Abstract e-WOM on customer’s behavioral intention to select a

AbstractThe popularityand the sales of certain product and services can be increased significantlyvia online reviews.

 In the context ofrestaurant industry, it seems that WOM plays a determined role in everyeffective marketing strategy for restaurants specifically those with limitedpromotion budgets. This paper aimsto apply the theory of planned behavior to investigate the impact of e-WOM onthe customer when choosing restaurant amongst alternatives.   IntroductionWOM refers to sharing opinions from one consumer to another.Baloglu and Macclary (1999) considered that WOM has a significant impact oncustomer’s perceived image. The spread of internet decreases the personalcommunication and made a transfer from WOM to e-WOM.E-WOM is defined as “any positive or negative statement made bypotential, actual, or former customers about a product or company which is madeavailable to multitude of the people and institutes via the internet.Based on previous studies, the popularity and the sales of certainproduct and services can be increased significantly via online reviews. Sen andLerman (2007) found that the valence of the reviews positively versusnegatively significantly affects consumer’s attitude toward the reviewedproduct.

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In the context of restaurant industry which is highly competitive, therestaurateurs try to have a deep understanding of the wants, needs andperception of customers to attract them and retain a long term relationship. Itseems that WOM plays a determined role in every effective marketing strategyfor restaurants specifically those with limited promotion budgets. Furthermore,the intangibility of the service and the difficulty to evaluate it before thepurchase bring risk, so the customers are more dependent on the interpersonalinfluence of e-WOM.  Increasing studies have shown that consumers are more interested inproducts discussed online, then those marketed traditionally. These studieshave proven that e-WOM has a significant effect on consumer behavior. Howeverfew researchers have examined the impact of WOM on behavioral intention in therestaurant sectors.

The aim of the research is to examine the influence of e-WOM oncustomers when choosing a restaurant. In this research, the theory of plannedbehavior was used to examine the influence of e-WOM on customer’s behavioral intentionto select a restaurant. Theoretical Background The TPB by Ajzen’s describedhow the behavior is formed and affected by three factors which are theattitude, subjective norms and perceived behavioral control. A large number ofresearches in the social science have used Ajzen’s model and address many areasas smoking behavior (Babrow et al., 1990),and ethical behavior (Flamnery andMary, 2000). These studies support the usefulness of Ajzen’s theory.

However,few studies that examines Ajzen’s model in the context of hospitality are present.The TPB as discussed by Ajzen (1991)  is a development of the theory of reasonedaction developed by Ajzen and Fishbein (1980) and considered as one of thefamous conceptual groundwork in all research related to the human action(Ajzen, 2001). According to the theory, there is a link between the belief ofindividuals and their behavior.

Customer’s attitudeMcguire (1969) provides a definition of attitude that is widelyheld by psychologists. He stated that an attitude is an evaluative response toan antecedent stimulus or attitude object. Ajzen (1988) elaborates on Mcguire’sdefinition by describing attitudes as a predisposition to respond favorably orunfavorably to an object. Based on Ajzen’s model, attitude is the degree towhich a person has a favorable or unfavorable evaluation or appraisal of thebehavior in question (Ajzen, 1991). In this study, we restrict the term “attitude”to a customer’s evaluation of a restaurant.

Subjective NormsSubjective norm is an original construct from TRA. It deals withthe influence of social environment or social pressure on the individuals andthus on behavioral intention (Fishbein and Ajzen, 1975).  Subjective norm is defined as “the perceivedsocial pressure to perform or not to perform the behavior” by the individual(Ajzen, 1991, p. 188). The role of subjective norm as a determinant ofintention is well documented in situations where the actual behavior entailstangible and beneficial consequences for the consumer (Taylor and Todd, 1995).Applied to this study, subjective norms reflect consumer perceptions of whetherthe feeling of choosing restaurant amongst others is accepted, encouraged andimplemented by the consumer’s circle of influence.

