Does Social Media Influencer Credibility Affect Attitudes and Engagement Behaviour? - Empirical Evidence

Abstract

Influencer marketing through social media platforms recently sparked vast interest between researchers and industry players to enhance their marketing strategy. In addition, advertising through social media influencers has become a trend in Malaysian social media product and service marketing. Previous conventional studies concentrating on celebrities as product endorsers have now switched to social media influencers for better benefits such as cost advantage and deeper reach in the community. Despite various social media studies, only a few highlighted influencer marketing credibility. Furthermore, the perceived credibility of social media influencers is still yet to be defined as the extension of the celebrity endorser credibility study. Hence, this paper examines social media influencer marketing credibility's effect on consumer attitudes and engagement behaviour. The study was conducted on Malaysian millennials residing in Klang Valley to obtain their opinion on a social media video related to a national car, Proton X70. The study reveals that all credibility dimensions have a positive effect on attitudes towards influencer (ATI) and video content (ATV), but only brand credibility (BC) has a positive effect on attitudes towards the X70 brand model (ATB). However, all credibility dimensions indirectly affect ATB via ATV. All attitude dimensions also positively affect social media engagement intentional behaviour (SCB). The result of the study is predicted to expand the scope of social media influencer marketing credibility, consumer attitudes, and social media engagement intentional behaviour. The study is also expected to benefit future automotive advertising strategies concerning social media influencers.

Keywords: Automotive marketing, consumer attitude, social media ınfluencer, socia media engagement

Introduction

Social plays a vital role in the modern marketing communication strategy, and its’ platform varies from microblogs such as Facebook and Twitter to video-sharing platforms such as YouTube and TikTok. Focusing on a social video-sharing platform, Kemp (2019) highlighted that Malaysian spend an average of 7.2 hours a week watching online videos, where YouTube is Malaysia's most active social media platform. In addition, most social media influencers share activities via YouTube as their primary social media platform compared to other platforms. On the other hand, a study by Edelman (2019) stressed that influencer marketing is crucial for brand growth, whereby around 63% of customers trust what the influencers say about a brand more than the brand says about itself. Bailis (2020) also claimed that nearly 90% of marketers find that the return on investment (ROI) from influencer marketing is either equally good or better than other marketing channels. In further research, Adetunji et al. (2018) elaborated that videos posted on Facebook and YouTube are an essential marketing effort to enhance car brand equity. Thus, it motivates a study on a YouTube video of social media influencers reviewing Malaysian national cars, referring to C-segment SUVs, namely Proton X70.

Problem Statement

Proton X70 has already been available in the Malaysian market since 2018, where most Malaysian today have great familiarity with the product brand. According to the Malaysian Automotive Association (2022), the Proton brand held only 16.6% of the total Malaysian passenger cars market share in 2019, and thus, new ideas in marketing strategy are still needed to increase their market share to stay competitive in the industry. Proton's previous advertising strategy from 2016 to 2017 is seen to be more concentrated on celebrity endorsers introducing their products to the community. Conversely, in 2020, Proton has slowly added a new marketing strategy by using social media influencers as product endorsers and ambassadors. Nevertheless, the influencer involvement with Proton Brand is still seen as minimal. Therefore, this study suggests several ideas in the area of social media influencer marketing credibility as a part of Proton’s future marketing strategy.

Furthermore, many pieces of literature on celebrities as endorsers have been widely studied by previous researchers. The work of Ohanian (1990) elaborated the tri-component model of celebrity endorser credibility, trustworthiness, expertise, and attractiveness. Hence, it is further heightened by Lafferty and Goldsmith (1999), who studied celebrity endorser credibility alongside corporate credibility with the effect on the advertisement and brand attitude. Later, Muda (2012) expanded the framework of credibility sources by measuring celebrity credibility, corporate credibility, and advertisement credibility. Up to this day, there are very few studies on social media influencer credibility and video content credibility. Therefore, this paper aims to extend Muda's (2012) study to measure the social media influencer marketing credibility dimension in the context of influencer credibility, video content credibility, and brand credibility.

