Establishment of an experience value model

Purpose – Previous research is mainly devoted to value connotations obtained from the physical environment, rather than the effect on experience value from the perspective of customers' self‐efficacies and involvement. This paper attempts to combine multivariate statistical analysis and nonlinear fuzzy neural network model for data analysis. Design/methodology/approach – Convenience sampling was adopted to investigate the employees from dozens of hi‐tech enterprises in the Hsinchu science‐based Industrial Park and Tainan Science‐based Industrial Park. Findings – Customers' involvement levels have a positive effect on experience value; customers' positive moods have stronger positive effect than negative moods; customers' experience value may vary due to different environmental atmospheres and self‐efficacies. Research limitations/implications – The investigation for the employees of a hi‐tech industry may deduce different implications due to various parent samples or sampling errors. So, subsequent research may perform a comparison of different regions or industries. Only 179 out of 500 samples are collected in this research. The relatively low‐recovery rate is attributed to the inclusions of numerous items in the questionnaire. This paper discusses transversely the predisposing influential factors of experience value. Practical implications – The empirical results show that the fuzzy neural network model could measure the relationship of variables more accurately and also eliminate the existing restrictions, making it suitable for social science sectors such as business management. Originality/value – Previous researches highlight the experience value of playfulness in the tourism industry, but little attention has been paid to the combination of education and playfulness along with self‐efficacy.