Factors Impacting Repurchase Intentions in Social Commerce Platforms: An Innovative and Expanding Business Model

Through information technology, the world is moving towards the digital economy, giving rise to social commerce. This type of marketing be considered a new form of e-commerce that incorporates a holistic approach to social media with the aim of helping users buy and sell products and services online. This empirical research aims to estimate the effects of the cognitive and emotional mechanisms of consumer trust and intimacy on repurchase in social commerce platforms. Thus, it aims to analyze in detail the behavior of consumers based on satisfaction and user-generated content, focusing on the moderating role of the buying habit between trust and repurchase, intimacy and repurchase. In this research, a quantitative study was conducted, targeting Morocco in order to analyze the effects of cognitive and emotional mechanisms on consumers' repurchase intention regarding social commerce platforms. Based on this, we studied the behavior of 3,854 social media users, 2,251 of whom have already made purchase on social commerce platforms. We employed econometric modeling using partial least squares-based structural equation modeling (PLS-SEM). The results of the structural equation estimation on all individuals who have already purchased on online sales platforms (2,251), showed firstly that there is a significant and positive relationship between the cognitive factors (Satisfaction and Confidence) on the intention and the repurchase behavior. As for the emotional factors (UGC and Intimacy), the relationship between these two constructs was found to be non-significant. However, intimacy was found to positively impact repurchase intention and behavior under moderation of buying habits.
JEL Classification M31
Full Article


The Internet is the backbone of our society, the evolution of social media first began with the advent of the e-mail that helped people communicate and network with their friends, family and peers across the globe. The most innovative development that has taken place since the beginning of the 21st century has been the social media revolution, which has brought millions of people much closer to each other who can share their views with others “anytime and anywhere”. The internet-based portals that were once launched to create platforms to help people associate online, have now become gateways to building brands and strengthening relationships with customers. They are creating new and numerous businesses and marketing challenges for organizations every day. It thereby becomes imperative to first know what these websites, platforms or applications are, understand what role they play in the society and how they impact consumer behavior and brand loyalty (Yang et al., 2021). The rise of social networking sites (SNS) has ushered in a new era in human development, which has met the age-old human need for social gratification (Meilatinova, 2021).

This empirical study investigates how consumers trust and intimacy are considered as cognitive and emotional mechanisms that influence the consumer’s intention to repurchase in social commerce and also explore the moderating role of shopping habit between trust and repurchase and intimacy and repurchase. These effects widely vary and differ across context of an economy; it is noticeable in the context of developing country against developed country. This research claims to investigate the application of these variables in social commerce under the context of Morocco. The aim of the manuscript is to advance what leads consumers to repurchase and not only purchase a specific good or service.

2.Literature Review

2.1. Social Commerce

New business model has opened up for electronic commerce, often called social commerce, involving the use of web 2.0 social media technology and infrastructure to help online commerce and user engagement. In 2005, the term social commerce was proposed for the first time by Yahoo! and with the participation of consumers of other social commerce platforms such as Amazon and Ebay, the concept social commerce start gaining popularity among users according to Zhang and Wang (2012). Social trading involves interpersonal partnerships and activities such as product appraisal, sharing of product information and reviews (Richter et al., 2007). According to Zong (2013), social trade is a business model that markets and sells goods or services through the combination of the social graph (interpersonal interaction) and the social media engagement graph (information flow interaction).

2.2.Cognitive Mechanisms

Repurchase decisions are partly influenced by irrational and rational factors such as satisfaction and trust, most repurchase decisions are the result of cognitive, emotional and behavioral factors.

2.2.1.Customer Satisfaction

According to Bloemer and Schröder (2002, pp.62-73), consumer satisfaction is the result of a process of comparison between expected and perceived performance. This process uses the paradigm of non-confirmation expectancy. This paradigm, also known as the expectancy confirmation model (ECM), is widely used in consumer behaviour studies. It was first developed by Oliver in 1980 and further developed by Anderson and Sullivan (1993, pp.125-143). According to ECM, consumers’ intention to repurchase a good is determined by their previous experiences with that product or service.

Consumers may consider their satisfaction as a general emotion related to their experience with a website. Some authors, such as Fournier and Glen Mick (1999, pp.5-23), Arnould and Price (1993, pp. 24-45), consider satisfaction as a pure emotion without any cognitive process.

