{"title":"A framework for cloud computing use to enhance job productivity","authors":"Sek-Kit Teh, S. Ho, Gaik-Yee Chan, C. Tan","doi":"10.1109/ISCAIE.2016.7575040","DOIUrl":null,"url":null,"abstract":"Increasing effectiveness and efficiency in job productivity is one of the most critical goals for businesses because a productive labor force is crucial in reducing the budget impact in business costs and in boosting job creation. While Cloud computing is an important technological development in this generation, its effect on job productivity is unclear. Cloud computing may promise lower cost and the capability to quickly scale resources up or down as workloads demanded, thus leading organizations in both the public and private sectors to consider shifting their applications and data to the Cloud. Although Cloud computing provides many advantages but barriers of Cloud usage such as security breaches, incompatibility with existing applications and unreliability of Cloud service reduce job productivity. This research hence aims to propose a framework on demography, Cloud characteristics and learning styles for Cloud computing usage, documentation and productivity. This research uses a systematic and methodological plan to coordinate research for optimum resource allocation. The intended population where data will be collected under this study will be 500 Cloud service users in a local region in Malaysia.","PeriodicalId":412517,"journal":{"name":"2016 IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCAIE.2016.7575040","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Increasing effectiveness and efficiency in job productivity is one of the most critical goals for businesses because a productive labor force is crucial in reducing the budget impact in business costs and in boosting job creation. While Cloud computing is an important technological development in this generation, its effect on job productivity is unclear. Cloud computing may promise lower cost and the capability to quickly scale resources up or down as workloads demanded, thus leading organizations in both the public and private sectors to consider shifting their applications and data to the Cloud. Although Cloud computing provides many advantages but barriers of Cloud usage such as security breaches, incompatibility with existing applications and unreliability of Cloud service reduce job productivity. This research hence aims to propose a framework on demography, Cloud characteristics and learning styles for Cloud computing usage, documentation and productivity. This research uses a systematic and methodological plan to coordinate research for optimum resource allocation. The intended population where data will be collected under this study will be 500 Cloud service users in a local region in Malaysia.