1. Introduction
Social capital is “the network of relationships among people who live and work in a particular society, enabling that society to function effectively”. It involves the effective functioning of social groups through interpersonal relationships, a shared sense of identity, a shared understanding, shared norms, shared values, trust, cooperation, and reciprocity. Social capital is a measure of the value of resources, both tangible (e.g., public spaces, private property) and intangible (e.g., actors, human capital, people), and the impact that these relationships have on the resources involved in each relationship, and on larger groups. It is generally seen as a form of capital that produces public goods for a common purpose (Cohen & Prusak, 2002). Social capital allows a group of people to work together effectively to achieve a common purpose or goal. It allows a society or organization, such as a corporation or a nonprofit, to function together as a whole through trust and shared identity, norms, values, and mutual relationships. Put simply, social capital benefits society as a whole through social relationships. As such, the study of how social capital works or fails to work pervades the social sciences (Dieu et al., 2022; Nguyen et al., 2022).
Brand image is a crucial concept in all marketing efforts, and it plays a key impact in purchasing decisions (in-role behaviour) and product recommendations (extra-role behavior). In the same way, social capital has a big impact on customer behavior. A group of academics adds to the literature by claiming that social capital influences consumer behavior by modifying customers’ knowledge of environmental issues. The association between social capital and financial performance has been discovered in some social capital research.
According to a study conducted in Pakistan’s banking business, social capital has a strong positive association with consumer in-role behavior and is negatively associated with unfavourable word of mouth (negative extra-role behaviour). Another study in Puerto Rico has added to the growing body of evidence indicating social networks have a major impact on social capital. As a result, it boosts or improves the firm’s performance. There are either one or no mediating variables in all of these studies. In Pakistan, research on the impact of social capital on brand image and C-C identification is sparse. There have been studies done on this, however they either cover the relationship between social capital and brand image or the relationship between social capital and C-C identity.
We expected that increasing social capital would improve brand image and consumer-company identification, resulting in favorable in-role and extra-role customer behavior toward the brand. No other study has included all of these variables in a structural model, therefore this is a unique endeavor. Furthermore, this concept has never been studied or worked on before, particularly in the context of Pakistan. Our study contributes to the body of knowledge on a hitherto unexplored theoretical model: the mediation of brand image and C-C identification over the relationship between social capital and consumer in and extra role behavior. This research used social capital theory to gain a better understanding of the relationship between social capital and customer behavior, particularly when mediated by C-C identification and brand image. It may be argued that the links between the variables have been theoretically and experimentally tested by this study.
2. Literature Review
2.1. Consumer Behavior
Consumer behavior is the study of individuals, groups, or organizations and all the activities associated with the purchase, use, and disposal of goods and services. Consumer behavior consists of how the consumer’s emotions, attitudes, and preferences affect buying behavior (Nghiem-Phu, 2022). Consumer behavior encompasses mental and physical activities that consumers engage in when searching for, evaluating, purchasing, and using products and services. In the marketplace, consumers exchange their scarce resources (including money, time, and effort) for items of value (Herlinawati et al., 2019). Consumer behavior refers to the acquisition, consumption, and disposal of products, services, time, and ideas by decision-making units. This behavior is pervasive, involving choices made by virtually all human beings in all societies and cultures.
An individual’s behavior is determined by the role of the person, and the person’s perception of how he or she should behave in particular environmental situations. It is rarely a valid indicator of the psychological core of an individual’s personality. Customer extra-role behaviors are helpful, discretionary behaviors of customers that support the ability of the firm to deliver service quality. Thus, customer extra role behaviors are voluntary acts on behalf of customers that benefit firms.
2.2. Brand Image
Brand Image is how customers think of a brand. It can be defined as the perception of the brand in the minds of the customers. This image develops over time. Customers form an image based on their interactions and experience with the brand. These interactions take place in many forms and do not necessarily involve the purchase or use of products and services. Brand image is the customer’s perception of your brand based on their interactions. In marketing, brand management begins with an analysis of how a brand is currently perceived in the market, proceeds to planning how the brand should be perceived if it is to achieve its objectives, and continues with ensuring that the brand is perceived as planned and secures its objectives.
Brand image is the current view of the customers about a brand. It can be defined as a unique bundle of associations within the minds of target customers. It signifies what the brand presently stands for. It is a set of beliefs held about a specific brand. In short, it is nothing but the consumers’ perception of the product. It is the manner in which a specific brand is positioned in the market. Brand image conveys emotional value and not just a mental image. Brand image is nothing but an organization’s character. It is an accumulation of contact and observation by people external to an organization
H1: Brand image has a direct relationship with Consumer In-role Behavior.