Many researchers have studied online satisfaction with online consumption experiences. Anderson and Srinivasan (2003, pp. 123-138) stated that it is an overall assessment of a website’s ability to meet the needs and expectations of its online users. Customer satisfaction is based on many experiences within the same relationship. It involves two specific aspects: the extrinsic or cognitive elements. The satisfaction generated by the extrinsic elements depends on the ability of the seller to achieve the set objectives. M’barki and Abakouy (2012, pp. 956-975) state that "satisfaction is the result of a series of experiences."


Trust has been studied in many areas, including economics and marketing (Kim and Benbasat, 2009, p. 216). Trust is composed of two stages called pre-purchase (before purchasing a good or a service) and post-purchase (after purchasing a good or a service) Zhang et al., 2011, (p. 677). We focus on the impact of trust and its antecedents on repurchase, as consumers tend to evaluate the good or service based on its actual performance after consumption, and after this first experience, they are likely to reevaluate their trust perception according to (Hsu et al., 2014, p. 727). In this situation, a repeated or familiar interaction can lead to mistrust or trust and is only present when the consumer wants to repurchase, making it a major source of trust (Ba and Pavlou, 2002, p. 38). The term "Trust" can be defined as "confidence in or reliance on some quality or attribute of a person or thing, or the truth in a statement" Furman, 2009, (p. 23).

Researchers such as Dwyer and Lagace (1986, p. 1), Smith and Barclay (1997, p. 12) have identified two main concepts of trust. The first equates trust with cognitive expectations or feelings, while the second equates trust with risky behaviour. McKnight et al. (2002, p. 4) argue that trust has three dimensions: benevolence (focusing on the interests of others), competence (technical skills and expertise), and integrity (keeping promises).

2.3.Emotional Mechanisms

In the context of repurchase on social commerce platforms, user-generated content and intimacy are considered emotional factors that can significantly impact repurchase intentions.

2.3.1.User Generated Content

According to O’Conner (2008, p. 27), user-generated content (UGC) is an important element in the buyer’s decision-making. Additionally, Dennhardt (2014, p. 396) noted that UGC presents a unique storytelling opportunity for marketers to enhance their brand, which builds trust between customers and the brands they are associated with. Gangi and Wasco (2009, p. 15) believed that UGC provides competitive advantages and new forms of value.

Previous literature has shown the relevance of UGC in various aspects. For instance, Chevalier and Mayzlin (2006, p. 345) and Lee and Han (2008, p. 33) explored the motivations of customers to create certain content, co-creation management, and the relationship between UGC and mercantile outcomes such as sales. Berthon (2008, p. 1) and Burmann (2010, p. 47) examined consumer and brand-generated advertisements. Moreover, Vadakkepatt, and Joshi (2015, p. 391) analyzed the UGC relationship and meaningful mercantile outcomes such as sales.

Abdelkader and Ebrahim (2021, p. 789) identified the mediating role of customer engagement (CE) between merchant-generated content (MGC) and UGC and repurchase intention in an online airline service community. Their results showed that UGC has a greater impact on CE and its dimensions than MGC. Additionally, customer engagement was found to be an important mediator of the relationship between merchants and UGC and repurchase intention.


Customer intimacy, which includes closeness, value, and mutual understanding, has been defined as a multidimensional construct (Baumannand Le Meunier-FitzHugh, 2014, p. 861; Brock and Zhou, 2012, p. 520; Sirdeshmukh et al., 2002, p. 18). Proximity, which refers to feelings of mutual empathy, commitment, emotional connection, and a sense of security in the relationship, is one of the dimensions of customer intimacy. Customer loyalty, on the other hand, is demonstrated by the consumer’s understanding of the value of maintaining a long-term relationship with a company, known as value perceptions (Baumannand Le Meunier-FitzHugh, 2014, p. 861; Brock and Zhou, 2012, p. 520; Sirdeshmukh et al., 2002, p. 19).

Bapna and Umyarov’s (2016, p. 872) model proposes that individuals are more likely to follow the opinions of their friends when they have few. Moreover, their model suggests that people in different intimate relationship groups may have varying preferences when it comes to purchasing products. This is due to the fact that these relationships influence how consumers perceive products, which consequently affects their willingness to buy initially and repurchase afterwards.

