Understanding the Factors of Brand Switching Intention in Smartphones by Framework of the Push-Pull-Mooring Model

Year 2023, Volume: 12 Issue: 3, 1727 - 1744, 30.09.2023

Görkem Erdoğan

https://doi.org/10.15869/itobiad.1300979

Abstract

The aim of this study is to investigate the factors affecting the brand switching intention of smartphone users in Turkey. For this purpose, a research model based on the Push-Pull-Mooring model has been developed. To understand users' intention to switch, dissatisfaction as push factor, attractiveness of alternatives and subjective norm as pull factor, switching costs, habit and low individual innovativeness factors as engagement factors are used. The population of the research consists of individuals living in Ankara and using smart phones. Face-to-face survey method is used as data collection tool in the research with convenience sampling method. The study has obtained 363 valid responses from the participants. In the study, 7 scales have been used within the scope of 7 Likert Type. Confirmatory factor analysis is carried out to to ensure the validity of the scales and reliability analysis is performed to determine the internal consistency of the scales constituting the study model. Six hypotheses created in the study are tested with the structural equation model. The analysis covering the effect of push, pull and mooring factors on users' brand switching intentions is carried out using AMOS 24 and SPSS 26 package programs. Statistical significance is accepted as p<0.05 throughout the study. As a result of the research, dissatisfaction, attractiveness of alternatives and subjective norm positively affected brand switching intention. According to the findings, itis found that switching costs and low individual innovativeness had a significant and negative effect on brand switching intention. In addition, it was concluded that the habit did not have a significant effect on the intention to switch. It is thought that the study will contribute to the literature since it is a study that examines the intentions of individuals to switch their smartphone brand using the Push-Pull-Mooring model. It is seen that the research findings are similar to the studies conducted in previous years. It is expected that the results obtained in the research will provide various theoretical contributions to the literatüre. Besides, results that may contribute to managerial practices have been obtained from the findings.

Keywords

Push-Pull-Mooring Model, Brand Switching Behavior, Smartphones, Intention to Switch, Mobile Communication Systems

Akıllı Telefonlarda Marka Değiştirme Niyetinin Öncüllerinin İtme-Çekme-Bağlama Modeli Çerçevesinde İncelenmesi

Abstract

Bu çalışmanın amacı, Türkiye’de akıllı telefon kullanıcıların marka değiştirme niyetini etkileyen faktörleri araştırmaktır. Bu amaçla, İtme-Çekme-Bağlama modeline dayalı bir araştırma modeli geliştirilmiştir. Tüketicilerin marka değiştirmesini hangi faktörlerin etkilediğini anlamak, akıllı telefon markaları için önemli bir konudur. Kullanıcıların değiştirme niyetini anlamak için itme faktörü olarak tatminsizlik, çekme faktörü olarak alternatif çekicilik ve öznel norm, bağlama faktörü olarak değiştirme maliyetleri, alışkanlık ve düşük bireysel yenilikçilik faktörleri kullanılmıştır. Araştırma evrenini Ankara’da yaşayan ve akıllı telefon kullanan bireyler oluşturmaktadır. Kolayda örneklem yöntemiyle araştırmada veri toplama aracı olarak yüz yüze anket metodu kullanılmıştır. Çalışma için katılımcılardan 363 geçerli yanıt elde edilmiştir. Çalışmada 7’li Likert tipi kapsamında 7 adet ölçek kullanılmıştır. Çalışma modelini oluşturan ölçeklerin geçerliliğin sağlanmasında doğrulayıcı faktör analizi ve içsel tutarlılığını tespit etmek için güvenirlik analizi yapılmıştır. Çalışmada oluşturulan altı hipotez yapısal eşitlik modeli ile test edilmiştir. İtme, çekme ve bağlama faktörlerin kullanıcıların marka değiştirme niyetleri üzerindeki etkisini kapsayan analiz AMOS 24 ve SPSS 26 paket programları kullanılarak yapılmıştır. Çalışma boyunca istatistiksel anlamlılık p<0,05 olarak kabul edilmiştir. Araştırma sonucunda tatminsizlik, alternatiflerin çekiciliği ve öznel norm marka değiştirme niyetini pozitif olarak etkilemektedir. Elde edilen bulgulara göre değiştirme maliyetlerinin ve düşük bireysel yeniliğin marka değiştirme niyeti üzerinde anlamlı ve negatif bir etkisi bulunmuştur. Ayrıca alışkanlığın değiştirme niyeti üzerinde anlamlı bir etkisi olmadığı sonucuna ulaşılmıştır. Çalışmanın İtme-Çekme-Bağlama modelini kullanarak bireylerin akıllı telefon marka değiştirme niyetlerini inceleyen bir çalışma olması nedeniyle alan yazına katkısı olacağı düşünülmektedir. Araştırma bulgularının önceki yıllarda yapılan çalışmalarla benzer olduğu görülmektedir. Araştırmada elde edilen sonuçların literatüre çeşitli teorik katkılar sağlaması beklenmekte ve yönetsel uygulamalara katkısı olabilecek bulgulara ulaşılmıştır.

