Utilitarian and Hedonic Values of eWOM Media and Online Booking Decisions for Tourist Destinations in India
Abstract
:1. Introduction
2. Literature Review
2.1. Utilitarian Value vs. Hedonic Value
2.2. Information Quality
2.3. Reviewer Proficiency
2.4. Reviewer Trustworthiness
2.5. Perceived Curiosity Fulfilment
2.6. Perceived Enjoyment
2.7. Ease of Use
2.8. Perceived Usefulness (PU)
2.9. Male vs. Female
3. Proposed Model and Hypotheses Formulation
4. Methodology
4.1. Sample Framework and Data Collection
4.2. Questionnaire Design and Measurement
4.3. Tools and Techniques
5. Findings
5.1. Descriptive Information
5.2. Exploratory Factor Analysis
5.3. Evaluating Measurement Model
5.4. Evaluating Structural Model
6. Discussion and Conclusions
Utilitarian and Hedonic Values of eWOM Media and Open Innovation
7. Theoretical Implications
8. Practical Implications
9. Limitation and Future Scope
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
(Part A) | ||
---|---|---|
Questions | Variables | Measurements |
1. | Gender |
|
2. | Age |
|
3. | Qualification |
|
4. | What is your primary source to get the information about tourist destinations in India? |
|
(Part B) | ||
Factors | Items | |
Information quality [52,53] | IQ1: The eWOM media provided me with the correct information about tourist destinations | |
IQ2: The information provided by the eWOM media was relevant to my requirements. | ||
IQ3: The tourist destinations information provided by the eWOM media is always up-to-date. | ||
IQ4: The information available on the eWOM media were very well organised. | ||
Reviewer proficiency [54] | RP1: People who left reviews on eWOM media are knowledgeable. | |
RP2: People who left reviews on eWOM media are experts. | ||
RP3: People who left reviews on eWOM media are experienced ones. | ||
Reviewer trustworthiness [54] | RT1: People who left reviews on eWOM media are reliable. | |
RT2: People who left reviews on eWOM media are honest. | ||
RT3: People who left reviews on eWOM media are sincere. | ||
RT4: People who left reviews on eWOM media have integrity. | ||
Perceived curiosity fulfilment [12,37] | PCF1: My imagination for tourist destinations develops when I use eWOM media. | |
PCF2: Interacting with this eWOM media makes me curious about searching for more tourist destinations. | ||
PCF3: Reading reviews of other reviewers on eWOM media excites my curiosity. | ||
Enjoyment [12,37] | ENJT1: Using eWOM media creates fun. | |
ENJT2: It was delightful to use eWOM media. | ||
ENJT3: It was exciting to interact with other experts on eWOM media. | ||
ENJT4: I find eWOM media usage very boring. | ||
Ease of Use [12] | EOU1: I feel comfortable using eWOM media. | |
EOU2: The eWOM media facilitates me to navigate anywhere within the website. | ||
EOU3: I find it easy to gain expertise using eWOM media. | ||
Perceived usefulness [12,37] | PUF1: The eWOM media enhances my knowledge of various tourist destinations. | |
PUF2: The eWOM media facilitates me to get information quickly regarding various tourist destinations. | ||
PUF3: The eWOM media assists me in getting various tourist destinations information more efficiently. | ||
PUF4: The eWOM media assists me in making online booking decisions more efficiently. | ||
Online booking decision [37,55] | OBD1: After using eWOM media, it is good to make an online purchase decision for tourism products and services. | |
OBD2: After using eWOM media, I have the intention to book tourist destinations online. | ||
OBD3: After using eWOM media, I am optimistic about making an online booking for a tourist destination. |
References
- Equitymaster. Indian Hotels Industry Report—Hotels Sector Research & Analysis in India. 2020. Available online: https://www.equitymaster.com/research-it/sector-info/hotels/Hotels-Sector-Analysis-Report.asp (accessed on 10 March 2022).
