Combining data mining and Game Theory in manufacturing strategy analysis

Wang, Yi

doi:10.1007/s10845-007-0054-4

Cited by 11 publications

(5 citation statements)

References 2 publications

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“…Game theory is an applied branch of mathematics used in many domains such as economics (Mendoza-Alonzo et al, 2019;Zameer et al, 2018), politics, management (Prasad et al, 2019), manufacturing (Wang, 2007;Trappey et al, 2013), mathematics, engineering (Ahmadi-Javid andHoseinpour, 2018;Xiaohui et al, 2014), organization, etc. The game theory concerns the mathematical study of the decision-making process and mathematical models of conflict and cooperation.…”

Section: Game Theorymentioning

confidence: 99%

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Development of balanced scorecard for manufacturing using interpretive structural modeling and game theory

Abedian

Amindoust

Jouzdani

et al. 2022

JAMR

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PurposeThe purpose of the study is to assess manufacturing firm performance indicators using a reasonably comprehensive integrated BSC-Game model to empirically determine the importance of the perspectives and indicators under evaluation and the best combination of indicators.Design/methodology/approachAfter identification of manufacturing indicators of the firm, the Shapley value index is used as the solution of the cooperative game to determine the importance of the perspectives and indicators under evaluation and the best combination of indicators to facilitate the achievement of target goals.FindingsThe game theory approach is used as a technique to rank BSC perspectives of the firm's manufacturing performance. The results reveal that the customers' perspective receives the highest ranking. The knowledge sharing, new technology, customer satisfaction and sale profitability are considered as the best combination of BSC indicators.Originality/valueThe integrated BSC-Game framework, approach and outcomes can be beneficial to practitioners and researchers who aim to select the proper indicators’ policy in manufacturing performance field.

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Section: Game Theorymentioning

confidence: 99%

“…, 2018), politics, management (Prasad et al. , 2019), manufacturing (Wang, 2007; Trappey et al. , 2013), mathematics, engineering (Ahmadi-Javid and Hoseinpour, 2018; Xiaohui et al.…”

Section: Literature Reviewmentioning

confidence: 99%

Development of balanced scorecard for manufacturing using interpretive structural modeling and game theory

Abedian

Amindoust

Jouzdani

et al. 2022

JAMR

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“…Giampiero considered a scenario where users are competing for substitutable resources or processes, and games with four different types of solution space are presented by a dynamic plot approach where the equilibrium and the process to reach a negotiated compromise solution have different characters [9]. Yi Wang used game theory in manufacturing decision-making applying data mining algorithms to extract information from databases and construct rules, and further more seek the equilibrium results by the extensive representation of the game mining [10].…”

Section: A Manufacturing Strategy Processmentioning

confidence: 99%

“…Data mining approaches based on computational intelligence has created new intelligent tools for extraction of useful information and knowledge [10] [13]. In general, Data mining functions can be divided into two broad categories: discovery DM and predictive DM.…”

Section: B Production Function and Variablesmentioning

confidence: 99%

A game theoretic approach to product-mix resource allocation

Yunzhi

Yanhua

et al. 2010

2010 5th IEEE Conference on Industrial Electronics and Applications

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In view of the common issue of product-mix resource allocation decision under limited manufacturing resource, this article proposes a new approach based on game theory. Firstly, a quantification method is applied to represent the utility of manufacturing resource and strategy profile, and then a multidimension game model is presented using these quantified manufacturing data as element of game theory. By solving the game model, the Nash equilibrium solution is regarded as optimal resource allocation strategy. The goal of the solution is to maximize the individual profit of each product. The desired equilibrium will meet the requirements for resource by the greatest degree to make each product achieve optimal production status, simultaneously the enterprise will get higher rate of return on investment.

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“…Lately, there has been a rise in the number of statistical models that use economic analysis and game theory to better understand the behaviour of the relevant players in many applications. It has been used to improve manufacturing strategies (Wang, 2007), in credit card fraud detection (Vatsa et al, 2005), and in phishing detection for spam filtering (L 'Huillier et al, 2009), to name a few. In this paper, we present a procedure that extends application credit scorecards by differentiating defaulters into two groups, those who default due to the lack of willingness to repay, and those who fail to pay because they do not have the capacity to do so.…”

Section: Introductionmentioning

confidence: 99%

Improving credit scoring by differentiating defaulter behaviour

Bravo

Thomas

Weber

2015

Journal of the Operational Research Society

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We present a methodology for improving credit scoring models by distinguishing two forms of rational behaviour of loan defaulters. It is common knowledge among practitioners that there are two types of defaulters, those who do not pay because of cash flow problems ('Can't Pay'), and those that do not pay because of lack of willingness to pay ('Won't Pay'). This work proposes to differentiate them using a game theory model that describes their behaviour. This separation of behaviours is represented by a set of constraints that form part of a semi-supervised constrained clustering algorithm, constructing a new target variable summarizing relevant future information. Within this approach the results of several supervised models are benchmarked, in which the models deliver the probability of belonging to one of these three new classes (good payers, 'Can't Pays', and 'Won't Pays'). The process improves classification accuracy significantly, and delivers strong insights regarding the behaviour of defaulters.

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Combining data mining and Game Theory in manufacturing strategy analysis

Cited by 11 publications

References 2 publications

Development of balanced scorecard for manufacturing using interpretive structural modeling and game theory

Development of balanced scorecard for manufacturing using interpretive structural modeling and game theory

A game theoretic approach to product-mix resource allocation

Improving credit scoring by differentiating defaulter behaviour

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