The mediating role of customer awareness to enhance the relationship between using social media tools and post-purchase behavior upon electrical devices buyers in Jordan

This study examined the effect of social media on post-purchase behavior on electrical device buyers in Jordan. Drawing on resource-based and knowledge-based previous studies, the mediating effects of customer awareness were also tested. Data were collected from 385 participants from the segment targeted group of customers in Jordan, and hypotheses were tested through partial least squares structural equation modeling using Smart PLS 4.0. The results showed that the mediating role of customer awareness influences enhancing the relationship between social media and promotion mix on the one hand, and post-purchase behavior (exit, voice, and loyalty) on the other hand. Our findings contribute to the existing literature by explaining and strengthening this relationship, which is also referred to as the black box through the mediation of customer awareness. Marketers should recognize the importance of this relationship to develop modern promotional tools in multiple social media to positively enhance the customers’ post-purchase behavior by giving them a competitive advantage.


Introduction
asserted that social media is 'fundamentally changing the way we communicate, collaborate, consume, and create".In this respect, social media tools have an impact on a large range of business processes, from marketing through to operations to finance (Luo et al., 2013).In other words, social media involves numerous e-platforms and services, including those related to online movies for example (Basuki et al., 2022).In the shade of the increasing use of digital technology and the internet, users can fulfill different needs, including communication, access to information, and e-shopping.Social media marketing is a new form of advertising which permits firms to target consumers with relevant and valuable content, which will result in increased consumer engagement and recognition of branded contents (Dahnil et al., 2014;De Vries et al., 2012;Michaelidou et al., 2011).In general, social media marketing tools are used to increase consumer purchase behavior of a product or service usage (Dewi et al., 2022).According to Hirschman model, several small and medium sized enterprises (SMEs), including the electrical devices companies, are using social media marketing to ameliorate customer loyalty through enhancing their awareness on the one hand, and reduce their voice and exit on the other hand (Mustafa et al., 2017;Yen & Chiang, 2021;Salhab et al., 2023).
Electrical devices as one of the durable goods whose purchase frequency is rather low compared to their prices, where some consumers purchase to fulfill their secondary needs, depending on their income level, effect of social media, promotion mix (advertising, sales promotion, public relation, direct marketing, and personal selling), considering that such items are less essential for survival; while other buyers may purchase to show off their wealth status; in essence, all these variables affect what is called post-purchase behavior in marketing field.

