Development of The Attitude Scale Towards Online Food Orders

Online Yemek Siparişlerine Yönelik Tutum Ölçeğinin Geliştirilmesi

Abstract

Nowadays, with the rapid development of technology and the widespread use of the internet and smart communication devices, changes have begun to occur in people's daily lives. In this process, the concepts of speed, time and convenience have become priorities for consumers. The aim of businesses to offer the best to consumers in the fastest, easiest and most economical way has enabled the emergence of many innovations and the development of new applications in the field of food.

In this study, the factors that determine consumers' acceptance and usage behavior of "Online Food Ordering Applications", which has emerged as a new trend in recent years, were examined. In this context, it is aimed to develop an attitude scale towards online food ordering.  Within the scope of this study, an online survey was conducted for customers using these applications in Sivas Province. The explanatory factor analysis sample of the study consisted of 385 people, and the confirmatory factor analysis sample consisted of 210 people.

According to the factor analysis results, a 3-factor scale was obtained that affects consumers' preferences in ordering food online. These factors are named as perceived website quality, time saving and economy, considering the items they contain. These 3 factors explain 66.26% of the total variance of the scale. Likewise, fit index values ​​in confirmatory factor analysis: χ2/df = 1.408< 3; 0.85<GFI=0.929; 0.90<IFI =0.967; 0.95<CFI=0.967; RMSEA= 0.044 < 0.08 was obtained. In the internal consistency analysis, the Alpha coefficient of the factors and the scale was found to be between 0.721-0.861. According to the results obtained, it was concluded that the scale is a valid and reliable measurement tool.It was observed that the "perceived website quality" and "time saving" factors, which are thought to affect the attitudes of consumers who order food online, do not show a significant difference according to demographic data (gender, age, education, occupation, monthly income). In addition, it was concluded that the averages of the "affordability" factor showed a significant difference according to monthly income.