, J. (2022). How Personality and Social Capital Affect Knowledge Sharing Intention in Online Health Support Groups?: A Person-Situation Perspective. International Journal of Human-Computer Interaction, 38(10), 885–896. doi:10.1080/10447318.2021.1976508. [39] McCrae, R. R., & Costa, P. T. (1997). Personality Trait Structure as a Human Universal. American Psychologist, 52(5), 509– 516. doi:10.1037/0003-066X.52.5.509. [40] Tang, J., Zhang, B., & Xiao, S. (2022). Examining the Intention of Authorization via Apps: Personality Traits and Expanded Privacy Calculus Perspectives. Behavioral Sciences, 12(7), 218. doi:10.3390/bs12070218. [41] Deng, S., Lin, Y., Liu, Y., Chen, X., & Li, H. (2017). How do personality traits shape information-sharing behaviour in social media? Exploring the mediating effect of generalized trust. Information Research, 22(3), 763. [42] Tulin, M., Lancee, B., & Volker, B. (2018). Personality and Social Capital. Social Psychology Quarterly, 81(4), 295–318. doi:10.1177/0190272518804533. [43] OECD. (2013). OECD Guidelines on Measuring Subjective Well-being. Organisation for Economic Co-operation and Development Publishing, Paris, France. doi: 10.1787/9789264191655-en. [44] Vittersø, J., & Nilsen, F. (2002). The conceptual and relational structure of subjective well-being, neuroticism, and extraversion: Once again, neuroticism is the important predictor of happiness. Social Indicators Research, 57(1), 89–118. doi:10.1023/A:1013831602280. [45] Furnham, A., & Cheng, H. (1999). Personality as predictor of mental health and happiness in the East and West. Personality and Individual Differences, 27(3), 395–403. doi:10.1016/S0191-8869(98)00250-5. [46] Costa, P. T., McCrae, R. R., & Dye, D. A. (1991). Facet scales for agreeableness and conscientiousness: A revision of tshe NEO personality inventory. Personality and Individual Differences, 12(9), 887–898. doi:10.1016/0191-8869(91)90177-D. [47] Barrick, M. R., & Mount, M. K. (1991). the Big Five Personality Dimensions and Job Performance: a Meta‐Analysis. Personnel Psychology, 44(1), 1–26. doi:10.1111/j.1744-6570.1991.tb00688.x. [48] Judge, T. A., Heller, D., & Mount, M. K. (2002). Five-factor model of personality and job satisfaction: A meta-analysis. Journal of Applied Psychology, 87(3), 530–541. doi:10.1037/0021-9010.87.3.530. HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 228 [49] Rose, C. L., Murphy, L. B., Byard, L., & Nikzad, K. (2002). The Role of the Big Five Personality Factors in Vigilance Performance and Workload. European Journal of Personality, 16(3), 185–200. doi:10.1002/per.451. [50] Judge, T. A., Higgins, C. A., Thoresen, C. J., & Barrick, M. R. (1999). The big five personality traits, general mental ability, and career success across the life span. Personnel Psychology, 52(3), 621–652. doi:10.1111/j.1744-6570.1999.tb00174.x. [51] Gerber, A. S., Huber, G. A., Doherty, D., & Dowling, C. M. (2012). Personality and the Strength and Direction of Partisan Identification. Political Behavior, 34(4), 653–688. doi:10.1007/s11109-011-9178-5. [52] Boyle, G. J., Matthews, G., & Saklofske, D. H. (2008). The SAGE handbook of personality theory and assessment: Volume 1 — personality theories and models. SAGE Publications, Thousand Oaks, United States. doi:10.4135/9781849200462. [53] Kircaburun, K., Alhabash, S., Tosuntaş, Ş. B., & Griffiths, M. D. (2020). Uses and Gratifications of Problematic Social Media Use Among University Students: a Simultaneous Examination of the Big Five of Personality Traits, Social Media Platforms, and Social Media Use Motives. International Journal of Mental Health and Addiction, 18(3), 525–547. doi:10.1007/s11469-018- 9940-6. [54] Seidman, G. (2013). Self-presentation and belonging on Facebook: How personality influences social media use and motivations. Personality and Individual Differences, 54(3), 402–407. doi:10.1016/j.paid.2012.10.009. [55] Stead, H., & Bibby, P. A. (2017). Personality, fear of missing out and problematic internet use and their relationship to subjective well-being. Computers in Human Behavior, 76, 534–540. doi:10.1016/j.chb.2017.08.016. [56] Ding, C., Cheng, H. K., Duan, Y., & Jin, Y. (2017). The power of the “like” button: The impact of social media on box office. Decision Support Systems, 94, 