Next Article in Journal
Selection of Landfill Cover Materials Based on Data Envelopment Analysis (DEA)—A Case Study on Four Typical Covering Materials
Next Article in Special Issue
Does SDGs Advertising Promote Ethical Consumer Behavior?: An Integrative Model of Ethical Consumption with Elements of Communication Strategy and Rational Purchase
Previous Article in Journal
Indicators of Geographic Potential and Business Opportunities for the Development of Active Tourism: Kayaking in Poland
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

What Drives the Digital Customer Experience and Customer Loyalty in Mobile Short-Form Video Shopping? Evidence from Douyin (TikTok)

1
School of Economics, Jiaxing University, Jiaxing 314001, China
2
Department of Business Administration, College of Management and Economics, Dongguk University, Gyeongju 38066, Korea
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(17), 10890; https://doi.org/10.3390/su141710890
Submission received: 23 July 2022 / Revised: 26 August 2022 / Accepted: 27 August 2022 / Published: 31 August 2022
(This article belongs to the Special Issue Experience Design and Digital Transformation in Business)

Abstract

:
Mobile short-form video (MSFV) shopping represents an emerging method of mobile e-commerce and indicates the future development trend of mobile e-commerce. Unlike other famous mobile commerce applications, MSFV apps provide customers with animated videos which enable them to view product information vividly. This study examines the associations between digital customer experience and customer loyalty based on a human–computer interaction approach. We draw on content quality, relationship quality, and stickiness to investigate customer attitudinal loyalty and behavioral loyalty. A total of 796 users who use the leading MSFV app in China were randomly surveyed, among whom 778 users were involved in testing the hypotheses. Our findings indicate that content and relationship quality positively influence customers’ stickiness to MSFV shopping. Moreover, stickiness positively mediates the indirect link between content quality and customer loyalty as well as relationship quality and customer loyalty. This study demonstrates the value of extending the human-computer interaction approach to MSFV shopping and contributes to the existing literature by offering a deeper understanding of customer loyalty in the context of MSFV shopping. In addition, it has some managerial implications for making the most of the MSFV app’s huge potential to help the sustainable growth of mobile e-commerce.

1. Introduction

With the rapid development of mobile devices, consumption through mobile short-form videos has increased worldwide, impacting our daily lives unprecedentedly and changing how people search for and share information. In addition, mobile MSFV apps are transforming how e-commerce providers do business and are contributing to the sustainable development of e-commerce. MSFV apps provide e-commerce vendors with tools to edit video clips, typically 5–15 s long, to help drive business in short video applications.
In China, the MSFV app leader, Douyin (known outside the country as TikTok), has expanded its e-commerce activities to sell products and provide services and other forms of content. According to Statista.com [1], there were more than 934 million short-form video users in China at the end of 2021, accounting for 90.5% of the country’s internet users. The Statista.com [2] survey has also shown that the user base of Douyin in the Chinese market will surpass 835 million by 2025. Among these users, more than half of them accessed their Douyin account on mobile devices. Thanks to the MSFV app, traditional mobile e-commerce can integrate social media functions, video clips, and celebrities to improve digital customer experiences. Douyin has designed a range of shopping portals on different types of content to capture customers’ purchasing intentions after interacting with product content. Customers can easily be directed to the product page, whether a short-form video or a hashtag page. Customers can purchase products from the Douyin store via a short-form video, complete the transaction with Douyin Pay, and share their shopping experiences with their peers through social networking tools in the app. By incorporating these technological and social features into digital customer experiences, mobile e-commerce can evolve into sustainable e-commerce and revolutionize how people buy through their mobile devices.
The MSFV app enables mobile e-commerce providers to sell products, interact with customers, and cultivate customer relationships. The increased use of digital media has created a new channel for consumers to shop for goods and services. Through its broad coverage and value chain, MSFV shopping has become a vital component of the new economic cycle [3]. Customers can actively interact with their peers, enriching their shopping experiences and making more informed purchasing decisions [4]. Despite the rapid development of mobile e-commerce, MSFV shopping still faces many challenges and difficulties. For example, low customer loyalty results from uneven product quality, opaque prices, high refund rates, and customer complaints. Mobile e-commerce providers must effectively induce customer purchasing intention and improve customer loyalty to establish a presence in this business model.
A comprehensive review of the previous literature reveals a significant research gap. Most previous studies have tended to focus on various intentions or behaviors related to the application of MSFV apps, such as user experiences and technology adoption intent [5], short-form video application addiction [6], using motivation and influencing factors of users’ participation [7], customers’ participation behaviors [4], video formats [8], short-form video app continuance intention to use [9], content features of short-form video and customer purchase intentions [10], and factors influencing users’ engagement behaviors [11]. For example, Mou et al. [9] found that the app recommendation algorithm positively affected individual satisfaction, the novelty of new products, and privacy concerns. A product’s reputation negatively moderated the recommendation algorithm’s influence on the privacy issue. Individuals’ privacy concerns positively impact privacy-protection behavior, and privacy-protection behavior positively impacts satisfaction. In addition, Ren et al. [4] proved that positive customer involvement behaviors improved customers’ perceptions of value, which boosted consumers’ happiness. However, there are few studies that have examined digital customer experiential determinants (i.e., vividness, diagnosticity, participation, trust, recommendation, and commitment), customers’ stickiness to MSFV shopping, and customers’ loyalty in an integrated framework. To fill the gap, we must fully explain and improve our understanding of customers’ stickiness and loyalty behaviors in the context of MSFV shopping, using a framework that combines key content-related factors and seller-customer relationship-related factors.
Meanwhile, previous studies on customer loyalty have examined customer loyalty from various perspectives. Anderson et al. [12] found that hedonic and utilitarian motivations affected the loyalty of social commerce websites. According to Hew et al. [13], users who continued to use and were satisfied with mobile social commerce were more likely to be loyal to the brand. Cheng et al. [14] found that trust in the app positively affected social purchasing intention, while trust in other members strongly affected word-of-mouth intention. To strengthen effective management processes and to increase customer repurchase intention, mobile e-commerce providers need to encourage cooperative behaviors [14]. In addition, trust and identification with the virtual community have also been shown to influence customer engagement, which positively impacted customer loyalty [15,16]. However, very few studies have investigated customer loyalty in the context of MSFV shopping.
Along with this trend, this study examines the digital customer experience in MSFV shopping and its influence on customer stickiness and loyalty. We draw on the computer–human interaction approach and introduce content quality and relationship quality concepts to explore digital customer experience and investigate their influences on customers’ stickiness and loyalty toward MSFV shopping. In this study, content quality is measured through vividness and diagnosticity. Furthermore, we assess relationship quality through commitment, participation, trust, and recommendation. In addition, stickiness acts as a mediator between digital customer experience-related factors and customer loyalty. We focus on both attitudinal loyalty and behavioral loyalty to examine customers’ responses more accurately and comprehensively. Jacoby et al. [17] were the first authors who differentiated attitudinal loyalty and behavioral loyalty based on reasoned action. According to Cachero-Martínez and Vazquez-Casielles [18] and Bandyopadhyay and Martell [19], there are two types of loyalty: attitudinal (or mental) loyalty, which refers to consumers’ intentions and inclinations toward specific products or service providers, and behavioral loyalty, which relates to customers who repurchase products from a given vendor. To achieve the above research purposes, we suggest the following main research questions:
Q1 How does digital customer experience (i.e., content quality and relationship quality) predict customers’ stickiness to MSFV shopping?
Q2 How do customers’ stickiness to MSFV shopping affect their attitudinal and behavioral loyalty?
Q3 How does attitudinal loyalty influence behavioral loyalty in the context of MSFV shopping?
This study is structured based on the following sections: We review the previous relevant literature and propose a research model and hypotheses in Section 2 and Section 3; in Section 4, the research methodology and data collection are described; we distribute analysis results based on the proposed research model in Section 5; in the last section, we summarize the main research findings and provide implications for both theory and management.

