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- Auditing (4)
- NeuroIS (4)
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- Human capital (2)
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- Choice-based samples (1)
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Articles 1 - 20 of 20
Full-Text Articles in Management Information Systems
From Warning To Wallpaper: Why The Brain Habituates To Security Warnings, Bonnie Anderson, Anthony Vance, C. Brock Kirwan, Jeffrey L. Jenkins, David Eargle
From Warning To Wallpaper: Why The Brain Habituates To Security Warnings, Bonnie Anderson, Anthony Vance, C. Brock Kirwan, Jeffrey L. Jenkins, David Eargle
Faculty Publications
Warning messages are fundamental to users' security interactions. Unfortunately, research has shown that they are largely ineffective. A key contributor to this failure is habituation: decreased response to a repeated warning. Previous research has inferred the occurrence of habituation to warnings or measured it indirectly, such as through the proxy of a related behavior. Therefore, there is a gap in our understanding of how habituation to security warnings develops in the brain. Without direct measures of habituation, we are limited in designing warnings that can mitigate its effects. In this study, we use neurophysiological measures to directly observe habituation as …
More Harm Than Good? How Messages That Interrupt Can Make Us Vulnerable, Jeffrey L. Jenkins, Bonnie Anderson, Anthony Vance, C. Brock Kirwan, David Eargle
More Harm Than Good? How Messages That Interrupt Can Make Us Vulnerable, Jeffrey L. Jenkins, Bonnie Anderson, Anthony Vance, C. Brock Kirwan, David Eargle
Faculty Publications
System-generated alerts are ubiquitous in personal computing and, with the proliferation of mobile devices, daily activity. While these interruptions provide timely information, research shows they come at a high cost in terms of increased stress and decreased productivity. This is due to dual-task interference (DTI), a cognitive limitation in which even simple tasks cannot be simultaneously performed without significant performance loss. Although previous research has examined how DTI impacts the performance of a primary task (the task that was interrupted), no research has examined the effect of DTI on the interrupting task. This is an important gap because in many …
How Users Perceive And Respond To Security Messages: A Neurois Research Agenda And Empirical Study, Bonnie Anderson, Anthony Vance, C. Brock Kirwan, David Eargle, Jeffrey Jenkins
How Users Perceive And Respond To Security Messages: A Neurois Research Agenda And Empirical Study, Bonnie Anderson, Anthony Vance, C. Brock Kirwan, David Eargle, Jeffrey Jenkins
Faculty Publications
Users are vital to the information security of organizations. In spite of technical safeguards, users make many critical security decisions. An example is users' responses to security messages—discrete communication designed to persuade users to either impair or improve their security status. Research shows that although users are highly susceptible to malicious messages (e.g., phishing attacks), they are highly resistant to protective messages such as security warnings. Research is therefore needed to better understand how users perceive and respond to security messages. In this article, we argue for the potential of NeuroIS—cognitive neuroscience applied to information system (IS)—to shed new light …
Pipes, Pools And Filters: How Collaboration Networks Affect Innovative Performance, Harpeet Singh, David Kryscynski, Xinxin Li, Ram Gopal
Pipes, Pools And Filters: How Collaboration Networks Affect Innovative Performance, Harpeet Singh, David Kryscynski, Xinxin Li, Ram Gopal
Faculty Publications
Innovation requires inventors to have both "new knowledge" and the ability to combine and configure knowledge (i.e. "combinatory knowledge") and such knowledge may flow through networks. We argue that both combinatory knowledge and new knowledge are accessed through collaboration networks, but that inventors' abilities to access such knowledge depends on its location in the network. Combinatory knowledge transfers from direct contacts, but not easily from indirect contacts. In contrast, new knowledge transfers from both direct and indirect contacts, but is far more likely to be new and useful when it comes from indirect contacts. Exploring knowledge flows in 69,476 patents …
Early To Adopt And Early To Discontinue: The Impact Of Self-Perceived And Actual It-Knowledge On Technology Use Behaviors Of End Users, Rohit Aggarwal, David Kryscynski, Vishal Midha, Harpeet Singh