77–84. doi:10.1016/j.dss.2016.11.002. [57] Kim, J., & Lee, J. E. R. (2011). The facebook paths to happiness: Effects of the number of Facebook friends and self-presentation on subjective well-being. Cyberpsychology, Behavior, and Social Networking, 14(6), 359–364. doi:10.1089/cyber.2010.0374. [58] Wang, S. S. (2013). “I share, therefore I Am”: Personality traits, life satisfaction, and facebook Check-Ins. Cyberpsychology, Behavior, and Social Networking, 16(12), 870–877. doi:10.1089/cyber.2012.0395. [59] Tandoc, E. C., Ferrucci, P., & Duffy, M. (2015). Facebook use, envy, and depression among college students: Is facebooking depressing? Computers in Human Behavior, 43, 139–146. doi:10.1016/j.chb.2014.10.053. [60] Ding, Q., Zhang, Y. X., Wei, H., Huang, F., & Zhou, Z. K. (2017). Passive social network site use and subjective well-being among Chinese university students: A moderated mediation model of envy and gender. Personality and Individual Differences, 113, 142–146. doi:10.1016/j.paid.2017.03.027. [61] Ishii, K. (2017). Online communication with strong ties and subjective well-being in Japan. Computers in Human Behavior, 66, 129–137. doi:10.1016/j.chb.2016.09.033. [62] Kim, B., & Kim, Y. (2017). College students’ social media use and communication network heterogeneity: Implications for social capital and subjective well-being. Computers in Human Behavior, 73, 620–628. doi:10.1016/j.chb.2017.03.033. [63] Li, C., Shi, X., & Dang, J. (2014). Online communication and subjective well-being in Chinese college students: The mediating role of shyness and social self-efficacy. Computers in Human Behavior, 34, 89–95. doi:10.1016/j.chb.2014.01.032. [64] Longstreet, P., & Brooks, S. (2017). Life satisfaction: A key to managing internet & social media addiction. Technology in Society, 50, 73–77. doi:10.1016/j.techsoc.2017.05.003. [65] Hair, J., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. (2010). Multivariate data analysis upper. Pearson Education, Upper Saddle River, United States. [66] Rovinelli, R. J., & Hambleton, R. K. (1977). On the Use of Content Specialists in the Assessment of Criterion-Referenced Test Item Validity. Tijdschrift Voor Onderwijs Research, 2, 49-60. [67] Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM). Springer, Cham, Switzerland. doi:10.1007/978-3-030-80519-7. [68] Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152. doi:10.2753/MTP1069-6679190202. [69] Chin, W.W. (2010). How to Write Up and Report PLS Analyses. Handbook of Partial Least Squares. Springer Handbooks of Computational Statistics, Springer, Berlin, Germany. doi:10.1007/978-3-540-32827-8_29. [70] Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50. doi:10.1177/002224378101800104. [71] Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20(1), 277–319. doi:10.1108/S1474-7979(2009)0000020014. https://www.google.com/search?rlz=1C1GCEA_enIR1047IR1047&sxsrf=AB5stBgzAmWBxjpAvJKlZBMZvTvezEmT3Q:1690042808060&q=Thousand+Oaks&si=ACFMAn86XkhxzOC35jo3k1ec_mUa4PwHgnEtN6tbGWMWaJ9RAhzmi115i0zJGDOG4kK1o2IDSjdE5ZFb-unyb_55Z_msGKuqb2oEZ0ha7-fbHeU1nJFR3_kMHVqUht4_lPUkVYQktjPjz7EjDwxsY9URnRyV2SgstwCasowLtZtf0-B0xcjvTHghkce44cibDGmvhVrKIQrS&sa=X&ved=2ahUKEwj13-qJ3KKAAxXtQ_EDHVi7D_EQmxMoAXoECFsQAw HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 229 [72] Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Lawrence Erlbaum, Mahwah, United States. [73] Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879–891. doi:10.3758/BRM.40.3.879. [74] Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. doi:10.1108/EBR-11-2018-0203. [75] Flavián, C., Guinalíu, M., & Jordán, P. (2022). Virtual teams are here to stay: How personality traits, virtuality and leader gender impact trust in the leader and team commitment. European Research on Management and Business Economics, 28(2), 100193. doi:10.1016/j.iedeen.2021.100193. [76] Kraus, J., Scholz, D., & Baumann, M. (2021). What’s Driving Me? Exploration and Validation of a Hierarchical Personality Model for Trust in Automated Driving. Human Factors, 63(6), 1076–1105. doi:10.1177/0018720820922653. [77] Sharan, N. N., & Romano, D. M. (2020). The effects of personality and locus of control on trust in humans versus artificial intelligence. Heliyon, 6(8), 4572. doi:10.1016/j.heliyon.2020.e04572. [78] Zhang, T., Tao, D., Qu, X., Zhang, X., Zeng, J., Zhu, H., & Zhu, H. (2020). Automated