- Liu, Z.; Park, S. What makes a useful online review? Implication for travel product websites. Tour. Manag. 2015, 47, 140–151. [Google Scholar] [CrossRef] [Green Version]
- Kuan, K.K.Y.; Hui, K.L.; Prasarnphanich, P.; Lai, H.Y. What makes a review voted? An empirical investigation of review voting in online review systems. J. Assoc. Inf. Syst. 2015, 16, 48–71. [Google Scholar] [CrossRef] [Green Version]
- Cheung, C.M.K.; Lee, M.K.O. What drives consumers to spread electronic word of mouth in online consumer-opinion platforms. Decis. Support Syst. 2012, 53, 218–225. [Google Scholar] [CrossRef]
- Werenowska, A.; Rzepka, M. The role of social media in Generation Y travel decision-making process (Case Study in Poland). Information 2020, 11, 396. [Google Scholar] [CrossRef]
- Nusair, K.; Hua, N.; Ozturk, A.; Butt, I. A theoretical framework of electronic word-of-mouth against the backdrop of social networking websites. J. Travel Tour. Mark. 2017, 34, 653–665. [Google Scholar] [CrossRef]
- Cantallops, A.S.; Salvi, F. New consumer behavior: A review of research on eWOM and hotels. Int. J. Hosp. Manag. 2014, 36, 41–51. [Google Scholar] [CrossRef]
- Statista. Social Network User Penetration in India from 2015 to 2020, with Estimates Until 2025. 2022. Available online: https://www.statista.com/statistics/240960/share-of-indian-population-using-social-networks/ (accessed on 10 March 2022).
- Hu, Y.H.; Chen, K.; Lee, P.J. The effect of user-controllable filters on the prediction of online hotel reviews. Inf. Manag. 2017, 54, 728–744. [Google Scholar] [CrossRef]
- Elwalda, A.; Lü, K.; Ali, M. Perceived derived attributes of online customer reviews. Comput. Hum. Behav. 2016, 56, 306–319. [Google Scholar] [CrossRef] [Green Version]
- Venkatesh, V.; Davis, F.D. A theoretical extension of the technology acceptance model: Four longitudinal field studies. Manag. Sci. 2000, 46, 186–204. [Google Scholar] [CrossRef] [Green Version]
- Agarwal, R.; Karahanna, E. Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage. MIS Q. 2000, 24, 665–694. [Google Scholar] [CrossRef]
- Anderson, K.C.; Knight, D.K.; Pookulangara, S.; Josiam, B. Influence of hedonic and utilitarian motivations on retailer loyalty and purchase intention: A facebook perspective. J. Retail. Consum. Serv. 2014, 21, 773–779. [Google Scholar] [CrossRef]
- Deci, E.L.; Ryan, R.M. The general causality orientations scale: Self-Determination in personality. J. Res. Pers. 1985, 19, 109–134. [Google Scholar] [CrossRef]
- Chandon, P.; Wansink, B.; Laurent, G. A Benefit Congruency Framework of Sales Promotion Effectiveness. J. Mark. 2000, 64, 65–81. Available online: http://www.jstor.org/stable/3203478 (accessed on 14 February 2022). [CrossRef]
- Thakur, R. Understanding customer engagement and loyalty: A case of mobile devices for shopping. J. Retail. Consum. Serv. 2016, 32, 151–163. [Google Scholar] [CrossRef]
- Ayeh, J.K.; Au, N.; Law, R. Do we believe in TripAdvisor? Examining credibility perceptions and online travelers’ attitude toward using user-generated content. J. Travel Res. 2013, 52, 437–452. [Google Scholar] [CrossRef]
- Pappas, I.O.; Kourouthanassis, P.E.; Giannakos, M.N.; Lekakos, G. The interplay of online shopping motivations and experiential factors on personalised e-commerce: A complexity theory approach. Telemat. Inform. 2017, 34, 730–742. [Google Scholar] [CrossRef]
- Chakraborty, U. Perceived credibility of online hotel reviews and its impact on hotel booking intentions. Int. J. Contemp. Hosp. Manag. 2019, 31, 3465–3483. [Google Scholar] [CrossRef]
- Hwang, J.; Park, S.; Woo, M. Understanding user experiences of online travel review websites for hotel booking behaviours: An investigation of a dual motivation theory. Asia Pac. J. Tour. Res. 2018, 23, 359–372. [Google Scholar] [CrossRef]
- Lee, J.; Park, D.H.; Han, I. The effect of negative online consumer reviews on product attitude: An information processing view. Electron. Commer. Res. Appl. 2008, 7, 341–352. [Google Scholar] [CrossRef]
