The Impact of Social Media Marketing on Instagram Towards Brand Equity of Fashion Micro, Small and Medium Enterprises:
A Quantitative Study of Parira Clay
Karen Chelsea1*, Annisa Rahmani Qastharin1
1 School of Business and Management, Institut Teknologi Bandung, Bandung, Indonesia
*Corresponding Author: karen_chelsea@sbm-itb.ac.id
Accepted: 15 September 2021 | Published: 1 October 2021
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Abstract: The fashion industry has been going through continuously increasing competition.
This phenomenon serves as an obstacle, especially for fashion Micro, Small and Medium Enterprises (MSMEs) in building positive and strong brand equity. In this context, brand equity is defined as assets and liabilities that the brand produces to develop a competitive advantage.
With the growing usage of social media for business purposes, enterprises start to rely on social media marketing as an attempt to build their brand equity, Parira Clay as a newly established micro fashion enterprise in Indonesia is no exception. This study aims to evaluate whether social media marketing has an impact on the brand equity of Parira Clay. A quantitative approach was applied for this study. The data was collected through online survey distribution to respondents who followed Parira Clay on Instagram and have purchased its products. Data processing methods used were validity and reliability test and assumption test based on Ordinary Least Square requirement. Then, simple and multiple linear regression analysis through Adjusted R-Squared, F-test, and t-test was conducted to analyze the data. The result of this study indicates there is a significant impact of social media marketing on the brand equity of Parira Clay. This study suggests that Parira Clay can rely on its social media marketing use and functionalities in strengthening its brand equity. Social media marketing should be and considered an important tool when building a strong and positive brand equity.
Keywords: Social Media Marketing; Brand Equity; Fashion; Instagram; Micro, Small and Medium Enterprises
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1. Introduction
Brand plays an important role in marketing success, serving as a tool of differentiation and as reasons as to why the company’s offering is the best choice compared to those of competitors.
Brand is the idea people have in mind when faced with company’s offering, both practically and emotionally (Marion, 2015). How consumers feel and perceive toward a brand result in commercial value, known as rand equity. However, brand equity can either be an asset or liability depending on how well it performs. When it acts as an asset, it is capable in providing great contributing factors to company’s success, one of the factors is competitive advantage which enhance consumers’ confidence in making purchase and improve their user experience.
Now in the era of digitalization, social media usage for business purposes has been increasing.
Businesses start to rely on social media to improve their brand equity, including Micro, Small and Medium Enterprises (MSMEs). MSMEs play a huge role to macro economy of Indonesia.
The amount of business units that MSMEs have accounts to 99.9% of total business recorded
in Indonesia (Badan Pusat Statistik, 2020). In 2020, 42% of Indonesia MSMEs have joined social media platforms and achieved 26% increase of sales (Kementrian Koperasi dan UKM, 2020). The sales are dominated by fashion goods purchase as number one purchased goods online, taking up to 25.7% of total online spending in 2021, an increase of 50.7% from 2020.
On Instagram, Indonesia is the 4th country with the most users, accounting to 86 million users in 2021. As a business channel, it has gained more recognition as 90% of its users follow at least a business account, 2 out of 3 users stated that Instagram have increased their interaction with brand, and 50% people feel more interest towards a brand when seeing advertisement on Instagram. Considering its growing usage and recognition, social media, especially, Instagram has a potential as an important medium for fashion MSMEs to manage their brand equity.
Parira Clay is a local fashion micro enterprise specialized in handcrafted polymer earrings based in Bali, Indonesia. Its primary marketing activities are online based utilizing Instagram platform. Parira Clay’s marketing objectives are highly related to its brand wellness, which are to gain awareness towards its brand, perceived and associated as a high quality and exclusive brand, and obtain customers loyalty. However, Parira is no exception from the high competition of fashion industry. The fashion industry has always been known for its highly competitive environment due to its rapid growth and dynamic nature. Growing competitors and increasing usage of social media by business become a threat for Parira to achieve its marketing objectives as there are growing chances for Parira to be substituted by other competing brands.
