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Frank Labanca - One of the best experts on this subject based on the ideXlab platform.
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Online Dynamic Asynchronous Audit Strategy for Reflexivity in the Qualitative Paradigm
The Qualitative Report, 2014Co-Authors: Frank LabancaAbstract:The trustworthiness of a qualitative study can be increased by maintaining high credibility and objectivity. Of utmost importance to these factors is the reflexivity of the researcher. Standard journaling techniques are frequently used to maintain an Audit trail and document tentative interpretations of a study. One of the major limitations to paper-based reflexivity is the lack of regular Audit feedback. Online blogging tools can facilitate reflexivity and subsequent Auditing with ease. Blogs are potentially cost-free, and only a rudimentary understanding of a web browser and word processing program are necessary for effective use. Moreover, blogs provide a simple, contiguous interface for an effective Auditing process. An analysis of a reflexivity blog and subsequent Audits is examined here. Findings indicate that the multiple perspectives of the Auditors gave additional insights and that might not normally be considered by a researcher, providing a multi-arrayed perspective to interpretation of a study data set.
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online dynamic asynchronous Audit Strategy for reflexivity in the qualitative paradigm
The Qualitative Report, 2014Co-Authors: Frank LabancaAbstract:Qualitative research is based on the nature of ill-conceived problems: there is an open-endedness to the field of study (Kleinsasser, 2000). Since qualitative research focuses on interpretation and emerging design, there is no predetermined format for design and data collection (Merriam, 1998; Russell & Kelly, 2002; Stake, 1995). Depending on the nature of the research question, various models of study can be employed. For example, a case study might be appropriate for focused site-specific study on literacy strategies used in the classroom of a primary school teacher, while a phenomenological study might examine general practices that inhibit or enhance school effectiveness. Moreover, an ethnographic approach might be more relevant for a broader study of children's language development and use in different cultures. However, there are underlying methodological techniques that underpin the qualitative paradigm. Therefore it is critical for researchers to be mindful of trustworthiness when conducting a study. In order to maintain high trustworthiness in a qualitative study, Krefting (1991) suggested four criteria to ensure valid interpretation of data: truth value, applicability, consistency, and neutrality. In the qualitative approach, truth value is measured by credibility: having an adequate engagement in the research setting so recurrent patterns in data can be properly identified and verified. Applicability is established with transferability: allowing readers to be able to apply the findings of the study to their own situations. Transferability is different than generalizability, as a qualitative researcher is often unlikely to make blanket application of research findings to larger populations. Consistency in a study is enhanced by dependability: knowing that the patterns and themes that emerge from data are repeatable and replicable. Finally, neutrality ensures confirmability. This is not necessarily researcher objectivity but rather an external verification of findings. Since a qualitative researcher's perspective is naturally biased due to his or her close association with the data, sources, and methods, Audit strategies can be used to confirm findings (Bowen, 2009; Miller, 1997). It is critical that the researcher engage in robust and diverse strategies to Audit emerging data, both through self-reflective and external Audits (Rodgers & Cowles, 1993). Therefore, trustworthiness of (a) interpretations, and (b) findings are dependent on being able to demonstrate how they were reached (Mauthner & Doucet, 2003). One of the key tenets to trustworthy qualitative research is high quality reflexivity. Reflexivity, as defined by Schwandt (2001), is "the process of critical self-reflection on one's biases, theoretical predispositions, preferences," an acknowledgement that the "inquirer is part of the setting, context, and social phenomenon he or she seeks to understand ... and a means for critically inspecting the entire research process" (p. 224). Often taking the form of a handwritten journal, reflexivity is the opportunity for researchers to understand how their own experiences and understandings of phenomena affect the research process (Morrow, 2005). Reflexivity is connected to action and a part of the interpretive process in which participants and the researcher are engaged. Since knowledge does not correspond to an objective reality, but rather is socially constructed within the community of practice, reflexivity is intersubjective because it develops from the interaction between researchers and the sources and methods of data (Colombo, 2003). Therefore, trustworthiness increases when researchers delineate how findings reflect their own personal milieu (Hall & Callery, 2001). Reflexivity provides the rigor that makes data more transparent. Reflexivity encourages researchers to determine their positionality, identifying personal and theoretical commitments that can be critically examined and evaluated. …
Hennie Daniels - One of the best experts on this subject based on the ideXlab platform.
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CISIM - Uncovering Document Fraud in Maritime Freight Transport Based on Probabilistic Classification
Computer Information Systems and Industrial Management, 2015Co-Authors: Ron Triepels, Ad Feelders, Hennie DanielsAbstract:Deficient visibility in global supply chains causes significant risks for the customs brokerage practices of freight forwarders. One of the risks that freight forwarders face is that shipping documentation might contain document fraud and is used to declare a shipment. Traditional risk controls are ineffective in this regard since the creation of shipping documentation is uncontrollable by freight forwarders. In this paper, we propose a data mining approach that freight forwarders can use to detect document fraud from supply chain data. More specifically, we learn models that predict the presence of goods on an import declaration based on other declared goods and the trajectory of the shipment. Decision rules are used to produce miscoding alerts and smuggling alerts. Experimental tests show that our approach outperforms the traditional Audit Strategy in which random declarations are selected for further investigation.
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Uncovering Document Fraud in Maritime Freight Transport Based on Probabilistic Classification
2015Co-Authors: Ron Triepels, Ad Feelders, Hennie DanielsAbstract:Deficient visibility in global supply chains causes significant risks for the customs brokerage practices of freight forwarders. One of the risks that freight forwarders face is that shipping documentation might contain document fraud and is used to declare a shipment. Traditional risk controls are ineffective in this regard since the creation of shipping documentation is uncontrollable by freight forwarders. In this paper, we propose a data mining approach that freight forwarders can use to detect document fraud from supply chain data. More specifically, we learn models that predict the presence of goods on an import declaration based on other declared goods and the trajectory of the shipment. Decision rules are used to produce miscoding alerts and smuggling alerts. Experimental tests show that our approach outperforms the traditional Audit Strategy in which random declarations are selected for further investigation.
Leif Appelgren - One of the best experts on this subject based on the ideXlab platform.
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A survey of models for determining optimal Audit strategies
Advances in Accounting, 2020Co-Authors: Leif AppelgrenAbstract:Abstract The problem studied in this survey is how to optimize the allocation of Audit resources over an Auditee population with respect to available population statistics. The Auditees are assumed to optimize their expected utility based on information about the Audit Strategy. This survey is limited to models where the Auditee can vary the fraud amount along a continuous scale. If the Auditor is not able or willing to announce the Audit Strategy, a Nash equilibrium can be derived in which the Auditor and Auditee correctly anticipate each other's strategies. If the Auditor announces the Audit Strategy in advance, the problem is formulated as a sequential game with perfect information which is solved as an optimization problem. Early models in the literature resulted in unrealistically high degrees of fraud. Later models have incorporated a split into one group of inherently honest Auditees and another group of potentially dishonest Auditees. The fraction of inherently honest Auditees is exogenous. In this paper, the four combinations of non-announcing/pre-announcing the Strategy and all potentially dishonest/some inherently honest Auditees are studied. For the case of pre-announcing the Strategy with some inherently honest Auditees, two new solution methods are presented. Two main conclusions are as follows. First, models with some inherently honest Auditees have greater external validity. Second, when a pre-announced Strategy is feasible, as it often is with tax and benefit Audits, the pre-announced Strategy is preferred by the Auditor over the non-announced Strategy.
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Optimal Auditing of social benefit fraud: a case study
Empirical Economics, 2019Co-Authors: Leif AppelgrenAbstract:The aim of this paper is to study the effect of different Audit strategies on fraud in one particular social benefit system in Sweden. The efficiency of different Audit strategies is compared using a computer-based optimization algorithm. Two types of Audit strategies are used. One is to adapt the Audit intensity to the propensity for errors and fraud in different segments of the group studied. This type of Strategy is denoted segmentation Strategy. The second type of Audit Strategy is based on adaptation of behaviour through information. The model developed by Erard and Feinstein for tax Auditing is adapted for benefit fraud. In this model, the Audit intensity is controlled by a variable, and the Auditees are informed of the relationship between control variable and Audit intensity. The control variable used in this paper is the benefit amount claimed during a certain period. As the Audit intensity increases with the claim amount, the rational fraudster understands that reducing the amount of fraud decreases the risk of being Audited. This type of Strategy is denoted information Strategy . One main result is that the Erard and Feinstein model can be successfully adapted to benefit fraud. Using coarse estimates of Audit unit costs, the result of the study is that all persons should be Audited. For higher Audit costs, it is shown that the information Strategy is much more effective when compared to the segmentation Strategy.
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The Effect of Audit Strategy Information on Tax Compliance - An Empirical Study
2008Co-Authors: Leif AppelgrenAbstract:This paper deals with an experiment by the Swedish Tax Agency to test the effect of information to taxpayers regarding different Audit strategies . The experiment involved approximately 900 sole proprietors, divided into three groups, where one was informed that Audits would focus on taxpayers declaring the lowest income, i.e. according to a rational Audit Strategy. Another group was told that Audits would be made at random whereas the third was a control group. The effect of Strategy information was measured as the change in declared income between years. The principal finding was that declared income increased significantly more in the rational-Audit-Strategy group than in the control group.
Ron Triepels - One of the best experts on this subject based on the ideXlab platform.
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CISIM - Uncovering Document Fraud in Maritime Freight Transport Based on Probabilistic Classification
Computer Information Systems and Industrial Management, 2015Co-Authors: Ron Triepels, Ad Feelders, Hennie DanielsAbstract:Deficient visibility in global supply chains causes significant risks for the customs brokerage practices of freight forwarders. One of the risks that freight forwarders face is that shipping documentation might contain document fraud and is used to declare a shipment. Traditional risk controls are ineffective in this regard since the creation of shipping documentation is uncontrollable by freight forwarders. In this paper, we propose a data mining approach that freight forwarders can use to detect document fraud from supply chain data. More specifically, we learn models that predict the presence of goods on an import declaration based on other declared goods and the trajectory of the shipment. Decision rules are used to produce miscoding alerts and smuggling alerts. Experimental tests show that our approach outperforms the traditional Audit Strategy in which random declarations are selected for further investigation.
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Uncovering Document Fraud in Maritime Freight Transport Based on Probabilistic Classification
2015Co-Authors: Ron Triepels, Ad Feelders, Hennie DanielsAbstract:Deficient visibility in global supply chains causes significant risks for the customs brokerage practices of freight forwarders. One of the risks that freight forwarders face is that shipping documentation might contain document fraud and is used to declare a shipment. Traditional risk controls are ineffective in this regard since the creation of shipping documentation is uncontrollable by freight forwarders. In this paper, we propose a data mining approach that freight forwarders can use to detect document fraud from supply chain data. More specifically, we learn models that predict the presence of goods on an import declaration based on other declared goods and the trajectory of the shipment. Decision rules are used to produce miscoding alerts and smuggling alerts. Experimental tests show that our approach outperforms the traditional Audit Strategy in which random declarations are selected for further investigation.
Chung-long Kuo - One of the best experts on this subject based on the ideXlab platform.
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Using the artificial neural network to predict fraud litigation: Some empirical evidence from emerging markets
Expert Systems with Applications, 2009Co-Authors: Hsueh-ju Chen, Shaio Yan Huang, Chung-long KuoAbstract:Detecting corporate fraud and assessing the relative risk factors have been significant issues confronting the Auditing profession for decades. This study therefore aims to apply a neural network system to predict fraud litigation for assisting accountants on Audit Strategy making. The empirical results show that neural network provides not only a promising predicting accuracy, but also a better detecting power and a less misclassification cost comparing with that of a logit model and Auditor judgments. This suggests that an artificial intelligence technique is quite well in identifying a fraud-lawsuit presence, and hence could be a supportive tool for practitioners. Further, a remarkable finding related to the greater effects of management's capability on fraud commitments acquires an attentive investigation of ethic issues in emerging markets where contribute the most important force in the global economy nowadays.