ABSTRACT

The purpose of this paper is to propose an approach to the international market segmentation, which provides a comprehensive analysis on how social media platforms affect airline passenger’s adoption of Full Service Carriers (FSC) and Low Cost Carriers (LCC). Based on the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2), the variables that are investigated are Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Hedonic Motivation, Price-Saving Orientation, and Habit (Independent Variables). The seven independent variables that were applied in this research were used to see their relationship to Behavioral Intention (Dependent Variable) between Full Service Carriers passengers and Low Cost Carrier passengers to identify whether there are differences amongst the two groups.

The data were analyzed to illustrate whether the independent variables influences the dependent variable that allows the comparison between the two differing carriers. The results illustrates that there are significant differences for Performance Expectancy, Effort Expectancy, Hedonic Motivation, Price-Saving Orientation, and Habit towards Behavioral Intention between Full Service Carrier passengers and Low Cost Carrier passengers. However, Social Influence and Facilitating Conditions does not have significant differences towards Behavioral Intention between Full Service Carrier passengers and Low Cost Carrier passengers. According to the results, the imposed marketing strategies for the two carriers have various differences in order to stay competitive in their own way, in the same market segment, which caters to new or existing customers for the benefit of the carrier.

CONTENTS

ABSTRACT iii
ACKNOWLEDGEMENTS iv
CONTENTS v
LIST OF TABLES ix
LIST OF FIGURES xii
LIST OF FORMULAS xiii
CHAPTER ONE: INTRODUCTION 1
1.1 Research Background and Motivation 1
1.2 Research Questions 3
1.3 Research Objectives and Contributions 4
1.4 Research Procedure 4
1.4.1 Academic Contributions 4
1.4.2 Practical Contributions 5
1.5 Research Procedure 5
1.6 Research Structure 6
CHAPTER TWO: LITERATURE REVIEW 8
2.1 Differences Between Full Service Carriers and Low Cost Carrier 8
2.2 Dimensional Differentiation 10
2.3 Operating Component Costs 12 2.4 Social Media 14
2.5 UTAUT2 17
Performance Expectancy 18
Effort Expectancy 18
Social Influence 18
Facilitating Conditions 19
Hedonic Motivation 19
Price-Saving Orientation 19 Habit 20
Behavioral Intention 20
CHAPTER THREE: RESEARCH DESIGN AND METHODOLOGY 22
3.1 The Conceptual Framework 22
3.2 Hypotheses Development 24
3.3 Research Design 24
3.4 Sampling Plan 25
3.5 Main Study 25
3.6 Construct Measurement 26
3.6.1 Measurement of Independent Variables 26
Performance Expectancy 26
Effort Expectancy 27
Social Influence 28
Facilitating Conditions 29
Hedonic Motivation 29
Price-Saving Orientation 30
Habit 30
3.6.2 Measurement of Dependent Variable 31
Behavioral Intention 31
3.7 Demographic Profile of Respondents 32
3.8 Data Analysis Procedure 33
3.8.1 Descriptive Statistic Analysis 33
3.8.2 Factor Analysis 33
3.8.3 Item-to-Total Correlation 34
3.8.4 Internal Consistency Analysis 34
3.8.5 Confirmatory Factor Analysis 34
3.8.6 Multiple Regression Analysis 34
3.8.7 z-Statistics for the Difference between Two Regression Coefficients 34
CHAPTER FOUR: RESEARCH ANALYSIS AND RESULTS 36
4.1 Descriptive Analysis 36
4.1.1 Data Collection 36
4.1.2 Characteristics of Respondents 36
4.1.3 Measurement results of Relevant Variables 40
4.2 Factor Analysis and Reliability Tests 45
4.2.1 Performance Expectancy for Full Service Carrier Passengers 47
4.2.2 Effort Expectancy for Full Service Carrier Passengers 47
4.2.3 Social Influence for Full Service Carrier Passengers 49
4.2.4 Facilitating Conditions for Full Service Carrier Passengers 49
4.2.5 Hedonic Motivation for Full Service Carrier Passengers 51
4.2.6 Price-Saving Orientation for Full Service Carrier Passengers 51
4.2.7 Habit for Full Service Carrier Passengers 53
4.2.8 Behavioral Intention for Full Service Carrier Passengers 53
4.2.9 Performance Expectancy for Low Cost Carrier Passengers 55
4.2.10 Effort Expectancy for Low Cost Carrier Passengers 55
4.2.11 Social Influence for Low Cost Carrier Passengers 57
4.2.12 Facilitating Conditions for Low Cost Carrier Passengers 57
4.2.13 Hedonic Motivation for Low Cost Carrier Passengers 59
4.2.14 Price-Saving Orientation for Low Cost Carrier Passengers 59
4.2.15 Habit for Low Cost Carrier Passengers 61
4.2.16 Behavioral Intention for Full Service Carrier Passengers 61
4.3 Confirmatory Factor Analysis 61 4.3.1 Confirmatory Factor Analysis for Full Service Carrier Passengers 61
4.3.2 Confirmatory Factor Analysis for Low Cost Carrier
Passengers 65
4.4 Multiple Regression 69
4.4.1 The Effect of Performance Expectancy on Behavioral Intention of Full Service Carrier Passengers and Low Cost Carrier Passengers 69
4.4.2 The Effect of Effort Expectancy on Behavioral Intention of Full Service Carrier Passengers and Low Cost Carrier Passengers 70
4.4.3 The Effect of Social Influence on Behavioral Intention of Full Service Carrier Passengers and Low Cost Carrier Passengers 71
4.4.4 The Effect of Facilitating Conditions on Behavioral Intention of Full Service Carrier Passengers and Low Cost Carrier Passengers 72
4.4.5 The Effect of Hedonic Motivation on Behavioral Intention of Full Service Carrier Passengers and Low Cost Carrier Passengers 73
4.4.6 The Effect of Price-Saving Orientation on Behavioral Intention of Full Service Carrier Passengers and Low Cost Carrier Passengers 74
4.4.7 The Effect of Habit on Behavioral Intention of Full Service Carrier Passengers and Low Cost Carrier Passengers 75
4.4.8 The Summary of the Effect of Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Hedonic Motivation, Price-Saving Orientation and Habit on Behavioral Intention of Full Service Carrier Passengers and Low Cost Carrier Passengers 76
CHAPTER FIVE: CONCLUSIONS AND DISCUSSIONS 79
5.1 Research Conclusions 79
5.2 Suggestions and Implications 81
5.2.1 Implications for Academic Researchers 81
5.2.2 Practical Implications 81
5.3 Research Limitations and Future Research Directions 81
REFERENCES 83
APPENDICES 89
Appendix 1: English Questionnaire 89
Appendix 2: Chinese Questionnaire 95

