A Study on the Effects of Sales Promotion on Consumer Involvement and Purchase Intention in Tourism Industry
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Department of Tourism and Hospitality, Taipei City University of Science and Technology, TAIWAN
Online publish date: 2017-11-25
Publish date: 2017-11-25
EURASIA J. Math., Sci Tech. Ed 2017;13(12):8323–8330
This article belongs to the special issue "Problems of Application Analysis in Knowledge Management and Science-Mathematics-Education".
Sales Promotion has been the routine marketing of businesses appealing consumers to making orders and increasing media exposure in recent years. Sales Promotion is a tactic for the sales of goods with price or non-price discounts. There are various sales promotions in the market, but not all of them are effective in marketing, as brand image, perceived value, and purchase intention are also associated. Sales Promotion therefore has become a primary issue for marketing. Aiming at 2014 Kaohsiung International Travel Fair, 1000 copies of questionnaires are distributed to the customers, and 421 valid copies are retrieved, with the retrieval rate 42%. The research results present the significant correlations between 1. Sales Promotion and Consumer Involvement, 2. Consumer Involvement and Purchase Intention, and 3. Sales Promotion and Purchase Intention.
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structure equations models. Journal of Academy of Marking Science, 16(1), 74-94.
Barry, M. P. (2010). Why Enforcing its UNCAC Commitments Would be Good for Russia: A Computable General Equilibrium Model. Eurasia Journal of Business and Economics. Retrieved from http://ejbe. org/EJBE2010Vol03No05p93BARRY.pdf.
Berjani, B., & Strufe, T. (2011). A recommendation system for spots in location-based online social networks. Proceedings of the 4th Workshop on Social Network Systems, Salzburg, Austria.
Bhanot, S. (2012). Use of social media by companies to reach their customers. SIES Journal of Management, 8(1), 47-55.
Bobadilla, J., Serradilla, F., & MovieLens, A. H. (2009). Collaborative filtering adapted to recommender systems of e-learning. Knowledge-Based Systems, 22, 261-265.
Chang, H. C., & Tsai, H. P. (2011). Group RFM analysis as a novel framework to discover better customer consumption behavior. Expert Systems with Applications, 38, 14499-14513.
Chihani, B., Bertin, E., Jeanne, F., & Crespi, N. (2011). Context-aware systems: A case study. Paper Presented in The International Conference on Digital Information and Communication Technology and Its Application, Dijon, France, 1-15.
Cuieford, J. P. (1965). Fundamental Statistics in Psychology and Education, 4th Ed. NY: McGraw, Hill.
Defever, C., Pandelaere, M., & Roe, K. (2011). Inducing value-congruent behavior through advertising and the moderating role of attitudes toward advertising. Journal of Advertising, 40(2), 25-37.
Dehkordi, G. J., Rezvani, S., Rahman, M. S., Fouladivanda, F., Nahid, N., & Jouya, S. F. (2012). A conceptual study on e-marketing and its operation on firm’s promotion and understanding customer’s response. International Journal of Business and Management, 7(9), 114-124.
Delfos, J., Tan, T., & Veebebdaal, B. (2010). Design of a web-based LBS framework addressing usability, cost, and implementation constrains. World Wide Web Internet and Web Information Systems, 391-418.
Dhar, S., & Varshney, U. (2011). Challenges and business models for mobile location-based services and advertising. Communication of the ACM, 54(5), 121-129.
Huang, H., & Gartner, G. (2012). Using Context-aware Collaborative Filtering for POI Recommendation in Mobile Guides. In Advances in Location Based Services. Lecture Notes in Geoinformation and Cartography. Berlin: Springer Berlin, Heidelberg, 131-146.
Kao, D. T. (2011). Message sidedness in advertising: The moderating roles of need for cognition and time pressure in persuasion. Scandinavian Journal of Psychology, 52, 329-340.
Karatzoglou, A., Baltrunas, L., & Bohmer, M. (2011). Collaborative context-aware preference learning. NIPS Workshop, Sierra Nevada, Spain.
Kerlinger, F. N. (1986). Foundations of Behavioral Research, 3rd ed. FL: Harcourt Brace Jovanovich.
Khajvand, M., & Tarokh, M. J. (2011). Estimating customer future value of different customer segment based on adapted RFM model in retail banking context. Procedia Computer Science, 3(1), 1327-1332.
Kotler, P., Kartajaya, H., & Setiawan, I. (2010). Marketing 3.0: From Products to Customers to the Human Spirit, 1st Edition. New York: John Wiley & Sons.
Lee, J. S., & Olafsson, S. (2009). Two-way cooperative prediction for collaborative filtering recommendations. Expert Systems with Applications, 36(3), 5353-5361.
Li, D. C., Dai, W. L., & Tseng, W. T. (2011). A two-stage clustering method to analyze customer characteristics to build discriminative customer management: A case of textile manufacturing business. Expert Systems with Applications, 38(1), 7186-7191.
Li, L., & Du, T. C. (2012). Building a targeted mobile advertising system for location-based services. Decision Support Systems, 54(1), 1-8.
Lin, J., Li, X., Yang, Y., Liu, L., Guo, W., Li, X., & Li, L. (2011). A Context-Aware Recommender System for M-Commerce Applications. Berlin: Springer-Verlag Berlin Heidelberg, 217-228.
Mesforoush, A., & Tarokh M. J. (2013). Customer profitability segmentation for smes case study: network equipment company. International Journal of Research in Industrial Engineering, 2(1), 30-44.
Mettas, A. (2011). The development of decision-making skills. Eurasia Journal of Mathematics, Science and Technology Education, 7(11), 63-73.
Molitor, D., Reichhart, P., & Spann, M. (2012). Location-based advertising: what is the value of physical distance on the mobile internet? Institute of Electronic Commerce and Digital Markets, 1-14.
Ochi, P., Rao, S., Takayama, L., & Nass, C. (2010). Predictors of user perceptions of web recommender systems: How the basis for generating experience and search product recommendations affects user responses. International Journal of Human-Computer Studies, 68(8), 472-482.
Pinheiro, M. K., Carrillo-Ramos, A., Villanova-Oliver, M., Gensel, J., & Berbers, Y. (2010). Context-aware adaptation in web-based groupware systems. Web-Based Support Systems, Advanced Information and Knowledge Processing, 1, 3-32.
Shrivastava, V., Boghey, R., & Verma, B. (2011). A framework for improving target marketing using collaborative data mining approach. International Journal of Information and Communication Technology Research, 1(2), 69-72.
Stever, G. (2011). Celebrity worship: Critiquing a construct. Journal of Applied Social Psychology, 41(5), 27-35.
Sun, T. (2010). Antecedents and consequences of parasocial interaction with sport athletes and identification with sport teams. Journal of Sport Behavior, 33, 194-217.
Theran, S. A., Newberg, E. M., & Gleason, T. R. (2010). Adolescent girls’ parasocial interactions with media figures. The Journal of Genetic Psychology, 171(3), 270– 277.
Yim, M. Y. C., Cicchirillo, V. J., & Drumwright, M. E. (2012). The impact of stereoscopic three-dimensional (3-D) advertising: The role of presence in enhancing advertising effectiveness. Journal of Advertising, 41(2), 113-128.
Zhou, D., Wang, B., Rahimi, S. M., & Wang, X. (2012). A study of recommending locations on location-based social network by collaborative filtering. Advances in Artificial Intelligence Lecture Notes in Computer Science, 7310, 255-266.