Cloud Communications During the Pandemic From the Perspective of Collaboration Platforms

Author:

Kubacz-Szumska JoannaORCID, ,Szumski OskarORCID,

Abstract

Purpose: The aim of this research is focused on the identification of communication patterns prior and after COVID-19 was announced and the approach to the choices that end users make in various aspects of life. Design/methodology/approach: The authors decided to execute two-step research including practical use of 4 popular collaboration platforms: Microsoft Teams, Zoom, Jitsi, Google Meet, based on the proved user experience. After a defined focus group of respondents gathered hands-on experience in a controlled manner, using the defined communication platforms, further research was carried out in the form of a survey to assess the change of behavior of respondents, considering IT tools used to support distance learning and collaboration. The research included a comparison of behavior prior the epidemic and during the epidemic period. The research covered the following aspects: how the behavior patterns of UCC use have changed across the identified areas (business, educational, private) and what are the most preferred toolsets. The following structure was applied: a short introduction to the communication platforms, definition of the research method, analysis, and discussion of the identified results. Findings: The conducted survey identified the following elements: the level of digital communication among respondents and the familiarity with different platforms have a significant role in the use and development of UCC platforms. The generic conclusion of the research was that almost all respondents have prior experience using UCC platforms. The survey has proved the 100% use of UCC cross various areas of life. Based on the research, it has been noticed that respondents tend to use one or two UCC platforms as a standard for business and private use. UCC platforms that are more widely used across different areas of life are rated as the most preferred by the respondents and include Microsoft Teams (30%) and Google Meet (23%). Research limitations/implications: The usage of non-probabilistic sampling, a relatively small sample and the usage of qualitative analysis methods were major limitations of the conducted research. Firstly, the research data was collected from students of one specialty, from one specific university. The research did not find any cultural differences in distance learning and communication. Secondly, the study uses basic statistical measures without cross analysis to enable a deeper analysis of the research. Originality/value: The presented paper is a part of the research area related to communication platforms across various areas of peoples’ life. The research was aimed at the identification of the most preferable UCC platforms and features that serve the communication purpose. The cognitive value of the paper might also be seen in the focus on a relatively narrow and homogenous group of respondents (students of e-business and digital marketing).

Publisher

University of Warsaw

Subject

Pharmacology (medical)

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Data science for job market analysis: A survey on applications and techniques;Expert Systems with Applications;2024-10

2. Embracing Unified Communication and Collaboration: Business and Technological Trends;2024 9th International Conference on Smart and Sustainable Technologies (SpliTech);2024-06-25

3. Usability of Chat and Forum Discussion Tools in Higher Education;Proceedings of the 35th Australian Computer-Human Interaction Conference;2023-12-02

4. Multi-Party Secured Collaboration Architecture from Cloud to Edge;Journal of Computer Information Systems;2023-08-31

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3