Thus, this study aims to evaluate whether Parira Clay’s social media marketing has an impact towards its brand equity. Considering brand equity’s important role to business success, Parira Clay’s brand equity problems should be solved. Social media marketing acts as a potential force to determine Parira’s brand equity, especially with Parira Clay’s reliance on Instagram as its main marketing tool. By evaluating the impact of Parira Clay’s social media marketing on its brand equity, this study can identify whether Parira Clay’s social media marketing has effective and reliable use and functionalities to determine its brand equity.
2. Literature Review
2.1 Parira Clay
Parira Clay is an online-based polymer clay earrings business. It is as a local micro fashion enterprise, specialized in handcrafted polymer clay earrings. The business was founded on 25th February 2020 by a Bali artisan. As an online-based business, Parira Clay does its sales in online marketplaces (Tokopedia and Shopee) and it does its marketing activities in social media platform, which is Instagram. Its Instagram has 3.59% engagement rate as of April 2021 with audiences dominated by female (96.4%) in their 18-34 (77.1%). Parira Clay’s marketing objectives focus on its brand management, which are to gain awareness towards its brand, perceived and associated as high quality and exclusive brand, and obtain customers loyalty.
However, due to the high competitiveness of fashion industry, Parira Clay is faced with threats toward its brand-related marketing activities, as follow:
a. Brand awareness: Parira Clay is troubled in ensuring strong presence on Instagram as growing competitors cause a risk for Parira Clay to be drowned out by the competitors in search engine. Another thing is that its attempts to gain recognition from events referral are still not optimal due to the lack of audiences’ participation.
b. Brand associations and perceived quality: Some complains arise regarding customers dissatisfaction towards Parira Clay’s products, which becomes a threat for the brand association and perceived quality. Customers have the power of word-of-mouth and therefore have an ability to spread negative associations toward the brand utilizing communication functions that social media offers.
c. Brand loyalty: With the growing usage and functions of social media and the growing competition, consumers are exposed to more brands and choices that may be more relevant to their value and offer better deal to them. This situation is capable in disrupting purchase decision and threatens Parira Clay to be replaced by the consumers.
2.2 Fashion Industry
Fashion is an important part of Indonesian economy. Fashion is the industry with the biggest production growth in 2019 with yearly growth of 13.4% (Badan Pusat Statistik, 2019).
Globally, Indonesia is in the 9th rank for its revenue from fashion segment. Fashion industry has been growing at a rate of 4.78% yearly since 2011 and the market size has increased to 60% since 2011 to 2020 (Singh, 2018). However, fashion industry is known for being highly competitive due to its rapid growth. This growth is supported by online shopping trend, as 34%
consumers claim that their only spending increased in 2020 (Boice, 2021). Most of the spending is recorded to be dominated by the purchase of fashion goods as the number one goods to be purchased online with 59% share. Fashion online shopping provides consumers with convenience and blessing of variety under one roof. The competitiveness of fashion industry is also caused by fast fashion brands that possess fast products turnover and offer varieties, compelling the rest of the businesses in this industry to keep up.
2.3 Micro, Small and Medium Enterprises
Micro, Small and Medium Enterprises (MSMEs) are small-scaled businesses which are classified in the terms of their investment size (Jose, 2019). In Indonesia, MSMEs are defined as small businesses owned and managed by one person or small group of people with a certain amount of wealth and income based on UU No.20/2008. For developing countries, MSMEs play an important role to their macro economy by employing unskilled to skilled people, supporting the manufacturing sector, and even contributing to export. In Indonesia, MSMEs take up to 99.9% of total business units in Indonesia (Badan Pusat Statistik, 2020) and create employment for 97% of total workforces in Indonesia (Haryanti and Hidayah, 2018), which become proofs of its significant role to Indonesian macro economy. As digitalization era has increased social media usage, MSMEs have started to join social media. A survey conducted by World Bank and McKinsey claimed 42% of Indonesian MSMEs have joined social media platform and faced increase of sales to 26% (Kementrian Koperasi dan UKM, 2020).