Research Questions

The author prepared the research questions parallel to the hypothesis of the study. There are, in total, 5 main research questions and hypotheses for the study. In line with the previous study of celebrity endorsers, this paper replicates the credibility sources for social media influencers in particular. Lim et al. (2017) highlighted that the endorser’s attractiveness could enhance consumer attitudes towards endorsers. In addition, Wang et al. (2017) further confirm the significant positive relationship between endorser credibility and brand attitudes. Hence, therefore the results reflect the influencer credibility hypothesis H1 and research question R1 below:

H1: Influencer credibility will have a positive effect on consumer attitudes.

R1: Does Influencer credibility affect consumer attitudes?

Further, the author adapted the advertisement credibility from previous studies for video content credibility. Kim & Kim (2021) demonstrated that believability significantly influences consumer attitudes toward the advertisement. Similarly, Yang et al. (2017) also stressed that the advertisement value sub-element, advertisement credibility, significantly affects consumer attitude. With the previous literature support from Hansen et al. (2014) on YouTube video effect on consumer attitudes, therefore hypothesis H2 and research question R2 are declared as follows:

H2: Video content credibility will have a positive effect on consumer attitudes.

R2: Does video content credibility affect consumer attitudes?

Overall, the effect of existing brand credibility on consumer attitudes is rarely examined. Hence, in this thesis, the relationship is essential to be measured. Here, the author adapted company credibility from Muda (2012) for the brand credibility for this study. Therefore, hypothesis H3 and research question R3 are as stated below:

H3: Proton brand credibility will have a positive effect on consumer attitudes.

R3: Does Proton brand credibility affect consumer attitudes?

Moreover, Hovland et al. (1953) have suggested that source credibility has its maximum effects on acceptance when the source and the content are such that there would be a considerable discrepancy between the attitudinal responses to each of them alone. Since the study is scrutinised not only by measuring consumer attitudes in general but also separately measuring consumer attitudes towards influencers, video content, and brand model each, therefore the hypotheses are detailed as follows:

H1a: Influencer credibility will positively affect consumer attitudes toward the influencer.

H1b: Influencer credibility will positively affect consumer attitudes toward the video content.

H1c: Influencer credibility will positively affect consumer attitudes toward the X70 brand model.

H2a: Video content credibility will positively affect consumer attitudes toward the influencer.

H2b: Video content credibility will positively affect consumer attitudes toward the video content.

H2c: Video content credibility will positively affect consumer attitudes toward the X70 brand model.

H3a: Brand credibility will positively affect consumer attitudes toward the influencer.

H3b: Brand credibility will positively affect consumer attitudes toward the video content.

H3c: Brand credibility will positively affect consumer attitudes toward the X70 brand model.

Additionally, the detailed research questions are as follows:

R1a: Does influencer credibility affect consumer attitudes toward the influencer?

R1b: Does influencer credibility affect consumer attitudes toward the video content?

R1c: Does influencer credibility affect consumer attitudes toward the X70 brand model?

R2a: Does video content credibility affect consumer attitudes toward the influencer?

R2b: Does video content credibility affect consumer attitudes toward the video content?

R2c: Does video content credibility affect consumer attitudes toward the X70 brand model?

R3a: Does brand credibility affect consumer attitudes toward the influencer?

R3b: Does brand credibility affect consumer attitudes toward the video content?

R3c: Does brand credibility affect consumer attitudes toward the X70 brand model?

On top of that, Muda (2012) predicted that consumer attitudes toward advertisements would positively affect consumer attitudes toward the brand. A similar finding was unveiled by Lee et al. (2017) for a mobile ad, Schmuck et al. (2018) for green product advertisements and Hameed et al. (2020) for convenience and shopping product advertisements. Therefore, the following hypothesis H4 is proposed parallel with research question R4:

H4: Consumer attitudes toward the video content will positively affect consumer attitudes toward the X70 brand model.

R4: Do consumer attitudes toward the video content affect consumer attitudes toward the X70 brand model?

Other than that, Lu et al. (2014) studied Taiwanese blogs and found highly positive attitudes toward sponsored recommendation posts, which improves purchase intention. In the other work by Moldovan and Ciornea (2019), consumer attitude towards vloggers and products is significantly related to actions on YouTube to recommend the product. On that account, this study proposed to scrutinise the social media engagement intentional behaviour measurement into more detailed segments as in Cao et al. (2021). The link of attitudes towards social media engagement intentional behaviour is proposed as below hypothesis H5 and research question R5:

H5: Consumer attitudes will positively affect social media engagement intentional behaviour.

