Çevrimiçi Seyahat Planlamalarının AHP ve TOPSIS Yöntemleri ile Belirlenmesi

Abstract

Online alışveriş günümüzde oldukça popüler hale gelmiştir. Tüm dünyada sıklıkla kullanılan bu işlemler turizm sektöründe de oldukça yaygındır. Kullanıcılar seyahat planlamalarını gerçekleştirmek adına web siteleri, sosyal medya veya öneri sistemleri gibi alternatif platformları kullanabilmektedirler. Bu bağlamda seyahat işlemleri birçok uygulama ve platform üzerinden yapılabilmektedir. Bu yüzden hızlı işlem yapıp doğru kararlar verebilme adına kullanılacak olan platform önem kazanmaktadır. Buna göre seyahat planlaması yapacak olan kullanıcının birçok alternatif içerisinden en uygun olanı seçmesi bazen zor bir süreç olabilmektedir. Bu çalışmada online olarak seyahat işlemlerini yapabilmek adına hangi kriterlerin önemli olduğu araştırılmıştır. Bununla beraber kullanıcıların belirlenmiş kriterler doğrultusunda hangi platformları tercih edebileceği de araştırılmıştır. Böylelikle kişilerin seçeceği alternatifler içerisinden doğru sıralamanın hangisi olduğu ortaya konulmuştur. Çalışmada çok kriterli karar verme yöntemlerinden AHP ve TOPSIS yöntemleri tercih edilmiştir. Çalışmada ana kriterler olarak içerik kalitesi, kullanışlılık, memnuniyet, etkileşim imkanı, erişilebilirlik ve web tasarımı kriterleri kullanılmıştır. Ayrıca ana kriterlerin alt kriterleri de değerlendirilmeye alınmıştır. Alternatif seçenekler ise web siteleri, bloglar, Instagram, Facebook, Twitter, Google Yorumlar olarak belirlenmiştir. Çalışma sonucunda online seyahat işlemlerinde içerik kalitesi özelliği en önemli kriter olmuştur. Belirlenmiş alternatifler içerisinden ilk sırayı web siteleri almıştır.

Keywords

• Seyahat Planlaması
• AHP
• TOPSIS
• Sosyal Medya

Determining Online Travel Planning with AHP and TOPSIS Methods

Abstract

Online shopping has become increasingly popular in recent years. Online shopping transactions, which are frequently carried out by consumers all over the world, are also very common in the tourism sector. Users avail themselves of a variety of alternative platforms such as websites, social media or recommendation systems in order to realize their travel plans. Travel transactions can be performed through many applications and platforms. Therefore, it is becoming increasingly important to make the right choice of platform in order to perform faster transactions and make the right decisions. Accordingly, it can sometimes be a difficult process for the user who intends to plan a journey choosing the most suitable online platform from among many alternatives. This study investigated which criteria are important in order to make online travel transactions. In addition, the study included research into which platforms the users can choose in accordance with the determined criteria. Thus, the correct order of the alternatives that people can choose is revealed. In the study, AHP and TOPSIS methods, which are multi-criteria decision-making methods, were preferred. Content quality, usefulness, satisfaction, interaction opportunity, accessibility and web design criteria were used as the main criteria. In addition, sub-criteria of the main criteria were also evaluated. Alternative options were determined such as websites, blogs, Instagram, Facebook, Twitter, Google Comments. The study concludes that the content quality feature is the most important criterion in online travel transactions. Of all the online platforms, websites took the first place among the determined alternatives.

