Vol. 14 No. 2 (2026): Business & Management Studies: An International Journal
Articles

The mediating role of anticipated satisfaction in the relationship between functional value and purchase intention

PDF
  • Nazlı Tığlı,
  • Reha Saydan
Nazlı Tığlı
Lecturer Dr., Van Yuzuncu Yil University, Van, Türkiye
Reha Saydan
Prof. Dr., Van Yuzuncu Yil University, Van, Türkiye

Published 2026-06-25

Keywords

  • Functional Value, Anticipated Satisfaction, Purchase Intention
  • İşlevsel Değer, Beklenen Memnuniyet, Satın Alma Niyeti

How to Cite

The mediating role of anticipated satisfaction in the relationship between functional value and purchase intention. (2026). Business & Management Studies: An International Journal, 14(2), 1017-1028. https://doi.org/10.15295/bmij.v14i2.2780

Copyright (c) 2026 Nazlı Tığlı- Reha Saydan

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite

The mediating role of anticipated satisfaction in the relationship between functional value and purchase intention. (2026). Business & Management Studies: An International Journal, 14(2), 1017-1028. https://doi.org/10.15295/bmij.v14i2.2780

Abstract

This study examines the psychological mechanisms underlying purchase intention for cleaning robots, which are rapidly gaining importance in the smart home technology market. The main objective of the study is to empirically test the central mediating role of anticipated satisfaction in the effect of perceived functional value on purchase intention. Data for this study, focusing on cleaning robots, were collected from 276 female participants through face-to-face surveys. Jamovi and SPSS were used for the analysis. The study supports the value-satisfaction relationship in marketing theory by showing that perceived functional value influences purchase intention not only directly but also indirectly through anticipated satisfaction. Furthermore, these findings will guide smart device manufacturers in developing marketing strategies that align with potential users' expectations and in optimising their product design processes.