2. Literature Review and Theoretical Framework

2.1. Mobile Short-Form Video (MSFV) Shopping

The rapid development of mobile e-commerce, the growing popularity of social media, and the developed technology of mobile devices are the driving forces behind MSFV shopping [7,13]. Mobile e-commerce vendors are looking for marketing and business opportunities on social media platforms, since the virtual social media arena has evolved into a platform for communication, networking, and content sharing [20]. The MSFV app allows mobile e-commerce vendors to quickly and easily create videos with integrated recording, editing, and sharing capabilities. In addition, the MSFV app enables mobile e-commerce vendors to create roughly 15-second looping videos with advanced editing features such as in-camera speed controls, image tracking composites, collaborative split-screen video editing, and camera motion and visual effects. These editing features improve the basic features of mobile devices so that they can be used for business [21].
In addition, customers can actively participate in the marketing and purchasing products on the MSFV app [4]. Usually, there are two types of MSFV shopping forms: Customers can be directed to an online shopping mall (e.g., Taobao.com, JD.com) outside of the MSFV app or make purchases within the MSFV app. Similar to other social media platforms, on the MSFV app, influencers and their followers may form a parasocial bond, promoting ideas, services, and products [22]. Thus, MSFV shopping has unique advantages over traditional mobile e-commerce since it makes shopping novel, vivid, and ubiquitous. It also increases customer–customer and business–customer interactions.

2.2. Content Quality

The concept of content quality refers to the usefulness and value of the information that mobile services provide [23]. According to Davis [24], the concept of usefulness is that people believe using a certain information system improves their job performance. User experience is influenced by various factors such as the information’s immediacy and richness and the content’s personalization [25]. In the context of MSFV shopping, content is focused on what it offers and how it appeals to the users. Content quality is defined as a combination of elements that include the offering, appeal, and multimedia mix [26]. With the increase in MSFV apps, the relevant and engaging content that is presented to customers becomes important. MSFV shopping mainly aims to demonstrate vivid product content to customers and allow them to view product features and selling points in detail from MSFV apps. High-quality content is beneficial for customers as it increases their perceived value and helps them to make informed decisions when buying from MSFV shopping [27]. This study aims to analyze the degree to which customers are satisfied with the quality of the content that they view. These characteristics include the authenticity of the content, its richness, and its diagnosticity. Content quality in this study is measured as a multidimensional construct, namely, vividness and diagnosticity. A vivid product presentation is considered to be an effective demonstration as it allows customers to understand a product and its various features. According to Jiang and Benbasat [28], a vivid product presentation stimulates the senses and provides a variety of sensory channels. Furthermore, diagnosticity, in this study, is defined as the degree to which a customer perceives that the product information and characteristics embedded in MSFV shopping content are helpful and valuable for them to evaluate the product [29].

2.3. Relationship Quality

The intimacy or strength of a particular relationship is measured by the term “relationship quality” [30]. In the case of marketing, it quantifies the intensity of the relationship between a vendor and a customer, and it also impacts the possibility of a future transaction between the two parties [31]. Recently, relationship marketing research have focused on customer–vendor partnerships [32]. For instance, a better relationship with the customer means more positive interaction, which can help cultivate customer loyalty [33]. The previous research has measured relationship quality as a multidimensional construct that included trust, commitment, and satisfaction. Trust refers to the willingness to rely on a trusted exchange partner [34]. Satisfaction is a customer’s overall emotional response to a service or product provider’s performance [35]. Commitment is concerned with the wish to maintain a connection [34,36]. Previous research has shown that the quality of customer–vendor relationships (or salespeople, sellers, service providers, and brands) produces a variety of positive outcomes, including customer loyalty [37], brand co-creation [33,38], purchase intention [39,40,41,42], and social commerce continuance intention [43]. In this study, we synthesize findings from past studies and propose four dimensions of relationship quality: commitment, participation, recommendation, and trust. We define commitment as the extent to which customers believe an ongoing relationship with a vendor is vital to ensure maximum effort to maintain it in MSFV shopping. Participation refers to customers’ willingness to participate in transactions and activities with the MSFV shopping seller. The recommendation in MSFV shopping deals with customers’ willingness to recommend the products or services. Finally, trust in MSFV shopping refers to the extent to which the customers believe the seller is honest and reliable. Drawing on these findings, we suggest that the relationship quality between a customer and a seller in MSFV shopping is critical in influencing customers’ stickiness and loyalty.

2.4. Customer Stickiness

Similar to traditional e-commerce, customer stickiness is critical in managing MSFV shopping to create business value. The goal of MSFV shopping is to influence customers to purchase more frequently and to encourage customers to stick to MSFV shopping for a longer time period with higher use frequency. The more attention the MSFV shopping app receives from customers, the higher the likelihood that MSFV shopping generates sales transactions [4]. In other words, if MSFV shopping is shopped frequently and makes customers spend lots of time browsing, it is considered to exhibit the feature of stickiness. A high level of stickiness also helps customers and sellers to get along well in MSFV shopping [44].
Stickiness has been discussed from different perspectives in previous research. El-Manstrly et al. [45] indicated that trust was vital in strengthening members’ site stickiness in the context of a virtual travel community. Friedrich et al. [46], drawing on the stimulus-organism-response framework, found that the feature richness positively affected the website’s stickiness. Zhang et al. [47] pointed out that customer engagement with a company’s social network directly and positively influenced customer stickiness. Hu et al. [48] discussed followers’ stickiness with digital influencers based on a psychological perspective. Stickiness and social identification significantly impacted a user’s decision to make an in-app purchase [49]. In order to enhance the stickiness of MSFV shopping, it is necessary to improve content quality mechanisms and to cultivate customer–vendor relationship quality in addition to system functions (e.g., app aesthetic, interactivity, and navigability) [50,51,52,53]. This study supplements previous studies on customer stickiness [47,50,54]. Moreover, it provides practical guidance for MSFV app companies to develop better content quality mechanisms, foster healthier relationship quality with customers, and to increase the stickiness of MSFV shopping. In this study, stickiness is a measure of how well MSFV shopping can attract and keep customers. It is also a mediator between content quality, relationship quality, and customer loyalty.

2.5. Customer Attitudinal Loyalty and Behavioral Loyalty

Customer loyalty has become increasingly important in recent competitive markets as firms compete for success, growth, and profitability [16]. Long-term customer loyalty can be hindered by inertia, promotion events, geographic convenience, and strong brand loyalty. Individual, psychological, and environmental marketing elements may influence the frequency of repurchase [19]. As a result, a positive attitude could accompany the behavior [55,56]. In the same way, a customer’s mental attachment to a brand affirms their unexpressed loyalty but not their actual loyalty [57].
When defining and conceptualizing customer loyalty, there are two groups of opinions. Many scholars have investigated customer loyalty from attitudinal and behavioral perspectives. Dick and Basu [57] pointed out loyalty involved a positive attitude and repeat purchases. According to Cachero-Martinez and Vázquez-Casielles [18], different experiences could influence loyalty in two ways, i.e., they could directly influence attitudinal loyalty (e.g., when trustworthiness in e-shopping is low and customers are more uncertain) or could indirectly influence behavioral loyalty through emotional experience. Dick and Basu [57] theorized that customer loyalty was characterized by an agreeable attitude and repeat purchases, which was empirically tested by East et al. [58]. Kaur [59] explored customers’ attitudinal and behavioral loyalty toward virtual products. According to Kim et al. [60], qualified information and services provided by O2O apps positively impacted customers’ perceptions of privacy protection and customer satisfaction, resulting in both attitudinal and behavioral loyalty. Soedarto et al. [61] also investigated the association between two types of customer loyalty: attitudinal and behavioral. Their findings demonstrated that attitudinal loyalty was the driving force behind behavioral loyalty. Therefore, based on those findings, we propose that customers’ attitudinal and behavioral loyalty are also different in the context of MSFV shopping.

