Abstract
This study aims to investigate how product-related variables influence consumers’ purchase intentions in Indonesia, one of Asia’s primary emerging markets. Product type, consumer involvement and product review were identified as the key independent variables in an experimental research involving 181 samples. Having conducted the pretest, eight articles were consequently selected before the results from the online questionnaire were collated from the Indonesian respondents. The results showed that product type and product review were significant determinants of consumer attitudes and purchase intentions. Although product involvement was shown to have no substantial influence on consumer attitude, this study further found out that if a product is experience-based with low involvement, it does indeed have a positive influence on the attitude of consumers. Furthermore, respondents showed no discriminations against sponsored product reviews, which was contradictory to the norms presented in existing literature. This study also discusses both managerial and theoretical implications as well as the research limitations and future research directions derived from the case study.
1 Introduction
Research has shown that consumers tend to trust peer consumer reviews when searching for information online (e.g., Chaffey and Ellis-Chadwick 2012; Lee and Koo 2012). Therefore, it is in the company’s interest to possess abundant consumer-generated product reviewers, as they are the ones who play an important role in consumers’ decision-making process.
Rapidly growing Internet users in emerging markets, such as Indonesia, have begun to use the Internet as a new alternative to the traditional channels for searching product information before their purchase. Although there has been an emergence and continuous development of online shopping behavior in recent years, emerging markets, like Indonesia, are not familiar with online product reviews. Most of the current online shopping website reviews are about delivery and packaging, but not the actual products. This study will discuss the effect of online consumer-generated reviews on readers’ purchase intention in Indonesia and the factors that might influence their attitudes toward product review.
A number of researchers have studied the impacts of product review on consumption (e.g., Wulff et al. 2015), yet there is little research into how the internal variables of a product review could affect the consumer attitude toward a product and their purchase intention. This study will draw on the evidence from existing literature on the internal variables and test their effects on Indonesian consumers in order to gain better understanding of this problem. The result of this study is expected to be beneficial for marketers who consider utilizing the product review or other user-generated content as marketing communication to enhance their business performance in the Indonesian market.
2 Literature Review
2.1 Online Consumer Review
Consumers can easily use Web 2.0 tools to provide information about their purchasing experience on different platforms such as websites, online discussion forums and even their own personal blogs or video channels (Lee and Youn 2009). This information is classified as user-generated content (UGC). Chevalier and Mayzlin (2006) stated that about 61% of Internet users perceived UGC as valuable and credible. This echoed the findings of Bae and Lee (2010) that prospective consumers revealed more positive attitudes toward UGC than PGC (product-generated content) information, and they are more likely to visit websites with UGC reviews to learn more about the product before deciding to make a purchase.
Consumer opinions and recommendations can influence the image of products and services, in a positive or negative way (e.g., Fruth and Neacsu 2014). The vast development of online commerce and removal of time and space barriers lead the spread of recommendations via the Internet through networking sites (Facebook, Twitter, LinkedIn), personal blogs and specialized review sites (e.g., IMDB.com, TechinAsia). This has enabled the quick and potentially limitless dispersion of online UGC recommendations (Fruth and Neacsu 2014). When consumers generate online recommendations for others consumers, it can be considered as e-word of mouth (eWOM). eWOM is assumed to gives more benefit to consumers because it can reduce the consumers’ perceived risk of online shopping and stimulate purchase intention by providing detailed product information (Cheung et al. 2009). Furthermore, eWOM also plays an important role in reducing uncertainty and the amount of information that needs to be processed when making a decision.
There are several classifications of online reviews gathered from previous studies, such as written, audio, video and mixed reviews, but for this research the scope of media that will be used are written reviews. Written reviews are mostly typed in text; this allows the search engine to scan through its sentences, which results in more readers being attracted through search engines (Fruth and Neacsu 2014).
2.1.1 Valence of Consumers’ Online Review
Consumers providing online review or recommendations have the freedom to develop their personal blogs and present themselves as experts or specialized bloggers who frequently express their views on a certain product (Pan and Zhang 2011). Product reviews are highly influenced by the user’s personal preferences and usage conditions (Chen and Xie 2008); therefore, the valence of these reviews will be different regardless of whether they are positive or negative. However, negative reviews tend to be seen as more reliable and generalizable than the positive ones (Chevalier and Mayzlin 2006), hence exert greater influence on the sales of a product (Podsakoff et al. 2012). It has also been documented that helpful reviews with more details of the product tend to influence the potential customers’ decision more than the reviews that are not perceived to be helpful (Li et al. 2013).
