1. Introduction
Marketing strategies of companies focus mostly on promoting products to the market with the core objective as to customer persuasion; since the customers have a lot of knowledge, references, and choices before making a purchase decision; competition has also become extensively severe. Although celebrity endorsement exists as a common strategy, the rise of influencers has opened up the field for a different type of endorsement strategy known as influencer marketing. The use of internet has given a consumer immense access to information, and social media has enhanced it, making social media an inseparable element of everyday life (Pentina et al., 2018). Marketing in social media has become a key strategy for any company, as the growing numbers of social media users have made it a key marketplace for finding desired consumers for brand communication (Bianchi et al., 2017). Earlier, companies took advantage of the fame and social status of celebrities to promote their brands, but advancements in social media platforms has led to an upward recognition of influencers (Xu & Pratt, 2018). In recent years, the food businesses have been involved extensively in promoting their food products through influencer marketing strategy. Use of influencers is the approach of using famous personalities in advertisements to promote a brand (McCracken, 1986). Endorser application in brand promotion increases visibility of the brand in the market (Shrestha, 2019). Kotler et al. (2016) noted that, use of influencers can gain more trust compared to celebrity endorsement, as consumers tend to accept the influencers as a more trustworthy and reliable source of getting valid information. Due to the active presence in virtual media, influencers tend to have a significant impact in generating purchase intention in the customers (Kotler et al., 2016). This study tries to identify the correlational impact of purchase intention with respect to five variables – source credibility, source attractiveness, source compatibility, source familiarity, and attitude towards influencers. The study aims to bridge the gap in literature by examining factors affecting attitudes toward food influencers and their impact purchase intention. Understanding the impacts of these variables can give effective understandings of consumer behavior that can benefit marketing practitioners of food brands for developing promotional strategies for creating a positive approach. The study focuses on the following research questions:
RQ1. What is/are the key factor(s) that influence customers’ attitudes towards food influencers?
RQ2. Do consumers’ attitude towards food influencers’ impact purchase intention?
2. Theoretical Background
2.1. Marketing 4.0: Influencer Marketing
The difference between an influencer and a celebrity is often neglected by many. However, the difference is existent especially in the digital era. Influencers are mostly netizens, people who gained recognition through the internet and are active in the internet by promoting their self-made contents (Kotler et al., 2016). In the era of the internet, social media endorsers also play a vital role due to the greater ability of buzz-marketing and proven to be a comparatively cheaper option as a marketing tool for companies (Harrison, 2017; Patel, 2016; Talaverna, 2015). The emergence and growing popularity of social media led to the advent of a new marketing approach, namely, influencer marketing (Li et al., 2012). Kotler et al. (2016) highlights that, brands need to create brand affinity to ensure a positive buzz in the market and gain more market share through repurchase of new customers. A key source for creating brand affinity is to follow influencer marketing strategy (Kotler et al., 2016). The use of endorsers is considered credible, trustworthy, and knowledgeable to the generation z consumers (Lim et al., 2017).
2.2. The Concept of Purchase Intention
A consumer’s buying behavior is widely connected to celebrity endorsement (Arai et al., 2014). A number of studies suggest that a consumer’s purchase intention is correlated to influencer or endorser involvement (Goldsmith et al., 2000; Mathur et al., 1997). Purchase intention indicates the frequency and probability that an individual will buy an item (Phelps & Hoy, 1996) and refers to the probability or intention of buying a product (Burton et al., 1998). Purchase intention is correlated with word of mouth (Shrestha, 2019). Erkan and Evans (2018) suggest that E-word of mouth (E-WOM) is more effective when made by recognized personalities and has a powerful impact on online consumers’ purchase intention. Kudeshia and Kumar (2017) stress that the quantity of E-WOM can also influence the purchase intention of consumers. If the endorser has an inspiring image and popularity, the consumer’s purchase intention is affected by it as well (Staff, 2011). Purchase intention is considered a useful element in forecasting market share and estimated sales for a brand (Morwitz, 2014).
3. Conceptual Framework: Model & Hypothesis
3.1. Conceptual Model
The derived model in Table 1, is largely based on the theory of planned behavior (Ajzen, 1991), and other constructs were sourced from prior literature (Carroll, 2009; O'Mahony & Meenaghan, 1997; Ohanian, 1990; Metzger et al., 2003; Bardia et al., 2011; Erdogan, 1999; Petty et al., 1983; Till & Busler, 2000; Kamins & Gupta, 1994; Zajonc, 1968; Shimp, 2000; Armitage & Conner, 2001; Cooke & Sheeran, 2004; Bergkvist et al., 2016). The aim of this research is to determine the factors affecting consumers’ attitudes toward food influencers. It subsequently examines how the latter stimulates purchase intention.