2.4 Social Media Marketing
One of the most essential activity in e-commerce is social media marketing, especially considering the growing number of businesses in digital platforms and growing online purchase as consumers’ responses toward the situation. 170 million social media users are recorded in Indonesia, which are 61.8% of Indonesian total population (Kemp, 2021). Social media marketing is defined as facilitating customers interaction through digital media to encourage positive engagement towards brands to create commercial value (Chaffey, 2002). Instagram is one of the most reliable sales channels with its fitness of offerings (David, 2019), as Instagram can bring a lot of advantages with proper strategies, one of them is Instagram Marketing, which is a social media marketing by utilizing Instagram to promote business (Gaid, 2021). This study evaluates social media marketing using Smith’s (2007) Honeycomb model, the theory offers important forces that represent social media through its use and functionalities. It provides
resource to better understand how social media works through its use and functions and acts as a checklist of key strategic factors behind Parira Clay’s social media to identify the dimensions that effectively contribute to its social media marketing. Honeycomb model consists of seven dimensions that can be used flexibly according to one’s social media relevancy.
Figure 1: Honeycomb Model Source: Smith (2007)
Identity
Identity is the extent to which social media users disclose their identity to the public. Social media users tend to reveal their feelings and opinions through engagement that can be done consciously or unconsciously. Identity can be seen through profile and shared contents.
Presence
Presence is the extent to which social media users can recognize the availability of other users online. Presence dimension is a bridge that connect reality and the virtual realities. Frequency of update and consumers exposure toward the brand are indication of presence. Higher level of presence creates a more memorable impact with the customers.
Relationships
Relationships is the extent social media users are related or connected with one another.
Relatedness indicates associations between users such as following, customer-initiated contents, and referral. It can be seen from customers-initiated content and relevant connection.
Reputation
Reputation is the extent to which the users of social media can identify others’ social standing.
Reputation is earned through the value of shared contents, number of likes and followers, and thoughts expressed by consumers in comments section.
Group
Group represents the extent of group formation in social media platforms. However, this dimension is excluded from this study due to the lack of relevance since Parira Clay has no social media activities that involve group formation or membership.
Conversation
Conversation dimension represents the extent of communication between social media users.
After all, social media’s main purpose is to facilitate conversation among users. Conversation dimension can be seen through two-way communication, brand-related comments, and reply.
Sharing
Sharing is the extent of content trading in social media platforms. It is crucial since all social media activities require sharing. By sharing, business makes a statement, communicate values, and create addition to its image that may leave long-term impression (Kietzmann. Hermekens, McCarthy, and Sivestre, 2011). Consumers interest indicate the value of shared contents.
2.5 Brand Equity
Brand equity is assets and liabilities that the brand produced to give values to the business.
Brand equity that acts as an asset can bring competitive advantage that result in many benefits such as higher revenue from growing sales, lower price sensitivity, ease in expanding product lines, marketing productivity, etc. Brand equity is all about recognition and successful brands are those that drive recognition within emotional part of consumers (Aaker, 2021). Brand equity that is approached with the perspective that a brand is meaningless if it has no value to customer is referred as customer-based brand equity (CBBE) (Keller, 1993). The four dimensions of CBBE are used as the measures of brand equity.
Brand Awareness
Brand awareness represents the extent to which a brand is known and recognized by the consumers. It is important for both new brands to get recognition from consumers and well- known brands to be recalled by consumers. Brand awareness offers consumers an opportunity to familiarize themselves to the brand that may lead to liking and further consideration.
Brand Associations
Brand associations represent the feelings and thought people have when they see a brand based on their memory. Associations toward the brand assist consumers in generating and verifying information about the brand, position the brand, provide reason-of-purchase, and develop positive feelings (Aaker, 1991).
Perceived Quality
Perceived quality represents the extent to which the brand is known or expected to deliver good quality. It acts as differentiation tool that influences consumers to choose a certain brand compared to the other brands through its superiority. Perceived quality is based on consumers’
experience with the brand that may lead to satisfaction or dissatisfaction.
Brand loyalty
Brand loyalty represents the extent of customers loyalty toward the brand. It can be seen from repetitive purchasing behaviors and strength of brand preference compared to others. To achieve it, business must offer functional benefits and values compatibility with customers.