- Lin, J.C.C.; Lu, H. Towards an understanding of the behavioural intention to use a website. Int. J. Inf. Manag. 2000, 20, 197–208. [Google Scholar] [CrossRef]
- Park, J.H.; Gu, B.; Leung, A.C.M.; Konana, P. An investigation of information sharing and seeking behaviors in online investment communities. Comput. Hum. Behav. 2014, 31, 1–12. [Google Scholar] [CrossRef]
- Cheung, C.M.; Thadani, D.R. The impact of electronic word-of-mouth communication: A literature analysis and integrative model. Decis. Support Syst. 2012, 54, 461–470. [Google Scholar] [CrossRef]
- Park, D.H.; Lee, J. eWOM overload and its effect on consumer behavioral intention depending on consumer involvement. Electron. Commer. Res. Appl. 2008, 7, 386–398. [Google Scholar] [CrossRef]
- Filieri, R.; McLeay, F.; Tsui, B.; Lin, Z. Consumer perceptions of information helpfulness and determinants of purchase intention in online consumer reviews of services. Inf. Manag. 2018, 55, 956–970. [Google Scholar] [CrossRef]
- Jamil, R.A.; Hasnu, S.A.F. Consumer’s Reliance on Word of Mouse: Influence on Consumer’s Decision in an Online Information Asymmetry Context. J. Bus. Econ. 2013, 5, 171–205. Available online: https://journals.au.edu.pk/ojs/index.php/jbe/article/view/59 (accessed on 10 December 2021).
- Kim, S.; Park, J.; Lee, Y. The E-Word-of-Mouth effect on consumers internet shopping behaviour: Focus on apparel products. Int. J. Fash. Des. Technol. Educ. 2013, 6, 160–172. [Google Scholar] [CrossRef]
- Wang, X.; Wei, K.-K.; Teo, H.-H. The Acceptance of Product Recommendations from Web-Based Word-of-Mouth Systems: Effects of Information, Informant and System characteristics. In ICIS 2007 Proceedings. 2007. Available online: https://aisel.aisnet.org/icis2007/93 (accessed on 12 October 2021).
- Watts, S.A.; Zhang, W. Capitalizing on content: Information adoption in two online communities. J. Assoc. Inf. Syst. 2008, 9, 73–94. [Google Scholar] [CrossRef]
- Yoo, K.H.; Lee, Y.; Gretzel, U.; Fesenmaier, D.R. Trust in travel-related consumer generated media trust in travel-related consumer generated media. Inf. Commun. Technol. Tour. 2009, 2009, 49–59. [Google Scholar] [CrossRef] [Green Version]
- Hu, T.; Kettinger, W.J.; Poston, R.S. The effect of online social value on satisfaction and continued use of social media. Eur. J. Inf. Syst. 2017, 24, 391–410. [Google Scholar] [CrossRef]
- Van Dijk, E.; Zeelenberg, M. When curiosity killed regret: Avoiding or seeking the unknown in decision-making under uncertainty. J. Exp. Soc. Psychol. 2007, 43, 656–662. [Google Scholar] [CrossRef]
- Menon, S.; Soman, D. Managing the power of curiosity for effective web advertising strategies. J. Advert. 2013, 31, 1–14. [Google Scholar] [CrossRef]
- Reychav, I.; Wu, D. Are your users actively involved? A cognitive absorption perspective in mobile training. Comput. Hum. Behav. 2015, 44, 335–346. [Google Scholar] [CrossRef]
- Koo, C.; Chung, N. Examining the eco-technological knowledge of Smart Green IT adoption behavior: A self-determination perspective. Technol. Forecast. Soc. Change 2014, 88, 140–155. [Google Scholar] [CrossRef]
- Wang, P.; Li, H. Understanding the antecedents and consequences of the perceived usefulness of travel review websites. Int. J. Contemp. Hosp. Manag. 2019, 31, 1086–1103. [Google Scholar] [CrossRef]
- Padilla-Meléndez, A.; del Aguila-Obra, A.R.; Garrido-Moreno, A. Perceived playfulness, gender differences and technology acceptance model in a blended learning scenario. Comput. Educ. 2013, 63, 306–317. [Google Scholar] [CrossRef]
- Visinescu, L.L.; Sidorova, A.; Jones, M.C.; Prybutok, V.R. The influence of website dimensionality on customer experiences, perceptions and behavioral intentions: An exploration of 2D vs. 3D web design. Inf. Manag. 2015, 52, 1–17. [Google Scholar] [CrossRef]
- Davis, F.D. A Technology Acceptance Model for Empirically Testing New End-User Information Systems: Theory and Results. Ph.D. Thesis, Masachussets Institute of Technology, Sloan School of Management, Cambridge, MA, USA, 1985. Available online: http://hdl.handle.net/1721.1/15192 (accessed on 14 October 2021).