2.4.Repurchase Intention

Marketing research has highlighted the importance of consumer repurchase intention as one of the success factors of e-commerce (Liao et al., 2017, p. 87; Pee et al., 2018, p. 98); Zhang et al., 2011, p. 318). Consumer repurchase intention is part of consumer loyalty, which is defined as the good attitude of consumers of a particular retailer (Choi & Mai, 2018, p. 424). Acquiring new customers takes more time and effort than retaining existing customers.

Understanding consumers’ preferences for repurchase intention is an important issue for marketers and researchers. Previous B2C research has used social psychological theories to explain the formation, antecedents, and consequences of repurchase intention. Among them, expectation confirmation theory (ECT) Liao et al., (2017, p. 88) is one of the most commonly used theories. The theory suggests that satisfaction is a key factor affecting consumer repurchase intention, based on dis/confirmation by comparing expectations and performance. Previous studies have assumed that e-tailers’ ethics are the main focus of consumers’ pre-purchase expectations and post-purchase dis/confirmations (Yang et al., 2009, p. 441).

Previous studies have also used other theories to examine consumer repurchase intentions, such as Theory of Planned Behavior (TPB) (Pavlou & Fygenson, 2006, p. 125), Social Exchange Theory (SET) (Chou and Hsu, 2016, pp. 110-114), and Technology Acceptance Model (TAM) (Chiu et al., 2009, p. 994)

The framework proposed in Figure 1 projects the relationship between cognitive factors represented by customer satisfaction and trust and the emotional construct represented by brand-related UGC and intimacy, emphasizing the moderating role of purchase habit in the relationship between trust, intimacy and repurchase. In this model, perceived risk, social commerce interactions and corporate reputation are considered as control variables.

3.Research Hypotheses

3.1.Customer Satisfaction and Trust

This study considers satisfaction as a predictor of trust. This argument is supported by Dabholkar and Sheng (2012, pp. 99-111) who tested the effect of satisfaction on trust in online business transactions. A study by Ou and Sin (2003, p. 522) also confirmed the impact of customer satisfaction on trust, and they suggested that in order to build customer trust on the Internet, e-merchants must first address the privacy and security needs of Internet shoppers.

Boshoff and du Plessis (2009, p. 224) argue that trust is crucial in relationships, which means that customers must have a pleasant experience before they can be satisfied and ultimately lead to trust. Thus, deduced from the previous discussion, we propose the following hypothesis:

H1: Customer satisfaction has a positive impact on trust in social commerce

3.2.Customer Satisfaction and Intimacy

The relationship between consumer satisfaction and intimacy is regulated by Sternberg’s theory of love. Sternberg (1986, 1988, p. 201) defines love in three components (intimacy, passion, commitment), the larger the triangle, the more important the love. Intimacy refers to the connectedness of a relationship in social commerce, online users can get a warm experience of a service that will subsequently lead to satisfaction, and then intimacy by sharing the positive experience online, either in groups, forums or among friends and family.

In this study, the construction of intimacy is seen as an affective mechanism by which users feel close to each other through online chat and the exchange of experiences. In contrast to the existing literature that deals with commitment, the research on the concept of intimacy and relationship with the company assumes that individuals are motivated to engage in relationships (Emerson 1987, p. 96), that as relationships develop, interactions increase and consumers become intimate, followed by stronger attachments and positive emotions (Saavedra and Van Dyne 1999, p. 174).

H2: Customer satisfaction positively impacts customer intimacy.

3.3.User Generated Content and Customer Trust

Cheung et al. (2017, pp.177-180) argue that trust is, in fact, a factor influencing attitudes towards technology. Consumers’ attitudes towards online group buying directly affect the credibility of websites (Suki, 2017, p. 53). One theory explaining the relationship between these constructs is the Persuasive Knowledge Model (PKM), which argues that content generated by marketers activates consumers’ manipulative intent references, leading to uncertainty, but when brand-related references exist, it is considered more reliable, especially if it is organic rather than sponsored (Wei and Lu, 2013, p. 61).

Therefore, based on the above literature and empirical evidence, this study hypothesis the following:

H3: There is a positive relationship between user-generated content and consumer trust.

3.5.User Generated Content and Customer Intimacy

User-generated content and intimacy are treated as emotional mechanisms in this study, and the theory used to illustrate the relationship between these two constructs is accessibility diagnosis theory (Cheung et al., 2017, p. 5). As mentioned earlier, brand-related UGC in social media equates to Word of Mouth (WoM) recommendation, while some studies have shown that the transmission of WOM often has a strong impact on product or service judgments. For example, when consumers choose an automobile diagnostic center (Engel, Blackwell, & Kegerreis, 1969, p. 3), when choosing a doctor (Feldman and Spencer, 1965, p. 156), or when considering the purchase of a new product or service (Arndt, 1967, p. 291; Brown and Reingen, 1987, p. 350; Reagan & Kernan, 1986, p. 131; Riggins, 1983, p. 51).

