修订数据收集方法--来自澳大利亚金融业的证据

Ben Neilson , Tom Marty , Nat Daley
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引用次数: 0

摘要

在提供财务咨询所需的总时间中,数据收集所需的时间占了很大一部分。本研究将数据收集软件应用于财务规划过程,旨在确定其优势,以帮助减少获取财务建议过程中不断增加的障碍。实验性研究分为两个阶段,在定量输入记录数据收集软件使用的影响之前,先围绕问题主题寻求定性输入。研究试图通过比较澳大利亚专业实践中的传统方法和软件方法,证明软件使用可能对数据收集要求产生的有益影响。受访者被要求使用传统方法和数字方法完成数据收集输入,并在整个过程中记录指标。112 名消费者和 71 名执业顾问提供的信息均被记录在案。结果表明,使用软件可以减少完成任务所需的时间,通常还能提高数据的准确性。而传统方法耗时较长,数据准确性较低。研究结果旨在改进金融行业的传统实践方法。本研究通过考察数据收集方法对减少澳大利亚金融服务获取障碍的潜在影响,为金融规划文献做出了原创性贡献。
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Revising data collection methodology - evidence from the Australian financial sector

Time requirements of data collection account for a significant portion of the total time required to provide financial advice. This research applies data collection software to the financial planning process seeking to identify benefits that may assist to reduce rising barriers of accessing financial advice. Experimental two-phase study seeks qualitative input surrounding problematic themes before quantitative input records impacts of data collection software use. The research seeks to evidence beneficial impacts that software use may have on the data collection requirements by way of comparison between traditional and software methodologies in Australian professional practice. Respondents were asked to complete data collection inputs using both traditional and digital methods with metrics recorded throughout the process. Input from 112 consumers and 71 practising advisers were recorded. Results suggest the use of software may decrease time taken to complete task and often results in higher levels of data accuracy. Traditional methods were affiliated with extended time periods and lower levels of data accuracy. Results aim to evolve methods of traditional practise within the financial sector. The research provides original contributions to financial planning literature by examining the potential impact data collection methodologies may have on reducing barriers to accessing financial services in Australia.

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来源期刊
Journal of Finance and Data Science
Journal of Finance and Data Science Mathematics-Statistics and Probability
CiteScore
3.90
自引率
0.00%
发文量
15
审稿时长
30 days
期刊最新文献
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