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The role of big data and data analytics in the audit engagement process is evident. Notwithstanding, understanding how big data influences cognitive processes and, consequently, on the auditors’ judgment decision-making process is limited. The purpose of this paper is to present a conceptual framework on the cognitive process that may influence auditors’ judgment decision-making in the big data environment. The proposed framework predicts the relationships among data visualization integration, data processing modes, task complexity and auditors’ judgment decision-making.

The methodology to accomplish the conceptual framework is based on a thorough literature review that consists of theoretical discussions and comparative studies of other authors’ works and thinking. It also involves summarizing and interpreting previous contributions subjectively and narratively and extending the work in some fashion. Based on this approach, this paper formulates four propositions about data visualization integration, data processing modes, task complexity and auditors’ judgment decision-making. The proposed framework was built from cognitive theory addressing how auditors process data into useful information to make judgment decision-making.

The proposed framework expects that the cognitive process of data visualization integration and intuitive data processing mode will improve auditors’ judgment decision-making. This paper also contends that task complexity may influence the cognitive process of data visualization integration and processing modes because of the voluminous nature of data and the complexity of business processes. Hence, it is also expected that the relationships between data visualization integration and audit judgment decision-making and between processing mode and audit judgment decision-making will be moderated by task complexity.

There is a dearth of studies examining how big data and big data analytics affect auditors’ cognitive processes in making decisions. This paper will help researchers and auditors understand the behavioral consequences of data visualization integration and data processing mode in making judgment decision-making, given a certain level of task complexity.

With the advent of big data and the evolution of innovative audit procedures, the constructed framework can be used as a theoretical foundation for future empirical studies concerning auditors’ judgment decision-making. It highlights the potential of big data to transform the nature and practice of accounting and auditing.

Heuristics are used in the judgment and decision-making process of bank employees; however, discussions and research on the type or range of judgmental heuristics are very difficult to find throughout the world. In light of this, the purpose of this paper is to empirically analyze what types of heuristics are used in bank employees’ judgment and decision-making processes and the extent to which those types of heuristics prevent rational decision making due to the systematic biases they generate. In particular, this study aims to conduct empirical research based on various scenarios related to the banking industry.

To examine the heuristics in decision-making circumstances and the level of subsequent biases, the present study narrowed the scope of research to the three main types of heuristics introduced by Tversky and Kahneman (1974), namely, representativeness heuristics, availability heuristics and anchoring and adjustment heuristics. To analyze the bank employees’ decision making, this study specifically investigated the level of decision-making heuristics and the level of bias by focusing on these three types of heuristics. This study targeted bank employees who either sell financial products or are engaged in customer service work at a real/physical bank.

For representativeness heuristics, this study found bank employees’ judgment of probability was influenced by biases, such as insensitivity to prior probability, insensitivity to sample size, misconception of chance and insensitivity to predictability. Regarding availability heuristics, it found that bank employees judge the probability of events based on the ease of recalling an event instead of the actual frequency of the event, and so they fall prey to systematic biases. Finally, regarding anchoring and adjustment heuristics, this study found that employees fall prey to judgment biases as they judge the probability of conjunctive events and disjunctive events based on anchoring and insufficient adjustment.

Although people who are well-trained in statistics can avoid rudimentary errors, they fall prey to biased judgment at a similar level to those who are not properly trained in statistics when it comes to more complicated and ambiguous issues. It clearly indicates that it is risky to determine that financial experts would be more rational than the general public in making various judgments required in the policy-making process. To conclude, it is imperative to recognize the existence of heuristics-based systematic biases in the judgment and decision-making process and, furthermore, to reinforce the education and training system to improve bank employees’ rational choice and judgment ability.

The paper seeks to evaluate the prescriptive value of ethical decision‐making models.

The paper explores various types of models in the ethics literature in concert with knowledge from the decision sciences literature to develop a tentative list of evaluative criteria that might be applied to prescriptive models. It then applies these criteria to one prescriptive model from the ethics literature, developed by Petrick and Quinn, in an attempt to demonstrate the value of more comprehensive evaluation. It closes by considering future research aimed at the evaluation of ethical decision‐making models as well as research needed to validate the Petrick and Quinn model.

This critique finds that the Petrick‐Quinn judgment integrity model satisfies most of the criteria discussed in the ethical decision‐making literature. The primary opportunities for refining the Petrick‐Quinn model as a prescriptive framework for ethical decision making are: articulating the operational judgment component of the model as a formal, quantitative decision analysis, and conducting research to assess the real‐world utility of the model.

