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Developing an identity fraud measurement model: a factor analysis approach

机译:开发身份欺诈衡量模型:因素分析方法

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Purpose – Though many studies and reports have been published about the scale of identity fraud (IDF), no work has been done on developing models to measure IDF. The purpose of this paper is to propose a measurement model for IDF and test the validity of that measurement model. Design/methodology/approach – After providing a background on the concepts of IDF, the paper discusses the related term, identity theft. Next, a measurement model is developed, based on the current practice of measurement of IDF in four countries. Exploratory factor analysis (EFA) is used in identifying the indicators and factors of IDF. After the EFA is conducted, confirmatory factor analysis is employed to test the validity of the measurement model. These tests are conducted using the data collected from Canadian financial institutions. Findings – The review of the current empirical studies suggests that IDF should be assessed using a measurement model with 33 indicators to measure five factors of IDF. However, the analysis of Canadian financial institutions suggests that a measurement model that includes 27 indicators and four factors is most appropriate for the data. Research limitations/implications – The measurement model developed in the present paper is based on an examination of a sample of financial institutions in Canada. Hence, the results of this paper cannot be generalized to organizations in other sectors of the economy. Further studies in other sectors of the economy are required to identify industry-specific measurement model. Practical implications – This paper is the first approach toward developing a model for measuring IDF. Originality/value – This paper is the first study that attempts to scientifically identify and validate a measurement system in the area of IDF.
机译:目的–尽管已经发表了许多有关身份欺诈(IDF)规模的研究和报告,但仍未开展有关开发测量IDF的模型的工作。本文的目的是为IDF提出一个测量模型,并测试该测量模型的有效性。设计/方法/方法–在提供了IDF概念的背景知识之后,本文讨论了相关术语“身份盗用”。接下来,根据四个国家目前对IDF进行测量的实践,开发了一个测量模型。探索性因素分析(EFA)用于识别IDF的指标和因素。在进行全民教育之后,采用验证性因子分析来检验测量模型的有效性。这些测试是使用从加拿大金融机构收集的数据进行的。结果–对当前经验研究的回顾表明,应该使用具有33个指标的测量模型来评估IDF,以测量IDF的五个因素。但是,对加拿大金融机构的分析表明,包含27个指标和四个因素的衡量模型最适合该数据。研究的局限性/意义–本文开发的衡量模型基于对加拿大金融机构样本的考察。因此,本文的结果不能推广到其他经济部门的组织中。需要对经济的其他部门进行进一步研究,以识别特定于行业的度量模型。实际意义–本文是开发用于测量IDF模型的第一种方法。原创性/价值–本文是首次尝试在IDF领域中科学地识别和验证测量系统的研究。

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