2.1.2 Sponsored Product Review
Compared to the conventional sellers, online sellers can provide consumers with two types of product information. Seller-created product information can be seen on the websites and traditional communication channels such as advertisements. The other type of product information is consumer-created information, which is presented by consumers who have already purchased and used the product (Park et al. 2007a). This consumer-created information provided in this way is a new method of word-of-mouth communications as it also includes consumers’ experiences, evaluations and their personal opinions.
In sponsored reviews, companies (the ‘sellers’) give certain online users (the ‘reviewers’) compensations in exchange for their reviews on the online platform, such as personal blogs (e.g., Forrest and Cao 2010; Zhu and Zhang (2010). These compensations have led sponsored reviews or recommendations to be seen as having bias because it can be considered as one form of advertisement (Lu et al. 2014). Companies have been using sponsored online consumer reviews as a more effective marking tool (e.g., Becker-Olsen 2003; Chevalier and Mayzlin 2006), but its affects are often debatable.
Ballantine and Au (2015) found that consumers made no distinctions between sponsored and non-sponsored reviews while measuring the perceived credibility of the reviews and their impacts on brand attitude and purchase intentions. This echoed the findings of Lu et al. (2014) that readers’ trust in source credibility and their attitudes toward sponsored online posts remain unaffected after being made aware that such posts were sponsored. On the other hand, Hwang and Jeong (2016) noted the attitude changes among consumers toward online reviews with different sponsorship declaration messages. They concluded that consumers rated source credibility negatively toward reviews with a simple sponsorship disclosure message (e.g., this post is sponsored) while this negativity disappeared for those reviews with ‘honest opinions’ message (e.g., ‘this post is sponsored but the opinions are honest’).
This study will differentiate between non-sponsored and sponsored reviews because the Indonesian market is unfamiliar with online reviews, and therefore this differentiation will help companies understand how consumers react to different reviews. It will also contribute to the existing literature in its knowledge of how sponsored and organic reviews would influence readers’ attitudes and purchase behavior.
2.2 Product Type
Products can be broadly classified as either search goods or experience goods based on particular attributes consumers can differentiate through (e.g., Hsieh et al. 2005; Mudambi and Schuff 2010; Weathers et al. 2007).
Search goods are those goods whose specific attributes consumers can identify before purchase. The best examples of search goods are electronics, camera, mobile phones and laptops (Mudambi and Schuff 2010). Search goods are easier to acquire (Hsieh et al. 2005) and compare (Mudambi and Schuff 2010), without the need to interact with the product (Huang et al. 2009) before purchase. In case of search goods, consumers usually evaluate the product through instrumental evaluative cues or, put differently, by assessing the technical and more detailed performance of the product. Consumers tend to observe ratings of the search product, and these observations affect their valuations and purchase decisions.
Experience goods are those goods for which consumers cannot easily identify their attributes before purchase. Examples of experience goods include movies, books or video games (Weathers et al. 2007). Reviews of experience goods usually focus on the appearance or aesthetics of the product itself. Online reviews tend to depend on the senses of the reviewers to describe the experience they have felt while using the product, even though the experience of reviewer and potential consumers might be different based on their own personal perspective. Moreover, extrinsic cues such as the popularity of the product can be displayed by the number of reviews and therefore might have a great impact on consumers’ purchase intention.
Overall, the measurement of these two product type categories is different in terms of the volume and valence of the reviews (Huang et al. 2009); therefore, their effects on consumers’ attitude and purchase intention may also vary which is one of the aspects that will be studied in this research.
2.3 Product Involvement
Involvement is the perceived individual relevance of a product based on consumers’ values, needs and interest (e.g., Griffith et al. 2001; Zaichkowsky 1987). When consumers consider making a purchase, they are most likely to appraise the degree of involvement first (Clarke and Belk 1979). As their involvement grows, consumers tend to elaborate information processing further (Doh and Hwang 2009). Involvement with the products affects consumers’ decision process, and online reviews act as the information provider that they need to process the information (Quester and Smart 1998).
High-involvement consumers tend to be more motivated to devote the cognitive effort required to evaluate the true merits of a product, and are hence more influenced by the quality of reviews rather than the volume itself (Park et al. 2007a, b). Consumers with low product involvement tend to be more influenced by the dynamic attitude and volume of good reviews (Petty and Cacioppo 1984).