H2: Brand image has a direct relationship with Consumer Extra-role Behavior.
2.3. Customer-Company (C-C) Identification
C-C identification is the primary psychological substrate for the kind of deep, committed, and meaningful relationships that marketers are increasingly seeking to build with their customers. C-C identification refers to a social relationship between a company and its customers. According to the consumer-company identification theory, consumers feel a sense of attachment to a company and are attracted to the company when they perceive it has an identity similar to their own. For example, consumers identified themselves with companies performing corporate social responsibility activities, and such customer-company identification resulted in increased customer loyalty.
Consumer-Company Identification is a relatively new issue in the marketing academia. Bhattacharya and Sen (2003) explored the Social Identity theory and established Consumer-Company Identification as the primary psychological substrate for deep relationships between the organization and its customers.
H3: C-C Identification has a direct relationship with Consumer In-role Behavior.
H4: C-C Identification has a direct relationship with Consumer Extra-role Behavior.
2.4. Social Capital
Social capital is a set of shared values that allows individuals to work together in a group to effectively achieve a common purpose. In business, social capital can contribute to a company’s success by building a sense of shared values and mutual respect. The term social capital refers to a positive product of human interaction. The positive outcome may be tangible or intangible and may include useful information, innovative ideas, and future opportunities. It can be used to describe the contribution to an organization’s success that can be attributed to personal relationships and networks, both within and outside an organization. It can also be used to describe the personal relationships within a company that help build trust and respect among employees, leading to enhanced company performance. Social capital revolves around three dimensions: interconnected networks of relationships between individuals and groups (social ties or social participation), levels of trust that characterize these ties, and resources or benefits that are both gained and transferred by virtue of social ties and social participation (Field, 2003).
2.5. Social Capital and Consumer Behavior
Social capital theory suggests that consumers are embedded in a complex network of social relationships which are sources of both normative pressures on and support to individual choices and behavior, thereby facilitating collective action towards some socially accepted goals. These characteristics, associated with actor-perceived credibility of particular societies and other actor experiments, deliver the OBC with a robust and interactive attention strategy for customer-to-customer information.
H5 : Social capital has a direct relationship with Brand Image.
H6: Social capital has a direct relationship with C-C Identification.
H7: Social capital has a direct relationship with Consumer In-role Behavior.
H8: Social Capital has a direct relationship with Consumer Extra-role Behavior.
2.6. Mediatory Relationships
The authors used the brand image to mediate perceived quality and brand loyalty, along with other factors. We can state that brand loyalty may be regarded as both in-role and extra-role behavior because a consumer has selected a certain brand over others and because he is loyal, he is advocating it to others and helping the organization’s product to improve.
3. Methodology
3.1. Sampling
The region of the survey consisted of a particular organization in Pakistan. For the research review, the investigator used the quantitative analysis method. Purposive sampling was used. Purposive sampling (also known as judgment, selective or subjective sampling) is a sampling technique in which the researcher relies on his or her own judgment when choosing members of the population to participate in the study. (Mackey & Gass, 2015). As a result, the current study’s goal is to use purposive sampling for collecting data and to justify the use of purposive selection. The initial data was collected via a questionnaire that was sent to respondents selected from various departments of organizations in the private sector in Pakistan. A total of 425 people were surveyed, including men and women from various departments and organizations.
3.2. Measurement
The questionnaire is divided into two sections, the first of which includes personal questions such as gender, age, education, and income. The next section is questions concerning the exploration variables. A 5-point Likert scale is used, which is a type of psychometric response scale in which responders specify their level of agreement to a statement typically in five points: (1) Strongly disagree; (2) Disagree; (3) Neither agree nor disagree; (4) Agree; (5) Strongly agree.
3.3. Demographic Characteristics
The demographic characteristics of respondents are shown in Table 1. According to the illustrative conclusion, 65 percent of male respondents and 35 percent of female respondents took part in the survey. 60.2 percent of respondents were between the ages of 15 and 25, 38.9 percent were between the ages of 26 and 35, and only 1.10 percent were between the ages of 36 and 45. The education level of respondents was also recorded; 0.1 percent were undergraduates, 68.2 percent were graduates, 15.4 percent held master’s degrees, 14.1 percent were M.Phil students from business school, and 2.2 percent were Ph.D. students. When we looked at the monthly income of the respondents, we found that 55.2 percent of them were earning less than 15000 PKR, nearly 20.4 percent were earning between 15000 and 25000 PKR, 15.8 percent were earning between 25000 and 35000 PKR, and 7.2 percent were earning between 35000 and 40000 PKR. The majority of those who took part in this survey were students from various disciplines of study.
