scholarly journals Determination and Verification of the Key Assessment Indicators for the Insurance Market by Applying the Decomposition Multi-attribute Methods and Regression Analysis

2019 ◽  
Vol 10 (1) ◽  
pp. 5-24
Author(s):  
Martina Borovcová ◽  
Adéla Špačková
Keyword(s):  
Regression Analysis ◽  
Analytic Network Process ◽  
Insurance Market ◽  
Insurance Companies ◽  
Analytic Hierarchy ◽  
Insurance Contracts ◽  
Insurance Benefit ◽  
Comparison Approach ◽  
Network Process ◽  
Quantitative Indicators

The aim of the article is to determine and verify the key assessment indicators for the insurance market by applying the decomposition multi-attribute methods and regression analysis. The assessed specific indicators are qualitative indicators (insurance penetration, claim ratio) and quantitative indicators (gross premium, insurance benefit, number of insurance contracts, number of settled insurance claims, number of employees, number of commercial insurance companies, concentration of the insurance market, and more). The decomposition multi-criteria AHP method (analytic hierarchy process) and ANP method (analytic network process) based on the Saaty pair comparison approach are described, including the computation procedure. The described methods are then applied to determine the preferences of the indicators for the insurance market. Subsequently, a particular regression model is created. Our findings reveal the resulting preferences of individual indicators of the insurance market evaluation and key assessment indicators.

scholarly journals Using the Analytical Network Process to Select the Best Strategy for Reducing Risks in a Supply Chain

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
L. Hosseini ◽  
R. Tavakkoli-Moghaddam ◽  
B. Vahdani ◽  
S. M. Mousavi ◽  
R. Kia
Keyword(s):  
Supply Chain ◽  
Multicriteria Decision Making ◽  
Analytic Network Process ◽  
Supply Chain Network ◽  
Total Quality ◽  
Analytic Hierarchy ◽  
Network Process ◽  
Supply Chain Risks ◽  
Hierarchy Process ◽  
Different Levels

This paper considers four types of the most prominent risks in the supply chain. Their subcriteria and relations between them and within the network are also considered. In a supply chain, risks are mostly created by fluctuations. The aim of this study is to adopt a strategy for eliminating or reducing risks in a supply chain network. Having various solutions helps the supply chain to be resilient. Therefore, five alternatives are considered, namely, total quality management (TQM), leanness, alignment, adaptability, and agility. This paper develops a new network of supply chain risks by considering the interactions between risks. Perhaps, the network elements have interacted with some or all of the factors (clusters) or subfactors. We constitute supply chain risks in the analytic network process (ANP), which attracted less attention in the previous studies. Most of the studies about making a decision in supply chains have been applied in analytic hierarchy process (AHP) network. The present study considers the ANP as a well-known multicriteria decision making (MCDM) technique to choose the best alternative, because of the interdependency and feedbacks of different levels of the network. Finally, the ANP selects TQM as the best alternative among the considered ones.

scholarly journals Integration of AHP and GTMA to Make a Reliable Decision in Complex Decision-Making Problems: Application of the Logistics Provider Selection Problem as a Case Study

Symmetry ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 766
Author(s):  
Danijela Tuljak-Suban ◽  
Patricija Bajec
Keyword(s):  
Decision Making ◽  
Analytic Network Process ◽  
Third Party ◽  
Selection Problem ◽  
New Method ◽  
Analytic Hierarchy ◽  
Decision Making Problem ◽  
Network Process ◽  
Complex Decision Making ◽  
Complex Decision

When solving a Multi-Criteria Decision-Making problem of any degree of complexity, many researchers rely on the analytic hierarchy process (AHP). To consider mutual connections between criteria and clusters at the same level and not only the hierarchical structure between criteria and subcriteria, researchers often upgrade from AHP to the Analytic Network Process (ANP), which also examines the interdependency of criteria. However, the ANP method requires a large number of pairwise comparisons. In the case of a complex decision-making problem, the authors of this paper suggest upgrading the AHP method with the graph theory and matrix approach (GTMA) for several reasons: (1) The new method is based on digraphs and permanent value computation, which does not require a hypothesis about interdependency; (2) in case of similar alternatives, the distinguishable coefficient of the new method is higher than those computed for AHP and ANP; (3) the new method allows decision makers to rank comparable alternatives and to combine structurally similar methods without increasing the number of comparisons and the understanding of the results. The developed method (AH-GTMA) is validated by a numerical example of a complex decision-making problem based on a symmetrical set of similar alternatives, a third party logistic provider (3PLP) selection problem.

Comparative Analysis of AHP and ANP Model for Lean Production System Justification

2014 ◽  
Vol 591 ◽  
pp. 197-201 ◽  
Author(s):  
K. Venkataraman ◽  
B. Vijaya Ramnath ◽  
S. Kannapan ◽  
L. Bruce Selva Vinoth ◽  
K. Vetri Velmurugan
Keyword(s):  
Comparative Analysis ◽  
Manufacturing System ◽  
Analytic Network Process ◽  
Computer Integrated Manufacturing ◽  
Lead Times ◽  
Analytic Hierarchy ◽  
Industrial Organizations ◽  
Network Process ◽  
Great Pressure ◽  
Tools And Techniques

Industrial organizations are in great pressure to reduce costs, improve quality, cut down on lead times and improve flexibility. Companies are thus turning their attention to implement lean. This has created urgency to apply new tools and techniques to reduce various wastes. This paper deals with comparative analysis of analytic hierarchy process (AHP) and analytic network process (ANP) to select the best manufacturing process among traditional, lean and computer integrated manufacturing system. Six criteria such as quality, flexibility, productivity, innovation, morale and competitive advantage are considered for evaluation and also considering their sub criteria, the best manufacturing system is selected.

Prioritizing Risk-level Factors in Comprehensive Automobile Insurance Management: A Hybrid Multi-criteria Decision-making Model

2020 ◽  
pp. 097215092093228
Author(s):  
Zahra Shams Esfandabadi ◽  
Meisam Ranjbari ◽  
Simone Domenico Scagnelli
Keyword(s):  
Insurance Market ◽  
Insurance Companies ◽  
Risk Level ◽  
Automobile Insurance ◽  
Two Phase ◽  
Analytic Hierarchy ◽  
Factors Affecting ◽  
Risk Levels ◽  
Fuzzy Delphi ◽  
The Individual

An efficient risk-level prediction for newly proposed insurance policies plays a significant role in the survival of companies in the highly competitive insurance market. In Iran, risk assessment in comprehensive automobile insurance, which is a part of motor insurance, is only based on the vehicle attributes without proper consideration of personal and behavioural characteristics of driver(s). As a result, pricing is unfair in most of the cases and this can put insurance companies in an unfavourable financial position due to attracting high-risk drivers instead of low-risk ones. In this scenario, to identify and prioritize important factors affecting risk levels and to move towards a fair ratemaking, a two-phase process based on fuzzy Delphi method (FDM) and fuzzy analytic hierarchy process (FAHP) is proposed in this research. Additionally, similarity aggregation method (SAM) is applied to combine the individual fuzzy opinions of the surveyed experts into a group fuzzy consensus opinion. The results of this empirical study contribute to the insurance market of Iran by proposing appropriate weighting of the relevant risk factors to support stakeholders and policymakers for assessing risks more accurately, as well as designing more effective databases and insurance proposal forms.

Diminishing Utility Decision Model for Weighting Criteria

2015 ◽  
Vol 14 (06) ◽  
pp. 1263-1284 ◽  
Author(s):  
Jih-Jeng Huang ◽  
Masahiro Inuiguchi
Keyword(s):  
Analytic Hierarchy Process ◽  
Decision Model ◽  
Marginal Utility ◽  
Analytic Network Process ◽  
Analytic Hierarchy ◽  
Numerical Examples ◽  
Absorbing State ◽  
Network Process ◽  
Diminishing Marginal Utility ◽  
Hierarchy Process

The analytic hierarchy/network process (analytic hierarchy process (AHP)/analytic network process (ANP)) became the most popular tool for weighting criteria in the field of multiple criteria analysis during the 1980s. However, these models often suffer from criticisms because of their theoretical and practical problems. In this paper, the diminishing utility decision model (DUDM) is proposed in order to retain the pros and avoid the cons of the AHP and ANP for weighting criteria. The DUDM integrates the AHP and the concept of diminishing marginal utility in order to model the main and interaction weights of criteria, respectively. From the results of the numerical examples, it can be seen that the proposed method can solve two major limitations of the ANP. First, the proposed method can significantly reduce the number of questions that are asked in the ANP. Second, the proposed method can ensure convergence in many situations and avoid the problem of the ANP with regard to the absorbing state.

scholarly journals A Warehouse Social and Environmental Performance Metrics Framework

2020 ◽  
Vol 32 (4) ◽  
pp. 513-526
Author(s):  
Patricija Bajec ◽  
Danijela Tuljak-Suban ◽  
Ivona Bajor
Keyword(s):  
Supply Chain ◽  
Performance Metrics ◽  
Social Performance ◽  
Methodological Approach ◽  
Analytic Network Process ◽  
Performance Measurement System ◽  
Analytic Hierarchy ◽  
Fuzzy Delphi ◽  
Network Process ◽  
Social And Environmental Performance

To improve the supply chain performance in all three aspects of sustainability (social, economic, and environmental), a comprehensive sustainable performance measurement system that captures all the supply chain partners’ efforts and commitments is required. Warehouse, as the second largest logistics source of environmental pollution in the supply chain has been almost completely overlooked and ignored in the past studies. To fill this gap, a warehouse performance metrics framework for environmental and social performance measures was proposed using a novel Fuzzy Delphi and Best-worst methodological approach. The method is less time-consuming than the Analytic Hierarchy Process or Analytic Network Process, it does not address whether criteria are dependent or independent, requires fewer comparisons of criteria, but still produces reliable and credible results. The presented framework consists of 32 equally formulated environmental and social performance indicators, including formulas and measurement units. The 14 most important indicators are ranked according to the requirements of different stakeholders.

scholarly journals A Markovian-QFD approach in addressing the changing priorities of the customer needs

2016 ◽  
Vol 33 (8) ◽  
pp. 1062-1075 ◽  
Author(s):  
Mehdi Rajabi Asadabadi
Keyword(s):  
Markov Chain ◽  
Markov Chains ◽  
Quality Function Deployment ◽  
Analytic Network Process ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Customer Needs ◽  
Customer Preferences ◽  
Network Process ◽  
Qfd Method

PurposeThe purpose of this paper is to introduce a solution to the problem of changing priorities of customer needs (CNs) in quality function deployment (QFD). Customer preferences and priorities are not very stable and they may change before products are ready for the market. Therefore, finding CNs accurately is a key to reach a higher level of customer satisfaction through improving products. Design/methodology/approachIn the proposed model, a Markov chain is employed to model the changing priorities of CNs. The Markov chain finds a pattern of future CNs, the main inputs of QFD. The QFD method is applied to translate CNs into product requirements (PRs). The analytic network process (ANP) is attached to QFD to ensure that all the relations among the elements, inner and outer, are taken into consideration during the translation process. Thus, CNs are received and adjusted by a Markov chain. FindingsThe application of Markov chains for an ANP-QFD model develops an adequate method of finding a pattern of changing priorities of CNs. This pattern enables the ANP-QFD method to work independent of the initial CNs, and originates a Markovain ANP-QFD. Originality/valueThis study originates a stochastic ANP-QFD model. There have been several papers employing various tools and techniques such as the ANP or analytic hierarchy process for QFD to find accurate relations between PRs and CNs. While there are a few papers applying Markov chains to predict the future of the relations of QFD, there is no study which traces the changes in priorities of the CNs during the improvement process. This is addressed by applying a Markovian ANP-QFD. The model is validated through a case study.

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