3. Hypotheses Development and Research Model

3.1. Content Quality and Relationship Quality

Content quality is a critical matter for MSFV shopping. Hence, MSFV shopping providers must not compromise the quality of video content. Based on the above discussions, this study assumes that the quality of MSFV shopping content can influence customers’ practical and psychological values in a positive way, which can eventually improve customer loyalty and can increase their likelihood of sticking to the shopping mode. In this study, vividness and diagnosticity are subconstructs of content quality. MSFV shopping vividly demonstrates products by fostering authenticity and visualization through short-form videos, and customers can acquire the diagnostic information they need. A vivid product demonstration can help customers to understand various benefits of a seller’s offering, and thus, may enhance the value perceived by customers [28]. In addition, the features of vivid presentation in MSFV shopping will help customers to understand product information more clearly [62]. Customers will consider their use of MSFV shopping as satisfactory and valuable if the app provides them with high-quality product information [51]. In addition to vividness, various diagnostic information included in the content can also help customers to understand a particular product’s various features and benefits [29,63]. Previous studies have found that information with vividness and diagnosticity obtained by users in the cyber environment was particularly valuable in the information search context because it helped users to better understand the value of this information [29,62,63,64,65]. The vivid and diagnostic product information provided by a short-form video makes customers feel that the relationship with the seller is good, and the MSFV app is a valuable tool for shopping.
Because a well-designed short-form video can better satisfy customers’ needs for shopping, customers will receive a good impression of content quality and have confidence in a seller’s performance [66]. This will improve the relationship quality between customers and sellers. Therefore, if customers perceive higher content quality in MSFV shopping, the resulting relationship benefits will influence their intention to participate in activities frequently, to recommend the app, and will cultivate mutual trust and commitment. Consequently, MSFV shopping content quality may influence the relationship quality with a seller. Thus, we propose the following hypotheses:
H1. 
Content quality of MSFV shopping is positively associated with the customer-seller relationship quality.

3.2. Relationship Quality and Customer Stickiness

A high-quality relationship increases the likelihood of good interactions and promotes customer loyalty. The quality of a seller’s relationship with their customers is essential to a successful sales process. This is because it allows them to maintain their relationship with the customer [43]. Under these circumstances, customers will be more committed and show trust in MSFV shopping, participate in activities held by the seller, and recommend it to other friends if the relationship quality is good and they are satisfied, which will positively affect the customer’s stickiness to MSFV shopping [45,67]. MSFV shopping is a channel to obtain valuable product information and recommendations and share buying experiences [4]. If customers trust and commit to MSFV shopping, they are more likely to stick to it even if they are not satisfied with other aspects of it [45,51,68]. Customers’ sense of belonging and resistance to change are more likely to develop by posting more comments, photos, articles, or videos, and sharing their experiences [69]. One of the most frequently cited reasons for the failure of virtual platforms is the lack of members’ active participation and commitment [70]. Therefore, we propose that the relationship quality of MSFV shopping may positively affect customers’ stickiness to MSFV shopping. Suppose MSFV shopping provides opportunities for developing and managing their online relationships with customers, when sellers’ relationships with their customers are strong, they develop a deeper understanding of their customers and can encourage them to participate in MSFV shopping. Lastly, these psychological traits and customers’ sense of belonging make it more likely that MSFV shopping will become very sticky.
H2. 
Relationship quality of MSFV shopping is positively associated with customer stickiness.

3.3. Content Quality and Stickiness

Studies have shown that the presence of high-quality content can help users to increase their likelihood of returning to a website [71,72]. Since content quality impacts customer loyalty, web managers should focus on improving the quality of their websites to increase customer stickiness [71,73,74]. High-quality content (i.e., vividness and diagnosticity) can help to boost customers’ stickiness to MSFV shopping as it has become a new form of mobile commerce that enables users to interact with each other through various media. If an MSFV shopping seller can provide high value, customers tend to be highly satisfied. Moreover, perceived value is a crucial contributor to customers’ loyalty, especially in competitive business environments such as electronic commerce. For MSFV shopping, if the perceived value is lower than that of other providers, customers will turn to other sellers [75], and thus, their stickiness tends to be decreased [62]. In MSFV shopping, the perceived value generated from high-quality content critically affects customers’ stickiness and plays an important role in maintaining long-term customer relationships [76]. Therefore, customers’ judgments about MSFV shopping’s overall excellence and fitness for use are supposed to affect customers’ stickiness [72,74]. Thus, the following hypothesis was proposed:
H3. 
Content quality of MSFV shopping is positively associated with customer stickiness.

3.4. Customer Stickiness and Customer Loyalty

Customers who have previously had positive experiences with MSFV shopping may develop cumulative MSFV shopping stickiness, eventually leading to customer loyalty. Our current research discusses both attitudinal loyalty and behavioral loyalty. Attitudinal loyalty refers to customers’ psychological intentions and preferences for a product or service provider, such as MSFV shopping. In contrast, behavioral loyalty refers to actual repeated purchases from MSFV shopping. Attitudinal loyalty and behavioral loyalty are both critical for increasing the use of the service and for reuse and repurchase in MSFV shopping [4,6,60]. Loyalty is becoming increasingly important in e-commerce as users’ shopping habits change more frequently. Customers’ stickiness is regarded as a universal criterion of e-commerce loyalty. As a result, many organizations are focusing on effective website/app design and efficient business tactics to retain customers [15,77,78]. Stickiness has been found to be effective in increasing the length, frequency, and depth of customer retention, and stickiness can lead to the development of consumer loyalty in the long term. Holland and Menzel [79] pointed out that people who were more likely to stay on a website rather than move to another website revealed loyalty to the website. A change in stickiness can affect the generation and development of loyalty. According to Kabadayi and Gupta [80], customers’ website or app loyalty can be defined as the desire or inclination to spend more time on a website or the willingness to revisit the website or app. As a result, customer loyalty is a deep part of a customer’s behavior that may be enhanced by an increase in their stickiness, since the more often they visit a website or app, the more they identify with it (i.e., become familiar with it) [81].
Furthermore, according to the principle of attitude-behavior consistency, people’s attitudes are predictors of their behavior [56,82]. According to Dick and Basu [57], in marketing, customer loyalty can be considered to be an attitude–behavior relationship that identifies the influence of attitude on behavior. Based on the findings of Dick and Basu [57], Bandyopadhyay and Martell [19] empirically tested and confirmed that attitudinal loyalty affected behavioral fidelity. Previous studies have also proven that customers with higher attitudinal loyalty usually showed higher behavioral loyalty [56,83]. As a result, the following hypotheses are proposed based on the theoretical underpinnings mentioned above. Based on the literature review and theoretical framework, Figure 1 shows the research model reflecting the developed hypotheses.
H4. 
Customer stickiness to MSFV shopping is positively associated with attitudinal loyalty.
H5. 
Customer stickiness to MSFV shopping is positively associated with behavioral loyalty.
H6. 
Attitudinal loyalty is positively associated with behavioral loyalty.

4. Research Methodology

4.1. Measurement Development

This study examined the role of content quality, relationship quality, and stickiness on determining customer loyalty in MSFV shopping. We proposed that enhanced content quality (vividness and diagnosticity) and relationship quality (commitment, trust, participation, and recommendation) could easily trigger stickiness in MSFV shopping, which would positively influence customer loyalty (attitudinal loyalty and behavioral loyalty). In addition, content quality and relationship quality are second-order constructs among five constructs. We adopted the vividness and diagnosticity measurement items from Chen et al. [65], and we developed the measurement items of commitment, trust, participation, and recommendation for relationship quality by reviewing the studies of Liang et al. [43] and Hu et al. [84]. Referring to Zhang et al. [47], three items assessed MSFV shopping stickiness. Finally, we measured customer loyalty from attitudinal loyalty and behavioral loyalty and developed the items based on Kim et al. [60] and Ferm and Thaichon [85].
A Likert 5-point scale (from 1 = strongly disagree to 5 = strongly agree) was applied to measure these items. To verify these hypotheses, we conducted a survey to evaluate our research model. The questionnaire contained respondents’ demographic characteristics and self-reported items. Five constructs were included in the questionnaire: content quality (two dimensions), relationship quality (four dimensions), stickiness, attitudinal loyalty, and behavioral loyalty. First, we extracted the measurement items from previous studies and translated these items into Chinese. Then, we adopted the principle of back-translation to maintain the accuracy of the intended meaning of the items. After confirming the questionnaire, we gave it to a small group of experts to make sure that each measurement item was clear (Table A1 in Appendix A).

