Abstract
E-commerce has grown steadily since internet access became more available in the mid-1990s. Informativeness plays a key role in online shopping decisions. Potential customers usually collect useful information and do a comparison before considering the purchase. Electronic word-of-mouth (eWOM) is considered a reliable source of information. Customer reviews and influencer reviews can be considered eWOM. They represent customers’ sharing of experience and evaluation of a product or service with other potential shoppers. There is abundant evidence concerning the influence of eWOM on purchase intention. However, there are few studies on influencer reviews and purchase intention. This study aims to investigate the impact of customer review and influencer review to purchase intention and the mediating role of trust to those relationship. A quantitative experimental study (2 × 1) was conducted. Two hundred respondents from three cities in Greater Jakarta were divided into two groups to self-rate their opinion on customer review, influencer review, trust and purchase intention. Data collected was analysed PLS using SmartPLS. The study results showed that influencer review has a positive impact on purchase intention. On the other hand, customer review failed to show its influence. Trust as a moderating variable was also not validated in this study.
Keywords: Customer review, Influencer, Trust, Purchase intention, Social media, Technology adoption, Business management, Marketing, Digital media
Customer Review; Influencer; Trust; Purchase intention; Social Media; Technology Adoption; Business Management; Marketing; Digital Media.
1. Introdution
E-commerce has grown steadily since internet access became more available in the mid-1990s. In 2019 in the US, the share of e-commerce was 11.1% of total retail, up from 5.8% in 2013 [1] and expected to increase to 13.7% by 2021. In Indonesia, the share of e-commerce of total retail is only 3% [2]. Considering the preference of the younger customer for online shopping, the e-commerce sector in Indonesia is expected to grow significantly.
Informativeness plays a key role in online shopping decisions [3]. Potential customers collect useful information and compare it before deciding on the purchase [3], and electronic word-of-mouth (eWOM) is considered a good source of information. Customer reviews and influencer endorsements can both be considered eWOM because they represent customers sharing their experience evaluation of a product or service with other potential shoppers [4]. When customers share their good experiences, it shows customer satisfaction with the product [5]. Literature on eWOM has generally used customer reviews as an example of eWOM. The influence of eWOM on purchase intention has been proved by various authors [6, 7, 8, 9]. Customer reviews play an important role in online shopping decision-making. Ninety-one percent of customers claimed that they read customer reviews before making purchasing decisions [10].
On the other hand, the literature on the effectiveness of influencer endorsements on purchase intention are still limited. While the idea of someone ‘influential’ might be convincing, there is very little evidence showing that influencers actually improve performance [11]. There are limited scholarly research examining the relationship between influencers and performance [12]. In December 2019, a search in Science Direct for the keywords ‘Influencer’ and ‘Purchase Intention’ for all years only yielded 32 results, while there were only seven results in Google Scholar for all years for the same search period and similar keywords. Despite the limited research available on influencer endorsements, marketers in many organisations plan to spend heavily on influencers [13]. This study aims to confirm the influence of customer reviews on purchase intention and provide evidence of the relationship between influencer endorsements and purchase intention. The other goal of this study is to reconfirm the moderating effect of trust in the reviewer on purchase intention. The premise is that if the customers trust the reviewer, both for customer reviews and influencer endorsements, they are more likely to have a purchase intention.
This paper is structured as follows: the next section presents a literature review on signalling theory, eWOM, customer reviews, influencer endorsements, trust and hypothesis development. Thereafter, the methodology of the empirical study is described and the findings are presented. Finally, the conclusion, limitations and recommendations for further research are given.
2. Literature review
2.1. Signalling theory
Signalling theory has become increasingly popular in strategic management studies [14]. This theory focuses on the issue of decision-making and how the parties involved use signals to reduce uncertainty related to making decisions in cases of incomplete and asymmetrical information [14]. In signalling theory, the signal can be both negative and positive. Those signals are important for the receivers in making decisions.
The birth of signalling theory can be traced back to the seminal work of Spence in 1973 [15] on the labour market, where he introduced asymmetric information for decision-making in an economic model. Signalling theory is concerned with reducing the effect of asymmetric information between two parties [16]. According to signalling theory, there are three elements: signaller, signal and receiver [17]. The signaller is the individual who obtains information about an individual, product or organisation. The signal is the information itself, which can be both positive and negative. The receiver is the third element in the signalling timeline. The receiver is the one who lacks information about an individual, product or organisation [16].
