在Covid-19时代,在大多数蓝色巴厘岛度假村,多任务处理在最大限度地提高员工效率方面的应用

None Gde Yudhie Adhitya Surya Pratama, None Ni Nyoman Triyuni, None I Wayan Basi Arjana, None Made Ruki, None Ni Wayan Wahyu Astuti
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引用次数: 0

摘要

目的:本研究旨在研究新冠肺炎疫情期间,在Most Blue Bali度假村,多任务处理对质量绩效的影响,以最大限度地提高员工效率。研究方法:本研究的样本量为30人,抽样方法为简单抽样。使用的数据分析方法是定量分析,使用效度和信度检验、经典假设检验、F检验、决定系数、t检验和多元回归分析。 结果与讨论:运用多元回归方法,可以得出多任务变量数量对顾客满意度有正向显著影响,显著性值(P值)为0.0030<0.05。年龄对顾客满意度的影响为正但不显著,显著值为0.727>0.05。任务完成方法对顾客满意度有正向但不显著的影响,显著性值(P值)为0.080>0.05。职位对顾客满意度的影响为正但不显著,显著性值(P值)为0.383>0.05。同时,多任务量、年龄、任务完成方式、职位对顾客满意度有显著影响,F值为11.217,显著性值(P值)为0.000<0.05。 含义:结果的决定系数为0.58,这意味着58%的质量绩效变量的变化是由多任务处理的数量、年龄、完成任务的方法和职位一起解释的,而剩下的52%是由本研究未包括的其他变量解释的。 & # x0D;关键词:多任务,质量绩效,影响,应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Application of Multitasking For Maximizing Staff Effectiveness During The Covid-19 Era at Most Blue Bali Resort
Purpose: This research was conducted to examine the effect of multitasking on quality performance for maximizing staff effectiveness during the Covid-19 era at Most Blue Bali Resort. Research methods: The sample used in this study amounted to 30 respondents—the sampling method used simple sampling. The data analysis method used is a quantitative analysis using validity and reliability tests, classical assumption test, F test, coefficient of determination, t-test, and multiple regression analysis. Results and discussion: Using the multiple regression method, it can be concluded that the amount of multitasking variable has a positive and significant effect on customer satisfaction with a significance value (P value) of 0.0030<0.05. Age has a positive but insignificant effect on customer satisfaction with a significance value (P value) of 0.727>0.05. The method of task completion has a positive but insignificant impact on customer satisfaction with a significance value (P value) of 0.080>0.05. The position has a positive but insignificant effect on customer satisfaction with a significance value (P value) of 0.383>0.05. Simultaneously, the amount of multitasking, age, method of task completion, and position has a significant effect on customer satisfaction with an F count of 11.217 with a significance figure (P value) of 0.000<0.05. Implication: The resulting coefficient of determination is 0.58, which means that 58 percent of changes in the quality performance variable are explained by the amount of multitasking, age, method of task completion, and position together, while the remaining 52 percent is explained by other variables not included in this research. Keywords: multitask, quality performance, influence, application.
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