H4: There is a positive relationship between user-generated content and intimacy.

3.6.Trust and Repurchase Intention

McCole and Palmer (2001, p. 212) state that "online repurchase requires customer trust." This assertion is supported by previous research that found positive links between customers’ beliefs about trust and their intentions to buy online as mentioned by Spreng et al., (1996, pp. 15-23); Oliver & Linder, (1981, p.412). Additionally, a body of literature has consistently demonstrated that customers are more likely to make purchases on websites that they trust based on arguments proposed byMcKnight & Chervany, (2001, pp.36-40). Trust is also a critical factor that influences customers’ willingness to browse products and make purchases on online platforms, regardless of their level of experience with online shopping Pavlou & Gefen, (2004, p.39). Finally, Sullivan (2018) found that users who trust social commerce communities are more likely to redeem online. Thus, trust plays a significant role in users’ decision-making processes when it comes to social commerce (Sullivan 2018). Therefore, we propose the following hypothesis:

H5: The higher the trust in social commerce, the more willing online shopping customers are to repurchase.

3.7.Intimacy and Repurchase Intention

Research results initiated by Brock and Zhou, (2012, pp. 110-115) show that consumer intimacy has a positive impact on repurchase intention, and that high customer intimacy can also encourage consumers to return to purchase on social commerce platforms. Product and service recommendations in social commerce can improve the credibility of the information.

Online users’ willingness to buy is also influenced by friends or family members. Bapna and Umyarov, (2015, p. 356) revealed the fact that the fewer friends’ online customers have, the more likely they are to follow their advice and recommendations. This statement explains the importance of the number of friends and family when it comes to privacy influencing a user’s repurchase intention. The more information that is exchanged, the more likely online customers are to adopt the views expressed by those around them. Based on the above discussion, Hypothesis 6 is proposed:

H6: Intimacy between users in social commerce can help increase customers’ willingness to repurchase.

3.8.The Moderating Role of Shopping Habits

Online shopping habits refer to the extent to which people automatically make purchases based on their past online shopping experiences (Chiu et al., 2005, p. 459); Limayem et al., 2000, p. 421). According to previous studies, the relationship between habit and purchase intention can be classified under two perspectives, as mentioned by Khalifa and Liu, (2007, p. 780): the first is that habits have a direct effect on repurchase intentions, and the second perspective is that habits modulate the relationship between repurchase intention and its antecedent factors.

This study uses cognitive and emotional mechanisms to explain the relationship between consumer trust and repurchase intention, and intimacy and repurchase intention under the moderation of buying habits, as mentioned by Chou and Hsu, (2016, pp. 28-29). Attachment reflects consumers’ online reputation and the attractiveness and benefits derived from their relationships with retailers to maintain a strong relationship with them (Chou and Hsu, 2016, pp. 32-33). The higher the experience level, the lower the uncertainty. Previous research states that 45% of consumption behaviors are repeated almost daily and eventually become habitual behavior (Verplanken and Wood, 2006, p. 92). Therefore, this study proposes the following hypotheses:

H7: Buying habits positively moderate the relationship between trust and repurchase intention.

H8: Buying habits positively moderate the relationship between intimacy and repurchase intention.

3.9.Repurchase Intention and Actual Repurchase Behavior

Repurchasing is defined as actual consumer behavior that results in multiple purchases of the same product or service. Most consumer purchases are repeated potential purchases (Peyrot and Van Doren, 1994, p. 37). Customers repeatedly buy similar products from similar sellers, and most purchases represent a series of events rather than a single isolated event. The link between purchase intention and actual repurchase behaviors is based on the theory of rational action and the theory of planned behavior (Ajzen and Fishbein, 1980, p. 95; Ajzen, 1991, p. 181). Both theories state that actual behavior is a function of behavioral intention. Consumers who express a positive purchase intention are more likely to buy again than those who express a negative purchase intention. From the above discussion, we suggest the following hypothesis:

H9: Repurchase intention positively impacts actual repurchase behavior.

