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Article

Customer Behavior as an Outcome of Social Media Marketing: The Role of Social Media Marketing Activity and Customer Experience

1
Department of Information Management, College of Management, National Kaohsiung University of Science and Technology, Kaohsiung 824005, Taiwan
2
Tansetee Charoen Mankhongkit Company, Ltd., Bangkok 10150, Thailand
3
School of Philosophy and Sociology, Lanzhou University, Lanzhou 730030, China
4
Chulalongkorn Business School, Chulalongkorn University, Bangkok 10330, Thailand
*
Authors to whom correspondence should be addressed.
Sustainability 2021, 13(1), 189; https://doi.org/10.3390/su13010189
Submission received: 24 November 2020 / Revised: 15 December 2020 / Accepted: 20 December 2020 / Published: 28 December 2020

Abstract

:
Social media has been playing an important role in marketing strategy. As a part of social media, social networking sites (SNS) can be utilized by enterprises to create direct communication and good relationships with their customers. Therefore, enterprises using SNS have to select the right marketing content to enhance strong customer relationships, which lead to their behavior generating sustainable performance for enterprises. This research considered social media marketing activity (SMMA) and Customer Experience (CX) to measure the customer’s relationship quality, which can impact customer behavioral outcomes, which are purchase intention, loyalty intention, and participation intention. The 413 online questionnaire surveys were measured and analyzed using SmartPLS 3. The results show that SMMA and CX have a significant influence on the customer relationship quality, which also leads to a positive impact on customer behavioral outcomes. This research guides enterprises that SNS’s marketing content has to follow SMMA and CX dimensions to achieve the marketing objective and generate sustainable performance for enterprises.

1. Introduction

Social media has been widely used by enterprises as a marketing strategy tool. As a part of social media, social networking sites (SNS) allow users to connect with each other. SNS possibly become a reciprocal communication medium between the enterprise and customers. SNS’s ability to reach a wide range of users, its low cost [1], and the fact it has become a part of the lives of common citizens is useful for enterprises to ensure the appeal of marketing activities, create customer awareness, and build virtual brand communities [2]. However, a survey conducted by the Ministry of Communication and Informatics Republic of Indonesia in 2019 [3] found that most people use social media platforms to sell a product or service, but when they want to buy, they prefer to use a marketplace platform. This indicates that despite the marketplace platform having advanced features, social media may still be able to encourage people to buy through social media by providing the right marketing activity content. Therefore, to get the most out of a marketing activity on social media, enterprise have to understand the importance of the content or the message’s form that they want to deliver and its impact on consumers’ experience, which can lead to achievement of the company’s marketing goals.
Social media marketing activities (SMMA) and customer experience (CX) can collectively engage in marketing on SNS. These two constructs are interrelated because rationally, all the enterprise’s marketing activities in SNS and/or experiences perceived by customers will affect the customer response and are involved in their analysis process before the purchase stage. Together, these two items can build a customer relationship that contributes to the achievement of the enterprise’s marketing objectives. In recent years, several empirical studies have been conducted to examine the acceptance of SMMA in various fields and environments, as well as CX. Yet, none of them discuss them together in one research framework. SMMA research has been done on social media users [2], luxury fashion brands [4], the airplane industry [5], and the e-commerce industry [6]. Meanwhile, research about CX has been done in many fields, such as blog environments [7,8], travel agencies [9], and social media commerce [10]. Thus, to overcome the shortcomings of previous studies, this research proposes a framework that integrates SMMA and CX.
An enterprise or anyone who wants to utilize social media as a marketing channel may provide marketing services, techniques, strategies, and designs that demonstrate social involvement and meet the community characteristics [11]. The marketing content in SNS should not only rely on commercial-oriented aspects, but should also be social-oriented or involve active interaction between users [12], which leads to deep communication and good relationships between them [13]. Creating marketing content on SNS is a challenge for enterprises since they must be able to adjust the marketing content to customer personal preferences or community preferences. Therefore, the enterprise has to select the right marketing content to enhance strong relationships, which leads to customer behavior that generates sustainable performance for enterprises.
This study set out to explore the effect of SMMA and CX on customer engagement, which is represented by the relationship quality construct, and investigate its influence on loyalty intention, purchase intention, and customer participation intention in social commerce activity. Table 1 shows the operational definition of each construct in this study. Further, attempts were made to provide insights and guides for enterprises to demonstrate whether using SNS as a marketing tool is the right decision and what kind of SNS’s marketing content they have to follow to achieve their marketing objective and generate sustainable performance for their enterprise. Social media as a marketing tool and its prospected outcomes creates a sustainable impact in terms of business performance. Abbas et al. [14] found that the use of social media marketing platforms by enterprises is able to measure and stimulate sustainable business performance. Moreover, social media is an important aspect in the context of sustainable marketing strategies to support the growth of positive customer behavior.

2. Literature Review

2.1. Social Media Marketing Activity

A recent systematic review investigated that social media is internet-based channels that enable users to interact with large or specific communities who derive value from user-generated content and a sense of connection with others, whether in real time or asynchronously [15]. The importance of using social media is gained from interactions or connections with other users and content created by an organization, enterprise, or a person. A social media marketing strategy refers to an organization’s integrated activities that turn social media communication (networks) and interactions (influences) into useful strategic means to achieve desired marketing results [16]. The scope of social media marketing is the use of social media as a way of interacting with one or a few stakeholders as a necessary tool for communication.
Kim and Ko [4] developed a construct of social media marketing (SMMA) to emphasize that using social media as a marketing tool will have a different appeal compared to traditional marketing platforms such as printed advertising, billboard, etc. The advantages of social media as a marketing tool are: first, the customer will be more entertained by the enterprise’s free marketing content and will produce social network activity. Second, customers are able to customize information searching by utilizing the default search feature on SNS, hashtags, or direct custom searching services provided by the enterprise. Third, social media is real time and fast, allowing customers to get the latest information and trends in products/services offered by the enterprise. Fourth, a social media marketing campaign makes it possible to generate direct interactions between users that can lead to, fifth, word-of-mouth effects, which includes customer willingness to pass along information seen in enterprise’s social media to the others. Thus, SMMA involves five constructs: entertainment, interaction, trendiness, customization, and word of mouth.
Kim and Ko [4] found that SMMA has a major effect on brand equity, buying intentions, etc. Furthermore, other studies have investigated SMMA in different situations and demonstrated several of its consequences. An analytical result by Chen and Lin [2] suggests that SMMA has an indirect effect on social identity and perceived value on satisfaction. Meanwhile, social identity and perceived worth directly impact satisfaction, which then affects intentional consistency, intentional involvement, and purchasing intention. Seo and Park [5] demonstrated that SMMA has a positive influence on brand awareness and brand image, suggesting that SMMA is a precedent that leads to brand equity. Sequentially, brand awareness and brand image had a positive effect on commitment and e word-of-mouth. The aforementioned prior research observed that SMMA as a second-order reflective construct, which means the indicators of a construct (entertainment, interaction, trendiness, customization, and word-of-mouth), is considered to be caused by that construct, which is SMMA.

2.2. Customer Experience

Recent literature defines customer experience (CX) as a multidimensional construct that reflects on the cognitive, emotional, behavioral, sensory, and social responses of the consumer to the enterprise’s products or services during the customer’s buying journey [17]. The products or services offered online are considered to comparatively offer a poor experience due to the inability to communicate with service personnel and a lack of face-to-face interaction [18]. However, enterprises should provide a trigger for consumers to engage in online experiences such as good information processing by customers, perceived benefits, perceived ease-of-use, etc. [19]. CX is one of the essential frameworks that should be considered by the manager to identify and act on opportunities that improve the enterprise’s competitive position [20].
CX has been developed to assist marketers to determine multiple forms of experiences. The initial work by Schmitt [21] demonstrated that there are five types of CX as a basis for overall experiential marketing analysis. All of these five types are generated by private events that occur in response to some stimuli and occur as a result of encountering, observing, or experiencing circumstances. The following section will explain these five types of experience.
  • Sense: view, sound, scent, taste, and touch are the primary senses able to influence the customer’s purchase decision. However, the SNS’s user interface lacks taste, scent, and touch, which makes visual stimuli and sound key deciding factors of an SNS’s favorability.
  • Feel: customer’s inner sensations and emotions that are possible to arise if they saw experiential texts, music, and photographs that create a direct interaction between consumers and service/product providers so that customers are willing to respond to the product and generates positive emotional feedback [22].
  • Think: this kind of experience is intended to make it possible for the user group to think in more innovative ways, allowing them to acquire a simple perception of the experience and improve their participation as a result of the marketing campaign.
  • Act: this kind of experience incorporates different choices for behaviors, including physical activities, patterns of life, and engagement. Behavioral activities in a user’s everyday life provide a permanent impression or become a direct subconscious reaction.
  • Relate: this form of perception transcends intimate and human feelings, linking the ideal self with others or cultures. After this experience, a relationship is formed between the person and a larger social structure.
Furthermore, these have been extensively investigated in an attempt to understand the impact of CX. Prior research pointed out CX as a second-order formative construct [7,8], based on the argument that each dimension of CX can be separate from each other and each indicator moves without relation to each other (no covariance), e.g., a consumer could have a high perception of sensory experiences but a low perception of relating experiences. In other words, the indicators (sense, feel, act, think, relate) are considered to be the cause of the latent variable, which is CX, separately or simultaneously. Hsu and Tsou [8] found that information credibility is essential to promoting consumer experience, which, in turn, is important to improve purchasing intention. Besides, greater involvement with the blog significantly improves the influence of CX on the purchase intention. Chen and Lin [7] reported that the sustainability of social relationships is significantly influenced by continued intention and satisfaction with blogs, while the impacts of CX and perceived value on continued intention are also important.

