Keywords

1 Introduction

The new marketing practices and changes have an had incredible impact on consumers’ purchasing process and information-acquisition process. The linear purchasing process does no longer apply and marketers have to develop new ways in which to interact, learn and persuade consumer to buy certain products and services. The path to purchase of consumers all around the world is experiencing changes, with multiple challenges and opportunities for marketers. In terms of technologies’ impact on marketing, social media represents a development that is changing traditional marketing frameworks.

For marketing purposes, social media represents an important channel that can facilitate many marketing activities including ‘customer relationship management, customer service, buyer research, lead generation, sales promotion delivery channel, paid advertising channel, and branding’ (Ashley and Tutten 2015). Murdough (2009) states that social media provides the right tools for communicating, participating, attracting, engaging consumers and sharing targeted branded messages to audience segments.

One of the most prevalent social media platforms is Facebook. In 2017, at the end of the fourth quarter of 2017, Facebook reported 2.13 billion monthly active Facebook users (MUAs) and 1.4 billion daily active users (DAUs), on average (Facebook 2018). Monthly active users represent people who have logged in at least once in the last 30 days, and daily active users are those people who have logged in at least once during a day. According to Nielsen (2017), 29% of consumers who use social media platforms frequently expressed the importance they place on supporting their preferred brands, mentioning how important it is for them to find and share brand related information on Facebook. Also, 61% of Facebook users who interact with a brand or company about something they saw on TV are female (Nielsen 2017).

Online media opened the opportunity to learn from this consumer behavior because marketers can address consumers directly. Marketers also have the tools to monitor and screen consumers’ discussions about the brands, their brand attitudes and perceptions, electronic-word-of-mouth and interactions between consumers regarding certain brands (C2C/eWOM), consumer participation and involvement, loyalty and satisfaction. Eventually, all these concepts are related to relationship marketing. A recent research by Jung et al. (2012) found that online social networks could provide new relationship marketing opportunities and that can add new types of value for an online or offline business that aims to succeed in understanding its customers.

Overall, this paper’s contribution is threefold. First, we contribute to marketing knowledge by proposing and testing a conceptual framework of how online consumer activity on Facebook can influence consumer loyalty. Second, our empirical contribution is based on the quantification of different variables on consumer loyalty. Third, we present theoretical and managerial contributions of the empirical findings, as well as inputs regarding limitations of the research and future directions for further examination and exploration of the current research subject.

2 Conceptual Framework

2.1 Customer Loyalty

Typically, literature classifies customer loyalty as behavioral and attitudinal dimension of consumer behavior. On one hand, behavioral loyalty is measured through a brand’s purchasing frequency by its loyal customers (Yi and Jeon 2003). On the other hand, attitudinal loyalty is defined by Oliver (1997) as a commitment to rebuy a particular brand, while disregarding other competitive offers. High competition levels in international markets have strengthened the significance of loyalty which can be harnessed to accomplish sustainable competitive advantage (Aksoy 2013). Marketing managers have to develop and execute innovative strategies to achieve consumer trust and loyalty (Dominici and Guzzo 2010). Consumer loyalty is also related to positive word of mouth (WOM) (Reichheld and Sasser 1990; Kandampully et al. 2015).

Nonetheless, customer loyalty to a particular company is the result of the satisfaction they experience from the consumption of their offer. Thus, customer loyalty is considered by some authors to be superior to customer satisfaction to the company in question, a condition that can be achieved by overcoming the initial expectations of customers by a company’s performance. Oliver and Swan (1989) and Oliver (1999) define loyalty as a deep commitment held by a customer to continue to rebuy a certain brand in the future, ignoring the situational factors or marketing efforts of competitors that try to influence his/her purchasing decisions.

In the online context, Srinivasan et al. (2002, p. 43) have defined loyalty (e-loyalty), with an emphasis on behavioral dimension, as “the customer’s favorable attitude towards a web retailer resulting in repeated purchasing behavior.” Thus, loyalty can be measured by focusing on future buying behavior and profit for the company a consumer usually buys from. Loyal customers that are in a long-term relationship with a company tend to extend their relationship, providing cumulative rewards to the firm (Srinivasan et al. 2002; Kandampully et al. 2015).

2.2 Customer Satisfaction

Oliver (1980) proposed that customer satisfaction refers to the psychological state that summarizes the results when the emotion surrounding the expectations is associated with consumer sentiments, regarding the previous consumer experience. Bloemer and Ruyter (1998) consider that the satisfaction for a brand represents a person’s experiences following the consumption of a particular brand, more specifically it represents a subjective assessment of the client, of the extent to which the performance of the brand has initially responded to its expectations.