Figure 1.Conceptual framework

4. Research Methodology

In our study, we used the non-probability technique as a sampling method. It was used to reduce the sampling constraint and error during data collection, which will lead to better accuracy and consistency of the generated result. There are four ways to proceed in a non-probability sample to draw the population of interest: convenience, judgment, quota and snowball.

4.1. Research Context

The study was conducted in Morocco, targeting social media users, who use social commerce to purchase goods and services, in order to understand the impact of cognitive and emotional mechanisms on their repurchase intention. The social media used in this study are Instagram, Facebook and LinkedIn.

4.2. Data Collection and Sample

The sampling method that seems to be most suitable for our study would be snowball sampling. This approach involves using individuals as sources for identifying additional sampling units. To carry out this snowball sampling, we solicited several Moroccan influencers, whom we contacted through different means: telephone, direct contact, and the use of social networks to inform them about the study.

After obtaining their approval to participate in the survey, we sent them the link to the questionnaire, as well as to all our contacts on social networks and in our various WhatsApp, Facebook, Instagram and LinkedIn groups. Once this first group was identified and contacted, they continued the recruitment process by in turn forwarding the web address of the online questionnaire to their communities and ensuring that they filled it out and shared the link to the questionnaire. This recruitment chain allowed us greater penetration of the target population's networks and ensured the representativeness of the sample Data collection is carried out via questionnaire containing items that can be aggregated and scored by statistical methods, namely a 5-point Likert interval scale. At the end of the survey, we were able to collect 3854 fully usable responses for processing, 2,251 of whom have already made purchase on social commerce platforms.

We have a database comprising 55% women and 44% men. Out of the employed individuals, 69.8% are between the ages of 18 and 30, earning less than 500 $, making up 42.2%. The results of our flat sorting analysis indicate that 52.7% of our sample are satisfied with the quality of the product or service provided, while 56.3% display confidence in the content published on social media platforms. Additionally, 31.3% moderately share content on social media. Furthermore, our findings demonstrate that 52.9 million individuals prefer to purchase goods offline, with a purchase frequency of 1 to 2 times per month. It is noteworthy that only 3.7% of our sample do not express an intention to repurchase, and 96.3% of individuals who express an intention to repurchase do so.

5. Analysis and Results

Repurchase intention was measured using the partial least squares-based structural equation modeling (PLS-SEM), a 27-item questionnaire that assesses the impact of cognitive and emotional factors on repurchase intention. Participants were asked to rate the extent to which they experienced each variable on a 5-point Likert scale ranging from 0 (Not satisfied) to 5 (completely satisfied). The PLS-SEM has been widely used and validated in various studies.

5.1. Confirmatory Factor Analysis

In order to ensure convergent validity, we try to show that the construct measures, which theoretically should be related to each other, are related in this way after the analysis. Three types of estimates, namely factor loadings, composite reliability (CR) and average variance extracted (AVE), have been suggested to establish convergent validity. Firstly, all item loadings are examined and a loading value of 0.50 or above is considered acceptable in the multivariate analysis literature (Fornell & Larcker, 1981; Hair et al., 2010, 2014).

It can be seen in Table 1 that all items have a saturation above 0.60. The suggested ideal value for FC is 0.70 (Fornell & Larcker, 1981; Hair et al., 2010) and it can be seen that the FC values for all constructs were in the range of 0.787 to 0.1, which is well above the prescribed values. Thirdly, the average variance extracted (AVE), which is the extent of the common variance between the indicators of the latent constructs in the study, was examined. Its value should ideally be above 0.50 (Fornell & Larcker, 1981; J F Hair et al., 2010). This condition was also fully met, with AVE values ranging from 0.595 to 0.1. Thus, the results indicate that there is convergent validity. Although the Cronbach's alpha values and composite reliability values for this research study are obtained using Smart PLS, the value considered appropriate for the Cronbach's alpha coefficients is 0.60. As can be seen in Table 1 and Figure 2, this condition was also fully met, with Cronbach's Alpha values ranging from 0.472 to 0.1.

