基于用户日志的互联网服务满意度研究

M. Ojebode, B. I. Akhigbe
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引用次数: 0

摘要

我们目前正处于数字时代的风口浪尖,人们不断地使用互联网服务(Int-Sevs)进行各种目的,如学习、教学和研究。然而,缺乏对用户满意度的充分了解仍然对Int-Sevs适应用户的动态需求和在大学范围内实时提供所需服务构成巨大挑战。这种认识是必要的,以了解是什么影响了一所大学的绩效。因此,本文分析了一所大学互联网服务的120个用户在三个月内收集的约65000个日志项的用户日志。采用混合方法。因此,两步聚类和交叉稳定技术被应用于识别自然分组,并检查它们的现有关系(分别),以确定用户满意度的存在。结果显示,用户满意度与关键绩效指标(kpi)之间存在显著的关联和关系。该研究的结论是,通过数据和有效的技术,可以调查以用户满意度为中心的kpi,以找出影响大学IntSevs表现的因素。用户体验的质量被忽略,留待将来在一项可想象的纵向研究中考虑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Users’ Satisfaction with Internet Service Performance-Based on User Log
We are currently on the cusp of a digital era when people engage Internet services (Int-Sevs) ceaselessly for sundry purposes such as learning, teaching, and research. However, the lack of sufficient understanding of user satisfaction still poses a huge challenge to Int-Sevs adaption to users’ dynamic needs and the provision of required services in real-time within the university’s context. This understanding is needful concerning what influences the performance of the Int-Sevs of a university. This paper, therefore, analyses the user log of about 65000 log items generated by 120 users of a university’s internet services that were collected over three months. The mixed-method approach was adopted. Thus, the two-step clustering and crosstabulation techniques were applied to identify natural groupings and examine them for existing relationships (respectively) to determine the existence of user satisfaction. The results showed a significant association and relationship between user satisfaction and Key Performance Indicators (KPIs). The study concluded that with data and efficient techniques, KPIs with user-centric criteria like user satisfaction could be investigated to find what influences the performance of a university’s IntSevs. The quality of users’ experience was omitted and left to be considered in the future in a conceivably longitudinal study.
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