Is traditional media communication less effective than social media and personal selling for brand building? Empirical evidence from a cosmetics brand in Indonesia

Abstract

This study empirically examines the effects of four types of media communication (traditional media advertising, firm-created social media, user-generated social media, and personal selling) on brand attitude. The effect of brand attitude on rerepurchase intention was also tested. The research applied a survey method to collect the data. For this purpose, judgmental sampling was used and 302 female respondents who use cosmetic products of a certain brand were gathered. Then, the data were analyzed using structural equation modeling. The results show that firm-created social media communication, user-generated social media communication, and personal selling have positive effects on brand attitude. However, traditional media communication does not influence brand attitude significantly. This study also corroborates the effect of brand attitude on repurchase intention. The research complements the previous studies that investigate only several media by examining comprehensively four types of media communication representing two poles: mass media (traditional advertising) versus personalized media (firm-created social media, user-generated social media, and personal selling); and non-interactive (traditional advertising) versus interactive media (firm-created social media, user-generated social media, and personal selling). The findings also provide guidelines for companies when planning and deciding the media communication for their promotion. These guidelines enable companies to target their communication activities more effectively.

Keywords:

• advertising
• marketing communication
• digital marketing
• social media
• brand attitude

PUBLIC INTEREST STATEMENT

Communication refers to the mode through which people or companies convey messages or ideas. When sending messages, communication requires a specific media to reach the target audience. Hence, companies have used various communication media to persuade consumers. In the past, many companies have used mass and one-way communication media such as television, radio, and newspaper. However, currently the massive use of social media among individuals has also encouraged companies to employ this interactive media. This study attempts to examine the effects of four types of communication media (traditional media advertising, firm-created social media, user-generated social media, and personal selling) on brand attitude. This study focuses on how each media platform affects customers’ evaluation of a brand. The media types investigated in the current research represent two poles of interactivity: non-interactive versus interactive media. This study uses the research context of a cosmetic brand and female customers in Indonesia. The results of this study show that interactive media have greater effects on customers than that of non-interactive media. The findings also provide direction for business practitioners in choosing the types of media effectively in communicating with their customers.

1. Introduction

The advancement of technology has changed how people interact with brands and companies and has become a topic of concern for organizations’ strategic decision making (Pan & Truong, 2018), including strategic communication. The implication is that business activities are transforming into a trend from previously traditional-based activities to all-digital interaction. Many companies have started to shift some portions of their communication activities from traditional media to digital media. As reported by Statista (Navarro, 2023), the spending of global newspaper advertising has been declining since 2007 from the value of 113 billion U.S. dollars to only 26.6 billion dollars, as predicted for 2024. On the other hand, the value of digital advertising spending worldwide rose from 521.02 billion U.S. dollars in 2021 to the projected value of 876 billion dollars by 2026 (Statista Research Department, 2023). Traditional media communication includes newspaper, magazines, television and radio broadcasts (Andrews & Shimp, 2018).

One of the industries particularly affected by changes in communication media is the cosmetics industry. In the past, consumer behavior in using cosmetics products was driven mainly by mass advertising by featuring celebrities in television advertising, radio broadcast, or print media. However, the use of social media for communication regarding cosmetics products has become more popular, as it can adapt to individual users’ needs. The application of social media as a form of communication can initiate new economic opportunities through the collaboration of producers with users, including a new profession of social media influencer (De Veirman et al., 2017). That is why it is not surprising that, currently, many influencers on social media applications such as TikTok, YouTube, or Instagram post content related to the use of cosmetics. Although this is not the only driving factor, this condition also helps encourage consumers to use cosmetic products. According to Grand View Research (2023), the global market size of cosmetics products reached USD 262.21 billion in 2022, with an expected compound annual growth rate of 4.2% from 2023 to 2030.

The majority of consumers around the world are addicted to using social media, thereby presenting an opportunity for brand owners to communicate their brands to consumers. Many brands, including in the cosmetics industry, attempt to use social media and keep or drop their conventional media activities such as traditional advertising.

Actually, the usage of communication media was intended to create awareness, positive feelings, understanding, association, and purchase behavior among customers (Moriarty et al., 2019). Therefore, companies cannot neglect customers as their target audience. Successful communication depends on customers’ acceptance of communication. Hence, the media selection becomes a crucial decision, whether companies use traditional advertising, personal selling, digital communication, or a combination of methods. Therefore, companies need to choose media effectively.