Brand loyalty may lead to defensive forces from competitive threats and generate more revenue
2.6 Conceptual Framework and Hypothesis
The conceptual framework and hypothesis generation of this study is in accordance with four step CBBE model (Keller, 2001) that explains the connection of social media marketing dimensions based on Honeycomb model (Smith, 2007) and customer-based brand equity (CBBE) (Aaker, 1991) dimensions. The utilization of the theories and conceptual framework
are adapted from previous studies by Babac (2011) and Tresna and Wijaya (2015). From Keller’s (2001) CBBE model, a conceptual framework as follow was developed:
Figure 2: Impact of Social Media on Brand Equity (ISMBE) Conceptual Framework Source: Babac (2001); Tresna and Wijaya (2015)
The first step of CBBE four step model (Keller, 2001) is to establish brand identity which objective is to increase the depth and breadth of customers awareness. The task to deliver identity of brand is through communicating and delivering the brand message. Therefore, Honeycomb model dimensions which are related to brand equity based on the first step is identity and conversation, while the CBBE dimension is represented by brand awareness.
The second step of the model is creating appropriate brand meaning. Brand meaning is how the brand is associated by the customers through its performance and imagery. Therefore, the CBBE dimension relevant to this step is brand associations. Sharing and presence of Honeycomb model can determine brand associations as what brand shares in social media represents the image that a brand wants to be associated with and become information materials for customers to shape their understanding of the brand. Repetitive and similar ideas exposed to customers through optimal presence function may leave stronger impact to one’s memory.
The third step is drawing positive brand response that can be brand judgment for its performance and brand feelings for its social value. Positive perceived quality is the expected brand response. Positive perceived quality can be improved through reputation building function of social media that establish one’s position in society (Kietzmann et al., 2011). Thus, the relevant dimensions of Honeycomb and CBBE which are reputation and perceived quality.
The fourth and final step is forming brand relationship. According to the theory, the objective of well-maintained brand relationship is to achieve intense and active loyalty of customers to the brand. Stronger relationship leads customers to feel more connected and increase their willingness to connect with the brand. Therefore, the Honeycomb model to represents this step is relationship, while brand loyalty is CBBE dimension to represent brand equity.
The Impact of Social Media on Brand Equity (ISMBE) framework describes the impact of specific social media dimensions of Honeycomb Model towards each dimension of Aaker’s (1991) customer-based brand equity (CBBE). Social media marketing represented by Smith’s (2007) Honeycomb model’s dimensions act as independent variable, while brand equity represented by Aaker’s (1991) customer-based brand equity acts as dependent variable. It is in
line with this study objective to evaluate the impact of social media marketing on brand equity of Parira Clay. To achieve this study objective, the following hypotheses were constructed:
H1a: There is a significant impact of Parira Clay’s identity on its brand awareness.
H1b: There is a significant impact of Parira Clay’s conversation on its brand awareness.
H1c: There is a simultaneous significant impact of Parira Clay’s identity and conversation on its brand awareness.
H2a: There is a significant impact of Parira Clay’s sharing on its brand associations.
H2b: There is a significant impact of Parira Clay’s presence on its brand associations.
H2c: There is a simultaneous significant impact of Parira Clay’s sharing and presence on its brand associations.
H3 : There is a significant impact of Parira Clay’s reputation on its perceived quality.
H4 : There is a significant impact of Parira Clay’s relationship on its brand loyalty.
3. Methodology
This study uses quantitative approach that collect and analyze numerical data that allow broader samples, less biased, and greater accuracy (Bhandari, 2020). The primary data of this research is collected through online survey distributed to the respondents through private message function of Instagram. The secondary data of this research is collected from online-based sources regarding supporting information and theories to be used as the basis of the study.
The population of the study is Parira Clay’s followers on Instagram, the total of its followers as of 27th May 2021 was 2,155. The population was chosen as respondents because the group has been exposed to Parira Clay’s marketing attempt on Instagram. The sample is chosen using judgmental sampling based on the researcher’s judgment of the respondents’ interaction with Parira Clay, with the criteria that they follow Parira Clay’s Instagram and have made a purchase with Parira Clay before. The sample size is based on Bullen (2013), where the minimum sample for meaningful result is 100 and the maximum is 10% of the population which is 216.
Online survey is used to measure social media marketing and brand equity variables. The questionnaires were given in 5-likert scale in which the respondents can choose their level of agreement to the given statements, with 1 as strongly disagree and 5 as strongly agree.
