The thesis aims to determine how the online reviews influences consumer buying intentions and give suggestions and recommendation for businesses to gain good online reviews from customers to promote products as a new online advertising strategy. a research model was developed based on a combination of information acceptance model (IAM) and rational action theory (TRA). The results of analysis by SPSS tool and SEM linear structure panel with 9 variables showed the impact of online review characteristics, characteristics of online reviewers as well as characteristics of audiences and the reliability of online evaluation, which are the main element of online reviews influencing consumer buying intention in mobile devices.
R ESEARCH BACKGROUND 8 1.2 R ESEARCH QUESTIONS 9
With the explosion of information, the advent and development of the Internet have changed the method of seeking information about consumer products With these useful features, today the Internet has become the main source of information for a large number of tourists to use in the decision-making process for choosing products and services, which results in significantly changing in consumer behaviour of customers The Internet allows customers to share their opinions about experiences and experiences of products and services with countless other consumers The Internet is a worldwide computer network that allows communication between millions of users and access to various resources, people can give personal experiences, thoughts, opinions and easily reach out to communities around the globe The Internet has provided a better way for consumers to gather product information and advice regarding consumption from other consumers through online reviews Consumers can submit comments, feedbacks and product reviews on weblogs, discussion forums, rating sites, and social networking sites (e.g Facebook, Twitter, etc.), this has led to the creation of a diverse online review community Online reviews from previous consumers will be used by potential customers as they now begin to be interested in gathering more information from customers who have experience using the product The term "online reviews" is increasingly mentioned and is an important information channel to assist customers in search and decision-making activities, including reviews related to mobile devices.
A DoubleClick survey in 2016 also found that for many types of products, such as electronics, home and personal products, product review websites influence the purchasing decisions of customers (DoubleClick, 2016) In addition, due to the peculiarities of Internet communication, online reviews deserve the attention of marketing researchers and managers. Mobile phone equipment is a really necessary product for people, especially in the era of the information technology boom Currently, there are many types of mobile devices on the market with different brands, domestically produced or imported from abroad According to the latest report of market research firm Kantar Worldpanel Vietnam, the Vietnamese mobile phone market is growing very hot, with an average speed of about 20% per year and an average of 1 to 2 new mobile phones brands entered the market (Kantar, 2017) This shows that the mobile phone market in Vietnam is growing and more diverse Standing in such a market, consumers who want to buy a quality and the appropriate product must carefully research the product information from different sources before making a purchase. Consumers often seek information and decide to buy a mobile device based on information from relatives and friends, advice at the point of sale or through forums In which the form of searching for information via the Internet is used by many consumers and is increasingly popular In addition, consumers tend to be more proactive in sharing commercial information and trust in information provided by other consumers rather than information provided by sellers or marketers Therefore, understanding the impact of online reviews on the decision to buy mobile devices can help managers in getting the product to consumers
However, with the strong interactive nature and extremely fast spread of information on theInternet, unfavourable online reviews for businesses can be the source of an unintended communication crisis Therefore, business owners and marketers need to understand and manage these communication flows In fact, the study of the role of online reviews or more generally, eWOM (e-Worth Of Mouth) in the process of finding information on online customers has been interested by many researchers However, most studies focus on understanding the impact of information in online reviews on branding and customer engagement in the fields of general merchandise and other services There have not been many studies focusing on the impact of online reviews on the mobile device business market.Hence, the research paper will explore the impact of online reviews on the choice of mobile devices.
As mentioned above, as there is a lack of empirical findings and studies on the effects of online reviews of mobile device purchasing motive, especially in Vietnam, the research paper aims at identifying and determining elements of digital reviews that influence the buying intention by seeking answers for following questions:
● What parts of the digital evaluations affect customers’ purchase decisions?
● What elements of the digital reviewers affect the customers’ purchase decisions?
● What is the effect of consumers’ characteristics on their purchase intention?