The competing use of media between contemporary digital marketing and traditional communication methods charges companies with the task of choosing effective media in communicating with their target audience. Every form of media has unique characteristics. For example, non-interactive traditional media such as television, radio advertising, or printed media only support one-way communication from companies to customers. While traditional media do not allow conversation between companies and customers, this is not the case for digital media or social media, which support multiple conversations not only between companies and customers, but also among customers.

Communication media outlets can also be differentiated by the size and characteristics of receivers. Mass media send messages to large, diverse audiences. In contrast, personal selling and social media deliver messages based on targeted persons. Previously, communication has been in the companies’ control. Only big brands had the budget to run mass media advertising, using traditional paid media such as television, radio, magazines, and newspaper. Today, consumers have increased control over the messages they receive about brands in social media, known as earned media (Moriarty et al., 2019). As stated by Pöyry et al. (2022), the informational persuasion in digital media can be shared easily and anonymously.

From a budget perspective, an empirical study showed that the use of digital marketing through social media is only $2.5 CPM (cost per thousand impressions) compared to traditional marketing TV at $28 CPM, newspaper at $16 CPM, radio at $10 CPM, and billboards at $5 CPM (Lyfe Marketing, 2023). Thus, social media has a relative competitive advantage over other communication channels (Jin et al., 2019).

For companies, the existence of various media offers opportunities to strategically communicate with customers. Strategic communication is a vital aspect for companies, even for start-ups, to build their brands (Chaudhri et al., 2022). Hence, at the beginning, companies should make strategic decisions regarding the right media to communicate with their customers. When companies communicate frequently about their brands with their customers, they build positive perceptions among their customers toward the brands. Therefore, companies must investigate and measure the effectiveness of the communication media used.

Previous studies have been conducted about the effects of communication media on brand attitude. For example, Abzari et al. (2014) and Tümer et al. (2019) investigated the effects of traditional media and social media on brand attitude or brand trust. Meanwhile, Bruhn et al. (2012) and Morra et al. (2018) focused on traditional media, user-generated social media, and firm-created social media as antecedent variables in their research.

However, previous studies have produced limited results. Prior research has not included personal selling as a type of communication that needs further exploration. For certain products, personal selling is crucial, as some customers have less information and still hope to consult directly. For example, many customers still rely on the information provided by personal selling when buying cosmetic products. Hence, this study attempts to fill this gap by incorporating the effect of personal selling on brand attitude.

The research questions (RQ) in this study can be categorized into two main questions.

RQ1:

How do the four types of communication media (traditional media advertising, firm-created social media, user-generated social media, and personal selling) affect brand attitudes?

RQ2:

What is the effect of brand attitude on repurchase intention?

These research questions are crucial for the future of brand communication. As stated by Besley (2020), one of the big problems in communication is to examine the communication effectiveness, such as the types of channels used. To achieve the research objectives, this study used two main theories as a base of explanations: Stimulus-Organism-Response (S-O-R) Theory (Mehrabian & Russell, 1974), and Selective Exposure Theory (SET) (Klapper, 1960; Knobloch-Westerwick, 2015). S-O-R theory was used to explain the effects of four types of media (as Stimulus) on brand attitude (as Organism) and sequentially on purchase intention (as Response). SET elucidates the judgment regarding whether certain media have effects or not based on their exposure to customers.

The research context used in this study was a cosmetic brand marketed in Indonesia. Indonesia has experienced increasing demand and a growing market for cosmetics products, and therefore, it offers significant opportunity for cosmetic brands to influence consumers using communication media. In addition, as the fourth most populous country in the world, Indonesia has approximately 191.4 million active social media users and has seen a recent increase in brands utilizing social media as a complementary element to their marketing communication (Nurhayati-Wolff, 2023). Therefore, this context is very suitable for this study. This study contributes to the existing literature on the communication effects of media that have not previously been covered comprehensively. This study also offers guidance for brand owners in selecting and managing media channels to promote their products.