Keywords

İtme-Çekme-Bağlama Modeli, Marka Değiştirme Davranışı, Akıllı Telefonlar, Değiştirme Niyeti, Mobil İletişim Sistemleri

References

• Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information systems research, 9(2), 204-215.
• Ajzen, I. (1991). Theory of planned Behavior: Organizational behavior and human decision processes. Journal of Leisure Research, 100(1), 96e109.
• Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411.
• Appiah, D., Ozuem, W., Howell, K. E., & Lancaster, G. (2019). Brand switching and consumer identification with brands in the smartphones industry. Journal of Consumer Behaviour, 18(6), 463-473.
• Bankmycell, (2022). January 2023 Mobile User Statistics. https://www.bankmycell.com/blog/how-many-phones-are-in-the-world.
• Bansal, H. S., Taylor, S. F., & James, Y. S. (2005). Migrating to new service Providers: Toward a unifying framework of consumers' switching behaviors. Journal of the Academy of Marketing Science, 33(1), 96e115.
• Chang, H. H., Wong, K. H., & Li, S. Y. (2017). Applying push-pull-mooring to investigate channel switching behaviors: M-shopping self-efficacy and switching costs as moderators. Electronic Commerce Research and Applications, 24, 50-67.
• Chiu, C. M., Hsu, M. H., Lai, H., & Chang, C. M. (2012). Re-examining the influence of trust on online repeat purchase intention: The moderating role of habit and its antecedents. Decision Support Systems, 53(4), 835-845.
• Christino, J., Silva, T., Moura, L. R., & Fonseca, L. H. (2020). Antecedents and consequents of brand love in the smartphone market: an extended study of the impact of switching cost. Journal of Promotion Management, 26(3), 301-321.
• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
• Gefen, D., Straub, D., & Boudreau, M. C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the association for information systems, 4(1), 7.
• Gefen, D., & Straub, D. (2005). A practical guide to factorial validity using PLS-graph: Tutorial and annotated example. Communications of the Association for Information Systems, 16(1), 91-109.
• Gerpott, T. J., Rams, W., & Schindler, A. (2001). Customer retention, loyalty, and satisfaction in the German mobile cellular telecommunications market. Telecommunications policy, 25(4), 249-269.
• Guo, J., Shan, S., Wang, Y., & Khan, Y. A. (2021). Analyzing Chinese customers’ switching intention of smartphone brands: Integrating the push-pull-mooring framework. Discrete Dynamics in Nature and Society, 2021, 1-14.
• Hsiao, M. H., & Chen, L. C. (2015). Smart phone demand: An empirical study on the relationships between phone handset, Internet access and mobile services. Telematics and Informatics, 32(1), 158-168.
• Hsieh, J. K., Hsieh, Y. C., Chiu, H. C., & Feng, Y. C. (2012). Post-adoption switching behavior for online service substitutes: A perspective of the push–pull–mooring framework. Computers in Human Behavior, 28(5), 1912-1920.
• Jones, M. A., Mothersbaugh, D. L., & Beatty, S. E. (2000). Switching barriers and repurchase intentions in services. Journal of retailing, 76(2), 259-274.
• Kim, H. W. (2010). The effects of switching costs on user resistance to enterprise systems implementation. IEEE Transactions on Engineering Management, 58(3), 471-482.
• Kim, S., Choi, M. J., & Choi, J. S. (2019). Empirical study on the factors affecting individuals’ switching intention to augmented/virtual reality content services based on push-pull-mooring theory. Information, 11(1), 25.
• Kim, J., Lee, H., & Lee, J. (2020). Smartphone preferences and brand loyalty: A discrete choice model reflecting the reference point and peer effect. Journal of Retailing and Consumer Services, 52, 101907.
• 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.
• Kline. R. B. (2011). Principles and Practice of Structural Equation Modeling. Third Edition. London: The Guilford Press.
• Lam, S. Y., Shankar, V., Erramilli, M. K., & Murthy, B. (2004). Customer value, satisfaction, loyalty, and switching costs: an illustration from a business-to-business service context. Journal of the academy of marketing science, 32(3), 293-311.
• Levesque, T. J., & McDougall, G. H. (1996). Customer dissatisfaction: the relationship between types of problems and customer response. Canadian Journal of Administrative Sciences/Revue Canadienne des Sciences de l'Administration, 13(3), 264-276.
• Liao, J., Li, M., Wei, H., & Tong, Z. (2021). Antecedents of smartphone brand switching: a push–pull–mooring framework. Asia Pacific Journal of Marketing and Logistics, 33(7), 1596-1614.
• Liao, C., Palvia, P., & Lin, H. N. (2006). The roles of habit and web site quality in e-commerce. International Journal of Information Management, 26(6), 469-483.