vehicle acceptance in China: Social influence and initial trust are key determinants. Transportation Research Part C: Emerging Technologies, 112, 220–233. doi:10.1016/j.trc.2020.01.027. [79] Abdullahi, A. M., Orji, R., Rabiu, A. M., & Kawu, A. A. (2020). Personality and Subjective Well-Being: Towards Personalized Persuasive Interventions for Health and Well-Being. Online Journal of Public Health Informatics, 12(1), 1-24. doi:10.5210/ojphi.v12i1.10335. [80] Han, J. H. (2020). The effects of personality traits on subjective well-being and behavioral intention associated with serious leisure experiences. Journal of Asian Finance, Economics and Business, 7(5), 167–176. doi:10.13106/JAFEB.2020.VOL7.NO5.167. [81] Kmieciak, R. (2020). Trust, knowledge sharing, and innovative work behavior: empirical evidence from Poland. European Journal of Innovation Management, 24(5), 1832–1859. doi:10.1108/EJIM-04-2020-0134. [82] Mutahar, Y., Farea, M. M., Abdulrab, M., Al-Mamary, Y. H., Alfalah, A. A., & Grada, M. (2022). The contribution of trust to academic knowledge sharing among academics in the Malaysian research institutions. Cogent Business & Management, 9(1). doi:10.1080/23311975.2022.2038762. [83] Renqiang, X., & Wende, Z. (2022). An empirical study on the impact of platform environmental factors on knowledge sharing in virtual communities. Technology in Society, 71, 102094. doi:10.1016/j.techsoc.2022.102094. [84] Wen, P., & Wang, R. (2021). Does knowledge structure matter? Key factors influencing formal and informal knowledge sharing in manufacturing. Journal of Knowledge Management, 26(9), 2275–2305. doi:10.1108/JKM-06-2021-0478. [85] Yen, C. (2022). Exploring member’s knowledge sharing intention in online health communities: The effects of social support and overload. PLOS ONE, 17(3), e0265628. doi:10.1371/journal.pone.0265628. [86] Yen, C., & Valentine, E. (2023). Building Caregivers’ Social Support on Social Network Sites Through Online Support Groups. Cyberpsychology, Behavior, and Social Networking, 26(1), 57–64. doi:10.1089/cyber.2022.0094. [87] Hamza, M. A., Rehman, S., Sarwar, A., & Choudhary, K. N. (2023). Is knowledge a tenement? The mediating role of team member exchange over the relationship of big five personality traits and knowledge-hiding behavior. VINE Journal of Information and Knowledge Management Systems, 53(1), 166–186. doi:10.1108/VJIKMS-05-2020-0084. HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 230 Appendix I “Consumer’s Personality Traits and Knowledge-sharing Behavior on Shoppertainment Platforms: The Mediating Role of Subjective Well-being and Trust” Dear Volunteer / Research Participants, This questionnaire is part of the research project “Consumer’s Personality Traits and Knowledge-sharing Behavior on Shoppertainment Platforms: The Mediating Role of Subjective Well-being and Trust ”The objective is to study the direct and indirect influences of consumer personality on knowledge-sharing behavior through shoppertainment platforms using subjective well-being and trust as mediators. As a key informant, the researcher would like to ask for your kindness in answering the questionnaire truthfully .You have the right to accept or refuse to provide information .There will be no loss of benefit or impact .Participation in the research is voluntary without compulsion .You have the right to refuse participation in the research by selecting a check in the box of not agreeing to participate in the research questionnaire .If you are willing to participate in the research and realize the rights protection guidelines already, you can check the consent to participate in the research and continue to answer the questionnaire .In addition, if the respondents feel uncomfortable providing information, they can stop the questionnaire anytime .Confidential data is only accessible to the researcher, and the data is destroyed once the research is complete .Reporting of research findings will be done in general with prudence .The name and any personal information of the respondents won’t appear in the research as a reference or in the documents related to this research before receiving permission from the respondents before using it .This research is conducted for educational purposes only .The researcher would like to thank everyone who took the time to answer this questionnaire, which will be an essential part of helping this research succeed. Researcher Do you agree to provide information by answering the questionnaire?  