In online shopping, potential customers are faced with perceived risks and uncertainties. They cannot evaluate the products directly and physically. The availability of other parties who can share their experiences, evaluations and perceptions of products or services in the form of eWOM information can help potential customers in reducing asymmetric information. This will reduce potential customer perceived risk and increase potential customers’ confidence in making purchase decisions.
2.2. E-WOM
WOM is defined as direct communication from person-to-person of an opinion about a product and/or service [18]. The diffusion of WOM is an important mechanism for information to reach a large population, thereby possibly influencing 1) public opinion; 2) adoption of innovation; and 3) the market share of a new product or brand awareness [19]. WOM is important for customers’ buying decisions [4]. EWOM has been reported to have greater power than traditional WOM [5] because it reaches a large population rapidly [20].
With the increasing trend of online shopping, since consumers cannot evaluate the product directly and physically, eWOM has become a prominent source of information for potential customers [20, 21]. Informativeness is one of the most significant factors influencing a shopper's decisions with respect to online purchases [3]. The online consumer would like to collect and compare useful information when considering a product purchase, and informativeness aids the consumer in evaluating alternative products and in making the best choice [3]. EWOM is differentiated from traditional WOM by the online context as a way of exchanging information regarding the usage and characteristics of products and services [4]. It differs from the traditional oral form of interpersonal communication among friends or acquaintances [10], which is private in nature, in that eWOM can be shared with others openly [22].
EWOM is defined as internet-mediated opinions and recommendations on products and services from peers [23]. EWOM can be “any positive or negative statement made by potential, actual or former customers about a product or company that is made available to a multitude of people and institutions via the internet” [4]. It is an informal communication from one customer to other potential customers about the usage, ownership, or characteristics of certain goods and services or their sellers [24].
For online purchasing, eWOM plays an important role in helping customers make purchasing decisions while considering the perceived risks involved [10]. EWOM serves as a decision-making tool. Many potential online shoppers wait and observe others before making such decisions, and information from others is known to increase consumer confidence [24].
Previous studies have shown the consequences of eWOM [10], argued that positive eWOM can strengthen the relationship between consumer trust and intention to shop online. Setiawan et al. (2014) showed that eWOM has an indirect effect on satisfaction and loyalty, mediated by destination images in the tourism industry [25], while Yoo et al. (2013) showed a direct influence of eWOM on loyalty [26]. The direct influence of eWOM on purchase intention has been reported by various authors. Di Pietro et al. (2012) in [13] showed the relationship between eWOM and intention to choose a travel destination. EWOM's direct influence on purchase intention has also been reported by [6, 7, 8, 9]. Other consequences of eWOM include trust in e-commerce. EWOM information has been reported by [27] to have a positive and significant impact on the trust of the seller. Trust and online reputation are influenced by eWOM, as reported by Anderson and Barton, 1989. Credible and trusted eWOM influences the reputation of e-commerce [28]. Customer reviews and influencer endorsements can be considered electronic word-of-mouth (eWOM) because they represent customers sharing their experience and evaluation of a product or service with other potential shoppers [4].
2.3. Customer reviews
Electronic customer reviews are defined as peer-generated product evaluations posted on company or third-party websites [29]. Online shopping, just like traditional shopping, is a social activity. People's purchase decisions tend to be influenced by their interactions with others [30]. Online customer reviews can reduce the risks perceived by consumers [10] and improve their degree of satisfaction [24], as well as their efficiency in making decisions [24]. During their online search for a product, consumers encounter dozens or even hundreds of pieces of product information and alternatives. Customer reviews give people more reason for a decision and increase the decision-maker's confidence. These customer reviews provide additional information, expert reviews and personalised advice, which can add value to potential customers [29]. [10] showed that 91% of participants read customers' reviews before purchasing a new product or service, while 46% of the participants in that study said that their decisions were influenced by those comments. Seventy-seven per cent of online shoppers in the US reported using consumer-generated reviews and ratings to help them make decisions.
Online reviews are considered credible because the contents are real users' own experiences with the products or services. The users are perceived to have no vested interest and no intention to deceive the readers [31]. Longer reviews that include details of the products and specific information about the products increase the quality of the review. The number of peer reviews can also reduce uncertainty concerning the product's quality, while consistency between comments from one user to another improves the credibility of the review [24]. Customer reviews have been known to improve sales significantly [24] and to increase the credibility of the website. Reviews make consumer visits more attractive and increase the time spent on the website [29]. They also enhance consumer confidence in the product [10].