In this second chapter, the author will discuss the previous researches of Word-of-mouth and Electronic word-of-mouth and demonstrate what are the differences between them. Furthermore, a section of discussion about online reviews will be included, following by examining what are the factors that might have influences customers’ final purchase intention of mobile devices, which consists of aspects of the reviews, personalities of the reviewers and of the targeted audience.
2.1 Word-of-mouth and Electronic word-of-mouth
Word of mouth marketing (WOM) has been studied and mentioned in many marketing materials, scientific research projects from the past over 50 years According to Johan Arndt
(1967), one of the world's leading oral communication pioneers, WOM can be interpreted as communication between two individuals “whom the receiver perceives as non-commercial,concerning a brand, product, or a service” (Arndt, 1967) Non-commercial characters are well received by people who speak without commercial intention namely promoting or selling products This implies the typical aspects of word of mouth as person-to-person communication, only applicable for the age before the advent of the Internet Then,Silverman (1997) defined word of mouth as a form of information about products, services or ideas among people who are not related to the company that provides the product or service
(Silverman, 1997) According to Patton (2000), the definition of word of mouth is a message about an organization's product or service, which includes the belief and quality of products or services transmitted from one person to another Stokes and Lomax (2002) argued that word of mouth is an effective way of communicating among individuals in relation to certain products and services Along this line, Kirby and Marsden (2006) defined word of mouth as words, communication between people, between recipients and communicators related to a brand, a product, a service or information on the market Most recently, Word of Mouth Marketing Association (WOMMA) defines it as “the act of consumers providing information to other consumers” (WOMMA, 2005) This definition is deemed considerably wide-ranging and applicable to not only conventional methods (offline) and word of mouth on the digital platforms (online) Word of mouth is considered as a form of informal marketing communication as it uses customers as its representatives to convey advertising information as described in the figure below:
WOM can be started directly between consumers (consumer-generated) which has no external effects or started purposely by marketers (marketer-generated) as a marketing activity (Evans and Erkan, 2014) Arndt (1967) discussed that consumers consider consumer- generated WOM as being more trustworthy than marketer-generated WOM (Arndt, 1967).Furthermore, in the literature, WOM can also be categorised as positive WOM and negativeWOM The definition of positive WOM is being information related to the product which conveyed by satisfied customers (Holmes and Lett, 1977), while negative WOM has been described as dissatisfying experiences with the products or services being communicated between friends and relatives (Blodgett et al., 1993) Lee and Cranage (2014) believed that negative WOM can produce a seriously potential destructive impact on a company’s image and reputation, which leads to affecting sales and market share The reason for this is discussed as WOM being in an uncontrollable environment and is very difficult to measure
(Erkan, 2016) East et al (2008) argued that positive WOM is more influential than negative WOM, while Chevalier and Mayzlin (2006) believed negative WOM has more significant effects on consumers.
With the advent of the Internet, a revolution in communication took place Consumers begin to shift from face-to-face communication directly to online forms (Pollach, 2006) The Internet is a perfect environment for consumers to express and share their feelings about a product or service with everyone With the Internet, people do not communicate with each other but rather force them to use an assistive device that connects to the internet like a computer or phone to interact by texting, sharing pictures and clips WOM type in the context of the global electronic communication environment is called an electronic word of mouth (electronic word of mouth, eWOM for short) (Chu and Kim, 2011) Hennig-Thurau et al.
(2004) defined eWOM as any kind of statement, both positive or negative, made by actual, potential or even former customers relating to a product and are available on the Internet for people and establishments to get access (Thorsten Hennig-Thurau, 2004) In other words, eWOM can also be known as WOM on the Internet and online, digital platforms (Goldenberg and Muller, 2001).
Like traditional offline WOM, eWOM can either be consumer-generated or marketer- generated Although the information on the Internet is usually created by marketers and distributed through company-owned websites or social media platforms, people can still share their personal opinions to others with media content creations such as texts, pictures or videos (Evans and Erkan, 2014) Cheung & Thadani (2012) listed different types of eWOM platforms including social media networks, shopping websites, review websites, blogs or discussion forums.