Social media and post-purchase behavior
Ala- Mutka et al. (2009) has defined social media as "instruments utilized by organizations to engage in socially-based activities such as sharing photos and videos, networking within the social context, and blogging and micro-blogging".Accordingly, most companies nowadays advertise on different social media pages including LinkedIn, Facebook, Instagram, YouTube, Twitter, and WhatsApp as businesses and organizations of different kinds are increasingly relying on these platforms (Saxena & Khanna, 2013).Evidently, there is a link between consumer and e-platforms given the enormous influence of social media on consumer behavior, from the being aware of a disparity between their actual circumstances and those they consider ideal or desirable, the need recognition stage, through to searching information and post-purchase behaviors like the statements of consumer satisfaction, dissatisfaction, delight in the best cases (Voramontri, & Klieb, 2019).
Consumers buying process does not end upon finishing buying goods or services only.After purchase, the consumer may achieve satisfaction or otherwise.It relies on two factors, namely the user's expectations and performance.And this eventually would create three potential situations of the consumer's satisfaction level.The first is when performance exceeds the expectations of consumers, then consumers will be satisfied.The second situation is when performance is below expectations of users, then consumers will experience dissatisfaction.The third situation is when performance matches expectations of the consumers, which may make them satisfied with a product or service bought.This rating will determine whether consumers will continue to buy products from the same company (purchases looping), or they will make a choice to choose products or services from other companies for the future purchases.Garín-Muñoz et al. (2016) argued that exit or post-purchase behaviour may have been able to generate two situations which are satisfaction or dissatisfaction.The second condition usually causes the user to give word of mouth (WoM) to others, spreading negative reviews on the result of his buying behaviour that can become a hazardous multiplied rejection consequence in the future.In fewer occasions, the consumer makes claims to the firm or to other institutions or organizations of several kinds.On the other hand, satisfaction will lead to a growth of habit of the brand's use logically, a growth of loyalty.In both conditions of claim or loyalty, the firm creates relationship formulas with its customers increasingly, after sales services (post-purchase behaviour).These structures, along with mouth-ear communication (WoM) and the voice option from agencies which are different information sources to the firm, which give feedback to the model, will enable improvements in existing services or products.Lastly, this feedback closes both internal and external circuits, and permanently shows the cyclical nature of human behaviour.Usually, at this stage, there will be a feeling of anxiety or cognitive dissonance.When associated with this study, the post-purchase behaviour is assumed that it will determine whether users will continue to use the same product, or they will stop using it and choose other providers.Thus, the hypothesis that can be formulated in this study for this element (social media marketing) is as follows: H1: Social media marketing has a positive effect on post-purchase behavior.Kotler and Armstrong (2016) have shown that the market targeted by a marketing communicator may not have any idea about the product or service being advertised at all, and that they may only know its name, or a few things about it.Consequently, marketers should first target building the consumer's awareness towards the product.Awareness has been defined as the level or the amount of information customers have about the product's properties, and how persuaded they are to try it, and how reminded they are to buy.That is, the higher the customer's awareness is towards a product, the more they will try and buy it.Social media is an e-platform which enables consumers to communicate, collaborate and share information, and helps firms with direct sales as well, customer acquisition and retention, as stated by Bilgin (2018).In most cases, businesses that have succeeded often use social media marketing as a strategy to establish a link with e-consumers, according to Elaydi (2018) who stated that digital WOM is an elemental avant-garde behind this growing marketing phenomenon.According to Godey et al. (2016) andBilgin, (2018) Social media marketing encompasses dimensions like interaction, entertainment, trendiness, customization, and WOM.For Aaker, (1991) he has defined awareness as "the ability of a prospective purchaser to recognize or remember that a brand is a member of a certain product category".This is because awareness minimizes the time and risk which consumers may spend in their search for the product they intend to buy (Verbeke et al., 2005).Being a brand that comes to mind at first means that it has become the most aware brand in the product category (Bilgin, 2018).Social media marketing has become an important tool for building and enhancing awareness, as stated by (Bilgin, 2018).In this regard, consumers are expected to opt for the brand about which they have information.Aaker (1996) stated that brand awareness consists of four levels, namely brand recognition, brand recall, top of the mind brand, and dominant brand.On their part, Tsimonis and Dimitriadis (2014) found that brand awareness is one of the most important outputs expected from businesses' social media marketing activities.The results of Seo and Park (2018), İsmail (2017), Fanion (2011) have revealed that social media is a pivotal tool in building and raising brand awareness with customers.Abdolvand et al. (2016) noted that awareness and knowledge have become a foundation in changing consumers' opinion, readiness, and behavior towards products, which in turn is a prerequisite to achieve the growth in the markets.Ramli et al., (2020), Prasetyaningsih and Astini (2016) showed that awareness has a positive link with purchase decision and loyalty; however, the relation between customer awareness and post-purchase behavior have not been studied yet.Thus, the hypotheses that can be formulated in this study are as follows:

Customer awareness
H2: Social media marketing has a positive effect on customer awareness.

H3: Customer awareness has a positive effect on post-purchase behavior.
H4: Customer awareness mediates the relationship between social media marketing and post-purchase behavior.