2.4. Influencer endorsements
Influencer marketing is the most important new approach to marketing. Influencer marketing is a type of marketing that focuses on certain key individuals rather than the target market as a whole, because these individuals have been identified as prospective buyers. Thus, influencer marketing involves marketing activities around these “influencers” [32].
Social and influencer marketing are arguably the hottest concepts in online advertising at the moment [33]. Most organisations that advertise online must have a “social” strategy [34]. Deploying influencers, such as Instafamous people, for branding has become an important aspect of social media marketing campaigns [35]. The trend of the “Influencer Marketing Goldrush” is about to explode in popularity as a marketing tactic. A recent survey of 1,300 marketers found that 74% planned to invest in influencers over the next 12 months. According to Hubspot, 71% of consumers were more likely to make a purchase when the product was mentioned in social media, and 92% would trust an influencer's marketing review of a brand when making a purchasing decision [13].
An influencer is defined as “someone who exhibits some combination of desirable attributes—whether personal attributes like credibility, expertise, or enthusiasm, or network attributes such as connectivity or centrality—that allows them to influence a disproportionately large number of others” [19]. Influencers are at the forefront of social trends. They could be innovators who create new ideas, concepts or content that regularly grab the attention of social media. They could be early adopters or those who discover trends before anyone else, and enliven them with their own creativity, spreading them further on social media [33]. They are individuals who are effective in spreading messages about new products, starting and popularising new trends and driving up sales [12]. Influencer marketing is the process of developing a relationship between such influential individuals and potential buyers [32].
Influencers are known to have high numbers of followers, which enables them to have a wide reach [35]. They are considered by their followers to have learnt about different topics and products. With their popularity and their role as opinion leaders, influencers are more likely to influence sales. A Marketing Dive study stated that 41% of marketers claimed that marketing campaigns using influencers were more successful than traditional ones [33].
2.5. Trust
Trust plays an important role in all transactions, considering the uncertainty and the risk involved. In e-commerce, trust is crucial and one of the most influential factors [30]. Consumers are unlikely to conduct an online transaction if they do not trust the seller [36]. Trust is defined as “the willingness of a party to be vulnerable to the actions of another party based on the expectation that the trustee will perform a particular action important to the trust, irrespective of the ability to monitor or control that other party” [37].
In e-commerce, trust is a belief in the good faith of sellers that consumers have after reviewing their characteristics [36]. Another definition of trust in the context of e-commerce is as a subjective belief that the seller will fulfil their obligations, as those obligations are understood by the consumer [36]. Trust is a “willingness to rely on an exchange partner (i.e., reliable person who keeps promises [38]. Trust can be bestowed upon a person, a product, an organisation, an institution or a role [9]. In this study, trust is a subjective belief of potential customer to a person who provides customer review or endorsement.
Trust has been known to facilitate business transactions between two parties who are lack of prior experiences in mutual confidence. It means not only reducing perceived risk, but also enhancing the customer's perceived value. Trust has a moderating effect on the process and behaviour [39] and it can help to reduce the anxiety, vulnerability and uncertainty that may be caused by the transaction, resulting in greater satisfaction. Trust can create a positive attitude towards transaction behaviour, which will lead to transaction intention [30], and is important in creating expected and satisfying results in online transactions [9]. It has been shown in various studies that trust positively influences customers' online purchase intentions, and the higher the degree of consumers' trust, the higher the degree of consumers' purchase intention [9]. Trust in e-reviews also has a positive impact on choice [28, 40].
2.6. Hypothesis development
Customer reviews and influencer endorsements are part of electronic word-of-mouth (eWOM) because they represent customers who are sharing their experiences and evaluations of products or services with other potential shoppers [4]. Peer-generated reviews have been known to help potential customers in making purchase decisions. They reduce the perceived risk and increase confidence in and attitude towards the products [10].
Positive eWOM can strengthen the relationship between a consumer's trust and intention to shop online [10]. Bokunewicz and Shulman (2016), referring to Di Pietro et al. (2012) stated that there is a positive relationship between eWOM and intention to choose travel destinations. The authors in [6, 7, 8] and [9] agreed that eWOM has a direct influence on purchase intentions (see Figure 1).
H1:
Customer reviews have a positive influence on purchase intention
Influencers have a high number of followers. High numbers of followers enable influencers to have a wide reach [35]. With high likability and their role as opinion leaders, influencers are more likely to influence sales. A Marketing Dive study stated that 41% marketers claimed that marketing campaigns using influencers are more successful than traditional ones [33].
