Una revisión sistemática del papel del "Big Data Analytics" en la reducción de la influencia de los errores cognitivos en el juicio de auditoría

A systematic review of the role of Big Data Analytics in reducing the influence of cognitive errors on the audit judgement


  • Fawad Ahmad LUISS Guido Carli University, Rome, Italy
DOI: https://doi.org/10.6018/rcsar.382251
Palabras clave: Calidad de la auditoría, Auditores Big4, Ajustes por devengo, Regulación auditora


La revisión sistemática de la literatura proporciona la asociación entre los procesos de la memoria, el juicio de los auditores y el proceso de toma de decisiones bajo la influencia de errores cognitivos. Debido a los limitados recursos cognitivos, los auditores no pueden analizar la población de transacciones contables; por lo tanto, utilizan el muestreo y la heurística para el procesamiento de la información. En el contexto de Big Data (BD), los auditores pueden enfrentarse a un problema similar de sobrecarga de información y exhibir errores cognitivos, lo que resulta en la selección y análisis de indicios de información irrelevantes. No obstante, la analítica de Big Data (BDA) puede facilitar el procesamiento de información y el análisis de datos complejos y diversos al reducir la influencia de los errores cognitivos del auditor. El presente estudio adapta el marco de trabajo de Ding et al (2017) en el contexto de la auditoría que identifica las causas de los errores cognitivos que influyen en el procesamiento de la información del auditor. Esta revisión identificó 75 estudios relacionados con la auditoría para elaborar el papel de BD y BDA en la mejora del juicio de auditoría. Además, el papel de la memoria, los errores cognitivos y el juicio y la toma de decisiones se destacan mediante el uso de 61 estudios. El análisis proporciona una visión útil de los diferentes aspectos abiertos de la cuestión proponiendo propuestas y preguntas de estudio que puedan ser exploradas por la investigación futura para obtener una comprensión amplia de la asociación entre la memoria y el juicio de auditoría en el contexto de BD y BDA.


Los datos de descargas todavía no están disponibles.


Ahlawat, S. S. (1999). Order effects and memory for evidence in individual versus group decision making in auditing. Journal of Behavioral Decision Making, 12(1), 71.

Alles, M. (2015). The drivers of the adoption and facilitators of the evolution of Big Data by the audit profession. Accounting Horizons, 29(2), 439-449.

Alles, M. G., Kogan, A., & Vasarhelyi, M. A. (2008). Putting continuous auditing theory into practice: Lessons from two pilot implementations. Journal of Information Systems, 22(2), 195-214.

Alles, M., & Gray, G. L. (2016). Incorporating Big Data in audits: Identifying inhibitors and a research agenda to address those inhibitors. International Journal of Accounting Information Systems, 22, 44-59.

Alles, M., Brennan, G., Kogan, A., & Vasarhelyi, M. A. (2006). Continuous monitoring of business process controls: A pilot implementation of a continuous auditing system at Siemens. International Journal of Accounting Information Systems, 7(2), 137-161.

Amer, T. S. (2005). Bias due to visual illusion in the graphical presentation of accounting information. Journal of Information Systems, 19(1), 1-18.

Anderson, J. C., Kaplan, S. E., & Reckers, P. M. (1992). The effects of output interference on analytical procedures judgments. Auditing, 11(2), 1.

Appelbaum, D. A., Kogan, A., & Vasarhelyi, M. A. (2018). Analytical procedures in external auditing: A comprehensive literature survey and framework for external audit analytics. Journal of Accounting Literature, 40, 83-101.

Appelbaum, D., Kogan, A., & Vasarhelyi, M. A. (2017). Big Data and analytics in the modern audit engagement: Research needs. Auditing: A Journal of Practice & Theory, 36(4), 1-27.

Arnold, V., Sutton, S. G., Hayne, S. C., & Smith, C. A. (2000). Group decision making: The impact of opportunity-cost time pressure and group support systems. Behavioral Research in Accounting, 12, 69.

Asare, S. K. (1992). The auditor's going-concern decision: Interaction of task variables and the sequential processing of evidence. Accounting Review, 379-393.

Ashton, A. H., & Ashton, R. H. (1988). Sequential belief revision in auditing. Accounting Review, 623-641.

Ashton, R. H. (1974). Behavioral implications of information overload in managerial accounting reports. Cost and Management, 48(4), 37-40.