2. Literature review

2.1. Stimulus-organism-response theory and selective exposure theory

Living things, including humans, can respond to any changing situation in their habitat. The variety of response forms is highly dependent on the individual process when evaluating the changes that occur. This understanding drove Mehrabian and Russell (1974) to develop the idea of S-O-R theory. The theory postulates that emotions stimulated by environmental stimuli strongly influence behavioural responses. The spectrum of individual responses depends on the individual assessment process of these stimuli, under which individuals assess a stimulus based on their knowledge and experience. This theory was initially developed to satisfy psychological interest, but its application is widespread in other areas, including business and management. For example, Ming et al. (2021) adopted S-O-R theory to study the relationship between live streaming commerce and impulse buying. Goyal et al. (2022) examined the effects of external and internal stimuli on perceived value and trust based on S-O-R theory. Istijanto et al. (2023) applied S-O-R theory to test the effects of new product attributes on purchase intention.

An example of stimulus component is communication. Communication is an essential element for social interaction in society, because it facilitates social interaction. The communication process begins with the sender initiating a message, producing it, reproducing it, or simply conveying information. Then the message is delivered to the receivers through a media or tool. In the delivery process, the potential for interference or noise can appear in the media, affecting the recipients’ interpretation of the message. The greater the disturbance, the more asymmetric information will affect decision-making (Auer, 2017).

On the other side, the receivers can select which types of messages to which they are exposed. According to SET (Klapper, 1960; Knobloch-Westerwick, 2015), “people are more likely to expose themselves to media content that is congruent and to avoid media content that is incongruent with their attitudes and behaviour” (Van Oosten et al., 2015, p. 1081). In the business context, this means that consumers select messages from brands’ communication media that are in line with their interests or attitudes. If the messages are not relevant personally to them or are incongruent with their attitudes, consumers will impede the media contents. For example, customers may change the television channel or skip advertising on social media when they see content irrelevant to them.

Communication conditions are changing. In the past, most customers strongly depended on traditional mass media, such as television or radio, and therefore they were not as free to select exposure. Thank to social media, modern customers have extensive opportunities to select their exposures. This can happen because digital media and social media offer customers the authority to visit and choose their exposures. Thus, the selection of communication media can affect the effectiveness of a message. This study attempts to expand SET on the media types that have communication effects on customers.

2.2. Communication to consumers

Communication media from companies to their customers has various types. One of them is advertising. Advertising is “a paid, mediated form of communication from an identifiable source, designed to persuade the receiver to take some action, now or in the future” (Andrews & Shimp, 2018, p. 549). Formerly, the presence of television, newspaper, and radio allowed individuals and corporations to broadcast messages. Companies used these traditional mass media platforms to promote their products and services.

Companies can also employ personal communication, which refers to messages delivered by salespeople. Personal selling is “a paid, person-to-person communication in which a seller determines the needs and wants of prospective buyers and attempts to persuade these buyers to purchase the company’s products or services” (Andrews & Shimp, 2018, p. 555). With salespeople, prospective buyers will feel efficient in making purchases because of the availability of the information they need (Crittenden et al., 2014). Rehman et al. (2017) state that salespeople can advocate for the distribution of information to the requirements of potential customers without being constrained by an information standard. In addition, personal communication can identify the needs of prospective buyers so that information can be effectively conveyed more precisely to reduce asymmetric information (Wang et al., 2012).

In the meantime, the availability of internet technology has fundamentally altered how people communicate (Hermsen et al., 2016). Thomas (2017) emphasized the interactive and participatory aspects of contemporary communication as distinctive of significant interpersonal communication in the digital age. Technological adoption in the media area has increased users’ ability to reach consumers. This adoption has also been shown to change the interaction pattern of people, which is increasingly departing from the ancient interaction pattern (De Veirman et al., 2017). The reach dimensions are becoming more comprehensive and borderless and include increased societal involvement.

Hence, the emergence of social media has mainly changed how people and organizations communicate with each other. Social media is “web-based and mobile technology used to turn communication into interactive dialogue” (Andrews & Shimp, 2018, p. 557). Social media facilitates personal and interactive conversations between multiple subjects such as between one company and its customers, between one customer and many companies, and among the customers themselves. Hence, customers have more control with social media than with traditional media. The interactive characteristic of social media becomes a strong advantage of this media, and this study further explores this characteristic.

2.3. Effects communication on brand attitude and repurchase intention

In the business context, one of the main objectives of communication is to build a strong brand. According to the International Organization for Standardization, as cited by the American Marketing Association (2023), brand “is an intangible asset that is intended to create distinctive images and associations in the minds of stakeholders, thereby generating economic benefit/values”. Hence, brands are considered essential factors that can motivate customers to purchase (Kumar & Amresh, 2017).

