人气
心理学
款待
价值(数学)
结构方程建模
验证性因素分析
独创性
感知
酒店业
人口
营销
社会心理学
旅游
业务
社会学
统计
机器学习
人口学
神经科学
法学
计算机科学
数学
服务(商务)
政治学
创造力
作者
Juhee Kang,David J. Kwun,Jeeyeon Jeannie Hahm
出处
期刊:International Journal of Contemporary Hospitality Management
[Emerald (MCB UP)]
日期:2022-06-02
卷期号:34 (11): 4266-4287
被引量:6
标识
DOI:10.1108/ijchm-10-2021-1231
摘要
Purpose The goal of this paper is to investigate the relationships between consumers’ value perceptions, satisfaction and involvement, and, ultimately, their effects on behavioral intentions in the contexts of alternative golf (AG) and traditional golf (TG). Design/methodology/approach Data were collected from potential golfers who had visited AG facilities in the past 12 months. Data were analyzed using confirmatory factor analysis and structural equation modeling. Findings The findings of this study indicated that perceived value is a key element of developing satisfaction and promoting involvement, which resulted in visitors’ behavioral intentions toward AG and TG. In addition, satisfaction and involvement were found to sequentially mediate these relationships, and gender had a moderating effect on the relationship between AG and TG behavioral intentions. Practical implications This study theoretically contributes to the literature by proposing an extensive research model that attempted to capture the connection between AG and TG intentions and the sequential mediating effects of satisfaction and involvement. The strong connection between AG and TG found in this study suggest practical implications for managers, marketers and sales personnel for both AG and TG. Originality/value AG is defined as a non-traditional way to play golf that focuses more on entertainment and leisure activities. AG facilities are highly experiential spaces that include both golf and hospitality elements. The popularity of AG has increased in recent years with mostly anecdotal evidence of its influence on TG. This study empirically tested the role of AG in increasing the TG population.
科研通智能强力驱动
Strongly Powered by AbleSci AI