Multicriteria decision aid methods for the prediction of business failure:
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| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Boston [u.a.]
Kluwer
1998
|
| Series: | Applied optimization
12 |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XXIV, 171 S. graph. Darst. |
| ISBN: | 0792349008 |
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| 245 | 1 | 0 | |a Multicriteria decision aid methods for the prediction of business failure |c Constantin Zopounidis and Augustinos I. Dimitras |
| 264 | 1 | |a Boston [u.a.] |b Kluwer |c 1998 | |
| 300 | |a XXIV, 171 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
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| 650 | 7 | |a Besliskunde |2 gtt | |
| 650 | 7 | |a Entreprises - Disparition - Prévision |2 ram | |
| 650 | 7 | |a Faillissement |2 gtt | |
| 650 | 7 | |a Prognoses |2 gtt | |
| 650 | 7 | |a Teoria da decisão (administração executiva) |2 larpcal | |
| 650 | 4 | |a Bankruptcy -- Forecasting | |
| 650 | 4 | |a Business failures -- Forecasting | |
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| adam_text | TABLE OF CONTENTS
Aknowledgments ix
Table of Contents xi
List of Tables xv
List of Figures xix
Prologue xxi
Chapter I. Business Failure Research: Some Statistics, Methods,
Models and Variables 1
1.1. Introduction 1
1.2. Methods and models 6
1.2.1. Univariate statistical methods 7
1.2.2. Discriminant analysis 8
1.2.3. Linear probability model 12
1.2.4. Logit and probit analyses 13
1.2.5. Recursive partitioning algorithm 16
1.2.6. Survival Analysis 19
1.2.7. Expert Systems 21
1.2.8. Neural Networks 22
1.3. Financial ratios and other characteristics 24
1.4. Conclusions 30
Chapter II. Multicriteria Decision Aid Methodology 31
2.1. Introduction 31
2.2. Multiobjective Mathematical Programming 33
2.2.1 Multiobjective Mathematical Programming for
bankruptcy prediction 34
2.3. Multiattribute Utility Theory 38
2.4. Outranking Relations Approach 39
2.5. Preference Disaggregation Approach 41
2.6. Multicriteria Analysis and Business Failure 42
Chapter III. ELECTRE TRI Method and Business Failure Prediction 45
3.1. Introduction 45
3.2. ELECTRE TRI 46
3.3. The study of Dimitras, Zopounidis and Hurson (1995) 53
3.3.1. Sample and data 53
xii
3.3.2. Classification Results 55
3.4. The study of Dimitras (1995) 60
3.4.1. Sample and data 60
3.4.2. Classification Results 61
3.4.3. Comparison between ELECTRE TRI and
discriminant analysis 66
3.5. Concluding remarks 67
Chapter IV. Rough Sets and Business Failure Prediction 69
4.1. Introduction 69
4.1.1. Information table and indiscernibility relation 69
4.1.2. Approximation of sets 70
4.1.3. Reduction and dependency of attributes 71
4.1.4. Decision rules 72
4.1.5. Decision support using decision rules 73
4.1.6. Valued closeness relation (VCR) 74
4.2. The study of Slowinski and Zopounidis (1995) 77
4.2.1. Sample and data 77
4.2.2. Application 78
4.3. The study of Dimitras, Slowinski, Susmaga, and
Zopounidis (1997) 89
4.3.1. Sample and data 89
4.3.2. Application 89
4.3.3. Comparison of the rough set approach with the
discriminant analysis 99
4.3.4. Comparison of the rough set approach with the logit
analysis 103
4.4. The study of Greco, Matarazzo and Slowinski (1997) 106
4.4.1. Sample and data 110
4.4.2 Application Ill
4.5. Concluding remarks 116
Chapter V. Preference Disaggregation Method and Business Failure
Prediction 117
5.1. Introduction 117
5.2. The UTA Method 117
5.3. The study of Zopounidis (1987) The MINORA System 119
5.3.1. First step 126
5.3.2. Second Step 129
xiii
5.3.3. Third step 130
5.3.4. Fourth step 131
5.3. The study of Zopounidis and Doumpos (1997) The
UTADIS method 135
5.3.1. The UTADIS method 135
5.3.2. Sample and data 139
5.3.3. Classification results 142
5.3.4. Comparison between UTADIS and Discriminant
Analysis 143
5.4. Concluding remarks 145
Conclusions 147
References 151
LIST OF TABLES
Table 1.1: Business Failures in USA in the period 1971 1991 2
Table 1.2: Business failures in Greece in the period 1973 1996 4