Table 1: Questionnaire Items
SOCIAL MEDIA MARKETING QUESTIONNAIRE ITEMS Identity
Parira Clay reveals its business information through its profile on Instagram ID1 Parira Clay Instagram’s shared contents keep updating information of its products ID2 I can easily recognize Parira Clay by its profile picture on its Instagram ID3 Presence
Whenever I login to my Instagram, I see Parira Clay’s content PR1
I often receive notification from Parira Clay PR2
The frequency of updates from Parira Clay is high PR3
Relationship
Customers often share contents related to Parira Clay on Instagram RL1 Parira Clay follows accounts in relevance with its business RL2 Parira Clay reposts contents from customers in its Instagram feeds or story RL3 Reputation
Parira Clay receives positive comments from customers RP1 Parira Clay has a big number of followers compared to other earring clay brands RP2 Parira Clay receives a lot of “likes” in its shared contents RP3 Conversation
Parira Clay replies to the comments from customers on its Instagram CV1 Parira Clay answers to my chat in its personal message CV2
I believe Parira Clay Instagram is interactive CV3
Sharing Parira Clay shares interesting photos on Instagram SH1
Parira Clay shares interesting videos on Instagram SH2
Parira Clay shares interesting hashtags on Instagram SH3
Parira Clay shares interesting caption on Instagram SH4
Parira Clay shares important links on Instagram that lead to its online stores SH5 BRAND EQUITY QUESTIONNAIRE ITEMS
Brand Awareness
I am aware of Parira Clay AW1
I can recognize Parira Clay among competing brands AW2
I know how Parira Clay’s logo looks like AW3
When I think of clay earrings, Parira Clay is the first brand I think of. AW4 When I want to purchase clay earrings, Parira Clay is the first brand I recall AW5
Brand Associations
I see Parira Clay as an exclusive accessories brand AS1
Parira Clay fulfils my needs in fashion AS2
Style that Parira Clay offers matches my fashion preference AS3 I believe Parira Clay is unique compared to the other clay earring brands AS4
I see Parira Clay as an eye-catching brand AS5
I can quickly recall the logo of Parira Clay AS6
Perceived Quality
Parira Clay is of good quality PQ1
I can expect superior performance from Parira Clay PQ2
Parira Clay is better compared to other brand(s) of similar products in appearance PQ3 The customer service quality of Parira Clay is high compared to other brands PQ4 Contents in Parira Clay’s Instagram are more unique compared to other brands PQ5 Events in Parira Clay’s Instagram are more unique compared to other brands PQ6 Brand
Loyalty
After using Parira Clay’s brand, I grew fond of it BL1
I will definitely buy Parira Clay’s product again BL2
I will still buy Parira Clay’s product even when the price is higher than others BL3 I will not buy from another brand when Parira Clay is available at the store BL4
After data collection, the data is statically processed to interpret and evaluate the data using SPSS. The study uses simple and multiple linear regression analysis to estimate the relationship between independent and dependent variables. The linear regression models tested in this study are: (1.) First multiple linear regression model with identity and conversation as independent variables and brand awareness as dependent variable; (2.) Second multiple linear regression model with sharing and presence as independent variables and brand associations as dependent variable; (3.) First simple linear regression model with reputation as independent variable and perceived quality as dependent variable; (4.) Second simple linear regression model with relationship as independent variable and brand loyalty as dependent variable.
The data analysis started with validity and reliability test as the main requirement for capable and feasible data. Then, continued with classical assumption test based on Ordinary Least Square (OLS) to minimize differences between independent and dependent variables. OLS is considered as Best Linear Unbiased Estimator (BLUE) (Wooldridge, 2013). The requirements need to be fulfilled in OLS are no multicollinearity, no autocorrelation, no heteroscedasticity, and normal distribution. Finally, hypothesis tests are done to test whether the hypotheses are acceptable or not. Adjusted R-Squared is tested to determine the goodness-of-fit. Then, F-test is conducted to estimate significant impact of independent variables to dependent variables.
Lastly, t-test is conducted to estimate individual impact of multiple linear regression models.
4. Data Analysis and Discussion
The data analyzed is generated from a total of 103 female respondents at the age of 18-34 years old (96.2%) and 25-34 years old (35%) who live mostly in Jakarta (64.1%). The respondents are mostly poor middle class (28.2%) and aspirant middle class (28.2%). Their preference and purchasing factors toward Parira Clay are its aesthetic (86.4%), products quality (77.7%), and
variety offered (72.8%). Many of the respondents are influenced by friends (43.7%) to interact with Parira Clay with incentive to gain information (78.6%) and entertainment (44.7%).
