MOBİL MARKET ALIŞVERİŞİNDE ALGILANAN DEĞERİN ÖNCÜLLERİ VE SONUÇLARI

Abstract

Amaç- Çalışma, mobil market alışveriş (MMA) kapsamında tüketicilerin algıladıkları değerin öncüllerinin ve sonuçlarının incelenmesini amaçlamaktadır. Çalışmada finansal riskin ve performans riskinin algılanan değer üzerindeki, algılanan değerin yeniden satın alma niyeti ve kurumsal imaj üzerindeki etkisi incelenmiştir. Yöntem- Çalışmada kolayda örnekleme yöntemi kullanılmıştır. Veriler, Ankara’da yaşayan 271 kullanıcıdan anket yöntemiyle toplanmış ve yapısal eşitlik modellemesi ile analiz edilmiştir. Normallik ve Cronbach Alfa değerleri SPSS 26 paket programıyla; uyum iyiliği değerleri, geçerlilik analizi ve yol modellemesi ise AMOS 24 paket programıyla gerçekleştirilmiştir. Bulgular- Finansal riskin (β=-0,389; p<0,001) algılanan değer üzerinde performans riskine (β=-0,228; p<0,001) göre biraz daha güçlü bir olumsuz etkisi vardır. Algılanan değerin, yeniden satın alma niyeti (β=0,622; p<0,001) ve kurumsal kimliği (β=0,262; p<0,001) üzerinde olumlu etkisi olduğu sonucuna ulaşılmıştır. Sonuç- Araştırma sonucunda finansal riskin ve performans riskin algılanan değeri negatif yönde etkilediği ortaya çıkartılmıştır. MMA kullanımı tüketicinin parasının karşılığını verdiği zaman, bireyin ürün satın almak için bu mobil hizmeti kullanmaya devam etmeyi düşünmesine neden olacaktır. Ayrıca MMA kullanımının tüketici için faydalı olması, bireylerde market alışverişi ürünleri satan bu şirketin topluma sosyal bir katkısı ve olumlu bir imajı olduğu algısının oluşmasına sebep olmaktadır.

Keywords

• Mobil market alışverişi
• mobil alışveriş
• algılanan değer
• yeniden satın alma niyeti
• kurumsal imaj

ANTECEDENTS AND CONSEQUENCES OF PERCEIVED VALUE IN MOBILE GROCERY SHOPPING

Abstract

Purpose- The study aims to examine the antecedents and consequences of consumers' perceived value within the scope of mobile grocery shopping (MGS). In the study, the effect of financial risk and performance risk on perceived value, and the effect of perceived value on repurchase intention and corporate image were examined. Methodology- Convenience sampling method has been used in the study. Data are collected from 271 users living in Ankara by survey method and analyzed by structural equation model. Normality and Cronbach Alpha values are conducted with SPSS 26 package program; Goodness of fit values, validity analysis and path modelling are carried out with the AMOS 24 package program. Findings- Financial risk (β=-0.389; p<0.001) has a slightly stronger negative impact on perceived value than performance risk (β=-0.228; p<0.001). It was concluded that perceived value positively affects repurchase intention (β=0.622; p<0.001) and corporate identity (β=0.262; p<0.001). Conclusion- As a result of the research, it is revealed that financial risk and performance risk affect the perceived value negatively. When the use of MMA is worth the money to the consumer, it will lead to the individual to consider continuing to use this mobile service to purchase products. Moreover, the fact that the use of MMA is beneficial for the consumer causes the perception that this company, which sells grocery products, has a social contribution and a positive image to the society.

Keywords

• Mobile grocery shopping
• mobile commerce
• perceived value
• repurchase intention
• corporate image

References

1. Al Amin, M., Arefin, M. S., Hossain, I., Islam, M. R., Sultana, N., & Hossain, M. N. (2022). Evaluating the determinants of customers’ mobile grocery shopping application (MGSA) adoption during COVID-19 pandemic. Journal of Global Marketing, 35(3), 228-247.
2. Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411-423.
3. Aydin, S., & Özer, G. (2005). The analysis of antecedents of customer loyalty in the Turkish mobile telecommunication market. European Journal of Marketing. 39(7/8), 910-925.
4. Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94.
5. Barich, H., & Kotler, P. (1991). A framework for marketing image management. Sloan Management Review, 32(2), 94–104.
6. Chen, Z., & Dubinsky, A. J. (2003). A conceptual model of perceived customer value in e‐commerce: A preliminary investigation. Psychology & Marketing, 20(4), 323-347.
7. Cheng, J. M. S., Wang, E. S. T., Lin, J. Y. C., & Vivek, S. D. (2009). Why do customers utilize the internet as a retailing platform? A view from consumer perceived value. Asia Pacific Journal of Marketing and Logistics, 21(1), 144-160.
8. Chi, H.K., Yeh, H.R., Jang, B.F. (2008). The effects of service quality, customer perceived value, customer satisfaction on behavioral intentions: a study of mobile value-added services in Taiwan. The Business Review, 10 (1), 129– 135.