Based on this idea, companies attempt to build their brand as a strategy that can help them reach their business objectives. Companies plan to marketing communication objectives and run their communication activities to influence customers’ behaviour toward their brands (Andrews & Shimp, 2018). In this case, consumer attitude (Ajzen, 1985) plays an important role. Attitude is an evaluative statement of people toward the object they observe (Park et al., 2021), such as a brand. Grashuis (2018) stresses the value of a company’s brand in standing out from the competition and ensuring financial success.

Brand attitude refers to consumer evaluations of a brand’s performance based on the criteria formed by the relationship between emotions and cognitive beliefs (Lee et al., 2017; Pagla & Brennan, 2014). Brand attitude can be measured by evaluating the brand, which represents cognitive and affective aspects (Kumar & Amresh, 2017). Moreover, the role of brand attitude can serve as a strong predictor of buying behaviour (Lee et al., 2017). Ramesh et al. (2018) found that brand attitudes correspond to customer purchasing patterns. Therefore, brands act as vital evaluation instruments in purchasing and distinguish brand attitude as the most critical factor in predicting buying behaviour.

The concept of behavioural intention is widely used to predict behaviour, especially its relationship with the purchase of a product (Kumar & Amresh, 2017; Paesbrugghe et al., 2018). Ali et al. (2020), Morra et al. (2018), and Toldos-Romero et al. (2015) employ purchasing intention to justify brand purchase behaviour. Since brand affects consumer purchase behaviour, brand has become one of the dominant topics discussed in the marketing area. Hence, previous studies have investigated the factors that contribute to a strong brand, including communication media. The theories of media effects have attempted to reveal the conditions under which communication media influence people or customers (Valkenburg et al., 2016). This study tries to address the effects of communication media on brand attitude and repurchase intention for a cosmetic brand.

2.4. Hypotheses development

Dwivedi and Mcdonald (2020) determined that traditional media still has a crucial influence on sales results. In their study, media is irreplaceable, even though it is motivated by the presence of more modern communication media. Ren et al. (2022) shared a similar viewpoint that emphasised the importance of conventional media in shaping or influencing public opinion in the face of the widespread usage of social media for information dissemination. Moreover, Morra et al. (2018) assert that the presence of social media does not replace the contribution of traditional media to brand awareness.

Tümer et al. (2019) states that traditional media still contributes to message delivery to consumers amid the emergence of more modern media (social media). Although social media is widely believed to dominate consumer communication, traditional media continues to play a significant role in many areas (Husain et al., 2022; Morra et al., 2018). Moriarty et al. (2019) asserted that advertising has an important role to build a brand image. Based on these notions, the first hypothesis is proposed as follows:

H1:

Traditional media as a non-interactive communication platform has a positive effect on brand attitude.

Social media is transforming into a communication instrument beyond traditional media. In addition to being embedded into a compact, portable device, social features are more attractive in terms of usage, user interface, and features. Schivinski and Dabrowski (2016) and Morra et al. (2018) divide messages on social media into communication from fully controlled companies (firm-created social media) and messages generated by users through social networks (user-generated social media). Although they have different roles, both types of messaging contribute significantly to changing people’s perceptions and behaviour (Jin et al., 2019). Systematically, De Veirman et al. (2017) reveal that social media presents an important message in influencing customers on certain brands. From these arguments, the following hypotheses are put forward:

H2:

Firm-created social media as interactive media has a positive effect on brand attitude.

H3:

User-generated social media as interactive media has a positive effect on brand attitude.

Rehman et al. (2017 suggest that the key benefit of personal communication is its capacity to deliver a flexible or tailored message in response to the requirements of potential customers. In addition, due to its nature, personal communication has emotional advantages, since potential customers feel prioritized in a face-to-face setting and are more focused on providing consultations rather than being oriented toward sales performance (Paesbrugghe et al., 2018). Using a more humane approach, individuals are often more easily influenced. This influence is obtained since personal communication meets potential customers’ needs. Persuasively, sellers try to convey their message in the buying process of prospective consumers to influence purchasing decisions or at least to become a product reference for potential consumers. The hypothesis is as follows:

H4:

Personal selling has a positive effect on brand attitude.

Ali et al. (2020) and Toldos-Romero et al. (2015) assert that purchase intention can be used to measure a brand’s attitude. Attitude is a result of evaluation of performance through functional and emotional attributes. Therefore, when the evaluation of a product or brand is positive, the intention toward the purchase follows the results of evaluation. Kumar and Amresh (2017) and Lee et al. (2017) empirically test how attitudes toward a brand can justify the purchase intention of a product. Based on these ideas, the following hypothesis is formed:

H5:

Brand attitude has a positive effect on repurchase intention.