H2:
Influencer endorsement has a positive influence on purchase intention
Online consumers tend to gather information before making decisions because learning about the products and services from other consumers’ experiences could reduce the perceived risk and increase the confidence of online shoppers. Customer reviews and influencer endorsements are considered trusted and credible sources of information.
Trust plays an important aspect in the transaction, considering the uncertainty and risk involved. In e-commerce, trust is crucial and one of the most influential factors [30]. Consumers are unlikely to make an online transaction if they do not trust the seller [36]. Trust can create a positive attitude toward transaction behaviour, which leads to transaction intention [30].
The resulting hypotheses are:
H3:
Trust moderates customer review, leading to purchase intention
H4:
Trust moderates influencer endorsement, leading to purchase intention
Figure 1.
Research framework.
3. Methodology
3.1. Research design
This study carried out experiments with a two (customer review vs influencer endorsement) by one (purchase intention) between-subjects design (2 × 1). Two hundred respondents were assigned to one of two conditions. One hundred respondents received the customer review and the other 100 had the influencer endorsement. A purposive sampling method was used for an online survey via respondents’ mobile phones. Each participant was identified with an individual number. All respondents were university students from Jakarta, Bogor and Tangerang. They represented young consumers.
3.2. Experimental stimulus product
The smartphone was selected as the experimental stimulus for two reasons. First, the respondents were interested in knowing other consumers' views on the target product. Second, smartphones appealed to and were therefore readily accessible and purchased by the respondents. The present research, therefore, selected a smartphone that met those two conditions. Smartphone penetration is very high in Indonesia and thus consumers often purchase this product. Moreover, previous studies also refer to online reviews of high-end products, such as smartphones, as a relevant stimulus product. In the current study, the smartphone had a fictional brand name of Smart Ace. The study's design was based on the experimental study done by [31]. In this study, all the customers' names, influencers, website names and brand names used were fictitious. The study was an academic study, not for commercial purposes, which was also indicated at the beginning of the questionnaires.
3.3. Online consumer review and influencer endorsement
Various review comments posted on company and consumer websites create an online customer review. Based on the preliminary study, customer reviews are more trusted if pictures are posted, there are many reviews and there is a mixture of negative and positive reviews. Therefore, a fictitious list of customer reviews was designed, which included those criteria (Appendix 1).
Fictitious influencers were designed by mimicking two influencers (one male and one female) with more than 100,000 followers on Instagram. One of their typical product reviews was copied, but the attributes were changed to suit the smartphone (Appendix 2).
3.4. Procedures and participants
The experiment was online and sent to participants directly via WA application, which is one of the most popular communication applications in Indonesia. The participants were 200 students at four Indonesian universities, one in Jakarta, one in Bogor and two in Tangerang. Selection of the respondents was done using the purposive sampling method. There were five lecturers from four universities involved in this study. Each lecturers had to have two classes. Each class was assigned to one treatment. For example, lecturer A had two classes, Class X and Class Z. All students from Class X were asked to respond to the Influencer Questionnaire and all students from Class Z were asked to respond to the Customer Review Questionnaire. Each university had 50% male respondents and 50% female respondents, with 25% male customer reviews and 25% female customer reviews, and 25% male influencer endorsements and 25% female influencer endorsements.
For customer reviews, participants were asked to imagine they were searching for information about a smartphone, and the web pages they searched had a consumer-generated information aggregator (http://gadgetplace.com) for the product called Smart Ace (Appendix 1). For the influencer endorsements, participants were invited to imagine visiting Instagram pages of an influencer to find their review of the product (Appendix 2).
In part one, after reading the first page of the experimental website or Instagram page, in which the fictitious customer reviews and influencer endorsements were shown, the participants were asked to give information about their gender, year of birth, campus location and hometown. Afterward, respondents were guided to part two of the survey, which related to variable statements. Participants were asked to rate the reviews concerning usefulness, trust and intention to purchase the reviewed product, attitudes, items for manipulation check, and other online review-related questions. All content of the questionnaires used casual Bahasa Indonesia, which is common language used by younger people.
3.5. Measurements
All measurement scales used in this study (Table 1), except items used in the manipulation check and demographics, used a framework from a previous study. Customer review and influencer endorsement measures used four items, each modified from [41], trust measures used three items modified from [36] and purchase intention measures used four items modified from [42].
Table 1.