Ashton, R. H. (1990). Pressure and performance in accounting decision settings: Paradoxical effects of incentives, feedback, and justification. Journal of Accounting Research, 148-180.

Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. Psychology of learning and motivation, 2, 89-195.

Baddeley, A. D., & Hitch, G. J. (1977). Recency re-examined. Attention and performance VI, 647-667.

Benbasat, I., & Taylor, R. N. (1982). Behavioral aspects of information processing for the design of management information systems. IEEE Transactions on Systems, Man, and Cybernetics, 12(4), 439-450.

Bennett, G. B., & Hatfield, R. C. (2017). Do Approaching Deadlines Influence Auditors' Materiality Assessments?. Auditing: A Journal of Practice and Theory. 36 (4), 29-48.

Birnberg, J. G., & Shields, M. D. (1984). The role of attention and memory in accounting decisions. Accounting, Organizations and Society, 9(3-4), 365-382.

Blay, A. D. (2005). Independence threats, litigation risk, and the auditor's decision process. Contemporary Accounting Research, 22(4), 759-789.

Bless, H. (2000). The interplay of affect and cognition: The mediating role of general knowledge structures. In J. P. Forgas (Ed.), Studies in emotion and social interaction, second series. Feeling and thinking: The role of affect in social cognition (pp. 201-222). New York: Cambridge University Press.

Bonner, S. E. (2008). Judgment and decision making in accounting. Prentice Hall.

Bower, G. H. (1992). How might emotions affect learning. The handbook of emotion and memory: Research and theory, 3, 31.

Brainerd, C. J., & Reyna, V. F. (2002). Fuzzy-trace theory and false memory. Current Directions in Psychological Science, 11(5), 164-169.

Braun, R. L. (2000). The effect of time pressure on auditor attention to qualitative aspects of misstatements indicative of potential fraudulent financial reporting. Accounting, Organizations and Society, 25(3), 243-259.

Brown-Liburd, H., Issa, H., & Lombardi, D. (2015). Behavioral implications of Big Data's impact on audit judgment and decision making and future research directions. Accounting Horizons, 29(2), 451-468.

Bruner, J. S., & Austin, G. A. (1986). A study of thinking. Transaction publishers.

Buchanan, J., & Kock, N. (2001). Information overload: A decision making perspective. In Multiple Criteria Decision Making in the New Millennium (49-58). Springer, Berlin, Heidelberg.

Cao, M., Chychyla, R., & Stewart, T. (2015). Big Data analytics in financial statement audits. Accounting Horizons, 29(2), 423-429.

Capriotti, R. J. (2014). Big Data Bringing Big Changes to Accounting. Pennsylvania CPA Journal, 85(2), 1-3.

Chang, C. J., Yen, S. H., & Duh, R. R. (2002). An empirical examination of competing theories to explain the framing effect in accounting-related decisions. Behavioral Research in Accounting, 14(1), 35-64.

Chewning Jr, E. G., & Harrell, A. M. (1990). The effect of information load on decision makers' cue utilization levels and decision quality in a financial distress decision task. Accounting, Organizations and Society, 15(6), 527-542.

Chewning, E. G., & Harrell, A. M. (1990). The effect of information load on decision makers' cue utilization levels and decision quality in a financial distress decision task. Accounting, Organizations and Society, 15(6), 527-542.

Choo, F. (1995). Auditors' judgment performance under stress: A test of the predicted relationship by three theoretical models. Journal of Accounting, Auditing & Finance, 10(3), 611-641.

Chung, J. O., Cohen, J. R., & Monroe, G. S. (2008). The effect of moods on auditors’ inventory valuation decisions. Auditing: A Journal of Practice & Theory, 27(2), 137-159.

Cianci, A. M., & Bierstaker, J. L. (2009). The impact of positive and negative mood on the hypothesis generation and ethical judgments of auditors. Auditing: A Journal of Practice & Theory, 28(2), 119-144.

Clore, G. L., & Huntsinger, J. R. (2007). How emotions inform judgment and regulate thought. Trends in Cognitive Sciences, 11(9), 393-399.

Courtis, J. K. (2004). Colour as visual rhetoric in financial reporting. Accounting Forum, 28 (3), 265-281.