Electronic word of mouth (eWOM) has long been evaluated as an influential marketing tool(Bickart and Schindler, 2001; Kumar and Benbasat, 2006) Some previous studies have shown the impact of eWOM from the above foundation on consumer buying intentions(Bickart and Schindler, 2001; See-To and Ho, 2014) However, the invention of social media platforms such as Facebook, Twitter, Instagram has transformed the communication battle and introducing unconventional facets of eWOM eWOM now is not only the marketing tool for marketers to deliver a message about their products or service but it helps to spread marketing message on large scale by viral campaigns on social networks (Miller andLammas, 2010) And the viral ability of eWOM on social media is considered to make a great influence on both branding of the company and the buying decision of customers This is because by giving purchasers permission to connect and exchange information with their current digital platforms, people now are able to offering their personal experiences and opinions about the brands or services to other people ranging from families, friends or even strangers visiting the forms (Chu and Kim, 2011) And the viral of exchange in information and opinions of current customers about products and service makes potential customer remind about that products and services, which helps to increase brand-awareness (Al Halbusi and Tehseen, 2018) Besides, together with the popularity of social media, customers have tendency to search for reviews and recommendations about products on social networks with their friends and relatives And they tend to choose products which have a wide range of positive reviews and get more discussion from their network (Poturak and Turkyilmaz, 2018). From the literature review on eWOM above, it can be seen that the viral of online review on social media channels make a contribution to purchasing decision of customers But there is still have no specific research paper on how eWOM has an effect on buying decision of mobile devices.
2.1.3 The differences between WOM and EWOM
Unlike traditional word of mouth (WOM) that must communicate via face-to-face speech, eWOM can easily convey information by sending messages, emails, comments on forums, social networks, review sites Most of the information on the internet is presented in text form, stored and available for long periods of time (Park and Lee, 2008), so eWOM messages are easily seen and gathered by anyone, regardless of time and place, with the access to the Internet (Chen and Xie, 2008) This helps to overcome the weakness of WOM, can only spread information in the local social network (Brown and Reingen, 1987), so eWOM advertisement has the potential to grow and increase in its speed (Hung and Li, 2007).
However, there are also potential risks in the advancement of eWOM As the WOM information is highly reliable because the information is mainly provided by trusted individuals around them such as relatives or close companions (Ratchford et al., 2001),provided information from eWOM , however, is not completed so that anyone can share and spread information Therefore, the source of the eWOM message can come from consumers who are not familiar, so it is difficult for recipients to determine the level of information quality and the reliability of the information posted (Chatterjee, 2006) Therefore, the content and origin of eWOM information are important factors affecting eWOM's reliability (Park et al., 2007).
The next difference between these two forms is control, eWOM information will be easier to control Online sellers can control the exact location of messages spread on the website or push positive reviews on the front page of the web to attract consumers' attention (Park and Kim, 2008) But the information from WOM cannot do this because it spreads through direct face-to-face communication between consumers That's why it is difficult for WOM to measure more effectively than eWOM Dellarocas (2003) stated that eWOM is considered both as a competent, cost-effective advertising method and as a helpful, significant information source for consumers when they are in need of advice of the purchase.
C OLLECTION OF DATA 43 5.2 D ESCRIPTION OF SAMPLING 43 5.2.1 G ENDER 43 5.2.2 A GE 44 5.2.3 O CCUPATION 45 5.2.4 I NCOME 46 5.3 R ESULTS OF TESTING SCALES 47 5.3.1 R ESULTS OF TESTING C RONBACH A LPHA RELIABILITY COEFFICIENT 47 5.3.2 EFA DISCOVERY FACTOR ANALYSIS 48 5.3.3 R EGRESSION ANALYSIS AND RESULTS 50
Primary data were collected using non-random sampling method through the questionnaire survey The author gave out 204 questionnaire paper to eliminate invalid questionnaires, the remaining sample size was 197.
With a total of 197 responses, there were 87 respondents with female respondents (accounting for 44.2%), and 110 male respondents with male gender (accounting for 55.8%).
