新冠肺炎期间,产品创新和价格对halodoc健康应用服务客户满意度的影响(2021年万隆halodoc应用用户调查)

Deden Tarmidi, S. Mardhatillah, F. Masripah, D. Febriyanto, T. Pribadi
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引用次数: 3

摘要

本研究旨在了解产品创新(X1)和价格(X2)对Halodoc在万隆应用的客户满意度(Y)的影响程度。本研究中使用的方法是一种定量方法,对万隆Halodoc应用程序用户的100名受访者使用SPSS25 Windows软件进行多元回归分析计算。该研究的主要数据使用问卷调查,次要数据通过期刊出版物、文章和理论书籍获得。研究结果表明,变量产品创新(X1)和价格(X2)共同对变量客户满意度(Y)产生显著影响。这些结果向研究人员表明,万隆的halodoc应用用户在评估使用产品创新和价格等产品的满意度时考虑了这一观点。©2021卡拉德尼兹工业大学。保留所有权利。
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The influence of product innovation and price on customer satisfaction in halodoc health application services during COVID-19 (Survey of HaloDoc app users in Bandung in 2021)
This research was conducted to find out how much influence product innovation (X1) and Price (X2) on Customer Satisfaction (Y) on Halodoc application in Bandung. The method used in this study is a quantitative method with 100 respondents of Halodoc application users in Bandung with multiple regression analysis calculations processed in SPSS25 Windows software. The main data from the study used questionnaire surveys, and secondary data was obtained through journal publications, articles, and theory books. According to the results of this study shows that the variable Product Innovation (X1) and Price (X2) has a significant influence together on the variable Customer Satisfaction (Y). These results showed the researchers that halodoc application users in Bandung considered the perspective when assessing satisfaction in using a product such as Product Innovation and Price offered. © 2021 Karadeniz Technical University. All rights reserved.
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The Existence of Characters on relations between certain intrinsic topologies in certain partially ordered sets A new approach on some operator theory in certain semi-inner-product space The influence of product innovation and price on customer satisfaction in halodoc health application services during COVID-19 (Survey of HaloDoc app users in Bandung in 2021) The technology of mobile banking and its impact on the financial growth during the Covid-19 pandemic in the Gulf region Classification of COVID-19 from chest X-ray images using a deep convolutional neural network
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