Cowan, N. (2010). The magical mystery four: How is working memory capacity limited, and why?. Current Directions in Psychological Science, 19(1), 51-57.

Criss, A. H., Malmberg, K. J., & Shiffrin, R. M. (2011). Output interference in recognition memory. Journal of Memory and Language, 64(4), 316-326.

Danner, U. N., Aarts, H., & de Vries, N. K. (2007). Habit formation and multiple means to goal attainment: Repeated retrieval of target means causes inhibited access to competitors. Personality and Social Psychology Bulletin, 33(10), 1367-1379.

Ding, Y., Hellmann, A., & De Mello, L. (2017). Factors driving memory fallibility: A conceptual framework for accounting and finance studies. Journal of Behavioral and Experimental Finance, 14, 14-22.

Dominique, J. F., Roozendaal, B., & McGaugh, J. L. (1998). Stress and glucocorticoids impair retrieval of long-term spatial memory. Nature, 394(6695), 787-790.

Dowling, C., & Leech, S. (2007). Audit support systems and decision aids: Current practice and opportunities for future research. International Journal of Accounting Information Systems, 8(2), 92-116.

Driver, M. J., & Mock, T. J. (1975). Human information processing, decision style theory, and accounting information systems. Accounting Review, 50(3), 490-508.

Earley, C. E. (2015). Data analytics in auditing: Opportunities and challenges. Business Horizons, 58(5), 493-500.

Endler, N. S., & Magnusson, D. (1976). Toward an interactional psychology of personality. Psychological bulletin, 83(5), 956.

Enget, K., Saucedo, G. D., & Wright, N. S. (2017). Mystery, Inc.: A Big Data case. Journal of Accounting Education, 38, 9-22.

Estes, W. K. (1986). Array models for category learning. Cognitive psychology, 18(4), 500-549.

Fiske, S. T., & Taylor, S. E. (2013). Social cognition: From brains to culture. Sage.

Forgas, J. P. (1995). Strange couples: Mood effects on judgments and memory about prototypical and atypical relationships. Personality and Social Psychology Bulletin, 21(7), 747-765.

Frederick, D. M. (1991). Auditors' representation and retrieval of internal control knowledge. Accounting Review, 240-258.

Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137-144.

Gaudine, A., & Thorne, L. (2001). Emotion and ethical decision-making in organizations. Journal of Business Ethics, 31(2), 175-187.

Gepp, A., Linnenluecke, M. K., O’Neill, T. J., & Smith, T. (2018). Big data techniques in auditing research and practice: Current trends and future opportunities. Journal of Accounting Literature, 40, 102-115.

Gibbins, M. (1984). Propositions about the psychology of professional judgment in public accounting. Journal of Accounting Research, 103-125.

Glover, S. M. (1997). The influence of time pressure and accountability on auditors' processing of nondiagnostic information. Journal of Accounting Research, 35(2), 213-226.

Green, W. (2008). Does repetition impair auditors' judgments?. Managerial Auditing Journal, 23(8), 724-743.

Grossman, A. M., & Welker, R. B. (2011). Does the arrangement of audit evidence according to causal connections make auditors more susceptible to memory conjunction errors?. Behavioral Research in Accounting, 23(2), 93-115.

Guiral‐Contreras, A., Gonzalo‐Angulo, J. A., & Rodgers, W. (2007). Information content and recency effect of the audit report in loan rating decisions. Accounting & Finance, 47(2), 285-304.

Gul, F. A., Wu, D., & Yang, Z. (2013). Do individual auditors affect audit quality? Evidence from archival data. Accounting Review, 88(6), 1993-2023.

Hackenbrack, K. (1992). Implications of seemingly irrelevant evidence in audit judgment. Journal of Accounting Research, 126-136.

Hastie, R., & Dawes, R. M. (2010). Rational choice in an uncertain world: The psychology of judgment and decision making. Sage.

Hellmann, A. (2016). The role of accounting in behavioral finance. Journal of Behavioral and Experimental Finance, 9, 39-42.

Hellmann, A., Yeow, C., & De Mello, L. (2017). The influence of textual presentation order and graphical presentation on the judgements of non-professional investors. Accounting and Business Research, 47(4), 455-470.

Henckens, M. J., Hermans, E. J., Pu, Z., Joëls, M., & Fernández, G. (2009). Stressed memories: how acute stress affects memory formation in humans. Journal of Neuroscience, 29(32), 10111-10119.