2.4 Attitude Toward Product Review
In order to facilitate online purchasing decision, companies often either provide their own online product information or allow users to share product reviews online (e.g., Chatterjee 2001; Chen and Xie 2004). In relation with the review’s valence, Doh et al. (2009) stated that both positive and negative eWOM could impact consumers’ attitude toward the product, although a few negative messages within a vast amount of positive messages are not critically harmful. On the whole, consumers tend to choose a product with more recent reviews and small sample size indicating a salient summary of percentage on the ratings (Wulff et al. 2015).
Consumers perceive user-generated reviews as true, factual and unbiased (Hass 1981). They are also likely to trust reviewers or sites that they perceive as credible (Lu et al. 2014). This is particularly important for consumers with less knowledge of the product (Cheung et al. 2009). When consumers feel that the review messages are untrue or being modified by the company through sponsored content but without sponsorship declaration, the credibility of the source decreases while consumer resistance to such reviews increases (Lee and Koo 2012). Declaration of sponsorship helps both reviewers and the company to build trust and lead to positive consumer attitudes toward the product.
2.5 Purchase Intention
Purchase intention can be defined as the willingness of a consumer to purchase a specific or particular product, and it is influenced by the information that they find related to that specific product. Lu et al. (2014) suggested that consumers’ purchase intention can be highly influenced by the valence and sponsored status of the review. This echoed the findings of Lee and Koo (2012) that readers would resist the persuasive intent of the review if they sensed that the message is biased or with sponsored content.
The different effects of valence reviews, product involvement, and reviewer’s sponsored status on purchase intention will be studied in this research. The results will highlight the most effective and appropriate ways of using online reviews for certain products and/or targeted segment of consumers in Indonesia.
2.6 Summary
In conclusion, the controlled variables such as product type, product involvement and sponsored status are chosen to develop the proposed model in this research. Based on the factors from these variables, the responses of consumer attitude toward product review and their purchase intention can be measured and analyzed. The specific relationships between the individual variables and consumer attitude toward product review and purchase intention are going to be explained in conceptual framework and hypothesis development.
3 Conceptual Framework and Hypotheses Development
Online information search behaviors for product type (search and experience goods) are non-identical (Lu et al. 2014). It is likely that the different variables of product type could have direct relationship to consumer attitudes toward product review. The amount of information they are searching for search goods is more likely to be more detailed regarding the capabilities of consumers to evaluate the attributes of the product before purchasing. In contrast, experience goods could mainly be evaluated after the purchase of product. Furthermore, Mudambi and Schuff (2010) mentioned that reviews about experience goods are supposedly subjective and have an unstable nature even when the reviewers have experienced the product themselves. Thus, we consider that consumers will appreciate online reviews more favorably for experience goods rather than search goods. They might have a better attitude toward experience goods because the attribute of the product cannot be easily identified and verified without others’ experience. Thus, the following hypothesis is derived:
H1: Consumers will be more likely to have positive (a) attitude toward, (b) trust on, and (c) purchase intention for the product review for experience goods compared with search goods.
Product involvement is also considered as an affecting factor toward consumer attitude regarding the different behavior when confronted with high- or low-involvement product. It has been discussed that consumers tend to be more active looking for information and allocate more time to consider when buying high-involvement compared with low-involvement goods (Park et al. 2007a, b). Low-involvement goods consist of products that consumers don’t need to think deeply about when purchasing and don’t have specific preferences for, so the loyalty of the brand is considered lower than high involvement. In contrast, products considered as high involvement have a larger impact on the consumer, including their financial status and personal preferences, so their attitudes might get affected by the type of product involvement included in the article. Therefore, the following hypothesis is constructed:
H2: Consumer’s (a) attitude, (b) trust and (c) purchase intention for the product review will be higher for high-involvement products than low-involvement products.
When an article is sponsored, some reviewers willingly state that they are being sponsored and some of them implicitly mention it. The research by Lu et al. (2014) mentioned that there are two methods of sponsorship for product reviewers, which are direct monetary sponsorship and indirect monetary sponsorship. However, it was proven that the sponsorship type does not significantly affect consumer attitudes toward the sponsored articles. Therefore, this research will implement broader scope by differentiating the variables into sponsored and non-sponsored reviews. Podsakoff et al. (2012) suggested that when information comes through opinions or recommendations from others, positive information might be less credible and generalizable in contrast with negative information. Hence, this research will implement positive articles as the samples and analyze the respondent’s reaction when confronted with sponsored or non-sponsored positive article. Based on the supporting evidence, the following hypothesis is derived:
H3: Consumers have more positive (a) attitude, (b) trust and (c) purchase intention for product reviews if the review in the article is not sponsored compared with sponsored (Fig. 6.1).