While there has been a proliferation of research concerning business ethics, little attention has been focused on evaluating the utility of ethical decision‐making models. Accordingly, this paper advances theory, research and practice regarding ethical decision making in organizations.

The monographs and reviews on audit judgment and decision-making research published over the years have strengthened this strand of research in auditing by providing insights and suggesting avenues for future research. However, no such comprehensive reviews have been published so far for the research undertaken in the domain of accounting judgment. This chapter reviews the accounting judgment and decision-making research published during 1972–2010 in the five top-tier accounting journals. It evaluates the characteristics and significance of these studies, their theoretical and methodological strengths and weaknesses, and suggests avenues for future research. The insights into accounting judgment and decision-making research provided in this chapter may be useful for improving the research method, theory development, and hypotheses' formulation stages of future studies. The analysis presented in this chapter may also provide the necessary impetus to strengthen this strand of research in accounting in the future.

An ongoing debate in the field of organizational decision-making concerns the use of intuition versus analytical rationality in decision-making. For the purpose of contributing to this debate we use a rich empirical dataset built from a longitudinal study of information technology project prioritization in a large financial institution to investigate how managers make space for the use of intuition in decision-making. Our findings show that during project prioritization meetings, senior decision makers apply three different techniques: bringing-in project intangibles, co-promoting intuitive judgments, and associating intuitive judgments with shared group context, when they make space for intuition in decision processes.

This paper aims to examine complex clinical decision‐making processes in trauma center units of hospitals in terms of the immediate impact of complexity on the medical team involved in the trauma event.

It is proposed to develop a model of decision‐making processes in trauma events that uses a Bayesian classifier model with convolution and deconvolution operators to study real‐time observed trauma data for the decision‐making process under tremendous stress. The objective is to explore and explain physicians' decision‐making processes under stress and time constraints during actual trauma events from the perspective of complexity.

Because physicians have blurred information and cues that are tainted by random environmental noise during injury‐related events, they must de‐blur (de‐convolute) the collected data to find a best approximation of the real data for decision‐making processes.

The data collection and analysis is innovative and the permission to access raw audio and video data from an active trauma center will differentiate this study from similar studies that rely on simulations, self report and case study approaches.

Clinical decision makers in trauma centers are placed in situations that are increasingly complex, making decision‐making and problem‐solving processes multifaceted.

The science of complex adaptive systems, together with human judgment theories, provide important concepts and tools for responding to the challenges of healthcare this century and beyond.

This paper aims to examine the influence of ethical judgement on decision-making behaviour related to ethical issues of Islamic banking practitioners in the United Arab Emirates (UAE).

The study adopted a confirmatory approach in which validated/established “normative ethical standards” are taken into the consideration as theoretical underpinning. In total, 262 samples are collected from Islamic banking practitioners in the UAE and data analysis is conducted using structural equation modelling.

The empirical findings indicate that the decision-making behaviour related to ethical issues of Islamic banking practitioners in UAE does not adhere to any set of normative ethical standards and respondents are pragmatic in nature when it comes to the decision-making behaviour related to ethical matters.

The study elucidates to what extent Islamic banking practitioners have encountered themselves with situations that demand the proper attention to the ethical aspects, which affecting decision-making behaviour related to ethical issues. According to the findings, those situations considerably demand the attention of ethical judgement in the decision-making behaviour of Islamic banking practitioners. Hence, it is recommended for Islamic banks in UAE to contain or intensify the training on the importance of ethics, Islamic thought and worldview to enhance corporate decision-making and banking profitability within the purview of Islamic principles.

While ample emphasis has been given to the juristic (fiqh) aspects of Sharīʿah-compliant in Islamic banking and finance, relatively little has been attempted to explore its ethical dimensions (akhlaq) in the compliance parameters. Further, Sharīʿah-compliant has been product-centric rather than people-centric. While there is numerous literature documented that links ethics and Islamic banking and finance, ethical framework and practice in Islamic finance institutions, studies focusing on the “people” and their “ethical decision-making behaviour” in Islamic financial institutions found missing in the literature. These gaps serve as justification for undertaking this research.