Early To Adopt And Early To Discontinue: The Impact Of Self-Perceived And Actual It-Knowledge On Technology Use Behaviors Of End Users, Rohit Aggarwal, David Kryscynski, Vishal Midha, Harpeet Singh
Faculty Publications
For organizations to achieve the benefits of new IT systems their users must adopt and then actually use these new systems. Recent models help to articulate the potentially different explanations for why some users will adopt and then continue using new technologies, but these models have not explicitly incorporated IT-knowledge. This is particularly important in contexts where the user base may be non-IT professionals—i.e. the users may vary substantially in their basic IT-knowledge. We draw upon psychology to argue that in situations where there is wide variance in actual IT-knowledge there will often exist U relationship between actual and self-perceived …
Evaluating Venture Technical Competence In Vc Investment Decisions, Rohit Aggarwal, David Kryscynski, Harpeet Singh
Evaluating Venture Technical Competence In Vc Investment Decisions, Rohit Aggarwal, David Kryscynski, Harpeet Singh
Faculty Publications
While much research emphasizes the importance of venture technical-competence for venture success and, therefore, the importance of venture technical-competence in VC investment decisions, we know little about why some VCs may be better than others at assessing the technical-competence of ventures. We gathered unique and proprietary data from 33 VCs and 308 ventures that sought series A funding from those VCs. We show that VC assessment of ventures predicts VC investment, and venture technical-competence predicts subsequent venture failure. This means that VCs that over-assess ventures are more likely to invest in firms that are more likely to fail. We then …
Making Strategic Human Capital Relevant: A Time-Sensitive Opportunity, David Kryscynski, Dave Ulrich
Making Strategic Human Capital Relevant: A Time-Sensitive Opportunity, David Kryscynski, Dave Ulrich
Faculty Publications
The domain of strategic human capital is emerging at the intersection of strategy and strategic human resource management. Because it is still in the development phase, its core underlying assumptions have not yet solidified. This presents a unique and time-sensitive opportunity to explore and challenge these core assumptions and, specifically, to evaluate whether these assumptions mesh with the lived experiences of practicing managers. We argue that now is the time for the field to ground itself in practical phenomena so that its insights moving forward can be both academically rigorous and practically relevant. In this paper we illustrate the problems …
Using Measures Of Risk Perception To Predict Information Security Behavior: Insights From Electroencephalography (Eeg), Anthony Vance, Bonnie Anderson, C. Brock Kirwan, David Eargle
Using Measures Of Risk Perception To Predict Information Security Behavior: Insights From Electroencephalography (Eeg), Anthony Vance, Bonnie Anderson, C. Brock Kirwan, David Eargle
Faculty Publications
Users' perceptions of risks have important implications for information security, as the actions of individual users can compromise entire systems. Therefore, there is a critical need to understand how users perceive and respond to information security risks. Previous research on perceptions of information security risk has chiefly relied on self-reported measures. Although these studies are valuable, risk perceptions are often associated with feelings—such as fear or doubt—that are difficult to measure accurately using survey instruments. Additionally, it is unclear how these self-reported measures map to actual security behavior. This paper contributes by demonstrating that risk-taking behavior is effectively predicted using …
Rethinking Sustained Competitive Advantage From Human Capital, Benjamin Campbell, Russell Coff, David Kryscynski
Rethinking Sustained Competitive Advantage From Human Capital, Benjamin Campbell, Russell Coff, David Kryscynski
Faculty Publications
The strategy literature often emphasizes firm-specific human capital as a source of competitive advantage based on the assumption that it constrains employee mobility. This paper first identifies three boundary conditions that limit the applicability of this logic. It then offers a more comprehensive framework of human capital-based advantage that explores both demand- and supply-side mobility constraints. The critical insight is that these mobility constraints have more explanatory power than the firm-specificity of human capital.