4 Methodology
4.1 Research Design and Measures
Manipulation Variables
The research applied a 2 (product type) × 2 (product involvement) × 2 (sponsorship) between-subject design. Consumer reviews are provided with two types: sponsored and non-sponsored. They can be differentiated by choosing the reviews that mention ‘in partnership with, sponsored by, given samples for honest reviews…,’ which clearly expose and inform the consumer that they are being compensated by the company of the product they reviewed. The research also adopts a within-subject design. Each respondent will be provided a questionnaire with eight examples of written positive product reviews that consist of sponsored and non-sponsored reviewers. Respondents will then be asked how they perceive the reviews and about their purchase intention.
Search goods and experience goods are selected as the two products types. Search goods will be identified through asking the consumers whether the product performance is easy to evaluate prior to the purchase. Experience goods product will be identified in contrast with the search goods attributes and focusing on the consumers’ perspective about the appearance of the product. Search goods products can be thoroughly evaluated by consumers before purchase and technology product and beverage are the best examples of it. On the other hand, experience product demands the consumer’s personal senses experience the specific attributes, and may render varied experiences among consumers. The best examples of experience goods are travel agency and food delivery service, in which consumers need to get their hands on the actual product first before evaluating the detailed attributes. Through the product type, consumers’ search behavior and the utilization of information source can influence their purchase intention (King and Balasubramanian 1994).
Consumer involvement represents the product’s relevance for the consumer’s life. If the product being reviewed is generally complex, risky, expensive or demand extensive information processing, then it would be considered as a high-involvement product. Respondents will be asked whether the product that they were searching has a high level of involvement in their life, and how their attitudes toward product reviews relate to the attributes. In contrast, the low-involvement product consists of items that are habitually needed by the consumers but they don’t need to conduct thorough research when purchasing the product, due to easy availability of information and lower purchasing cost. Respondents will be asked about these variables in order to measure the significant effects of consumer involvement in their attitude toward product review and how it might impact their final purchase intention phase.
Independent variables will be measured as manipulation check on a seven-point Likert-type scale ranging from 1 (strongly disagree) to 7 (strongly agree) to validate whether the manipulation has been successful. The score on each variable will denote whether the respondents were able to differentiate the stimulus variables in the articles shown.
Dependent Variables
Attitudes toward product review and purchase intention are measured as the two dependent variables. According to Lu et al. (2014) and Obermiller and Spangenberg (1998), attitudes toward the product review variable will contain credibility, trustworthiness and product review valence as indicators to measure how the independent variables effect these factors of attitudes. Seven-point Likert-type numeric scales ranging from 1 (strongly disagree) to 7 (strongly agree) are used. Respondents will need to respond about what they feel and think about product review after measuring the involvement, product type and sponsor status involved in the making of established product review.
4.2 Data Collection
Procedure
Electronic survey links are sent out through social media posting, online shopping forums and several selected blogs of product reviewers. Google Form is used as the data collection platform. When participants access the links, they will be directed to the survey and asked whether they have read or watched product reviews before the research to make sure they have the experience to identify various types of product review before participating in the research. Participants who have never read product reviews before will be guided to the end of the questionnaire and excluded from the analysis.
Pretest
Pretest was conducted with a sample of 30 master students. The pretest respondents were asked to measure the product that was provided through seven-point Likert scale in order to highlight which of the products are appropriate to be used in mass survey. The respondents were choosing respectively the value of the statements provided in the questionnaire.
Pretest results show that two products were easily identified by respondents as search goods, which were laptop (Mean before = 5.83, Mean after = 6.49) and soft drinks (Mean before = 5.87, Mean after = 6.23). Laptop is perceived as a high-involvement product (Mean = 6.76) while soft drinks are perceived a low-involvement product (Mean = 3.84). For the experience goods, travel agency (Mean before= 3.66, Mean after = 5.74) and food delivery service (Mean before = 4.48, Mean after = 5.62) are perceived to be suitable. Travel agency is perceived as a high-involvement product (Mean = 6.37) and food delivery service is considered as a low-involvement product (Mean = 4.58).