Delivering superior customer value and satisfaction is crucial to a firm’s competitiveness (Kotler and Armstrong 2018). It is essential to know what customers value most, and this information further helps firms in allocating resources for a continuous improvement based on their needs and wants. To deliver superior service quality, an online business must first understand how customers perceive and evaluate its service quality (Lee et al. 2016).

Lee et al. (2016) and Pappas et al. (2014) establish that a satisfied customer is more likely to provide repeat business for a company. Thus, consumer satisfaction is not only a crucial element that impacts customers’ online purchasing behavior, but it is also a key factor for generating customer loyalty. Hsu et al. (2007) note that consumer satisfaction has a positive influence on customers’ intention to repeat their online purchases, which further leads to behavioral loyalty. Meanwhile, in e-commerce, Anderson and Srinivasan (2003) define satisfaction as “the contentment of the customer with respect to his or her prior purchasing experience with a given electronic commerce firm”.

In researching consumer satisfaction, marketing academics have focused their research efforts on the measurement of service quality to better comprehend satisfaction. Nonetheless, both academics and marketing practitioners agree that customer satisfaction is an important concept for retention and enhancement of the value of companies. Especially in an online setting, there is a direct relationship between customer satisfaction and e-stores’ performance (Anderson and Srinivasan 2003).

2.3 Consumer Participation

Customer or consumer participation is an aspect mentioned in various studies from multiple marketing perspectives. For instance, Prahalad and Ramaswamy (2004) emphasized the idea of an “active co-producer” involved in the process of delivering and consuming a service. Using a similar idea, Vargo and Lusch (2004, 2008) have established that a client always participates as a co-producer.

Since 1990, Dabholkar (1990) has defined consumer participation as “the extent to which a customer is involved in producing and delivering services.” As observed from this definition, customer participation, as well as related concepts of co-production and co-creation have viewed the customer’s connection with organizations only in exchange situations. In line with these premises, Vivek (2009) states that the notion of participation involves the customer’s connection with organizations only in exchange situations, as the client’s engagement is a wider term that goes beyond basic exchanges.

Customer participation in existing research is only studied in the context of an exchange. Customer participation can occur at different times: during the purchasing decision process, after a purchase decision has been made, during the exchange process, or after the exchange or transaction. According to Eisingerich and Bell (2006), customer participation has a significant impact on loyalty. As clients participate and have a higher level of involvement with a company, they tend to share the credit, and the fault, for service results, and in addition they will tend to develop new brand-related connections in online settings. It is vital for companies to keep their clients involved in all stages of a product’s life cycle and develop or adjust products that best reflect the needs and wants of their targeted consumers.

As indicated by the service-dominant logic, clients are seen ‘proactive value co-creators’ as opposed to uninvolved and passive receivers of value (Payne et al. 2008; Chen and Wang 2016). Therefore, companies have to facilitate the value co-creation process. On one hand, customer participation reflects the efforts of co-creation on consumer’s side (Chan et al. 2010), and on the other hand, companies can engage in closer, longer and more profitable relationships with their customers (Bendapudi and Leone 2003; Payne et al. 2008; Chen and Wang 2016).

2.4 Consumer Involvement

Consumer involvement has been broadly defined as a targeted objective of motivation that indicates the extent to which the decision is viewed as personally relevant to client (Mittal and Lee 1989). Involvement is interpreted as a consumer’s motivation to look for information that can be used to manage and mitigate any potential and inherent risk in the decision-making process, in order to facilitate a decision regarding a particular alternative choice (Delgado-Ballester and Munuera-Aleman 2001).

Within this emerging body of work, consumer brand ‘involvement,’ which reflects a consumer’s level of interest in, and personal relevance of a brand, has gained significant attention (Zaichkowsky 1985, 1994; Coulter et al. 2003). Various authors (Zaichkowsky 1994; Mittal 1995) defined consumer involvement as an individual’s level of interest and personal relevance in relation to a focal object/decision in terms of one’s basic values, goals and self-concept.

Gordon et al. (1998) note that a state of involvement with a brand generates a sense of psychological attachment with regard to customers’ subsequent thoughts, feelings, and behaviors. Moreover, if the client is involved, he/she is more likely to respond positively to marketing efforts that try to customize his/her acquisition experience or his/her brand interaction, especially in creating a basis for consumer loyalty. Likewise, Oliver (1997) argued that customers with a high degree of involvement with their preferred brands tend to be more loyal in the long term.

Vivek (2009) proposed that involvement may arise as a situational concept or a long-term concept in consumer’s perceptions, attitudes and behavior. The situational involvement of consumers represents a temporary elation or shift in consumer’s interest that fluctuates during the time allocated to the final acquisition decision, while the long-term involvement is a stable phenomenon that represents consumer’s personal interest over a longer period of time (Vivek 2009). Consumer involvement with a particular marketing object provides the ability and motivation to initiate brand-related conversations with others, exhibit brand advocacy behavior and develop loyalty. In online settings, involvement takes the form of reviews posted on the Internet, associated with different products of services (Hollebeek et al. 2014), that consumers tend to buy on a regular basis.

2.5 Consumer-to-Consumer Interactions About Brands and eWOM

Word-of-mouth (WOM) represents the informal communications directed at other consumers about the ownership, usage, or characteristics of particular goods and services and/or their sellers (Matos and Rossi 2008; Verma et al. 2016). WOM has been recognized as the most essential path for managers to distinguish consumer loyalty and commitment among clients (Matos and Rossi 2008). Electronic WOM (eWOM), both negative and positive, is known to strongly affect shoppers when contrasted with other data sources (Bickart and Schindler 2001).

Additionally, WOM cannot be specifically controlled by the marketers as consumers can freely share experiences on different social platforms. Furthermore, eWOM has been specifically connected to online purchases. Verma et al. (2016) discovered that eWOM was for the most part related to relationship marketing efforts, followed by customer loyalty and ‘expectation of continuity’. Customer-provided WOM, online or offline, positive or negative, is closely reviewed by current and potential customers (Brown et al. 2007; Khare et al. 2011; Kandampully et al. 2015). Thus, WOM is a very powerful tool that needs to be harnessed in the scope of consumer loyalty. In addition, loyal clients frequently advocate a company or a brand on social media networks (electronic WOM), linking networks of friends and prospects to a particular company (See-To and Ho 2014), thus generating brand-related consumer-to-consumer interactions.

2.6 Research Hypotheses

Bases on the conceptual framework described in the previous sections, we propose the following research hypotheses that will be examined in this study:

  • H1. Customer satisfaction has a positive and direct impact on customer loyalty for brands that activate on social media.

  • H2. Consumer participation has a positive and direct impact on customer loyalty for brands that activate on social media.

  • H3. Consumer involvement has a positive and direct impact on customer loyalty for brands that activate on social media.

  • H4. Consumer-to-consumer interactions about brands and eWOM activities have a positive and direct impact on customer loyalty for brands that activate on social media.

3 Research Methodology

3.1 Research Design

The research setting for this paper refers to consumer behavior on social media services, particularly Facebook and  consumer interactions with brands on this social platform. Through this research we will examine which consumer behavior concept has a higher impact in generating loyalty for the brands consumers interact with on Facebook.

The investigated and proposed model is based on a quantitative marketing research from primary sources. This research aimed to discover new ways in which to develop and enhance online customer loyalty as a result of people using Facebook as a platform of interaction with brands.

3.2 Data Collection and Research Instrument

This primary research used an online survey for data collection. The present research uses as a method the pilot survey, using a convenience sample technique. The constructs examined in this study are presented in Table 1.

Table 1 Constructs explored in the empirical study
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The online survey was applied on a global scale, generating 391 usable responses from international respondents who live in USA (14.6%), Italy (6.4%), France (5.4%), Canada (4.9%), and Germany (4.9%). The respondents were male in a proportion of 69.6%, with 97.4% of respondents with Bachelor, Master or Ph.D. Studies. Table 2 provides additional information on the profile of the respondents.

Table 2 Respondents’ profile
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Moreover, extending the profile of the respondents, we’ve examined the familiarity of the respondents with Facebook. Table 3 shows descriptive statistics and their related questions.

Table 3 Familiarity of respondents with Facebook
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4 Results of the Empirical Analysis

4.1 Exploratory Factor Analysis

In this research, the Exploratory Factor Analysis is used to create a summary of the scales used to examine the model for consumer loyalty based on different behavioral constructs that highlight social media interaction with brands. EFA was conducted in SPSS, using the Principal Components method, in order to extract the factors. The results for the exploratory factor analysis are shown in Table 4.

Table 4 Exploratory Factor Analysis results
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The factor analysis helped reduce the number of scale items associated with each dimension. Additionally, we used the Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO) in order to examine the relevancy of this econometric technique. For each dimension one factor was extracted that summarized each dimension in a relevant manner, as showcased by the adequate KMO scores for each newly created factor, as each KMO score is higher than the 0.5 threshold. High values (between 0.5 and 1.0) indicate that the factor is adequate (Table 4).

Further, these factors will be included in an Automatic Linear Modeling that explores which dimension has a higher impact on consumer loyalty.

4.2 Results of the Automatic Linear Modeling

At this stage of the empirical analysis, a SPSS specific procedure was employed, namely Automatic Linear Modeling (ALM).

This econometric technique is used to forecast and model a continuous target variable (in this case, consumer loyalty) based on linear relationships between the target variable and its established predictors (Involvement, Satisfaction, Customer-to-Customer Interactions or electronic Word-of-Mouth, and Consumer Participation).

The model used the Forward Stepwise method which adds effects and removes them at each step of the procedure, based on the Information Criterion (AICC). Also, the preparation of the data was automatic. The accuracy value is reflected by an adjusted R-square of 0.620 or 62%.

Figure 1 shows the importance of the predictors examined in the model, regarding the target variable of consumer loyalty. Also, according to IBM Corp. (2017), ‘the importance of a predictor represents the residual sum of squares with the predictor removed from the model’. For generating consumer loyalty using a particular social media platform, the model shows that the most important variable is ‘Involvement’.

Fig. 1
figure 1

Predictor importance in relation to target variable (consumer loyalty)

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The ANOVA table presents explanations about the model, by exploring how the predictors (or independent variables) associate with each other and what impacts these collaborations have on the target variable. Table 5 displays the factors that are statistically significant as indicated by the F test.

Table 5 Analysis of variance statistics for the model
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For this model with four independent variables (Involvement, Satisfaction, Customer-to-Customer Interactions or electronic Word-of-Mouth, and Consumer Participation) included in the Automatic Linear Modeling procedure, we notice the significant interaction between these predictors and loyalty that is generated by consumers’ use of social media in relation to brands (Table 5). More specifically, involvement generated a F-score of 82.201 (Sig. < 0.000), satisfaction registered a F-score of 20.090 (Sig. < 0.000), and interactions between customers in online settings (C2C-eWOM) reported a F-score of 18.860 (Sig. < 0.000), while the lowest F-score was observed for consumer participation, with a value of 9.443 (Sig. < 0.000). All the relationships in this model were deemed significant.

Table 6 shows the assessments for parameters incorporated into the general model and their individual effects on the target variable on consumer loyalty for brands on Facebook. The coefficient of each independent variable shows the relationship of each predictor to the model’s target variable. As it can be observed, all the predictors have positive estimates, except the intercept of the automatic linear model.

Table 6 Coefficients results
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First, as it can be observed in Table 6, consumer involvement has been established as the concept that has the greatest importance (0.629) in driving customer loyalty, in this particular proposed model. Involvement also highlighted the highest score for the t test, namely 9.066, at a significance level of 0.000. This finding supports previously reported results (Hollebeek et al. 2014; Zaichkowsky 1985, 1994; Mittal 1995). As previously reported and highlighted in this paper, the consumer behavior variable with the most significant impact on consumers’ loyalty for a particular brand on Facebook is consumer involvement. Therefore, this variable should play a key role in online marketing strategies and tactics, as they relate to developing better relationships with consumers.

Second, the results of this study demonstrate that the customer loyalty of satisfied customers was affected by customer satisfaction (t test value of 4.482. and an importance value of 0.154). Also, numerous studies have presented the positive and direct relationship between customer satisfaction and customer loyalty (Chen and Wang 2016; Payne et al. 2008). Thus, this empirical study contributes to important digital marketing knowledge by highlighting the idea that customer satisfaction positively affects customer loyalty.

Lastly, online customer interactions (t test value of 4.343, significant at a p < 0.000) regarding brands and their participation (t test value of 3.073, significant at a p < 0.000) in brand-related activities also developed positive and noteworthy relationships with the target variable from this empirical research, namely customer loyalty. Both of these relationships are aligned with previous research, particularly in relation to the positive relationship between customer participation and customer loyalty (Bendapudi and Leone 2003; Vargo and Lusch 2016) and between electronic-Word-of-Mouth and customer loyalty (Jahn and Kunz 2012; Kara 2015; Kandampully et al. 2015).

5 Discussion

5.1 Theoretical Contributions

This study contributes to online marketing literature in several ways. First, this study contributes to online marketing literature as this paper shows that the customer satisfaction and customer involvement are valuable triggers for customer loyalty in online settings, particularly in social media marketing used for developing relationships with targeted customers. In this paper we also highlight the critical role of eWOM and consumer participation in driving loyalty. The key findings of this study are discussed in more detail, below.

This research provides empirical evidence in support of the importance of consumer involvement and satisfaction in consumer loyalty for brands that are active and use social media as a medium for communication with targeted audiences (Dholakia and Zhao 2010). These two concepts will be a prerequisite for a company’s efforts in improving its value and overall performance.

Although the positive effect of customer satisfaction on loyalty, as our results reveal, has been widely accepted in the literature, this paper adds additional contributions by highlighting the importance of consumer involvement on social media. Furthermore, this empirical study adds novel insights by demonstrating that social media usage plays a key role in developing loyalty by amplifying consumer satisfaction and involvement.

For generating consumer loyalty using social media platforms, the model shows that the most important variable is ‘Involvement’. Holbrook and Hirschman (1982) clarified that involvement includes cognitive engagement and orientation reaction in their clarification of consumer buying behavior (Brodie et al. 2013). On one hand, cognitive engagement is related to situations in which consumers get to solve problems using logic. On the other hand, orientation reaction reflects emotional and enthusiastic activities for consumers.

Moreover, through customer participation, customers get the opportunity to develop economic and relational benefits, as well as engage in joyful experiences, thus allowing organizations to create customer satisfaction and loyalty, which are seen as key competitive advantages (Chen and Wang 2016; Payne et al. 2008; Vargo and Lusch 2016; Hollebeek et al. 2016).

5.2 Managerial Implications

We trust that our empirical investigation has essential ramifications for marketers. Social media networks will continue to facilitate consumer interactions with and about different preferred brands, and it is expected that consumers will continue to pursue, develop and participate in discussions about their brand experience on social networks. Therefore, marketing managers have to monitor and adjust their social media strategies based on dissemination of information and patterns of consumers’ behavior regarding brand-related discussions on social networks.

These monitored activities will be aimed at creating consumer involvement and satisfaction, which will further lead to consumer loyalty. Marketing managers have to develop interesting online activities that engage and involve consumers, such as games, quizzes, questions about product performance, product improvement or general brand experience, so that consumers can develop a deep sense of involvement with a particular brand on social media, and further improve loyalty, customer relationships and firm performance. Therefore, marketing managers should develop customer relationship building activities on social media, which will emphasize consumer loyalty (Srinivasan et al. 2002; Brodie et al. 2013; Wirtz et al. 2013; Hollebeek et al. 2016), involvement (Vivek 2009; Mittal 1995), satisfaction (Oliver 1999; Lee et al. 2009; Pappas et al. 2014), and consumer participation/co-creation (Prahalad and Ramaswamy 2004; Payne et al. 2008; Vargo and Lusch 2016).

For social media strategies that generate consumer involvement and loyalty, Jahn and Kunz (2012) developed a study on Facebook using Katz’s (1959) gratification theory. In their study, Jahn and Kunz (2012) examined consumer participation in brand pages and discovered that utilitarian and hedonic content were both generating participation and could provide a prerequisite for consumer loyalty. According to Ashley and Tuten (2015), gratification theory suggests social media participants are likely to desire both entertainment, and information, however, entertainment may provide a stronger factor engagement with well-known brands, rather than information because consumers are already familiar with their features and benefits.

Considering the expansion of consumer involvement, participation and engagement in WOM practices via social media networks by actively posting their evaluations, reviews and opinions about brands or products, marketers should try to contact particular consumers and include them in the process of developing a brand on social media. As Kara (2015) suggests, companies could also offer these consumers’ incentives for their social media postings regarding their brand experiences. Moreover, this type of consumer involvement in developing the brand on social media and generating WOM or C2C interactions (Khare et al. 2011) should not go without an official reply from the brand.

5.3 Future Directions for Research and Limitations

To gain a more thorough understanding of the research questions and objectives of this empirical study, additional studies could help further examine the influences of customer loyalty in social media marketing and their impact on consumer behavior. Further academic papers should include a more comprehensive list of concepts that explain consumer behavior on social media and test their impact on consumer loyalty. Thus, we encourage research that explores the antecedents of customer loyalty and identify potential factors of the relationship between customer loyalty and their antecedents. Finally, future research should examine the effectiveness of online social media practices with actual brand acquisitions and consumer loyalty.

Another direction for research would be to segment the consumers in high- experienced and low-experienced consumers. As Dholakia and Zhao (2010) noted, high-experienced customers tend to be more difficult to experience satisfaction and therefore, their loyalty may also be more difficult to establish in an online setting.

Furthermore, the convenience sample of this study limits the generalization of the findings, thus future studies should focus on more objective measures.