Perceived Behavioral Control PBC is defined as, given thepresence or absence of requisite resources and opportunities, the individual’sperception of the ease or difficulty in performing the behavior of interest(Ajzen, 1991). In another word, the behavior is correlated to the confidence ofthe individual in hisher ability of performing that behavior. Behavioral Intention (BI)Intention is defined as the perception of an individual towardsperformance of a particular behavior (Fishbein and Ajzen, 1975). The intentionis predicted by attitude and subjective norm. Behavioral intention representsthe extent of the individual’s intentions to perform or not to perform onecertain behavior (Ajzen, 1991).  LiteratureReview1-e- WOM in Restaurant IndustryWOM is a form of interpersonal communication amongst consumers. Researchalso revealed that WOM is a consequence of customer’s emotional responses to consumptionexperiences. Yet, researchs still lack in the domain of restaurant industry.

The intangibility and the higher risk associated to the service drive thecustomer to rely on other’s opinions to evaluate the service before purchase.The intention toward eating out in a particular place increases when positiverecommendations are made, affecting referent beliefs. These beliefs seem tohave important weight in the decision-making process. According to Cousins etal.

, (2002), there are various motives that drive customers to talk aboutrestaurant. They classify the elements of the restaurant offer in order ofimportance as: food and drink, service, cleanliness-hygiene, value for moneyand ambiance. Additionally, the type of restaurant moderated the relationshipbetween restaurant service and ambience quality and customer behavioral.  The advanced technology spreads the e-WOM andmakes it accessible to millions of people. According to the study of Kasabov(2016) in the Chinese context, he found that the information is a keymotivation to seek e-WOM in social networks, information relevance andusefulness motivate customers to solicit e-WOM and information quantitysignificantly affects customer’s behavior. Moreover, Baber et al., (2016) foundthat attitude mediates the relationship between online WOM communication andcustomer purchase intention.

Based on these previous studies, there is a high potential impactof e-WOM on the consumer decisions process. In the next section, Ajzen’s TPBwill be described to provide a frame work to develop research hypotheses.2.TPBThe theoretical model employed in this research is based on thetheory of planned behavior. It offers a comprehensive yet parsimoniouspsychological theory that identifies a causal structure for explaining a widerange of human behavior (Morris et al.

, 2005). Attitude, subjective norms andperceived behavioral control influence an individual’s intention to perform agiven behavior. However, many researchers criticized TPB is that the theory ispurely rational, not taking account of cognitive and affective factors that areknown to bias human judgments and behavior. “In reality, the theory draws amuch more complex and nuanced picture, and the emotions result from beliefs andaffect intention and behavior” (Ajzen, 2011, p. 1116).In general, the more favorable the attitude toward the behavior,the stronger will an individual’s intention to perform the behavior.

Moreover,WOM is acknowledged to play a considerable role in influencing and formingconsumer attitudes and behavioral intentions (Chatterjee, 2001; Chevalier and Mayzlin, 2006; Sen and Lerman,2007; Smith and Vogt, 1995; Xia and Bechwati, 2008). Ying and Chung (2007)stated that positive WOM leads to more favorable attitude toward a specificproduct. In sum, the literature indicates that e-WOM has a significant impacton attitude.

Thus, it is hypothesized that:Ø  H1: e-WOM has a significant impacton customer’s attitude.Ø  H1a: Attitude has a significantimpact on customer’s intention to choosing restaurant offers Lebanese food inBeirut.TPB views the role of social pressure to be more important when themotivation to comply with that pressure is greater (Mathieson, 1991). Pavlov and Fygensen (2006) found that subjectivenorms affect user’s intention to make online purchase.

The previous studiesdiffer in the results. Davis et al stated that there is no significant relationshipbetween subjective norms and intention. However, Taylor and Todd have shownsignificant relationship between Subjective norms and intention. It is assumedin the literature that the model using TPB framework shows that subjectivenorms have a significant relationship with intention. Further, Guoqing et al.,(2009) in their study of Chinese consumers found that WOM has a positiveinfluence on the receiver’s objective norms. Thus, it is hypothesized that:Ø  H2: e-WOM has a significant impacton subjective norms.