Building upon the result, we developed eight articles that consist of previously selected products with the differentiation of sponsored status (see Table 6.1). The articles clearly inform the respondents about the sponsorship status and about being tested. Participants were able to point out which articles are sponsored and which are not. To avoid bias, fictitious brand names were used, and respondents were randomly provided with one of the eight articles.
Sample
Indonesian market is widely considered as an emerging market. The data were collated from participants aged 21 to 35 in the Indonesian market. This particular demographic is used due to the evidence that the Y generation that was born around the 1980s and early 1990s has had constant access to technology, thus making it easier for them to search for information through written or video reviews on the inter web. In addition, the Y generation has already stepped into productive ages and has started making their own income, and therefore their consumption behavior (where they will spend their income) is completely up to them. Furthermore, previous online surveys such as Forrest and Cao (2010) stated that online consumers are generally younger and better educated compared to conventional age segment. Thus, the selection of Y generation consumers as the target for this research is unbiased and appropriate.
Initially, 209 responses were collected and 181 valid responses were finally achieved (48.1% females). The majority (63.5%) of the respondents are graduates while 33.7% of them have finished their master’s degree. In terms of the reviewers’ usage experience, many respondents already had 1–5 years experience of using product review; in particular, 24.9% had experience of more than 5 years. This fact can help the research to be more valid in analyzing consumer attitude toward product review because, presumably, it can be considered that respondents had already encountered several product reviews and already developed their own perception toward them, which might give greater insight on the subject.
5 Result
5.1 Descriptive and Reliability Results
Table 6.2 shows the score of mean and standard deviation of dependent variables and control variables used in this research.
We test the validity and reliability following the recommendation of Malhotra (1987). Cronbach’s alpha and inter-item correlation are tested to validate the scale. The result shows good reliability of attitude (Cronbach’s alpha = 0.89), trust (Cronbach’s alpha = 0.89) and purchase intention (Cronbach’s alpha = 0.75).
5.2 Manipulation Check
Product Type
Respondents were asked to rate the product type indicators after they had finished reading the article, to verify that the manipulation was successful. They were asked to answer the two questions developed by Krishnan and Hartline (2001) on a seven-point Likert scale. The questions enquire as to the ability of respondents to assess the product attribute before or after purchasing the product or service. ANOVA result shows that respondents who got the search goods articles got higher mean (Mean = 2.52, SD = 1.113, N = 88) compared to the respondents who got experience goods (Mean = 6.57, SD = 1.117, N = 93, F (1,179) = 595.146, p < 0.001). Based on the result, the manipulation can be considered successful as the scores are consistent with previously stated theory of Mudambi and Schuff (2010), who suggested that search goods are harder to evaluate before buying or using the product or service and this statement correlates with the findings. In addition, the standard deviation of search goods is lower than experience and it supports the argument.
Product Involvement
Product involvement has four indicators: interest, pleasure, sign and risk probability. The result has shown that high-involvement product received a higher mean score (Mean = 5.60, SD = 2.06, N = 96) in contrast to low-involvement product (Mean = 3.47, SD = 2.056, N = 85, F (1,179) = 48.455, p < 0.001). The manipulation worked because it is consistent with the discussion by Laurent and Kapferer (1985), which explains the condition that when the mean is higher it can be classified as high involvement due to the fulfillment of self-interest, pleasure, sign and risk probability.
Review Sponsorship
Lastly, the sponsorship variable has a two-item scale to calculate the mean score on each factor, which are sponsorship and non-sponsorship. There is respectively the same number of sponsored and non-sponsored articles, and from the mean score non-sponsorship is rated higher (Mean = 5.045, SD = 2.29, N = 88) compared with sponsored (Mean = 4.18, SD = 2.27, N = 93, F (1, 179) = 6.478, p < 0.05). This indicates that the manipulation results in a favorable outcome due to the fact that means are relatively different; therefore, it reflects that the respondents are fully aware of the sponsored status given in the article.
5.3 Hypotheses Testing
Descriptive result summarizes consumers’ attitude toward reviews under different conditions (see Table 6.3).
ANOVA is used to analyze consumers’ attitude and purchase intention toward different product reviews. The result (see Table 6.4) shows that product type has a significant effect on consumer attitude toward product review (F (1,181) = 5.08, p < 0.05). Surprisingly, no significant effect of sponsorship or involvement has been found. These findings suggest that product type (i.e., search goods vs. experience goods) is the most important factor when considering the effect of online reviews. Even sponsored reviews will benefit the company with similar positive attitude as non-sponsored reviews.