Table 1: Descriptive Statistics
The following table illustrates the statistical data used to explain the questions to understand the role of social capital. Table 2 shows the mean and standard deviation of variables: Social Capital, Brand Image, C-C Identification, In-role behavior, and Extra role behavior. The minimum mean is 3.322, with a standard deviation of 1.193. The maximum mean was is 4.329, with a standard deviation of 0.854. Observing the results, we find that the standard deviation is lesser than the mean; this suggests that the mean value may represent the data most accurately.
Table 2: Variables and their Items with CFA
3.4. Structural Equation Modeling
The structural equation model (SEM) was used, and the testing was carried out using Smart PLS software. The testing was also done to examine the indirect and direct effects of all the constructs. It is utilized to analyze the structural connection between exogenous and endogenous variables.
3.5. Measurement of Outer Model
3.5.1. Composite Reliability
Composite reliability (sometimes called construct reliability) is a measure of internal consistency in scale items, much like Cronbach’s alpha. The composite reliability measures the internal consistency of indicator variables loading on the latent variable. If the Composite reliability is greater than 0.7 then the indicator variables loading on the latent variable have shared variance among them (Hair et al, 2017).
Cronbach’s alpha is a measure of internal consistency, that is, how closely related a set of items are as a group. It is considered to be a measure of scale reliability. A “high” value for alpha does not imply that the measure is unidimensional. A generally accepted rule is that α of 0.6–0.7 indicates an acceptable level of reliability, and 0.8 or greater is a very good level. However, values higher than 0.95 are not necessarily good, since they might be an indication of redundancy. With three items each, the Cronbach alpha values of the two conditional variables, C-C Identification, and brand image, were 0.742 and 0.809, respectively. The Cronbach alpha value for consumer role behavior with 3 items is 0.780. The Cronbach alpha value for extra-role behavior is 0.820. Hence all constructs are reliable (Table 3).
Table 3: Composite Reliability
3.5.2. Convergent Validity
Convergent validity refers to how closely the new scale is related to other variables and other measures of the same construct (Carmines & Zeller, 1979). Not only should the construct correlate with related variables but it should not correlate with dissimilar, unrelated ones (Table 4).
Table 4: Cronbach Alphas, rho_A, Composite Reliabilities, and AVE
3.5.3. Discriminant Validity
Discriminant validity is demonstrated by evidence that measures of constructs that theoretically should not be highly related to each other are, in fact, not found to be highly correlated to each other. (Carmines & Zeller, 1979). Discriminate validity is confirmed if the constructs have an AVE loading of more than 0.5, indicating that the construct explained at least 50% of the variance in the dependent variable.
3.5.4. Model Fit Measures
A number of parameters identify the ability of a criterion in SEM-PLS, including the standardized root-mean-square residual (SRMR), the accuracy of model fits such as d ULS and d G, the Normed Fit Index (NFI), and 2 (Chi-square). Table 6 provides the approximate criterion for both the estimated and saturated model. The estimated model assesses the relationship between the variables. The saturated criterion measures the variation in both estimated and saturated models.
Table 5: Discriminant Validity
Table 6: Fit Summary
4. Results and Discussion
The structural model aids in the comprehension and analysis of the complicated relationships between variables (Sarstedt & Cheah, 2019). SmartPLS 3.2.3 was used to test the structural model. Bootstrapping was used to test the structural model (Hair et al., 2012). Below is a screenshot of the results after running the test, as well as an explanation of the findings. SmartPLS reveals that the t-values for structural criterion measures originated from performing the bootstrap procedure. The outcomes of path coefficients for all hypotheses are indicated in the following diagram. The t-value bigger than 1.96 (p < 0.005) indicates that the relationship is significant at 95% confidence level (α = 0.05). The path diagram showed in Figure 1.
Figure 1: Path Diagram
Hypothesis 1 is supported, which shows that social capital has a significant impact on consumer in-role behavior when mediated by C-C identification. This hypothesis has been inferred since T-stats is 4.811, and P-value is 0.000, indicating that it is significant. Hypothesis 2 states that brand image is strongly associated with consumer extra-role behavior and is directly linked to it. Customers’ purchase behavior is likely to be influenced by brand image. If a customer is pleased with a brand’s image, they would naturally tell others about it, implying that Extra role behavior has increased. This hypothesis has been inferred since T-stats is 6.619 and P-value is 0.000, indicating that it is significant.