Table 1: Formulation of Constructs based on Relevant Literature
Figure 1: Proposed Conceptual Model
3.2. Hypothesis Development
Credibility refers to the degree to which the source is perceived as having critical information or enough experience to offer a fair-minded judgment (Carroll, 2009; O'Mahony & Meenaghan, 1997). Ohanian (1990) argues that source credibility and source attractiveness are effective persuasion indicators and adds that attractiveness of source is firmly identified with endorser's appearance that could improve influence depending on amiability, likeness, or attractive quality to target the crowd. Research on advertisements identifies that endorser’s physical attractiveness has an effect on customer’s judgement towards the product (Ohanian, 1990). Messages shared by a credible source can affect customer’s trust, decisions, attitudes, and behaviors (Wang et al., 2017). An endorser who is seen as profoundly dependable and credible would prompt shoppers' lack of interest towards the promoting message, bringing about higher acknowledgment of the conveyed message (Metzger et al., 2003). A learned endorser is more powerful at convincing the customer to purchase the item (Bardia et al., 2011). As such, the hypothesis statement is as follows:
H1: Attitude towards Influencer has a significant relationship with source credibility.
A positive correlation has been identified between source attractiveness and purchase intention in a number of earlier studies (Erdogan, 1999; Petty et al., 1983). Effectiveness of a customer is directly correlated with source attractiveness (McGuire, 1985). Endorsers with appealing highlights can apply an uplifting disposition on shoppers accordingly with a buying expectation (Till & Busler, 2000). Perception towards a brand can be altogether improved by an endorser's allure (Bardia et al., 2011; Hakimi et al., 2011; Tantiseneepong et al., 2012). Therefore, the hypothesis statement is as follows:
H2: Attitude towards influencer has a significant relationship with source attractiveness.
An appropriate compatibility between the brand and the influencer may provide success in generating significant level of purchase intention (Till & Busler, 1998). Positive attitude towards the influencer’s brand can occur if the compatibility between the brand and the endorser exists (Kamins & Gupta, 1994). A coordination between an endorser and the brand is the most major objective in accomplishing shoppers' attitude (Shimp, 2000). In that regard, the hypothesis statement is as follows:
H3: Attitude towards influencer has a significant relationship with product match up.
An individual whose name influences public attention, interest, and individual value from the general population is known as a celebrity (Kotler, 2009). Familiarity means the knowledge of being aware about something partially or completely through direct or indirect experience of it (Erdogan, 1999). Customers who are provided greater exposure to the endorser creates significant positive attitude for the endorser (Zajonc, 1968). Kotler et al. (2016) noted that there is a strong connection between a customer’s positive attitude towards a brand and an endorser if the person endorsing is well known to its target customers. Thus, the hypothesis statement is as follows:
H4: Attitude towards influencer has a significant relationship with source familiarity
Attitude refers to the extent to which an individual approves a behavior before achieving it (Al-Debei et al., 2013). Individuals are more likely to embrace a behavior for which their attitudes are favorable (Armitage and Conner, 2001). Cooke & Sheeran (2004) stress that the relationship between consumer attitudes and intentions is usually more consistent when consumers are highly involved. Further research identifies attitude toward the influencer as a direct predictor to purchase intention (Bergkvist et al., 2016). The hypothesis statement is as follows:
H5: Purchase intention has significant relationship with Attitude towards Influencer.
4. Methods
4.1. Measurement
The study has two major portions. The constructs are developed based on qualitative judgments based on prior literature. The quantitative study is based upon the respondents’ participation through a survey questionnaire based on Likert-scales. The questionnaire is divided into two parts where the first part was related to demographic information and the second part contained questions regarding source credibility, source attractiveness, source compatibility, source familiarity, attitude towards influencer, and purchase intention. The scale was anchored on “5 – Strongly Agree” to “1 – Strongly Disagree”. The demographic determinants are sex, age, marital status, profession, educational background, monthly household income, most used social media, and influencer visibility or presence. Cronbach’s alpha test is conducted to determine the internal consistency of the responses, and Exploratory Factor Analysis (EFA) is conducted to ensure the accuracy of the responses to finalize the valid constructs. Multivariate regression analysis are undertaken to determine purchase intention. First, constructs present in the research instruments are source credibility, source attractiveness, source compatibility, and source familiarity as independent variables while Attitude towards influencer are considered as dependent variable. Later, attitude towards influencer is considered as independent variable while purchase intention was the dependent variable. Microsoft Excel 2019 was used for data cleaning and Statistical Package for Social Sciences (SPSS) version 26 was used for further statistical analysis. AMOS version 18 has been used to create the graphical model. The analyzed results are showcased in both graphical and tabular format.