LIST OF TABLES

Table 3-1 Measurement Items for Performance Expectancy 27
Table 3-2 Measurement Items for Effort Expectancy 28
Table 3-3 Measurement Items for Social Influence 28
Table 3-4 Measurement Items for Facilitating Conditions 29
Table 3-5 Measurement Items for Hedonic Motivation 30
Table 3-6 Measurement Items for Price-Saving Orientation 30
Table 3-7 Measurement Items for Habit 31
Table 3-8 Measurement Items for Behavioral Intention 32
Table 3-9 Measurement Items for Demographic Profile 33
Table 4-1 Characteristics of Respondents: Full Service Carriers (n=325) 37
Table 4-2 Characteristics of Respondents: Low Cost Carriers (n=325) 39
Table 4-3 Descriptive Analyses for Full Service Carriers 41
Table 4-4 Descriptive Analyses for Low Cost Carriers 43
Table 4-5 Results of Factor Analysis and Reliability Test on Performance
Expectancy for Full Service Carriers 46
Table 4-6 Results of Factor Analysis and Reliability Test on Effort Expectancy for Full Service Carriers 46
Table 4-7 Results of Factor Analysis and Reliability Test on Social Influence for Full Service Carriers 48
Table 4-8 Results of Factor Analysis and Reliability Test on Facilitating Conditions for Full Service Carriers 48
Table 4-9 Results of Factor Analysis and Reliability Test on Hedonic Motivation for Full Service Carriers 50
Table 4-10 Results of Factor Analysis and Reliability Test on Price-Saving Orientation for Full Service Carriers 50
Table 4-11 Results of Factor Analysis and Reliability Test on Habit for Full Service Carriers 52
Table 4-12 Results of Factor Analysis and Reliability Test on Behavioral Intention for Full Service Carriers 52
Table 4-13 Results of Factor Analysis and Reliability Test on Performance Expectancy for Low Cost Carriers 54
Table 4-14 Results of Factor Analysis and Reliability Test on Effort Expectancy for Low Cost Carriers 54
Table 4-15 Results of Factor Analysis and Reliability Test on Social Influence for Low Service Carriers 56
Table 4-16 Results of Factor Analysis and Reliability Test on Facilitating Conditions for Low Cost Carriers 56
Table 4-17 Results of Factor Analysis and Reliability Test on Hedonic Motivation for Low Cost Carriers 58
Table 4-18 Results of Factor Analysis and Reliability Test on Price-Saving Orientation for Low Cost Carriers 58
Table 4-19 Results of Factor Analysis and Reliability Test on Habit for Low Cost Carriers 60
Table 4-20 Results of Factor Analysis and Reliability Test on Behavioral Intention for Low Cost Carriers 60
Table 4-21 Results of Confirmatory Factor Analysis for Full Service Carriers 62
Table 4-22 Results of Confirmatory Factor Analysis for Low Cost Carriers 66
Table 4-23 Regression Coefficient Estimates of the Effect of Performance Expectancy on Behavioral Intention of Full Service Carriers and Low Cost Carriers 69
Table 4-24 Regression Coefficient Estimates of the Effect of Effort Expectancy on Behavioral Intention of Full Service Carriers and Low Cost Carriers 70
Table 4-25 Regression Coefficient Estimates of the effect of Social Influence on Behavioral Intention of Full Service Carriers and Low Cost Carriers 71
Table 4-26 Regression Coefficient Estimates of the Effect of Facilitating Conditions on Behavioral Intention of Full Service Carriers and Low Cost Carriers 72
Table 4-27 Regression Coefficient Estimates of the Effect of Hedonic Motivation on Behavioral Intention of Full Service Carriers and Low Cost Carriers 73
Table 4-28 Regression Coefficient Estimates of the Effect of Price-Saving Orientation on Behavioral Intention of Full Service Carriers and Low Cost Carriers 74
Table 4-29 Regression Coefficient Estimates of the Effect of Habit on Behavioral Intention of Full Service Carriers and Low Cost Carriers 75
Table 4-30 Summary for Seven Regression Coefficient Estimates of the Effect of Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Hedonic Motivation, Price-Saving Orientation and Habit on Behavioral Intention of Full Service Carriers and Low Cost Carriers 77
Table 5-1 Hypotheses and Results of Empirical Tests 79

LIST OF FIGURES

Figure 1.1 Flow Chart of Research Procedures 6
Figure 2.1 Differences Between Full Service Carriers and Low Cost Carriers 9
Figure 2.2 Carrier Characteristics 10
Figure 2.3 The Potential Dimensions of Managerial Differentiation 11
Figure 2.4 Full Service Carriers Operating Component Costs 13
Figure 2.5 Low Cost Carriers Operating Component Cost 14
Figure 2.6 Models and Theories Integrated in the UTAUT 17
Figure 3.1 Conceptual Framework 23
Figure 4.1 Result of Confirmatory Factor Analysis for Full Service Carriers 64
Figure 4.2 Result of Confirmatory Factor Analysis for Low Cost Carriers 68

REFERENCES

Ajzen, I. (1991). The theory of planned behaviour. Organizational Behavior and Human Decision Processes, 50, 179-211.