Table 1.3: Business Failures in European countries in the period 1992 19%,
Source: Newspaper To Vima , 8 6 1997 5
Table 1.4: Number of studies by country in the study of Dimitras et al. (19%) 26
Table 1.5: Use of methods by country in the study of Dimitras et al. (19%) 27
Table 1.6: Use of financial ratios by country in the study of Dimitras et al. (19%) 28
Table 3.1: Modeling of qualitative criteria in the study of Dimitras, Zopounidis and
Hurson(1995) 55
Table 3.2: The Industrial Bank s multicriteria evaluation in the study of Dimitras,
Zopounidis and Hurson (1995) 56
Table 3.3: Profile n and relative thresholds in the study of Dimitras, Zopounidis
and Hurson (1995) 57
Table 3.4: Profile n and relative thresholds in the study of Dimitras, Zopounidis
and Hurson (1995) 57
Table 3.5: Grouping of firms by optimistic procedure in the study of Dimitras,
Zopounidis and Hurson (1995) 57
Table 3.6: Grouping of firms by pessimistic procedure in the study of Dimitras,
Zopounidis and Hurson (1995) 58
Table 3.7: Misclassification analysis of the optimistic procedure in the study of
Dimitras, Zopounidis and Hurson (1995) 59
Table 3.8: Misclassification analysis of pessimistic procedure in the study of
Dimitras, Zopounidis and Hurson (1995) 59
Table 3.9: Profile, relative thresholds and weights in the study of Dimitras (1995) 63
Table 3.10: Classification accuracy and misclassification analysis of grouping
provided by pessimistic procedure for the years 1 to 5 of the basic
sample in the study of Dimitras (1995) 63
Table 3.1 ^Classification accuracy and misclassification analysis of grouping
provided by optimistic procedure for the years 1 to 5 of the basic
sample in the study of Dimitras (1995) 64
Table 3.12:Classification accuracy, category of uncertainty and misclassification
analysis of grouping provided by total classification for the years 1 to 5
of the basic sample in the study of Dimitras (1995) 65
Table 3.13:Classification accuracy, group of uncertainty and misclassification
analysis of grouping provided by total classification for the years 1 to 3
of the holdout sample in the study of Dimitras (1995) 65
Table 3.14: Discriminant function s coefficients in the study of Dimitras (1995) 66
Table 3.15: Classification accuracy of the discriminant function for the years 1 to 5
of the basic sample in the study of Dimitras (1995) 67
Table 3.16:Classification accuracy of the discriminant function for the years 1 to 3
of the holdout sample in the study of Dimitras (1995) 67
Table 4.1: The codes for the terms of qualitative attributes in the study of Slowinski
and Zopounidis (1995) 79
xvi
Table 4.2: The definition of norms for quantitative attributes in the study of
Slowinski and Zopounidis (1995) 80
Table 4.3: Original Information System in the study of Slowinski and Zopounidis
(1995) 81
Table 4.4: Accuracy of approximation of each category by 12 attributes in the coded
information system in the study of Slowinski and Zopounidis (1995) 82
Table 4.5: Reducts of the coded information table in the study of Slowinski and
Zopounidis (1995) 82
Table 4.6: Quality of sorting by single attributes in the study of Slowinski and
Zopounidis (1995) 83
Table 4.7: Quality of sorting by pairs of attributes including the core (At) in the
study of Slowinski and Zopounidis (1995) 83
Table 4.8: Quality of sorting by triples of attributes including the pair {Aly As) in the
study of Slowinski and Zopounidis (1995) 84
Table 4.9: Quality of sorting by quadruples of attributes including the triple {An, A*,
Au) in the study of Slowinski and Zopounidis (1995) 84
Table4.10:The 15 rules algorithm in the study of Slowinski and Zopounidis (1995) 85
Table 4.1 l:The 11 rules algorithm in the study of Slowinski and Zopounidis (1995) 86
Table 4.12: Sub intervals (norms) defined for the 12 attributes in the study of
Dimitras et al. (1997) 90
Table 4.13: Code numbers given to the sub intervals in the study of Dimitras et al.
(1997) 92
Table 4.14: Reducts of the coded information table in the study of Dimitras et al.
