A BIBLIOMETRIC ANALYSIS OF THE LITERATURE ON THE ORIGINS OF THE TECHNOLOGY ACCEPTANCE MODEL (TAM) AND A MARKETING-SIDED APPROACH TO TAM

Yıl 2023, Cilt: 18 Sayı: 59, 1 - 14, 31.01.2023

Zübeyir Çelik , Aypar Uslu

https://doi.org/10.14783/maruoneri.1171625

Cited By: 2

Öz

This study aims to visually present the bibliometric data sources related to the origin of TAM as a result of the literature review by running the VOSviewer visual mapping technique. The bibliometric data sources obtained, the selected studies and the citation counts of these studies are for the researchers who contributed to TAM, the theoretical foundations of TAM, the key components of TAM, and the application areas of TAM. The PRISMA 2009 Flow Diagram was used for a systematic literature review. Many studies published from 1985, when the original TAM was introduced, to 2008, when TAM 3 was introduced, contributed to the development of TAM, and most of these studies have over one thousand citation counts. Fred D. Davis and/or Viswanath Venkatesh have co-authored with some of the researchers contributing to TAM. The theoretical foundations of TAM are based on many more theories/models in addition to the theory of reasoned action. In addition to the two key components of ease of use and usefulness, TAM has other key components. Finally, management information technology, management information systems, and computer technology are areas where TAM is applied. Explanations are provided in this present study with a marketing-sided approach to the application areas of TAM.

Anahtar Kelimeler

Technolog Acceptance Model, Origin, Bibliometic Analysis, Marketing

TEKNOLOJİ KABUL MODELİ (TKM)’NİN KÖKENLERİNE İLİŞKİN LİTERATÜRÜN BİBLİYOMETRİK ANALİZİ VE TKM’YE PAZARLAMA YÖNLÜ BİR YAKLAŞIM

Öz

Bu çalışma, VOSviewer görsel haritalama tekniğini çalıştırarak, literatür taraması sonucunda TKM'nin kökeni ile ilgili bibliyometrik veri kaynaklarını görsel olarak sunmayı amaçlamaktadır. Elde edilen bibliyometrik veri kaynakları, seçilen çalışmalar ve bu çalışmaların atıf sayıları, TKM'ye katkıda bulunan araştırmacılar, TKM'nin teorik temelleri, TKM'nin temel bileşenleri ve TKM'nin uygulama alanları içindir. PRISMA 2009 Akış Diagramı, sistematik bir literatür taraması için kullanılmıştır. Orijinal TKM'nin tanıtıldığı 1985 yılından, TKM 3'ün tanıtıldığı 2008 yılına kadar yayımlanan birçok çalışma, TKM'nin geliştirilmesine katkıda bulunmuştur ve bu çalışmaların çoğu binin üzerinde atıf sayısına sahiptir. Fred D. Davis ve/veya Viswanath Venkatesh, TKM’ye katkıda bulunan bazı araştırmacılarla ortak yazarlığa sahiptir. TKM'nin teorik temelleri, gerekçeli eylem teorisine ek olarak daha birçok teoriye/modele dayanmaktadır. Kullanım kolaylığı ve fayda gibi iki temel bileşene ek olarak, TKM'nin başka temel bileşenleri de vardır. Son olarak, yönetim bilgi teknolojisi, yönetim bilgi sistemleri ve bilgisayar teknolojisi, TKM'nin uygulandığı alanlardır. TKM'nin uygulama alanlarına pazarlama yönlü bir yaklaşımla bu mevcut çalışmada açıklamalar sağlanmaktadır.