Measures.
| Customer Reviews | CR01: I often read customer review to know product impression by others |
| (Jalilvand, 2012) | CR02: To make sure I buy the right product, I often read customer review |
| CR03: I frequently gather information from customer review to help me choose the right product | |
| CR04: When I buy a product, customer review make me confident in purchasing the product | |
| Influencer Endorsement | IR01: I often read influencer review to know product impression by others |
| (Jalilvand, 2012) | IR02: To make sure I buy the right product, I often read influencer review |
| IR03: I frequently gather information from influencer review to help me choose the right product | |
| IR04: When I buy a product, influencer review make me confident in purchasing the product | |
| Trust | TR01: This product review has integrity |
| (Ponte, 2015) | TR02: This product review is reliable |
| TR03: This product review is trustworthy | |
| Purchase Intention | PI01: After reviewing the comment, the likelihood of purchasing this smartphone is high |
| (Lien, 2015) | PI02: If I am going to purchase smartphone, I would consider this smartphone |
| PI03: The probability that I would consider purchasing this smartphone is high | |
| PI04: My willingness to purchase this smartphone is high |
A six-point Likert scale (from 1 strongly disagree to 6 strongly agree) was used for respondents to rate their opinion. With a six-point Likert scale, the mid-point is omitted to avoid a social desirability bias [43]. Additional demographic information, such as age, gender, educational background and respondent's origin, was also requested for descriptive analysis.
All data collected were analysed using descriptive analysis and PLS with SmarPLS. There are two stages of analysis. The first stage is the outer model, which is to determine the validity and reliability of each research indicator. The second stage is the inner model, which aims to determine the relationship between latent variables.
4. Results
4.1. Descriptive analysis
This study compared the two groups, which were Influencer Endorsement and Customer Review. From a total of 187 participants, 104 were in the Influencer Endorsement group and the Customer Review group. The majority (98.4%) of respondents were born between 1995 and 2005 (Generation Z). They were 49.7% male and 48.1% female. Ninety-two per cent of respondents were university students. Their campuses included Jakarta (12.3%), Tangerang (39.6%), Bogor (39.6%) and others (5.9%) (see Table 2).
Table 2.
Respondent characteristic.
| Respondent Characteristic | Influencer Review |
Customer Review |
Total |
||||
|---|---|---|---|---|---|---|---|
| Number | % | Number | % | Number | % | ||
| Year of Birth | 1995–2005 | 103 | 99 | 81 | 97,6 | 184 | 98,4 |
| Gender | Male | 55 | 52,9 | 38 | 45,8 | 93 | 49,7 |
| Female | 47 | 45,2 | 43 | 51,8 | 90 | 48,1 | |
| No Answer | 2 | 1,9 | 2 | 2,4 | 4 | 2,1 | |
| Educational Background | High School Graduate | 3 | 2,9 | 2 | 2,4 | 5 | 2,7 |
| University Students | 94 | 90,4 | 78 | 94 | 172 | 92 | |
| University Graduate | 7 | 6,7 | 3 | 3,6 | 10 | 5,3 | |
| Campus location, if student | Jakarta | 10 | 9,6 | 13 | 15,7 | 23 | 12,3 |
| Tangerang | 44 | 42,3 | 30 | 36,1 | 74 | 39,6 | |
| Bekasi | 0 | 0 | 2 | 2,4 | 2 | 1,1 | |
| Bogor | 40 | 38,5 | 34 | 41 | 74 | 39,6 | |
| Others | 5 | 4,8 | 4 | 4,8 | 9 | 4,8 | |
| Place of Origin | Jabodetabek | 61 | 58,7 | - | - | 61 | 32,6 |
| Others | 43 | 41,3 | - | - | 43 | 23 | |
| No Answer | - | - | 83 | 100 | 83 | 44,4 | |
| Total | 104 | 100 | 83 | 100 | 187 | 100 | |
The descriptive analysis showed that, for all questions, the average score was more than three out of six. The highest average was the Influencer Endorsement, with an average of 4.63. The lowest score was Purchase Intention from Customer Reviews at 3.46 (see Table 3).
Table 3.
Descriptive analysis of variables.
| Questions | Influncer Review | Customer Review |
|---|---|---|
| Trust to Influencer/Customer Review | 4,34 | 3,64 |
| Influencer/Customer Review | 4,63 | 4,13 |
| Purchase Intention | 4,13 | 3,46 |
4.2. Measurement model analysis
This study aimed to examine the effect of influencer endorsements and customer reviews on trust moderated purchase intention. Data were processed using structural equation modelling with partial least square (PLS), which is a variant-based alternative. In structural equation modelling, PLS uses two stages of evaluation. The first stage is the outer model, which is to determine the validity and reliability of each research indicator. The second stage is the inner model, which aims to determine the relationship between latent variables.