Figure 7 Age group of sampling
As can be seen from the graph, there is a domination of numbers of respondents in the age group from 18 to 29 years old, accounted for 60.4% which is more than a half of the total number 197 respondents Group of respondents within the age from 30 to 39 years old is the second largest group, consisted of 24.9% of the total number The other two groups are respondents are people in their 40s and people from 50 to 60 years old, comprised of 9.1% and 5.6% of the total number of respondents respectively.
Higher managerial/ pro- fessional/ administrative
Junior managerial/ clerical/ administrative/ college students
Semi and unskilled manual worker
State pensioners/ casual workers/ unemployed
Figure 8 Occupation group status of sampling
As we can see from the pie chart, the majority of the sampling are people with the occupation group of Junior managerial/clerical/administrative/ college students, which has the number of
93, accounted for nearly half of the total number of respondents (46.6%) The second largest group includes 56 respondents who are Intermediate managerial/ professional/administrative, consists of 28.4% the total sampling, following by a group of 18 respondents who are Higher managerial/professional/ administrative accounting for 9.1%; and 14 respondents who are in the occupation group State pensioners/ casual workers/ unemployed, comprised of 7.1%. Finally, 11 respondents are Skilled manual worker; and 6 remaining respondents are Semi and unskilled manual worker, accounted for 5.1% and 3.0% of the total number of respondents respectively.
No income Under 5.000.000 VND 5.000.000 VND – 10.000.000VND 10.000.000VND – 20.000.000VND Over 20.000.000VND
Figure 9 Income group of sampling
As can be seen from the graph, the largest income group is people with average income from VND 10 to 20 million, 56 respondents (accounting for 28.4%) At the second place are 52 respondents with income from VND 5 to 10 million, which comprised of 24.9% of the total number, following by a group of 43 respondents with an income of more than VND 20 million consists of 20.8% Finally, there are 33 respondents with an income of less than VND
5 million, accounted for 15.7%, and only 20 respondents who have no income, 9.8% of the total sampling.
5.3.1 Results of testing Cronbach Alpha reliability coefficient
4 items: COT1, COT2, COT3 and COT4 0.546
7 items: CAR1, CAR2, CAR3, CAR4, CAR5 and CAR6
Consumer knowledge (COK) 3 items: COK1, COK2 and
Consumer preferences (COP) 5 items: COP1, COP2,
Table 2 Results from Cronbach Alpha test
Group of factors “Characteristics of the reviews” has 2 indicators, including CON with 2 items (Online context of the reviews) and COT with 4 items (Content of the reviews) with Cronbach Alpha coefficients of 0.43 and 0.5 respectively (less than 0.6) From the table above, it can be seen that both CON1, CON2 and COT2 are removed Besides, the removal of these indicators also increases the Cronbach Alpha coefficient, so they will be excluded from the group After removing these two indicators, conducting a reanalysis of Cronbach Alpha results in Cronbach Alpha coefficient is all larger than 0.6, thus they will be used for factor analysis
The "Characteristics of the reviewers" factor group has 7 items; the Cronbach Alpha coefficient is 0.695 (greater than 0.6) Of which all 6 items are accepted to be used for factor analysis.
The "Characteristics of audiences" factor group has two indicators, Consumer Knowledge (COK) and Consumer preferences (COP) and all items belong to these two indicators are all accepted due to the fact that Cronbach Alpha are 0.688 and 0.672 respectively, which are all larger than 0.6.
After checking the Cronbach Alpha reliability coefficient, there will be 18 items in 5 indicator groups (category 5 nonconforming indicators) will be used to conduct factor analysis The method chosen for factor analysis is the principal components method with the declaration of the number of factors 5 for ease of research After performing the necessary declarations and running factor analysis, the detailed results are given The analysis results can be described as follows:
Extracti on Sums of Squared Loading s
Rotation Sums of Squared Loadings
Table 4 The Rotated Component Matrix
KMO (Kaiser-Meyer-Olkin) coefficient is equal to 0.79 (greater than 0.5) and Sig