4.1. Sample & Data Collection
The study is conclusive following a single-cross sectional data collection procedure and a non-probability sampling method. Before conducting the mass survey, a sample survey of 50 randomly picked respondents was conducted to determine the questionnaire and its constructs’ reliability. Responses were collected through Google Forms. The sample for the research was people who reside in urban areas and purchase restaurant-based foods endorsed by any influencer, one or multiple times over a year. Judgmental sampling has been followed in conducting the survey, and the participants have been chosen based on whether they had purchased any food product that is endorsed by a brand ambassador or influencer in the past. Survey was conducted on 548 respondents, and 48 responses were found to be invalid and were removed from the analysis. Thus, the final sample for the analysis is 500. Samples containing more than 200 respondents are considered to be large samples (Kline, 1998) has the ability provide valid and meaningful results (Eldred, 1987). As the study contains 500 respondents, the dataset is both large and sufficient to provide a valid result. For determining eligibility, respondents were asked if they used social media and if they had been to any restaurant or ordered/purchased any food item that was endorsed by any food influencer.
Table 2: Respondents’ Profile
5. Results
5.1. Demographic Analysis
The demographics provide interesting findings of the respondents that give a better understanding of a particular group of cohorts related to the responses. The study contains a well-balanced respondents based on gender as 56.8% of the respondents are male while 43.2% are female. 84.6% of the responses were from 18-24 age groups who are the dominant users of social media, and 87.8% of the total respondents were students. The dominant social media of the respondents were Facebook (76.6%), followed by Instagram (11.2%), Linkedin (4.8%), and Tiktok (4%).
5.2. Reliability Analysis
Cronbach’s coefficient alpha has been used to measure the internal consistency of the scales for conducting the reliability analysis. A reliable threshold value of Cronbach’s alpha has to be above 0.7 (Hair et al., 2010). Internal consistency of all the constructs is found to be satisfactory as all the values are above 0.7. No items were required to be deleted during the reliability test, as all the values showcased highest Cronbach’s alpha value and above 0.7 as well.
Table 3: Reliability Statistics
5.3. Exploratory Factor Analysis (EFA)
Exploratory factor analysis is conducted on whether influencer endorsement has an impact on the attitude towards influencer and the purchase intention. EFA gives a better understanding of the items of the constructs related to the accuracy of the responses. The items removed after multiple stages of analysis are as follows: SC1, SC3, SC5, SC6, SA1, PM1, PI1, and PI2. The factor loading values are satisfactory with KMO Coefficient of 0.876 and significance of Bartlett’s test of 0.000. All five reflective constructs in this study fulfilled the requirements, as composite reliability (CR) were above the minimum threshold of 0.7 and AVEs (Average Variance Extracted) were greater than 0.5 (Hair et al., 2016).
Based on the results presented in Table 4, it is clear that there are 6 factors that can be used for the analysis. Although some items were removed during the exploratory factor analysis, no constructs were required to be removed.
Table 4: Results of Exploratory Factor Analysis (EFA)
Figure 2: Correction of Conceptual Model
5.4. Correlation Analysis
A correlation analysis has been conducted to understand the correlations between each variable. The target of the study was to determine correlation among source credibility, source attractiveness, product match up, source familiarity, and attitude towards influencer with respect to the purchase intention. Average score of multi items for each construct was considered for the analysis. All the values were found to be statistically significant. The strongest positive correlation value has been identified between attitude towards influencer and source familiarity (r = .611, p < 0.01), followed by Purchase Intention and Attitude towards Influencer (r = .512, p < 0.01). Though there was a significant positive correlation between Attitude towards influencer and Source Credibility, the value was quite low (r = .237, p < 0.01) when compared to other variables. This identifies source familiarity to be a significantly stronger predictor for generating a positive attitude. A normal distribution or bell-shaped curve is present, as the skewness for all the variables were below ±2.0 and all variables’ kurtosis was less than the cutoff value of ±10.
Table 5: Correlation Analysis
Note: *Correlation is significant at 0.01 level (two-tailed)
Figure 3: Histogram signifying the bell-shaped curve for the data
5.5. Linear Regression Analysis
To determine significant relationships that drive purchase intention, two separate linear regressions were conducted, and both models were found to be fit. Chin (1998) reveals that the key criterion for assessing the structural model is the coefficient of determination (R-square) of the endogenous latent variables. The latter has to be higher than 0.33 for a model to be moderately specified (Chin, 1998).