- Fard, M.H.; Marvi, R. Viral marketing and purchase intentions of mobile applications users. Int. J. Emerg. Mark. 2020, 15, 287–301. [Google Scholar] [CrossRef]
- Tarhini, A.; Hone, K.; Liu, X. The effects of individual differences on e-learning users’ behaviour in developing countries: A structural equation model. Comput. Hum. Behav. 2014, 41, 153–163. [Google Scholar] [CrossRef] [Green Version]
- Kim, J.S. An extended technology acceptance model in behavioral intention toward hotel tablet apps with moderating effects of gender and age. Int. J. Contemp. Hosp. Manag. 2016, 28, 1535–1553. [Google Scholar] [CrossRef]
- Tan, G.W.H.; Ooi, K.B. Gender and age: Do they really moderate mobile tourism shopping behavior? Telemat. Inform. 2018, 35, 1617–1642. [Google Scholar] [CrossRef]
- Herrero, Á.; Martín, H.S. Developing and testing a global model to explain the adoption of websites by users in rural tourism accommodations. Int. J. Hosp. Manag. 2012, 31, 1178–1186. [Google Scholar] [CrossRef]
- Amin, M.; Resaei, S.; Abolghasemi, M. User satisfaction with mobile websites: The impact of perceived usefulness (PU), perceived ease of use (PEOU) and trust. Nankai Bus. Rev. Int. 2014, 5, 258–274. [Google Scholar] [CrossRef]
- Racherla, P.; Friske, W. Perceived ‘usefulness’ of online consumer reviews: An exploratory investigation across three services categories. Electron. Commer. Res. Appl. 2012, 11, 548–559. [Google Scholar] [CrossRef]
- Litvin, S.W.; Goldsmith, R.E.; Pan, B. Electronic word-of-mouth in hospitality and tourism management. Tour. Manag. 2008, 29, 458–468. [Google Scholar] [CrossRef]
- Kowatsch, T.; Maass, W. In-store consumer behavior: How mobile recommendation agents influence usage intentions, product purchases, and store preferences. Comput. Hum. Behav. 2010, 26, 697–704. [Google Scholar] [CrossRef] [Green Version]
- Ramkissoon, H.; Nunkoo, R. More than just biological sex differences: Examining the structural relationship between gender identity and information search behavior. J. Hosp. Tour. Res. 2012, 36, 191–215. [Google Scholar] [CrossRef]
- Lynott, P.P.; Mccandless, N.J. The impact of age vs. life experience on the gender role attitudes of women in different cohorts. J. Women Aging 2000, 12, 5–21. [Google Scholar] [CrossRef]
- Cheung, C.M.K.; Lee, M.K.O.; Rabjohn, N. The impact of electronic word-of-mouth: The adoption of online opinions in online customer communities. Internet Res. 2008, 18, 229–247. [Google Scholar] [CrossRef]
- Hsu, C.L.; Chang, K.C.; Chen, M.C. The impact of website quality on customer satisfaction and purchase intention: Perceived playfulness and perceived flow as mediators. Inf. Syst. E-Bus. Manag. 2012, 10, 549–570. [Google Scholar] [CrossRef]
- Ayeh, J.K. Travellers’ acceptance of consumer-generated media: An integrated model of technology acceptance and source credibility theories. Comput. Hum. Behav. 2015, 48, 173–180. [Google Scholar] [CrossRef]
- Lee, J.; Lee, J.N. Understanding the product information inference process in electronic word-of-mouth: An objectivity-subjectivity dichotomy perspective. Inf. Manag. 2009, 46, 302–311. [Google Scholar] [CrossRef]
- Roy, S.; Nagpaul, P.S.; Mohapatra, P.K. Developing a model to measure the effectiveness of research units. Int. J. Oper. Prod. Manag. 2003, 23, 1514–1531. [Google Scholar] [CrossRef]
- Hair, J.F., Jr.; Black, W.C.; Babin, B.J.; Anderson, R.E. Multivariate Data Analysis, 8th ed.; Cengage: Noida, India, 2018; ISBN 9789353501358. [Google Scholar]
- Chin, W.W. Issues and opinion on structural equation modeling. MIS Q. 1998, 22, 7–16. Available online: https://www.jstor.org/stable/249674 (accessed on 13 March 2021).
- Bagozzi, R.P.; Yi, Y. On the evaluation of structural equation models. J. Acad. Mark. Sci. 1988, 16, 74–94. [Google Scholar] [CrossRef]
- Fornell, C.; Larcker, D.F. Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 1981, 18, 39–50. [Google Scholar] [CrossRef]
- Bentler, P.M.; Bonett, D.G. Significance tests and goodness of fit in the analysis of covariance structures. Psychol. Bull. 1980, 88, 588–606. [Google Scholar] [CrossRef]
- Erkan, I.; Evans, C. The influence of eWOM in social media on consumers’ purchase intentions: An extended approach to information adoption. Comput. Hum. Behav. 2016, 61, 47–55. [Google Scholar] [CrossRef]
- Tsao, W.C.; Hsieh, M.T. eWOM persuasiveness: Do eWOM platforms and product type matter? Electron. Commer. Res. 2015, 15, 509–541. [Google Scholar] [CrossRef]
- Wei, K.; Ram, J. Perceived usefulness of podcasting in organisational learning: The role of information characteristics. Comput. Hum. Behav. 2016, 64, 859–870. [Google Scholar] [CrossRef]
- Chaiken, S. Heuristic versus systematic information processing and the use of source versus message cues in persuasion. J. Pers. Soc. Psychol. 1980, 39, 752–766. [Google Scholar] [CrossRef]
- Atkinson, M.A.; Kydd, C. Individual characteristics associated with world wide web use: An empirical study of playfulness and motivation. ACM SYGMIS Database Data Base Adv. Inf. Syst. 1997, 28, 53–62. [Google Scholar] [CrossRef]
- Acheampong, P.; Zhiwen, L.; Hiran, K.K.; Serwaa, O.E.; Boateng, F.; Bediako, I.A. Examining the intervening role of age and gender on mobile payment acceptance in Ghana: UTAUT Model. Can. J. Appl. Sci. Technol. 2018, 6, 141–151. Available online: http://www.onlinejournal.org.uk/index.php/cajast/article/view/303/305 (accessed on 15 September 2021).
- Assaker, G. Age and gender differences in online travel reviews and user-generated-content (UGC) adoption: Extending the technology acceptance model (TAM) with credibility theory. J. Hosp. Mark. Manag. 2020, 29, 428–449. [Google Scholar] [CrossRef]
- Chesbrough, H.W. Open Innovation: The New Imperative for Creating and Profiting from Technology; Harvard Business School Press: Boston, MA, USA, 2003. [Google Scholar]
- Salter, A.; Ter Wal, A.L.J.; Criscuolo, P.; Alexy, O. Open for ideation: Individual level openness and idea generation in R&D. J. Prod. Innov. Manag. 2015, 32, 488–504. [Google Scholar] [CrossRef] [Green Version]
- Zhang, K.; Chen, Y.; Lin, Z. Mapping destination images and behavioral patterns from user-generated photos: A computer vision approach. Asia Pac. J. Tour. Res. 2020, 25, 1199–1214. [Google Scholar] [CrossRef]
- Chesbrough, H.; Vanhaverbeke, W.; West, J. (Eds.) Open Innovation: Researching A New Paradigm; Oxford University Press: Oxford, UK, 2006. [Google Scholar]
- Fernandes, C.; Ferreira, J.; Peris-Ortiz, M. Open Innovation: Past, Present and Future Trends. J. Organ. Change Manag. 2019, 32, 578–602. [Google Scholar] [CrossRef]
- West, J.; Bogers, M. Leveraging external sources of innovation: A review of research on open innovation. J. Prod. Innov. Manag. 2013, 31, 814–831. [Google Scholar] [CrossRef]
