Bibliographic record
Abstract
Citation (2020), "Index", Karim, K.E. (Ed.) Advances in Accounting Behavioral Research (Advances in Accounting Behavioural Research, Vol. 23), Emerald Publishing Limited, Bingley, pp. 163-168. https://doi.org/10.1108/S1475-148820200000023007 Publisher: Emerald Publishing Limited Copyright © 2020 Emerald Publishing Limited INDEX ABM simulations. See Agent-based modeling (ABM) simulations Accountants, 4, 139 Australian, 147 Canadian, 148 career anchors, 158 forensic, 27 millennials, 31, 149, 150, 158 older generations, 31 organizational citizenship, 8 personality, 121 professional, 142, 152, 157 public accounting industry, 23 risk averse, 4 social desirability response bias (SDRB), 9 survey, 7 Taiwan, 7 (un)ethical behavior, 9 Accounting choice disclosure, 59, 67 agency risks, 53 anchor-and-adjustment phenomenon, 57, 58 conservative accounting choice, 53, 56–57 disconfirming attributes, 58 execution risk, 53 market risk, 54 overpayment risk, 53, 55 revenue outcomes, 53, 54 Account risk disclosure, 59, 67 agency risk, 55 anchor-and-adjustment phenomenon, 57, 58 conservative accounting choice, 56–57 disconfirming attributes, 58 economic realities, 55 risk-averse behaviors, 55 Accredited investors, 50 ACFE. See Association of Certified Fraud Examiners (ACFE) Agency risks, 53, 55 Agent-based modeling (ABM) simulations, 27 Aggressive accounting choice, 48, 49, 55, 63 Agreeableness, 120–121, 123, 125, 128, 131–132 Alibaba, 23 Altruism, 7, 8 Analysis of variance (ANOVA), 12, 13, 64–65, 67, 155 Anchor-and-adjustment phenomenon, 57, 58 Angel investors accounting choice disclosure. See also Accounting choice disclosure, 48 account risk disclosure, 55–60 angel valuation judgments, 51–53 “changes” approach, 61 demographic information, 62, 63 disconfirming disclosure, 49, 68 experimental design, 61 FASB revenue recognition standard, 60 hypotheses testing, 64–66 limitations, 69–70 manipulation checks, 63 non financial vs financial models, 63–64 private company investment, 48 prospect theory, 49 revenue account, 61–62 seed equity investment (SEI) contexts, 49–50 straight-equity funding, 60 Tukey HSD post hoc pairwise analysis, 67–68 Antifraud control mechanisms, 78, 79 factor analysis, 94 Kaiser criterion, 88, 89 scoring coefficients, 107 statistics, 82 tetrachoric cross-correlation matrix, 84, 104 Asset misappropriation, 79 Certified Fraud Examiners (CFEs), 82 defined, 78 determinants, 78 loss sizes, 80, 81, 95 organizational losses predictors, 91, 110–117 sociodemographic factors, 78 Association of Certified Fraud Examiners (ACFE), 78–79, 81, 95–96, 101 “Attentive” supervisor, 123 AU-C-Section 240 (AICPA), 24 Autonomy Corp., 23 Behavioral red flags (BRFs) antifraud control mechanisms, 79, 82, 84, 88 Association of Certified Fraud Examiners (ACFE), 78–79, 81, 95–96, 101 comprehensive analysis, 79–81 Coterie, 88, 93 exploratory factor analysis (EFA), 79, 82, 84–89, 95 financial distress, 88, 90, 93 hierarchical linear models (HLMs), 84 industry clustering, 84 large-scale fraud, 94 low-income group, 93 micro-level database, 81–82 monetary vs. nonmonetary issues, 88 occupational misconduct, 77, 79 organizational losses predictors, 88, 91–92, 108–109 organizational misconduct, 77, 78, 79 organization type clustering, 84, 85 parallel analysis (PA), 84, 89, 90 private vs. work-related issues, 88 robustness, 94–95 scoring coefficients, 106 tenure, 93–94 tetrachoric cross-correlation matrix, 82–84, 102–103 Behavioral warning signs, 78 Big five personality traits, 8, 121–122, 126, 131, 134–135 Buffer/conduit theory, 27, 40–41 culture-oriented internal controls, 26 dynamic orientation, 30 ethical conduct, 29 fraud-related values, 22, 25 indicators, 29, 35, 36, 38 individual and collective