International Conference on the Internet, Cyber Security and Information Systems最新文献_第4页

A Data-Driven Decision-Making Model for the Third-Party Logistics (3PL) Industry 第三方物流(3PL)行业的数据驱动决策模型

International Conference on the Internet, Cyber Security and Information Systems Pub Date : 2019-10-25 DOI: 10.29007/4v3j

F. Moyo, B. Scholtz, Mohammed Alhassan

{"title":"A Data-Driven Decision-Making Model for the Third-Party Logistics (3PL) Industry","authors":"F. Moyo, B. Scholtz, Mohammed Alhassan","doi":"10.29007/4v3j","DOIUrl":"https://doi.org/10.29007/4v3j","url":null,"abstract":"The evolution of the supply chain has resulted in a growth in the usage of technology and data generated and distributed within the industry. Third-party logistics (3PL) companies operating within the supply chain industry are not maximising the capabilities of data to make wellinformed decisions. The purpose of this paper is to address this gap and to develop a prescriptive, theoretical model for data-driven decision-making (DDDM). To address the gap, a literature review of DDDM in 3PL industry and in other contexts was conducted. The proposed model is built based on the consideration of existing DDDM models and frameworks; data and data analytics principles to collect, store, manage and analyse data; and the Cynefin framework. Existing models and frameworks for DDDM do not provide explicit guidelines on how to apply DDDM in a 3PL and supply chain context. The proposed DDDM model constitutes of three phases, namely: (1) the setup phase, that considers data knowledge and decision-making knowledge; (2) execution phase; and (3) the learning phase. The application of the model in 3PL companies can support the decisionmaking process in these companies, with a consideration of the challenges and opportunities that exist in the supply chain. The decision-makers in 3PLs can thus make better-informed decisions that positively impact their enterprises and the supply chain.","PeriodicalId":383192,"journal":{"name":"International Conference on the Internet, Cyber Security and Information Systems","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132753684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Industry 4.0 Businesses Environments: Fostering Cyber Security Culture in a Culturally Diverse workplace 工业4.0商业环境:在多元文化的工作场所培育网络安全文化

International Conference on the Internet, Cyber Security and Information Systems Pub Date : 2019-10-25 DOI: 10.29007/r64x

Tapiwa Gundu, Mark Maronga, D. Boucher

引用次数: 1

Artificial Intelligence Affordances for Business Innovation: A Systematic Review of Literature 商业创新的人工智能支持:文献系统综述

International Conference on the Internet, Cyber Security and Information Systems Pub Date : 2019-10-25 DOI: 10.29007/jj72

Luqman Achmat, I. Brown

{"title":"Artificial Intelligence Affordances for Business Innovation: A Systematic Review of Literature","authors":"Luqman Achmat, I. Brown","doi":"10.29007/jj72","DOIUrl":"https://doi.org/10.29007/jj72","url":null,"abstract":"Emerging technologies like artificial intelligence (AI) have begun to play an evermore important role in business innovation. The purpose of this paper is to review current literature to identify definitions and concepts related to artificial intelligence affordances and how artificial intelligence affords business innovation. Using a systematic six-step literature review methodology conducted with an iterative disposition, seven major affordances of AI for business innovation were identified, i.e. (i) Automate business processes, (ii) Customise end user interaction, (iii) Proactively anticipate and react to changes, (iv) Augment and upskill the workforce, (v) Assist decision making, (vi) Improve risk management, and (vii) Develop and enhance intellectual property. The literature surveyed furthermore shows that there are several gaps which allow for further research. Firstly, the definition of artificial intelligence is inconsistent and there is no widely accepted definition. Several AI-based technologies and applications being developed (e.g. Machine Learning, Deep Learning, Natural Language Processing and Neural Networks) require a clear understanding of the affordances of such technologies to be able to make informed strategic decisions. Therefore, understanding the affordances of artificial intelligence in general plays an important role in making such decisions.","PeriodicalId":383192,"journal":{"name":"International Conference on the Internet, Cyber Security and Information Systems","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124560401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Adoption of Business Intelligence in the South African public social sector Department 商业智能在南非公共社会部门的应用

International Conference on the Internet, Cyber Security and Information Systems Pub Date : 2019-10-25 DOI: 10.29007/kqhq

Hosiah Masha, T. Adeyelure, Osden Jokonya

{"title":"Adoption of Business Intelligence in the South African public social sector Department","authors":"Hosiah Masha, T. Adeyelure, Osden Jokonya","doi":"10.29007/kqhq","DOIUrl":"https://doi.org/10.29007/kqhq","url":null,"abstract":"Social Sector department is expected to transform socio economic stands of the poor through technology by digitising service delivery processes in order to enhance decision making, however this has created lot of silo systems with large volumes of data to be manipulated and used. Business Intelligence is seen as supporting technology required to deal with the problem but the sector does not have a model or a framework to adopt the technology. Hence this study intended to develop a model for adoption of Business Intelligence in the South African public social sector Department. Two theoretical frameworks that is Implementation Effectiveness Theoretical Model and Technology Organisation Environment were employed to guide the study by following quantitative method. A survey was used to collect data at government department by means of closed-ended questionnaires, through simple random sampling to produce the results. To measure the relationship between dependent and independent variables data was coded into Statistical Package for Social Science (SPSS) tool for correlations analysis, then conducted regression analysis for constructs contributions. The results show that only three out of the six identified constructs from the research model were accepted to formulate the adoption model. Most previous work done in adoption of BI in public sector has focussed on broader public domain which creates a huge gap in addressing specific requirements or factors influencing adoption of BI in a particular sector. To reduce vagueness and complexity this study investigated factors influencing adoption of BI in South African public social sector Department","PeriodicalId":383192,"journal":{"name":"International Conference on the Internet, Cyber Security and Information Systems","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126960100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0