Araştırma Makalesi
BibTex RIS Kaynak Göster

Mobil Otel Rezervasyonu Sistemlerinde Tüketici Tatminini Etkileyen Faktörlerin Görev-Teknoloji Uyumu Modeli ile İncelenmesi

Yıl 2024, Cilt: 8 Sayı: 2, 890 - 911, 30.11.2024
https://doi.org/10.30561/sinopusd.1239493

Öz

Mobil Otel Rezervasyonu Sistemlerinde müşteri tatminini etkileyen faktörlerin Görev-Teknoloji Uyum Modeli çerçevesinde belirlenmesi bu araştırmanın amacını oluşturmaktadır. Araştırmanın verileri Ankara ilinde yaşayan 423 kişiden anket yoluyla elde edilmiştir. Araştırma verilerinin analizi, SPSS ve AMOS programlarını kullanarak yapısal eşitlik modellemesi yöntemiyle gerçekleştirilmiştir. Araştırma sonucu görev özelliklerinin ve teknoloji özelliklerinin, görev-teknoloji uyumu üzerinde pozitif yönlü ve anlamlı etkisinin olduğu ortaya koymaktadır. Diğer taraftan görev-teknoloji uyumunun, algılanan değerin ve algılanan keyfin müşteri tatminini pozitif yönde etkilediği bulgusuna ulaşılmıştır. Yapılan analizler ile çalışmanın hipotezlerin sonucundan elde edilen bulguların ilgili literatürü destekler nitelikte olduğu tespit edilmiştir. Elde edilen sonuçlar hem mobil otel rezervasyon sistemleri konusunda yeni bakış açılarına işaret edecek olması hem de literatüre katkı sağlaması bakımından önem arz etmektedir.