Research methodology
This article examines the effect of social media marketing tools on post-purchase behavior and the mediating effect of customer awareness of electrical devices buyers in Jordan.In this study, we used five predictors of social media marketing based on Kim and Ko (2012).For measuring customer awareness, the study used 6 predictors based on Aaker (1996) and postpurchase behavior scales were adopted from O'Cass and Pecotich (2005) also used by Mustafa et al. (2017).Table 1 illustrates a list of variables and predictors of measurement.The study collected primary data through the questionnaire from visitors to electrical devices agencies in Jordan.Data was collected from clients of electrical devices agencies in Amman, the capital.This is because the largest percentage of electrical devices agencies are concentrated in Amman, which is a great opportunity to obtain the highest volume of data.Regarding the number of scale categories, there is no clear-cut rule for the suitability of the categories that should be used (a Likert scale one to five-point or a Likert scale one to seven-point) for reducing confusion to the respondents, we use a Likert scale one to five-point .The sample was selected using simple random samples.The questionnaire was distributed through social networks.According to Sugiyono (2017), data gathering will be effective if a certain number of samples is fulfilled or achieved and spread over a large area.The total number of respondents was approximately 400 respondents.After data entry and screening (missing data, constant responses, increasing and decreasing scale in responses, binary responses, and high and low values in responses), 84 questionnaires were excluded, and the number of valid questionnaires for analysis reached 316, representing a response rate of approximately 73%.Since this research has 21 indicators to measure the three variables, the minimum sample needed is 270 respondents or ten times the number of indicators (Hair et al., 2014).Used by (Mustafa et al., 2017) I will consider a replacement of the product I am evaluating another product which I didn't support in the previous times I will suggest changes and some recommendations to improve V I will work with them to straighten out any problems, to reduce the phenomena of exit Right now, I am working together with them to improve the situation I will not do anything to solve the product problem, so I'll remain supporting the same product.L I will recommend the product to my friends and family to support in the next times I will buy and support the same product in the next times Customer awareness

Social media
Post-purchase behavior

Findings
To check the reliability and validity of the items, we used Smart-PLS to achieve this objective and tested the correlation between variables.According to Hair et al., (2019), Smart-PLS is appropriate for obtaining better results even in the case of complex and large sample sizes, and it is considered the best estimation tool for primary data.Smart-PLS helps evaluate the validity and reliability of the measurement model.To inspect the reliability, Smart-PLS provides the possibility to use a factor loading indicator and the average variance extracted (AVE) to obtain the convergent validity, in addition to the composite reliability (CR) to evaluate the reliability and Cronbach alpha to evaluate the internal consistency.In contrast, discriminant validity is assessed by measures such as Fornell Larcker, cross-loading, and Heterotrait Monotrait (HTMT) ratio.Also, Smart PLS helps evaluate the structural model, examine correlations, test direct and indirect paths, and analyze mediation effect.
The present study used Cronbach's alpha and an exploratory factor analysis (EFA) to assess the reliability and validity of the measurements along the line of many social science studies (Goaill, Perumal, & Noor, 2014;Ong, Salleh, & Yusoff, 2015), specifically in marketing context.The researcher employed the statistical package for social SPSS version 23 to test the internal consistency of the constructs.Table 2 shows that all measures attained a high-reliability coefficient, ranging from 64.3 to 91.4.The coefficients were all above the threshold value of 0.60, which implies high reliability (Sekaran, 2003;Hair et al.., 2017).The results in Table 3 indicates that the loading coefficients are more than 70%, and several items have been dropped because the loading coefficients are weak, which are (SMM6, CA6, PPB9 (E3, V3, L3)).The results show convergent validity, indicating the correlations between the items with loading coefficients greater than 70%.CR greater than 0.7 and AVE values greater than 0.5 indicate the converging's validity.Finally, Cronbach's alpha values are also more than 70%, which reveals internal consistency between the paragraphs, no errors in results, and the reliability of the measurement model is high.The correlation between variables was assessed to evaluate discriminant validity, and variable reliability was reviewed using the Fornell-Larcker procedures.The results in Table 4 indicate that the first value (the square root of AVE) in the first column is greater than the values of the other correlations, as is the case for the rows, as the square root value of the AVE in each row is higher than the rest of the correlation values in the same row.The discriminant validity was also confirmed by examining the results of cross-loading (see Table 5), as the values did not show a high correlation with other variables but only in this variable itself, which is considered a good indication that the values of discriminant validity are acceptable.Fig. 2 demonstrates the outer loading coefficients' results for the measurement model's constructs.