R5: Do consumer attitudes affect social media engagement intentional behaviour?

With detailed hypotheses and research question elements as follows:

H5a: Consumer attitudes toward the Influencer will positively affect social media engagement intentional behaviour.

H5b: Consumer attitudes toward the video content will positively affect social media engagement intentional behaviour.

H5c: Consumer attitudes toward the X70 brand model will positively affect social media engagement and intentional behaviour.

R5a: Do consumer attitudes toward the Influencer affect social media engagement intentional behaviour?

R5b: Do consumer attitudes toward the video content affect social media engagement intentional behaviour?

R5c: Do consumer attitudes toward the X70 brand model affect social media engagement and intentional behaviour?

Purpose of the Study

Overall, the result of the study is expected to contribute to the marketing strategy framework for future research references. This analysis would also suggest specific approaches for millennials to gain positive social media intentional behaviour of potential customers. The study findings would benefit all marketing practices for the automobile industry and other target market sectors. In detail, this study would also provide a clear strategy for industry players to improve their marketing strategy through social media influencer credibility, video content (advertisement), and brand credibility. Other scholars' literature suggests that social media influencer marketing investment is either better or comparable to other marketing channels (Bailis, 2020). The influencer marketing strategy is also seen as a cost-effective strategy to gain consumer purchases. Also, Malaysia's social media users have reached a high penetration rate of at least 81% of the population (Kemp, 2020). Therefore, the influencer marketing strategy is only suitable for countries with high social media penetration rates.

In addition, this study also shows how important it is for Proton to strategise its influencer marketing strategy based on the suggested pairing of credibility sources. These comprise influencer credibility, video content credibility, and Proton brand credibility. All these credibility sources were proven to indirectly affect the attitudes toward the X70 brand model. However, marketers need to be extra careful with selecting the influencers and the video content about to be published by the influencer. Here, marketers need to choose influencers who portray good credibility, similar to celebrity endorsers who are perceived as attractive and trustworthy, have expertise in the area, and have proper decorum (Muda, 2012). At the same time, the video content could be user-generated but needs to be advised by the marketers to have the element of honesty and believability to maintain the content’s credibility (Hasanah & Wahid, 2019).

Research Methods

This study used quantitative methods within a set of online self-administered questionnaires as measurement tools. The respondent refers to urban millennials born from 1981 until 1996 (Saidon et al., 2017) and residing in Klang Valley, Malaysia. The millennials in this study include two main groups, which are (i) young urban millennials and (ii) mature urban millennials, based on Musa et al. (2017). Young urban millennials (YUM) are the younger generation of millennials who are new to the workforce, and most of them are at the beginning stage of building their career. On the other hand, urban millennials (MUM) are seen to have a more stable income, an established career, and are more mature in their buying behaviour. For the data collecting method, the respondents were first asked to watch a YouTube video (around 2 minutes duration) embedded in the online questionnaire. The footage shows three social media influencers talking about the Proton X70 SUV in general. Then, the respondents were asked to answer a set of questionnaires related to this study comprised of 7 constructs with a total of 68 items adapted from previous academic publications. Refer to the Table 1 below.

The study started with a pilot test to test the completeness of the measurement method. Viechtbauer et al. (2015) elaborated that a pilot study goal is to identify unforeseen problems, such as ambiguous inclusion or exclusion criteria or misinterpretations of questionnaire items. The pilot test will use 30 samples parallel to the previous researchers’ suggestions, such as in Hertzog (2008) and Johanson and Brooks (2010). Final data collection targeted to receive a total of 400 samples: 200 samples from Young Urban Millennials and another 200 sets from Matured Urban Millennials. Based on G*Power measurement (Hair et al., 2010), it is suggested the minimum sample desirable for medium-size effect related to the study framework is 119 samples. Therefore, 200 samples for each millennial category are considered adequate before the data screening and cleaning.