Agree  Disagree Sample filtering questions Have you ever shopped through the TikTok shop and shared your knowledge, information, news, and shopping experiences in the Thai TikTok community?  Yes  No Section 1: Information of respondents Please mark  in the box next to the question that you agree with your answer. 1. Gender  Male  Female  LGBTQIA+  Non applicable 2 .Age  less than 18 years old  18 - 25 years old  26 - 41 years old  42 - 55 years old  56 - 76 years old  77 years old or older 3. Highest level of education  Undergraduate  Bachelor's degree  Master's degree  PhD 4 .Experience in using the TikTok shop application  less than 1 year  1 - 3 years  3 - 5 years  5 - 7 years  More than 7 years https://dict.longdo.com/search/ANONYMOUS https://dict.longdo.com/search/ANONYMOUS HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 231 Section 2: Questions on Consumer’s Personality Traits and Knowledge-sharing Behavior on Shoppertainment Platforms: The Mediating Role of Subjective Well-being and Trust Please mark  in the box that corresponds to your level of opinion directly .The criteria for consideration are as follows: Score level 5 means strongly agree. Score level 4 means agree. Score level 3 means neutral . Score level 2 means disagree. Score level 1 means strongly disagree. What is your opinion about these statements? Opinion level 5 4 3 2 1 Knowledge-sharing behavior on the shoppertainment platform KLS1 You Like to share information or knowledge about buying products from TikTok shop with your fellow members through the TikTok community. KLS2 You often join to communicate comment or answer fellow members' questions about buying products from TikTok shop in the TikTok community. KLS3 You often post questions or create threads asking for advice on anything you want to know about purchasing products from the TikTok shop from fellow members through the TikTok community. KLS4 If possible, you would like to share your knowledge or opinions with your fellow members about purchasing products from the TikTok shop through the TikTok community. KLS5 You are someone who is willing to help or advise fellow members about purchasing products from the TikTok shop through the TikTok community. Subjective Well-being SWB1 In the future, do you think your life will be as expected? SWB2 If you have a long life, you think that you will take action to change everything around yourself. SWB3 You consider yourself an interesting person. SWB4 You think of yourself as a person who has alertness. SWB5 You think of yourself as a person who is enthusiastic. SWB6 You think of yourself as a person who is committed to life's goals. SWB7 You think of yourself as a person who is full of disappointment. SWB8 You think of yourself as someone who is full of paranoia. SWB9 You think of yourself as someone who is full of anxiety. SWB10 You think of yourself as someone who is full of sorrow. Trust TRT1 You trust the content or information about purchasing products from the TikTok shop that fellow members share through the TikTok community is considered as trust knowledge. TRT2 You feel that your fellow TikTok community members trust other fellow members. TRT3 You tend to trust your fellow TikTok community members and intend to discuss things with each other. TRT4 You feel comfortable talking with fellow TikTok community members about personal matters. TRT5 You believe that if you share your own problems .Your fellow TikTok community members are sincere to help you. Extraversion EXT1 You are a person who likes to be with many people. EXT2 You are assertive. Openness to experience OPE1 You are friendly. OPE2 You always have new creative ideas. Neuroticism NEU1 You are usually nervous. NEU2 You are easily to be mad. NEU3 You usually have a depress and pressure. HighTech and Innovation Journal Vol. 4, No. 1, March, 2023 232 Conscientiousness CON1 You are always responsible To the duty. CON2 You always achieve goals. Agreeableness AGR1 You are a good listener . AGR2 You are a simple person. AGR3 You are an altruistic person. Thank you for answering the questionnaire.