Based on the hypotheses, the conceptual model can be described in Figure 1.

Figure 1. Research model.

3. Methodology

3.1. Data collection and sampling method

In line with the quantitative research method, this study employed a survey. The research context was a cosmetic product with a global brand (“M”) marketed in Indonesia. This brand was chosen because it used various media including traditional advertising, social media, and personal selling in its communication activities. Therefore, the brand was suitable for the objectives of this study.

The sampling method applied was judgmental sampling (Malhotra, 2020). The method was beneficial in selecting the target respondents, i.e., females who had bought cosmetics products (brand of “M”) within the last three months. The study sought female respondents, because women are the main customers of cosmetics products (Kanwar & Huang, 2022). Respondents were selected from Jakarta, the capital city of Indonesia. This metropolitan area has a significant number of customers (mostly young females) who use cosmetics. In public places such as universities and shopping malls, respondents were approached and asked whether they bought the targeted cosmetics product (brand of “M”) within the last three months. Only respondents who met the criteria are chosen to participate in this study. If they agreed to participate, they were given a questionnaire. They answered the questionnaire, a process of 10–12 minutes. A special souvenir was given to respondents who answered the questionnaire completely. Regarding sample size, Hair et al. (2014, p. 574) suggest that models containing six variables need at least 150 respondents. This study employed 302 respondents, which is more than suggested.

3.2. Constructs and instruments

This study used six constructs with three measuring items for each construct. Therefore, the questionnaire had 18 items. The items were adapted from previous studies. All of the measuring items were scored on a 5-point Likert scale with anchors ranging from 1 (strongly disagree) to 5 (strongly agree).

3.3. Analysis method

This study applied the Structural Equation Modeling (SEM) technique. We employed two packages of software: SPSS version 26 (Field, 2017) and LISREL version 8.8 (Jöreskog & Sörbom, 1996). The SEM analysis enables us to simultaneously examine the measurements and the relationships between the variables of interest (Mayfield et al., 2008). Following Anderson and Gerbing (1988), the main analysis of this research comprised two stages: (1) validating the measurement model and (2) testing the structural model.

4. Data analysis

4.1. Respondent profiles

This survey had 309 respondents. However, seven responses were invalid, resulting in 302 responses of useable data. In Indonesia, where this research was carried out, the majority of cosmetics customers are females. Therefore, 100% of the respondents are female, with most of them (78.1%) belonging in the age group between 20–24 years old. This age group is considered the most likely to use various communication media, including social media. In addition, the majority of them are significant drivers of the cosmetics market (Statista Research Department, 2023). All respondents live in Jakarta, with a majority (85.8%) buying cosmetic products 1–2 times per month. The brand of “M” is the context in this study, as explained previously. Table 1 presents the detailed characteristics of the respondents.

Table 1. Sample characteristics

Demographic characteristics	Category	Frequency	%
Gender	Female	302	100.0
Age group	Below 20 years old	57	18.9
	20–24 years old	236	78.1
	25 years old and more	9	3.0
Occupation	Student	267	88.4
	Employee	11	3.6
	Business owner	10	3.3
	Others	14	4.7
Residential city	Jakarta	302	100.0
Buying frequency	1–2 times per month	259	85.8
	3–4 times per month	26	8.6
	More than 5 times	17	5.6

4.2. Validity, reliability, and measurement model

The measurement model was evaluated using an exploratory factor analysis (EFA) and a confirmatory factor analysis (CFA). This research used convergent validity (meaning whether the measuring items can reflect their corresponding construct effectively) and discriminant validity (whether the constructs are statistically different) to test construct validity. Convergent validity was examined using average variance extracted (AVE) and factor loadings (Hair et al., 2014, p. 618). All of the AVE values in this study were higher than 0.5, ranging from 0.6432 to 0.7939, suggesting that the scale has good convergent validity (Hair et al., 2014). Furthermore, the values of factor loading for each item of the related constructs were also greater than 0.5, ranging from 0.609 to 0.909 (KMO = 0.973, Bartlett's test of sphericity 3.990.390, sig < 0.01), indicating acceptable validity (Hair et al., 2014, p. 115).