The study is examined under both the measurement model and structural model. For the measurement model, the study measured the data's internal consistency, convergent validity, and discriminant validity (Ramayah et al., 2018). As for the structural model, Zweig and Webster (2003) suggested that SEM is suitable for addressing the research question with multiple relationships between the dependent and independent variables. Thus, the data analysis for the structural model of the study will use the structural equations modelling (SEM) method, Smart PLS3, to find the significance of the variable relationships and the effects based on the hypotheses.

Findings

A total of 426 respondents participated in this study. In this study, 32.4% of the participants were males, and the remaining were females. These statistics were comparable with the ethnic composition of the urban population of Klang Valley by Suruhanjaya Pilihan Raya Malaysia (2018), as follows: 46.5% Malay, 43.2% Chinese, 7.3% Indians, and 3.1% others. The millennial group of the participants was YUM (69.7%) and MUM (30.3%). Whilst the car brand ownership of the participants was Perodua (25.1%), Proton (13.4%), Honda (10.6%), Toyota (8.7%), Nissan (2.8%), Mazda (2.1%), Mitsubishi (0.2%), other brands (8.9%), and no car ownership (28.2%).

Structural Model

Further, this paper also analyses the structural model via the lateral collinearity assessment and the hypothesis testing result (assessment on the significance and relevance of the structural model relationships, the level of R2, the size effect f2, and the predictive relevance Q2. The lateral collinearity results for the data show that all the VIF values range from 1.413 to 3.645, which does not exceed the maximum allowed threshold of 5.0 based on Hair et al. (2017). The detailed structural model result is exhibited in Figure 1.

See Full Size >

The result exhibited that all credibility dimensions Influencer Credibility (IC), Video Content Credibility (VC), and Brand Credibility (BC) have a positive effect on attitudes toward Influencer (ATI) and video content (ATV), supporting the hypotheses H1a, H1b, H2a, H2b, H3a, and H3b. The study also explicated that only brand credibility (BC) was found to have a positive effect on attitudes toward the X70 brand model (β=0.482, t=8.675, p<0.01) and supported the hypotheses H3c. Thus, the hypotheses H1c (β=-0.083, t=0.061, n.s.) and H2c (β=-0.005, t=0.075, n.s.) are not supported for this study.

Further analysis, however, shows that influencer credibility (IC) and video content credibility (VC) have an indirect positive effect on attitudes toward the X70 brand model (ATB) via attitudes towards video content. The positive effect of ATV on ATB supports hypothesis H4 (β=0.387, t=5.996, p<0.01). In addition, all consumer attitudes dimensions (ATI, ATV, and ATB) positively affect social media engagement intentional behaviour (SCB), supporting hypotheses H5a, H5b, and H5c. The full result of accepted hypotheses is also tabulated in Table 5 as follows:

See Full Size >

Conclusion

Recently, researchers have extensively conducted the study of social media as a marketing medium, including the study of social media influencers as endorsers of products or services. This paper examined the extension of the social media influencer marketing credibility model, which integrates consumer attitudes and social media engagement intentional behaviour. The study finding explains that consumer attitudes (ATI, ATV, and ATB) affected social media engagement intentional behaviour (SCB). On the other hand, Cao et al. (2021) explain intentional engagement is a critical factor in determining consumer engagement activities such as contributing, consuming, or creating to gain the most effective social media marketing strategy. To achieve this, social media marketers need to secure positive effects from all aspects of consumer attitudes, namely ATI, ATV, and ATB.

Furthermore, the study also highlights the importance of attitudes toward video content (ATV), which positively affects attitudes toward the X70 brand model (ATB), as exhibited in H4. The result shows all credibility elements would affect attitudes towards the X70 brand model (ATB) via attitudes toward video content (ATV). This positive effect of ATV on ATB is also supported by previous literature, such as Laksmidewi and Soelasih (2019) and Lee et al. (2017), for a similar positive effect of attitude towards advertisement on attitudes toward the brand. The result suggested an excellent strategy to improve customer attitude towards the brand, especially for Proton brand models, in the future. After all, to induce good consumer attitudes toward video content (ATV). This study also reveals that all of the positive effects from credibility dimensions (IC, VC, and BC) or, namely, ‘social media engagement marketing credibility’, are equally important for marketing strategy. The findings highlighted that the credibility dimensions positively affect attitudes toward the video content (ATV), as exhibited in H1b, H2b and H3b.