Furthermore, the effect of product type is moderated by involvement (F (1, 181) = 5.42, p < 0.05). When involvement is high, there is no significant difference in attitude between search goods (Mean = 4.49) and experience goods (Mean = 4.50). However, when involvement is low, attitude toward reviews on experience goods (Mean = 4.90) is significantly higher than that on search goods (Mean = 4.10). See Fig. 6.2 for details.
Similar results have also been found for trust and purchase intention.
6 Conclusions and Implications
The research aims to analyze the effects of different factors on consumers’ responses toward customer reviews in an emerging market. Based on the findings from literature reviews, three factors are selected—product type (search and experience goods), product involvement (high and low) and sponsorship ( sponsored and non-sponsored review). A 2 x 2 x 2 between-subject design experiment was conducted. Consumers’ trust on, attitude toward, and purchase intention for the products were measured as consumer responses to the reviews. Based on the data collected from 181 respondents through online platforms, some interesting results were found.
6.1 Theoretical Contributions
This study provides a valuable academic contribution toward online marketing and social media, extends existing findings to an emerging market, and identifies some interesting findings.
Firstly, consumers will respond differently to reviews for different product types. Specifically, consumers respond to online reviews on experience products in a more favorable way than search products. This is consistent with the literature. This might be caused by the fact that it is much easier to assess search goods compared to experience goods (Hsieh et al. 2005). Thus, consumers will rely more on other people’s experience to evaluate experience goods. Hence, they have more favorable response toward the experience goods product review.
Secondly, no significant difference has been identified in consumers’ responses if the reviews are sponsored by the company. This is surprising and in conflict with common sense and existing findings. This indicates that consumers in an emerging market do not care about whether the written reviews are sponsored by the company. They still appreciate the benefit from other people’s reviews even when the other people are sponsored by the company. They treat the sources of online review indifferently.
Thirdly, there is no significant relationship between product involvement and consumer responses in an emerging market. When making a purchase, consumers in an emerging market will pay attention to product review equally, regardless of whether the involvement is high or low. The reason could probably be that the information available in an emerging market is limited and consumers appreciate all sorts of information, especially other users’ experiences and opinions.
Finally, there is a significant interaction between involvement and product types. Although involvement itself does not change consumers’ responses to reviews, it will moderate the effect of product type on consumers’ responses. When consumers are making a less important decision (i.e., low involvement), they will have a much more positive response toward the reviews about experience goods rather than about search goods. This is because consumers will appreciate the benefit from other people’s opinions on experience goods. However, when consumers are making an important decision, they will appreciate other people’s opinions independent of the product types. It could be explained by the fact that when making an important decision, no matter what type of product they are going to purchase, consumers treat reviews as equally important (even for a search good).
6.2 Managerial Implications
This research provides valuable and constructive online marketing communication implication for companies in an emerging market. Firstly, product reviews can foster positive eWOM in an online platform and might trigger improvement in purchase intention of the consumer. Secondly, by carefully identifying the product that is going to be reviewed (product type or involvement), marketers could strategically make suitable plans to handle how the reviews will be displayed. Thirdly, marketers can feel relieved when sponsoring a review article, as consumers in an emerging market will pay attention to the sponsorships. Furthermore, product reviews about experience-based product/service should be maintained with the quality of content to attract the consumer to experience it themselves. And finally, if the product is experience based and considered a low-involvement product, consumers tend to trust the reviews more.
6.3 Limitations and Future Works
The current study focuses only on an emerging market. A cross-cultural study between a developed market and an emerging market will enrich the current findings and show some differences clearly. Some cultural factors should be examined as moderators. Similarly, some personal traits would play some roles as well, such as risk aversion.
The underlying mechanism of the current relationships is not examined. Further works should focus on some mediating effect in the relationships between product types, sponsorship, involvement and consumers’ responses—for instance, whether the online review works as uncertain reduction in the emerging market.
Finally, other characteristics of online reviews are worthwhile to be examined in further works—for example, format and valence of online reviews.
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Jiang, T., Liu, Y. (2018). Digital Business and Chinese Consumers’ Purchase Intentions in Indonesia. In: Kim, YC., Chen, PC. (eds) The Digitization of Business in China. Palgrave Macmillan Asian Business Series. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-79048-0_6
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