Ø  H2a: Subjective norms have asignificant impact on customer’s intention to choosing restaurant offersLebanese food in Beirut.Perceived behavioral control is an important factor predictingbehavior. Previous studies have shown that perceived behavioral control affectsthe intention to purchase Halal food products, and intention to consume softdrink.

Also, Cheng et al., (2006) found that negative WOM communication ispositively related to perceived behavioral control. Thus, it is hypothesizedthat:Ø  H3: e-WOM has a significant impacton P.B.CØ  H3a: P.B.C has a significant impacton customer’s intention to choosing restaurant offers Lebanese food in Beirut.

2.1 Proposed Conceptual Framework Attitude Subjective norms                         Perceived Behavioral control Intention to select restaurant                                                        Electronic Word of Mouth                                                                                                                                                                                                                                                                                                                                                                                  ResearchMethodology TargetPopulationThe target population for this study is the restaurant that offeredLebanese food located in Beirut. In this city, there are a plenty of shoppingmalls, restaurants, bars and hotels that attract people to visit that area, andconsequently, the customers will confront many alternatives for a specificobject (e.g.

restaurant). SamplingFrameNon-probability sampling technique will adopt in this study asthere is an inaccessibility to gain sufficient information for a samplingframe. The research will base on Zomato. It is an online application; Zomatocovers more than 3,800 restaurants in Beirut and is available on web and mobile(iOS, Android, Windows Phone and Blackberry). Through Zomato, users can browsethrough restaurant information, read and write restaurant reviews, sharepictures and build a personal network of people whose trusted opinions. The 10selected top restaurants in Beirut are: El Denye Hek, Loris, Furn Beaino, BabelBay, Diwan Beirut, Socrate, Em Charif, Abd El Wahab, Le pêcheur and Nasma.Sampling ElementsThe sampling elements are therestaurant patrons who have selected a restaurant amongst the top 10 mentionedabove.Sampling sizeAt a  95% confidence levelbased on a 5% margin of error, a population of 100,000 requires 383 samples, while a 10,00,000 will need 384samples  (Saunders et al.

, 2009). Thus, atotal of 500 questionnaires will be distributed to the target respondentsResearchInstrumentA self-administered pilot test will conduct, and a survey questionnaireswill be used in this research because this is the most commonly used method toobtain data from a huge amount of respondents. Besides that, it is quick,efficient, less costly and accurate in assessing information from the targetrespondents.Construct MeasurementFirstly, demographic details will be asked to gather data about therespondent’s age, education level achieved, the monthly income, and thefrequency of using online application to select restaurant. Secondly, thesurvey questionnaires will consist questions about the independent variables (e-WOM)and the dependent variable (attitude, subjective norms, and perceivedbehavioral control), then the independent variables (attitude, subjectivenorms, and perceived behavioral control), and the dependent variable (intentionto select restaurant).   ReferencesAjzen, I.

and Fishbein, M. (1980), Understanding Attitudes and Predicting SocialBehavior, Prentice-Hall, Englewood Cliffs, NJ.Ajzen, I.(1991), “The theory of planned behavior”, Organizational Behavior and HumanDecision Process, Vol. 50 No. 2, pp. 179-211 Ajzen, I.

(2001), “Attitudes”, Annual Review of Psychology, Vol. 52 No. 1, pp. 27-58.

Ajzen, I.(2011), “Theory of planned behaviour”, in van Lange, P.A.M., Kruglanski, A.W.and Higgins, E.

T. (Eds), Handbook of Theories of Social Psychology: Volume One,Sage Publication, pp. 438-459.Baber,A., Thurasamy, R., Malik, M.I.