The next step was to compare the square root of AVE and factor correlation coefficients to examine the discriminant validity. The discriminant validity is considered to be good if the square root of AVE for each construct exceeds the correlation between any pair of constructs (Fornell & Larcker, 1981). The results showed that the square root of AVE for each factor was larger than its correlation coefficients with other factors. Hence, the results fulfill the discriminant validity criteria.

We then tested the construct reliability by measuring composite reliability (CR) and Cronbach’s alpha factors. The results indicate that the composite reliability (CR) of each factor ranges from 0.8433 to 0.9199 or above the recommended value of 0.7 (Hair et al., 2014, p. 605), and this indicates an acceptable construct reliability. In addition, all of the values of Cronbach’s alpha (from 0.837 to 0.919) exceed 0.7, also indicating good reliability (Nunnally, 1978). In summary, the results present that the values of validity and reliability measurements for all factors in this study are acceptable. Tables 2 and 3 exhibit the detailed values of the measurements, including the mean and the standard deviation of each construct. The results of the data analysis are discussed in the next section.

Table 2. Convergent validity and reliability measurement

Constructs and items	Reference	Factor loadings
Traditional media communication (TMC) Cronbach’s alpha = 0.871, CR = 0.873, AVE = 0.701
I am satisfied with the traditional media campaigns of [brand], i.e. radio, TV, print advertisements (TMC1) The level of the traditional media campaigns of [brand] (i.e. radio, TV, print advertisements) meets my expectations (TMC2) Compared with the very good traditional media campaigns (i.e. radio, TV, print advertisements) of other brands, the traditional media campaigns of [brand] perform well (TMC3)	Tsiros et al. (2004), Bruhn et al. (2012), Morra et al. (2018)	0.834 0.858 0.826
Firm-created social media communication (FSMC) Cronbach’s alpha = 0.882, CR = 0.884, AVE = 0.722
I am satisfied with the company’s social media communications for [brand] (FSMC1) The level of the company’s social media communications for [brand] meets my expectations (FSMC2) This company’s social media communications for [brand] perform well, when compared with the social media communications of other companies (FSMC3)	Tsiros et al. (2004), Bruhn et al. (2012), Morra et al. (2018)	0.742 0.772 0.858
User-generated social media communication (USMC) Cronbach’s alpha = 0.910, CR = 0.915, AVE = 0.782
I am satisfied with the content generated on social media sites by other users about [brand] (USMC1) The level of the content generated on social media sites by other users about [brand] meets my expectations (USMC2) The content generated on social media sites by other users about [brand] performs well, when compared with other brands (USMC3)	Tsiros et al. (2004), Bruhn et al. (2012), Morra et al. (2018)	0.851 0.796 0.857
Personal selling communication (PSC) Cronbach’s alpha = 0.919, CR = 0.919, AVE = 0.793
I am satisfied with the company’s personal selling communications (i.e. interaction with sales promotion persons) given for [brand] (PSC1) The level of the company’s personal selling communications (i.e. interaction with sales promotion persons) for [brand] meets my expectations (PSC2) This company’s personal selling communications (i.e. interaction with sales promotion persons) for [brand] perform well, when compared with the social media communications of other companies (PSC3)	Modified from items used in FSMC	0.906 0.909 0.890
Brand attitude (BA) Cronbach’s alpha = 0.837, CR = 0.843, AVE = 0.643
I have a pleasant idea of [brand] (BA1) [Brand] has a good reputation (BA2) I associate positive characteristics with [brand] (BA3)	Bruhn et al. (2012)	0.761 0.765 0.609
Repurchase intention (PI) Cronbach’s alpha = 0.871, CR = 0.871, AVE = 0.695
It is possible that I will rebuy [brand] in the future (PI1) I will seriously consider repurchasing [brand] (PI2) It is highly likely that I will rebuy [brand] (PI3)	Modified from Grewal et al. (1998), Bruhn et al. (2012)	0.750 0.823 0.815

Table 3. Mean, SD, construct correlations, and discriminant validity

Construct	Mean	Standard Deviation	TMC	FSMC	USMC	PSC	BA	PI
TMC	3.5695	0.8441	0.837
FSMC	3.7826	0.8116	0.486	0.850
USMC	3.8311	0.8342	0.470	0.573	0.884
PSC	3.5342	0.8699	0.251	0.323	0.244	0.891
BA	3.9547	0.6941	0.344	0.532	0.454	0.431	0.802
PI	3.7528	0.8164	0.389	0.481	0.490	0.250	0.703	0.834