4.1 Validity and Reliability Test
Validity test was conducted with Corrected Item-Total Correlation test to assess accuracy of the measurement in reflecting the analyzed situation (Troy, 2021). The value of Corrected Item- Total Correlation as r calculated should be greater than r table for the measurement to be valid (Sujawerni, 2014). The value of r table is 0.1937, based on significance of 5% and degree of freedom of 101 (df= 103-2= 101). From the result of validity test, all social media marketing questionnaire items Corrected Item-Total Correlation have value ≥ 0.358 and brand equity questionnaire item Corrected Item-Total Correlation with value ≥ 0.468. The values of 0.358 and 0.468 ae greater than 0.1937, therefore the measurement is considered valid.
Then, reliability test was conducted to test the dependability and trustworthiness in accuration.
The reliability test was done with Guttman Split-Half Coefficient. The measurement is considered reliable when the coefficient is greater than or equal to 0.8 (Sarwono, 2015). The reliability test shows result of Guttman Split-Half Coefficients for social media marketing questionnaire items to be 0.843 and brand equity to be 0.821, meaning that all questionnaire items have Guttman Split-Half Coefficients more than 0.8, therefore deemed as reliable.
4.3 Classical Assumption Test
First, multicollinearity test by analyzing Tolerance and Variance Inflation Factor (VIF) is done to assure that the independent variables in multiple linear regression models to be independent from each other. The Tolerance should be ≥ 0.1 and VIF ≤ 10 to indicate no multicollinearity.
The result of multicollinearity test is seen in Table 2. The result shows that first multiple linear regression model with identity and conversation as independent variables have Tolerance of 0.659 and VIF of 1.517. The second multiple linear regression model with presence and sharing as independent variables have Tolerance of 0.887 and VIF of 1.127. All models have Tolerance more than 0.1 and VIF less than 10, meaning that there is no multicollinearity in the models.
Table 2: Multicollinearity Test Result with Tolerance and VIF
Model Independent Variable Tolerance Variance Inflation Factor (VIF) First Multiple Linear
Regression Model
Identity 0.659 1.517
Conversation 0.659 1.517
Second Multiple Linear Regression Model
Presence 0.887 1.127
Sharing 0.887 1.127
Second assumption test is autocorrelation test using Durbin-Watson. The value of Durbin- Watson (d) should be greater than its upper limit (dU) and less than 4-dU to confirm no autocorrelation (dU < d < 4-dU). The result of analysis is seen in Table 3. The values of dU and dL can be found in Durbin-Watson table with significance level of 5%. First multiple linear regression model has d value of 2.033 and second multiple linear regression model has d value of 1.813, both are greater than their dU of 1.7186 and less than their 4-dU of 2.2814, meaning that the first and second multiple linear regression models have no autocorrelation. First simple linear regression model has d value of 1.892 and second simple linear regression model has d value of 1.920, which are greater than dU of 1.6985 and less than 4-dU of 2.3015, meaning that the first and second simple linear regression models have no autocorrelation.
Table 3: Autocorrelation Test Result with Durbin-Watson
Model d dL dU 4-dL 4-dU
First Multiple Linear Regression Model 2.033 1.6396 1.7186 2.3604 2.2814 Second Multiple Linear Regression Model 1.813 1.6396 1.7186 2.3604 2.2814 First Simple Linear Regression Model 1.892 1.6593 1.6985 2.3407 2.3015 Second Simple Linear Regression Model 1.920 1.6593 1.6985 2.3407 2.3015
Third, heteroscedasticity test was conducted with Glejser to test to detect unequal variances within the regression models. According to Glejser, the significant value should be > 0.05 to indicate no occurrence of heteroscedasticity. The result is Table 4 that shows all significant to be greater than 0.05. Thus, there is no heteroscedasticity and constant variances are maintained.
Table 4: Heteroscedasticity Test Result with Glejser
Model Variable Significant
First Multiple Linear Regression Model Identity 0.794
Conversation 0.125
Second Multiple Linear Regression Model Presence 0.485
Sharing 0.288
First Simple Linear Regression Model Reputation 0.340
Second Simple Linear Regression Model Relationship 0.176
Fourth and last requirement of OLS is normality test. The test was conducted with Kolmogrov- Smirnov test. Kolmogrov-Smirnov Asymptotic significance 2-tailed should be >0.05 for the data to be deemed normally distributed. The result of normality test is featured in Table 5, in which all Kolmogrov-Smirnov Asymptotic significance 2-tailed have values more than 0.05 indicating that all regression models are normally distributed.
