Game theory-based environmental LCC control behavior analysis

Zhang, Xiaoyan; Zhou, Yanju; Qing-lan, Han

doi:10.1016/j.jclepro.2018.11.237

Cited by 11 publications

(7 citation statements)

References 20 publications

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“…Among them, Huang and Ge research is based on the theory of planned behavior (TPB), introducing consumer cognitive state, product cognition, and incentive policy measures and constructing an influence mechanism model of electric vehicle purchase intention [6]. Zhang et al have used evolutionary game models to study how environmental life cycle cost (E-LCC) control has affected the decisionmaking behavior of manufacturers [7]. Olaleye research has combined and extended the unified theory of acceptance and use of technology with the theory of trust and satisfaction to explain the usefulness of mobile applications to retail customers [8].…”

Section: Introductionmentioning

confidence: 99%

Consumer Behavior Based on Big Data and Cloud Computing and Construction of Customer Perception Mobile Terminal System

Shu

Ho³

et al. 2022

Security and Communication Networks

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The arrival of the era of big data has realized the transformation of people’s production and lifestyle. At the same time, it also increases people’s desire to consume, and the feedback behavior of consumers’ comments and ratings is the feedback of users’ experience in merchants’ products, that is, the matching of products to consumer needs and preferences. When the product can reach the user’s satisfaction level, the customer-aware mobile terminal system is constructed and optimized by using the advanced methods and technologies of big data information display and the principles and laws of the collaborative filtering algorithm in cloud computing. It ensures the ecological development of the consumer industry. Among them, in the experimental evaluation of the collaborative filtering recommendation algorithm, the mean absolute error (MAE) and root mean square error (RMSE) values of the SVD++ algorithm are higher than those of the other three algorithm models, indicating that other algorithm models can effectively improve the accuracy of the recommendation algorithm. A cross-sectional comparative analysis of experimental results has shown that, as the number of neighbors increased, the MAE and RMSE values first decreased and then increased. When the number of neighbors N is 25, the MAE and RMSE reach the minimum value, so the optimal number of neighbors is 25. Therefore, it is very important to use the collaborative filtering algorithm to analyze and construct the consumer behavior and customer perception mobile terminal system.

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Section: Introductionmentioning

confidence: 99%

Consumer Behavior Based on Big Data and Cloud Computing and Construction of Customer Perception Mobile Terminal System

Shu

Ho³

et al. 2022

Security and Communication Networks

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“…Evolutionary game theory combines the analytical approach of game theory with that of evolutionary dynamics. Thus, it is more accurate to reflect the dynamic equilibrium of game behavior between limited rational groups (Smith and Price, 1973; Chen and Hu, 2018; Zhang et al , 2019). Nowadays, evolutionary game theory is an important analytical method that has been widely applied in social governance (Kennedy, 1994; Moledina et al , 2003), governmental administration (Barrett, 1994; Liu et al , 2017a, b; Wu et al , 2017) and business operations and management fields (Wang and Zheng, 2018; Zha et al , 2018).…”

Section: Methodsmentioning

confidence: 99%

An evolutionary game analysis of user-pay public–private partnership projects

Song

Yuan

et al. 2020

ECAM

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PurposeWith the growing demand for infrastructure and public services in recent years, PPP-UP have attracted a great deal of attention. However, while the user focuses on the payment for use and the private sector is concerned with its return on investment, the public sector pays more attention to the efficient utilization of public funds. In order to analyze the willingness of each stakeholder to join PPP-UP, an evolutionary game model involving the three parties is constructed.Design/methodology/approachAn evolutionary game model is established that considers the users and the public and private sectors in user-pay public-private-partnership projects (PPP-UP). Eight scenarios of equilibriums and the game's evolutionary stable strategies are analyzed, and the corresponding stability conditions are then obtained. A situation where all three players are willing to cooperate in theory is also examined. The key influencing parameters that affect cooperation behaviors are further discussed.FindingsFirst, the results illustrate that by properly adjusting the influencing factors, the cooperation status among the three parties can be changed along with certain evolutionary trends. Second, it is hard to modify unsatisfactory evolutionary stability by small changes in both the price compensation of and the construction and operation compensation. Third, it is necessary to involve the users in the decision-making process in PPP-UP and take their demands regarding benefits and payments into account.Originality/valueIn this paper, we focus on PPP-UP to research interactions among the public and private sectors and the users. Based on the analysis of the evolutionary game, to facilitate the successful implementation and development of a project, several conditions are needed to ensure tripartite cooperation. Several recommendations are then proposed for decision-makers in PPP-UP.

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“…Environmental cost control refers to the process by which enterprises control and manage environmental costs through scientific means, thereby predicting, calculating, evaluating, and analyzing environmental costs in an organized manner. According to the requirements of relevant national laws and regulations, enterprises can achieve the goal of green and sustainable operation [9]. Environmental costs are different from the general costs of enterprises.…”

Section: Environmental Cost Control Of Enterprisesmentioning

confidence: 99%

The Analysis of Environmental Cost Control of Manufacturing Enterprises Using Deep Learning Optimization Algorithm and Internet of Things

Jin

Chen

2022

Computational Intelligence and Neuroscience

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Under the background of the Internet of things (IoT), the problems between the actual production and the environment are also prominent. The environmental cost control in the production process of manufacturing enterprises are discussed to reduce the environmental cost and promote the improvement of production efficiency. First, the environmental cost under the background of IoT is analyzed. Also, the environmental cost control methods in the production process of traditional manufacturing enterprises are investigated. Second, based on the principle of traditional genetic algorithm, the fast-nondominated sorting genetic algorithm (NSGA-II) of multiobjective genetic algorithm is introduced to complete the optimization of BP neural network (BPNN) algorithm in deep learning (DL), and the multiobjective GA optimization BPNN model is established. Finally, the multiobjective GA algorithm is used to empirically analyze the environmental cost control capability of a paper-making enterprise. It is compared with enterprises with excellent and poor environmental cost control capabilities in the same industry to find out secondary indexes. The results show that environmental costs have long-term and economic characteristics. The global search ability of BPNN optimized by multiobjective GA is improved, and the local optimal dilemma is avoided. Through empirical analysis, it is found that the comprehensive capability of the environmental cost control of the enterprise is better, scored 79 or more, and the indexes of insufficient development and advantages are obtained. As IoT rapidly develops, it is necessary to further improve the ability of enterprises in environmental cost management, which is very important to promote the development of enterprises and enhance their core competitiveness. It is hoped that this investigation can provide certain reference significance for improving the environmental cost management capability of enterprises, increasing production efficiency, and reducing environmental costs.

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Game theory-based environmental LCC control behavior analysis

Cited by 11 publications

References 20 publications

Consumer Behavior Based on Big Data and Cloud Computing and Construction of Customer Perception Mobile Terminal System

Consumer Behavior Based on Big Data and Cloud Computing and Construction of Customer Perception Mobile Terminal System

An evolutionary game analysis of user-pay public–private partnership projects

The Analysis of Environmental Cost Control of Manufacturing Enterprises Using Deep Learning Optimization Algorithm and Internet of Things

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