Kaynakça

  • Alalwan, A. A., Baabdullah, A. M., Rana, N. P., Tamilmani, K., & Dwivedi, Y. K. (2018). Examining adoption of mobile internet in Saudi Arabia: Extending TAM with perceived enjoyment, innovativeness and trust. Technology in Society, 55, 100-110.
  • Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411.
  • Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the academy of marketing science, 16(1), 74-94.
  • Cheng, Y. M. (2019). How does task-technology fit influence cloud-based e-learning continuance and impact?. Education+ Training, 61(4), 480-499.
  • Criteo, (2018). 7 key trends for the travel industry in 2018. https://www.criteo.com/blog/travel-market-research/.
  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace 1. Journal of applied social psychology, 22(14), 1111-1132.
  • Del Bosque, I. R., & San Martín, H. (2008). Tourist satisfaction a cognitive-affective model. Annals of tourism research, 35(2), 551-573.
  • Fornell, C. ve Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement eror. Journal of Marketing, 18(1), 39-50.
  • Goodhue, D. L. (1998). Development and measurement validity of a task‐technology fit instrument for user evaluations of information system. Decision sciences, 29(1), 105-138.
  • Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS quarterly, 213-236.
  • Gürbüz, S., ve Şahin, F. (2017). Sosyal Bilimlerde Araştırma Yöntemleri: Felsefe-Yöntem-Analiz, Ankara: Seçkin Yayıncılık.
  • Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). New York: Pearson.
  • Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal, 6(1), 1-55.
  • Kim, J. J., Chua, B. L., & Han, H. (2021). Mobile hotel reservations and customer behavior: Channel familiarity and channel type. Journal of Vacation Marketing, 27(1), 82-102.
  • Kim, M. J., Chung, N., Lee, C. K., & Preis, M. W. (2015). Motivations and use context in mobile tourism shopping: Applying contingency and task–technology fit theories. International Journal of Tourism Research, 17(1), 13-24.
  • Kline. R. B. (2011). Principles and Practice of Structural Equation Modeling. Third Edition. London: The Guilford Press.
  • Law, R., Chan, I. C. C., & Wang, L. (2018). A comprehensive review of mobile technology use in hospitality and tourism. Journal of Hospitality Marketing & Management, 27(6), 626-648.
  • Lee, M. K., Cheung, C. M., & Chen, Z. (2005). Acceptance of Internet-based learning medium: the role of extrinsic and intrinsic motivation. Information & management, 42(8), 1095-1104.
  • Lee, K. C., Lee, S., & Kim, J. S. (2004). Analysis of mobile commerce performance by using the task-technology fit. In IFIP Working Conference on Mobile Information Systems (pp. 135-153). Springer, Boston, MA.
  • Lin, W. S. (2012). Perceived fit and satisfaction on web learning performance: IS continuance intention and task-technology fit perspectives. International Journal of Human-Computer Studies, 70(7), 498-507.
  • Lin, H. H., & Wang, Y. S. (2006). An examination of the determinants of customer loyalty in mobile commerce contexts. Information & management, 43(3), 271-282.
  • Linton H., & Kwortnik R. (2015). The mobile revolution is here: are you ready? Cornell Hospitality Rep 15(6):18. Murphy, H. C., Chen, M. M., & Cossutta, M. (2016). An investigation of multiple devices and information sources used in the hotel booking process. Tourism management, 52, 44-51.
  • Mohamad, M. A., Hanafiah, M. H., & Radzi, S. M. (2021). Understanding tourist mobile hotel booking behaviour: Incorporating perceived enjoyment and perceived price value in the modified Technology Acceptance Model. Tourism & Management Studies, 17(1), 19-30.
  • Mohd, N., Mohamad, A. H., Norzuwana, S., Mohd, H. H., & Muhammad, I. Z. (2017). Customer's acceptance, usage and M-satisfaction of Mobile Hotel Reservation Apps (MHRA). Journal of Tourism, Hospitality and Culinary Arts, 9(2), 425-442.
  • Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of marketing research, 17(4), 460-469.
  • Ozturk, A. B., Nusair, K., Okumus, F., & Singh, D. (2017). Understanding mobile hotel booking loyalty: an integration of privacy calculus theory and trust-risk framework. Information Systems Frontiers, 19(4), 753-767.
  • Qin, M., Tang, C. H. H., Jang, S. S., & Lehto, X. (2017). Mobile app introduction and shareholder returns. Journal of Hospitality and Tourism Management, 31, 173-180.
  • Rahi, S., Khan, M. M., & Alghizzawi, M. (2020). Extension of technology continuance theory (TCT) with task technology fit (TTF) in the context of Internet banking user continuance intention. International Journal of Quality & Reliability Management, 38(4), 986-1004.
  • Ratna, S., Utami, H. N., Astuti, E. S., & Muflih, M. (2020). The technology tasks fit, its impact on the use of information system, performance and users’ satisfaction. VINE Journal of Information and Knowledge Management Systems, 50(3), 369-386.
  • Rezaei, S., & Valaei, N. (2017). Crafting experiential value via smartphone apps channel. Marketing Intelligence & Planning, 35(5), 688-702.
  • Spreng, R. A., MacKenzie, S. B., & Olshavsky, R. W. (1996). A reexamination of the determinants of consumer satisfaction. Journal of marketing, 60(3), 15-32.
  • Statista, (2020). Forecast number of mobile devices worldwide from 2020 to 2025 (in billions). https://www.statista.com/statistics/245501/multiple-mobile-device-ownership-worldwide/
  • Tabachnick, B. G. ve Fidell, L. S. (2014). Using Multivariate Statistics, (6nd ed.), Boston, Pearson. Tam, C., & Oliveira, T. (2016). Performance impact of mobile banking: using the task-technology fit (TTF) approach. International Journal of Bank Marketing, 34(4), 434-457.
  • Tao, M., Nawaz, M. Z., Nawaz, S., Butt, A. H., & Ahmad, H. (2018). Users’ acceptance of innovative mobile hotel booking trends: UK vs. PRC. Information Technology & Tourism, 20(1), 9-36.
  • Travel Agent Central, (2017). Stats: Hotel Bookings on Mobile Devices Up 67 Percent. https://www.travelagentcentral.com/running-your-business/stats-hotel-bookings-mobile-devices-up-67-percent
  • Vagrani, A., Kumar, N., & Ilavarasan, P. V. (2017). Decline in mobile application life cycle. Procedia computer science, 122, 957-964.
  • Valaei, N., Nikhashemi, S. R., Bressolles, G., & Jin, H. H. (2019). A (n)(a) symmetric perspective towards task-technology-performance fit in mobile app industry. Journal of enterprise information management, 32(5), 887-912.
  • Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, 157-178.
  • Wang, Y. S., Li, H. T., Li, C. R., & Zhang, D. Z. (2016). Factors affecting hotels' adoption of mobile reservation systems: A technology-organization-environment framework. Tourism Management, 53, 163-172.
  • Wang, H. Y., & Wang, S. H. (2010). Predicting mobile hotel reservation adoption: Insight from a perceived value standpoint. International Journal of Hospitality Management, 29(4), 598-608.
  • Williams, P., & Soutar, G. N. (2009). Value, satisfaction and behavioral intentions in an adventure tourism context. Annals of tourism research, 36(3), 413-438.
  • Wu, J. S., Law, R., & Liu, J. (2018). Co-creating value with customers: a study of mobile hotel bookings in China. International Journal of Contemporary Hospitality Management, 30(4), 2056-2074.
  • Xiang, Z., Tussyadiah, I., & Buhalis, D. (2015). Smart destinations: foundations, analytics, and applications. Journal of Destination Marketing and Management. 4(3), 143-144.
  • Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. Journal of marketing, 52(3), 2-22.
  • 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.