4.2. Data Collection

We conducted an online survey dedicated to customers with MSFV shopping experience. The survey was conducted via a famous and reliable online survey provider, and the surveying period lasted from early May 2022 to late June 2022. Finally, 796 samples were collected. We checked the IP addresses and the time each respondent spent answering the survey to ensure the validity of the collected questionnaires. Finally, 778 valid questionnaires remained. The effective recovery rate was 97.7%. As shown in Table 1, among all valid samples, 345 samples were male (44.3%), and 433 samples were female (55.7%). The majority of respondents (n = 319, 41%) were between the ages of 25 and 34. Respondents with a monthly income of between 4000 to 5900 CNY were 188 (24.2%). As for the user experience of MSFV shopping, most had used it for 2 to 3 years (n = 316, 40.6%). Most of the respondents spent less than 100 CNY on MSFV shopping (n = 314, 40.4%). The detailed information on demographic characteristics is listed in Table 1.

5. Data Analysis and Results

Considering the research model, research purpose, and data characteristics, we adopted covariance-based structural equation modeling (CB-SEM) for assessing the proposed model [86] since it could provide us with complete resources for verifying the hypotheses. We used SPSS 26 and AMOS 22 to analyze the data and to evaluate the measurement and structural models.

5.1. Measurement Model

We evaluated the measurement model by assessing the value of the factoring loading, composite reliability (CR), and average variance extracted (AVE). From the findings shown in Table 2, we can see that item loadings are greater than 0.6, which meets the criterion suggested by Fornell and Larcker [87]. Fornell and Lacker [87] and Hair et al. [88] indicated that the cut-off values for CR and AVE were 0.7 and 0.5, respectively. Table 2 shows that the CR value is higher than 0.7, and the AVE value is higher than 0.5. Therefore, all values demonstrated good validity and reliability.
In the next step, we evaluated the discriminant validity. According to Fornell and Larcker [87], the square root of the AVE should be higher than the correlations among the constructs. As shown in Table 3, the diagonal (in bold) values represent the square root of the AVE, and other values represent the correlations among the constructs. The results show that the square root of AVE is higher than all off-diagonal values, indicating good discriminant validity of the measurement model.

5.2. Common Method Bias

Podsakoff et al. [89] suggested that common method variance may exist in single-source data. We performed Harman’s single-factor test to check the collected data’s common method bias (CMB). All the measurement items were loaded into a principal component without rotation. It has been suggested that a problem with CMB exists if the total variance of one factor exceeds 50%. In our study, the first factor accounts for 32.937% of the variance, less than 50%. Thus, the data do not have a problem with CMB.

5.3. Structural Model

We assessed the structural model to verify the relationships between the constructs proposed in the research model. Through the analysis, we found that all paths were positive and significant at the 0.05 level. Table 4 displays the standardized path coefficients between constructs, the significance levels of the constructs, and the explanatory power (R2) of each construct. The rule of thumb indicates that R2 values of 25%, 50%, and 75% represents weak, average, and substantial explanatory power, respectively. In our study, the R2 values of relationship quality, stickiness, attitudinal loyalty, and behavioral loyalty were 49%, 53.7%, 35.6%, and 52.3%, respectively, indicating an acceptable level of explanation. As shown in Table 4, content quality is positively associated with relationship quality with a path coefficient of 0.70 (p < 0.001). The content quality explained 49% of the variance in relationship quality, indicating H1 was supported. Relationship quality is positively related to MSFV shopping stickiness with a path coefficient of 0.428 (p < 0.001), and content quality is positively associated with MSFV shopping stickiness with a path coefficient of 0.367 (p < 0.001). Content quality and relationship quality explained 53.7% of the variance in stickiness, proving H2 and H3 are supported. Furthermore, stickiness positively affects attitudinal loyalty with a path coefficient of 0.597 (p < 0.001) and explains 35.6% of the variance, supporting H4. In addition, stickiness positively influences behavioral loyalty with a path coefficient of 0.509 (p < 0.001). Finally, attitudinal loyalty positively affects behavioral loyalty with a path coefficient of 0.292 (p < 0.001). Stickiness and attitudinal loyalty explain 52.3% of the variance in behavioral loyalty. H5 and H6 are supported. Moreover, the fit for the structural model is acceptable. Details of the hypothesis testing and model fit can be found in Table 4 and Table 5.

5.4. Mediation Effect of Stickiness among Content Quality, Relationship Quality, and Customer Loyalty

Since one of the purposes of this research was to explore the role of stickiness in determining customers’ loyalty in the context of MSFV shopping, we evaluated the mediating effect of stickiness between content quality, relationship quality, and customer loyalty (both attitudinal loyalty and behavioral loyalty). A mediating effect can be used to improve the performance of the research model by adding a mediator to the basic linear regression. To that end, we introduced stickiness into our research model. This study applied a bootstrapping method to verify the mediating effect of stickiness among content quality, relationship quality, customer attitudinal loyalty, and customer behavioral loyalty. It has been suggested that when the upper and lower confidence intervals (95% CI) do not contain zero, the mediating variable is supposed to have a mediating influence between an independent variable (X) and a dependent variable (Y). As expected, results indicate a significant mediation of stickiness between content quality and attitudinal loyalty (mediation effect 0.183, LLCI = 0.119, ULCI = 0.253) and a significant mediation effect of stickiness between content quality and behavioral loyalty (mediation effect 0.227, LLCI = 0.157, ULCI = 0.304). In addition, stickiness to MSFV shopping significantly mediates the relationship between relationship quality and attitudinal loyalty (mediation effect 0.207, LLCI = 0.133, ULCI = 0.287), as well as the relationship between relationship quality and behavioral loyalty (mediation effect 0.225, LLCI = 0.151, ULCI = 0.299).

6. Discussion and Implications for Research and Practice

6.1. Discussion of Key Findings

MSFV shopping provides customers with various contents and improves their consumption experiences. Through the lens of digital customer experiences, this study explores customer loyalty in MSFV shopping. We take a human–computer interaction (HCI) approach and address the effects of content quality and relationship quality on customer loyalty through the stickiness of MSFV shopping. Under a HCI approach, MSFV shopping qualities (content quality and relationship quality) are used to assess the digital customer experience. Two types of content quality and four types of relationship quality are explored: diagnosticity, vividness, commitment, participation, trust, and recommendation. Furthermore, stickiness acts as a psychological mediator between digital customer experience and customer response (loyalty). We used findings from previous related studies to demonstrate how these concepts could be operationalized [43,44,46,60,84,85,90].
First of all, our findings indicate that the content quality (i.e., diagnosticity and vividness) within MSFV shopping is a strong indicator (β = 0.7, p < 0.001) of relationship quality (commitment, participation, trust, and recommendation). This confirms the previous research findings [43,65]. Customers can obtain product information through well-designed content in MSFV shopping before purchasing. As a result, customers rely more on vivid and diagnostic demonstrations to make rational decisions. They may become committed to MSFV shopping, build trust with a seller, participate in activities provided by a seller more frequently, and recommend MSFV shopping to their friends. When these benefits and good experiences add up, they help to build a good relationship with MSFV shopping sellers. Second, the findings show that content quality (β = 0.367, p < 0.001) and relationship quality (β = 0.428, p < 0.001) can both significantly predict customer stickiness in MSFV shopping, which provides a valuable supplement to the existing literature. Even though several studies have investigated customer behavior in the context of MSFV shopping, few studies have addressed MSFV shopping stickiness. Therefore, our research contributes to a better understanding of the stickiness in MSFV shopping. Stickiness is also found to have a positive influence on both attitudinal loyalty and behavioral loyalty. This is consistent with Roy [50], who found a direct effect of stickiness on loyalty in an e-retail context. Third, stickiness positively mediates the relationship between MSFV shopping qualities (content quality and relationship quality) and customer loyalty. Therefore, it can be concluded that content quality and relationship quality are significant factors affecting customers’ stickiness to MSFV shopping, and therefore, affecting customer loyalty. MSFV shopping operators should pay special attention to these elements to cultivate customer interest, since customers first and foremost rely heavily on the content that the seller demonstrates before making a formal buying decision. Developing new mechanisms to enhance content quality and building a good and high-quality relationship with customers should result in them sticking to MSFV shopping and further improve their loyalty.
As compared with previous studies, this study adds to the MSFV shopping literature in the following ways: First, this study demonstrates the value of applying the HCI approach to MSFV shopping. In contrast to previous research that has focused on technological determinants and user behavior, we investigated the relationship between digital customer experience and customer loyalty. Second, we developed two constructs (vividness and diagnosticity) to measure content quality based on the nature of MSFV shopping. Furthermore, commitment, participation, recommendation, and trust were adopted to assess relationship quality by synthesizing prior research findings. Lastly, the role of stickiness as a psychological mediator has been proven. This study could provide researchers with ideas for more in-depth research on the digital customer experience and customer loyalty in MSFV shopping. It could also provide MSFV shopping vendors more ideas for improving the quality of MSFV shopping and enhancing customer loyalty.