values, 23 layers, 26 management control systems (MCSs), 24 OC-related auditing guidance, 24 risk factors, 23 taxonomy, 28 Business ethics research, 9 Capital budgeting, 8 Career anchors definition, 142, 143 manage careers, 146–147 other fields, 147–148 primary, 142, 150, 153, 156 types, 142 validity, 143–144 Career management, 146–147 Career Orientations Inventory (COI), 142, 146, 148 Cash incentives, 4 Certified Fraud Examiners (CFEs), 78, 80–82, 88, 90 Certified Public Accountants (CPAs), 147 Chi-square test, 11, 12 goodness of fit test, 153 independence, 156, 157 Citigroup, 22, 77 Collective fraud orientations, 23, 28 Committee of Sponsoring Organizations (COSO) Fraud Risk Management Guide, 22 Internal Control–Integrated Framework, 22, 24 Comparables, 51 Conscientiousness, 121–123, 125–129, 131–132 Conservative accounting choice, 48, 53, 55–57, 63 Corporate fraud scandals, 22–23 Cross-correlation matrix factors, 105 tetrachoric, 82–84, 102–103 C-suite responsibility, 23 Deutsche Bank, 23, 77 Ethics, 8, 40–41 behavior, 30, 36, 38 codes of conduct, 26, 29 concerns, 30, 38 decision-making, 28 fraud risk management, 22 integrity and, 22 models, 24 performance appraisal, 30–31 standards, 24 tone at the top, 28–29 Execution risk, 53 Exploratory factor analysis (EFA), 79, 82, 84–89, 95 Extant theory, 22 External organizational behavior, 31 Extraversion, 120, 121–129, 131–132, 134 Fair promotion practices, 31 FASB revenue recognition standard, 60 Financial distress, 88, 90, 93 Financial reporting, 49 Fraud-deterring organizational orientations, 22 Fraud-encouraging individual orientations, 22, 23 Fraud-fighting model, 28 Fraud-related values. See also Organizational culture (OC), 22, 24, 25, 28, 40 Fraud risk management, 22 Hierarchical linear models (HLMs), 84–85, 94, 108–111, 116–117 Incentives, 3–5 performance effects, 6, 7 social desirability response bias (SDRB), 16 Industry clustering, 84 Internal organizational behavior, 31 International Country Risk Guide, 96 Job performance, 120, 123, 124 Job satisfaction, 7, 80, 142, 148, 150, 157 Job stress, 7 JP Morgan, 77 Kaiser criterion, 88, 89 KPMG, 80, 101 Leader-member exchange (LMX) theory, 123, 124 LIBOR scandal, 77 Locus of control (LOC), 6–7, 10–14 Management control systems (MCSs), 22, 24, 29, 30 Management information systems (MIS), 147 Market risk, 54 Marlowe-Crowne scale, 11 Millennials, 36 accountants, 142, 149, 150, 158 characteristics, 144–146 older generations, 31–32 organizational culture (OC), 31–32 Monetary incentives, 2–4, 6, 9, 13 types, 5 Neuroticism, 121–125, 128–129, 131–132 Nonmonetary incentives, 3, 4 Not-for-profit organizations, 80 OC. See Organizational culture (OC) Occupational fraud. See also Asset misappropriation, 96 Occupational misconduct, 77, 79 Older generations, 31–32 OLS models, 84–85, 88, 94–95, 108–117 Openness, 121–123, 125, 128, 129, 131–132 Organizational behavior, 120–124, 134 Organizational citizenship, 8 Organizational commitment, 30, 142, 148 Organizational culture (OC) A-B-C analysis, 25 buffer/conduit theory. See also Buffer/conduit theory, 29 collective fraud orientations, 23, 28 corporate fraud scandals, 22–23 C-suite responsibility, 23 demographic information, 33, 34 employees’ values on fraud, 28 ethical concerns, 30 ethics-oriented performance appraisal content, 30 extant theory, 22 factor analysis, 23, 24 fraud control, 28 fraud-fighting model, 28 fraud-related values, 22, 24 fraud risk management, 22 hypothesis-testing research, 24 individual fraud orientations, 23, 27 instrument, fraud orientation, 32–33 integrity and ethical values, 22 internal control, 21–24 management control systems (MCSs), 22, 24 millennials, 31–32 multivariate analysis, 37–40 older generations, 31–32 performance goals, ethical