All indicators from all related variables showed loading factors >0.5. The composite reliability (CR) for all variables was also >0.7. The AVE score for all variables was also >0.5. Therefore, it can be concluded that the measurements were reliable and valid (Table 4). Discriminant validity test with a Fornell-Larcker criterion showed that the root square of AVE of all variables was the highest between variables, compared to other variables. This showed that all tested variables had good discriminant validity.
Table 4.
Measurement model analysis.
| Latent Variable | Indicator | Loading Fcator |
T-Stat | AVE |
Remark | CR |
Remark |
|---|---|---|---|---|---|---|---|
| (>0,5) | (>0,5) | (>0,7) | |||||
| Influencer Review | |||||||
| Trust to Influencer Review | IFTR01 | 0,886 | 25,261 | 0,82 | Valid | 0,932 | Reliable |
| IFTR02 | 0,937 | 69,836 | Valid | ||||
| IFTR03 | 0,893 | 31,774 | Valid | ||||
| Influencer Review | IF01 | 0,819 | 14,177 | 0,751 | Valid | 0,9 | Reliable |
| IF02 | 0,899 | 32,383 | Valid | ||||
| IF03 | 0,88 | 37,516 | Valid | ||||
| Purchase Intention | PI01 | 0,702 | 10,685 | 0,601 | Valid | 0,883 | Reliable |
| PI02 | 0,827 | 19,497 | Valid | ||||
| PI03 | 0,723 | 9,963 | Valid | ||||
| PI04 | 0,812 | 14,023 | Valid | ||||
| PI05 | 0,806 | 16,415 | Valid | ||||
| Customer Review | |||||||
| Trust to Customer Review | CRTR01 | 0,812 | 11,234 | 0,766 | Valid | 0,907 | Reliable |
| CRTR02 | 0,883 | 21,14 | Valid | ||||
| CRTR03 | 0,927 | 45,939 | Valid | ||||
| Customer Review | CR01 | 0,865 | 3,984 | 0,778 | Valid | 0,913 | Reliable |
| CR02 | 0,883 | 3,805 | Valid | ||||
| CR03 | 0,898 | 3,876 | Valid | ||||
| Purchase Intention | PI02 | 0,881 | 25,971 | 0,775 | Valid | 0,932 | Reliable |
| PI03 | 0,815 | 10,909 | Valid | ||||
| PI04 | 0,921 | 43,065 | Valid | ||||
| PI05 | 0,899 | 29,668 | Valid | ||||
4.3. Structural model analysis
In this study, several structural model tests were carried out, namely prediction relevance (Stone-Geisser's Q2) and R-square test. The Q2 test result showed that Q2 for all relationships between variables was more than zero. This was evidence that the model had predictive relevance. The R-square of the Influencer group was 0.505. This shows that the Influencer Endorsement variable moderated by Trust in Influencer Endorsement had an influence of 50.5% on Purchase Intention, while the remaining 49.5% was influenced by other variables. The coefficient of determination (R-square) found in the Customer group was 0.323, which shows that the Customer Review variable moderated by Trust in Customer Review had an influence of 32.2% on Purchase Intention, while the remaining 67.7% was influenced by other variables (Figures 2 and 3).
Figure 2.
Path analysis of structural model (bootstrapping) - influencer review.
Figure 3.
Path analysis of structural model (bootstrapping) - customer review.
4.4. Hypothesis testing
Table 5 shows that the influence of Influencer Endorsement on Purchase Intention had T-Sat 6.299 and P-value 0.000. Both figures were higher than the standard reference; therefore, H1 was accepted. The influence of Customer Review on Purchase Intention had T-Stat 0.357, which was lower than T-table (1.96), and P-value 0.722, which was higher than 0.05. This showed that Customer Review did not significantly influence purchase intention. Therefore, H2 was rejected. The analysis between groups showed that T-value was 3.802, which was higher than T-table 1.96. Therefore, it can be concluded that the two groups were different.
Table 5.
Hypothesis testing – influencer and customer review to purchase intention.
| Relationship | Path | T-Stat | P Values | T total | Conclusion |
|---|---|---|---|---|---|
| Influencer Review-> Purchase Intention | 0,535 | 6,299 | 0,000 | 1,96 | H1 accepted |
| Customer Review-> Purchase Intention | -0,045 | 0,357 | 0,722 | 1,96 | H2 rejected |
| Moderating Effect 1 (Influencer Review∗Trust) -> Purchase Intention | 0,073 | 0,881 | 0,379 | 1,96 | H3 rejected |
| Moderating Effect 1 (Customer Review∗Trust) -> Purchase Intention | 0 | 0,001 | 0,999 | 1,96 | H4 rejected |
Hypothesis testing for the moderating effect of Trust in Influencer Endorsement to Purchase Intention showed that T-Stat was 0.881 and P-value 0.379. Therefore, H3 was rejected. T-Stat and P-value of the moderating effect of trust in Customer Review to Purchase Intention were 0.001 and 0.999 respectively. H4 was rejected based on those results.