Keywords

• Travel Planning
• AHP
• TOPSIS
• Social Media

References

1. Ahani, A., Nilashi, M., Yadegaridehkordi, E., Sanzogni, L., Tarik, A. R., Knox, K., ... & Ibrahim, O. (2019). Revealing customers’ satisfaction and preferences through online review analysis: The case of Canary Islands hotels. Journal of Retailing and Consumer Services, 51, 331-343. google scholar
2. Al-Harbi, K. M. A. S. (2001). Application of the AHP in project management. International journal of project management, 19(1), 19-27. google scholar
3. Akgün, İ., & Erdal, H. (2019). Solving an ammunition distribution network design problem using multi-objective mathematical modeling, combined AHP-TOPSIS, and GIS. Computers & Industrial Engineering, 129, 512-528. google scholar
4. Alptekin, G. I., & Büyüközkan, G. (2011). An integrated case-based reasoning and MCDM system for Web based tourism destination planning. Expert Systems with Applications, 38(3), 2125-2132. google scholar
5. Alshibly, H. H. (2014). Evaluating E-HRM success: A validation of the information systems success model. International Journal of Human Resource Studies, 4(3), 107-124. google scholar
6. Arora, M., & Gupta, A. (2017). E-Governance Parameters Assessment: An AHP Approach. Indian Journal of Computer Science, 2(1), 16-22. google scholar
7. Aurum, A., & Wohlin, C. (2003). The fundamental nature of requirements engineering activities as a decision-making process. Information and Software Technology, 45(14), 945-954. google scholar
8. Badri, M. A. (1999). Combining the analytic hierarchy process and goal programming for global facility location-allocation problem. International journal of production economics, 62(3), 237-248. google scholar