Hypothesis 3: C-C identification has a direct (positive) relationship with in-role customer behavior. Consumers will adopt all varieties of the same brand if consumer company identification is clear in their minds. The T-stats is 6.293, indicating a strong link between C-C Identification and in-role customer behavior. A P-value of 0.000 was used to deduce the hypothesis. C-C identification is directly related to customer extra-role behavior, according to Hypothesis 4. Buyers’ sense of a close tie between the corporation and themselves is aided by consumer company identification. This hypothesis has been inferred since T-stats is 4.960, and P-value is 0.000, indicating that it is significant.
Hypothesis 5 demonstrates a strong positive association between social capital and brand image, as evidenced by the T-stat of 3.687 and a significant P-value of 0.000. As a result, H5 was deduced. Hence, companies with high social capital are more likely to portray their brand in a positive light to their customers. Social capital and C-C identification are positively associated, according to Hypothesis 6. A recognized value of corporate social responsibility is customer company identification into consumer citizenship behavior. Because the T-stat is 7.368, showing a positive association, and the P-value is 0.05, it will link social capital to consumer company identification.
The P-value for Hypothesis 7 is 0.081, indicating a positive but insignificant association between social capital and customer in-role behavior. This means that, regardless of how much social capital a corporation has, its social capital has no effect on consumer in-role behavior! Consumers are less inclined to engage in in-role behavior. According to H8, social capital is associated with consumer Extra-role behavior in a good way. Customers’ assumptions about what they can and cannot do, are useful in determining consumer selection. Because the T-stats are 3.353, and the P-value is 0.000, this hypothesis has been inferred.
Hypothesis 9 demonstrates that, when mediated by brand image, the link between social capital and customer in-role is significant and positive. Customers are well-informed about their products. They talk about their experiences with others. If the customer is happy with the brand image, he will use a wide range of products without being confused. Hypothesis 10 is accepted. As a result, when consumer company identification and information sharing are used as mediators, there is a significant positive relationship between social capital and customer behavior. When the relevance of such information is insignificant, purchasers dominate and de-emphasize any unfavorable information they may receive about the organization or the item with which they are associated. The T-statistic is 4.665 and the P-value is 0.000.
When a brand image is used as a mediator variable, hypothesis 11 shows that social capital has a significant and positive impact on customer Extra role behavior. According to the findings, positive brand identities are the primary driver of customer priority. The significance level is less than 0.05. The t-stats for H11 are 3.083, and the P-value of 0.000 indicates that it is significantly revealed. The association between social capital and consumer extra-role behavior, according to Hypothesis 12, is significant and positive. This hypothesis has been inferred since T-stats is 3.601, and P-value is 0.000, indicating that it is significant.
The intervention or mediation effect can peak when the product of the path between the exogenous variable and the mediator (path a) and the path between the mediator and the endogenous variable (path b) is statistically significant (Base paper). Through the third exemplary mediator variable, mediation analysis is used to investigate the cause and effect relationship between independent and dependent variables (Carrión et al., 2017). Because it makes no assumptions about the sampling division of statistics and may be applied to small sample sizes, the bootstrapping approach is suited for mediation research (Carrión et al., 2017). To perform a mediation study in PLS-SEM, the first step is to assess the independent variables’ direct or immediate impact on the endogenous variable, which should be significant if the mediator is not present. According to Table 8, brand images and C-C identification appear to considerably moderate the impact of social capital on both in-the-role and extra-role behavior.
Table 7: T-stats and P-values of Direct Effects
Table 8: Mediation Effects
5. Conclusion and Managerial Implications
The goal of this study was to find out how social capital affects consumer role behavior. The mediating effects of customer-company identification (C-C Identification) and brand image are also examined in this study. Our findings have made a significant contribution to the literature in a number of ways. To begin with, the study discovered that social capital has a direct, undeniable, and significant association with brand image and C-C identity. This refers to the understanding that a company’s social capital, which is a broad sense is the network of connections, can increase with the increase of brand image and an increase in the identification between the company and customers. Similarly, the relationships between social capital and consumer in role and extra-role behavior were also checked; it was found that social capital has a specific and substantial relationship with customer extra-role behavior. The connection between in-role behavior and social capital indicated no significant relationship; however, this result cannot be generalized until tested several thousand times.
Second, this research adds to our understanding of the links between brand image and consumer role behavior. It was discovered that improving a brand’s image can lead to an increase in consumer in-role and extra-role behaviors. These connections were discovered to be substantial and proportionate to one another. Similarly, we looked at the links between C-C identification and customer role behaviors, which were equally significant, showing that an increase in C-C identification increases the likelihood of purchase behavior and extra-role behavior, such as promoting a product to others. Our conclusion on C-C identification is backed up by a 2005 study, which found that C-C identification had a strong and positive influence on the consumer’s extra-role behavior.