Furthermore, the effect of trust was tested to see whether it had a direct effect on purchase intention. Trust, both in Influencer Endorsement and Customer Review, showed T-Stat higher than T-table (T-Stat was 3.789 for Trust in Influencer Endorsement and 5.481 for Trust in Customer Review) and the P-value was <0.05 (P-value = 0.000 for both Trust in Influencer Review and Trust in Customer Review). From the above hypothesis testing, it can be seen that trust does not have a moderating effect, but it has a direct effect. Therefore, it can be concluded that trust is a predictor variable, not a moderator.
5. Discussion
The results of this study provide further evidence that eWOM influences purchase intention. This shows that in online shopping decision-making, information from ‘experienced’ customers is considered valuable by potential customers. In online shopping, eWOM plays an important role in reducing the asymmetric information of potential customers. Previous studies showed that eWOM had a positive influence on purchase intention [10]. and [24] have shown how eWOM helps customers by reducing uncertainty and increasing their purchase confidence. The evaluations of ‘experienced’ customers can reduce the uncertainty and perceived risk, and therefore eWOM influences decision-making for purchases.
However, this study also showed that not all eWOM influences purchase intention. Influencer endorsement has a positive impact on purchase intention, but the customer review failed to show an influence on purchase intention. There are several explanations as to why the customer review did not significantly influence purchase intention. The first issue is trust. Information is valued based on the reliability. One of the source of reliability is trusted source. In this study, the information that participants got from other customers’ reviews seemed not to be very well trusted. The average score for trust in customer review was only 3.64 out of 6, unlike score for trust from influencer which was higher (4.3). This means that most of the participants only slightly agreed that they trusted the customer reviews [12]. argued that a feeling of closeness creates a strong attachment, which leads to higher trust. In this study, it seems that the participant “customers” could not really relate or closely attach to the other customers who had written the reviews; therefore, any information given did not increase their confidence enough to purchase.
The other explanation relates to the information itself. Informativeness is considered the most significant factor influencing customers' decisions in online shopping [3]. To become valuable, information should be of a high quality. High-quality information may help customers to know a product better and make better decisions [3]. In online customer reviews, quality is often the issue. Most of the time, customers only write a short, unspecific review. Many will only comment with ‘like’ and give a rating without any further explanation [29]. confirmed that a review that is deep, long and specific helps to increase confidence.
The last possible explanation relates to the product itself. In this study, a premium mobile phone was used as the target product. It was considered expensive for most of the respondents in this study. To spend a lot of money, getting full information is important [44]. also confirmed that the types of products influence customers’ attitudes toward online shopping. The more expensive the product is, the more risk the customer is taking. Consumers need more information to reduce their uncertainty, and customer reviews alone are not enough as an information source to support their decision-making.
Unlike a customer review, it seems that an influencer endorsement has a positive influence on purchase intention. An influencer has a high number of followers; therefore, their message will reach a large number of people [35]. stated that this wide reach can leverage the power of WOM and, at the same time, also create a huge amount of discussion. ‘Group’ opinion and consensus can be informally built. The high number of followers also influences the level of this likeability. When the majority of group members ‘like’ a post, it influences the opinion of other followers, which will become more similar to the rest of the group.
Furthermore, influencer endorsement also involves the role of leadership. When a group of people consider someone as ‘their’ leader, they will trust this person. Trust has been known to be a determinant of decision-making. In this case, the perceived leadership role borne by the influencer fosters a level of trust in his/her followers. The followers may know that the influencer is paid to post product endorsements; however, they may also consider that the influencer has his/her reputation and their followers' trust to keep, and therefore he/she will only endorse a good product. The followers also feel that they have a good connection with the influencer. A study from [21] showed that strong and weak ties have a different impact on purchase intention. Unlike customers, whom the consumers consider ‘unknown’, followers feel they have a ‘strong tie’ to the influencer. Therefore, their opinions matter and they are trusted.