Ajzen, I. (2001). Nature and operation of attitudes. Annual Review of Psychology, 52(1), 27-58.

Alba, J., Lynch, J., Weitz, B., Janiszewski, C., Lutz, R., Sawyer, A., & Wood, S. (1997). Interactive home shopping: consumer, retailer, and manufacturer incentives to participate in electronic marketplaces. Journal of Marketing 6, 38–53.

Arsal, I., Backman, S., & Baldwin, E. (2008). Influence of an online travel community on travel decisions. In P. O’Connor, W. Hopken, & U. Gretzel (Eds.), Information and communication technologies in tourism 2008 (pp. 82–93). Vienna, Austria: Springer.

Ayeh, J. K., Au, N., & Law, R. (2013). Predicting the intention to use consumer- generated media for travel planning. Tourism Management, 35(April), 132– 143.

Barrett, P. (2007). Structural equation modelling: Adjudging model fit. Personality and Individual differences, 42(5), 815-824.

Berrittella, M., La Franca, L., & Zito, P. (2009). An analytic hierarchy process for ranking operating costs of low cost and full service airlines. Journal of Air Transport Management, 15(5), 249-255.

Brown, S. A., & Venkatesh, V. (2005). A model of adoption of technology in the household: A baseline model test and extension incorporating household life cycle. Management Information Systems Quarterly, 29(3), 4.

Buhalis, D. (1998). Strategic use of information technologies in the tourism industry. Tourism Management, 19(5), 409–421.

Byrne, B. (1998). Structural Equation Modeling with LISREL, PRELIS, and SIMPLIS.

Chung, J. Y., & Buhalis, D. (2008a). Information needs in online social networks. Information Technology & Tourism, 10, 267–281.

Chung, J. Y., & Buhalis, D. (2008b). Web 2.0: A study of online travel community. In P. O’Connor, W. Hopken, & U. Gretzel (Eds.), Information and communication technologies in tourism 2008 (pp. 70–81). Vienna, Austria: Springer.

Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: development of a measure and initial test. MIS Quarterly, 19(2), 189-211.

Compete Incorporated (2007). Consumer generated content: learning form the innovators. Compete Incorporated. Retrieved August 7, 2012, from <http://www.competeinc.com/research/newsletters/traveltsrends_conumer_g enerated_travel_content/>.

Dabholkar P. A., & Bagozzi R. P. (2002). An attitudinal model of technology-based self-service: moderating effects of consumer traits and situational factors. Journal of the Academy of Market Science, 30(3), 184–201.

Daft, R. L., & Lengel, R. H. (1986). Organizational information requirements, media richness, and structural design. Management Science, 32(5), 554—571.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13(3), 319-339.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982-1003.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111-1132.

Diamantopoulos, A., Siguaw, J. A., & Siguaw, J. A. (2000). Introducing LISREL: A guide for the uninitiated. Sage.

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.

Fodness, D., & Murray, B. (1997). Tourist information search. Annals of Tourism Research, 24(3), 503–523.

Fotis, J., Buhalis, D., & Rossides, N. (2012). Social media use and impact during the holiday travel planning process. In M. Fuchs, F. Ricci, & L. Cantoni (Eds.), Information and communication technologies in tourism 2012 (pp. 13–24). Vienna, Austria: Springer-Verlag.

Gelman, A., & Pardoe, I. (2006). Bayesian measures of explained variance and pooling in multilevel (hierarchical) models. Technometrics, 48(2), 241-251.

Gillen, D., & Morrison, W. (2003). Bundling, integration and the delivered price of air travel: are low cost carriers full service competitors?. Journal of Air Transport Management, 9(1), 15-23.

Goffman, E. (1959). The presentation of self in everyday life. New York: Doubleday Anchor Books.

Gretzel, U., & Yoo, K. H. (2008). Use and impact of online travel reviews. In P. O’Connor, W. Hopken, & U. Gretzel (Eds.), Information and communication technologies in tourism 2008 (pp. 35–46). Vienna, Austria: Springer.