Testing the Structural Model (Inner Model)
The next step after examining the measurement model reliability and validity was to assess the structural model (inner model).Hair et al., (2017), Henseler and Sarstedt (2013) suggested some criteria for that, namely coefficient of determination (R²), path coefficients, effect size (f²), and goodness of fit (GoF).Each test will be discussed separately in the following section.

Coefficient of Determination/ R Square (R²)
An important criterion to evaluate a structural model (inner model) is the coefficient of determination or R² is the effect of the combination of the exogenous variables on the endogenous variables.Its value ranges between 0 and 1 with 1 representing complete predictive accuracy (Hair et al., 2014b).Chin (1998) suggested that the values of R² that above 0.67 are considered high, while values ranging from 0.33 to 0.67 are moderate, whereas values between 0.19 to 0.33 are weak.Table 6 illustrates the rule of thumb of R².In this research, the researcher followed Chin, (1998), as a guideline.The results showed that all values of R² had fulfilled the criteria of Chin (1998).Accordingly, the quality of the structural model can be assessed by R² value which shows the variance in the endogenous variable that is explained by the exogenous variables.
Secondly, the R² value of exit was 0.315, indicating that customer awareness can account for 31.5% of the variance in the customer exit, which is weak.The R² value of voice was 0.353, indicating that customer awareness can account for 35.3% of the variance in the customer voice, which is moderate.The R² of loyalty is 0.583, indicating that customer awareness can account for 58.3% of the variance in the customer loyalty, which is moderate.Table 7 displays the result.Effect Size (f²) Hair et al., (2014b) argued that 'through R² is a valued tool for assessing the quality of a PLS model, too much reliance on R² can prove problematic".They add that 'the decision for a model should be based on the adjusted R², which penalized increasing model complexity by reducing the (adjusted) R² when additional constructs are added to the model".According to Cohen (1998), values of f 2 above 0.35 are considered large effect size, while values ranging from 0.15 to 0.35 are medium, whereas values between 0.02 to 0.15 are considered small effect size; and lastly any values less than 0.02 are considered with no effect size.In this research, the f² of the endogenous and mediator on the endogenous variables was calculated using Cohen's formula.Table 8 displays the results.Table 8 shows the large effect size of social media marketing (f² = 0.4242) on customer awareness.In sum, it is obvious that the large effect size of social media marketing influences customer awareness.According to the research framework, logically, the researcher decided to test the structural model (effect size, the predictive relevance of the model, and good of fitness), for the three options separately.Started with the effect size of the exit constructs as shown in Table 9.From the above table, it is obvious that the social media marketing had a medium effect size on the component of customer response which is customer exit.In contrast, there was no effect size of the customer awareness on the customer exit.Table 10 illustrates the effect size of the independent variable (SMM and CA as a mediator) on voice constructs.From the above table, it was observed that the SSM had a medium effect size on the component of customer response which is customer voice, while there was a very small effect size of the customer awareness on voice.Table 11 illustrates the effect size of the independent variable (SMM, and CA as a mediator) on loyalty constructs.As shown in the above table, it was noticed that the SMM had no effect size on the component of customer response which is customer loyalty.In contrast, there was a large effect size of the customer awareness on the customer loyalty.