PDF

References

  1. An, D., Ji, S., & Jan, I. U. (2021). Investigating the determinants and barriers of purchase intention of innovative new products. Sustainability, 13(2), 740. doi:10.3390/su13020740
  2. Avcı, İ., Koçan, M., & Kırmızıbiber, A. (2024). Evaluation of consumers' use of smart robotic vacuum cleaners under extended expectation-confirmation model. Market-Tržište, 36(1), 25-42. doi:10.22598/mt.2024.36.1.25
  3. Bagozzi, R. P., Yi, Y. ve Phillips, L. W. (1991). "Assessing Construct Validity in Organisational Research", Administrative Science Quarterly, 36(3), s. 421–458.
  4. Balasubramanian, S., Karrh, J. A., & Patwardhan, H. (2006). Audience response to product placements: An integrative framework and future research agenda. Journal of Advertising, 35(3), 115-141. doi:10.2753/JOA0091-3367350308
  5. Berg, A. (1994). A gendered technology? From automated to cognitive home appliances. In C. Cockburn & R. Furst-Dilic (Eds.), Bringing technology home: Gender and technology in a changing Europe (pp. 94-113). Buckingham: Open University Press.
  6. Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351–370. doi:10.2307/3250921
  7. Bilici, F. (2025). Tüketicilerin akıllı robot süpürgeleri kullanma niyeti üzerinde iyimserlik ve yenilikçiliğin rolü. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 25(1), 243-270. doi:10.18037/ausbd.1567807
  8. Bilici, F., & İnam, S. (2024). Tüketicilerin akıllı robot süpürgelere yönelik tutum ve robot süpürgeleri kullanma niyeti üzerine bir araştırma. Uluslararası Yönetim İktisat ve İşletme Dergisi, 20(3), 552-586. doi:10.17130/ijmeb.1364854
  9. Bilici, F., & Özdemir, E. (2019). Tüketicilerin artırılmış gerçeklik teknolojilerini kullanmaya yönelik tutum ve niyeti üzerine bir araştırma. Business & Management Studies: An International Journal, 7(5), 2011-2033. doi:10.15295/bmij.v7i5.1252
  10. Coelho, P. S., Bairrada, C. M., & de Matos Coelho, A. F. (2020). The role of brand personality and brand experience in the relationship between brand equity and functional value. Journal of Brand Management, 27(4), 384-399. doi:10.1057/s41262-020-00188-7
  11. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. doi:10.2307/249008
  12. Delgado-Ballester, E., & Fernandez-Sabiote, E. (2015). Brand experimental value versus brand functional value: Which matters more for the brand? European Journal of Marketing, 49(11/12), 1857-1879. doi:10.1108/EJM-02-2014-0129
  13. Demirgüneş, K. S. (2015). Algılanan değerin satın alma niyeti üzerine etkisi ve müşteri memnuniyetinin aracı rolü: Küresel markalı temizlik ürünleri üzerine bir uygulama. İşletme ve Ekonomi Araştırmaları Dergisi, 6(1), 125-143.
  14. Doszhan, R., Zhanibekova, G., Baimukhanova, S., & Shaikh, A. A. (2026). Sustainable financial technologies. European Research on Management and Business Economics, 32, 100315. doi:10.1016/j.iedeen.2026.100315
  15. Durmuş, B., Yurtkoru, E. S., & Çinko, M. (2016). Sosyal bilimlerde SPSS’le veri analizi (6. baskı). Beta Basım Yayım Dağıtım.
  16. Dülek, B., Koçak, H., & Yaşar, M. E. (2025). Analysing perceptions towards smart home devices through the UTAUT model: A study on robot vacuum users. Bingöl Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 30, 483-495. doi:10.29029/busbed.1689400
  17. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behaviour: An introduction to theory and research. Reading, MA: Addison-Wesley.
  18. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. doi:10.2307/3151312
  19. Fuller, C. M., Simmering, M. J., Atinc, G., Atinc, Y., & Babin, B. J. (2016). Common methods variance detection in business research. Journal of Business Research, 69(8), 3192-3198. doi:10.1016/j.jbusres.2016.03.004
  20. George, D., & Mallery, P. (2010). SPSS for Windows step by step: A simple guide and reference (10th ed., 17.0 update). Pearson.
  21. Granzin, K. L., & Schjelderup, K. H. (2001). Situation as an influence on anticipated satisfaction. Advances in Consumer Research, 28, 237-238.
  22. Hair, J. F., Jr., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate data analysis (Seventh Edition). Upper Saddle River, NJ: Pearson Prentice Hall.
  23. Hu, L. T. ve 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), s. 1–55. doi:10.1080/10705519909540118
  24. Kass, R. A., & Tinsley, H. E. (1979). Factor analysis of usage patterns. Applied Psychological Measurement, 3(1), 120-138. doi:10.1177/014662167900300111
  25. Kim, H. W., Chan, H. C., & Gupta, S. (2007). Value-based adoption of mobile internet: An empirical investigation. Decision Support Systems, 43(1), 111-126. doi:10.1016/j.dss.2005.05.009
  26. Krishnamurthy, A., & Kumar, S. R. (2015). Exploring the formation of consumer expectations. Journal of Customer Behaviour, 14(1), 7–31. doi:10.1362/147539215X14302333552807
  27. Li, J., Cowan, K., Yazdanparast, A., & Ansell, J. (2024). Vibrotactile feedback in m-commerce: Stimulating perceived control and perceived ownership to increase anticipated satisfaction. Psychology & Marketing, 41(8), 1748–1768. doi:10.1002/mar.22008
  28. Loewenstein, G. (1987). Anticipation and the valuation of delayed consumption. The Economic Journal, 97(387), 666-684. doi:10.2307/2232929
  29. Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory third edition. mcgraw-hili. Inc, 1, 752.
  30. Pecotich, A., & Churchill Jr, G. A. (1981). An examination of the anticipated-satisfaction importance valence controversy. Organisational Behaviour and Human Performance, 27(2), 213–226. doi:10.1016/0030-5073(81)90022-4
  31. Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioural research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879-903. doi:10.1037/0021-9010.88.5.879
  32. Proynova, R. (2017). User satisfaction with information systems: A multi-perspective meta-analysis (doctoral thesis). Heidelberg University, Heidelberg.
  33. Rodríguez-Ardura, I., & Meseguer-Artola, A. (2020). Editorial: How to prevent, detect and control common method variance in electronic commerce research. Journal of Theoretical and Applied Electronic Commerce Research, 15(2), i-v
  34. Shiv, B., & Huber, J. (2000). The impact of anticipating satisfaction on consumer choice. Journal of Consumer Research, 27(2), 202–216. doi:10.1086/314320
  35. Sivo, S. A., Saunders, C., Chang, Q., & Jiang, J. J. (2006). How low should you go? Low response rates and the validity of inference in IS questionnaire research. Journal of the Association for Information Systems, 7(6), 351-414. doi:10.17705/1jais.00093
  36. Söderlund, M. (2003). The retrospective and the prospective mind and the after‐effects of product consumption. European Journal of Marketing, 37(10), 1430-1451. doi:10.1108/03090560310487194
  37. Strengers, Y., Gram-Hanssen, K., Dahlgren, K., & Aagaard, L. K. (2022). Energy, emerging technologies and gender in homes. Buildings and Cities, 3(1), 842–853. doi:10.5334/bc.273
  38. Tor-Kadıoğlu, C. (2020). Tüketicilerin akıllı robot süpürge kullanımı üzerine bir araştırma. Üçüncü Sektör Sosyal Ekonomi Dergisi, 55(4), 2515–2537. doi:10.15659/3.sektor-sosyal-ekonomi.20.11.1450
  39. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. doi:10.2307/30036540
  40. Vroom, V. H. (1964). Work and motivation. New York, NY: Wiley.
  41. Wang, E. S. T. (2010). The moderating role of customer perceived value on online shopping behaviour. Online Information Review, 35(3), 333–359. doi:10.1108/14684521111151414
  42. Wells, W., & Tan, C. S. L. (2024). Factors influencing consumer acceptance of high-tech products. Journal of Asia Business Studies, 18(3), 593–608. doi:10.1108/JABS-01-2023-0007
  43. Wilson VanVoorhis, C. R., & Morgan, B. L. (2007). Understanding power and rules of thumb for determining sample sizes. Tutorial in Quantitative Methods for Psychology, 3(2), 43–50.
  44. Wu, L. H., Wu, L. C., & Chang, S. C. (2016). Exploring consumers' intention to accept smartwatch. Computers in Human Behaviour, 64, 383–392. doi:10.1016/j.chb.2015.11.013
  45. Yaşlıoğlu, M. M. (2017). Sosyal bilimlerde faktör analizi ve geçerlilik: Keşfedici ve doğrulayıcı faktör analizlerinin kullanımı. İstanbul Üniversitesi İşletme Fakültesi Dergisi, 46(Özel Sayı), 74-85.