• Lin, T. C., & Huang, S. L. (2014). Understanding the determinants of consumers' switching intentions in a standards war. International Journal of Electronic Commerce, 19(1), 163-189.
• Lisana, L. (2022). Factors affecting university students switching intention to mobile learning: a push-pull-mooring theory perspective. Education and Information Technologies, 1-21.
• Lu, J., Yao, J. E., & Yu, C. S. (2005). Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology. The Journal of Strategic Information Systems, 14(3), 245-268.
• Lu, T. (2017). Smartphone users replace their device every twenty-one months. Counterpoint Research, 13, https://www.counterpointresearch.com/smartphone-users-replace-their-device-every-twenty-one-months/
• Lu, H. P., & Wung, Y. S. (2021). Applying transaction cost theory and push-pull-mooring model to investigate mobile payment switching behaviors with well-established traditional financial infrastructure. Journal of theoretical and applied electronic commerce research, 16(2), 1-21.
• Moon, B. (1995). Paradigms in migration research: exploring'moorings' as a schema. Progress in human geography, 19(4), 504-524.
• Msaed, C., Al-Kwifi, S. O., & Ahmed, Z. U. (2017). Building a comprehensive model to investigate factors behind switching intention of high-technology products. Journal of Product & Brand Management, 26(2), 102-119.
• Nikhashemi, S. R., Valaei, N., & Tarofder, A. K. (2017). Does brand personality and perceived product quality play a major role in mobile phone consumers’ switching behaviour?. Global Business Review, 18(3), 108-127.
• Oliveira, T., Thomas, M., Baptista, G., & Campos, F. (2016). Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology. Computers in human behavior, 61, 404-414.
• Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. JMR, Journal of Marketing Research, 17(4), 460–469.
• Pae, J. H., & Hyun, J. S. (2006). Technology advancement strategy on patronage decisions: the role of switching costs in high-technology markets. The International Journal of Management Sciences, 34(1), 19-27.
• Rong-Da Liang, A., Lee, C. L., & Tung, W. (2014). The role of sunk costs in online consumer decision-making. Electronic Commerce Research and Applications, 13(1), 56-68.
• Statista, (2023a). Number of smartphone users in Turkey 2019-2028 (in millions). https://www.statista.com/statistics/467181/forecast-of-smartphone-users-in-turkey/
• Statista, (2023b). Global smartphone market share from 4th quarter 2009 to 2nd quarter 2023. https://www.statista.com/statistics/271496/global-market-share-held-by-smartphone-vendors-since-4th-quarter-2009/
• Sun, Y., Liu, D., Chen, S., Wu, X., Shen, X. L., & Zhang, X. (2017). Understanding users' switching behavior of mobile instant messaging applications: An empirical study from the perspective of push-pull-mooring framework. Computers in Human Behavior, 75, 727-738.
• Tabachnick, B.G. ve Fidell, L.S. (2013). Using Multivariate Statistics, Boston: Pearson.
• Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information systems research, 6(2), 144-176.
• Verplanken, B., & Aarts, H. (1999). Habit, attitude, and planned behaviour: is habit an empty construct or an interesting case of goal-directed automaticity?. European review of social psychology, 10(1), 101-134.
• Yoon, C., Jeong, C., & Rolland, E. (2015). Understanding individual adoption of mobile instant messaging: A multiple perspectives approach. Information Technology and Management, 16(2), 139-151.
• Yoon, C., & Lim, D. (2021). Customers’ Intentions to Switch to Internet-Only Banks: Perspective of the Push-Pull-Mooring Model. Sustainability, 13(14), 8062.
• Zhang, K. Z., Cheung, C. M., Lee, M. K., & Chen, H. (2008). Understanding the blog service switching in Hong Kong: an empirical investigation. In Proceedings of the 41st annual Hawaii international conference on system sciences (HICSS 2008), 269-277.
• Zhou, T. (2016). Examining user switch between mobile stores: A push-pull-mooring perspective. Information Resources Management Journal (IRMJ), 29(2), 1-13.
• Zhou, T. (2021). Understanding Users' Switching Between Social Media Platforms: A PPM Perspective. International Journal of Information Systems in the Service Sector (IJISSS), 13(1), 54-67.
• Zins, A. H. (2001). Relative attitudes and commitment in customer loyalty models: Some experiences in the commercial airline industry. International Journal of Service Industry Management, 12(3), 269-294.
• Zippia, (2022). 20 vital smartphone usage statistics [2022]: Facts, data, and trends on mobile use in the U.S. https://www.zippia.com/advice/smartphone-usage-statistics/.