6.2. Implications for Research

This study contributes several theoretical implications for existing MSFV shopping research. First and foremost, to the best of the authors’ knowledge, it is the first study to use an HCI approach to investigate the factors that influence customer loyalty in the context of MSFV shopping based on content quality and relationship quality. By reviewing the limited research in this area, we found that the topics discussed have been focused on the intention of adopting MSFV applications [5], continuance intention to use MSFV applications [9,91], and discontinuous usage behavior [92]. Furthermore, in recent years, HCI research has focused on feature recognition, brain–computer interface, online social communication, user interface design, and task efficiency [93]. The existing research, however, does not consider the application’s various aspects, such as the technology’s structure, concept, and psychological impact. The current study thoroughly examines the impact of HCI on customer loyalty in the context of MSFV shopping. Furthermore, it strengthens the phenomenon’s internal and external mechanisms and provides valuable application research for the study of HCI theory.
Second, the findings demonstrated the importance of content quality in facilitating customer stickiness and developing customer loyalty in MSFV shopping. This study examined content quality as a multidimensional construct in terms of vividness and diagnosticity. In addition, we examined relationship quality as a multidimensional construct. In contrast to earlier studies [32,39,43] that measured relationship quality in terms of commitment, trust, and satisfaction, we evaluated it in terms of commitment, trust, participation, and recommendation. The results demonstrated the significant relationship between content quality and relationship quality, supporting previous studies in the mobile commerce field. This study also provided empirical evidence that this framework could be extended to the MSFV shopping context. These findings provide a better understanding of what types of MSFV shopping features would facilitate customer loyalty as well as theoretical guidance for developing HCI activities.
Third, we confirmed the mediating effect of stickiness among content quality, relationship quality, and customer loyalty. This indicates that vivid and diagnostic content and seller–buyer relationship quality can influence loyalty through stickiness. Although many studies have emphasized the importance of stickiness in virtual space, empirical research on stickiness in the context of MSFV shopping has been lacking. This study filled this gap by providing empirical evidence of the interdependence among content quality, relationship quality, stickiness, and customer loyalty in MSFV shopping. The findings indicate that stickiness is an important psychological component that can help customers to develop loyalty and participate in HCI.

6.3. Implications for Practice

In addition to theoretical contributions, this study also provides several important practical implications for MSFV shopping operators. First, the findings showed that content quality was a critical predictor of relationship quality and customer stickiness. Therefore, MSFV shopping operators need to make greater efforts to develop more mechanisms to enhance information content quality. For example, operators can improve the digital customer experience by allowing them to try out products using immersive technology such as virtual reality. Concerning vividness, MSFV shopping operators need to pay more attention to demonstrating information. They can make videos more vivid to make a more interesting and useful presentation, which will help to better target customers’ understanding of the information. They should also consider including emotionally provoking and diverse content in their advertisements so that they can interact with their customers. In addition to entertaining and engaging customers, providers need to consider incorporating a variety of incentives to increase customer engagement and customer stickiness. For example, they could add interactive links and themes to make the content more appealing and create a reward system that encourages customers to share their experiences.
Regarding diagnosticity, understanding the various elements of the multimedia presentation can also help to improve the effectiveness of MSFV shopping content. MSFV shopping operators should make reviews and posts more visible and readable to enhance digital customers’ experiences. Operators can also enlist the help of celebrities to promote their products. Celebrities must be knowledgeable about the products, and their image must be consistent with the products being sold.
Second, MSFV shopping operators must conduct market research and promote products based on customer preferences. This would help them to have a good relationship with their customers. Positive experiences in MSFV shopping would increase mutual trust between a seller and customer, contribute to a customer committing to a relationship, increase customer participation in MSFV shopping, and increase the likelihood that they recommend it to their friends. Tracking and managing customer interactions is another strategy that MSFV shopping providers could consider. This would allow them to develop more effective promotional strategies, boost conversion rates, and strengthen seller–customer relationships. Highly engaged customers are a great source of information, and providers should be able to learn from them.
Third, the results proved that stickiness mediated the relationships among content quality, relationship quality, and customer loyalty. These findings provided suggestions to MSFV shopping operators on making the content sticky. Since customer stickiness is crucial in MSFV shopping, MSFV shopping operators should develop tactics to increase customer stickiness. For instance, MSFV shopping operators could develop attractive design features and could introduce innovative functions to improve customers’ user experiences. Finally, MSFV shopping operators need to cultivate a positive customer attitude, since a positive attitude toward MSFV shopping influences customers’ evaluations. MSFV shopping operators need to take steps to offer reliable products at competitive prices, to provide better customer service after the sale, and to improve the supervision mechanism in the app to foster a positive customer attitude.

7. Limitations and Future Research Directions

Although this study provides valuable implications for research and practice, it has some limitations. First, since China is a geographically huge country, regional and economic differences are also valuable factors that would influence customer behavior, we suggest that follow-up studies take this fact into consideration. Second, we only surveyed customers from China, and cultural differences may also exist in other countries. As we know, Douyin has an international version known as TikTok. Future researchers may look at how the proposed research model works in different countries and compare the findings. Third, since the literature in the MSFV shopping area is relatively limited, this study extended theories and constructs from previous e-commerce, mobile commerce, and social commerce research. In future research, it is suggested to develop unique constructs in the MSFV shopping context. Lastly, we focused on digital customer experiences to discuss customer loyalty. Future studies could explore customer loyalty by adopting other approaches, such as the social-tech approach.

Author Contributions

Conceptualization, Q.Y. and Y.-C.L.; methodology, Q.Y. and Y.-C.L.; software, Q.Y.; validation, Q.Y. and Y.-C.L.; formal analysis, Q.Y. and Y.-C.L.; investigation, Q.Y.; data curation, Q.Y. and Y.-C.L.; writing—original draft preparation, Q.Y.; writing—review and editing, Y.-C.L.; visualization, Q.Y. and Y.-C.L.; supervision, Y.-C.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data that support the findings of this study are available from the authors upon reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table A1. Questionnaire items.
Table A1. Questionnaire items.
ConstructsMeasurement ItemsSources
Content qualityDiagnosticity (DIA)MSFV shopping is helpful for me to evaluate the product.[65]
MSFV shopping is helpful in familiarizing me with the product.
MSFV shopping is helpful for me to understand the performance of the product.
Vividness (VID)The product demonstration from MSFV shopping is clear.[65]
The product demonstration from MSFV shopping is detailed.
I can acquire product information from different sensory channels through MSFV shopping.
The MSFV shopping contains product information that is exciting to senses.
Relationship qualityCommitment (COMM)I am proud to belong to the membership of MSFV shopping. [43,84]
I feel a sense of belonging to MSFV shopping.
I care about the long-term success of MSFV shopping.
Participation (PART)I actively participate in transactions with MSFV shopping.[43,84]
I go to MSFV shopping directly to make purchase.
I actively make purchases from MSFV shopping.
Trust (TRUS)MSFV shopping provides unbiased products/services.[43,84]
MSFV shopping is honest.
I consider MSFV shopping to be of integrity.
Recommendation (RECM)I often recommend MSFV shopping to others.[43,84]
I tell my friends about MSFV shopping.
I want my friends to buy from MSFV shopping.
Stickiness (STIC)I would stay for a long time while browsing MSFV shopping.[47]
I intend to prolong my stays on MSFV shopping.
I would visit MSFV shopping frequently.
Attitudinal loyalty (AL)I feel close to MSFV shopping.[60,85]
MSFV shopping will be my favorite shopping channel.
I feel emotionally attached to MSFV shopping.
I feel like a part of a family as a customer of MSFV shopping.
Behavioral loyalty (BL)I want to continue to use MSFV shopping.[60,85]
I am willing to recommend MSFV shopping to others.
If I buy a product, I am willing to continue to buy and search for products through MSFV shopping.