Examination of Factors Affecting Consumer Satisfaction in Mobile Hotel Reservation Systems with Task-technology Fit Model

Yıl 2024, Cilt: 8 Sayı: 2, 890 - 911, 30.11.2024
https://doi.org/10.30561/sinopusd.1239493

Öz

The aim of this research is to determine the factors affecting customer satisfaction in Mobile Hotel Reservation Systems within the framework of the Task-Technology Fit Model. The data of the research were obtained from 423 people living in Ankara through a questionnaire. Analysis of the research data was carried out with the structural equation modeling method using SPSS and AMOS programs. The results of the research reveal that task characteristics and technology characteristics have a positive and significant effect on task-technology fit. On the other hand, it is found that task-technology fit, perceived value and perceived enjoyment positively affect customer satisfaction. With the analyzes made, it has been determined that the findings obtained from the results of the hypotheses of the study support the relevant literature. The results obtained are important in terms of both pointing out new perspectives on mobile hotel reservation systems and contributing to the literature.

Kaynakça

  • Alalwan, A. A., Baabdullah, A. M., Rana, N. P., Tamilmani, K., & Dwivedi, Y. K. (2018). Examining adoption of mobile internet in Saudi Arabia: Extending TAM with perceived enjoyment, innovativeness and trust. Technology in Society, 55, 100-110.
  • Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411.
  • Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the academy of marketing science, 16(1), 74-94.
  • Cheng, Y. M. (2019). How does task-technology fit influence cloud-based e-learning continuance and impact?. Education+ Training, 61(4), 480-499.
  • Criteo, (2018). 7 key trends for the travel industry in 2018. https://www.criteo.com/blog/travel-market-research/.
  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace 1. Journal of applied social psychology, 22(14), 1111-1132.
  • Del Bosque, I. R., & San Martín, H. (2008). Tourist satisfaction a cognitive-affective model. Annals of tourism research, 35(2), 551-573.
  • Fornell, C. ve Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement eror. Journal of Marketing, 18(1), 39-50.
  • Goodhue, D. L. (1998). Development and measurement validity of a task‐technology fit instrument for user evaluations of information system. Decision sciences, 29(1), 105-138.
  • Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS quarterly, 213-236.
  • Gürbüz, S., ve Şahin, F. (2017). Sosyal Bilimlerde Araştırma Yöntemleri: Felsefe-Yöntem-Analiz, Ankara: Seçkin Yayıncılık.
  • Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). New York: Pearson.
  • Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal, 6(1), 1-55.
  • Kim, J. J., Chua, B. L., & Han, H. (2021). Mobile hotel reservations and customer behavior: Channel familiarity and channel type. Journal of Vacation Marketing, 27(1), 82-102.
  • Kim, M. J., Chung, N., Lee, C. K., & Preis, M. W. (2015). Motivations and use context in mobile tourism shopping: Applying contingency and task–technology fit theories. International Journal of Tourism Research, 17(1), 13-24.
  • Kline. R. B. (2011). Principles and Practice of Structural Equation Modeling. Third Edition. London: The Guilford Press.
  • Law, R., Chan, I. C. C., & Wang, L. (2018). A comprehensive review of mobile technology use in hospitality and tourism. Journal of Hospitality Marketing & Management, 27(6), 626-648.
  • Lee, M. K., Cheung, C. M., & Chen, Z. (2005). Acceptance of Internet-based learning medium: the role of extrinsic and intrinsic motivation. Information & management, 42(8), 1095-1104.
  • Lee, K. C., Lee, S., & Kim, J. S. (2004). Analysis of mobile commerce performance by using the task-technology fit. In IFIP Working Conference on Mobile Information Systems (pp. 135-153). Springer, Boston, MA.
  • Lin, W. S. (2012). Perceived fit and satisfaction on web learning performance: IS continuance intention and task-technology fit perspectives. International Journal of Human-Computer Studies, 70(7), 498-507.
  • Lin, H. H., & Wang, Y. S. (2006). An examination of the determinants of customer loyalty in mobile commerce contexts. Information & management, 43(3), 271-282.
  • Linton H., & Kwortnik R. (2015). The mobile revolution is here: are you ready? Cornell Hospitality Rep 15(6):18. Murphy, H. C., Chen, M. M., & Cossutta, M. (2016). An investigation of multiple devices and information sources used in the hotel booking process. Tourism management, 52, 44-51.
  • Mohamad, M. A., Hanafiah, M. H., & Radzi, S. M. (2021). Understanding tourist mobile hotel booking behaviour: Incorporating perceived enjoyment and perceived price value in the modified Technology Acceptance Model. Tourism & Management Studies, 17(1), 19-30.