Huang, C.-Y., Chou, C.-J., & Lin, P.-C. (2010). Involvement theory in constructing bloggers’ intention to purchase travel products. Tourism Management, 31(4), 513–526.

Jarach, D., Zerbini, F., & Miniero, G. (2009). When legacy carriers converge with low-cost carriers: Exploring the fusion of European airline business models through a case-based analysis. Journal of Air Transport Management, 15(6), 287-293.

Jensen, J. M. (2012). Shopping orientation and online travel shopping: the role of travel experience. International Journal of Tourism Research, 14(1), 56-70.
Johnson, E. J., & Payne, J. W. (1985). Effort and accuracy in choice. Management Science, 31(4), 395–414.

Jones, M. A., Mothersbaugh, D. L., & Beatty, S. E. (2000). Switching barrier and repurchase intentions in services. Journal of Retailing, 76(2), 259–274.

Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of Social Media. Business horizons, 53(1), 59-68.

Kang, M., & Schuett, M. A. (2013). Determinants of sharing travel experiences in social media. Journal of Travel & Tourism Marketing, 30(1–2), 93–107.

Kim, M. K., Park, M. C., & Jeong, D. H. (2004). The effects of customer satisfaction and switching barrier on customer loyalty in Korean mobile telecommunication services. Telecommunications Policy, 28(2), 145–159.

Kim, S. S., & Malhotra, N. K. (2005). A longitudinal model of continued IS use: An integrative view of four mechanisms underlying postadoption phenomena. Management science, 51(5), 741-755.

Kim, D.-Y., Lehto, X. Y., & Morrison, A. M. (2007). Gender differences in online travel information search: Implications for marketing communications on the internet. Tourism Management, 28(2), 423–433.

Kim, H. W., & Kankanhalli, A. (2009). Investigating user resistance to information systems implementation: a status Quo bias perspective. MIS Quarterly, 33(3), 556–582.

Kim, L. H., Qu, H., & Kim, D. J. (2009). A study of perceived risk and risk reduction of purchasing air-tickets online. Journal of Travel & Tourism Marketing, 26(3), 203–224.

Limayem, M., Hirt, S. G., & Cheung, C. M. (2007). How habit limits the predictive power of intention: The case of information systems continuance. Mis Quarterly, 705-737.

Mediabistro (2012). Social media’s influence on the travel industry. Retrieved November 3rd, 2014, from <http://www.mediabistro.com/alltwitter/online- travel-industry_b25865>.

Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192-222.

McCracken, P. W. (1980). The uncertain 1980’s. Economic Outlook USA 7, 101–111.

Natarajan, T., Balasubramanian, S. A., & Manickavasagam, S. (2010). Customer’s choice amongst self service technology (SST) channels in retail banking: a study using analytical hierarchy process (AHP). Journal Internet Banking and Commerce, 15(2), 1–16.

O’Connell, J. F., & Williams, G. (2005). Passengers’ perceptions of low cost airlines and full service carriers: A case study involving Ryanair, Aer Lingus, Air Asia and Malaysia Airlines. Journal of Air Transport Management, 11(4), 259-272.

OECD. (2007). Participative web and user-created content: Web 2.0, wikis, and social networking. Paris: Organisation for Economic Co-operation and Development.

Paternoster, R., Brame, R., Mazerolle, P., & Piquero, A. (1998). Using the correct statistical test for the equality of regression coefficients. Criminology, 36(4), 859-866.

Ray, G., Muhanna, W. A., & Barney, J. B. (2005). Information technology and the performance of the customer service process: a resource-based analysis. MIS Quarterly, 29(4), 625–652.

Reibstein, D. J. (2002). What attracts customers to online stores, and what keeps them coming back? Journal of the Academy of Marketing Science 30(4), 465–473.

Rust, R. T., Kannan, P. K. (2003) E-service: a new paradigm for business in the electronic environment. Communications ACM, 46(6), 36–42.