Goodness of Fit (GoF) of Model
The next criterion used to assess and predict the quality of a model was Goodness of Fit (GoF).The GoF (0 < GoF < 1) is the geometric mean of both average variances extracted (AVE) and the R² average of the endogenous variables.According to Wetzels, Odekerken-Schroder, and Oppen (2009), the rule of thumb for a minimum acceptable standard of GoF is that (small = 0.1, medium = 0.25, and large = 0.36) to be considered as global valid PLS model, respectively.In this research, the formula of GoF shows the result, which revealed that the values of the GoF ranged from 0.478 to 0.652.Following Wetzels et al.'s (2009) criteria, as shown in Table 12, it can be concluded that the GoF model of this study was large enough to have sufficient global PLS model validity.Path coefficients are the final step to assess the structural model.Hair et al., (2017) stated that this step aims to examine the hypothesized relationships linking the variables.To determine the relationships, the researcher ran the bootstrapping procedure.The bootstrapping algorithm in smart PLS 2.0 3M is a non-parametric resampling approach.According to Hair et al., (2014b), 'path coefficient values are standardized on a range from -1 to +1, with coefficients closer to +1 representing strong positive relationships and coefficients closer to -1 indicating strong negative relationships".In this research, t-value (t-test) and standard error for each path coefficient model were provided from the bootstrapping results in PLS-SEM.Table 13 presents the critical t-values for a two-tailed test which determines whether the assumed relationship is significant or not based on the value of t-value.

Table 13 T-value Criteria T-value criteria Hypothesis relationship result based on Chin criterion T-value less than 1.64
Rejected From 1.65 to 1.95, with p-value from 0.05 to 0.010.
Accepted with weak evidence From 1.96 to 2.58, with p-value from 0.01 to 0.05.
Accepted with significance relation Above 2.58, with p-value 0.01and below.
Accepted with strong significance In this research, seven direct effect hypotheses were formulated.Table 14 shows the bootstrapping and the path coefficient results of the hypothesized relationships.Specifically, the following hypothesized relationships were examined: Depending on the values in the above table, the results of six hypotheses were supported, while one is not supported.Thus, the descriptions of the results of the hypotheses are as follows: H1: There is a significant relationship between (SMM) and E, which was examined by using the PLS-SEM bootstrapping approach.Empirical result of PLS-SEM indicates that the proposed relationship between SMM and E was highly significant at (β = 0.593, t = 9.92, p < 0.000), thus H-2 was supported (refer to Table 14).H2: There is a significant association between SMM and V.The outcome of the PLS-SEM bootstrapping analysis shows that there is a positive significant association between SMM and V, at (β = 0.547, t = 10.80,p < 0.000), (refer to Table 14).H3: There is no significant association between SMM and L, which was developed to test this association.Statistical result of the PLS-SEM bootstrapping approach shows that there is no significant association between SMM and L at (β = 0.040, t = 1.029, p < 0.30) (See Table 14).H4: There is a significant relationship between (SMM) and CA, which was examined using the PLS-SEM bootstrapping approach.Empirical result of PLS-SEM indicates that the proposed relationship between SMM and CA was highly significant at (β = 0.567, t = 15.81,p < 0.000) and thus H-1 was supported (refer to Table 14).
H5: There is a significant association between CA and E. The outcome of the PLS-SEM bootstrapping analysis shows that there is a negative significant association between CA and E, at (β = -0.149,t = 2.73, p < 0.000), (refer to Table 14).H6: There is a significant association between CA and V.The outcome of the PLS-SEM bootstrapping analysis shows that there is a negative significant association between CA and V, at (β = -0.103,t = 2.12, p < 0.03), (refer to Table 14).H7: There is a significant association between CA and L. The outcome of the PLS-SEM bootstrapping analysis shows that there is a positive significant association between CA and L, at (β = 0.645, t = 14.69, p < 0.00), (refer to Table 14).

Discussion
The study explored how social media marketing impacts customer awareness, and post-purchase behavior (exit, voice, and loyalty).The findings revealed that social media marketing plays a significant role in stimulating consumers to repurchase.Specifically, social media marketing activities were found to have a significant influence on the buying behavior of Jordanian consumers.This supports earlier studies by Voramontri and Klieb, (2019) and Saxena and Khanna, (2013), which suggested that social media marketing enhances customers repurchase, leading to an increase in their willingness to purchase.Social media provides a platform for consumers to engage with products through customer awareness, which can lead to an increase in customer loyalty.This is consistent with research conducted by (Bilgin, 2018).Customer awareness was found to have a significant impact on social media marketing and post-purchase behavior.By establishing sustainable and efficient social media channels, customers can become more knowledgeable about products and services, which can encourage them to spread positive WOM.A more interactive social media system enables consumers to share information about products and services more freely, resulting in wider and faster dissemination of information.Additionally, the increasing popularity of social media in Jordan may prompt consumers to turn to social media as a source of information about products and services, which could also lead in turn to an increase in consumer purchase intentions.