, Sadiq, B., Islam, S. and Sajjad, M. (2016),”Online word-of-mouth antecedents, attitude and intention-to purchaseelectronic products in Pakistan”, Telematics and Informatics, Vol. 33 No. 2,pp.

388-400.Babrow,A.S., Black, D.

R. and Tiffany, S.T.

(1990), “Beliefs, attitudes, intentions,and a smokingcessation program: a planned behavior analysis of communicationcampaign development”, Health Communication, Vol. 2 No. 3, pp. 145-63.Baloglu,S. and McCleary, K.W. (1999), “A model of destination image formation”, Annalsof Tourism Research, Vol.

35 No. 4, pp. 11-15.Chatterjee,P. (2001), “Online reviews: do consumers use them?”, Advances in ConsumerResearch, Vol. 28 No.

1, pp. 129-33.Cheng,S., Lam, T.

and Hsu, C.H.C. (2006), “Negative word-of-mouth communicationintention: an application of the theory of planned behavior”, Journal ofHospitality & Tourism Research, Vol.

30 No. 1, pp. 95-116.Cousins,J.

, Foskett, D. and Gillespie, C. (2002), Food and Beverage Management, 2nded.

, Prentice-Hall, HarlowDavis,F.D., Bagozzi, R.P.

and Warshaw, P.R. (1989), “User acceptance of computertechnology: a comparison of two theoretical models”, Management Science, Vol.35 No.

8, pp. 982-1003Fishbein,M. and Ajzen, I. (1975), Belief, Attitude, Intention, and Behavior: AnIntroduction to Theory and Research, Addison-Wesley, Reading, MA.Flannery,B.L. and May, D.

R. (2000), “Environmental ethical decision making in the USmetal-finishing industry”, Academy of Management Journal, Vol. 43 No.

4, pp.642-62. Guoqing,G., Zhongke, Z., Kai, C. and Xiaofan, W. (2009), “The influence of WOM onconsumers’ intention of brand switching: the mediate role of subjective norms”,paper presented at the Summit International Marketing Science and ManagementTechnology Conference, December, Beijing, December 26-29, available at:www.

seiofbluemountain.com/upload/ product/200911/2009scyxhy01a8.pdf (accessedFebruary 28, 2011).Kasabov,E. (2016), “Unknown, surprising, and economically significant: the realities ofelectronic word of mouth in Chinese social networking sites”, Journal ofBusiness Research, Vol. 69 No. 2, pp.

642-652.Mathieson,K. (1991), “Predicting user intentions: comparing the technology acceptancemodel with the theory of planned behavior”, Information Systems Research, Vol.2 No. 3, pp. 173-91.Morris,M.G.

, Venkatesh, V. and Ackerman, P. (2005), “Gender and age differences inemployee decisions about new technology: an extension to the theory of plannedbehavior”, IEEE Transactions on Engineering Management, Vol. 52 No. 1, pp.

69-84Pavlou,P.A. and Fygenson, M.

(2006), “Understanding and predicting electronic commerceadoption: an extension of the theory of planned behavior”, MIS Quarterly, Vol.30 No. 1, pp. 115-43.Taylor,S.

and Todd, P. (1995), “Decomposition and crossover effects in the theory ofplanned behaviour: a study of consumer adoption intentions”, InternationalJournal of Research in Marketing, Vol. 12 No.

2, pp. 137-55.Saunders,M.

, Lewis, P., & Thornhill, A. (2009). Research methods for business  students. (5th  Edition.

). Essex: Pearson Education LimitedSen, S.and Lerman, D. (2007), “Why are you telling me this? An examination intonegative consumer reviews on the web”, Journal of Interactive Marketing, Vol.21 No. 4, pp.

76-94.Ying,H.L. and Chung, C.

M.Y. (2007), “The effects of single-message single-sourcemixed word-ofmouth on product attitude and purchase intention”, Asia PacificJournal of Marketing, Vol. 19 No. 1, pp. 75-86.