2.3. Relationship Quality

Relationship quality refers to the extensive overview of the strength of collaborative intentions, reciprocal disclosure, and intense follow-up communications between two parties [23,24]. Tajvidi et al. [25] explain that the key focus of the marketing relationship is the establishment of relationships between two parties, which are service providers and customers. Anastasiei and Dospinescu [26] mention that trust as part of the dimension of relationship quality depends on what kind of message was delivered by the enterprise. The quality of relations is a significant factor for a positive relationship [27]. Relationship quality is an essential factor to maintain customer loyalty [28], purchase intention [29,30], and intention to participate in social commerce [31].
Relationship quality is conceptualized as a composite or multidimensional construct and three distinct yet related components have been identified, trust, satisfaction, and commitment [24,32]. However, the research concentrates only on trust and satisfaction. The reasons why it only involved trust and satisfaction in the relationship quality construct are: first, numerous prior studies discussed relationship quality as a second-order construct of trust and satisfaction as its dimension [33,34,35,36], therefore removing commitment should have little impact on the construct measurement. Second, commitment is a relationship outcome [37] that belongs to customer loyalty [38]. Besides, some of the literature argued that commitment is not part of the relationship quality construct [39,40,41].
Most of the initial studies conceptualize relationship quality as the mediator between its antecedents and consequences. A study found that the quality of the relationship between the user and the social networking website mediates the influence of social support and website quality toward the intention to use social commerce and continuing to use social networking sites [6]. Masri et al. [42] found that the satisfaction of customers has a beneficial effect on the intention to continue. The quality of the information system has a favorable relation to satisfaction, trust, and customer continuance intention. Perceived value also impacts customer satisfaction and trust. Zhang et al. [43] suggest brand loyalty as an outcome of the quality of relationships, which are further affected by self-congruity, societal norms, quality of information, and interactivity.

2.4. Three Customer Behavioral Outcomes

The notion of relationship marketing is based on the idea that establishing and maintaining relationship quality with customers would result in positive firm-related consequences such as consumer loyalty, word-of-mouth (WOM), and sales performance [24]. Ensuring the continued usage of users is more essential. Therefore, relationship quality becomes an important role to retain existing customers because acquiring new customers costs more time and effort [44]. Other than that, the key to success for service providers is when customers are eager to give their feedback after perceiving a service.
The implementation of customer behaviors (e.g., purchase intention, loyalty intention, and participation intention) toward the enterprise is motivated by the concept of relationship quality [29,30,31,45]. Customers like to associate themselves with the enterprise because beneficial values of their own and those of the company overlap with each other. Furthermore, customers are willing to support the company and if they observe any deficiency in service or have any suggestions for improvement, as a customer, they like to share this with the company instead of just switching to another company.
This research considered purchase intention, loyalty intention, and participation intention as customer behaviors that reflect the benefit of the utilization of SNS as a marketing tool. Purchase intention is the desire of the customer to buy a product [46]. Schiffman and Kanuk [47] argued that purchasing willingness is a possibility of a customer buying a certain product, with a stronger likelihood of them buying it. In buying products, customers will look for relevant knowledge based on their perceptions and the surrounding environment. If a certain amount of knowledge has been collected, customers tend to analyze, consider, compare, and end in actual purchasing. Previous research has demonstrated that purchasing intentions can be seen as a primary indicator of customer behavior [48,49]. Customer loyalty is a customer’s long-standing ability to purchase from a seller [50]. Customer loyalty assures the company’s continuing profit [51]. It estimates long term financial advantages. Committed customers are essential to upholding a high degree of contact and good ties to the enterprise [52]. The customers who rely more on a particular enterprise give less exposure to competitors. Thus, competitor marketing campaigns will not impact their purchasing choices and they will remain loyal to the company [53,54]. From a marketing point of view, intention to participate should be considered if the organization wishes to accomplish good marketing across the community [55]. Participation intention is the desire of members to take part in the enterprise’s events, program, or discussion [2], which leads to the suggestion and recommendation of the product or service to non-members [31].

3. Hypotheses Development

The main purpose of marketing activity is to build communication between the corporation and its customers, which can lead to a good relationship among them and creates interest in what the corporation offers. Social media is one of the marketing tools to enhance customer engagement [59]. In the online shopping context, trust is an important thing among the customer because of the lack of product tangibility [60]. Trust was also influenced by the reputation of the enterprise on social commerce activity [61]. Meanwhile, Zhan et al. [62] found that the community’s life satisfaction was influenced by their social media usage. On the other hand, corporation online convenience is able to enhance the level of customer satisfaction [63]. Both trust and satisfaction are considered as a dimension of relationship quality [64,65]. This research proposed H1 based on the above discussion.
Hypothesis 1 (H1).
SMMA is positively related to relationship quality.
Nowadays, customers can easily interact with corporations through any media, including social media. These situations encourage the corporation to make some adjustments or adapt to create and deliver a positive CX. Rajaobelina [9] asserted that the CX contributes to enhancing the relationships between the corporation and its customers. Positive CX can serve as a parameter for enhancing relationship quality to develop a marketing strategy [66]. This research proposed H2 based on the above discussion.
Hypothesis 2 (H2).
CX is positively related to relationship quality.
The massive development of digital media urges enterprises to engage their customers in digital media, especially social media, to manage the relationship and raise interactive marketing, which can drive profit. In the context of social commerce, company profits are driven by consumer behavior, including customer purchase intention, loyalty, and customer participation intention. As a part of the dimension relationship quality, trust has a positive influence on purchase intention [30,58,67] and satisfaction has a significant influence on purchase intention [29,68,69]. Then, customer loyalty has become an important outcome that represents a good relationship between the corporation and its customers [43,45]. Besides, customer interactions across virtual/physical channels will influence sustainable customer loyalty [70]. A customer’s intention to share their experience, knowledge, and information about a particular product and service, as well as take part in enterprise events, discussions, or programs are characteristic of social commerce. The research found that customer intention to participate in social commerce was influenced by the relationship quality of the corporate and customer [31,71]. Moreover, satisfaction as one of the relationship quality constructs also influences intention to participate [2], as well as trust, which plays a critical role in improving consumer intention to participate [72].
Based on the above discussion, this research argues that if customers associate themselves with the enterprise’s brand culture in social media, they can improve the positive relationships of users with the brands and avoid the purchase of rivalry goods. In other words, this situation is able to enhance the customer’s purchase intention because of a good connection with the enterprise or brand. Moreover, good relations among the customers and enterprise can create loyal customers as well as customer willingness to participate in an event or program held by the enterprise. Thus, this research proposed H3–H5 as follows.
Hypothesis 3 (H3).
Relationship quality is positively related to purchase intention.
Hypothesis 4 (H4).
Relationship quality is positively related to loyalty intention.
Hypothesis 5 (H5).
Relationship quality is positively related to participation intention.

4. Research Method

The method used for gathering samples’ data was a self-assessment online questionnaire survey from January 2020 until July 2020. The participant in this research is an Indonesian social media user who had experience using social media as a buying platform. Based on the survey conducted by We are Social in 2020 [73], Indonesia is ranked third in the world in terms of growth in social media use after China and India, who reached a 15 million and 130 million user growth in one year, respectively. Therefore, Indonesian citizens are appropriate to represent these research respondents. Data filtering was conducted to exclude the non-experienced users of social commerce. Of the 539 respondents who intended to fill out our questionnaire, only 413 respondents were found to have experience with social commerce. Table 2 provides the demographic composition of the respondents.
The questionnaire was divided into two parts, demographic information and hypotheses measurements questions. This study has drawn up the entire framework based on the respective frameworks used in previous research (as shown in Figure 1). The questions were based on the initial study and pre-validated scales. The validity of the questionnaire contents was subsequently properly verified. Seven Likert scales were adopted in this research to enhance the accuracy of the scales [74].
In the overview section of the questionnaire, to boost the participant’s willingness and motivation, the respondents were notified that the 20 participants who submitted a legitimate questionnaire would be rewarded a bonus as a mobile credit or an e-wallet balance. Each user was asked to provide an e-mail address to make sure that they did not participate in the survey multiple times.
VIF analysis was conducted to check the multicollinearity between the construct [75] and make sure that the model is relevant [76]. The SmartPLS calculation result provides the inner VIF value. Hair et al. [77] mention that VIF values for the variables have to be < 5.0. As shown in Table 3, the inner VIF value in this research ranged from 1.000 to 3.306, which means there are no potential multicollinearity effects between the latent construct.

5. Data Analysis

Measurement and analysis of partial least squares (PLS) was conducted using SmartPLS 3. Table 4 explains the measurements items used in this study. Reliability and validity analysis were done in the measurement stages and the path coefficients and explaining the strength of the structural model were tested and checked in the analysis stages. These two stages aimed to affirm the reliability and validity of the constructs and thus, to check the interactions between them [78]. This research explored the causal interaction between the practices of SMMA, CX, relationship quality, purchase intention, loyalty intention, and participation intention, which each contained a variety of measuring items discussed in previous studies.
PLS was more acceptable for this research than another structural equation modeling (SEM) analysis approach for the following reasons. First, PLS was ideal for the discussion of causal relations between variables and is able to handle the constructed model as well as measure items simultaneously [79]. Moreover, PLS can evaluate complicated predictive models (including multiple research constructs and variables) [80]. This research framework observed multiple paths and relations of SMMA, CX, relationship quality, and three behavioral outcomes, which is considered a complex model. To conduct the PLS analysis, the size of the sample should be at least 5 to 10 times the total path in the model. In this research, the size of the sample was 413 and the number of total paths was 5, which meets the fit and is suitable for PLS analysis [81]. Second, prior research identified CX as a second-order formative construct [7,9]. Furthermore, PLS is superior to covariance-based SEM because PLS can simultaneously process reflective indicators and formative indicators [80,82]. Meanwhile, other analytical methods can only assess reflective indicators.
Despite its advantages, the PLS method has several drawbacks [83]. First, PLS-SEM optimizes the parameters of the model and then estimates the structural model path coefficients in the second step. To solve this problem, several researchers who were well proficient in social media marketing thoroughly verified the questionnaire to make sure that the measurement items are suitable for this research, resulting in a proper finding. Another problem restricting the use of PLS-SEM for testing and confirmation is that there is no appropriate global measurement of model fit. Thus, this research adopted goodness of fit obtained from a manual calculation based on a proven prior study.

5.1. Outer Model and Validation

Three basic aspects tested in the outer model were reliability analysis, convergent validity, and discriminant validity. All constructs had 0.7 and above composite reliability criterion values, which suggested acceptable construct reliability. In Fornell’s and Larcker’s [84] suggestions, a construct has convergent validity if the predictor factor loading exceeds 0.5 and the AVE exceeds 0.5. Factor loads and reliability test results are presented in Table 5 for the different construct items. Furthermore, the level of discrimination between measured variables and various construct criteria is identified in discriminant validity. When the factor load of each latent item for each assigned construct is higher than the factor loadings of each other construct, each variable implied an appropriate discrimination validity [77]. The analysis of cross-loads and factor loadings suggest strong discriminant validity, which is provided in Table 6.
Tenenhaus et al. [85] demonstrated how to understand the Goodness of Fit (GOF) of the proposed model on the following calculation:
G O F = A V E ¯ × R 2 ¯ = 0.79 × 0.65 = 0.77 .
According to the aforementioned result, the GOF is 0.77, which reaches the 0.36 cut-off criteria for a large impact size [86].

5.2. Inner Model Result and Hypotheses Testing

The inner PLS model analysis was used in this research to test the hypotheses. Table 7 explains the hypotheses testing result, path coefficients, p-value, and t-value. The results show that all hypotheses are significant and have a positive value. Figure 2 also illustrates the results of the hypotheses.
Table 7 and Figure 2 presented that SMMA has a positive and significant effect on relationship quality, supporting H1 (SMMA → RQ: β = 0.330, t-value = 5.880). Furthermore, the analysis showed that CX positively and significantly impacts relationship quality, which supports H2 (CX → RQ: β = 0.430, t-value = 6.775). Finally, relationship quality significantly and positively affected purchase intention, loyalty intention, and participate intention (RQ → INT: β = 0.741, t-value = 26.410; RQ → LYL: β = 0.749, t-value = 25.221; RQ → INP: β = 0.676, t-value = 25.221).

5.3. Testing of Mediation Effects

Path analysis and the Sobel test were used to determine whether the mediating variable discussed in this research was statistically significant or not [87]. Table 8 shows that the Sobel test result was used to obtain the Z value and estimated p-values as determinants of whether an important indirect effect existed. All mediator’s z-values are greater than 1.96, which shows a significant mediation impact between the independent and the dependent variable.

6. Discussion

This research was focused on the integration of Kim and Ko’s [4] SMMA and Schmitt’s [21] CX. Then, both were combined with relationship quality as the influencing factors of the three kinds of customer behavior outcomes to investigate the social networking sites as marketing tools. Good marketing activity and good customer experience relies on what kind of content (message) is provided on social media by the marketing manager [26]. There are some important findings and contributions from the empirical outcomes of this research, both for the academic and practitioner.

6.1. Theoretical Implications

This study contributes to the literature on SMMA and CX in several ways. Firstly, we provide a holistic model of the antecedents to the customer behavior outcomes (purchase, loyalty, and participation) in responding to the SNS marketing content. Although social media marketing has gained research interest, a holistic model explaining the formation of intention, loyalty, and participation in such platforms has remained absent from the existing research. Second, this study is the first to simultaneously confirm SMMA and CX of SNS marketing to relationship quality. Although it is widely acknowledged by researchers that SMMA can lead to relationship quality [2,4,5], as well as CX to relationship quality [7,9,17], our study adds to these studies by integrating the SMMA and CX in the framework to relationship quality in the context of social media marketing. This research also contributes significantly to the related literature by drawing from a new dataset on an existing marketing survey.