San Martín, H., & Herrero, Á. (2012). Influence of the user’s psychological factors on the online purchase intention in rural tourism: Integrating innovativeness to the UTAUT framework. Tourism Management, 33(2), 341-350.

Schau, H. J., & Gilly, M. C. (2003). We are what we post? Self- presentation in personal web space. Journal of Consumer Research, 30(3), 385-404.

Schifter, D. B., & Ajzen, I. (1985). Intention, perceived control, and weight loss: an application of the theory of planned behaviour. Journal of Personality and Social Psychology, 49, 842-851.

Sharma N., & Patterson P. G. (2000). Switching costs, alternative attractiveness and experience as moderators of relationship commitment in professional consumer services. International Journal of Service Industries Management, 11(5), 470–490.

Sheeran, P., Trafimow, D., & Armitage, C. J. (2003). Predicting Behaviour from Perceived Behavioural Control: Tests of the Accuracy Assumption of the Theory of Planned Behaviour. British Journal of Social Psychology. 42(3), 393-410.

Shevlin, M., & Miles, J. N. (1998). Effects of sample size, model specification and factor loadings on the GFI in confirmatory factor analysis. Personality and Individual Differences, 25(1), 85-90.

Short, J., Williams, E., & Christie, B. (1976). The social psychology of telecommunications. Hoboken, NJ: John Wiley & Sons, Ltd.

Tabachnick, B. G., & Fidell, L. S. (2007). Using Multivariate Statistics., 5th Edition.(Pearson: Boston, MA.).

Taylor, S., & Todd, P. A. (1995). Decomposition and crossover effects in the theory of planned behavior: a study of consumer adoption intentions. International Journal of Research Marketing 12, 137–155.

Thompson, R., Higgins, C., & Howell, J. (1991). Personal computing: toward a conceptual model of utilization. MIS Quarterly, 15(1), 125-143.

Tripadvisor (2014). TripBarometer April 2014: Global edition. Retrieved November 3rd, 2014, from <http://www.tripadvisor.com/TripAdvisorInsights/n2200/tripbarometer-april- 2014-global-edition>.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27, 425- 478.

Venkatesh, V., Davis, F. D., & Morris, M. G. (2007). Dead or alive? The development, trajectory and future of technology adoption research. Journal of the association for information systems, 8(4), 267-286.

Venkatesh, V., Thong, J., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178.

Wang, Y., & Fesenmaier, D. R. (2004). Modeling participation in an online travel community. Journal of Travel Research, 42(3), 261–270.

Werthner, H., & Klein, S. (1999). Information technology and tourism – A challenging relationship. Vienna/New York: Springer.

Werthner, H., & Ricci, F. (2004). E-commerce and tourism. Communications of the ACM, 47(12), 101–105.

Wheaton, B., Muthen, B., Alwin, D. F., & Summers, G. F. (1977). Assessing reliability and stability in panel models. Sociological methodology, 8(1), 84- 136.

Wiedemann, A. U., Schüz, B., Sniehotta, F. F., Scholz, U., & Schwarzer, R. (2009). Disentangling the relation between intentions, planning, and behaviour: A moderated mediation analysis. Psychology and Health, 24, 67-79.

Wen, I. (2012). An empirical study of an online travel purchase. Journal of Travel & Tourism Marketing, 29(1), 18-39.

Wu, J. H., Chen, Y. C., & Lin, L. M. (2007). Empirical evaluation of the revised end user computing acceptance model. Computers in Human Behavior, 23(1), 162–174.

Xue, L., Ray, G., & Sambamurthy, V. (2012). Efficiency or innovation: How do industry environments moderate the effects of firms’ IT asset portfolios? MIS Quarterly, 36(2), 509–528.

Yoo, K.-H., & Gretzel, U. (2011). Influence of personality on travel-related consumer-generated media creation. Computers in Human Behavior, 27(2), 609–621.

Zhou, T., Lu, Y., & Wang, B. (2010). Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior, 26(4), 760- 767.