For the first linear regression, as per the graphical model, the dependent variable was Attitude towards influencer, and independent variables were source credibility, source attractiveness, product match up, and source familiarity. The regression model shows that, R2 = 0.527. R2 = 0.653, is to be found for the second linear regression analysis which considered Purchase Intention as dependent variable while attitude towards influencer as the independent variable.
As demonstrated in Table 6, H2 of source attractiveness (β = .107, p < 0.01), H3 of product match-up (β = .044, p < 0.01), H4 of source familiarity (β = .534, p < 0.01), and H5 of attitude towards influencer (β = .512, p < 0.01) are found to be statistically significant while H1 of source credibility (β = -.012, p > 0.10) was found as statistically insignificant.
Table 6: Path Coefficients of the Research Hypothesis
Note: *insignificant at 10% level of significance
According to Chin (1998), models that have a moderate R square level (above 33%) has the ability to explain the interrelationships of the constructs. As both models in this study has R square level above the minimum limit, both models have the ability to explain purchase intention through the constructs present in the study.
6. Discussion
6.1. Theoretical Implication
The study possesses two vital theoretical implications. First, attitude towards the influencer is positively influenced by source credibility, source attractiveness, and source familiarity, which are consistent with the findings previously mentioned in the literature (Kotler, 2009; Erdogan, 1999; Kotler et al., 2016; Petty et al., 1983; Zajonc, 1968; Till & Busler, 1998; Kamins & Gupta, 1994). Source familiarity was the strongest factor affecting attitude towards the influencer, followed by product match-up and source attractiveness. The finding aligns with the previous study that claimed if an endorser is well-known to the audience; it generates a positive attitude for the endorser (Zajonc, 1968). However, the study also finds that there is no significant relationship between attitude towards influencer and source credibility, thus, it opposes the findings of certain studies (Ohanian, 1990; Metzger et al., 2003; Wang et al., 2017). However, a study claimed source credibility to be a weak predictor for generating attitude (Schweiger & Cress, 2019). Schweiger & Cress (2019) noted that predetermined perspective towards an influencer often neglects credibility of the endorser. The study further finds a strong variation between purchase intention and attitude towards influencer that indicates that purchase intention can be explained by attitude towards the food influencer. This was also found to be consistent with the previous study (Bergkvist et al., 2016). This implies that food influencers not only influence consumers’ attitudes toward a certain brand but also create purchase intentions. These theoretical implications lead to conclude that influencer marketing is a good alternative for food companies aiming to create purchase intention among existing and potential customers.
6.2. Practical Implication
The findings of the research provide two practical implications for the food industry practicing or willing to practice influencer marketing. From the study, it is clarified that attitude towards influencer is highly recommended to create a positive internet-based word of mouth or E-WOM. However, in terms of food industry influencers, attitude towards influencers is significantly associated with the attractiveness, compatibility or product match up, and familiarity of the influencer. Source Familiarity is the strongest predictor for generating a positive attitude towards the influencer. Brand Practitioners may keep these factors identified through the study for effective selection of influencers for food marketing. Second, the study’s finding of attitude towards influencer significantly impacting purchase intention gives a clear indication that if the food brand is willing to generate purchase intention through influencer marketing, the brand must keep a focus on factors that generate a positive attitude towards the influencer. Thus, the study serves as a guide for the management when choosing influencers for the food brands.
6.3. Scope of Future Research
The study is subject to certain limitations despite the theoretical and practical implications. The study was conducted on specific geographical area only; thus, similar studies conducted in other geographical locations can provide a much precise finding that mitigates the social, cultural and economic differences thus can strengthen the argument. The study is also limited to openly accessible literature only thus adding more literature can also strengthen the arguments. It is also recommended that qualitative study can be conducted focusing on the topic that can bring out interesting factors and outcomes relevant to the food industry.
7. Conclusion
The contribution of this study to the existing knowledge was to determine the significant factors influencing purchase intention of food brands when influencer marketing is conducted. From the sample of 500 random and valid responses, a model was developed to determine the attitude towards influencer that ultimately creates the purchase intention. To determine the factors that affect the attitude, 4 constructs were identified that may possess probable relationship for generating attitude and finally purchase intention. The study found source attractiveness, product match up, and source familiarity to be significant factors that impacts attitude towards influencer while finding product source credibility to be an insignificant factor influencing attitude towards influencer. As previous studies suggested, this study also identifies the ability of Attitude towards Influencer in generating purchase intention. The study found that if a food brand wishes to initiate influencer marketing strategy, the brand must consider whether the customers will have a positive attitude towards the influencer, and in order to generate a positive attitude towards the influencer, the brand must ensure that the influencer is attractive, compatible, and familiar, with familiarity as the prime concern. This research adds to the body of the literature by understanding consumers’ perceptions of food influencers and their impact on attitudes and purchase intentions.
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