Tourism has expanded dramatically in Nigeria over the last six decades, becoming one of the largest and fastest-growing sectors of the Nigerian like in the global economy. The World Travel and Tourism index ranked Nigeria 129th out of 140 countries and Nigeria’s ranking is well below average rankings for sub-Saharan Africa. This study was motivated by the need to explore the antecedents of tourists’ behavioural intentions from the perspectives of the expectations confirmation model. The study extended the model by adding perceived trust to original components. Several studies have been conducted from the perspective of this model in tourism in many countries but none in Nigeria. The study was based on a sample 400 tourists selected from the five states in the South East geopolitical zone of Nigeria out of which 317 respondents returned valid questionnaire. The study population was infinite hence respondents were those seen at the various tourist sites and who agreed to fill the questionnaire. The analysis utilized partial least squares structural equations modelling (PLS-SEM) with the aid of WarpPLS version 7.0. All the hypothesised relationships are statistically significant (Table 6). The 95% confidence intervals straddle no zero in-between for all the hypotheses. The Effect sizes in our analysis range from as high as 0.409 for Confirmation which is the highest to 0.209 for PP and 0.149 for CE. Conf. and PT have 0.094 and 0.084 respectively hence all the IVs in our analysis fall within acceptable range from medium to high effect sizes and are all considered relevant in our model. Implications of the study were also discussed and recommendations for further study were also made.
| Published in | International Journal of Education, Culture and Society (Volume 6, Issue 5) |
| DOI | 10.11648/j.ijecs.20210605.13 |
| Page(s) | 176-189 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Antecedent, Tourist, Behavioural Intention, Confirmation Model, Tourism, Southeast Nigeria
| [1] | World Travel and Tourism Council (WTTC, 2020), Nigeria: 2020 Annual research: key highlights. Online. |
| [2] | Oliver RL (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 460–469. |
| [3] | Weber K (1997). The assessment of tourist satisfaction using the expectancy disconfirmation theory: A study of the German travel market in Australia, Pacific Tourism Review, 1 (1): 35–45. |
| [4] | Johnson MD & C Fornell (1991). A framework for comparing customer satisfaction across individuals and product categories. Journal of Economic Psychology, 12: 267–286. |
| [5] | Wong IA & LDA Dioko (2013). Understanding the mediated moderating role of customer expectations in the customer satisfaction model: The case of casinos, Tourism Management, 36; 188–199. |
| [6] | Mohajerani P & A Miremadi (2012). Customer Satisfaction Modeling in Hotel Industry: A Case Study of Kish Island in Iran. International Journal of Marketing Studies, 4 (3); Canadian Centre of Science and Education, www.ccsenet.org/ijms |
| [7] | Aziz NA, Arffin AAM, Omar NA & SK Yoon (2011). An investigation of international and domestic satisfaction in heritage context: Implications for destination marketing, Journal Pengursan, 33 (11): 61-76. |
| [8] | Yunduk, J, Suk-Kyu K & Y Jae-Gu (2019). Determinants of Behavioural Intentions in the Context of Sport Tourism with the Aim of Sustaining Sporting Destinations, Sustainability 2019, 11, 3073; doi: 10.3390/su11113073 www.mdpi.com/journal/sustainability |
| [9] | United Nations World Tourism Organisation (UNWTO) (1995), Technical Manual: collection of tourism expenditure statistics, World Tourism Organisation online document. Assessed on 2nd October, 2020. |
| [10] | Goeldner, CR & JRB Ritchie (2012). Tourism: Principles, Practices, and Philosophies, Hoboken, New Jersey: John Wiley & Sons, Inc. |
| [11] | Alamai MM, Kirfi UH, & AF Ladi (2018). Tourism and the Economy of Nigeria: A synthesis of its contributions to GDP from 2005-2016. Advances in Social Sciences Research Journal, 5 (11) 256-263. |