Table 1. Results of confirmatory factors analysis

Constructs Items Std.Dev Cronbach‘s alpha rho_A Composite Reliability Average Variance Extracted (AVE)
Satisfaction SAT1 0.688 0.876 0.896 0.907 0.622
SAT2 0.697
SAT3 0.895
SAT4 0.88
SAT5 0.733
SAT6 0.812
UGC CGU1 0.995 0.88 3.224 0.92 0.852
CGU2 0.846
TRUST TST3 0.787 0.894 0.907 0.927 0.761
TST4 0.939
TST5 0.871
TST6 0.885
Intimacy INT1 0.762 0.815 0.885 0.886 0.722
INT2 0.882
INT3 0.898
Shopping habit SH2 0.7 0.565 0.741 0.806 0.679
SH3 0.932
Social interaction SIN1 0.87 0.472 0.501 0.787 0.651
SIN2 0.737
Risk RSK1 0.934 0.914 1.108 0.933 0.825
RSK2 0.972
RSK3 0.81
Repurchase intention RPI2 0.661 0.885 0.891 0.911 0.595
RPI3 0.792
RPI4 0.681
RPI5 0.865
RPI6 0.803
RPI7 0.845
RPI8 0.729
Repurchase behavior RBE1 1 1 1 1 1

The CFA also implied discriminant validity testing based on Fornell-Larcker criterion. The results given in table 2, indicate that the measures of all constructs, satisfaction, UGC, trust, intimacy, buying habits, social interaction, risk, repurchase intention and repurchase behavior, show that the actual measurement of their variables reflects the discriminant validity of the constructs.

Table 2. Fornell-Larcker criterion

  1 2 3 4 5 6 7 8 9
1 Satisfaction 0.789                
2 UGC -0.08 0.923              
3 Trust 0.617 -0.167 0.872            
4 Intimacy 0.531 -0.008 0.208 0.85          
5 Shop_habits 0.269 0.175 0.087 0.436 0.824        
6 SoInter 0.429 0.566 0.222 0.472 0.396 0.807      
7 Risk -0.103 -0.104 -0.153 0.003 -0.255 -0.192 0.908    
8 RPI 0.697 -0.045 0.608 0.535 0.587 0.435 -0.15 0.772  
9 Repurchase Behavior 0.029 0.23 -0.116 0.113 0.554 0.158 -0.209 0.393 1

Figure 2. Measurement model and results

Source: Extracted from Smart PLS

5.2. Model Results

 The table 3 below, report the results of proposed hypotheses, respectively, all hypotheses are supported regarding the dataset, however the path coefficient of H4 is low compared to other constructs, and it was found non supported and significant. However, for the 09 hypothetical relationships, 08 are confirmed and 1 is not confirmed, i.e., 91.66% of the total data evaluated.

Table 3. Model fit

Path Coeff P Results Hypothesis
H1: Satisfaction à Trust 0.608 0 0.608 Accepted H1
H2: Satisfaction à Intimacy 0.533 0 0.394 Accepted H2
H3: UGCà Trust -0.118 0 0.023 Accepted H3
H4: UGCà Intimacy 0.036 0.188 0.002 Rejected H4
H5: Trust à Repurchase intention 0.592 0 1.908 Accepted H5
H6: Trust * Shop_habits -> Rep intention 0.097 0 0.04 Accepted H6
H7: Intimacy à Repurchase intention 0.066 0 0.016 Accepted H7
H8: Intimacy * Shop_habits à Repurchase intention -0.267 0 0.788 Accepted H8
H9: Repurchase intention à Repurchase behaviour 0.395 0 0.185 Accepted H9

The R² values of the endogenous constructs reflect the strength of the model as shown in table 4 below. However, it may also be useful to estimate the substantiality of the impact of an exogenous construct on the endogenous construct, which is assessed by running the model once omitting the exogenous construct (generating an excluded R²) and once retaining the exogenous construct (generating an included R2).

Table 4. Assessment of the structural model

    Coeff Std Err T-Static P L95% BC CI U95% BC CI
R2 Trust 0.395 0.018 22.175 <0.001 0.36 0.43
Intimacy 0.283 0.016 18.003 <0.001 0.251 0.313
Repurchase intention 0.836 0.01 85.25 <0.001 0.816 0.854
Repurchase behavior 0.156 0.036 4.284 <0.001 0.085 0.228
Q2 Trust 0.294  
Intimacy 0.185 0.016
Repurchase intention 0.485 0.01
Repurchase behavior 0.151 0.036

6. Discussion and Conclusion

6.1. Discussion

The results confirm the importance of trust and intimacy in repurchase in the Moroccan context. Similarly, satisfaction affects trust and intimacy, and user-generated content affects that trust, leading to repurchase via moderation of buying habits.