behavior, 30 performance review systems, 31 predisposition to commit fraud, 27 professional education participants, 32 recruitment and training, 29 risk factors, 24 susceptibility to social influence, 27–28 tone at the top, 28–29 univariate analysis, 35–37 written rules, 29–30 Organizational misconduct, 77, 78, 79 Organization type clustering, 84, 85 Overpayment risk, 53, 55 Parallel analysis (PA), 84, 89, 90 Participation rates, 10, 15–16 vs. chi-square test, 12 incentives, 3–5 locus of control (LOC), 6–7 payment level, 5 prosocial behavior (PSB), 7–8 social contract, 5, 6 social desirability response bias (SDRB), 8–9 treatment condition effort, 12 variables of interest, 6 Percentage ownership interest, 52 Performance review systems, 31 Personality traits, 120, 122–127, 131, 132 PriceWaterhouseCoopers (PWC), 144 Principal component analysis (PCA), 37, 39, 150 Private company accounting and reporting conservative accounting choice, 60 disclosure requirements, 49 Prosocial behavior (PSB), 7–8, 10–14 Prosocial Tendencies Measure, 11 Public company investors, 49–50, 53, 60, 68 Qualtrics software, 149 Recruiting method and participant behavior actual volunteers, 2 chi-square test, 11, 12 compensation, 15, 16 data collection, 10 demographic information, 11 individual difference variables, 14, 15, 16 instruments, 10–11 least effective method, 16 limitations, 17 monetary incentive, 9, 13 outcome variables, 10 participation rates. See also Participation rates, 2, 3 pseudo volunteers, 2 pure volunteers, 3 sample characteristics, 3, 4 social contract, 13 statistical tests, 2 treatment condition effort, 12 true volunteers, 2 undergraduate accounting class, research project, 10 variable of interest, 2 Revenue account, 61–62 Revenue outcomes, 53, 54 Scorecard Approach, 51 Seed equity investors (SEIs) accounting disclosures, 48 angel investors, 50, 64 incentives, 48 investee company management, 49 investment decisions, 62 percentage ownership interest, 48 venture capitalists (VCs), 50 Self-assessed job performance, 7 Self-deception bias, 8 Self-justify unethical behavior, 31 Social contract, 4–6, 13 participation rates, 5, 6 Social desirability response bias (SDRB), 8–14 SoftCo., 60, 61 Straight-equity funding, 60 Supervisor abuse, 122, 127, 131–132 Supervisor feedback, 120–122, 132, 134 Supervisor support, 121–122, 133–134 Conscientiousness, 132 definitions, 123 effects, 123–124 Extraversion, 132 questionnaire, 127 “Tolerant” supervisor, 123 Tukey HSD post hoc pairwise analysis, 67–68 Turnover, 120–122 effects, 123–124 intentions, 124 US Statement of Auditing Standard (SAS) No, 99, 80, 101 Valuation judgments, 68 accounting choice disclosure, 53–60 account risk disclosure, 55–60 angel funding, 53 cell means plot, 65, 66 entrepreneur(s) relationship, 52 financial information, 51, 53 investment decisions, 69 nonfinancial information, 51 percentage ownership interest, 52 primary financial interest, 66 Variance inflation factor (VIF) test, 108–111, 116–117, 129 employees vs. managers, 94–95 firm sizes, 95 lowest and largest values exclusion, 95 Vendor-specific objective evidence (VSOE), 60 Venture capitalists (VCs), 50, 69 Venture Capital Method, 51 Book Chapters Prelims Recruiting Method and Its Impact on Participant Behavior Connecting Organizational Culture to Fraud: Buffer/Conduit Theory Angel Investor Value Judgments and the Effects of Accounting Disclosures Behavioral Red Flags and Loss Sizes from Asset Misappropriation: Evidence from the US Effects of Supervisor's Personality on the Support, Abuse, and Feedback Provided to Junior Accountants Career Anchors of Millennial Accountants Index
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.041 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".