| [12] | Munzali D (2011). Tourism development in Nigeria: challenges and prospects for resource diversification. Accessed July 12 (2021) from: https://www.scribd.com/doc/53329130. |
| [13] | Gunning JG (2000). Models of customer satisfaction and service quality as research instruments in construction management. In: Akintoye A, editor. 16th Annual ARCOM Conference, 6-8 September 2000: 1. Glasgow Caledonian University, Association of Researchers in Construction Management. UK: ARCOM; pp. 21-30. |
| [14] | Anderson RE. What is Customer Satisfaction and Why is it Important? 2010. Retrieved from: https://EzineArticles.com/expert/Rose-Elsa Anderson/725116. |
| [15] | Jiang JJ & G Klein (2009), Expectation-Confirmation Theory: Capitalizing on Descriptive Power, IGI Global, Online Document. |
| [16] | Johnson MD, Gustafson A, Andreassen TW, Lervik L, & J Cha (2001). The evolution and future of national customer satisfaction index models. Journal of economic Psychology, 22 (2): 217-245. |
| [17] | Zeithaml VA, Parasuraman A & LL Berry (1990). Delivering Quality Service. New York: The Free Press. |
| [18] | Bebko CP (2000). Service intangibility and its impact on consumer expectations of service quality, Journal of Services Marketing, 14 (1): 9-26. |
| [19] | Song H, Van der Veen R, Li G & JL Chen (2012). The Hong Kong tourist satisfaction index, Annals of Tourism Research 39 (1): 459–479. |
| [20] | Churchill GA, & C Surprenant (1982). An investigation into the determinants of customer satisfaction, Journal of Marketing Research 1982, 491–504. |
| [21] | Boo S & Busser JA (2018). Tourists' hotel event experience and satisfaction: An integrative approach, Journal of Travel & Tourism Marketing 35 (7), 895–908. |
| [22] | Chen YY, Chien Hsu Y, Chau Tseng H & Y Chen Lee (2010). Confirmation of Expectations and Satisfaction with the Internet Shopping: The Role of Internet Self efficacy, Computer and Information Science, 3 (3), 14-22. |
| [23] | Bhattacherjee A (2001). Understanding s continuance: an expectation-confirmation model. MIS Quarterly, 25 (3), 351-370. |
| [24] | Chiou JS (2004). The antecedents of consumers’ loyalty toward Internet service provider. Information & Management, 41, 685–695. |
| [25] | Reichheld FF (2001). Lead for loyalty. Harvard business review, 76–84. |
| [26] | Gefen D, Karahanna E & D Straub (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27 (1), 51–90. |
| [27] | Wallin AT & B Lindestad (1998). Customer loyalty and complex services: The impact of corporate image on quality, customer satisfaction and loyalty for customers with varying degrees of service expertise. Int. J. Serv. Ind. Manag. 1998, 9, 7–23. |
| [28] | Chi CGQ & H Qu (2008). Examining the structural relationships of destination image, tourist satisfaction and destination loyalty: An integrated approach. Tourism. Management. 2008, 29, 624–636. |
| [29] | Lee DS & Han HS (2016). A study on the behaviour intention of festival visitors by using theory of planned behaviour: Focusing on moderation effect of perceived risk. Tour. Res., 41, 205–225. |
| [30] | Yunduk JI, Yu A & K Suk-Kyu (2020). The Antecedents of Tourists’ Behavioural Intentions at Sporting Events: The Case of South Korea, Sustainability 2020, 11, 3073; doi: 10.3390/su11113073 www.mdpi.com/journal/sustainability |
| [31] | Terblanche N S (2006): An application of the American customer satisfaction index (ACSI) in the South African motor vehicle industry, South African Journal of Business Management, ISSN 2078-5976, African Online Scientific Information Systems (AOSIS), Cape Town, Vol. 37, Iss. 4, pp. 29-38, http://dx.doi.org/10.4102/sajbm.v37i4.611 |
| [32] | Hair JF Bush RP & DJ Ortinau DJ (2003). Marketing research within a changing information environment. New York: McGraw Hill Publishers. Online Edition. |
| [33] | Okeke, T. C., Olise, M. C. & Ezeh, G. A. (2014). Research methods in business and management science. 4th edition. Goder ventures Enugu, Nigeria. |
| [34] | Osakwe, C. N (2019), Understanding customer-perceived quality in informal stores, Journal of Services Marketing, 33 (2), 133-147. https://doi.org/10.1108/JSM-05-2018-0162 |