Finally, the Mediated analysis looks at how two variables influence or are affected by a third variable. Furthermore, we investigated the mediating impacts of brand image and identified several key features. When mediated by brand image, social capital is linked to customer behavior. Within the customer decision-making procedure of the purchase, the brand is a crucial component in picking a product or service. There is a link between in-role behavior (consumer purchasing preferences) and the decision to purchase a brand’s product. According to our findings, brand image functions as a mediator variable that has a significant impact on the consumer extra-role behavior, which is a dependent variable in the criterion. The dependent variables are both consumer in-role and extra-role behavior. It is all about consumer awareness or perception. When mediated by brand image, the relationship between social capital and in-role conduct (what people believe about individuals, perception) is strong. Social capital or community members are beneficial to their knowledge and conduct when it comes to brand image consciousness aspects. The brand image serves as a go-between. Consumer company identity is the second mediator, and it has a direct and positive relationship with customer in-role or extra-role behavior. Customers can gain the psychological need of self-identification by comparing different brand identities, or customer impressions of what customers believe about the brand.
Our research has shed light on the connections between social capital, brand image, C-C identification, and in-role and extra-role consumer behavior. In comparison to prior research in the Pakistani environment, this study presents a precise framework, making it unique. This study has important managerial implications for how managers and researchers can improve their company’s competitive advantage by focusing on its social capital, particularly when the mediation of brand image and C-C identification is discussed. A company’s social capital will likely result in improved customer service and extra-role conduct.
*Acknowledgements:
[1] We are thankful to the National Natural Science Foundation of China for supporting this research under fund number 72163018.
[2] There is no conflict of interest among the authors.
참고문헌
- Bhattacharya, C., & Sen, S. (2003). Consumer-company identification: A framework for understanding consumers' relationships with companies. Journal of Marketing, 67(2), 76-88. https://doi.org/10.212314123 https://doi.org/10.212314123
- Carmines, E. G., & Zeller, R. A. (1979). Reliability and validity assessment. Thousand Oaks, CA: Sage Publications.
- Carrion, G. C., Nitzl, C., & Roldan, J. L. (2017). Mediation analyses in partial least squares structural equation modeling: Guidelines and empirical examples. New York: Springer.
- Cohen, D., & Prusak, L. (2002). In good company: How social capital makes organizations work. Boston, MA: Harvard Business School Press.
- Dieu, T., Ho, A., Tran, Q. B., & Hoang, T. T. Van. (2022). The Impact of Sharing Culture on Opportunistic Behavior and Effectiveness of Employee Management : A Case Study in Vietnam. Journal of Asian Finance, Economics, and Business, 9(1), 423-435. https://doi.org/10.13106/jafeb.2022.vol9.no1.0423
- Field, J. (2003). Psycholinguistics: A resource book for students. Susses, UK: Psychology Press.
- Hair, J. F., Sarstedt, M., Pieper, T. M., & Ringle, C. M. (2012). The use of partial least squares structural equation modeling in strategic management research: a review of past practices and recommendations for future applications. Long Range Planning, 45(5-6), 320-340. https://doi.org/10.1016/j.lrp.2012.09.008
- Hair, J. F., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: Updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107-123. https://doi.org/10.1504/IJMDA.2017.087624
- Herlinawati, E., Suryana, A. E., & Machmud, A. (2019). The effect of entrepreneurial orientation on SMEs business performance in Indonesia. Journal of Entrepreneurship Education, 22(5). https://www.abacademies.org/articles/the-effect-of-entrepreneurialorientation-on-smes-business-performance-in-indonesia-8621.html
- Mackey, A., & Gass, S. M. (2015). Second language research: Methodology and design. London, UK: Routledge.
- Nghiem-Phu, B. (2022). Consumer behavior towards purchasing Feng Shui Goods: An empirical study from Vietnam. Journal of Asian Finance, Economics, and Business, 9(1), 83-92. https://doi.org/10.13106/jafeb.2022.vol9.no1.0083
- Nguyen, H. T., Le, M. K., Thuy, T., Nguyen, D., Phuong, V., Dao, L., & Nguyen, N. T. (2022). Social capital and migration: A case study of rural Vietnam. Journal of Asian Finance, Economics, and Business, 9(1), 63-71. https://doi.org/10.13106/jafeb.2022.vol9.no1.0063
- Sarstedt, M., & Cheah, J. H. (2019). Partial least squares structural equation modeling using SmartPLS: A software review. New York: Springer.