- Yun, J.J.; Park, K.; Gaudio, G.D.; Corte, V.D. Open innovation ecosystems of restaurants: Geographical economics of successful restaurants from three cities. Eur. Plan. Stud. 2020, 28, 2348–2367. [Google Scholar] [CrossRef]
- Marasco, A.; De Martino, M.; Magnotti, F.; Morvillo, A. Collaborative innovation in tourism and hospitality: A systematic review of the literature. Int. J. Contemp. Hosp. Manag. 2018, 30, 2364–2395. [Google Scholar] [CrossRef]
- Behrens, J. The Effects of Familiarity and Online Consumer Reviews, on Consumers’ Trust, Risk Perception, and Behavioral Intentions. Master’s Thesis, University of Twente, Enschede, The Netherlands, 2014. [Google Scholar]
- Yun, J.J.; Cooke, P.; Park, J. Evolution and variety in complex geographies and enterprise policies. Eur. Plan. Stud. 2017, 25, 729–738. [Google Scholar] [CrossRef] [Green Version]
- Filieri, R.; McLeay, F. E-WOM and accommodation: An analysis of the factors that influence travelers’ adoption of information from online reviews. J. Travel Res. 2013, 53, 44–57. [Google Scholar] [CrossRef]
Variables | N | Frequency (%) | |
---|---|---|---|
Gender | Male | 175 | 51.77% |
Female | 163 | 48.22% | |
Age | <25 | 158 | 46.74% |
26–35 | 63 | 18.63% | |
36–45 | 61 | 18.04% | |
>46 | 56 | 16.56% | |
Educational qualification | Under-graduate | 105 | 31.06% |
Post-graduate | 195 | 57.69% | |
Others | 38 | 11.24% | |
Source of tourist destination information | Official tourism sites | 21 | 6.21% |
Travel review sites | 207 | 61.24% | |
Social networking sites | 56 | 16.56% | |
Personal travel blogs | 28 | 8.28% | |
Travel agency | 15 | 4.43% | |
Others | 11 | 3.25% |
KMO | Bartlett’s Test |
---|---|
0.878 | Approx. Chi-Square (6679.156) |
df (378) | |
Sig. (0.000) |
Variables | C1 | C2 | C3 | C4 | C5 | C6 | C7 | C8 |
---|---|---|---|---|---|---|---|---|
RP1 | 0.858 | |||||||
RP2 | 0.886 | |||||||
RP3 | 0.863 | |||||||
PENJ1 | 0.872 | |||||||
PENJ2 | 0.849 | |||||||
PENJ3 | 0.90 | |||||||
PENJ4 | 0.864 | |||||||
EOU1 | 0.842 | |||||||
EOU2 | 0.870 | |||||||
EOU3 | 0.864 | |||||||
PCF1 | 0.837 | |||||||
PCF2 | 0.879 | |||||||
PCF3 | 0.860 | |||||||
RT1 | 0.861 | |||||||
RT2 | 0.901 | |||||||
RT3 | 0.90 | |||||||
RT4 | 0.854 | |||||||
IQ1 | 0.843 | |||||||
IQ2 | 0.847 | |||||||
IQ3 | 0.899 | |||||||
IQ4 | 0.811 | |||||||
PU1 | 0.833 | |||||||
PU2 | 0.791 | |||||||
PU3 | 0.849 | |||||||
PU4 | 0.822 | |||||||
OBD1 | 0.716 | |||||||
OBD2 | 0.805 | |||||||
OBD3 | 0.784 | |||||||
Total Variance Explained (Cumulative%) | 17.56 | 22.237 | 18.726 | 40.963 | 52.33 | 60.904 | 69.459 | 77.956 |
Construct | Items | Items Loading | CR | AVE |
---|---|---|---|---|
Reviewer proficiency | RP1 | 0.825 | 0.874 | 0.699 |
RP2 | 0.888 | |||
RP3 | 0.791 | |||
Perceived enjoyment | PENJ1 | 0.873 | 0.918 | 0.737 |
PENJ2 | 0.854 | |||
PENJ3 | 0.875 | |||
PENJ4 | 0.832 | |||
Ease of use | EOU1 | 0.787 | 0.863 | 0.678 |
EOU2 | 0.862 | |||
EOU3 | 0.818 | |||
Perceived curiosity fulfilment | PCF1 | 0.816 | 0.868 | 0.686 |
PCF2 | 0.842 | |||