Note: diagonal values (bold) display the square root of AVE

4.3. Structural model

After successfully assessing the measurement model, the next step was to evaluate the structural model. The maximum likelihood estimation method (95% significance level) was applied to assess the structural model. The goodness of the model fit was evaluated by using the main indices (Bentler & Dudgeon, 1996; Hair et al., 2014; Hu & Bentler, 1999); i.e., χ2/df (Cmin or the normed chi-square should be less than 5), Root Mean Square Error of Approximation (RMSEA; should be below 0.08), Adjusted Goodness of Fit Index (AGFI; should be more than 0.80), Normed Fit Index (NFI; should be more than 0.90), Comparative Fit Index (CFI; should be more than 0.90), and Standardized Root Mean Square Residual (SRMR; should be less than 0.08). The results indicated a good fit with χ2/df = 2.53, RMSEA = 0.07, AGFI = 0.86, NFI = 0.96, CFI = 0.97, and SRMR = 0.05. In other words, all values fulfilled the prerequisite indicators as a good fit.

After demonstrating the good fit of the model, the authors carried out hypotheses testing to examine the effects of each communication media on brand attitude. The final test was to assess the effect of brand attitude on repurchase intention. For this purpose, the authors used the values of standardized coefficient estimates (β), t-test, and p-value gained from LISREL output.

The findings revealed that traditional media communication (β = 0.02, p > 0.05) did not influence brand attitude significantly. This indicated that H1 is not supported by data. Next, the results showed the significantly positive effect of firm-created social media content (β = 0.38, p < 0.05), user-generated social media content (β = 0.23, p < 0.05), and personal selling (β = 0.23, p < 0.05) on brand attitude. Therefore, H2, H3, and H4 are supported. Finally, brand attitude also has a positive effect (β = 0.83, p < 0.05) on repurchase intention. Therefore, H5 is supported by the data. Detailed information of hypotheses testing is presented in Table 4 and Figure 2.

Figure 2. LISREL output.

Table 4. Results of Standardized estimates of the structural model

Hypotheses	Path	Standardized Estimate (β)	p-value	Result
H1	TMC → BA	0.02	0.3947	Not supported
H2	FSMC → BA	0.38	0.0000	Supported
H3	USMC → BA	0.23	0.0007	Supported
H4	PSC → BA	0.21	0.0001	Supported
H5	BA → PI	0.83	0.0000	Supported

5. Discussion

5.1. Theoretical contribution

This study attempts to test empirically the effects of four types of media communication (traditional media advertising, firm-created social media, user-generated social media, and personal selling) on brand attitude. The results showed that firm-created social media, user-generated social media, and personal selling affect brand attitude. Among the three, firm-created social media has the greatest effect, followed by user-generated social media and personal selling. These three types of media are interactive and personalized media, thus two-way communication is preferred by customers.

In contrast to the past, this study also finds that traditional media communication does not influence brand attitude significantly in the context of a cosmetic brand. The advertising media has changed substantively during the past two decades as digital media have become increasingly popular (Laurie et al., 2019). It also illuminates that, in the digital era, personalized and interactive media have an effect on brand attitude.

The findings were in line with S-O-R theory (Mehrabian & Russell, 1974). This means that only stimulus that emerged from certain media with distinct effects can create an organism (brand attitude in this context). Then, the organism (brand attitude) influences consumers’ response; i.e., intention to buy the product. As the stimulus evolves through the popularity of digital media and social media, the role of each communication media changes. Interactive stimulus has relatively greater effects than that of non-interactive ones. Thus, based on SET (Klapper, 1960; Knobloch-Westerwick, 2015), the audience or consumers are more inclined toward exposure that is consistent with their attitudes or views. According to Sundar et al. (2015), one of the interaction types is related to the media types themselves. Since each media format has its own characteristics, such as the level of interactivity (interactive vs non-interactive), the audience or consumers can select the types of media whose exposure is more controlled by them in order to get messages congruent with their attitudes.

In the past, traditional media such as television advertising, print media, or radio broadcasting tended to dictate content to the audience. Consumers had relatively little choice regarding the availability of media. As stated by Bui et al. (2023), traditional advertising methods only offer one way communication (non-interactive), whereas social media facilitate interactive communications. Traditional media communication is not controlled by consumers compared to digital media or social media. For example, when consumers are exposed to TV advertisements that are incongruent with their attitudes, they may wait until the exposure ends or change to another channel. In contrast, social media offers exposure that consumers can easily control. When using social media, consumers have more control to select the exposure compared to non-interactive media.