This evidence supports the findings of Elbeltagi and Agag (2016, p.288) and Limbu et al. (2012, pp.134-154) that trust fully mediates between social interaction and consumer repurchase intention. This research focused on online consumers who have recently used social commerce to purchase a product or service, in order to understand the factors that may affect them and lead them to repurchase a product from the online retail platform they transacted with.

The results show that the constructs of the model are positively correlated. Finally, shopping habit is considered a moderating factor in our research framework, as confirmed by previous research (Choi & Mai, 2018, p.291). The results show that the higher the level of online shopping habits, the lower the effect of perceived risk on repurchase intention. This study supports the arguments presented in Chiu, Wang, Fang and Huang (2014, pp.85-114). This result suggests that marketers should deploy loyalty programs to stimulate Internet users' buying habits in order to push them to actually repurchase.

The contribution of this work is twofold. First, we integrate trust and intimacy into the research model and find that purchase habit plays a moderating role between cognitive construct, emotional construct and repurchase intention. Second, based on these mechanisms, we explore the influence of satisfaction and UGC on trust and intimacy, which helps to explain the current debate in these areas as to whether a high satisfaction index will affect trust construction and whether Moroccans are more motivated by trust or intimacy when it comes to repurchase.

6.2. Conclusion

Today, the popularity of social media offers retailers and service providers the opportunity to grow their business through social commerce. While retailers such as Cocacola, Samsung ... etc have increased their profits through it, however, some retailers (such as Walmart) have failed to capitalize on this type of business (Hajli et al., 2017, pp.131-141).

As a new economic method, social commerce has created a wave of socio-economics. Socio-economics is a value model rooted in social relations. It is driven by human-centered social relationships, leveraging the spontaneous power of community and user self-creation, and focusing on collective intelligence and synergies. Social networks and social commerce are beginning to see their potential value.

In fact, the impact of social technology is spreading to all corners of the world and helping to solve the challenges faced by some economies around the world through social networks. Listen to consumers and end users on social networks and provide positive feedback in real time. As a result of this survey, we were able to build a database of 3854 observations, of which 2251 are part of our target population are those who have made an online purchase in the last three, six months. In this research we opted for econometric modelling, using partial least squares regression (PLS-SEM) to determine the factors impacting on intention and actual purchase behavior in the context of social commerce.

The results confirmed the importance of trust and intimacy on repurchase for the Moroccan consumer. Secondly, satisfaction influences trust and intimacy, while user-generated content only influences trust and not intimacy to redeem. This evidence reconfirmed the findings of Elbeltagi and Agag (2016, p.300) and Limbu et al. (2012, pp.134-154) that trust is a complete mediation between social interaction and consumers repurchase intention. This research focused on online consumers who have recently used social commerce to purchase a product or service, in order to understand the factors that may affect them and lead them to repurchase a product from a specific retailer with whom they have transacted.

We proposed nine research hypotheses, which were intended to address our core problem. The results showed that the constructs of our conceptual model are positively correlated. Finally, the buying habit is considered as a moderating factor in our research framework. The results showed that the higher the level of online shopping habit, the lower the influence of perceived risk on repurchase intention. This research supports the arguments indicated in Chiu, Wang, Fang and Huang (2014, pp.85-114). This result suggests that marketers deploy loyalty programs to stimulate users' online purchase habit.

Our research was developed in the context of developing countries, specifically my country Morocco, due to the monitored data collection and access to respondents in order to save a lot of costs, the aim of this research is to find out the behavioral intention of consumers in developing countries, but it was only executed in one country, so other researchers could focus on more developing countries to have a deeper understanding of repurchase intention, trust building and its antecedents. Or adopt the context of countries (developing and developed) in a single study.

Some concepts in the model, such as satisfaction and user-generated content, were chosen as unidimensional concepts. Future research could consider them as multidimensional concepts, in order to better explain their roles, as they are crucial factors in social commerce (Chou et al, 2018, pp. 117-134). Finally, the research left the question open for respondents regarding a specific social commerce platform, this gives the opportunity for future research to focus on a specific social commerce platform, this could better frame the understanding of consumer choices, to better design their behavior.


Acknowledgements: This work was supported by the personal efforts of the author.

Funding: This research received no external funding

Conflicts of Interest: The authors state that they have no conflicts of interest.

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Hajar Anabir, University of Hassan II – Casablanca, Morocco
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Hassan II University, Morocco