Contribution of the study
The present study provided contributions to the body of knowledge as well as to practice.Theoretically, due to the limited number of studies conducted to understand the post-purchase behavior of customers to buy electrical devices in the Jordanian context, this study was undertaken to contribute to the body of knowledge by understanding the influence of social media tools on customers post-purchase behavior using customer awareness as a mediator.In addition, practically, this study provided some useful implications for the practitioners of the electrical device industry in Jordan.The results of the present study could help the wholesalers and retailers of such products formulate and create the right guidelines in the formulation of the right marketing strategies to enable them to successfully target and persuade the customers in Jordan about the benefits of electrical devices in their households.

Conclusion
Customer awareness enhances their opinions through social media marketing tools.Thus, they become an essential aspect of modern life, providing a platform for individuals to share their consumption patterns, product preferences, opinions, and experiences with others.This vast realm of communication, where consumers interact with each other, presents significant opportunities for businesses to promote their products at a lower cost, with greater speed, and to a larger audience.Companies have recognized this potential and are creating their own social media profiles to engage consumers by sharing product information, discounts, advertisements, and promotions through various activities.This research aimed to examine the impact of social media marketing tools on post-purchase behavior through customer awareness in Jordan.The study found that strong brands with effective social media marketing strategies are more likely to attract consumers to spread positive WOM or e-WOM messages and influence others to purchase or not purchase their products (exit, voice, and loyalty).Specifically, promoting products through social media tools can enhance their awareness, leading to increased consumer engagement and interaction.Therefore, businesses should incorporate social media strategies in their marketing plans to expand their brand network, foster community development, and increase interaction between products and consumers.In order to enhance profits and to maintain existing customers and gain new potential customers it is advisable for businesses to make consumers aware of their products or services through social media and establish strong relationships with customers through online communities.This study provides insights for Jordanian academics and practitioners on the impact of social media marketing to enhance customer awareness.The results indicate that Jordanian consumers heavily rely on social media tools during their purchasing decision-making process.Therefore, it is fateful for electrical devices agents in Jordan to recognize the significance of social media tools as effective marketing tool activities into their marketing strategies.The findings suggest that social media marketing can be an effective channel to reach Jordanian consumers and promote products and services.

Limitations and future work
The present study provides a brief discussion about the limitations and suggests some directions for future research.First, the generalizability of the results is one of the limitations of scientific research.Thus, the current study is not an exception.This study was conducted in Jordan.Therefore, to expand the validity and generalizability of the results, future work needs to be undertaken in other regions of the Middle East.Second, although the sample size of this study was adequate and appropriate, future researchers may use a larger sample to enhance the robustness of the results.In addition, this study focused mainly on electrical devices, hence, in the future, there is a need to conduct a study to understand the mediating role of customer awareness to enhance the relationship between using social media tools and post-purchase behavior in other industries such as cosmetics and apparel.Moreover, the existing study adopted a quantitative research approach to understand the topic of the study, which failed.Therefore, future work might be carried out using qualitative research approaches such as interviews or focus groups to obtain more insights on the topic of the study.

Table 1
Construct measurement easy to deliver my opinion about the brand.The content shared in SMM of particular brand is the updated information.the brand provides the information that I needed.I like the way the ads this brand has posted on SMM.

Table 4
Discriminant validity

Table 7
R-square of Endogenous Latent Variables

Table 9
The Effect Size of the Exit Constructs

Table 12
Results of Goodness of Fit of Model

Table 14
Path Coefficient of the Main Hypotheses (Direct Path)