Hence, SET can extend not only to contents or messages, but also to the types of communication media. Consumers are more reluctant to use traditional media, as they cannot accommodate selective exposure like social media can. The interactive characteristic facilitates consumers to select the content exposure. The same circumstances also arise in the case of personal selling, as salespersons can provide information that is suitable for consumers. Although personal selling communication is categorized as old media, its interactive characteristic keeps allowing the delivery of messages suitable to consumers’ attitudes.

Lastly, the results of this study also corroborate that brand attitude has an effect on repurchase intention. This finding also supports previous studies. In accordance with S-O-R theory, brand attitude (as an organism) is formed through messages delivered through media types that suit customer beliefs. Then, the positive attitude toward a brand encourages customers to purchase or repurchase from the brand in the future.

5.2. Managerial implications

Communication is a vital element for companies and therefore must be well planned and managed (Verhoeven et al., 2020). The results of this study point out that companies need to formulate their marketing communication strategically, since not all media have a significant impact on brand attitude. A message that is not channelled through suitable media has no significant effect on building the brand.

As the external environment has changed from one-way communication to two-way communication, companies should pay attention to interactive media. Traditional media communication such as traditional television advertising, radio broadcast, and mass media (Tümer et al., 2019) have passive characteristics and give limited control to customers. These kinds of media do not facilitate interactive communication between senders (companies) and receivers (customers). On the other hand, social interactive media has become more efficient and effective after the advancement of the internet technology (De Veirman et al., 2017). Hence, social media content (both firm created and user generated) has more advantages than traditional media advertising. Furthermore, personal selling communication, even though it is not a new media, is still effective for communicating with customers. Personal selling is considered interactive and a form of personal communication media. Salespersons must maintain their roles in creating messages that convey information to specific customers and give fast responses to the questions asked by them.

For media owners, this study recommends that they accept challenges to make their media more interactive. They must innovate by adding and enhancing interactive features in their communication media. This is not an easy task, but advanced technology can help to facilitate the interaction.

Lastly, this study reveals that brand attitude has an effect on repurchase intention. Brand managers should continue to build their company’s brand more effectively. Having a positive brand attitude requires resources such as appropriate communication media. This requires some financial sources, media planning, and a selection of media channels. Proactive efforts will bring returns to companies when customers are exposed to the media and buy a brand’s products. Therefore, building a positive brand attitude must be viewed as an investment for companies.

6. Limitation and future research

In general, research always faces limitations, as does this study. First, this study investigated a global brand of cosmetic products marketed in Indonesia. Cosmetic products are categorized in the consultative category, i.e., products that need relatively deep information for customers when buying them, compared to fast-moving consumer goods which require minimum information. Future study can investigate other product categories to test the generalizability of our findings. Second, the respondents in this study are Indonesian females, the majority of whom are ages 20–25 years old. Future study can explore respondents in other countries with different respondents’ characteristics to enrich the findings.

The current research only considered four types of communication media. This does not mean exhaustive media. Future research can investigate relatively new forms such as game advertising and will provide rich insights into the industry. Lastly, future studies can also examine the effects of moderating variables such as different genders, age groups, or occupations. This will shed the light on the findings for different target audiences.

Acknowledgement

The authors thank the five blind reviewers and the editors for their valuable suggestions. The thanks also go to Steven Randy Istijanto who helped for data collection and Kantor Riset SBE Universitas Prasetiya Mulya for the final proofread.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The work was supported by the Research Center (LPPM), Universitas Prasetiya Mulya [Internal Grant 2023].

Notes on contributors

Istijanto

Istijanto is Assistant Professor of Management at the School of Business and Economics, Universitas Prasetiya Mulya, Jakarta, Indonesia. He has published more than a dozen books over the years in the field of management. His research papers have been published in Quality Assurance in Education, Transportation Research Interdisciplinary Perspectives, Young Consumers, Spanish Journal of Marketing-ESIC, among others. He also served as a reviewer for several international journal and business consultant.

Ambara Purusottama

Ambara Purusottama is Assistant Professor of Management at the School of Business and Economics, Universitas Prasetiya Mulya, Jakarta, Indonesia. He has written research paper in several national and international journals, such as Business Process Management Journal. Ambara also often provides management training and consulting.