Hilton, R. W. (1980). Integrating normative and descriptive theories of information processing. Journal of Accounting Research, 477-505.

Hirshleifer, D., & Teoh, S. H. (2003). Limited attention, information disclosure, and financial reporting. Journal of Accounting and Economics, 36(1), 337-386.

Hoch, S. J. (1984). Availability and interference in predictive judgment. Journal of Experimental Psychology: Learning, Memory, and Cognition, 10(4), 649.

Hogarth, R. M., & Einhorn, H. J. (1992). Order effects in belief updating: The belief-adjustment model. Cognitive Psychology, 24(1), 1-55.

Hsieh, H. F., & Shannon, S. E. (2005). Three approaches to qualitative content analysis. Qualitative Health Research, 15(9), 1277-1288.

Huerta, E., & Jensen, S. (2017). An accounting information systems perspective on data analytics and Big Data. Journal of Information Systems, 31(3), 101-114.

Iselin, E. R. (1988). The effects of information load and information diversity on decision quality in a structured decision task. Accounting, Organizations and Society, 13(2), 147-164.

Issa, H., & Kogan, A. (2014). A predictive ordered logistic regression model as a tool for quality review of control risk assessments. Journal of Information Systems, 28(2), 209-229.

Johansen, M. K., Savage, J., Fouquet, N., & Shanks, D. R. (2015). Salience not status: How category labels influence feature inference. Cognitive Science, 39(7), 1594-1621.

Johnson, E. N. (1994). Auditor memory for audit evidence: Effects of group assistance, time delay, and memory task. Auditing, 13(1), 36.

Jonides, J., Lewis, R. L., Nee, D. E., Lustig, C. A., Berman, M. G., & Moore, K. S. (2008). The Mind and Brain of Short-Term Memory. Annual Review of Psychology, 59, 193-224.

Kachelmeier, S. J., & Messier Jr, W. F. (1990). An investigation of the influence of a nonstatistical decision aid on auditor sample size decisions. Accounting Review, 209-226.

Kahneman, D. & Tversky, A., (1979), “Prospect theory: An analysis of decision under risk”. Econometrica: Journal of the Econometric Society, 263-291.

Kahneman, D. (2002). Maps of bounded rationality: A perspective on intuitive judgment and choice. Nobel Prize Lecture, 8, 351-401.

Kida, T., & Smith, J. F. (1995). The encoding and retrieval of numerical data for decision making in accounting contexts: Model development. Accounting, Organizations and Society, 20(7-8), 585-610.

Kida, T., Smith, J. F., & Maletta, M. (1998). The effects of encoded memory traces for numerical data on accounting decision making. Accounting, Organizations and Society, 23(5-6), 451-466.

Kiken, L. G., & Fredrickson, B. L. (2017). Cognitive Aspects of Positive Emotions: A Broader View for Well-Being. In The Happy Mind: Cognitive Contributions to Well-Being (pp. 157-175). Springer, Cham.

Kleinmuntz, B. (1990). Why we still use our heads instead of formulas: Toward an integrative approach. Psychological bulletin, 107(3), 296.

Kogan, A., Alles, M. G., Vasarhelyi, M. A., & Wu, J. (2014). Design and evaluation of a continuous data level auditing system. Auditing: A Journal of Practice & Theory, 33(4), 221-245.

Kokina, J., & Davenport, T. H. (2017). The emergence of artificial intelligence: How automation is changing auditing. Journal of Emerging Technologies in Accounting, 14(1), 115-122.

Kopp, L. S., & Bierstaker, J. L. (2006). Auditors’ memory of internal control information: the effect of documentation preparation versus review. Advances in Accounting Behavioral Research, 9, 27-50.

Kruschke, J. K., & Johansen, M. K. (1999). A model of probabilistic category learning. Journal of Experimental Psychology-Learning Memory and Cognition, 25(5), 1083-1119.

Kuhlmann, S., Piel, M., & Wolf, O. T. (2005). Impaired memory retrieval after psychosocial stress in healthy young men. Journal of Neuroscience, 25(11), 2977-2982.

Labrinidis, A., & Jagadish, H. V. (2012). Challenges and opportunities with big data. Proceedings of the VLDB Endowment, 5(12), 2032-2033.