The results of the study show that not all types of eWOM are effective at influencing purchase intention. The type of product influences what type of eWOM is effective. In this study, for luxury products, such as an expensive smartphone, customer review was not effective. The information from customer reviews was less trusted and was therefore considered less valuable. For luxury products, influencer endorsement is considered more valuable by potential customers. Besides the factor of trust, it seems that, for luxury products, ‘opinion leader’ status also plays an important role. An influencer is considered ‘the leader of his/her pack’, and therefore their opinion matters.
Trust has been studied extensively, particularly its influence on intention. It has been studied for its role as a direct variable [30] or a moderator variable [39]. Trust plays an important aspect in the transaction, considering the uncertainty and risk involved. In e-commerce, trust is crucial and one of the most influential factors [30]. Consumers are unlikely to make an online transaction if they do not trust the seller [36]. Trust can create a positive attitude towards transaction behaviour, which leads to transaction intention [30].
This study failed to show the moderating effect of trust on customer reviews and influencer endorsements to purchase intention. This study also failed to show that the higher the level of trust in the review, the higher the purchase intention. However, the alternative model showed that trust was not a moderator but an independent variable, which influenced purchase intention directly.
This phenomenon can be explained by referring to signalling theory. “Signals support the identification of an interacting partner as either trustworthy or untrustworthy during the relationship” [45]. Trust acted as a moderator when the partner was assessed during the relationship by observing the partner's observable signal. In this study, there was no contact between the influencer and the respondent. Therefore, the relationship between trust in the influencer's endorsement and purchase intention was not a moderating effect, but a direct effect. Further study is needed to see whether the role of trust is independent or mediating.
6. Conclusion
Informativeness plays a key role in online shopping. Electronic word-of-mouth (eWOM) is considered a good source of information. Customer reviews and influencer endorsements can be considered eWOM because they represent customers sharing with other potential shoppers their experience and their evaluation of a product or service. This study shows that not all types of customer review are effective in influencing purchase intention. For luxury products, influencer endorsement, but not customer review, influences purchase intention. This study, however, failed to show the moderation effect of trust on the relationship of influencer endorsement to purchase intention.
6.1. Theoretical implication
The results of this study provide further evidence that eWOM influences purchase intention, although not all types of eWOM influence purchase intention. This study showed that influencer endorsements had a positive impact on purchase intention, but customer reviews failed to show an influence on purchase intention. Trust as a moderating variable was also not validated in this study. This study confirms that not all types of eWOM can influence purchase intention. The influence of different types of eWOM depends on different types of products.
This study also contributes to the literature on influencer endorsements, which is currently still limited. Further research into influencer endorsements’ effects on purchase intentions should be carried out extensively, considering the huge sums of money involved in this activity.
6.2. Managerial implication
Influencer marketing is a hot trend and 41% of marketers claimed that they will use influencers in their upcoming marketing campaigns. However, studies that show the effectiveness of influencer endorsement are still limited. This study provides empirical evidence on how influencer endorsement positively influences purchase intention. This evidence can provide insight to marketers that using influencer endorsement in their marketing campaigns is effective. This study also showed that not all types of eWOM are effective. For perceived expensive products, influencer endorsement is effective, but not customer review.
6.3. Limitations and further research
This study has some limitations. The first limitation was the use of a fictitious brand. For expensive products, such as smartphones, the brand influences decision-making. Therefore, the next study should consider the use of a real, exclusive brand. The second limitation was the use of fictitious websites and influencers. The next study should consider using real websites, customer reviews and influencers to give a stronger impression. The third limitation was the study location. The respondents were from Greater Jakarta. Broader coverage should be explored for future studies. Further study to investigate how different generations are influenced by different types of eWOM could also be interesting. Despite previous study results on the relationship of trust to purchase intention, this study failed to show a significant relationship. The alternative model showed that trust has a direct effect on purchase intention. Further study to reconfirm the role of trust directly on purchase intentions should be explored.
Declarations
Author contribution statement
D. D. Tjiptadi: Conceived and designed the experiments; Performed the experiments; Wrote the paper.
D. Tjahjana: Performed the experiments; Analyzed and interpreted the data.
S.B. Abdinagoro: Conceived and designed the experiments; Performed the experiments.
D. Gandasari: Performed the experiments; Wrote the paper.
M. Zainal: Performed the experiments.
Funding statement
D.D. Tjiptadi was supported by Binus University and D. Tjahjana was supported by University Multimedia National.
Declaration of interests statement
The authors declare no conflict of interest.
Additional information
No additional information is available for this paper.
Appendix 1.
Appendix 2.
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