Drilling For Micro-Foundations Of Human Capital Based Competitive Advantages, Russell Coff, David Kryscynski
Drilling For Micro-Foundations Of Human Capital Based Competitive Advantages, Russell Coff, David Kryscynski
Faculty Publications
From the origins of the Resource Based View, scholars have emphasized the importance of human capital as a source of sustained competitive advantage and recently there has been great interest in gaining a better understanding of the micro-foundations of strategic capabilities. Along these lines, there is little doubt that heterogeneous human capital is often a critical underlying mechanism for capabilities. Here, we explore how individual level phenomena underpin isolating mechanisms that sustain human capital-based advantages but also create management dilemmas that must be resolved in order to create value. The solutions to these challenges cannot be found purely in generic …
Data Mining Of Forensic Association Rules, James V. Hansen, Paul Benjamin Lowry, Rayman D. Meservy
Data Mining Of Forensic Association Rules, James V. Hansen, Paul Benjamin Lowry, Rayman D. Meservy
Faculty Publications
Data mining offers a potentially powerful method for analyzing the large data sets that are typically found in forensic computing (FC) investigations to discover useful and previously unknown patterns within the data. The contribution of this paper is an innovative and rigorous data mining methodology that enables effective search of large volumes of complex data to discover offender profiles. These profiles are based on association rules, which are computationally sound, flexible, easily interpreted, and provide a ready set of data for refinement via predictive models. Methodology incorporates link analysis and creation of predictive models based on association rule input.
An Adaptive Learning Model Which Accommodates Asymmetric Error Costs And Choice-Based Samples, James V. Hansen, James B. Mcdonald, Rayman D. Meservy
An Adaptive Learning Model Which Accommodates Asymmetric Error Costs And Choice-Based Samples, James V. Hansen, James B. Mcdonald, Rayman D. Meservy
Faculty Publications
This paper introduces an adaptive-learning model, EGB2, which optimizes over a parameter space to fit data to a family of models based on maximum-likelihood criteria. We also show how EGB2 can be modified to handle asymmetric costs of Type I and Type II errors, thereby minimizing misclassification costs. It has been shown that standard methods of computing maximum-likelihood estimators of qualitative-response models are generally inconsistent when applied to sample data with different proportions than found in the universe from which the sample is drawn. We investigate how a choice estimator, based on weighting each observation's contribution to the log-likelihood function, …
Case-Based Reasoning: Application Techniques For Decision Support, James V. Hansen, Rayman D. Meservy, Larry E. Wood
Case-Based Reasoning: Application Techniques For Decision Support, James V. Hansen, Rayman D. Meservy, Larry E. Wood
Faculty Publications
Decision-support systems can be improved by enabling them to use past decisions to assist in making present ones. Reasoning from relevant past cases is appealing because it corresponds to some of the processes an expert uses to solve problems quickly and accurately. All this depends on an effective method of organizing cases for retrieval. This paper investigates the use of inductive networks as a means for case organization and outlines an approach to determining the desired number of cases-or assessing the reliability of a given number. Our method is demonstrated by application to decision making on corporate tax audits.
Learn Audit Selection Rules From Data: A Genetic Algorithms Approach, David P. Greene, Rayman D. Meservy, Stephen F. Smith
Learn Audit Selection Rules From Data: A Genetic Algorithms Approach, David P. Greene, Rayman D. Meservy, Stephen F. Smith
Faculty Publications
The construction of expert systems typically require the availability of expertise that can be modeled. However, there are many important problems where no expertise exists, yet there is a wealth of data indicating results in different situations. Machine learning algorithms attempt to discover rules which capture the regularities that exists in such data.