Humans tend to rely on beliefs, assumptions and cognitive rules‐of‐thumb for making judgments and are biased against taking more uncertain alternatives. Such inertia has implications for client organizations' decision making about innovations, which are inherently more uncertain than conventional alternatives. The purpose of this paper is to contribute to furthering the understanding of barriers to overcoming inertia in client decision making in new‐build.

A descriptive behavioural decision‐making perspective is combined with an organizational information‐processing perspective. To identify and discuss individual and organizational barriers that potentially distort clients' decision making on innovation, the analysis addresses aggregated data from four studies. The analysis focuses on inferences and interpretations made by decision makers in Swedish client organizations, their information‐processing practices and the subsequent impacts on perceived meanings and judgments about industrialized multi‐storey, timber‐framed building innovations, which are perceived by Swedish clients as new and different building alternatives.

Cognitive and organizational barriers maintain status‐quo decisions. Clients are inclined to make biased judgments about industrialized‐building alternatives because non‐applicable cognitive rules‐of‐thumb, based on their experiences of conventional‐building alternatives, are used. Furthermore, client organizations' information‐processing practices do not allow different meanings to surface, interact and potentially suggest different conclusions, at odds with established beliefs.

The paper's conclusions highlight how inertia is sustained in client decision making in new‐build. They illustrate the limitations of a common engineering approach, i.e. supporting decision making about innovations by focusing on providing more information to the decision maker in order to reduce uncertainty, as well as managing multiple meanings by reductionism.

Prior research suggests that decision-makers can be biased by anecdotal data, even in the presence of more informative statistical data. A bias for anecdotal data can have significant implications for managers since judgments are often made when both statistical and anecdotal data are present. However, since much of the prior research has been conducted primarily on non-professionals engaged in unfamiliar tasks, it is unclear whether anecdotal biases will occur in managerial decision-making, where training and professional duties may reduce the effects of such a bias. Smith and Kida (1991) note, for example, that judgment biases are often mitigated or modified when trained professionals perform job-related tasks. In this study, managers and others with significant business experience were asked to make a capital budgeting decision in the presence of both statistical and anecdotal data. The results indicate that decision-makers ignored, or underweighted, statistical data in favor of anecdotal data, leading to suboptimal decisions. However, a scientific judgment orientation decision-aid did help to mitigate the effects of that bias. The implications of these results for decision-making in managerial accounting are discussed.

The purpose of this study is to examine how trends in historical data influence two types of predictive judgments: territory selection and salesperson hiring. Sales managers are confronted frequently with decisions that explicitly or implicitly involve forecasting with limited information. In doing so, they conceptualize how the magnitude of these trend effects may be affected by the experience managers have in making these types of judgments. Study 1 provides evidence of a curvilinear relationship between experience and reliance on the trend data whereby the sales territory selections of novice sales managers exhibited greater susceptibility to informational trends than did the evaluations of naïve and expert decision-makers. A benchmark analysis in Study 2 further revealed that the salesperson selections made by novice and expert sales managers were equally biased, albeit in opposite directions, with novices overweighting and experts underweighting historical performance trends. Implications of these findings are discussed, as are avenues for future research.

The authors employ an online experimental design methodology of practicing managers. For Study 1, they use regression, whereas Study 2 uses a deterministic process to develop a priori predictive benchmark forecasts. Ordinary least squares is then used to estimate manager’s decisions, which are then compared to the predictive forecasts to determine accuracy.

Study 1 provides evidence of a curvilinear relationship between experience and reliance on the trend data whereby the sales territory selections of novice sales managers exhibited greater susceptibility to informational trends than did the evaluations of naïve and expert decision-makers. A benchmark analysis in Study 2 further revealed that the salesperson selections made by novice and expert sales managers were equally biased, albeit in opposite directions, with novices overweighting and experts underweighting historical performance trends.

The present inquiry is the first to provide insights into an important issue that has been the subject of equivocal findings, namely, whether experience in a judgmental domain exerts a facilitating or debilitating effect on sales manager decision-making. In this regard, some research supports the intuition that experience in making a particular type of decision can insulate managers from judgmental bias and, in doing so, improve decision quality (see Shanteau, [1992a] for a summary). In contrast, other work provides a more pessimistic view by demonstrating that the quality of decision-making is either unaffected by or can erode with additional experience (Hutchinson et al., 2010). To help reconcile these conflicting findings, the authors presented and tested a theoretical framework conceptualizing how trends may influence predictive judgments across three levels of decision-maker experience.