Lampinen, J. M., Watkins, K. N., & Odegard, T. N. (2006). Phantom ROC: Recollection rejection in a hybrid conjoint recognition signal detection model. Memory, 14(6), 655-671.

Lerner, J. S., Li, Y., Valdesolo, P., & Kassam, K. S. (2015). Emotion and decision making. Annual Review of Psychology, 66.

Libby, R. (1985). Availability and the generation of hypotheses in analytical review. Journal of Accounting Research, 648-667.

Libby, R., & Trotman, K. T. (1993). The review process as a control for differential recall of evidence in auditor judgments. Accounting, Organizations and Society, 18(6), 559-574.

Libby, R., Bloomfield, R., & Nelson, M. W. (2002). Experimental research in financial accounting. Accounting, Organizations and Society, 27(8), 775-810.

Lowe, D. J., & Reckers, P. M. (1997). The influence of outcome effects, decision aid usage, and intolerance of ambiguity on evaluations of professional audit judgement. International Journal of Auditing, 1(1), 43-58.

Mac Donald Jr, A. P. (1970). Revised scale for ambiguity tolerance: Reliability and validity. Psychological Reports, 26(3), 791-798.

Maines, L. A. (1995). Judgment and decision-making research in financial accounting: A review and analysis. Judgment and decision-making research in accounting and auditing, 76-101.

Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A. H. (2016). Big Data: The next frontier for innovation, competition, and productivity. A report by the McKinsey Global Institute, May 2011.

McKinney Jr, E., Yoos II, C. J., & Snead, K. (2017). The need for ‘skeptical’accountants in the era of Big Data. Journal of Accounting Education, 38, 63-80.

Messier Jr, W. F., Kachelmeier, S. J., & Jensen, K. L. (2001). An experimental assessment of recent professional developments in nonstatistical audit sampling guidance. Auditing: A Journal of Practice & Theory, 20(1), 81-96.

Miller, D., & Gordon, L. A. (1975). Conceptual levels and the design of accounting information systems. Decision Sciences, 6(2), 259-269.

Mock, T. J., & Vasarhelyi, M. A. (1978). A synthesis of the information economics and lens models. Journal of Accounting Research, 414-423.

Moeckel, R. (1990). On central configurations. Mathematische Zeitschrift, 205(1), 499-517.

Moffitt, K. C., & Vasarhelyi, M. A. (2013). AIS in an age of Big Data. Journal of Information Systems, 27(2), 1-19.

Moher, D., Shamseer, L., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., ... & Stewart, L. A. (2015). Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systematic Reviews, 4(1), 1.

Morrill, J. B., Morrill, C. K., & Kopp, L. S. (2011). Internal control assessment and interference effects. Behavioral Research in Accounting, 24(1), 73-90.

Moser, D. V. (1989). The effects of output interference, availability, and accounting information on investors' predictive judgments. Accounting Review, 433-448.

Neath, I., & Nairne, J. S. (1995). Word-length effects in immediate memory: Overwriting trace decay theory. Psychonomic Bulletin & Review, 2(4), 429-441.

Nelson, M., & Tan, H. T. (2005). Judgment and decision making research in auditing: A task, person, and interpersonal interaction perspective. Auditing: A Journal of Practice & Theory, 24(s-1), 41-71.

Nisbett, R. E., Zukier, H., & Lemley, R. E. (1981). The dilution effect: Nondiagnostic information weakens the implications of diagnostic information. Cognitive Psychology, 13(2), 248-277.

Norton, R. W. (1975). Measurement of ambiguity tolerance. Journal of Personality Assessment, 39(6), 607-619.

Pincus, K. V. (1989). The efficacy of a red flags questionnaire for assessing the possibility of fraud. Accounting, Organizations and Society, 14(1-2), 153-163.

Reyna, V. F., & Brainerd, C. J. (1995). Fuzzy-trace theory: An interim synthesis. Learning and Individual Differences, 7(1), 1-75.

Ricciardi, V. (2008). The psychology of risk: The behavioral finance perspective. Handbook of finance.

Roediger III, H. L., & Karpicke, J. D. (2006). The power of testing memory: Basic research and implications for educational practice. Perspectives on Psychological Science, 1(3), 181-210.

Roediger, H. L., & Thorpe, L. A. (1978). The role of recall time in producing hypermnesia. Memory & Cognition, 6(3), 296-305.