6.2. Managerial Implications

This study contributes specifically to enterprises who consider utilizing social media as their marketing channel. The results suggest to marketing managers the importance of creating social media-based content or messages that influence customers’ behavioral outcomes and leads to marketing objective goals. Based on Hypothesis 1, testing found that SMMA has a significant influence on relationship quality, thus for the marketing manager as an SNS marketing content organizer, first, they have to create content or messages, such as combining the content with an interesting story, music, layout design, or other entertainment stuff, with the main purpose of evoking customer happiness, excitement, or entertainment after seeing the company’s marketing content [88]. Second, creating interaction marketing content is one of the important factors, for example, by utilizing the SNS (e.g., Instagram or Facebook) stories features, marketing managers are able to create Q&A sessions, multiple-choice, and so on, which can create two-way direct communication between the customer and enterprise. Third, published marketing content has to be based on the current situation and new, whether it is related to the company itself or other things outside the company that indicates the current situation, however it must be relevant. For example, posting what is new in the store, releasing special Christmas items at the end of the year, etc., which can make customers feel up-to-date by seeing this kind of content. Fourth, as much as possible, the layout of the content/marketing posts on SNS is easy to understand, clear, and neat so that customers can easily find the product information they want. The hashtag feature is also very useful for customers when they want to find product information based on related keywords [89]. Finally, the idea of SNS marketing content should indirectly invite or even force customers to share it elsewhere, such as on their personal SNS account, online community group, etc. For example, by giving a bonus or discount if they share it on their page, tag three of their friends on SNS, etc. This content establishment strategy enhances the relationship quality among the enterprise and customers.
Hypothesis 2 testing found that CX has a significant positive influence on relationship quality. Since CX has become a significant predictor, arranging SNS marketing content based on what builds up the CX construct is a necessary move. In designing content marketing, managers must be able to reap the benefits of the five human-possessed senses to drive them to the purchasing stage. However, using SNS, people cannot experience the sense of taste, the sense of smell, and the sense of touch. The remaining two senses, the sense of seeing and the sense of hearing, must be completely used or perhaps make up for the lack of the three senses mentioned before. Hultén et al. [90] found that a digital object could possibly replicate the sense of touch, sense of smell, or sense of taste by providing a well “described” image/figure. Therefore, photography skills, graphic design skills, and visual commination skills are needed. Other than that, creating SNS marketing content that touches customers’ sensations and emotions is necessary. When marketing content successfully touches customers’ emotions, they are able to think, consider, and easily understand the marketing message. Customers who favorably perceive marketing messages are willing to act or express their behavior, which supports the enterprise’s objective and creates a good relationship between the customer and enterprise. By designing the SNS marketing content based on the CX approaches, relationship quality between the enterprise and its customers can certainly be developed.
Together, well organized SNS’s marketing content based on the SMMA and CX dimensions will create a strong relationship between customer and enterprise, which leads to the customer’s behavior. Relationship quality is the main objective of relational marketing [57] and can minimize effort and cost by retaining current customers [44]. Based on Hypotheses 3–5, we found that managing relationship quality is essential because good relationship quality between customer and enterprise will enhance customer willingness to purchase, willingness to be a loyal customer, and willingness to participate in the enterprise program. Consumers’ product information sources have shifted from traditional media to social media. Therefore, in this social media era, enterprises need to understand how the quality of marketing content, type, and times help to achieve marketing objectives and retain sustainable performance for enterprises. Moreover, marketing objectives can be achieved by creating a brand image that meets each person’s characteristics, some of which also depend on their marketing activities and marketing content designs, which leads to a good perceived customer experience [91]. The findings of the mediation test confirm that relationship quality is important because if the marketing manager is able to help consumers to associate themselves with the enterprise’s brand culture, they can improve the positive relationships of users with the brands they want and thus, avoid the purchase of rivalry goods. Moreover, customers can be retained as loyal customers and may participate in any event or program held by the enterprise because of a strong connection between them.

7. Conclusions and Future Work

In this digital age, marketers are increasingly aware that marketing content should not only give priority to commercial-oriented aspects, but also give more priority to social-oriented aspects or highlight interactions between sellers and buyers. Utilizing social media as a marketing tool is a good choice as long as the marketing content fulfills the parameters shown in the SMMA and CX. Therefore, marketers have to think critically and creatively to establish great marketing content that meets the personal preference of the target customer. All of these activities impact the quality of the relationship between customer and enterprise and managing a good customer–enterprise relationship is a necessary strategy to achieve the marketing objective. Furthermore, three behavioral outcomes (purchase intention, loyalty intention, and participation intention) would go positively hand in hand with relationship quality, which was previously structured by appropriate marketing content.
Despite attempts to undertake a comprehensive research framework, research methodology, and data collection, many shortcomings could be discussed in future studies. First, the differences among various types of SNS were not analyzed. In particular, regarding the recent trending SNS “TikTok”, some marketers have started to use this platform as a marketing medium. Thus, future studies will require participants from different platforms to provide findings and consequences that are more inclusive. Second, people tend to have biases for particular social platforms in various regions or countries. Further analysis will investigate whether people from different countries or societies prefer different social media and whether they have particular motives and need social media analysis from a regional perspective. Third, further deepening the relationship between consumer behavior and social media is possible by using actual-technological assessment, such as eye-tracking movement technology, to understand user experience [92] and to strengthen self-psychological assessment. Finally, business is not only about how customers are managed, but also facilitates social collaborative interactions and eases the dialog that respects customers [93]. Therefore, further study needs to find out the link between social media and customer relationship management (CRM) to understand deeply how to maintain relationship quality between an enterprise and its customers technically by applying CRM through social media.

Author Contributions

Conceptualization, A.W. and S.-C.C.; methodology, A.W., Y.M., and A.R.; validation, Y.M. and A.R.; formal analysis, A.W. and U.W.; investigation, A.W.; writing—original draft preparation, A.W., S.-C.C., U.W., Y.M., and A.R.; writing—review and editing, A.W., S.-C.C., U.W., Y.M., and A.R.; visualization, S.-C.C. and U.W.; supervision, S.-C.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Ethical review and approval was not required for this study on human participants in accordance with the local legislation and institutional requirements.

Informed Consent Statement

Written informed consent from the patients/participants was not required to participate in this study in accordance with the national legislation and the institutional requirements.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation, to any qualified researchers.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Ajina, A.S. The perceived value of social media marketing: An empirical study of online word of mouth in Saudi Arabian context. Entrep. Sustain. Issues 2019, 6, 1512–1527. [Google Scholar] [CrossRef] [Green Version]
  2. Chen, S.-C.; Lin, C.-P. Understanding the effect of social media marketing activities: The mediation of social identification, perceived value, and satisfaction. Technol. Forecast. Soc. Chang. 2019, 140, 22–32. [Google Scholar] [CrossRef]
  3. Research and Development Center—Ministry of Communication and Informatics. Survey Penggunaan TIK Serta Implikasinya Terhadap Aspek Sosial, Budaya dan Ekonomi Masyarakat (Survey on the Use of ICT and Its Implications for the Social, Cultural and Economic Aspects of Society). Jakarta, Indonesia. 2019. Available online: https://balitbangsdm.kominfo.go.id/?mod=publikasi&a=dl&page_id=705&cid=9&download_id=232 (accessed on 21 November 2020).
  4. Kim, A.J.; Ko, E. Do social media marketing activities enhance customer equity? An empirical study of luxury fashion brand. Bus. Res. 2012, 65, 1480–1486. [Google Scholar] [CrossRef]
  5. Seo, E.-J.; Park, J.-W. A study on the effects of social media marketing activities on brand equity and customer response in the airline industry. J. Air Transp. Manag. 2018, 66, 36–41. [Google Scholar] [CrossRef]
  6. Yadav, M.; Rahman, Z. The influence of social media marketing activities on customer loyalty: A study of e-commerce industry. Benchmarking 2018, 25, 3882–3905. [Google Scholar] [CrossRef]
  7. Chen, S.-C.; Lin, C.-P. The impact of customer experience and perceived value on sustainable social relationship in blogs: An empirical study. Technol. Forecast. Soc. Chang. 2015, 96, 40–50. [Google Scholar] [CrossRef]
  8. Hsu, H.Y.; Tsou, H.-T. Understanding customer experiences in online blog environments. Int. J. Inf. Manag. 2011, 31, 510–523. [Google Scholar] [CrossRef]
  9. Rajaobelina, L. The Impact of Customer Experience on Relationship Quality with Travel Agencies in a Multichannel Environment. J. Travel Res. 2017, 57, 206–217. [Google Scholar] [CrossRef]
  10. Wijaya, I.W.K.; Rai, A.A.G.; Hariguna, T. The impact of customer experience on customer behavior intention use in social media commerce, an extended expectation confirmation model: An empirical study. Manag. Sci. Lett. 2019, 9, 2009–2020. [Google Scholar] [CrossRef]
  11. Ruangkanjanases, A.; Hsu, S.-L.; Wu, Y.J.; Chen, S.-C.; Chang, J.-Y. What Drives Continuance Intention towards Social Media? Social Influence and Identity Perspectives. Sustainability 2020, 12, 7081. [Google Scholar] [CrossRef]
  12. Ko, H.-C. Social desire or commercial desire? The factors driving social sharing and shopping intentions on social commerce platforms. Electron. Commer. Res. Appl. 2018, 28, 1–15. [Google Scholar] [CrossRef]
  13. Wang, W.Y.; Pauleen, D.J.; Zhang, T. How social media applications affect B2B communication and improve business performance in SMEs. Ind. Mark. Manag. 2016, 54, 4–14. [Google Scholar] [CrossRef]
  14. Abbas, J.; Mahmood, S.; Ali, G.; Raza, M.A.; Aman, J.; Bano, S.; Nurunnabi, M. The effects of corporate social responsibility practices and environmental factors through a moderating role of social media marketing on sustainable performance of business firms. Sustainability 2019, 11, 3434. [Google Scholar] [CrossRef] [Green Version]
  15. Carr, C.T.; Hayes, R.A. Social Media: Defining, Developing, and Divining. Atl. J. Commun. 2015, 23, 46–65. [Google Scholar] [CrossRef]
  16. Li, F.; Larimo, J.; Leonidou, L.C. Social media marketing strategy: Definition, conceptualization, taxonomy, validation, and future agenda. J. Acad. Mark. Sci. 2020, 48, 1–20. [Google Scholar] [CrossRef]
  17. Lemon, K.N.; Verhoef, P.C. Understanding customer experience throughout the customer journey. J. Mark. 2016, 80, 69–96. [Google Scholar] [CrossRef]
  18. McLean, G.; Wilson, A. Evolving the online customer experience... is there a role for online customer support? Comput. Hum. Behav. 2016, 60, 602–610. [Google Scholar] [CrossRef] [Green Version]
  19. Rose, S.; Hair, N.; Clark, M. Online Customer Experience: A Review of the Business-to-Consumer Online Purchase Context. Int. Int. J. Manag. Rev. 2011, 13, 24–39. [Google Scholar] [CrossRef]
  20. Keiningham, T.; Aksoy, L.; Bruce, H.L.; Cadet, F.; Clennell, N.; Hodgkinson, I.R.; Kearney, T. Customer experience driven business model innovation. J. Bus. Res. 2020, 116, 431–440. [Google Scholar] [CrossRef]
  21. Schmitt, B. Experiential Marketing. J. Mark. Manag. 1999, 15, 53–67. [Google Scholar] [CrossRef]
  22. Kim, D.; Perdue, R.R. The effects of cognitive, affective, and sensory attributes on hotel choice. Int. J. Hosp. Manag. 2013, 35, 246–257. [Google Scholar] [CrossRef]
  23. Crosby, L.A.; Evans, K.R.; Cowles, D. Relationship Quality in Services Selling: An Interpersonal Influence Perspective. J. Mark. 1990, 54, 68–81. [Google Scholar] [CrossRef]
  24. Palmatier, R.W.; Dant, R.P.; Grewal, D.; Evans, K.R. Factors influencing the effectiveness of relationship marketing: A meta-analysis. J. Mark. 2006, 70, 136–153. [Google Scholar] [CrossRef]
  25. Tajvidi, M.; Richard, M.-O.; Wang, Y.; Hajli, N. Brand co-creation through social commerce information sharing: The role of social media. J. Bus. Res. 2018, 121, 1–11. [Google Scholar] [CrossRef] [Green Version]
  26. Anastasiei, B.; Dospinescu, N. Facebook Advertising, Relationship between Types of Message, Brand Attitude and Perceived Buying Risk. Ann. Econ. Ser. 2017, 6, 18–26. [Google Scholar]
  27. Bejou, D.; Wray, B.; Ingram, T.N. Determinants of relationship quality: An artificial neural network analysis. J. Bus. Res. 1996, 36, 137–143. [Google Scholar] [CrossRef]
  28. Giovanis, A.; Athanasopoulou, P.; Tsoukatos, E. The role of service fairness in the service quality—Relationship quality—Customer loyalty chain: An empirical study. J. Serv. Theory Pr. 2015, 25, 744–776. [Google Scholar] [CrossRef]
  29. Chen, C.-C.; Chang, Y.-C. What drives purchase intention on Airbnb? Perspectives of consumer reviews, information quality, and media richness. Telemat. Inform. 2018, 35, 1512–1523. [Google Scholar] [CrossRef]
  30. Oliveira, T.; Alhinho, M.; Rita, P.; Dhillon, G. Modelling and testing consumer trust dimensions in e-commerce. Comput. Hum. Behav. 2017, 71, 153–164. [Google Scholar] [CrossRef] [Green Version]
  31. Hajli, M.N. The role of social support on relationship quality and social commerce. Technol. Forecast. Soc. Chang. 2014, 87, 17–27. [Google Scholar] [CrossRef]
  32. Garbarino, E.; Johnson, M.S. The different roles of satisfaction, trust, and commitment in customer relationships. J. Mark. 1999, 63, 70–87. [Google Scholar] [CrossRef]
  33. Rajaobelina, L.; Bergeron, J. Antecedents and consequences of buyer-seller relationship quality in the financial services industry. Int. J. Bank Mark. 2009, 27, 359–380. [Google Scholar] [CrossRef]
  34. Hsu, C.-L.; Chen, M.-C.; Kikuchi, K.; Machida, I. Elucidating the determinants of purchase intention toward social shopping sites: A comparative study of Taiwan and Japan. Telemat. Inform. 2017, 34, 326–338. [Google Scholar] [CrossRef]
  35. Chen, S.-C.; Liu, S.-C.; Li, S.-H.; Yen, D.C. Understanding the mediating effects of relationship quality on technology acceptance: An empirical study of E-appointment system. J. Med. Syst. 2013, 37, 9981. [Google Scholar] [CrossRef] [PubMed]
  36. Chen, S.-C.; Jong, D.; Lai, M.-T. Assessing the relationship between technology readiness and continuance intention in an e-appointment system: Relationship quality as a mediator. Med. Syst. 2014, 38, 76. [Google Scholar] [CrossRef] [PubMed]
  37. Kim, W.G.; Lee, Y.-K.; Yoo, Y.-J. Predictors of Relationship Quality and Relationship Outcomes in Luxury Restaurants. J. Hosp. Tour. Res. 2006, 30, 143–169. [Google Scholar] [CrossRef]
  38. Liu, C.-T.; Guo, Y.M.; Lee, C.-H. The effects of relationship quality and switching barriers on customer loyalty. Int. J. Inf. Manag. 2011, 31, 71–79. [Google Scholar] [CrossRef]