References

  1. Number of Short Video Users in China 2018–2021. Available online: https://www.statista.com/statistics/1005629/china-short-video-user-number/ (accessed on 6 May 2022).
  2. Douyin User Number in China 2021–2025. Available online: https://www.statista.com/statistics/1090314/china-douyin-tiktok-user-number/ (accessed on 6 May 2022).
  3. Hu, Z.; Guo, Z. The application of short videos in the transmission of China’s excellent traditional culture—Taking the TikTok App as an example. Media Forum. 2020, 2, 72. [Google Scholar]
  4. Ren, J.; Yang, J.; Zhu, M.; Majeed, S. Relationship between consumer participation behaviors and consumer stickiness on mobile short video social platform under the development of ICT: Based on value co-creation theory perspective. Inf. Technol. Dev. 2021, 27, 697–717. [Google Scholar] [CrossRef]
  5. Wang, Y. Humor and camera view on mobile short-form video apps influence user experience and technology-adoption intent, an example of TikTok (DouYin). Comput. Hum. Behav. 2020, 110, 106373. [Google Scholar] [CrossRef]
  6. Zhang, X.; Wu, Y.; Liu, S. Exploring short-form video application addiction: Socio-technical and attachment perspectives. Telemat. Inform. 2019, 42, 101243. [Google Scholar] [CrossRef]
  7. Zeng, N. Using Motivation of Short Video Advertising Marketing in China: An Exploratory Study of Douyin. J. Korea. Soc. Comput. Inf. 2021, 26, 229–237. [Google Scholar]
  8. Mulier, L.; Slabbinck, H.; Vermeir, I. This way up: The effectiveness of mobile vertical video marketing. J. Interact. Mark. 2021, 55, 1–15. [Google Scholar] [CrossRef]
  9. Mou, X.; Xu, F.; Du, J.T. Examining the factors influencing college students’ continuance intention to use short-form video APP. Aslib J. Inf. Manag. 2021, 73, 992–1013. [Google Scholar] [CrossRef]
  10. Xiao, Y.; Wang, L.; Wang, P. Research on the influence of content features of short video marketing on consumer purchase intentions. In Proceedings of the 4th International Conference on Modern Management, Education Technology and Social Science, Dalian, Chian, 20–22 September 2019; pp. 415–422. [Google Scholar]
  11. Meng, K.S.; Leung, L. Factors influencing TikTok engagement behaviors in China: An examination of gratifications sought, narcissism, and the Big Five personality traits. Telecomm. Policy 2021, 45, 102172. [Google Scholar] [CrossRef]
  12. Anderson, K.C.; Knight, D.K.; Pookulangara, S.; Josiam, B. Influence of hedonic and utilitarian motivations on retailer loyalty and purchase intention: A Facebook perspective. J. Retail. Consum. Serv. 2014, 21, 773–779. [Google Scholar] [CrossRef]
  13. Hew, J.J.; Lee, V.H.; Ooi, K.B.; Lin, B. Mobile social commerce: The booster for brand loyalty? Comput. Hum. Behav. 2016, 59, 142–154. [Google Scholar] [CrossRef]
  14. Cheng, X.; Gu, Y.; Shen, J. An integrated view of particularized trust in social commerce: An empirical investigation. Int. J. Inf. Manag. 2019, 45, 1–12. [Google Scholar] [CrossRef]
  15. Molinillo, S.; Anaya-S’ anchez, R.; Li’ ebana-Cabanillas, F. Analyzing the effect of social support and community factors on customer engagement and its impact on loyalty behaviors toward social commerce websites. Comput. Hum. Behav. 2020, 108, 105980. [Google Scholar] [CrossRef]
  16. Nadeem, W.; Khani, A.H.; Schultz, C.D.; Adam, N.A.; Attar, R.W.; Hajli, N. How social presence drives commitment and loyalty with online brand communities? the role of social commerce trust. J. Retail. Consum. Serv. 2020, 55, 102136. [Google Scholar] [CrossRef]
  17. Jacoby, J.; Chestnut, R.W.; Fisher, W.A. A behavioral process approach to information acquisition in nondurable purchasing. J. Market. Res. 1978, 15, 532–544. [Google Scholar] [CrossRef]
  18. Cachero-Martínez, S.; Vázquez-Casielles, R. Building consumer loyalty through e-shopping experiences: The mediating role of emotions. J. Retail. Consum. Serv. 2021, 60, 102481. [Google Scholar] [CrossRef]
  19. Bandyopadhyay, S.; Martell, M. Does attitudinal loyalty influence behavioral loyalty? A theoretical and empirical study. J. Retail. Consum. Serv. 2007, 14, 35–44. [Google Scholar] [CrossRef]
  20. Paniagua, J.; Sapena, J. Business performance and social media: Love or hate? Bus. Horiz. 2014, 57, 719–728. [Google Scholar] [CrossRef]
  21. Omar, B.; Dequan, W. Watch, share or create: The influence of personality traits and user motivation on TikTok mobile video usage. Int. J. Interact. Mob. Technol. 2020, 14, 121–137. [Google Scholar] [CrossRef]
  22. Wright, C. Are beauty bloggers more influential than traditional industry experts? J. Prom. Commun. 2017, 5, 303–322. [Google Scholar]
  23. Huizingh, E.K. The content and design of web sites: An empirical study. Inf. Manag. 2000, 37, 123–134. [Google Scholar] [CrossRef]
  24. Davis, F.D. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 1989, 13, 319–340. [Google Scholar] [CrossRef]
  25. Jung, Y.; Perez-Mira, B.; Wiley-Patton, S. Consumer adoption of mobile TV: Examining psychological flow and media content. Comput. Hum. Behav. 2009, 25, 123–129. [Google Scholar] [CrossRef]
  26. Schilit, B.; Adams, N.; Want, R. Context-aware computing applications. In Proceedings of the 1994 First Workshop on Mobile Computing Systems and Applications, Santa Cruz, CA, USA, 8–9 December 1994; IEEE: Piscataway, NJ, USA, 1994; pp. 85–90. [Google Scholar]
  27. Yang, H.; Lee, H. Exploring user acceptance of streaming media devices: An extended perspective of flow theory. Inf. Syst. E-Bus. Manag. 2018, 16, 1–27. [Google Scholar] [CrossRef]
  28. Jiang, Z.; Benbasat, I. The effects of presentation formats and task complexity on online consumers’ product understanding. MIS Q. 2007, 31, 475–500. [Google Scholar] [CrossRef]
  29. Yin, C.; Zhang, X. Incorporating message format into user evaluation of microblog information credibility: A nonlinear perspective. Inf. Process. Manag. 2020, 57, 102345. [Google Scholar] [CrossRef] [PubMed]
  30. Hennig-Thurau, T.; Klee, A. The impact of customer satisfaction and relationship quality on customer retention: A critical reassessment and model development. Psychol. Mark. 1997, 14, 737–764. [Google Scholar] [CrossRef]
  31. 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]
  32. 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. 2020, 121, 476–486. [Google Scholar] [CrossRef]
  33. 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. 2021, 115, 105238. [Google Scholar] [CrossRef]
  34. Moorman, C.; Deshpande, R.; Zaltman, G. Factors affecting trust in market research relationships. J. Mark. 1993, 57, 81–101. [Google Scholar] [CrossRef]
  35. Gustafsson, A.; Johnson, M.D.; Roos, I. The effects of customer satisfaction, relationship commitment dimensions, and triggers on customer retention. J. Mark. 2005, 69, 210–218. [Google Scholar] [CrossRef]
  36. Wisker, Z.L. Examining relationship quality in e-tailing experiences: A moderated mediated model. Mark. Intell. Plan. 2020, 38, 863–876. [Google Scholar] [CrossRef]
  37. 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]
  38. Tajvidi, R.; Karami, A. The effect of social media on firm performance. Comput. Hum. Behav. 2021, 115, 105174. [Google Scholar] [CrossRef]
  39. 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]