Ruchkin, D. S., Grafman, J., Cameron, K., & Berndt, R. S. (2003). Working memory retention systems: A state of activated long-term memory. Behavioral and Brain Sciences, 26(6), 709-728.

Schacter, D. L. (1999). The seven sins of memory: Insights from psychology and cognitive neuroscience. American Psychologist, 54(3), 182.

Schick, A. G., Gordon, L. A., & Haka, S. (1990). Information overload: A temporal approach. Accounting, Organizations and Society, 15(3), 199-220.

Schneider, G. P., Dai, J., Janvrin, D. J., Ajayi, K., & Raschke, R. L. (2015). Infer, predict, and assure: Accounting opportunities in data analytics. Accounting Horizons, 29(3), 719-742.

Simnett, R. (1996). The effect of information selection, information processing and task complexity on predictive accuracy of auditors. Accounting, Organizations and Society, 21(7-8), 699-719.

Simon, H. A. (1978). Rationality as process and as product of thought. American Economic Review, 1-16.

Smith, J. F., & Kida, T. (1991). Heuristics and biases: Expertise and task realism in auditing. Psychological bulletin, 109(3), 472.

So, S., & Smith, M. (2002). Colour graphics and task complexity in multivariate decision making. Accounting, Auditing & Accountability Journal, 15(4), 565-593.

Spilker, B. C., & Prawitt, D. F. (1997). Adaptive responses to time pressure: The effects of experience on tax information search behavior. Behavioral Research in Accounting, 9, 172-198.

Stahlberg, D., & Maass, A. (1997). Hindsight bias: Impaired memory or biased reconstruction?. European Review of Social Psychology, 8(1), 105-132.

Stocks, M. H., & Harrell, A. (1995). The impact of an increase in accounting information level on the judgment quality of individuals and groups. Accounting, Organizations and Society, 20(7-8), 685-700.

Theis, J. C., Yankova, K., & Eulerich, M. (2012). Information order effects in the context of management commentary—initial experimental evidence. Journal of Management Control, 23(2), 133-150.

Tomlinson, T. D., Huber, D. E., Rieth, C. A., & Davelaar, E. J. (2009). An interference account of cue-independent forgetting in the no-think paradigm. Proceedings of the National Academy of Sciences, 106(37), 15588-15593.

Tonoki, A., & Davis, R. L. (2012). Aging impairs intermediate-term behavioral memory by disrupting the dorsal paired medial neuron memory trace. Proceedings of the National Academy of Sciences, 109(16), 6319-6324.

Tractinsky, N., & Meyer, J. (1999). Chartjunk or goldgraph? Effects of presentation objectives and content desirability on information presentation. MIS Quarterly, 397-420.

Tubbs, R. M., Messier Jr, W. F., & Knechel, W. R. (1990). Recency effects in the auditor's belief-revision process. Accounting Review, 452-460.

Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive Psychology, 5(2), 207-232.

Wadlinger, H. A., & Isaacowitz, D. M. (2006). Positive mood broadens visual attention to positive stimuli. Motivation and Emotion, 30(1), 87-99.

Weber, E. U., & Johnson, E. J. (2009). Mindful judgment and decision making. Annual Review of Psychology, 60, 53-85.

Weick, K. E. (1983). Stress in accounting systems. Accounting Review, 58(2), 350-369.

Whitecotton, S. M. (1996). The effects of experience and a decision aid on the slope, scatter, and bias of earnings forecasts. Organizational Behavior and Human Decision Processes, 66(1), 111-121.

Wright, W. F., & Bower, G. H. (1992). Mood effects on subjective probability assessment. Organizational Behavior and Human Decision Processes, 52(2), 276-291.

Zhang, J., Yang, X., & Appelbaum, D. (2015). Toward effective Big Data analysis in continuous auditing. Accounting Horizons, 29(2), 469-476.

Cómo citar
Ahmad, F. (2019). Una revisión sistemática del papel del "Big Data Analytics" en la reducción de la influencia de los errores cognitivos en el juicio de auditoría: A systematic review of the role of Big Data Analytics in reducing the influence of cognitive errors on the audit judgement. Revista de Contabilidad - Spanish Accounting Review, 22(2), 187–202. https://doi.org/10.6018/rcsar.382251