  39. Boles, J.S.; Johnson, J.T.; Barksdale, H.C. How Salespeople Build Quality Relationships: A Replication and Extension. J. Bus. Res. 2000, 48, 75–81. [Google Scholar] [CrossRef]
  40. Jap, S.D.; Manolis, C.; A Weitz, B. Relationship Quality and Buyer–Seller Interactions in Channels of Distribution. J. Bus. Res. 1999, 46, 303–313. [Google Scholar] [CrossRef]
  41. Holmlund, M. A definition, model, and empirical analysis of business-to-business relationship quality. Int. J. Serv. Ind. Manag. 2008, 19, 32–62. [Google Scholar] [CrossRef] [Green Version]
  42. Masri, N.W.; You, J.-J.; Ruangkanjanases, A.; Chen, S.-C.; Pan, C.-I. Assessing the effects of information system quality and relationship quality on continuance intention in e-tourism. Int. J. Environ. Res. Public Health 2020, 17, 174. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Zhang, K.Z.; Benyoucef, M.; Zhao, S.J. Building brand loyalty in social commerce: The case of brand microblogs. Electron. Commer. Res. Appl. 2016, 15, 14–25. [Google Scholar] [CrossRef]
  44. Tsai, H.-T.; Huang, H.-C. Determinants of e-repurchase intentions: An integrative model of quadruple retention drivers. Inf. Manag. 2007, 44, 231–239. [Google Scholar] [CrossRef]
  45. Choi, Y.G.; Hyun, S.S. Relationships between brand experiences, personality traits, prestige, relationship quality, and loyalty An empirical analysis of coffeehouse brands Analysis of coffeehouse brands 1185. Int. J. Contemp. Hosp. Manag. 2017, 29, 1185–1202. [Google Scholar] [CrossRef]
  46. Dodds, W.B.; Monroe, K.B.; Grewal, D. Effects of Price, Brand, and Store Information on Buyers’ Product Evaluations. J. Mark. Res. 1991, 28, 307–319. [Google Scholar] [CrossRef]
  47. Schiffman, L.G.; Kanuk, L.L. Consumer Behavior, 10th ed.; Prentice Hall: Upper Saddle River, NJ, USA, 2009. [Google Scholar]
  48. Hee, Y.K.; Jae-Eun, C. Consumer purchase intention for organic personal care products. J. Consum. Mark. 2011, 28, 40–47. [Google Scholar] [CrossRef]
  49. Lu, Y.; Zhao, L.; Wang, B. From virtual community members to C2C e-commerce buyers: Trust in virtual communities and its effect on consumers’ purchase intention. Electron. Commer. Res. Appl. 2010, 9, 346–360. [Google Scholar] [CrossRef]
  50. Edvardsson, B.; Johnson, M.D.; Gustafsson, A.; Strandvik, T. The effects of satisfaction and loyalty on profits and growth: Products versus services. Total. Qual. Manag. 2000, 11, 917–927. [Google Scholar] [CrossRef]
  51. Flavián, C.; Guinalíu, M.; Gurrea, R. The role played by perceived usability, satisfaction and consumer trust on website loyalty. Inf. Manag. 2006, 43, 1–14. [Google Scholar] [CrossRef]
  52. Hapsari, R.; Clemes, M.D.; Dean, D. The impact of service quality, customer engagement and selected marketing constructs on airline passenger loyalty. Int. J. Qual. Serv. Sci. 2017, 9, 21–40. [Google Scholar] [CrossRef]
  53. Wirtz, J.; Ambtman, A.D.; Bloemer, J.; Horváth, C.; Ramaseshan, B.; Van De Klundert, J.; Canli, Z.G.; Kandampully, J. Managing brands and customer engagement in online brand communities. J. Serv. Manag. 2013, 24, 223–244. [Google Scholar] [CrossRef] [Green Version]
  54. Islam, J.U.; Rahman, Z. Linking Customer Engagement to Trust and Word-of-Mouth on Facebook Brand Communities: An Empirical Study. J. Internet Commer. 2016, 15, 40–58. [Google Scholar] [CrossRef]
  55. Algesheimer, R.; Dholakia, U.M.; Herrmann, A. The Social Influence of Brand Community: Evidence from European Car Clubs. J. Mark. 2005, 69, 19–34. [Google Scholar] [CrossRef]
  56. Homburg, C.; Jozić, D.; Kuehnl, C. Customer experience management: Toward implementing an evolving marketing concept. J. Acad. Mark. Sci. 2017, 45, 377–401. [Google Scholar] [CrossRef]
  57. Tajvidi, M.; Wang, Y.; Hajli, N.; Love, P.E. Brand value Co-creation in social commerce: The role of interactivity, social support, and relationship quality. Comput. Hum. Behav. 2017, 115, 105238. [Google Scholar] [CrossRef] [Green Version]
  58. Bonsón, E.; Carvajal-Trujillo, E.; Escobar-Rodríguez, T. Escobar-Rodríguez, Influence of trust and perceived value on the intention to purchase travel online: Integrating the effects of assurance on trust antecedents. Tour. Manag. 2015, 47, 286–302. [Google Scholar] [CrossRef]
  59. Dwivedi, Y.K.; Ismagilova, E.; Hughes, D.L.; Carlson, J.; Filieri, R.; Jacobson, J.; Jain, V.; Karjaluoto, H.; Kefi, H.; Krishen, A.S.; et al. Setting the future of digital and social media marketing research: Perspectives and research propositions. Int. J. Inf. Manag. 2020, 53, 102168. [Google Scholar] [CrossRef]
  60. Haque, U.N.; Mazumder, R. A Study on the Relationship Between Customer Loyalty and Customer Trust in Online Shopping. Int. J. Online Mark. 2020, 10, 1–16. [Google Scholar] [CrossRef]
  61. Ben Yahia, I.; Al-Neama, N.; Kerbache, L. Investigating the drivers for social commerce in social media platforms: Importance of trust, social support and the platform perceived usage. J. Retail. Consum. Serv. 2018, 41, 11–19. [Google Scholar] [CrossRef]
  62. Zhan, L.; Sun, Y.; Wang, N.; Zhang, X. Understanding the influence of social media on people’s life satisfaction through two competing explanatory mechanisms. Aslib J. Inf. Manag. 2016, 68, 347–361. [Google Scholar] [CrossRef]
  63. Duarte, P.; Silva, S.C.E.; Ferreira, M.B. How convenient is it? Delivering online shopping convenience to enhance customer satisfaction and encourage e-WOM. J. Retail. Consum. Serv. 2018, 44, 161–169. [Google Scholar] [CrossRef]
  64. Alejandro, T.B.; Souza, D.V.; Boles, J.S.; Ribeiro, Á.H.P.; Monteiro, P.R.R. The outcome of company and account manager relationship quality on loyalty, relationship value and performance. Ind. Mark. Manag. 2011, 40, 36–43. [Google Scholar] [CrossRef]
  65. Zhang, Y.; Fang, Y.; Wei, K.-K.; Ramsey, E.; McCole, P.; Chen, H. Repurchase intention in B2C e-commerce—A relationship quality perspective. Inf. Manag. 2011, 48, 192–200. [Google Scholar] [CrossRef]
  66. Fernandes, T.; Pinto, T. Relationship quality determinants and outcomes in retail banking services: The role of customer experience. J. Retail. Consum. Serv. 2019, 50, 30–41. [Google Scholar] [CrossRef]
  67. Lu, B.; Fan, W.; Zhou, M. Social presence, trust, and social commerce purchase intention: An empirical research. Comput. Hum. Behav. 2016, 56, 225–237. [Google Scholar] [CrossRef] [Green Version]
  68. Ali, F. Hotel website quality, perceived flow, customer satisfaction and purchase intention. J. Hosp. Tour. Technol. 2016, 7, 213–228. [Google Scholar] [CrossRef]
  69. Hsu, C.-L.; Lin, J.C.-C. What drives purchase intention for paid mobile apps?-An expectation confirmation model with perceived value. Electron. Commer. Res. Appl. 2015, 14, 46–57. [Google Scholar] [CrossRef]
  70. Ho, C.-W.; Wang, Y.-B. Does social media marketing and brand community play the role in building a sustainable digital business strategy? Sustainability 2020, 12, 6417. [Google Scholar] [CrossRef]
  71. Liang, T.-P.; Ho, Y.-T.; Li, Y.-W.; Turban, E. What drives social commerce: The role of social support and relationship quality. Int. J. Electron. Commer. 2011, 16, 69–90. [Google Scholar] [CrossRef] [Green Version]
  72. Agag, G.; El-Masry, A.A. Understanding consumer intention to participate in online travel community and effects on consumer intention to purchase travel online and WOM: An integration of innovation diffusion theory and TAM with trust. Comput. Hum. Behav. 2016, 60, 97–111. [Google Scholar] [CrossRef] [Green Version]
  73. Digital 2020—We Are Social. Available online: https://wearesocial.com/digital-2020 (accessed on 14 December 2020).
  74. Churchill, G.A.; Peter, J.P. Research Design Effects on the Reliability of Rating Scales: A Meta-Analysis. J. Mark. Res. 1984, 21, 360. [Google Scholar] [CrossRef]
  75. Kline, R.B. Principles and Practice of Structural Equation Modeling; Guilford Press: New York, NY, USA, 1998. [Google Scholar]
  76. Dospinescu, O.; Anastasiei, B.; Dospinescu, N. Key factors determining the expected benefit of customers when using bank cards: An analysis on millennials and generation Z in Romania. Symmetry 2019, 11, 1449. [Google Scholar] [CrossRef] [Green Version]
  77. Hair, J.F., Jr.; Hult, G.T.M.; Ringle, C.; Sarstedt, M. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM); Sage: Los Angeles, CA, USA, 2016. [Google Scholar]
  78. Anderson, J.C.; Gerbing, D.W. Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach. Psychol. Bull. 1988, 103, 411–423. [Google Scholar] [CrossRef]
  79. Petter, S.; Straub, D.; Rai, A. Specifying Formative Constructs in Information Systems Research. 2007. Available online: https://scholarworks.gsu.edu/cis_facpubhttp://misq.org/ (accessed on 4 December 2020).
  80. Chin, W.W.; Newsted, P.R. Structural equation modeling analysis with small samples using partial least squares. Stat. Strategy Small Sample Res. 1999, 1, 307–341. [Google Scholar]
  81. Majchrzak, A.; Malhotra, A.; John, R. Perceived individual collaboration know-how development through information technology-enabled contextualization: Evidence from distributed teams. Inf. Syst. Res. 2005, 16, 9–27. [Google Scholar] [CrossRef]
  82. Urbach, N.; Ahlemann, F. Structural Equation Modeling in Information Systems Research Using Partial Least Squares. J. Inf. Technol. Theory Appl. 2010, 11, 5–40. [Google Scholar]
  83. Hair, J.F.; Ringle, C.M.; Sarstedt, M. PLS-SEM: Indeed a silver bullet. J. Mark. Theory Pr. 2011, 19, 139–152. [Google Scholar] [CrossRef]
  84. Fornell, C.; Larcker, D.F. Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. J. Mark. Res. 1981, 18, 39–50. [Google Scholar] [CrossRef]
  85. Tenenhaus, M.; Vinzi, V.E.; Chatelin, Y.-M.; Lauro, C. PLS path modeling. Comput. Stat. Data Anal. 2005, 48, 159–205. [Google Scholar] [CrossRef]
  86. Wetzels, M.; Odekerken-Schröder, G.; Van Oppen, C. Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS Q. Manag. Inf. Syst. 2009, 33, 177–196. [Google Scholar] [CrossRef]
  87. Sobel, M.E. Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models. Sociol. Methodol. 1982, 13, 290–312. [Google Scholar] [CrossRef]
  88. Krishna, A. Customer Sense: How the 5 Senses Influence Buying Behavior; Palgrave Macmillan: London, UK, 2013. [Google Scholar]
  89. Shin, J.; Chae, H.; Ko, E. The power of e-WOM using the hashtag: Focusing on SNS advertising of SPA brands. Int. J. Advert. 2018, 37, 71–85. [Google Scholar] [CrossRef]
  90. Hultén, B.; Broweus, N.; van Dijk, M. What is sensory marketing? In Sensory Marketing; Palgrave Macmillan: London, UK, 2009; pp. 1–23. [Google Scholar]
  91. Anastasiei, B.; Dospinescu, N. A model of the relationships between the Big Five personality traits and the motivations to deliver word-of-mouth online. Psihologija 2018, 51, 215–227. [Google Scholar] [CrossRef] [Green Version]
  92. Dospinescu, O.; Percă-Robu, A.E. The Analysis of E-Commerce Sites with Eye-Tracking Technologies. BRAIN. Broad Res. Artif. Intell. Neurosci. 2017, 8, 85–100. [Google Scholar]
  93. Baird, C.H.; Parasnis, G. From social media to social customer relationship management. Strategy Leadersh. 2011, 39, 30–37. [Google Scholar] [CrossRef]
Figure 1. Research Framework.
Figure 1. Research Framework.
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Figure 2. A framework of the inner model result. *** p-value < 0.001.
Figure 2. A framework of the inner model result. *** p-value < 0.001.
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Table 1. Operational definitions.
Table 1. Operational definitions.
ConstructDefinitionSource
Social Media Marketing Activity (SMMA)Measuring the social networking sites users’ understanding or perception towards the enterprises’ social media marketing activityKim and Ko [4]; Chen & Lin [2]
Customer Experience (CX)The extent of users’ involvement and observation in social networking sites’ (SNS’) marketing content that possibly produces sensory, emotional, and cognitive impacts, which enhance attraction, motivation, and acknowledgment and consequently, adds value.Schmitt [21]; Homburg et al. [56]; Chen & Lin [7]
Relationship QualityThe degree of the overall assessment of the strength of a relationship between SNS users and the enterprise as the key focus of SNS marketing contents, which involve cooperative intentions, mutual disclosure, and intensive follow up contact.Crosby et al. [23]; Palmatier et al. [24]; Tajvidi et al. [57]
Purchase IntentionCustomer willingness to purchase a product/service after perceiving SNS marketing content.Dodds et al. [46]; Bonsón Ponte et al. [58]
Loyalty IntentionCustomer willingness to be a loyal and committed customer after perceiving SNS marketing content.Flavián et al. [51]; Zhang et al. [43]
Participation IntentionCustomer willingness to present in a discussion (product review), program, or event held by the enterprise after perceiving SNS marketing content.Chen & Lin [2]; Hajli [31]
Table 2. Sample Demographics.
Table 2. Sample Demographics.
CharacteristicItemsFrequencyPercentage
GenderMale12530.3%
Female28869.7%
Age16–204410.7%
21–2521552.1%
26–309021.8%
31–35317.5%
>36338.0%
Education LevelHigh School327.7%
Diploma/Bachelor25962.7%
Master11928.8%
Doctoral30.7%
Table 3. Inner VIF result.
Table 3. Inner VIF result.
ConstructVIF
SMMA → REQ2.315
CX → REQ2.315
REQ → INT1.000
REQ → LYL1.000
REQ → INP1.000
SMMA = Social Media Marketing Activity; CX = Customer Experience; INP = Intention to participation; INT = Intention to Buy; LYL = Intention to Loyalty; REQ = Relationship Quality.
Table 4. Questionnaire measurement items.
Table 4. Questionnaire measurement items.
Measurement Items
Social Media Marketing activity; source: [2,4]
ENT1I purchase a product on social media online shop because of fun
ENT2I purchase a product on social media online shop because the contents shown are interesting
INT1I purchase a product on social media online shop because of allows me to share its information with others.
INT2I purchase a product on social media online shop because of possible to have a conversation/ comment sharing
INT3I purchase a product on social media online shop because it is easy to deliver my opinion.
TRN1I purchase a product on social media online shop because of contents shown are up to date.
TRN2I purchase a product on social media online shop because of shows the latest product information.
CUS1I purchase a product on social media online shop because of offers customized information searches.
CUS2I purchase a product on social media online shop because of provides customized service.
WOM1I’m willing to pass along information on the brand, product/ services from social media to my friends.
WOM2I’m willing to upload/ repost content from the social media online shop on my blog or social media/ microblog.
Customer Experience; source: [7,8]
SEN1The social media online shop’s post tries to engage my senses.
SEN2Participating (e.g., like commenting, sharing) on social media is very interesting.
FEL1The social media online shop’s post tries to put me in a certain mood.
FEL2The social media online shop makes me respond emotionally.
THK1The social media online shop tried to intrigue me.
THK1The social media online shop stimulates my curiosity.
ACT1The social media online shop tries to make me think about my lifestyle.
ACT2The social media online shop reminds me of activities I can do.
REL1The social media online shop tries to get me to think about relationships.
REL2I can relate to other customers through the social media online shop.
Relationship Quality; source: [30,58,67]
SAT1How satisfied are you with shopping online on social media?
SAT2How satisfied are you with the relationship with the online shops on social media?
SAT3Overall, I am satisfied with the online shops on social media
SAT4I am pleased with the experience of buying products from social media
SAT5I think buying products from social media is a good idea.
SAT6Overall, I am satisfied with the experience of purchasing products from social media
TRU1social media online shop can be relied upon to keep promises.
TRU2social media online shop is trustworthy.
TRU3I have full confidence in the social media online shop
TRU4If I required help, the seller on social media would do his/her best to help me.
TRU5Overall promises made by the seller on social media are likely to be reliable.
TRU6The seller on social media performs his/her role very well.
Purchase intention; source: [29,68,69]
INT1I am likely to purchase products on social media online shop
INT2I would consider purchasing products on social media online shop in the future.