  40. Maslow, A.H. The instinctoid nature of basic needs. J. Pers. 1954, 22, 326–347. [Google Scholar] [CrossRef]
  41. Lin, J.; Li, L.; Yan, Y.; Turel, O. Understanding Chinese consumer engagement in social commerce: The roles of social support and swift guanxi. Internet Res. 2018, 28, 2–22. [Google Scholar] [CrossRef]
  42. Dashti, M.; Sanayei, A.; Dolatabadi, H.R.; Javadi, M.H.M. Application of the stimuli-organism-response framework to factors influencing social commerce intentions among social network users. Int. J. Bus. Inf. Syst. 2019, 30, 177–202. [Google Scholar] [CrossRef]
  43. 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]
  44. Lin, J.; Luo, Z.; Cheng, X.; Li, L. Understanding the interplay of social commerce affordances and swift guanxi: An empirical study. Inf. Manag. 2019, 56, 213–224. [Google Scholar] [CrossRef]
  45. El-Manstrly, D.; Ali, F.; Steedman, C. Virtual travel community members’ stickiness behaviour: How and when it develops. Int. J. Hosp. Manag. 2020, 88, 102535. [Google Scholar] [CrossRef]
  46. Friedrich, T.; Schlauderer, S.; Overhage, S. The impact of social commerce feature richness on website stickiness through cognitive and affective factors: An experimental study. Electron. Commer. Res. Appl. 2019, 36, 100861. [Google Scholar] [CrossRef]
  47. Zhang, M.; Guo, L.; Hu, M.; Liu, W. Influence of customer engagement with company social networks on stickiness: Mediating effect of customer value creation. Int. J. Inf. Manag. 2017, 37, 229–240. [Google Scholar] [CrossRef]
  48. Hu, L.; Min, Q.; Han, S.; Liu, Z. Understanding followers’ stickiness to digital influencers: The effect of psychological responses. J. Inf. Manag. 2020, 54, 102169. [Google Scholar] [CrossRef]
  49. Hsu, C.L.; Lin, J.C.C. Effect of perceived value and social influences on mobile app stickiness and in-app purchase intention. Technol. Forecast. Soc. Chang. 2016, 108, 42–53. [Google Scholar] [CrossRef]
  50. Roy, S.K.; Lassar, W.M.; Butaney, G.T. The mediating impact of stickiness and loyalty on word-of-mouth promotion of retail websites: A consumer perspective. Eur. J. Mark. 2014, 48, 1828–1849. [Google Scholar]
  51. Wang, W.T.; Wang, Y.S.; Liu, E.R. The stickiness intention of group-buying websites: The integration of the commitment–trust theory and e-commerce success model. Inf. Manag. 2016, 53, 625–642. [Google Scholar] [CrossRef]
  52. Martinez, B.M.; McAndrews, L.E. The influence of mobile application design features on users’ stickiness intentions as mediated by emotional response. Int. J. Retail. Distrib. Manag. 2021, 49, 1497–1511. [Google Scholar] [CrossRef]
  53. Nandi, S.; Nandi, M.L.; Khandker, V. Impact of perceived interactivity and perceived value on mobile app stickiness: An emerging economy perspective. J. Consum. Mark. 2021, 38, 721–737. [Google Scholar] [CrossRef]
  54. Yin, M.; Tayyab, S.M.U.; Xu, X.Y.; Jia, S.W.; Wu, C.L. The investigation of mobile health stickiness: The role of social support in a sustainable health approach. Sustainability 2021, 13, 1693. [Google Scholar] [CrossRef]
  55. Tanford, S. The impact of tier level on attitudinal and behavioral loyalty of hotel reward program members. Int. J. Hosp. Manag. 2013, 34, 285–294. [Google Scholar] [CrossRef]
  56. Saini, S.; Singh, J. A link between attitudinal and behavioral loyalty of service customers. Bus. Perspect. Res. 2020, 8, 205–215. [Google Scholar] [CrossRef]
  57. Dick, A.S.; Basu, K. Customer loyalty: Toward an integrated conceptual framework. J. Acad. Mark. Sci. 1994, 22, 99–113. [Google Scholar] [CrossRef]
  58. East, R.; Gendall, P.; Hammond, K.; Lomax, W. Customer loyalty: Singular, additive or interactive? Australas. Mark. J. 2005, 13, 10–26. [Google Scholar] [CrossRef]
  59. Kaur, P.; Dhir, A.; Chen, S.; Rajala, R. Attitudinal and behavioral loyalty toward virtual goods. J. Comput. Inf. Syst. 2021, 61, 118–129. [Google Scholar] [CrossRef]
  60. Kim, Y.; Wang, Q.; Roh, T. Do information and service quality affect perceived privacy protection, satisfaction, and loyalty? Evidence from a Chinese O2O-based mobile shopping application. Telemat. Inform. 2021, 56, 101483. [Google Scholar] [CrossRef]
  61. Soedarto, T.; Kurniawan, G.S.A.; Sunarsono, R.J. The parceling of loyalty: Brand quality, brand affect, and brand trust effect on attitudinal loyalty and behavioral loyalty. Acad. Strateg. Manag. J. 2019, 18, 1–15. [Google Scholar]
  62. Bao, Z.; Zhu, Y. Understanding customers’ stickiness of live streaming commerce platforms: An empirical study based on modified e-commerce system success model. Asia Pac. J. Market. Logist. 2022; ahead-of-print. [Google Scholar]
  63. Lin, X.; Featherman, M.; Brooks, S.L.; Hajli, N. Exploring gender differences in online consumer purchase decision making: An online product presentation perspective. Inf. Syst. Front. 2019, 21, 1187–1201. [Google Scholar] [CrossRef]
  64. Filieri, R. What makes online reviews helpful? A diagnosticity-adoption framework to explain informational and normative influences in e-WOM. J. Bus. Res. 2015, 68, 1261–1270. [Google Scholar] [CrossRef]
  65. Chen, J.V.; Ruangsri, S.; Ha, Q.A.; Widjaja, A.E. An experimental study of consumers’ impulse buying behaviour in augmented reality mobile shopping apps. Behav. Inf. Technol. 2021, 1–22. [Google Scholar] [CrossRef]
  66. Liang, X.; Hu, X.; Islam, T.; Mubarik, M.S. Social support, source credibility, social influence, and solar photovoltaic panels purchase intention. Environ. Sci. Pollut. Res. 2021, 28, 57842–57859. [Google Scholar] [CrossRef] [PubMed]
  67. Li, Y.; Li, X.; Cai, J. How attachment affects user stickiness on live streaming platforms: A socio-technical approach perspective. J. Retail. Consum. Serv. 2021, 60, 102478. [Google Scholar] [CrossRef]
  68. Polites, G.L.; Williams, C.K.; Karahanna, E.; Seligman, L. A theoretical framework for consumer e-satisfaction and site stickiness: An evaluation in the context of online hotel reservations. J. Organ. Comput. Electron. Commer. 2012, 22, 1–37. [Google Scholar] [CrossRef]
  69. Yang, H.L.; Lin, C.L. Why do people stick to Facebook web site? A value theory-based view. Inf. Technol. People 2014, 27, 21–37. [Google Scholar] [CrossRef]
  70. Malinen, S. Understanding user participation in online communities: A systematic literature review of empirical studies. Comput. Hum. Behav. 2015, 46, 228–238. [Google Scholar] [CrossRef]
  71. Lin, J.C.C. Online stickiness: Its antecedents and effect on purchasing intention. Behav. Inf. Technol. 2007, 26, 507–516. [Google Scholar] [CrossRef]
  72. Lu, H.P.; Lee, M.R. Demographic differences and the antecedents of blog stickiness. Online Inf. Rev. 2010, 34, 21–38. [Google Scholar] [CrossRef]
  73. Lin, H.F. The role of online and offline features in sustaining virtual communities: An empirical study. Internet Res. 2007, 17, 119–138. [Google Scholar] [CrossRef]
  74. Xu, F.; Qi, Y.; Li, X. What affects the user stickiness of the mainstream media websites in China? Electron. Commer. Res. Appl. 2018, 29, 124–132. [Google Scholar] [CrossRef]
  75. Wang, Y.S. Assessing e-commerce systems success: A respecification and validation of the DeLone and McLean model of IS success. Inf. Syst. J. 2008, 18, 529–557. [Google Scholar] [CrossRef]