Table 5: Normality Test Result with Kolmogrov-Smirnov
Model Kolmogrov-Smirnov Asymptotic Significance 2-tailed
First Multiple Linear Regression Model 0.200
Second Multiple Linear Regression Model 0.079
First Simple Linear Regression Model 0.200
Second Simple Linear Regression Model 0.570
4.4 Hypothesis Test
The final step of data analysis is conducting hypothesis test to determine the acceptability of hypotheses. First, Adjusted R-Squared test is conducted to find out the goodness of fit as to what degree the dependent variables are explained by the dependent variables. R-Squared value of 10% is considered acceptable in most studies that involve human behaviors since human behaviours are difficult to predicts (Falk and Miller, 1992) (Van Tonder and Petzer, 2018).
The result of Adjusted R-Squared analysis is seen in Table 6, in which it shows that: (1.) The first multiple linear regression model has Adjusted R-Squared value of 0.25, meaning that 25%
variations in brand awareness can be explained by the variations in identity and conversation;
(2.) The second multiple linear regression model has Adjusted R-Squared value of 0.109, that indicates 10.9% variations in brand associations can be explained by the variations in sharing and presence; (3.) The first simple linear regression model has Adjusted R-Squared value of 0.257, thus 25.7% variations in perceived quality can be explained by the variations in reputation; (4.) The second simple linear regression model has Adjusted R-Squared value of 0.242, which means 24.2% variances in brand loyalty can be explained by the variations in relationship. All adjusted R-Squared values in the linear regression models are greater than 0.10, therefore all models are deemed as adequate in their goodness-of-fit.
Table 6: Adjusted R-Squared Result
Model R-Squared Adjusted R-Squared
First Multiple Linear Regression Model 0.265 0.250
Second Multiple Linear Regression Model 0.127 0.109
First Simple Linear Regression Model 0.265 0.257
Second Simple Linear Regression Model 0.249 0.242
Next, F-test was done to identify whether independent variables have significant impact on the dependent variables in linear regression models. The significant value < 0.05 or F calculated >
F table means that independent variables have a significant impact on dependent variables. For the multiple linear regression models, the F table value is 3.08671 (F table = F (k; n-k) = F (2;
101)) and simple linear regression models have F table value of 3.934253 (F table = F (k; n-k)
= F (1; 102)). The result of F-test analysis is features in Table 7.
Table 7: F-test Result
Model F Sig.
First Multiple Linear Regression Model 18.025 0.001
Second Multiple Linear Regression Model 7.242 0.001
First Simple Linear Regression Model 36.316 0.001
Second Simple Linear Regression Model 33.518 0.001
The first multiple linear regression model has F calculated of 18.025 which is more than 3.08571 and significant value of 0.001 which is less than 0.05. That means H1c which states
“there is a simultaneous significant impact of Parira Clay’s identity and conversation on its brand awareness” is accepted. The second multiple linear regression has F calculated of 7.242 which is greater than 3.08571 and significant value of 0.001 which is less than 0.05. That means H2c which states “there is a simultaneous significant impact of Parira Clay’s sharing and presence on its brand associations” is accepted.
The first simple linear regression has F calculated of 36.316 which is greater than 3.934 and significant value of 0.001 which is less than 0.05. That means H3 which states “there is a significant impact of Parira Clay’s reputation on its perceived quality” is accepted. The second simple linear regression has F calculated of 33.518 which is greater than 3.934 and significant value of 0.001 which is less than 0.05. That means H4 which states “there is a significant impact of Parira Clay’s relationship on its brand loyalty” is accepted.
Finally, t-test was conducted to analyze the individual impact of independent variables. The significance value < 0.05 or t calculated > t table indicates that each independent variable has individual significant impact on dependent variable. The t table value for multiple regression model is 1.983972 (t table = t (a/2; n-k-1) = t (0.005/2; 103-2-1).