9. Baki, R. (2020). Evaluating hotel websites through the use of fuzzy AHP and fuzzy TOPSIS. International Journal of Contemporary Hospitality Management. google scholar
10. Balouchi, M., & Khanmohammadi, E. (2015). Using logarithmic fuzzy preference programming to prioritization social media utilization based on tourists’ perspective. Foundations of Management, 7(1), 7-18. google scholar
11. Bhole, G. P., & Deshmukh, T. (2018). Multi-criteria decision making (MCDM) methods and its applications. International Journal for Research in Applied Science & Engineering Technology (IJRASET), 6(5), 899-915. google scholar
12. Bire, R. B., Conterius, A. L., & Nasar, A. (2021, April). Tourist preference and destination competitiveness using the AHP-TOPSIS hybrid model. In International Conference on Applied Science and Technology on Social Science (ICAST-SS 2020) (pp. 43-48). Atlantis Press. google scholar
13. Bire, R. B., Nugraha, Y. E., & Welly, F. R. A. (2021). A fuzzy-analytic hierarchy process of tourism supply chain performance: customer perspectives. Enlightening Tourism. A Pathmaking Journal, 11(2), 531-557. google scholar
14. Chaudhari, K., & Thakkar, A. (2020). A comprehensive survey on travel recommender systems. Archives of Computational Methods in Engineering, 27(5), 1545-1571. google scholar
15. Chen, C. W. D., & Cheng, C. Y. J. (2009). Understanding consumer intention in online shopping: a respecification and validation of the DeLone and McLean model. Behaviour & Information Technology, 28(4), 335-345. google scholar
16. Chen, T., & Wang, Y. C. (2021). A calibrated piecewise-linear FGM approach for travel destination recommendation during the COVID-19 pandemic. Applied Soft Computing, 109, 107535. google scholar
17. Cheng, Y. M. (2012). Effects of quality antecedents on e-learning acceptance. Internet Research. google scholar
18. Cheng, Y. M. (2014). Why do users intend to continue using the digital library? An integrated perspective. Aslib Journal of Information Management. google scholar
19. Choedon, T., & Lee, Y. C. (2018). Classification and evaluation of service requirements in mobile tourism application using Kano model and AHP. The Journal of Information Systems, 27(1), 43-65. google scholar
20. Choi, M., Law, R., & Heo, C. Y. (2018). An investigation of the perceived value of shopping tourism. Journal of travel Research, 57(7), 962-980. google scholar
21. Chowdhury, P., & Paul, S. K. (2020). Applications of MCDM methods in research on corporate sustainability: A systematic literature review. Management of Environmental Quality: An International Journal. google scholar
22. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340. google scholar
23. DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information systems research, 3(1), 60-95. google scholar
24. DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of management information systems, 19(4), 9-30. google scholar
25. De Wulf, K., Schillewaert, N., Muylle, S., & Rangarajan, D. (2006). The role of pleasure in web site success. Information & Management, 43(4), 434-446. google scholar
26. Do, T. H. N., & Shih, W. (2016). Destination decision-making process based on a hybrid MCDM model combining DEMATEL and ANP: The Case of Vietnam as a Destination. Modern Economy, 7(09), 966. google scholar
27. Eren, A., & Kaya, M. D. (2019). İş Zekâsı Sistemlerinde Karar Verme Başarısının İncelenmesi. Business & Management Studies: An International Journal, 7(5), 2148-2176. google scholar
28. Ersöz, F., & Kabak, M. (2010). Savunma sanayi uygulamalarinda çok kriterli karar verme yöntemlerinin literatür araştirmasi. Savunma Bilimleri Dergisi, 9(1), 97-125. google scholar
29. Filip, F. G. (2014). A decision-making perspective for designing and building information systems. International Journal of Computers Communications & Control, 7(2), 264-272. google scholar
30. Franek, J., & Kresta, A. (2014). Judgment scales and consistency measure in AHP. Procedia Economics and Finance, 12, 164-173. google scholar
31. Gohil, N. (2015). Role and impact of social media in tourism: a case study on the initiatives of Madhya Pradesh State Tourism. International Journal of Research in Economics and Social Sciences, 5(4), 8-15. google scholar
32. GuestCentric (2021). Oteller için Sosyal Medya, 2021, Retrieved September 1, 2021, from https://blog.guestcentric.com/ social-media-for-hotels-is-it-worth-it/ google scholar
33. Gul, S., & Topcu, I. (2015). A multi-attribute decision support model for the selection of touristic activities. International Journal of the Analytic Hierarchy Process, 7(3). google scholar
34. Hänninen, M., Smedlund, A., & Mitronen, L. (2018). Digitalization in retailing: multi-sided platforms as drivers of industry transformation. Baltic Journal of Management, 13(2), 152-168. google scholar
35. Hussain, T., Li, B., & Wang, D. (2018). What factors influence the sustainable tour process in social media usage? Examining a rural mountain region in Pakistan. Sustainability, 10(7), 2220. google scholar
36. Hwang, C. L., & Yoon, K. (1981). Methods for multiple attribute decision making. In Multiple attribute decision making (pp. 58-191). Springer, Berlin, Heidelberg. google scholar
37. Ip, C., Law, R., & Lee, H. A. (2012). The evaluation of hotel website functionality by fuzzy analytic hierarchy process. Journal of Travel & Tourism Marketing, 29(3), 263-278. google scholar
38. Jiaoman, D., Lei, L., & Xiang, L. (2018, October). Travel planning problem considering site selection and itinerary making. In Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems (pp. 29-36). google scholar
39. Karaatli, M., Ömürbek, N., Budak, İ., & Okan, D. A. Ğ. (2015). Çok kriterli karar verme yöntemleri ile yaşanabilir illerin sıralanması. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (33), 215-228. google scholar
40. Kutbi, A., & Alomar, M. (2017). The Importance of Social Media in Education and Prioritizing Process. Journal of King Abdulaziz University, 28(2), 27-37. google scholar
41. Lee, Y. W., Strong, D. M., Kahn, B. K., & Wang, R. Y. (2002). AIMQ: a methodology for information quality assessment. Information & management, 40(2), 133-146. google scholar
42. Lin, C. C. (2021). Investigating complimentary e-marketing strategy for small-and medium-sized enterprises at growth stage in taiwan. Information, 12(9), 380. google scholar
43. Lin, H. F. (2010). An application of fuzzy AHP for evaluating course website quality. Computers & Education, 54(4), 877-888. google scholar
44. Lin, Y. H., & Chen, C. F. (2013). Passengers’ shopping motivations and commercial activities at airports-The moderating effects of time pressure and impulse buying tendency. Tourism Management, 36, 426-434. google scholar
45. Mamula-Nikolic, T., Percic, K., & Necak, M. (2022). Designing a sustainable brand by engaging brand-consumers’ collaboration Generation Z co-creators and influencers in Serbia. Marketing, 53(1), 37-50. google scholar
46. Mardiana, S., Tjakraatmadja, J. H., & Aprianingsih, A. (2015). DeLone-McLean information system success model revisited: The separation of intention to use-use and the integration of technology acceptance models. International Journal of Economics and Financial Issues, 5(1), 172-182. google scholar
47. Mariani, M. M., Mura, M., & Di Felice, M. (2018). The determinants of Facebook social engagement for national tourism organizations’ Facebook pages: A quantitative approach. Journal of Destination Marketing & Management, 8, 312-325. google scholar
48. Narangajavana, Y., Fiol, L. J. C., Tena, M. Â. M., Artola, R. M. R., & García, J. S. (2017). The influence of social media in creating expectations. An empirical study for a tourist destination. Annals of Tourism Research, 65, 60-70. google scholar
49. Nazarail, N. N., & Kasim, Z. (2021). The selection of social networking sites using fuzzy analytical hierarchy process. ESTEEM Academic Journal, 17, 1-11. google scholar
50. Olorunniwo, F., Hsu, M. K., & Udo, G. J. (2006). Service quality, customer satisfaction, and behavioral intentions in the service factory. Journal of services marketing, 20(1), 59-72. google scholar
51. Opricovic, S., & Tzeng, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European journal of operational research, 156(2), 445-455. google scholar
52. Park, S. Y., Nam, M. W., & Cha, S. B. (2012). University students’ behavioral intention to use mobile learning: Evaluating the technology acceptance model. British journal of educational te Prabantoro, G., & Hariyanto, J. (2019, February). Social Media Preference as a Media of Business Marketing Communication of SMEs in Rawamangun East Jakarta. In 5th Annual International Conference on Management Research (AICMaR 2018) (pp. 165-169). Atlantis Press.chnology, 43(4), 592-605. google scholar
53. Petter, S., DeLone, W., & McLean, E. (2008). Measuring information systems success: models, dimensions, measures, and interrelationships. European journal of information systems, 17, 236-263. google scholar
54. Pop, R. A., Sâplâcan, Z., Dabija, D. C., & Alt, M. A. (2021). The impact of social media influencers on travel decisions: The role of trust in consumer decision journey. Current Issues in Tourism, 1-21. google scholar
55. Putri, D. A., & Alawiah, E. T. (2021). Decision Support System To Choose The Best Social Media Platform For Product Marketing Using Topsis Method. IJISTECH (International Journal of Information System and Technology), 5(4), 394-399. google scholar
56. Rai, A., Lang, S. S., & Welker, R. B. (2002). Assessing the validity of IS success models: An empirical test and theoretical analysis. Information systems research, 13(1), 50-69. google scholar
57. Rathore, A. K., Joshi, U. C., & Ilavarasan, P. V. (2017). Social media usage for tourism: A case of Rajasthan tourism. Procedia computer science, 122, 751-758. google scholar
58. Saaty, T. L. (2008). Decision making with the analytic hierarchy process. Int. J. Services Sciences, 1(1), 83-98. google scholar
59. Saaty, T. L. (1990). How to make a decision: the analytic hierarchy process. European journal of operational research, 48(1), 9-26. google scholar
60. Saaty Thomas, L. (1980). The analytic Hierarchy process. New York: McGrow-Hill. google scholar
61. Sari, N. K. A. P. (2021). Implementation of the AHP-SAW method in the decision support system for selecting the best tourism village. Jurnal Teknik Informatika CIT Medicom, 13(1), 24-35. google scholar
62. Setiawan, B., Trisdyani, N. L. P., Adnyana, P. P., Adnyana, I. N., Wiweka, K., & Wulandani, H. R. (2018). The profile and behaviour of ‘digital tourists’ when making decisions concerning travelling case study: Generation Z in South Jakarta. Advances in research, 17(2), 1-13. google scholar
63. Shapira, A., & Goldenberg, M. (2005). AHP-based equipment selection model for construction projects. Journal of construction engineering and management, 131(12), 1263-1273. google scholar
64. Sirsat, S. S., & Sirsat, M. S. (2016). A validation of the DeLone and McLean model on the educational information system of the Maharashtra State (India). International Journal of Education and Learning Systems, 1. google scholar
65. Stevie, Z., Karamaşa, Ç., Demir, E., & Korucuk, S. (2021). Assessing sustainable production under circular economy context using a novel rough-fuzzy MCDM model: A case of the forestry industry in the Eastern Black Sea region. Journal of Enterprise Information Management. google scholar
66. Sun, C. C. (2010). A performance evaluation model by integrating fuzzy AHP and fuzzy TOPSIS methods. Expert systems with applications, 37(12), 7745-7754. google scholar
67. Tang, C., & Ngerng, M. (2015). How do students select social networking sites? An analytic hierarchy process (AHP) model. International Journal of Cyber Society and Education, 8(2), 81-98. google scholar
68. Thuy, H. T. H., Hieu, V. M., & Duy, B. P. M. (2021). Intention to use facebook for travel planning: An investigation on generation Z users in Ho Chi Minh city. Webology, 18(Special Issue on Information Retrieval and Web Search), 92-106. google scholar
69. Tseng, A. (2017). Why do online tourists need sellers’ ratings? Exploration of the factors affecting regretful tourist e-satisfaction. Tourism Management, 59, 413-424. google scholar
70. Tseng, T. H., Wang, Y. S., & Tsai, Y. C. (2021). Applying an AHP Technique for Developing A Website Model of Third-Party Booking System. Journal of Hospitality & Tourism Research, 45(8), 1440-1463. google scholar
71. TURKSTAT (2021). Hanehalkı Bilişim Teknolojileri (BT) Kullanım Araştırması, 2021, Retrieved September 5, 2022, from https://data.tuik.gov.tr/Bulten/Index?p=Hanehalki-Bilisim-Teknolojileri-(BT)-Kullanim-Arastirmasi-2021-37437 google scholar
72. Urbach, N., & Müller, B. (2012). The updated DeLone and McLean model of information systems success. Information Systems Theory: Explaining and Predicting Our Digital Society, Vol. 1, 1-18. google scholar
73. Usui, R., Wei, X., & Funck, C. (2018). The power of social media in regional tourism development: a case study from Ökunoshima Island in Hiroshima, Japan. Current Issues in Tourism, 21(18), 2052-2056. google scholar
74. Vieira, G. L. (2018). Trip-Planning Optimization: Minimizing Cost and Travel Time in Itineraries with Multiple Destinations (Doctoral dissertation, MSc. Thesis., School of Engineering, Federal University of Minas Gerais). google scholar
75. Wang, L., Ali, Y., Nazir, S., & Niazi, M. (2020). ISA evaluation framework for security of internet of health things system using AHP-TOPSIS methods. IEEE Access, 8, 152316-152332. google scholar
76. Wang, Y. Y., Wang, Y. S., Lin, H. H., & Tsai, T. H. (2019). Developing and validating a model for assessing paid mobile learning app success. Interactive Learning Environments, 27(4), 458-477. google scholar
77. Wang, Y. S. (2008). Assessing e-commerce systems success: a respecification and validation of the DeLone and McLean model of IS success. Information systems journal, 18(5), 529-557. google scholar
78. Wang, Y. S., Wang, H. Y., & Shee, D. Y. (2007). Measuring e-learning systems success in an organizational context: Scale development and validation. Computers in Human Behavior, 23(4), 1792-1808. google scholar
79. Zanna, M., & Xuedong, G. (2016). DMO tourism website’s success evaluation model and framework. European journal of economics and management sciences, (4). google scholar
80. Zviran, M., & Erlich, Z. (2003). Measuring IS user satisfaction: review and implications. Communications of the Association for Information Systems, 12(1), 5. google scholar