Anahtar Kelimeler

Teknoloji Kabul Modeli, Köken, Bibliyometrik Analiz, Pazarlama

Kaynakça

• Afshan, S., Sharif, A., Waseem, N., & Frooghi, R. (2018). Internet banking in Pakistan: An extended technology acceptance perspective. International Journal of Business Information Systems, 27(3), 383-410.
• Ahmad, M. (2018). Review of the technology acceptance model (TAM) in internet banking and mobile banking. International Journal of Information Communication Technology and Digital Convergence, 3(1), 23-41.
• Al-Emran, M., & Granić, A. (2021). Is it still valid or outdated? A bibliometric analysis of the technology acceptance model and its applications from 2010 to 2020. In Recent Advances in Technology Acceptance Models and Theories (pp. 1-12). Springer, Cham.
• ALraja, M. N., & Aref, M. (2015). Customer acceptance of e-commerce: Integrating perceived risk with TAM. International Journal of Applied Business and Economic Research, 13(2), 913-921.
• Castañeda, J. A., Muñoz-Leiva, F., & Luque, T. (2007). Web Acceptance Model (WAM): Moderating effects of user experience. Information & Management, 44(4), 384-396.
• Chen, Y. M., Hsu, T. H., & Lu, Y. J. (2018). Impact of flow on mobile shopping intention. Journal of Retailing and Consumer Services, 41, 281-287.
• Chung, J., & Tan, F. B. (2004). Antecedents of perceived playfulness: An exploratory study on user acceptance of general information-searching websites. Information & Management, 41(7), 869-881.
• Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results (Doctoral dissertation, Massachusetts Institute of Technology).
• Davis, F. D. (1987). User acceptance of information systems: The technology acceptance model (TAM). Working paper no. 529, Graduate School of Business, University of Michigan.
• Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
• Davis, F. D. (1993). User acceptance of information technology: System characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies, 38(3), 475-487.
• 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 1. Journal of Applied Social Psychology, 22(14), 1111-1132.
• Davis, F. D., & Venkatesh, V. (1995). Measuring user acceptance of emerging information technologies: An assessment of possible method biases. In Proceedings of the Twenty-Eighth Annual Hawaii İnternational Conference on System Sciences (Vol. 4, pp. 729-736). IEEE.
• Davis, F. D., & Venkatesh, V. (1996). A critical assessment of potential measurement biases in the technology acceptance model: three experiments. International Journal of Human-Computer Studies, 45(1), 19-45.
• Davis, F. D., & Venkatesh, V. (2004). Toward preprototype user acceptance testing of new information systems: Implications for software project management. IEEE Transactions on Engineering Management, 51(1), 31-46.
• Dimoka, A., & Davis, F. D. (2008). Where does TAM reside in the brain? The neural mechanisms underlying technology adoption. ICIS 2008 Proceedings, 169.
• Eid, R. (2009). Extending TAM and IDT to predict the adoption of the internet for B-to-B marketing activities: An empirical study of UK companies. International Journal of E-Business Research (IJEBR), 5(4), 68-85.
• El-Gohary, H. (2010). Expanding TAM and IDT to understand the adoption of e-marketing by small business enterprises: An empirical investigation. International Journal of Customer Relationship Marketing and Management (IJCRMM), 1(3), 56-75.
• Gauzente, C., Ranchhod, A., & Gurau, C. (2008). SMS-marketing: A study of consumer saturation using an extended TAM approach. International Journal of Electronic Business, 6(3), 282-297.
• Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205-223.
• Kousha, K., & Thelwall, M. (2007). Google Scholar citations and Google Web/URL citations: A multi‐discipline exploratory analysis. Journal of the American Society for Information Science and Technology, 58(7), 1055-1065.
• Mathieson, K. (1991). Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2(3), 173-191.
• Pei, Z., Zhenxiang, Z., & Chunping, H. (2007). An extended TAM model for Chinese B2C Websites design. Journal of Global Information Technology Management, 10(1), 51-66.
• Reyes-Menendez, A., Saura, J. R., & Filipe, F. (2019). The importance of behavioral data to identify online fake reviews for tourism businesses: A systematic review. PeerJ Computer Science, 5, e219.
• Ritz, W., Wolf, M., & McQuitty, S. (2019). Digital marketing adoption and success for small businesses: The application of the do-it-yourself and technology acceptance models. Journal of Research in Interactive Marketing, 13(2), 179-203.
• Shankar, A., & Datta, B. (2018). Factors affecting mobile payment adoption intention: An Indian perspective. Global Business Review, 19(3_suppl), S72-S89.
• Shin, D. H., & Kim, W. Y. (2008). Applying the technology acceptance model and flow theory to cyworld user behavior: Implication of the web2. 0 user acceptance. CyberPsychology & Behavior, 11(3), 378-382.
• Sukhu, A., Zhang, T., & Bilgihan, A. (2015). Factors influencing information-sharing behaviors in social networking sites. Services Marketing Quarterly, 36(4), 317-334.
• Susanti, E., & Astuti, F. D. (2019). Technology acceptance model for digital marketing analysis. In Proceedings of the International Conferences on Information System and Technology (CONRIST) (pp. 85-91). SCITEPRESS–Science and Technology Publications, Lda..
• Tsai, M. T., Cheng, N. C., & Chen, K. S. (2011). Understanding online group buying intention: The roles of sense of virtual community and technology acceptance factors. Total Quality Management & Business Excellence, 22(10), 1091-1104.
• Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342-365.
• Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-315.
• Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451-481.
• Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
• Venkatesh, V., & Morris, M. G. (2000). Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115-139.
• Venkatesh, V., Speier, C., & Morris, M. G. (2002). User acceptance enablers in individual decision making about technology: Toward an integrated model. Decision Sciences, 33(2), 297-316.
• Wahdain, E. A., & Ahmad, M. N. (2014). User acceptance of information technology: Factors, theories and applications. Journal of Information Systems Research and Innovation, 6(1), 17-25.
• Yuan, S., Liu, Y., Yao, R., & Liu, J. (2016). An investigation of users’ continuance intention towards mobile banking in China. Information Development, 32(1), 20-34.