Identity in the first multiple linear regression model has t calculated of 1.532 which is < 1.98 and significant value of 0.129 which is > 0.05, meaning that identity has no significant impact on brand awareness. When this dimension is used individually without the existence of conversation dimension, identity dimension is unable to impact brand awareness. Therefore, H1a which states “there is a significant impact of identity on its brand awareness” is rejected.
Conversation on the other hand has significant impact on brand awareness even when used individually, without the existence of identity dimension. Conversation has t calculated of 3.820 which is > 1.98 and significant value of 0.001 which is < 0.05. Thus, H1b that states
“there is a significant impact of conversation on its brand awareness” is accepted.
Sharing in the second multiple linear regression model has t calculated of 2.347 which is > 1.98 and significant value of 0.021 which is < 0.05, indicating that H2a which states “there is a significant impact of sharing on its brand associations” is accepted. Presence has t calculated of 2.032 which is > 1.98 and significant value of 0.045 which is < 0.05, indicating that H2b
which states “there is a significant impact of presence on its brand associations” is accepted.
Table 8: T-test Result
Variables Unstandardized Coefficients Standardized Coefficients t Sig.
Identity 0.304 0.162 1.532 0.129
Conversation 0.649 0.403 3.820 0.001
Sharing 0.248 0.202 2.347 0.021
Presence 0.279 0.233 2.032 0.045
5. Discussion and Conclusion
The result of this study shows that Parira Clay’s social media marketing on Instagram has an impact towards its brand equity in four major ways: (1.) Identity and conversation as social media use and functionalities simultaneously impact brand awareness, conversation has individual impact on brand awareness, but identity must be used together with conversation to has an impact; (2.) Sharing and presence as social media use and functionalities simultaneously and individually impact brand associations; (3.) Reputation impacts perceived quality; and (4.) Relationship impacts brand loyalty. Based on the analysis, H1b, H1c, H2a, H2b, H2c, H3, and H4 are accepted, but H1a regarding individual impact of identity on brand awareness is rejected.
The findings are in accordance with previous studies by Babac (2011) and Tresna and Wijaya (2015) that social media marketing has an impact on brand equity of a brand. This research contributes to strengthen the qualification and industry scope of The Impact of Social Media on Brand Equity (ISMBE). However, this study shows contradiction of result with previous study that found each dimension of Honeycomb model has individual impact on certain dimension of brand equity, this study found that individual impact of identity is not identified on brand awareness. Thus, this study provides another insight of how the relationship between social media marketing and brand equity works to be further considered.
This study indicates that social media marketing has use and functionalities that bestows it an important role in determining Parira Clay’s brand equity. It suggests Parira Clay to put social media marketing into consideration in achieving strong and positive brand equity. The growing usage of social media for business purpose surely has its impact of Parira Clay’s brand, it needs to be reminded that marketing activities that Parira Clay does on Instagram have capabilities to determine and reflect its brand to shape consumers’ idea about Parira Clay. In implementing its social media marketing, Parira Clay is recommended: (1.) To be mindful in maintaining conversation to effectively deliver brand messages and benefit from its identity disclosure to gain higher recognition; (2.) To have notable associations of brand, considering audiences preference and value is important in content planning that Parira Clay share and making use of various functions of Instagram can be done to expose consumers more to the brand-generated contents; (3.) To see Instagram as a determinant of its social standing, maintaining positive image and responses to manage its reputation can result in greater perceived quality of its offerings; (4.) to intensify its connection with relevant accounts and customers to generate more attachment from customers and generates customers loyalty.
This study is also faced with several limitation. There are many theories that offer different
of them and only utilizes Smith’s (2007) Honeycomb model and Aaker’s (1991) CBBE, it is need to be reminded that future research is not limited to explore other theories relevant to the topic. Honeycomb model is also recommended to use, especially when seeking for flexibility since not all dimensions must be used when they are irrelevant. This study doesn’t guarantee Parira Clay to be sufficient to represent all fashion MSMEs in Indonesia, considering the diversity of fashion industry. Future research can do comparison of different brands of fashion MSMEs to gain greater insight and recommended to use ISMBE model to analyze different industry in doing so. Since this study has scope limited to Instagram, future research can expand the study using different platforms of social media or even do comparison of different platforms. Finally, using mixed method approach study is recommended to expand insight and findings credibility of the study, and choices of methods to be applied.
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