PCF3 | 0.828 | |||
Reviewer trustworthiness | RT1 | 0.888 | 0.932 | 0.775 |
RT2 | 0.911 | |||
RT3 | 0.871 | |||
RT4 | 0.851 | |||
Information quality | IQ1 | 0.842 | 0.913 | 0.725 |
IQ2 | 0.829 | |||
IQ3 | 0.910 | |||
IQ4 | 0.819 | |||
Perceived usefulness | PU1 | 0.862 | 0.908 | 0.712 |
PU2 | 0.761 | |||
PU3 | 0.885 | |||
PU4 | 0.792 | |||
Online booking decision | OBD1 | 0.758 | 0.855 | 0.662 |
OBD2 | 0.832 | |||
OBD3 | 0.796 |
HV_PENJ | HV_RP | HV_EOU | HV_PCF | HV_RT | UV_IQ | PU | OBD | |
---|---|---|---|---|---|---|---|---|
HV_PENJ | 0.859 | |||||||
HV_RP | 0.168 | 0.836 | ||||||
HV_EOU | 0.253 | 0.288 | 0.823 | |||||
HV_PCF | 0.193 | 0.275 | 0.185 | 0.828 | ||||
HV_RT | 0.288 | 0.233 | 0.160 | 0.330 | 0.880 | |||
UV_IQ | 0.263 | 0.137 | 0.185 | 0.265 | 0.309 | 0.851 | ||
PU | 0.290 | 0.272 | 0.342 | 0.295 | 0.313 | 0.402 | 0.844 | |
OBD | 0.292 | 0.218 | 0.286 | 0.257 | 0.315 | 0.426 | 0.718 | 0.814 |
Hypotheses | Estimate | SE | CR | P | Findings |
---|---|---|---|---|---|
H1: The PU of eWOM media is determined by the quality of information available. | 0.299 | 0.036 | 5.313 | *** | Supported at 99% |
H2: The PU of eWOM media is determined by the tourist’s belief in the reviewer’s proficiency. | 0.118 | 0.049 | 2.113 | 0.035 | Supported at 95% |
H3: The PU of eWOM media is determined by the tourist’s belief in the reviewer’s trustworthiness. | 0.137 | 0.035 | 2.534 | 0.011 | Supported at 95% |
H4. Perceived curiosity fulfilment regarding eWOM media strongly determines its PU. | 0.124 | 0.04 | 2.272 | 0.023 | Supported at 95% |
H5. Perceived enjoyment regarding eWOM media usage strongly determines its PU. | 0.114 | 0.046 | 2.031 | 0.042 | Supported at 95% |
H6: The PU of eWOM media is determined by the tourist’s belief in its ease of use. | 0.217 | 0.054 | 3.788 | *** | Supported at 99% |
H7: PU of eWOM media leads to OBD for tourist destinations. | 0.704 | 0.061 | 9.79 | *** | Supported at 99% |
Moderation Analysis | |||||
H8: Gender moderates the effect that PU of eWOM media has on OBD. | |||||
Male | 0.788 | 0.014 | 58.037 | *** | |
Female | 0.562 | 0.020 | 28.698 | *** | |
Z score (>2.58) | 3.448 | Supported at 99% |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Tariyal, A.; Bisht, S.; Rana, V.; Roy, S.; Pratap, S. Utilitarian and Hedonic Values of eWOM Media and Online Booking Decisions for Tourist Destinations in India. J. Open Innov. Technol. Mark. Complex. 2022, 8, 137. https://doi.org/10.3390/joitmc8030137
Tariyal A, Bisht S, Rana V, Roy S, Pratap S. Utilitarian and Hedonic Values of eWOM Media and Online Booking Decisions for Tourist Destinations in India. Journal of Open Innovation: Technology, Market, and Complexity. 2022; 8(3):137. https://doi.org/10.3390/joitmc8030137
Chicago/Turabian StyleTariyal, Amit, Swati Bisht, Vinay Rana, Santanu Roy, and Sumit Pratap. 2022. "Utilitarian and Hedonic Values of eWOM Media and Online Booking Decisions for Tourist Destinations in India" Journal of Open Innovation: Technology, Market, and Complexity 8, no. 3: 137. https://doi.org/10.3390/joitmc8030137