Case-Based Reasoning And Risk Assessment In Audit Judgment, Eric L. Denna, James V. Hansen, Rayman D. Meservy, Larry E. Wood
Case-Based Reasoning And Risk Assessment In Audit Judgment, Eric L. Denna, James V. Hansen, Rayman D. Meservy, Larry E. Wood
Faculty Publications
The purpose of this paper is to describe the results of an effort to utilize Case Based Reasoning (CBR) to model a specific audit judgment task. To date most efforts to develop computational models of audit judgment have used strictly rule-based representation methods. Some researchers have recently adopted more robust structures to model the auditor domain knowledge. Although these recent efforts to extend the representation methods appear to be more accurate descriptions of auditor reasoning and memory, they still lack a comprehensive. theory to guide the development of the model. A commonly encountered phenomenon in audit judgment is for an …
Investigating Expertise In Auditing, Paul E. Johnson, Andrew D. Bailey Jr, Rayman D. Meservy
Investigating Expertise In Auditing, Paul E. Johnson, Andrew D. Bailey Jr, Rayman D. Meservy
Faculty Publications
Research on human expertise in auditing contexts is an important area of study. Our objective in this paper is to present an approach to conducting research on human expertise. We begin with some issues of terminology and then propose a strategy for inquiry into the phenomena of expertise. Finally, we attempt to illustrate this strategy with three examples of recently completed work. The examples include: two from the auditing literature that involve the analysis of internal control and a medical diagnosis case which illustrates the "garden path" problem that is of concern in any decision making context, including auditing.
Kass: A Knowledge-Based Auditor Support System, Ramayya Krishnan, Rayman D. Meservy, Vandana Gadh
Kass: A Knowledge-Based Auditor Support System, Ramayya Krishnan, Rayman D. Meservy, Vandana Gadh
Faculty Publications
This paper describes the design of a knowledge-based system to assist auditors in the evaluatation of internal accounting controls and focusses on the logic-based language AL that has been developed as a knowledge representation formalism. Interesting features of AL include a declarative approach to modeling accounting systems and the means to explicitly describe authority structures typically used to enforce internal controls.
Internal Control Evaluation: A Computational Model Of The Review Process, Rayman D. Meservy, Andrew D. Bailey Jr, Paul E. Johnson
Internal Control Evaluation: A Computational Model Of The Review Process, Rayman D. Meservy, Andrew D. Bailey Jr, Paul E. Johnson
Faculty Publications
This study investigated the strategies by which experienced auditors evaluate systems of internal accounting controls. The research method included: (1) observations, using concurrent protocols, of a small sample of practicing auditors performing the internal control evaluation task; (2) extensive interviews with one of the practicing auditors; (3) formalization of auditor processes as a computational model; and (4) validation of the model. The simulation model was Im· plemented as an expert system and tuned to one auditor. The model output consists of a trace of the model processing including: (1) rec• ommendatlons for specific controls to be compliance tested; and (2) …
Auditing, Artificial Intelligence And Expert Systems, Andrew D. Bailey, Rayman D. Meservy, Gordon L. Duke, Paul E. Johnson, William Thompson
Auditing, Artificial Intelligence And Expert Systems, Andrew D. Bailey, Rayman D. Meservy, Gordon L. Duke, Paul E. Johnson, William Thompson
Faculty Publications
This paper will provide the reader with an introduction to the field of financial auditing and the applicability of Decision Support Systems (DSS), Artificial Intelligence (AI), and Expert Systems (ES) to that field of endeavor. The paper will also discuss a continuing research project concerning the application of DSS/AI/ES techniques to the evaluation of internal accounting controls. The reader will find that the evaluation of internal accounting controls is a critical step in every financial audit and that it is an area in which the auditor exhibits substantial expertise. It is thus an area of work particularly suited to the …
A Mathematical Contraction And Automated Analysis Of Internal Controls, Andrew D. Bailey Jr, Gordon Leon Duke, James Gerlach, Chen-En Ko, Rayman D. Meservy, Andrew B. Whinton
A Mathematical Contraction And Automated Analysis Of Internal Controls, Andrew D. Bailey Jr, Gordon Leon Duke, James Gerlach, Chen-En Ko, Rayman D. Meservy, Andrew B. Whinton
Faculty Publications
This paper presents a precedent oriented computer assisted method of designing, analyzing and evaluating systems of internal controls. The ..!..nternal Control _!iodel, TICOM III, is fundamentally a design and analysis tool useful in the context of Automated Office Information Systems (AOIS's). Traditional analysis and evaluation tools, such as flowcharting, written narratives and questionnaires, are inefficient, if not insufficient, to support the design and control analysis of these new systems. The advantages of TICOM III over traditional methods such as narrative description, questionnaires and flowcharts are: (1) the evaluation can be more rigorous and exhaustive because of the speed, accuracy and …