(1997) 93
Table 4.15:The minimal set of decision rules in the study of Dimitras et al. (1997) 94
Table 4.16: The set of strong decision rules (strength =8) in the study of Dimitras
etal. (1997) 95
Table 4.17: The set of strong and partly discriminant decision rules (strength = 8,
level of discrimination =90%) in the study of Dimitras et al. (1997) 96
Table 4.18: Parameters of the Valued Closeness Relation in the study of Dimitras et
al. (1997) 96
Table 4.19: Classification accuracy for the application of minimal set of rules on the
learning sample in the study of Dimitras et al. (1997) 97
Table 4.20: Classification accuracy for the application of the set of strong rules on
the learning sample in the study of Dimitras et al. (1997) 97
Table 4.21: Classification accuracy for the application of the set of strong , partly
discriminating rules on the learning sample in the study of Dimitras et al.
(1997) 98
Table 4.22: Classification accuracy for the application of minimal set of rules on the
testing sample in the study of Dimitras etal. (1997) 98
Table 4.23: Classification accuracy for the application of the set of strong rules on
the testing sample in the study of Dimitras et al. (1997) 99
Table 4.24: Classification accuracy for the application of the set of strong , partly
discriminating rules on the testing sample in the study of Dimitras et al.
(1997) 99
xvii
Table 4.25:Discriminant function s coefficients for the attributes of the complete
information table in the study of Dimitras et al. (1997) 100
Table 4.26:Discriminant function s coefficients for the attributes of the reduced
information table in the study of Dimitras etal. (1997) 101
Table 4.27: Classification accuracy for the application of the discriminant function,
defined on the complete information table, on the learning sample in the
study of Dimitras etal. (1997) 101
Table 4.28: Classification accuracy for the application of the discriminant function,
defined on the complete information table, on the testing sample in the
study of Dimitras et al. (1997) 102
Table 4.29: Classification accuracy for the application of the discriminant function,
defined on the reduced information table, on the learning sample in the
study of Dimitras et al. (1997) 102
Table 4.30: Classification accuracy for the application of the discriminant function,
defined on the reduced information table, on the testing sample in the
study of Dimitras et al. (1997) 102
Table 4.3l:Logit model s coefficients for the attributes of the reduced information
table in the study of Dimitras et al. (1997) 104
Table 4.32:Logit model s coefficients for the attributes of the complete information
table in the study of Dimitras et al. (1997) 104
Table 4.33: Classification accuracy for the application of the logit model, defined on
the attributes of the complete information table, on the learning sample
in the study of Dimitras etal. (1997) 105
Table 4.34: Classification accuracy for the application of the logit model, defined on
the attributes of the complete information table, on the testing sample in
the study of Dimitras etal. (1997) 105
Table 4.35: Classification accuracy for the application of the logit model, defined on
the attributes of the reduced information table, on the learning sample in
the study of Dimitras etal. (1997) 105
Table 4.36: Classification accuracy for the application of the logit model, defined on
the attributes of the reduced information table, on the testing sample in
the study of Dimitras etal. (1997) 106
Table 4.37:Reducts of the coded information table in the study of Greco et al. (1997)... 112
Table 4.38:Quality of sorting by single attributes in the study of Greco et al. (1997) 113
Table 4.39:Quality of sorting by triples of attributes including the core in the study
of Greco etal. (1997) 113
Table 4.40:Quality of sorting by triples of attributes including the triple (Ay, Ay, A?)
in the study of Greco etal. (1997) 114
Table 5.1: The financial evaluation criteria in the study of Zopounidis (1987) 123
Table 5.2: The strategic evaluation criteria in the study of Zopounidis (1987) 124
Table 5.3: Decision maker s judgment and multicriteria evaluation in the study of
Zopounidis (1987) 125
Table 5.4: Classification of the firms after the first step in the study of Zopounidis
(1987) 128
Table 5.5: Classification of the firms after the second step in the study of
Zopounidis (1987) 131
xviii
Table 5.6: Classification of the firms after the third step in the study of Zopounidis
(1987) 132
Table S.7: Classification accuracy and misclassification analysis of grouping for the
years 2 to S of the basic sample in the study of Zopounidis and
Doumpos(1997) 142
Table 5.8: Classification accuracy, and misclassification analysis for the years 1 to
3 of the control sample in the study of Zopounidis and Doumpos (1997) 143
Table S.9: Discriminant function s coefficients in the study of Zopounidis and
Doumpos(1997) 144
Table S. 10:Classification accuracy and misclassification analysis of grouping
provided by discriminant analysis for the years 1 to S of the basic
sample in the study of Zopounidis and Doumpos (1997) 144
Table 5.11:Classification accuracy and misclassification analysis of grouping
provided by discriminant analysis for the years 1, 2, 3 of the control
sample in the study of Zopounidis and Doumpos (1997) 145
I
i
LIST OF FIGURES j
Figure 1.1: The RPA1 tree in Frydman, Altaian and Kao (1985) 17
Figure 1.2: The RPA2 tree in Frydman, Altaian and Kao (1985) 18
Figure 1.3: The production system proposed by Hansen and Messier (1988) 22
Figure 1.4: The form of a neural network 23
Figure 3.1: Profiles and categories in ELECTRE TRI 47
Figure 3.2: Curve of concordance index cjlfl^i) 48
Figure 3.3: Curve of discordance index. D/a,ri) 49
Figure 3.4: Evaluation of business failure risk by ELECTRE TRI 52
Figure 4.1: Concordance and discordance indexes for object x and rule r, with
respect to attribute al 76
Figure5.1: The business failure risk evaluation process by MINORA System 121
Figure 5.2: Ranking versus global utility (First step) in the study of Zopounidis
(1987) 127
Figure 5.3: Ranking versus global utility (Second step) in the study of Zopounidis
(1987) 129
Figure 5.4: Ranking versus global utility (Third step) in the study of Zopounidis
(1987) 133
Figure 5.5: Ranking versus global utility (Fourth step) in the study of Zopounidis
(1987) 134
Figure 5.6: Distribution of the classes on the assessed utility 137
Figure 5.7: Marginal utilities of the evaluation criteria in the the study of
Zopounidis and Doumpos (1997) 140
|
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| id | DE-604.BV013385311 |
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| indexdate | 2024-07-09T18:44:55Z |
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| language | English |
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| spelling | Zopounidis, Constantin 1958- Verfasser (DE-588)115594213 aut Multicriteria decision aid methods for the prediction of business failure Constantin Zopounidis and Augustinos I. Dimitras Boston [u.a.] Kluwer 1998 XXIV, 171 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Applied optimization 12 Banqueroute - Prévision ram Besliskunde gtt Entreprises - Disparition - Prévision ram Faillissement gtt Prognoses gtt Teoria da decisão (administração executiva) larpcal Bankruptcy -- Forecasting Business failures -- Forecasting Multikriteria-Entscheidung (DE-588)4126083-1 gnd rswk-swf Multikriteria-Entscheidung (DE-588)4126083-1 s DE-604 Dimitras, Augustinos I. Verfasser aut Applied optimization 12 (DE-604)BV010841718 12 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009130710&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Zopounidis, Constantin 1958- Dimitras, Augustinos I. Multicriteria decision aid methods for the prediction of business failure Applied optimization Banqueroute - Prévision ram Besliskunde gtt Entreprises - Disparition - Prévision ram Faillissement gtt Prognoses gtt Teoria da decisão (administração executiva) larpcal Bankruptcy -- Forecasting Business failures -- Forecasting Multikriteria-Entscheidung (DE-588)4126083-1 gnd |
| subject_GND | (DE-588)4126083-1 |
| title | Multicriteria decision aid methods for the prediction of business failure |
| title_auth | Multicriteria decision aid methods for the prediction of business failure |
| title_exact_search | Multicriteria decision aid methods for the prediction of business failure |
| title_full | Multicriteria decision aid methods for the prediction of business failure Constantin Zopounidis and Augustinos I. Dimitras |
| title_fullStr | Multicriteria decision aid methods for the prediction of business failure Constantin Zopounidis and Augustinos I. Dimitras |
| title_full_unstemmed | Multicriteria decision aid methods for the prediction of business failure Constantin Zopounidis and Augustinos I. Dimitras |
| title_short | Multicriteria decision aid methods for the prediction of business failure |
| title_sort | multicriteria decision aid methods for the prediction of business failure |
| topic | Banqueroute - Prévision ram Besliskunde gtt Entreprises - Disparition - Prévision ram Faillissement gtt Prognoses gtt Teoria da decisão (administração executiva) larpcal Bankruptcy -- Forecasting Business failures -- Forecasting Multikriteria-Entscheidung (DE-588)4126083-1 gnd |
| topic_facet | Banqueroute - Prévision Besliskunde Entreprises - Disparition - Prévision Faillissement Prognoses Teoria da decisão (administração executiva) Bankruptcy -- Forecasting Business failures -- Forecasting Multikriteria-Entscheidung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009130710&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV010841718 |
| work_keys_str_mv | AT zopounidisconstantin multicriteriadecisionaidmethodsforthepredictionofbusinessfailure AT dimitrasaugustinosi multicriteriadecisionaidmethodsforthepredictionofbusinessfailure |