INT3It is likely that I will purchase products on social media online shop shortly.
INT4I am likely to buy a particular product on social media’s online shops.
Loyalty intention; source: [43,45]
LYL1I will purchase another product offered by social media in the future
LYL1I will purchase another product offered by social media online in the future
LYL2I will encourage/ recommend friends and relatives to use the product offered by social media
LYL3I intend to stay with social media as one of a shopping channel.
LYL4I intend to recommend social media to others
Participate intention; source: [2,31,71]
INP1When I saw the post from social media online shop that I like, I would “like” that.
INP2When I saw the post from social media online shop that I like, I would “comment” on that.
INP3When I saw the post from social media online shop that I like, I would “share” that.
INP4It is worth to share, comment and like on social media online shop
INP5I’m willing to provide my experience and suggestion when my friend wants to buy in social media online shop
INP6I’m willing to recommend which product is worth buying in social media online shop to my friend.
ACT = Act; CUS = Customization; ENT = Entertainment; FEL = Fell; INP = Intention to participation; INR = Interaction; INT = Intention to Buy; LYL = Intention to Loyalty; REL = Relate; SAT = Satisfaction; SEN = Sense; THK = Think; TRN = Trendiness; TRU = Trust; WOM = Word of Mouth.
Table 5. Reliability analysis and convergent validity.
Table 5. Reliability analysis and convergent validity.
Measurement ItemFactor Loading/WeightComposite ReliabilityAVEMeasurement ItemFactor LoadingComposite ReliabilityAVE
SEN0.24 (Weight)n/a (Formative construct)n/a (Formative construct)SAT10.870.960.78
FEL0.21 (Weight)SAT20.82
THK0.24 (Weight)SAT30.91
ACT0.25 (Weight)SAT40.94
REL0.22 (Weight)SAT50.86
SEN10.950.950.91SAT60.91
SEN20.96TRU10.870.960.79
FEL10.900.860.76TRU20.89
FEL20.84TRU30.89
THK10.920.910.84TRU40.86
THK20.92TRU50.91
ACT10.940.930.88TRU60.91
ACT20.94INT10.880.880.64
REL10.880.890.80INT20.76
REL20.91INT30.75
ENT10.890.900.81INT40.81
ENT20.91LYL10.870.930.78
INR10.870.930.81LYL20.92
INR20.92LYL30.85
INR30.91LYL40.90
TRN10.940.940.89INP10.760.900.59
TRN20.94INP20.68
CUS10.910.910.84INP30.72
CUS20.92INP40.84
WOM10.890.840.73INP50.77
WOM20.82INP60.83
ACT = Act; CUS = Customization; ENT = Entertainment; FEL = Fell; INP = Intention to participation; INR = Interaction; INT = Intention to Buy; LYL = Intention to Loyalty; REL = Relate; SAT = Satisfaction; SEN = Sense; THK = Think; TRN = Trendiness; TRU = Trust; WOM = Word of Mouth.
Table 6. Factor loadings and cross-loadings.
Table 6. Factor loadings and cross-loadings.
ACTCUSENTFELINPINRINTLYLRELSATSENTHKTRNTRUWOM
ACT10.940.420.540.590.490.480.490.480.710.620.560.590.480.610.50
ACT20.940.430.530.550.450.480.490.480.750.550.540.560.470.580.51
CUS10.380.910.490.440.400.430.370.390.400.410.460.490.600.380.49
CUS20.450.920.470.480.460.470.420.440.460.440.420.500.530.420.59
ENT10.540.430.890.530.460.550.440.440.500.520.560.560.530.470.52
ENT20.490.510.910.570.380.520.370.400.520.450.620.640.690.410.50
FEL10.570.460.600.900.380.460.390.440.550.570.730.740.630.510.52
FEL20.480.410.460.840.330.410.310.310.420.380.470.610.380.360.39
INP10.360.390.320.280.760.340.460.540.340.430.250.300.280.430.44
INP20.240.320.260.210.680.370.390.420.200.280.110.200.180.280.34
INP30.290.360.290.230.720.370.430.500.240.350.200.260.220.330.42
INP40.390.420.350.290.840.370.520.590.340.490.270.330.310.470.46
INP50.430.350.400.380.770.430.530.580.420.580.400.390.430.570.40
INP60.490.360.450.400.830.480.660.710.460.700.390.410.450.700.50
INR10.440.440.620.450.440.870.480.420.420.480.460.500.550.460.50
INR20.420.450.480.460.470.920.490.490.440.480.400.480.530.430.43
INR30.510.440.510.450.500.910.530.500.510.490.420.480.470.480.47
INT10.560.420.490.430.610.530.880.760.530.770.440.440.470.780.52
INT20.380.240.270.250.470.370.760.570.330.510.260.250.300.510.30
INT30.310.390.280.280.500.410.750.630.310.410.250.280.280.420.36
INT40.360.320.350.310.550.430.810.640.370.470.260.330.290.500.38
LYL10.420.410.390.350.620.440.760.870.400.630.350.370.440.630.47
LYL20.480.410.430.400.710.460.730.920.450.690.380.400.450.690.57
LYL30.430.400.450.400.590.460.680.850.440.580.380.400.450.590.46
LYL40.460.390.390.380.700.480.710.900.410.650.360.410.410.650.59
REL10.600.450.470.460.380.480.430.420.880.470.520.510.440.500.44
REL20.770.400.540.540.430.430.460.440.910.540.610.560.460.580.50
SAT10.520.410.500.500.520.410.560.590.490.870.470.470.480.730.52
SAT20.480.410.410.380.570.530.610.620.490.820.330.380.430.720.49
SAT30.530.420.450.500.560.460.590.640.460.910.450.490.490.770.50
SAT40.570.420.480.520.610.500.670.680.500.940.510.500.490.810.51
SAT50.590.400.500.520.580.480.670.650.550.860.500.520.490.770.49
SAT60.600.420.520.520.650.480.670.680.560.910.540.540.500.820.53
SEN10.510.440.630.620.330.430.360.380.560.480.950.650.570.430.49
SEN10.510.440.630.620.330.430.360.380.560.480.950.650.570.430.49
SEN20.600.470.620.710.390.470.390.410.640.530.960.760.600.500.50
SEN20.600.470.620.710.390.470.390.410.640.530.960.760.600.500.50
THK10.590.460.610.750.390.550.420.440.560.510.670.920.580.490.52
THK20.540.540.620.680.400.450.350.380.540.490.710.920.620.460.51
TRN10.450.590.630.550.410.560.410.460.450.500.540.600.940.450.50
TRN20.520.580.660.570.410.520.420.470.500.530.620.640.940.490.55
TRU10.590.360.420.450.560.450.660.620.560.800.460.470.420.870.49
TRU20.560.370.440.450.560.420.640.630.500.810.460.480.450.890.50
TRU30.560.400.440.480.540.410.630.650.520.780.470.480.460.890.51
TRU40.550.420.460.440.640.500.610.670.550.740.420.460.470.860.53
TRU50.550.420.460.430.570.480.670.640.570.750.420.450.450.910.54
TRU60.560.380.380.430.590.440.660.660.550.750.400.420.430.910.49
WOM10.510.530.580.540.470.490.480.560.530.580.560.580.590.570.89
WOM20.410.480.370.350.500.390.370.450.360.380.300.350.330.390.82
ACT = Act; CUS = Customization; ENT = Entertainment; FEL = Fell; INP = Intention to participation; INR = Interaction; INT = Intention to Buy; LYL = Intention to Loyalty; REL = Relate; SAT = Satisfaction; SEN = Sense; THK = Think; TRN = Trendiness; TRU = Trust; WOM = Word of Mouth.
Table 7. Summary of the inner model result.
Table 7. Summary of the inner model result.
HypothesisPath Coefficientt-ValueResult
H1SMMA → RQ0.330 ***5.880Supported
H2CX → RQ0.430 ***6.775Supported
H3RQ → INT0.741 ***26.410Supported
H4RQ → LYL0.749 ***25.221Supported
H5RQ → INP0.676 ***22.369Supported
Note: SMMA = Social Media Marketing Activity; CX = Customer Experience; RQ = Relationship Quality; INT = Intention to Buy; LYL = Loyalty Intention; INP = Participation Intention. *** p-value < 0.001.
Table 8. Mediation test result.
Table 8. Mediation test result.
ConstructConstruct Relationshipt-Value of Path CoefficientSobel Test’s z-Value
SMMA → RQ → INTSMMA → RQ
RQ → INT
6.000
26.188
5.848 ***
SMMA → RQ → LYLSMMA → RQ
RQ → LYL
6.000
25.185
5.837 ***
SMMA → RQ → INPSMMA → RQ
RQ → INP
6.000
22.272
5.793 ***
CX → RQ → INTCX → RQ
RQ → INT
6.712
26.188
6.502 ***
CX → RQ → LYLCX → RQ
RQ → INT
6.712
25.185
6.486 ***
CX → RQ → INPCX → RQ
RQ → LYL
6.712
22.272
6.426 ***
SMMA = Social Media Marketing Activity; CX = Customer Experience; RQ = Relationship Quality; INT = Intention to Buy; LYL = Loyalty Intention; INP = Participation Intention. *** p-value < 0.001.
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Wibowo, A.; Chen, S.-C.; Wiangin, U.; Ma, Y.; Ruangkanjanases, A. Customer Behavior as an Outcome of Social Media Marketing: The Role of Social Media Marketing Activity and Customer Experience. Sustainability 2021, 13, 189. https://doi.org/10.3390/su13010189

AMA Style

Wibowo A, Chen S-C, Wiangin U, Ma Y, Ruangkanjanases A. Customer Behavior as an Outcome of Social Media Marketing: The Role of Social Media Marketing Activity and Customer Experience. Sustainability. 2021; 13(1):189. https://doi.org/10.3390/su13010189

Chicago/Turabian Style

Wibowo, Ardy, Shih-Chih Chen, Uraiporn Wiangin, Yin Ma, and Athapol Ruangkanjanases. 2021. "Customer Behavior as an Outcome of Social Media Marketing: The Role of Social Media Marketing Activity and Customer Experience" Sustainability 13, no. 1: 189. https://doi.org/10.3390/su13010189

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