9. Cronin, J. J., Brady, M. K., & Hult, G. T. M. (2000). Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intentions in service environments. Journal of Retailing, 76(2), 193–218.
10. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
11. Forsythe, S. M., & Shi, B. (2003). Consumer patronage and risk perceptions in Internet shopping. Journal of Business research, 56(11), 867-875.
12. Grewal, D., Gotlieb, J., & Marmorstein, H. (1994). The moderating effects of message framing and source credibility on the price-perceived risk relationship. Journal of Consumer Research, 21(1), 145-153.
13. Hoh, P. Y., Loo, S. J., Tan, G. W. H., Lee, V. H., Aw, E. C. X., Cham, T. H., & Ooi, K. B. (2022). Understanding Valences in Mobile Grocery Shopping: Do Consumers’ Characteristics Matter?. Journal of Computer Information Systems, 1-14.
14. Hu, H. H., Kandampully, J., & Juwaheer, T. D. (2009). Relationships and impacts of service quality, perceived value, customer satisfaction, and image: an empirical study. The Service İndustries Journal, 29(2), 111-125.
15. Islam, M. S. (2010). The analysis of customer loyalty in Bangladeshi mobile phone industry. World Journal of Management, 2(2), 130-145.
16. Kerin, R. A., Jain, A., & Howard, D. J. (1992). Store shopping experience and consumer price-quality-value perceptions. Journal of Retailing, 68(4), 376.
17. Kim, Y., & Lee, J. (2000). Relationship between corporate image and customer loyalty in mobile communications service markets. Africa Journal of Business Management, 4(18), 4035-4041.
18. Kotler, P., & Armstrong, K. (2010). Principles of marketing: Global edition. New Jersey, Upper Saddle River: Pearson Prentice Hall.
19. Kuo, Y. F., Wu, C. M., & Deng, W. J. (2009). The relationships among service quality, perceived value, customer satisfaction, and post-purchase intention in mobile value-added services. Computers in Human Behavior, 25(4), 887-896.
20. Murillo-Zegarra, M., Ruiz-Mafe, C., & Sanz-Blas, S. (2020). The effects of mobile advertising alerts and perceived value on continuance intention for branded mobile apps. Sustainability, 12(17), 6753.
21. Murphy, P. E., & Enis, B. M. (1986). Classifying products strategically. Journal of Marketing, 50(3), 24-42.
22. Nguyen, N., & LeBlanc, G. (1998). The mediating role of corporate image on customers’ retention decisions: An Investigation in Financial Services. International Journal of Bank Marketing, 16(2), 52–65.
23. Pantano, E., & Priporas, C. V. (2016). The Effect of Mobile retailing on consumers' purchasing experiences: A dynamic perspective. Computers in Human Behavior, 61, 548-555.
24. Schiffman, L.G. and Kanuk, L.L. (2004). Consumer Behavior, 8th edition, Upper Saddle River, New Jersey: Pearson Education, Inc.
25. Sirdeshmukh, D., Singh, J., & Sabol, B. (2002). Consumer trust, value, and loyalty in relational exchanges. Journal of Marketing, 66(1), 15-37.
26. Snoj, B., Korda, A. P., & Mumel, D. (2004). The relationships among perceived quality, perceived risk and perceived product value. Journal of Product & Brand Management, 13, 156-167.
27. Statista, (2022). Forecast of the smartphone user penetration rate in Turkey from 2018 to 2024. https://www.statista.com/statistics/568281/predicted-smartphone-user-penetration-rate-in-turkey/
28. Tabachnick, B. G. & Fidell, L. S. (2013). Using Multivariate Statistics. Amerika Birleşik Devletleri, Pearson.
29. Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176.
30. Wang, Y., Lo, H. P., & Yang, Y. (2004). An integrated framework for service quality, customer value, satisfaction: Evidence from China’s telecommunication industry. Information Systems Frontiers, 6(4), 325–340.
31. Yang, H., Yu, J., Zo, H., & Choi, M. (2016). User acceptance of wearable devices: An extended perspective of perceived value. Telematics and Informatics, 33(2), 256-269.
32. 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.