| [35] | Ibrahim T. I & Roni, S. M. (2017), Partial Least Square Approach to Second Order Factor in Behavioural Study of Accounting Information System, SHS Web of Conferences 36, 00032 (2017). Pp. 1-7. |
| [36] | Koch, N. (2020), WarpPLS user manual: version 7.0, ScriptWarp Systems, Laredo, Texas, USA. Online Edition. Downloaded from: www.scriptwarp.com. Assessed on April 12, 2020. |
| [37] | Pallant, J. (2016). SPSS Survival Manual, 5th Edition. Berkshire, England: Open University Press. |
| [38] | Urbach, Nils & Ahlemann, Frederik (2010). Structural equation modeling in information systems research using partial least squares. Journal of Information Technology and Theory 11 (2): 5-36. |
| [39] | Tabachinick, B. G. &Fidell, L. S. (2013). Using multivariate statistics. Pearson Educational Inc. One Lake Street, Upper Saddle River, New Jersey. |
| [40] | Mackenzie, S. B. & Podsakoff, P. M. (2012), Common Method Bias in Marketing: Causes, Mechanisms, and Procedural Remedies, Journal of Retailing 88 (4), 542–555. |
| [41] | Podsakoff, P. M., MacKenzie, S. B., Podsakoff, P. M., Lee, Jeong-Leon, & Podsakoff, N. P. (2003), Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies,” Journal of Applied Psychology, 88 (5), 879–903. |
| [42] | Bagozzi, R. P., Yi, Y., & Phillips, L. W. (1991). Assessing construct validity in organizational research. Administrative Science Quarterly, 36 (3), 421–458. |
| [43] | Hair, J. F., Black, W. C., Babin, B. J. and Anderson, R. E. (2018), Multivariate Data Analysis, Andover, Hampshire, United Kingdom: Cengage Learning. |
| [44] | Obianefo C. A., Osuafor O. O. & John N. Ng’ombe (2021). On the Challenges Faced by Female Members of Agricultural Cooperatives in Southeast Nigeria. Journal of Agricultural Extension and Rural Development, 13 (2): 94-106. |
| [45] | Obianefo C. A., Osuafor O. O., Ezeano Caleb I. & Anumudu O. O. (2020). Mediation effect of adopting good agronomic practices on rice productivity in Anambra State. International Journal of Agricultural and Rural Development, 23 (1): 4913-4926. |
| [46] | Garson, G. D. (2016). Partial least squares: regression and structural equation models. Glenn Drive Asheboro, NC 27205 USA: Statistical Publishing Associates. E-book. |
| [47] | Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31 (1), 2–24. |
APA Style
Nwatu Basil Chibuike, Nwaizugbo Ireneus Chukwudi, Ganiyu Rahim Ajao. (2021). Antecedents of Tourists Behavioural Intentions, Perspectives of Expectations Confirmation Model: A Study of Select Tourism Cites in South-East Nigeria. International Journal of Education, Culture and Society, 6(5), 176-189. https://doi.org/10.11648/j.ijecs.20210605.13
ACS Style
Nwatu Basil Chibuike; Nwaizugbo Ireneus Chukwudi; Ganiyu Rahim Ajao. Antecedents of Tourists Behavioural Intentions, Perspectives of Expectations Confirmation Model: A Study of Select Tourism Cites in South-East Nigeria. Int. J. Educ. Cult. Soc. 2021, 6(5), 176-189. doi: 10.11648/j.ijecs.20210605.13
AMA Style
Nwatu Basil Chibuike, Nwaizugbo Ireneus Chukwudi, Ganiyu Rahim Ajao. Antecedents of Tourists Behavioural Intentions, Perspectives of Expectations Confirmation Model: A Study of Select Tourism Cites in South-East Nigeria. Int J Educ Cult Soc. 2021;6(5):176-189. doi: 10.11648/j.ijecs.20210605.13
Share This Article
Twitter
Linked In
Facebook
Copy
Download@article{10.11648/j.ijecs.20210605.13,
author = {Nwatu Basil Chibuike and Nwaizugbo Ireneus Chukwudi and Ganiyu Rahim Ajao},
title = {Antecedents of Tourists Behavioural Intentions, Perspectives of Expectations Confirmation Model: A Study of Select Tourism Cites in South-East Nigeria},
journal = {International Journal of Education, Culture and Society},
volume = {6},
number = {5},
pages = {176-189},
doi = {10.11648/j.ijecs.20210605.13},
url = {https://doi.org/10.11648/j.ijecs.20210605.13},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijecs.20210605.13},