In conclusion, the study has successfully examined the effect of social media engagement marketing credibility on consumer attitudes and social media engagement intentional behaviour empirically parallel to the CAB model theory. This paper also emphasises the importance of social media engagement marketing credibility, encompasses influencer credibility (IC), video content credibility (VC), and brand credibility (BC) as essential dimensions to gain positive consumer attitudes and consumer engagement intentional behaviour. In detail, the marketers are advised to choose an influencer who portrays good credibility. The influencer should be perceived as attractive, trustworthy, an expert in the area, and having proper decorum. At the same time, the video content could be user-generated but needs to be advised by the marketers to have the element of honesty and believability to maintain the content’s credibility. Another focal point is that the study explains the importance of attitudes toward video content (ATV) for the indirect effect of all credibility dimensions on attitudes towards the X70 brand model (ATB). This finding gave marketers insight into the fact that product advertising via influencer videos is very effective in improving consumer attitudes toward brands among the millennial generation cohort.

Several limitations were also highlighted for the study, where the location of the study only concentrated on the Klang Valley area, the most populous area in Malaysia and may not represent the whole country for the result. Also, the study only refers to the millennials, albeit other generations. Although Gen X seems to have high purchase power, their interaction with social media influencers is still unclear. Therefore, it will be interesting for future research to test the validity of the results in other generation cohorts and geographical locations. Barger et al. (2016) highlighted that customer satisfaction is always reported as being mitigated by customer engagement strategy, alongside different positive outcomes such as increasing customer lifetime value, share-of-wallet, customer loyalty, and brand profitability. This idea is also supported by Claffey and Brady (2014), by stressing that consumer engagement may lead to positive valences such as satisfaction and loyalty. It will also be fruitful to extend the framework by integrating influencer and brand attachment for future research.

References

• Ab Hamid, M. R., Sami, W., & Mohmad Sidek, M. H. (2017). Discriminant Validity Assessment: Use of Fornell & Larcker criterion versus HTMT Criterion. Journal of Physics: Conference Series, 890, 012163. DOI:

  Google Scholar

  Crossref

• Adetunji, R. R., Rashid, S. M., & Ishak, M. S. (2018). Social Media Marketing Communication and Consumer-Based Brand Equity: An Account of Automotive Brands in Malaysia. Jurnal Komunikasi, Malaysian Journal of Communication, 34(1), 1-19. DOI:

  Google Scholar

  Crossref

• An, J., Do, D. K. X., Ngo, L. V., & Quan, T. H. M. (2019). Turning brand credibility into positive word-of-mouth: integrating the signaling and social identity perspectives. Journal of Brand Management, 26(2), 157-175. DOI:

  Google Scholar

  Crossref

• Ariffin, S. K., Aun, T. L., & Salamzadeh, Y. (2018). How Personal Beliefs Influence Consumer Attitude towards Online Advertising in Malaysia: To Trust or Not to Trust? Global Business & Management Research, 10(1).

• Bailis, R. (2020). The State of Influencer Marketing: 10 Influencer Marketing Statistics to Inform Where You Invest. Big Commerce. https://www.bigcommerce.com /blog/influencer-marketing-statistics/

• Barger, V., Peltier, J. W., & Schultz, D. E. (2016). Social media and consumer engagement: a review and research agenda. Journal of Research in Interactive Marketing, 10(4), 268-287. DOI:

  Google Scholar

  Crossref

• Brodie, R. J., Hollebeek, L. D., Jurić, B., & Ilić, A. (2011). Customer engagement: Conceptual domain, fundamental propositions, and implications for research. Journal of service research, 14(3), 252-271.

• Cao, D., Meadows, M., Wong, D., & Xia, S. (2021). Understanding consumers' social media engagement behaviour: An examination of the moderation effect of social media context. Journal of Business Research, 122, 835-846. DOI:

  Google Scholar

  Crossref

• Carlson, J., Rahman, M., Voola, R., & De Vries, N. (2018). Customer engagement behaviours in social media: capturing innovation opportunities. Journal of Services Marketing, 32(1), 83-94. DOI:

  Google Scholar

  Crossref

• Chen, J., Teng, L., Yu, Y., & Yu, X. (2016). The effect of online information sources on purchase intentions between consumers with high and low susceptibility to informational influence. Journal of Business Research, 69(2), 467-475. DOI:

  Google Scholar

  Crossref

• Claffey, E., & Brady, M. (2014). A model of consumer engagement in a virtual customer environment. Journal of Customer Behaviour, 13(4), 325-346. DOI:

  Google Scholar

  Crossref

• Edelman. (2019, June 18). In Brands We Trust: 2019 Edelman Trust Barometer Special Report. https://www.edelman.com/sites/g/files/aatuss191/files/2019-06/2019_edelman_trust_barometer_special_report_in_brands_we_trust_executive_summary.pdf

• Erdem, T., & Swait, J. (2004). Brand Credibility, Brand Consideration, and Choice. Journal of Consumer Research, 31(1), 191-198. DOI:

  Google Scholar

  Crossref

• Esmaeilpour, M., & Aram, F. (2016). Investigating the impact of viral message appeal and message credibility on consumer attitude toward the brand. Management & Marketing, 11(2), 470-483. DOI:

  Google Scholar

  Crossref

• Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge Management: An Organizational Capabilities Perspective. Journal of Management Information Systems, 18(1), 185-214. DOI:

  Google Scholar

  Crossref

• Goldberg, M. E., & Hartwick, J. (1990). The Effects of Advertiser Reputation and Extremity of Advertising Claim on Advertising Effectiveness. Journal of Consumer Research, 17(2), 172. DOI:

  Google Scholar

  Crossref

• Goodrich, K., Schiller, S. Z., & Galletta, D. (2015). Consumer Reactions to Intrusiveness Of Online-Video Advertisements: Do Length, Informativeness, and Humor Help (or Hinder) Marketing Outcomes? Journal of Advertising Research, 55(1), 37-50. DOI:

  Google Scholar

  Crossref

• Greer, J. D. (2003). Evaluating the Credibility of Online Information: A Test of Source and Advertising Influence. Mass Communication and Society, 6(1), 11-28. DOI:

  Google Scholar

  Crossref

• Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2010). Multivariate Data Analysis. (7th Ed.). Pearson.

• Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage publications.

• Hameed, I., Babar Khan, M., & Shahab, A. (2019). Perceived Humorand Purchase Intention:Mediating Role of Attitude towards the Advertisement and Brand. Lahore Journal of Business, 8(2), 55-84. DOI:

  Google Scholar

  Crossref

• Hansen, S. S., Lee, J. K., & Lee, S. Y. (2014). Consumer-generated ads on YouTube: Impacts of source credibility and need for cognition on attitudes, interactive behaviors, and eWOM. Journal of Electronic Commerce Research, 15(3), 254.

• Hasanah, R., & Wahid, N. A. (2019). The Mediating Role of Consumer’s Attitude toward Advertising on the Relationship between Advertisement Content Credibility and Attitude toward Brand: The Case of Beauty Soap in Indonesia. International Journal of Multicultural and Multireligious Understanding, 6(9), 12-21.

• Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135. DOI:

  Google Scholar

  Crossref

• Hertzog, M. A. (2008). Considerations in determining sample size for pilot studies. Research in Nursing & Health, 31(2), 180-191. DOI:

  Google Scholar

  Crossref

• Hovland, C. I., Janis, I. L., & Kelley, H. H. (1953). Communication and Persuasion. Yale University Press.

• Hur, W.-M., Kim, H., & Woo, J. (2014). How CSR Leads to Corporate Brand Equity: Mediating Mechanisms of Corporate Brand Credibility and Reputation. Journal of Business Ethics, 125(1), 75-86. DOI:

  Google Scholar

  Crossref

• Johanson, G. A., & Brooks, G. P. (2010). Initial Scale Development: Sample Size for Pilot Studies. Educational and Psychological Measurement, 70(3), 394-400. DOI:

  Google Scholar

  Crossref

• Jordaan, Y., Ehlers, L., & Grové, J. M. (2022). Advertising credibility across media channels: perceptions of Generation Y consumers. Communicare: Journal for Communication Studies in Africa, 30(1), 1-20. DOI:

  Google Scholar

  Crossref

• Kemp, E., & Bui, M. (2011). Healthy brands: establishing brand credibility, commitment and connection among consumers. Journal of Consumer Marketing, 28(6), 429-437. DOI:

  Google Scholar

  Crossref

• Kemp, S. (2019, January 31). Digital 2019: Malaysia. DataReportal. https://datareportal.com/reports/digital-2019-malaysia

• Kemp, S. (2020, February 19). Digital 2020: Malaysia. DataReportal. https://datareportal.com/reports/digital-2020-malaysia

• Kim, T., & Kim, J. (2021). How Spatial Distance and Message Strategy in Cause-Related Marketing Ads Influence Consumers' Ad Believability and Attitudes. Sustainability, 13(12), 6775. DOI:

  Google Scholar

  Crossref

• Kline, R. B. (2011). Convergence of Structural Equation Modeling and Multilevel Modeling. Sage Publishing.

• Lafferty, B. A., & Goldsmith, R. E. (1999). Corporate Credibility's Role in Consumers' Attitudes and Purchase Intentions When a High versus a Low Credibility Endorser Is Used in the Ad. Journal of Business Research, 44(2), 109-116. DOI:

  Google Scholar

  Crossref

• Laksmidewi, D., & Soelasih, Y. J. D. B. (2019). Anthropomorphic Green Advertising: How to Enhance Consumers’ Environmental Concern. DLSU Business & Economics Review, 29(1), 72-84.

• Lee, E.-B., Lee, S.-G., & Yang, C.-G. (2017). The influences of advertisement attitude and brand attitude on purchase intention of smartphone advertising. Industrial Management & Data Systems, 117(6), 1011-1036. DOI:

  Google Scholar

  Crossref

• Lim, X. J., Radzol, A. M., Cheah, J., & Wong, M. W. (2017). The Impact of Social Media Influencers on Purchase Intention and the Mediation Effect of Customer Attitude. Asian Journal of Business Research, 7(2). DOI:

  Google Scholar

  Crossref

• Lu, L.-C., Chang, W.-P., & Chang, H.-H. (2014). Consumer attitudes toward blogger's sponsored recommendations and purchase intention: The effect of sponsorship type, product type, and brand awareness. Computers in Human Behavior, 34, 258-266. DOI:

  Google Scholar

  Crossref

• MacKenzie, S. B., Lutz, R. J., & Belch, G. E. (1986). The Role of Attitude toward the Ad as a Mediator of Advertising Effectiveness: A Test of Competing Explanations. Journal of Marketing Research, 23(2), 130. DOI:

  Google Scholar

  Crossref

• Malaysian Automotive Association. (2022, January 22). Market Review 2021. Press Release. http://www.maa.org.my/pdf/2021/Market_Review_2021.pdf

• Moldovan, R. A., & Ciornea, R. (2019). The Effect of Online Unpaid Reviews made by Renowned Vloggers: the Case of Smartphones. Marketing - from Information to Decision Journal, 2(2), 18-34. DOI:

  Google Scholar

  Crossref

• Muda, M., Musa, R., & Putit, L. (2010). Determinants of attitude toward celebrity-endorsed advertisements: A conceptual model. 2010 International Conference on Science and Social Research (CSSR 2010). DOI:

  Google Scholar

  Crossref

• Muda, M., Musa, R., Mohamed, R. N., & Borhan, H. (2014). Celebrity Entrepreneur Endorsement and Advertising Effectiveness. Procedia - Social and Behavioral Sciences, 130, 11-20. DOI:

  Google Scholar

  Crossref

• Muda. (2012). Modeling the Effects of Perceived Credibility on Consumers' Attitudes and Intention: Empirical Evidence from Simplysiti Print Advertisement. [Doctoral dissertation, Universiti Teknologi MARA].

• Musa, R., Saidon, J., & Rahman, S. A. (2017). Who's at Risk for Smartphone Nomophobia and Pathology; The Young or Matured Urban Millennials? Advanced Science Letters, 23(8), 7486-7489. DOI:

  Google Scholar

  Crossref

• Nouri, M. (2018). The Power of Influence: Traditional Celebrity Vs Social Media Influencer. Advance Writing: Pop Culture Intersection, 32.

