scholarly journals Multiobjective Decision-Making for Technical Characteristics Selection in a House of Quality

2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Jianmin Xie ◽  
Qin Qin ◽  
Maoting Jiang
Keyword(s):  
Decision Making ◽  
Influencing Factor ◽  
Relative Weight ◽  
Technical Characteristic ◽  
Technical Property ◽  
Market Demand ◽  
House Of Quality ◽  
Fuzzy Front End ◽  
Multiobjective Decision Making ◽  
Decision Making Model

Technical characteristics are an important influencing factor in fuzzy front-end of product innovation design and also an important output of the house of quality. The analysis and decision-making of technical characteristics are conducive to the rational allocation of resources according to their own advantages and the design of products in line with market demand. In view of the multiple objective constraints and internal fuzziness of technical property selection in the house of quality, the traditional methods have great limitations on the decision-making of technical property. Therefore, this paper proposes a multiobjective decision-making method for technical property selection in the house of quality, which aims to calculate and modify the basic importance of technical property. Based on the rough set algorithm, the basic importance of technical characteristics is determined by using the correlation matrix between consumer demand and technical characteristics, and the relative weight of multiple objectives is determined by “least squares.” On this basis, the multiobjective decision-making model of technical characteristic selection is established and calculated. At last, an example of mobile phone product design was used to verify the practicability and effectiveness of the method.

A multi-criteria decision making model for outsourcing maintenance services

Facilities ◽  
2015 ◽  
Vol 33 (3/4) ◽  
pp. 229-244 ◽  
Author(s):  
Mohammad A. Hassanain ◽  
Sadi Assaf ◽  
Abdul-Mohsen Al-Hammad ◽  
Ahmed Al-Nehmi
Keyword(s):  
Decision Making ◽  
Air Conditioning ◽  
Relative Weight ◽  
Equal Weight ◽  
Multi Criteria Decision Making ◽  
Content Type ◽  
Air Conditioning Systems ◽  
Decision Making Model ◽  
Outsourcing Decision

Purpose – The purpose of this paper is to present the development of a multi-criteria decision-making model for use by maintenance managers to consider before making a decision on outsourcing. Design/methodology/approach – Thirty-eight factors were identified for outsourcing maintenance services. These factors were grouped under six categories, namely: “strategic”, “management”, “technological”, “quality”, “economic” and “function characteristics”. The Analytic Hierarchy Process, as a multi-criteria decision-making model, was introduced and applied as an approach for maintenance managers in Saudi Arabian universities to consider before making a decision on outsourcing. A case study on the outsourcing decision of maintenance services of air-conditioning systems was carried out to apply the developed model. Findings – Data analysis indicated that all outsourcing decision groups of factors have almost equal weight, with the “quality” group of factors having the highest weight and the “technological” group of factors having the least weight. Further, the analysis indicated, in general, that the recommended decision for the maintenance managers is to outsource. However, an application of the developed model through a case study on the outsourcing of maintenance services of air-conditioning systems showed that the recommended action is not to outsource. Originality/value – The presented approach in this paper could be of practical benefit to maintenance managers in their decision making of whether or not to outsource maintenance services. The factors in the model were identified through a literature survey of research carried out in different countries. Therefore, the model could be applied in different settings, depending on the relative weight of the factors by the users.

scholarly journals Research on inventory pledge Financing Pledge Decision under Internet of Things Technology

2020 ◽  
Vol 4 (2) ◽  
pp. 80
Author(s):  
Zhang Xiangxiang ◽  
Gao Gengjun
Keyword(s):  
Decision Making ◽  
Internet Of Things ◽  
Coverage Rate ◽  
The Internet ◽  
Decision Making Process ◽  
Market Demand ◽  
Decision Making Model ◽  
Internet Of Things Technology ◽  
The Internet Of Things

Inventory pledge financing not only solves the financing difficulties of small and medium-sized enterprises, but also opens up business channels for banks. Under the random market demand, this article studies the pledge decision-making of perishable pledges in the inventory pledge business, and establishes that banks do not adopt and adopt the Internet of Things. The pledge rate decision-making model in the two technical situations aims at maximizing the profit at the end of the pledge period. The factors in the model such as the pledge rate, end-of-period income, and IoT technology coverage rate are analyzed respectively, and finally the decision-making process is verified through calculation examples. Studies have shown that, within a certain range, banks can use IoT technology to supervise pledges to obtain greater benefits. However, as the coverage of IoT technology increases, bank revenues continue to decrease, so to obtain greater benefits requires the Internet of Things technology set by the bank Invest.

scholarly journals A dual factor decision making model in green manufacturing

2021 ◽  
Author(s):  
Bahador Jamshidy
Keyword(s):  
Decision Making ◽  
Goal Programming ◽  
Product Information ◽  
Positive Impact ◽  
Green Manufacturing ◽  
Product Recovery ◽  
Market Demand ◽  
Decision Making Model ◽  
Second Category ◽  
The Impact

This study focuses on the evaluation of different methods of product recovery for GM. The evaluation is conducted through the application of a decision making model. The model evaluates product recovery options on the basis of two categories: optimization of objective factors and market demand. The first category in the model focuses on optimization of five objective factors, including environmental impact (E), cost (C), quality (Q), resource consumption (R), and time (T). Goal programming is used to solve the optimization problem. The goal programming is supported by the construction of a decision making tree with three branches: remanufacturing, refurbishing, and current manufacturing. The solution of the decision tree helps determine the best method of product recovery for GM. The second category in the model focuses on the evaluation of market demand. This further supports the selection of the best method for product recovery. To evaluate market demand, a Bayesian forecasting model is used in the construction of a decision making tree. The study shows that the availably of products information including the objective factors and market demand, has a positive impact on making product recovery decisions. It also shows how recovery decisions can be modeled in decision making tress to represent the impact of product information on those decisions.

scholarly journals Coordination Strategy of the Supply Chain with Consumer Preferences under the “Presale and Spot-Sale” Mode

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Xiaogang Cao ◽  
Hui Wu ◽  
Kebing Chen ◽  
Hui Wen
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Consumer Preferences ◽  
Consumer Preference ◽  
Third Party ◽  
Equilibrium Strategy ◽  
Market Demand ◽  
Exogenous Variables ◽  
Coordination Strategy ◽  
Decision Making Model

In recent years, the market economy has been booming, and the demand of consumers has begun to become diversified. Consumers’ preferences for products, the sensitivity of product prices, and other factors can often affect the market demand and also make enterprises realize the importance of consumer preferences. The decision-making model of the supply chain with consumer preference composed of a retailer and a third-party presale platform is established, and we analyze the implementation of a single presale model, a single spot-sale model, and decision-making models under the “presale and sale” mode. The equilibrium strategy of centralized decision and decentralized decision under the mode of “presale and sale” is compared, and the influence of the proportion of informed consumers and the exogenous variables of cross-period discount on supply chain decision is further analyzed. The coordination strategy of the decentralized decision supply chain under the mode of “presale and sale” is put forward, and the coordinated operation among supply chain members is realized. The results show that compared with other sales models, the “presale and spot-sale” model is more beneficial to the profit of the supply chain.

scholarly journals A dual factor decision making model in green manufacturing

2021 ◽  
Author(s):  
Bahador Jamshidy
Keyword(s):  
Decision Making ◽  
Goal Programming ◽  
Product Information ◽  
Positive Impact ◽  
Green Manufacturing ◽  
Product Recovery ◽  
Market Demand ◽  
Decision Making Model ◽  
Second Category ◽  
The Impact

This study focuses on the evaluation of different methods of product recovery for GM. The evaluation is conducted through the application of a decision making model. The model evaluates product recovery options on the basis of two categories: optimization of objective factors and market demand. The first category in the model focuses on optimization of five objective factors, including environmental impact (E), cost (C), quality (Q), resource consumption (R), and time (T). Goal programming is used to solve the optimization problem. The goal programming is supported by the construction of a decision making tree with three branches: remanufacturing, refurbishing, and current manufacturing. The solution of the decision tree helps determine the best method of product recovery for GM. The second category in the model focuses on the evaluation of market demand. This further supports the selection of the best method for product recovery. To evaluate market demand, a Bayesian forecasting model is used in the construction of a decision making tree. The study shows that the availably of products information including the objective factors and market demand, has a positive impact on making product recovery decisions. It also shows how recovery decisions can be modeled in decision making tress to represent the impact of product information on those decisions.

Applying the Multi-Criteria Decision Making Model for Ranking Commercial Banks: The Case of Vietnam

2019 ◽  
pp. 125-133
Author(s):  
Duong Truong Thi Thuy ◽  
Anh Pham Thi Hoang
Keyword(s):  
Decision Making ◽  
Commercial Banks ◽  
Decision Model ◽  
Business Models ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Topsis Method ◽  
Decision Making Model

Banking has always played an important role in the economy because of its effects on individuals as well as on the economy. In the process of renovation and modernization of the country, the system of commercial banks has changed dramatically. Business models and services have become more diversified. Therefore, the performance of commercial banks is always attracting the attention of managers, supervisors, banks and customers. Bank ranking can be viewed as a multi-criteria decision model. This article uses the technique for order of preference by similarity to ideal solution (TOPSIS) method to rank some commercial banks in Vietnam.

Multi-Attribute Decision-Making Model by Applying Grey Numbers

Informatica ◽  
2009 ◽  
Vol 20 (2) ◽  
pp. 305-320 ◽  
Author(s):  
Edmundas Kazimieras Zavadskas ◽  
Arturas Kaklauskas ◽  
Zenonas Turskis ◽  
Jolanta Tamošaitienė
Keyword(s):  
Decision Making ◽  
Multi Attribute Decision Making ◽  
Decision Making Model
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