abstract = {Tourism has expanded dramatically in Nigeria over the last six decades, becoming one of the largest and fastest-growing sectors of the Nigerian like in the global economy. The World Travel and Tourism index ranked Nigeria 129th out of 140 countries and Nigeria’s ranking is well below average rankings for sub-Saharan Africa. This study was motivated by the need to explore the antecedents of tourists’ behavioural intentions from the perspectives of the expectations confirmation model. The study extended the model by adding perceived trust to original components. Several studies have been conducted from the perspective of this model in tourism in many countries but none in Nigeria. The study was based on a sample 400 tourists selected from the five states in the South East geopolitical zone of Nigeria out of which 317 respondents returned valid questionnaire. The study population was infinite hence respondents were those seen at the various tourist sites and who agreed to fill the questionnaire. The analysis utilized partial least squares structural equations modelling (PLS-SEM) with the aid of WarpPLS version 7.0. All the hypothesised relationships are statistically significant (Table 6). The 95% confidence intervals straddle no zero in-between for all the hypotheses. The Effect sizes in our analysis range from as high as 0.409 for Confirmation which is the highest to 0.209 for PP and 0.149 for CE. Conf. and PT have 0.094 and 0.084 respectively hence all the IVs in our analysis fall within acceptable range from medium to high effect sizes and are all considered relevant in our model. Implications of the study were also discussed and recommendations for further study were also made.},
year = {2021}
}
TY - JOUR T1 - Antecedents of Tourists Behavioural Intentions, Perspectives of Expectations Confirmation Model: A Study of Select Tourism Cites in South-East Nigeria AU - Nwatu Basil Chibuike AU - Nwaizugbo Ireneus Chukwudi AU - Ganiyu Rahim Ajao Y1 - 2021/10/12 PY - 2021 N1 - https://doi.org/10.11648/j.ijecs.20210605.13 DO - 10.11648/j.ijecs.20210605.13 T2 - International Journal of Education, Culture and Society JF - International Journal of Education, Culture and Society JO - International Journal of Education, Culture and Society SP - 176 EP - 189 PB - Science Publishing Group SN - 2575-3363 UR - https://doi.org/10.11648/j.ijecs.20210605.13 AB - Tourism has expanded dramatically in Nigeria over the last six decades, becoming one of the largest and fastest-growing sectors of the Nigerian like in the global economy. The World Travel and Tourism index ranked Nigeria 129th out of 140 countries and Nigeria’s ranking is well below average rankings for sub-Saharan Africa. This study was motivated by the need to explore the antecedents of tourists’ behavioural intentions from the perspectives of the expectations confirmation model. The study extended the model by adding perceived trust to original components. Several studies have been conducted from the perspective of this model in tourism in many countries but none in Nigeria. The study was based on a sample 400 tourists selected from the five states in the South East geopolitical zone of Nigeria out of which 317 respondents returned valid questionnaire. The study population was infinite hence respondents were those seen at the various tourist sites and who agreed to fill the questionnaire. The analysis utilized partial least squares structural equations modelling (PLS-SEM) with the aid of WarpPLS version 7.0. All the hypothesised relationships are statistically significant (Table 6). The 95% confidence intervals straddle no zero in-between for all the hypotheses. The Effect sizes in our analysis range from as high as 0.409 for Confirmation which is the highest to 0.209 for PP and 0.149 for CE. Conf. and PT have 0.094 and 0.084 respectively hence all the IVs in our analysis fall within acceptable range from medium to high effect sizes and are all considered relevant in our model. Implications of the study were also discussed and recommendations for further study were also made. VL - 6 IS - 5 ER -
Email: