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Enregistrement W4230619355 · doi:10.1108/s1475-148820200000023007

Index

2020· paratext· en· W4230619355 sur OpenAlexaboutno aff

Notice bibliographique

RevueAdvances in accounting behavioral research · 2020
Typeparatext
Langueen
DomaineBusiness, Management and Accounting
ThématiqueAuditing, Earnings Management, Governance
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésIndex (typography)Computer scienceWorld Wide Web

Résumé

récupéré en direct d'OpenAlex

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

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,008
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Communication savante, Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,845
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,008
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0020,004
Études des sciences et des technologies0,0010,000
Communication savante0,0020,005
Science ouverte0,0030,003
Intégrité de la recherche0,0010,005
Charge utile insuffisante (le modèle a refusé de juger)0,0060,041

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,068
Tête enseignante GPT0,395
Écart entre enseignants0,326 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

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