• Ohanian, R. (1990). Construction and Validation of a Scale to Measure Celebrity Endorsers' Perceived Expertise, Trustworthiness, and Attractiveness. Journal of Advertising, 19(3), 39-52. DOI:

  Google Scholar

  Crossref

• Park, H. J., & Lin, L. M. (2020). The effects of match-ups on the consumer attitudes toward internet celebrities and their live streaming contents in the context of product endorsement. Journal of Retailing and Consumer Services, 52, 101934. DOI:

  Google Scholar

  Crossref

• Parwati, K. Y., Rohman, F., & Puspaningrum, A. (2021). The Effect of Self-Congruity and Celebrity Endorsement on Brand Loyalty With Brand Attitude As A Mediation Variables. Jurnal Aplikasi Manajemen, 19(1), 156-165. DOI:

  Google Scholar

  Crossref

• Primanto, A. B., & Dharmmesta, B. S. (2019). What happens after they laugh: How humorous advertisements have an effect on consumers’ attitudes, word of mouth intentions, and purchase intentions, with the need for humor playing a moderating role. Journal of Indonesian Economy and Business, 34(2), 117. DOI:

  Google Scholar

  Crossref

• Ramayah, T., Cheah, J., Chuah, F., Ting, H., & Memon, M. A. (2018). Partial Least Squares Structural Equation Modeling (PLS-SEM) Using Smartpls 3.0. An Updated Guide and Practical Guide to Statistical Analysis (2nd Ed.). Pearson.

• Saidon, J., Musa, R., Harris, M., & Harun, M. (2017). Pathological smartphone use and its consequences. Pertanika Journal of Social Sciences and Humanities, 25, 391-398.

• Schmuck, D., Matthes, J., & Naderer, B. (2018). Misleading Consumers with Green Advertising? An Affect-Reason-Involvement Account of Greenwashing Effects in Environmental Advertising. Journal of Advertising, 47(2), 127-145. DOI:

  Google Scholar

  Crossref

• Schouten, A. P., Janssen, L., & Verspaget, M. (2020). Celebrity vs. Influencer endorsements in advertising: the role of identification, credibility, and Product-Endorser fit. International Journal of Advertising, 39(2), 258-281. DOI:

  Google Scholar

  Crossref

• Solomon, M., White, K., & Dahl, D. W. (2017). Consumer Behaviour: Buying, Having and Being. (7th ed.). Toronto, Canada: Pearson.

• Spry, A., Pappu, R., & Bettina Cornwell, T. (2011). Celebrity endorsement, brand credibility and brand equity. European Journal of Marketing, 45(6), 882-909. DOI:

  Google Scholar

  Crossref

• Suruhanjaya Pilihan Raya Malaysia. (2018). Laporan Kajian Semula Persempadanan Mengenai Syor-Syor Yang Dicadangkan Bagi Bahagian-Bahagian Pilihan Raya Persekutuan Dan Negeri Di Dalam Negeri-Negeri Tanah Melayu Kali Keenam Tahun 2018 Jilid 1. http://www.spr.gov.my/sites/default/files/Jilid1KajianSemulaPersempadananV2.pdf

• Sweeney, J., & Swait, J. (2008). The effects of brand credibility on customer loyalty. Journal of Retailing and Consumer Services, 15(3), 179-193. DOI:

  Google Scholar

  Crossref

• Viechtbauer, W., Smits, L., Kotz, D., Budé, L., Spigt, M., Serroyen, J., & Crutzen, R. (2015). A simple formula for the calculation of sample size in pilot studies. Journal of Clinical Epidemiology, 68(11), 1375-1379. DOI:

  Google Scholar

  Crossref

• Wang, S. W., Kao, G. H.-Y., & Ngamsiriudom, W. (2017). Consumers' attitude of endorser credibility, brand and intention with respect to celebrity endorsement of the airline sector. Journal of Air Transport Management, 60, 10-17. DOI:

  Google Scholar

  Crossref

• Yang, K.-C., Huang, C.-H., Yang, C., & Yang, S. Y. (2017). Consumer attitudes toward online video advertisement: YouTube as a platform. Kybernetes, 46(5), 840-853. DOI:

  Google Scholar

  Crossref

• Zweig, D., & Webster, J. (2003). Personality as a moderator of monitoring acceptance. Computers in Human Behavior, 19(4), 479-493. DOI:

  Google Scholar

  Crossref