  76. Singh, S.; Singh, N.; Kalinić, Z.; Liébana-Cabanillas, F.J. Assessing determinants influencing continued use of live streaming services: An extended perceived value theory of streaming addiction. Expert Syst. Appl. 2021, 168, 114241. [Google Scholar] [CrossRef]
  77. Lin, L.; Hu, P.J.H.; Sheng, O.R.L.; Lee, J. Is stickiness profitable for electronic retailers? Commun. ACM 2010, 53, 132–136. [Google Scholar] [CrossRef]
  78. Chen, M.H.; Tsai, K.M.; Ke, Y.A. Enhancing Consumers’ Stickiness to Online Brand Communities as an Innovative Relationship Marketing Strategy. Int. J. Semant. Web. Inf. Syst. 2019, 15, 16–34. [Google Scholar] [CrossRef]
  79. Holland, J.; Menzel Baker, S. Customer participation in creating site brand loyalty. J. Interact. Mark. 2001, 15, 34–45. [Google Scholar] [CrossRef]
  80. Kabadayi, S.; Gupta, R. Website Loyalty: An Empirical Investigation of Its Antecedents. Int. J. Internet Mark. Advert. 2005, 2, 321–345. [Google Scholar] [CrossRef]
  81. Huang, L.; Jia, L.; Song, J. Antecedents of user stickiness and loyalty and their effects on users’ group-buying repurchase intention. In Proceedings of the Twenty First Americas Conference on Information Systems, Fajardo, Puerto Rico, 13–15 August 2015. [Google Scholar]
  82. Glasman, L.R.; Albarracín, D. Forming attitudes that predict future behavior: A meta-analysis of the attitude-behavior relation. Psychol. Bull. 2006, 132, 778. [Google Scholar] [CrossRef]
  83. Yao, T.; Qiu, Q.; Wei, Y. Retaining hotel employees as internal customers: Effect of organizational commitment on attitudinal and behavioral loyalty of employees. Int. J. Hosp. Manag. 2019, 76, 1–8. [Google Scholar] [CrossRef]
  84. Hu, T.; Dai, H.; Salam, A.F. Integrative qualities and dimensions of social commerce: Toward a unified view. Inf. Manag. 2019, 56, 249–270. [Google Scholar] [CrossRef]
  85. Ferm, L.E.C.; Thaichon, P. Customer pre-participatory social media drivers and their influence on attitudinal loyalty within the retail banking industry: A multi-group analysis utilizing social exchange theory. J. Retail. Consum. Serv. 2021, 61, 102584. [Google Scholar] [CrossRef]
  86. Gefen, D.; Rigdon, E.E.; Straub, D. Editor’s comments: An update and extension to SEM guidelines for administrative and social science research. MIS Q. 2011, 35, iii–xiv. [Google Scholar] [CrossRef]
  87. 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]
  88. Hair, J.F., Jr.; Anderson, R.E.; Tatham, R.L.; Black, W.C. Multivariate Data Analysis; Prentice-Hall: New Jersey, NJ, USA, 1998. [Google Scholar]
  89. Podsakoff, P.M.; MacKenzie, S.B.; Lee, J.Y.; Podsakoff, N.P. Common method biases in behavioral research: A critical review of the literature and recommended remedies. J. Appl. Psychol. 2003, 88, 879. [Google Scholar] [CrossRef] [PubMed]
  90. Uhm, J.P.; Kim, S.; Do, C.; Lee, H.W. How augmented reality (AR) experience affects purchase intention in sport E-commerce: Roles of perceived diagnosticity, psychological distance, and perceived risks. J. Retail. Consum. Serv. 2022, 67, 103027. [Google Scholar] [CrossRef]
  91. Song, S.; Zhao, Y.C.; Yao, X.; Ba, Z.; Zhu, Q. Short video apps as a health information source: An investigation of affordances, user experience and users’ intention to continue the use of TikTok. Internet Res. 2021, 31, 2120–2142. [Google Scholar] [CrossRef]
  92. Li, J.; Zhao, H.; Hussain, S.; Ming, J.; Wu, J. The Dark Side of Personalization Recommendation in Short-Form Video Applications: An Integrated Model from Information Perspective. In International Conference on Information; Springer: Cham, Switzerland, 2021; pp. 99–113. [Google Scholar]
  93. Gurcan, F.; Cagiltay, N.E.; Cagiltay, K. Mapping human–computer interaction research themes and trends from its existence to today: A topic modeling-based review of past 60 years. Int. J. Hum.-Comput. Int. 2021, 37, 267–280. [Google Scholar] [CrossRef]
Figure 1. Research model. Note: Content quality and relationship quality are measured as second-order constructs.
Figure 1. Research model. Note: Content quality and relationship quality are measured as second-order constructs.
Sustainability 14 10890 g001
Table 1. Respondents’ demographics.
Table 1. Respondents’ demographics.
DemographicFrequencyPercentage (%)
GenderMale34544.3
Female43355.7
AgeUnder 25 years9712.5
25–34 years31941
35–44 years17822.9
45–54 years12115.6
55 years and above638
Monthly income (CNY) Less than 2000476.1
2000–390015119.4
4000–590018824.2
6000–790016921.7
8000–990012415.9
10,000 and above9912.7
Time duration since using MSFV shoppingLess than one year 607.7
1–2 years 24631.6
2–3 years31640.6
More than 3 years15620.1
Monthly spending on MSFV shopping (CNY)Less than 100031440.4
1001–200028937.1
2001–300010213.1
3001–4000445.7
4001 and above293.7
Table 2. Factor loading, CR, and AVE.
Table 2. Factor loading, CR, and AVE.
ConstructsItemsItem LoadingsCRAVE
Diagnosticity DIA10.7700.8150.594
DIA20.790
DIA30.752
Vividness VIV10.7950.8730.633
VIV20.800
VIV30.786
VIV40.801
CommitmentCOMM10.7690.8020.575
COMM20.789
COMM30.715
ParticipationPART10.8070.8200.604
PART20.748
PART30.775
Trust TRUS10.6230.7860.553
TRUS20.781
TRUS30.813
Recommendation RECM10.7690.8170.599
RECM20.768
RECM30.784
StickinessSTIC10.7270.7890.555
STIC20.749
STIC30.759
Attitudinal loyaltyAL10.7890.8590.604
AL20.736
AL30.763
AL40.819
Behavioral loyaltyBL10.7900.8340.627
BL20.713
BL30.865
Table 3. Discriminant validity.
Table 3. Discriminant validity.
RQCQSTICALBL
RQ0.764
CQ0.489 **0.785
STIC0.543 **0.488 **0.772
AL0.381 **0.392 **0.475 **0.765
BL0.412 **0.329 **0.515 **0.508 **0.802
Note: ** p < 0.01. RQ, Relationship quality; CQ, content quality, STIC, stickiness, AL, attitudinal loyalty; BL, behavioral loyalty. Values in bold represent the square root of the AVE.
Table 4. Hypothesis test results.
Table 4. Hypothesis test results.
HypothesisPathβp-ValueR2Remarks
H1CQRQ0.70<0.0010.49Supported
H2RQSTIC0.428<0.0010.537Supported
H3CQSTIC0.367<0.001Supported
H4STICAL0.597<0.0010.356Supported
H5STICBL0.509<0.0010.523Supported
H6ALBL0.292<0.001Supported
Note: CQ, content quality; RQ, relationship quality; STIC, stickiness; AL, attitudinal loyalty; BL, behavioral loyalty.
Table 5. Model fit.
Table 5. Model fit.
Fit Indicesx2/dfGFIAGFINFICFIPGFIRMRRMSEA
Recommended value<3.0>0.9>0.8>0.9>0.9>0.6<0.08<0.08
Actual value2.1420.9360.9240.9320.9620.7850.0350.038
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Yang, Q.; Lee, Y.-C. What Drives the Digital Customer Experience and Customer Loyalty in Mobile Short-Form Video Shopping? Evidence from Douyin (TikTok). Sustainability 2022, 14, 10890. https://doi.org/10.3390/su141710890

AMA Style

Yang Q, Lee Y-C. What Drives the Digital Customer Experience and Customer Loyalty in Mobile Short-Form Video Shopping? Evidence from Douyin (TikTok). Sustainability. 2022; 14(17):10890. https://doi.org/10.3390/su141710890

Chicago/Turabian Style

Yang, Qin, and Young-Chan Lee. 2022. "What Drives the Digital Customer Experience and Customer Loyalty in Mobile Short-Form Video Shopping? Evidence from Douyin (TikTok)" Sustainability 14, no. 17: 10890. https://doi.org/10.3390/su141710890

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop