A systematic mapping study on customer loyalty and brand management

Tartaglione, Andrea Moretta; Cavacece, Ylenia; Russo, Giuseppe; Granata, Giuseppe Article A systematic mapping study on customer loyalty and brand management Administrative Sciences Provided in Cooperation with: MDPI – Multidisciplinary Digital Publishing Institute, Basel Suggested Citation: Tartaglione, Andrea Moretta; Cavacece, Ylenia; Russo, Giuseppe; Granata, Giuseppe (2019) : A systematic mapping study on customer loyalty and brand management, Administrative Sciences, ISSN 2076-3387, MDPI, Basel, Vol. 9, Iss. 1, pp. 1-21, https://doi.org/10.3390/admsci9010008 This Version is available at: https://hdl.handle.net/10419/239905 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ administrative sciences Review A Systematic Mapping Study on Customer Loyalty and Brand Management Andrea Moretta Tartaglione, Ylenia Cavacece *, Giuseppe Russo and Giuseppe Granata Department of Economics and Law, University of Cassino and Southern Lazio, 03043 Cassino, Italy; [email protected] (A.M.T.); [email protected] (G.R.); [email protected] (G.G.) *Correspondence: [email protected] Received: 10 November 2018; Accepted: 4 January 2019; Published: 11 January 2019   Abstract: Customer loyalty is a topic of great interest for marketing scholars due to its importance in gaining sustainable competitive advantages and financial outcomes. Literature is prolific of works regarding customer loyalty and brand management. In order to improve the quantity and quality of research publications, research themes mapping of published studies is required. The aim of this paper is to provide scholars with a systematization and mapping of the contributions on this topic to develop an effective research road map for future research. A bibliometric analysis and a mapping study have been conducted on 337 publications on customer loyalty and brand management from 2000 to 2018. The results present the most cited works on the topic, an evaluation map showing the most frequent and cited words and six clusters of words based on their co-occurrence. From the analysis of the clusters, the most relevant research findings, trends, and issues emerge, suggesting interesting theoretical and practical implications. Keywords: customer loyalty; brand; satisfaction; commitment; trust; engagement; bibliometric analysis; mapping study 1. Introduction Customer loyalty is one of the most debated topics in marketing literature of last decades. The great interest in customer loyalty can be attributed to its importance in achieving sustainable competitive advantages and financial outcomes (Grönroos 2009). Customer loyalty refers to positive attitudes of customers toward a company or brand that result in repeated repurchasing behaviors and in a lower customer sensitivity to the price and the offerings of competitors (Anderson and Srinivasan 2003). Loyal customers are more profitable than a new one, since they spend more with the firm and have lower servicing costs (Richard and Zhang 2012). Hence, managing and enhancing customer loyalty becomes a strategic imperative for firms. Brand acquires great importance in improving customer loyalty through the effective management of the brand awareness and brand image (Han et al. 2008). The emotional attachment towards a brand creates affective commitment that encourages consumers to constantly rely on a specific brand’s offering (Gustafsson et al. 2005;Lee et al. 2007), repurchase the same brand, spread good words, and not visit competitor’s stores (Han et al. 2018). These behaviors ultimately result in customer loyalty (Evanschitzky et al. 2006;Fullerton 2005;Iglesias et al. 2011;Mattila 2001). The interest in customer loyalty has resulted in a large number of contributions on this topic. Literature shows interesting advancements in its understanding and conceptualization. However, to date, further efforts are required of scholars (Nguyen et al. 2018;Shahid Iqbal et al. 2018;Sitorus and Yustisia 2018). The reason is that customer loyalty is a complex and multifaceted concept involving dynamic interactions and exchanges (Dick and Basu 1994). It is a multidimensional construct and some difficulties emerge in identifying its dimensions and operationalize them. First of all, customer Adm. Sci. 2019,9, 8; doi:10.3390/admsci9010008 www.mdpi.com/journal/admsci Adm. Sci. 2019,9, 8 2 of 21 loyalty can be defined as a combination of attitudinal and behavioral dimensions that create difficulties in analyzing it (Richard and Zhang 2012). Second, a large amount of research has been devoted to investigating its antecedents and consequences (Han et al. 2008;Pan et al. 2012) because loyalty is related to other complex variables like consumer involvement, trust, satisfaction, commitment, and engagement (Ball et al. 2004;Huang et al. 2006;Hajli et al. 2017). Moreover, in last years, the evolution of consumers and the development of social media have profoundly changed the consumers’ behaviors and the way that they interact with other consumers and with the firm itself (Dolan et al. 2016;Gensler et al. 2013;Pentina et al. 2013). For scholars, therefore, it is not easy to identify the directions to which address their efforts aimed at contributing to the advancement of the research on this topic. This paper aims to provide an overview of the research findings and trends by mapping the research field in clusters able to guide the researcher to the most influential works, results, and issues that need more insights. With this end, this paper offers a bibliometric analysis and a mapping study of the works on customer loyalty and brand management. Traditionally, researchers have analyzed earlier findings using two methods: the qualitative approach of a structured literature review and the quantitative approach of meta-analysis (Schmidt 2008). In last years, thanks to the introduction of online databases with citation data (e.g., Web Of Science) and the proliferation of software for conducting bibliometric analyses (e.g., SciMAT and BibExcel), bibliometric methods have spread. Bibliometric methods use a quantitative approach for the description, evaluation, and monitoring of published research. These methods, by using a systematic, transparent, and reproducible review process, allow the overcoming of the limits of narrative literature reviews, which often lack rigor and are exposed to bias by the researcher (Tranfield et al. 2003). As highlighted by Zupic and ˇ Cater (2015), bibliometric methods have been widely used to map the fields of strategic management since 1999. In the field of customer loyalty, Siemieniako (2018) provides a bibliometric analysis of scientific works published in the Scopus database in the period from 2003 to 2017; the analysis is focused only on the customer loyalty in the business-to-business context. With regard to the topic of brand management, some bibliometric analyses have been conducted, particularly on the consumer brand relationships (Fetscherin and Heinrich 2015), on brand personality (Llanos-Herrera and Merigo 2018;Radler 2018), and on corporate branding (Fetscherin and Usunier 2012). This work contributes to the previous knowledge by analyzing customer loyalty for both the B2B and B2C contexts, with a focus on the relationships between customer loyalty and brand management. Among the different bibliometric methods, this paper adopts the science mapping, which allow for mapping the cognitive structure and evolution of scientific fields and disciplines (Noyons et al. 1999) producing a spatial representation of them (Calero Medina and Leeuwen 2012;Small 1999). Based on the citation index, the most important papers on customer loyalty and brand management have been identified and analyzed to display the structural and dynamic aspects of scientific research (Börner et al. 2003;Morris and Van der Veer Martens 2008). In a second phase, the different works have been clustered on the basis of the words co-occurrence and each cluster has been analyzed to facilitate the identification of the relationships between each dimension involved. This work is organized, as follows: first, the method used is described; second, results are illustrated and then discussed; finally, conclusions, theoretical and practical implications are provided. 2. Materials and Methods This work is based on a bibliometric analysis and mapping study of the contributions about customer loyalty and brand management. Document information was recovered from the Web of Science’s (WOS) SCI-Expanded by Thomson Reuters. This database was chosen because it offers a significant advantage being multidisciplinary and including social sciences literature (Norris and Oppenheim 2007). Adm. Sci. 2019,9, 8 3 of 21 The analysis was carried out by searching for the Topic: (customer loyalty AND brand management), refined by: Web of Science Categories = (Business or Management) AND Document Types = (Article or Review or Book Chapter), using Indexes = Sci-Expanded, SSCI, A&HCI, CPCI-S, CPCI-SSH, BKCI-S, BKCI-SSH, ESCI, CCR-Expanded, IC (Waltman 2016). The search was conducted during September 2018 within the Timespan = 2000–2018 because a substantial presence of works on the subject was detected only starting from 2000 (only four works were found in all the ‘90s). Results have been collected in a unique database containing the variables of authors, language, year of publication, type of research, country, keywords, and cited references in each of the publications included in the search. First, a bibliometric analysis was conducted to identify the total publications by year, the sum of times cited by year, the most cited authors, and productive countries. A top ten of the most cited publications was created. Subsequently, the scientific mapping study was carried out using the software SciMAT, developed by the “SECABA” group from the University of Granada, which allows the construction of scientific maps as well as a better visualization of the evolution within a scientific area (Cobo et al. 2012). SciMAT provides different modules that help the analyst conduct a science mapping workflow: a module that is dedicated to the management of the knowledge base and its entities, a module responsible for conducting the science mapping analysis, and a module to visualize the generated results and maps (Cobo et al. 2012). To perform the analysis, the following configuration in SciMAT was established: word as the unit of analysis, co-occurrence analysis as the tool to build the networks, equivalence index as the similarity measure to normalize the networks, Jaccard index as the evolution measure, Inclusion index as the overlapping measure, the H-Index to detect the relevance, and the simple centers algorithm as the clustering algorithm to detect the clusters (Castillo-Vergara et al. 2018). The analysis provides an evaluation map for the topic “customer loyalty and brand management” with the most occurring words and their relevance in the publications analyzed. The relevance of the words was established on the basis of three measures: documents count, H-Index, and sum citations. For each relevant word of the analysis, a cluster of the related words was created, graphically showing the relevance of each word in the cluster and the links between each one. 3. Results 3.1. Bibliometric Analysis The search on Web of Science yielded 337 publications on customer loyalty and brand management. Publications started from 2000 and grew exponentially, reaching a pick in 2017. Because the search was conducted in September 2018, data related to the year 2018 are not complete but looking at the trend, it is assumed a confirmation of growth also for this year (Figure 1). Citations of works about customer loyalty and brand management date back to 2002 and then grew over the years, showing a constant growth rate (Figure 1). Adm. Sci. 2019, 9, x FOR PEER REVIEW 3 of 21 The analysis was carried out by searching for the Topic: (customer loyalty AND brand management), refined by: Web of Science Categories = (Business or Management) AND Document Types = (Article or Review or Book Chapter), using Indexes = Sci-Expanded, SSCI, A&HCI, CPCI-S, CPCI-SSH, BKCI-S, BKCI-SSH, ESCI, CCR-Expanded, IC (Waltman 2016). The search was conducted during September 2018 within the Timespan = 2000–2018 because a substantial presence of works on the subject was detected only starting from 2000 (only four works were found in all the ‘90s). Results have been collected in a unique database containing the variables of authors, language, year of publication, type of research, country, keywords, and cited references in each of the publications included in the search. First, a bibliometric analysis was conducted to identify the total publications by year, the sum of times cited by year, the most cited authors, and productive countries. A top ten of the most cited publications was created. Subsequently, the scientific mapping study was carried out using the software SciMAT, developed by the “SECABA” group from the University of Granada, which allows the construction of scientific maps as well as a better visualization of the evolution within a scientific area (Cobo et al. 2012). SciMAT provides different modules that help the analyst conduct a science mapping workflow: a module that is dedicated to the management of the knowledge base and its entities, a module responsible for conducting the science mapping analysis, and a module to visualize the generated results and maps (Cobo et al. 2012). To perform the analysis, the following configuration in SciMAT was established: word as the unit of analysis, co-occurrence analysis as the tool to build the networks, equivalence index as the similarity measure to normalize the networks, Jaccard index as the evolution measure, Inclusion index as the overlapping measure, the H-Index to detect the relevance, and the simple centers algorithm as the clustering algorithm to detect the clusters (Castillo-Vergara et al. 2018). The analysis provides an evaluation map for the topic “customer loyalty and brand management” with the most occurring words and their relevance in the publications analyzed. The relevance of the words was established on the basis of three measures: documents count, H-Index, and sum citations. For each relevant word of the analysis, a cluster of the related words was created, graphically showing the relevance of each word in the cluster and the links between each one. 3. Results 3.1. Bibliometric Analysis The search on Web of Science yielded 337 publications on customer loyalty and brand management. Publications started from 2000 and grew exponentially, reaching a pick in 2017. Because the search was conducted in September 2018, data related to the year 2018 are not complete but looking at the trend, it is assumed a confirmation of growth also for this year (Figure 1). Citations of works about customer loyalty and brand management date back to 2002 and then grew over the years, showing a constant growth rate (Figure 1). Total Publications by Year Sum of Times Cited by Year Figure 1. Publications and citations distribution by year. Adm. Sci. 2019,9, 8 4 of 21 Among the most productive authors, we find Heiner Evanschitzky, Sunil Gupta, and Peter C. Verhoef and most of the works have been published in the United States (Figure 2). Adm. Sci. 2019, 9, x FOR PEER REVIEW 4 of 21 Figure 1. Publications and citations distribution by year. Among the most productive authors, we find Heiner Evanschitzky, Sunil Gupta, and Peter C. Verhoef and most of the works have been published in the United States (Figure 2). Most Productive Authors Most Productive Countries Figure 2. Most productive Authors and Countries. The study of customer loyalty and brand management is transversal to different fields of study in the research areas of management and business, belonging to both the B2C and B2B contexts; the main ones are listed in the Table 1. Table 1. Fields of study. Field of Study Most Relevant Works Retail (Chiou et al. 2010; Baltas et al. 2010) e-Commerce (Jin et al. 2008; Ng 2013; Chen et al. 2009) Social media (Gamboa and Gonçalves 2014; Van Doorn et al. 2010; Zhang and Luo 2016) Service sector (Cassia et al. 2017, Han et al. 2008; Caruana 2002) Hospitality & Tourism (Chen and Myagmarsuren 2010; Horng et al. 2012; Huang and Chiu 2006) Table 2 shows a top ten of the most cited works about customer loyalty and brand management. From the analysis of these works, it is possible to identify the most relevant research topics in the Figure 2. Most productive Authors and Countries. The study of customer loyalty and brand management is transversal to different fields of study in the research areas of management and business, belonging to both the B2C and B2B contexts; the main ones are listed in the Table 1. Table 1. Fields of study. Field of Study Most Relevant Works Retail (Chiou et al. 2010;Baltas et al. 2010) e-Commerce (Jin et al. 2008;Ng 2013;Chen et al. 2009) Social media (Gamboa and Gonçalves 2014;Van Doorn et al. 2010;Zhang and Luo 2016) Service sector (Cassia et al. 2017;Han et al. 2008;Caruana 2002) Hospitality & Tourism (Chen and Myagmarsuren 2010;Horng et al. 2012;Huang et al. 2006) Table 2shows a top ten of the most cited works about customer loyalty and brand management. From the analysis of these works, it is possible to identify the most relevant research topics in the literature on customer loyalty. First of all, it should be noted that there is a strong interest from Adm. Sci. 2019,9, 8 5 of 21 the scientific community in the attempts of identification and operationalization of the dimensions of customer loyalty and their links with other variables related to the consumer, like satisfaction and engagement, or to the company, like reputation and brand image. Particularly, the work of McAlexander et al. (2002) tries to conceptualize customer loyalty as integration in a brand community and it received 894 citations since its publication. A great interest is also shown by scholars towards customer engagement behaviors (CEBs), defined as the customers’ behavioral manifestation toward a brand or firm, beyond purchase, that results from motivational drivers (Van Doorn et al. 2010). The attention is on the antecedents, impediments, and firm consequences of customer engagement (Verhoef et al. 2010). Table 2. Top 10 of the most cited works on customer loyalty and brand. Authors Publication Year Title Total Citations Average per Year McAlexander, J.H.; Schouten, J.W.; Koenig, H.F. 2002 Building brand community 894 52.59 Van Doorn, J.; Lemon, K.N.; Mittal, V.; Nass, S.; Pick, D.; Pirner, P.; Verhoef, P.C. 2010 Customer Engagement Behavior: Theoretical Foundations and Research Directions 518 57.56 Ganesh, J.; Arnold, M.J.; Reynolds, K.E. 2000 Understanding the customer base of service providers: An examination of the differences between switchers and stayers 429 22.58 Rauyruen, P.; Miller, K.E. 2007 Relationship quality as a predictor of B2B customer loyalty 297 24.75 Johnson, M.D.; Herrmann, A.; Huber, F. 2006 The evolution of loyalty intentions 278 21.38 Yi, Y.J.; Jeon, H. 2003 Effects of loyalty programs on value perception, program loyalty, and brand loyalty 245 15.31 Cooil, B.; Keiningham, T.L.; Aksoy, L.; Hsu, M. 2007 A longitudinal analysis of customer satisfaction and share of wallet: Investigating the moderating effect of customer characteristics 243 20.25 Verhoef, P.C.; Reinartz, W.J.; Krafft, M. 2010 Customer Engagement as a New Perspective in Customer Management 220 24.44 Cretu, A.E.; Brodie, R.J. 2007 The influence of brand image and company reputation where manufacturers market to small firms: A customer value perspective 220 18.33 Yi, Y.J.; La, S. 2004 What influences the relationship between customer satisfaction and repurchase intention? Investigating the effects of adjusted expectations and customer loyalty 210 14 In the same way, many authors have found useful for their research the study of Ganesh et al. (2000), which provides insights for a deeper understanding of the customer base in order to target the customer retention and loyalty-building efforts to the right customers. Another study of interest concerns the dimensions of relationship quality that can explain the influence of relationships on customer loyalty in terms of behavioral aspects (purchase intentions) and attitudinal loyalty (Rauyruen and Miller 2007); trust, commitment, satisfaction, and service quality are considered among the most important relationship quality dimensions. From the analysis of the selected publications, it also emerges a great scientific interest about the drivers of customer loyalty intentions toward the brand as variables that mediate the effects of value on intentions (Johnson et al. 2006). Other debated themes are the relationship between customer satisfaction and customer retention as the primary measure of loyalty (Cooil et al. 2007) and the influences of brand image and company reputation on customers’ perceptions of quality, customer value, and customer loyalty (Cretu and Brodie 2007). Finally, other most cited works investigate how loyalty influences the relationship between customer satisfaction and repurchase intention (Yi and La 2004), and how reward schemes of a loyalty Adm. Sci. 2019,9, 8 6 of 21 program influence the perceived value of the program and how value perception of the loyalty program affects customer loyalty (Yi and Jeon 2003). 3.2. Mapping Study From the scientific mapping study, an evaluation map emerged showing six relevant nodes. These nodes represent the most frequent words in the analyzed documents, as well as the most cited and relevant ones that are based on H-Index. As Figure 3shows, customer satisfaction is the most frequent, relevant, and cited topic in the works on customer loyalty and brand management, followed by consumer trust, brand community, consumer perceptions, consumer behavior, and competitive advantage. Adm. Sci. 2019, 9, x FOR PEER REVIEW 6 of 21 3.2. Mapping Study From the scientific mapping study, an evaluation map emerged showing six relevant nodes. These nodes represent the most frequent words in the analyzed documents, as well as the most cited and relevant ones that are based on H-Index. As Figure 3 shows, customer satisfaction is the most frequent, relevant, and cited topic in the works on customer loyalty and brand management, followed by consumer trust, brand community, consumer perceptions, consumer behavior, and competitive advantage. Documents Count H-Index Sum Citations Figure 3. Evolution map. At each node, the software identified a cluster of related words. The first cluster shows a high correlation between the words customer satisfaction and customer loyalty (Figure 4). Customer satisfaction, as a measure of the perceived quality, is considered to be the basis for the customer loyalty to the firm, and, in most cases to the brand, able to predict behavioral intentions of customers such as purchasing intentions. The majority of works in this area adopt a quantitative method proposing empirical models able to operationalize and measure these constructs. Customer loyalty, satisfaction, and intentions are generally operationalized as second order constructs and the correlations between them are generally analyzed through the method of the structural equation modelling. The second cluster detects a high correlation in the papers that were analyzed between the words consumer trust and consumer commitment (Figure 4). Particularly, in most cases, trust is considered to be an antecedent of consumer commitment. Several works attribute the increasing in trust and commitment to the Customer Relationship Management (CRM) policies of the firm aimed at influencing the perceived value of consumers. Others consider commitment and trust key elements of relationship marketing, and not only consequences, because they encourage marketers to work at preserving relationship investments. CRM, by increasing consumer commitment and trust, creates positive effects on the firm performance. These issues are mostly studied in the e-commerce context. Figure 3. Evolution map. At each node, the software identified a cluster of related words. The first cluster shows a high correlation between the words customer satisfaction and customer loyalty (Figure 4). Customer satisfaction, as a measure of the perceived quality, is considered to be the basis for the customer loyalty to the firm, and, in most cases to the brand, able to predict behavioral intentions of customers such as purchasing intentions. The majority of works in this area adopt a quantitative method proposing empirical models able to operationalize and measure these constructs. Customer loyalty, satisfaction, and intentions are generally operationalized as second order constructs and the correlations between them are generally analyzed through the method of the structural equation modelling. The second cluster detects a high correlation in the papers that were analyzed between the words consumer trust and consumer commitment (Figure 4). Particularly, in most cases, trust is considered to be an antecedent of consumer commitment. Several works attribute the increasing in trust and commitment to the Customer Relationship Management (CRM) policies of the firm aimed at influencing the perceived value of consumers. Others consider commitment and trust key elements of relationship marketing, and not only consequences, because they encourage marketers to work at preserving relationship investments. CRM, by increasing consumer commitment and trust, creates positive effects on the firm performance. These issues are mostly studied in the e-commerce context. Adm. Sci. 2019,9, 8 7 of 21 Adm. Sci. 2019, 9, x FOR PEER REVIEW 7 of 21 Cluster 1 *: Customer Satisfaction Cluster 2 **: Consumer Trust Node Most cited work Node Most cited work Customer Satisfaction Evanschitzky and Wunderlich 2006 Consumer Trust Chumpitaz Caceres and Paparoidamis 2007 Customer-Loyalty Kumara and Shah 2004 CRM Meyer-Waarden 2008 Empirical Model Cooil et al. 2007 Firm Performance Yi and La 2004 Perceived Quality Frank et al. 2014 Consumer Commitment McAlexander et al. 2002 Brand Loyalty Yi and Jeon 2003 Perceived Value Cretu and Brodie 2007 Behavioral Intentions Forgas-Coll et al. 2014 e-Commerce Jin et al. 2008 * Cluster 1: Density: 85.59 Density range: 1 Centrality: 102.7 Centrality range: 1 ** Cluster 2: Density: 14.63 Density range: 0.83 Centrality: 58.54 Centrality range: 0.83 Figure 4. Cluster 1 and cluster 2 (Chumpitaz Caceres and Paparoidamis 2007; Kumara and Shah 2004). The central node of the third cluster is the brand community (Figure 5). A brand community is generally defined as a customer–customer–brand triad (Muniz and O’Guinn 2001). The social aggregation of brand users and their relationships to the brand itself spread widely thanks to social media that favor interactions and information sharing. Participation in a brand community represents one of the main expressions of customer engagement that in these contexts is manifested through behaviors, such as the word-of-mouth. The interactions between consumers and companies within the brand communities often take the form of value co-creation paths. Value co-creation was introduced by the Service-Dominat logic (Vargo and Lusch 2004, 2008), which defines it as the creation of a joint value through the application of competences and the integration of resources between the firm and the customer. In cluster 4, consumer-perception is the concept around which many other topics are analyzed (Figure 5). Consumers’ perceptions about a company are mainly determined by the brand image but also by the brand equity. Brand equity represents the customer’s subjective and intangible perceptions and attitudes about the brand and it tends to represent the emotional and irrational aspects of the market offering that connect the customer with the brand. Consumers’ perceptions are also affected by the corporate social responsibility of the firm, which positively influences the benefit and the value perceived by the consumer in the company’s offer, the judgment of fairness in the price differential charged for it, and his/her buying intention, in a context where the socially responsible firm practices a price higher than the competition. Positive consumers’ perceptions about a firm or a brand represent a determinant of the purchase intentions, thus increasing the customer value. Figure 4. Cluster 1 and cluster 2 (Chumpitaz Caceres and Paparoidamis 2007;Kumara and Shah 2004). The central node of the third cluster is the brand community (Figure 5). A brand community is generally defined as a customer–customer–brand triad (Muniz and O’guinn 2001). The social aggregation of brand users and their relationships to the brand itself spread widely thanks to social media that favor interactions and information sharing. Participation in a brand community represents one of the main expressions of customer engagement that in these contexts is manifested through behaviors, such as the word-of-mouth. The interactions between consumers and companies within the brand communities often take the form of value co-creation paths. Value co-creation was introduced by the Service-Dominat logic (Vargo and Lusch 2004,2008), which defines it as the creation of a joint value through the application of competences and the integration of resources between the firm and the customer. In cluster 4, consumer-perception is the concept around which many other topics are analyzed (Figure 5). Consumers’ perceptions about a company are mainly determined by the brand image but also by the brand equity. Brand equity represents the customer’s subjective and intangible perceptions and attitudes about the brand and it tends to represent the emotional and irrational aspects of the market offering that connect the customer with the brand. Consumers’ perceptions are also affected by the corporate social responsibility of the firm, which positively influences the benefit and the value perceived by the consumer in the company’s offer, the judgment of fairness in the price differential charged for it, and his/her buying intention, in a context where the socially responsible firm practices a price higher than the competition. Positive consumers’ perceptions about a firm or a brand represent a determinant of the purchase intentions, thus increasing the customer value. Adm. Sci. 2019,9, 8 8 of 21 Adm. Sci. 2019, 9, x FOR PEER REVIEW 8 of 21 Cluster 3 *: Brand-Community Cluster 4 **: Consume r -Perceptions Node Most cited work Node Most cited work Brand-Community Jang et al. 2008 Consumer-perceptions Chaudhuri and Ligas 2009 Social Media Gamboa and Gonçalves 2014 Brand-Image Cretu and Brodie 2007 Service-Dominant logic Cassia et al. 2017 Brand Equity Torres and Tribò 2011 Value co-creation Kandampully et al. 2015 Repurchase Intentions Tsai and Huang 2007 Word-Of-Mouth Chang et al. 2013 CRS Pirsch et al. 2007 Customer Engagement Van Doorn et al. 2010 Customer Value Brodie et al. 2009 * Cluster 3: Density: 11.4 Density range: 0.67 Centrality: 30.72 Centrality range: 0.5 ** Cluster 4: Density: 6.89 Density range: 0.5 Centrality: 34.87 Centrality range: 0.67 Figure 5. Cluster 3 and cluster 4. Cluster 5 is focused on the consumer behaviors that depend on the customer involvement and the customer experience with the brand (Figure 6). Customer involvement motivates consumers to identify with product/service offerings, their consumption patterns, and consumption behavior. Involvement creates an urge within consumers to look for and think about the product/service category and the varying options before making decisions on brand preferences and the final act of purchase. It determinates the amount of physical and mental effort that a consumer puts into a purchase decision, thus influencing the decision-making process of consumers, particularly the purchasing decisions. These decisions also influence the choice of the store, for this reason these variables are studied above all in the retail context. Finally, in cluster 6 the central node is represented by the competitive advantage of the firm (Figure 6). The achievement of a sustainable competitive advantage depends on the ability of the firm to increase the switching costs for the customers to dissuade them from switching to a competitor’s product, brand, or services and thus enhancing the customer retention. Greater customer retention as well as lower customer sensitivity to company’s prices have positive effects on customer equity in terms of the total combined customer lifetime values of the company’s customers. Finally, firm reputation is one of the most important intangible resources for competitive advantage, because it possesses rarity, value, non-substitutability, and imperfect immutability. Firm reputation influences the perception of the company that is held by consumers, favorably influences new products amongst consumers making purchasing decisions that are more likely to take a risk on a new product if they already know and trust a company with a strong reputation. Figure 5. Cluster 3 and cluster 4. Cluster 5 is focused on the consumer behaviors that depend on the customer involvement and the customer experience with the brand (Figure 6). Customer involvement motivates consumers to identify with product/service offerings, their consumption patterns, and consumption behavior. Involvement creates an urge within consumers to look for and think about the product/service category and the varying options before making decisions on brand preferences and the final act of purchase. It determinates the amount of physical and mental effort that a consumer puts into a purchase decision, thus influencing the decision-making process of consumers, particularly the purchasing decisions. These decisions also influence the choice of the store, for this reason these variables are studied above all in the retail context. Finally, in cluster 6 the central node is represented by the competitive advantage of the firm (Figure 6). The achievement of a sustainable competitive advantage depends on the ability of the firm to increase the switching costs for the customers to dissuade them from switching to a competitor’s product, brand, or services and thus enhancing the customer retention. Greater customer retention as well as lower customer sensitivity to company’s prices have positive effects on customer equity in terms of the total combined customer lifetime values of the company’s customers. Finally, firm reputation is one of the most important intangible resources for competitive advantage, because it possesses rarity, value, non-substitutability, and imperfect immutability. Firm reputation influences the perception of the company that is held by consumers, favorably influences new products amongst consumers making purchasing decisions that are more likely to take a risk on a new product if they already know and trust a company with a strong reputation. Adm. 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