  • Mohd, N., Mohamad, A. H., Norzuwana, S., Mohd, H. H., & Muhammad, I. Z. (2017). Customer's acceptance, usage and M-satisfaction of Mobile Hotel Reservation Apps (MHRA). Journal of Tourism, Hospitality and Culinary Arts, 9(2), 425-442.
  • Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of marketing research, 17(4), 460-469.
  • Ozturk, A. B., Nusair, K., Okumus, F., & Singh, D. (2017). Understanding mobile hotel booking loyalty: an integration of privacy calculus theory and trust-risk framework. Information Systems Frontiers, 19(4), 753-767.
  • Qin, M., Tang, C. H. H., Jang, S. S., & Lehto, X. (2017). Mobile app introduction and shareholder returns. Journal of Hospitality and Tourism Management, 31, 173-180.
  • Rahi, S., Khan, M. M., & Alghizzawi, M. (2020). Extension of technology continuance theory (TCT) with task technology fit (TTF) in the context of Internet banking user continuance intention. International Journal of Quality & Reliability Management, 38(4), 986-1004.
  • Ratna, S., Utami, H. N., Astuti, E. S., & Muflih, M. (2020). The technology tasks fit, its impact on the use of information system, performance and users’ satisfaction. VINE Journal of Information and Knowledge Management Systems, 50(3), 369-386.
  • Rezaei, S., & Valaei, N. (2017). Crafting experiential value via smartphone apps channel. Marketing Intelligence & Planning, 35(5), 688-702.
  • Spreng, R. A., MacKenzie, S. B., & Olshavsky, R. W. (1996). A reexamination of the determinants of consumer satisfaction. Journal of marketing, 60(3), 15-32.
  • Statista, (2020). Forecast number of mobile devices worldwide from 2020 to 2025 (in billions). https://www.statista.com/statistics/245501/multiple-mobile-device-ownership-worldwide/
  • Tabachnick, B. G. ve Fidell, L. S. (2014). Using Multivariate Statistics, (6nd ed.), Boston, Pearson. Tam, C., & Oliveira, T. (2016). Performance impact of mobile banking: using the task-technology fit (TTF) approach. International Journal of Bank Marketing, 34(4), 434-457.
  • Tao, M., Nawaz, M. Z., Nawaz, S., Butt, A. H., & Ahmad, H. (2018). Users’ acceptance of innovative mobile hotel booking trends: UK vs. PRC. Information Technology & Tourism, 20(1), 9-36.
  • Travel Agent Central, (2017). Stats: Hotel Bookings on Mobile Devices Up 67 Percent. https://www.travelagentcentral.com/running-your-business/stats-hotel-bookings-mobile-devices-up-67-percent
  • Vagrani, A., Kumar, N., & Ilavarasan, P. V. (2017). Decline in mobile application life cycle. Procedia computer science, 122, 957-964.
  • Valaei, N., Nikhashemi, S. R., Bressolles, G., & Jin, H. H. (2019). A (n)(a) symmetric perspective towards task-technology-performance fit in mobile app industry. Journal of enterprise information management, 32(5), 887-912.
  • Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, 157-178.
  • Wang, Y. S., Li, H. T., Li, C. R., & Zhang, D. Z. (2016). Factors affecting hotels' adoption of mobile reservation systems: A technology-organization-environment framework. Tourism Management, 53, 163-172.
  • Wang, H. Y., & Wang, S. H. (2010). Predicting mobile hotel reservation adoption: Insight from a perceived value standpoint. International Journal of Hospitality Management, 29(4), 598-608.
  • Williams, P., & Soutar, G. N. (2009). Value, satisfaction and behavioral intentions in an adventure tourism context. Annals of tourism research, 36(3), 413-438.
  • Wu, J. S., Law, R., & Liu, J. (2018). Co-creating value with customers: a study of mobile hotel bookings in China. International Journal of Contemporary Hospitality Management, 30(4), 2056-2074.
  • Xiang, Z., Tussyadiah, I., & Buhalis, D. (2015). Smart destinations: foundations, analytics, and applications. Journal of Destination Marketing and Management. 4(3), 143-144.
  • Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. Journal of marketing, 52(3), 2-22.
  • 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.
Toplam 45 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Ekonomi, İşletme ve Yönetim Müfredatı ve Öğretimi
Bölüm Araştırma Makaleleri
Yazarlar

Görkem Erdoğan 0000-0002-2417-2718

Yayımlanma Tarihi 30 Kasım 2024
Gönderilme Tarihi 20 Ocak 2023
Yayımlandığı Sayı Yıl 2024 Cilt: 8 Sayı: 2

Kaynak Göster

APA Erdoğan, G. (2024). Mobil Otel Rezervasyonu Sistemlerinde Tüketici Tatminini Etkileyen Faktörlerin Görev-Teknoloji Uyumu Modeli ile İncelenmesi. Sinop Üniversitesi Sosyal Bilimler Dergisi, 8(2), 890-911. https://doi.org/10.30561/sinopusd.1239493

                                                 

                        Bu eser Creative Commons BY-NC-SA 2.0 (Atıf-Gayri Ticari-Aynı Lisansla Paylaş) ile lisanslanmıştır.