Mudita Uppal, Deepali Gupta, Nitin Goyal, A. Imoize, Arun C. S. Kumar, Stephen Ojo, S. Pani, Yongsung Kim, Jaeun Choi
The Internet of Things (IoT) is a platform that manages daily life tasks to establish an interaction between things and humans. One of its applications, the smart office that uses the Internet to monitor electrical appliances and sensor data using an automation system, is presented in this study. Some of the limitations of the existing office automation system are an unfriendly user interface, lack of IoT technology, high cost, or restricted range of wireless transmission. Therefore, this paper presents the design and fabrication of an IoT-based office automation system with a user-friendly smartphone interface. Also, real-time data monitoring is conducted for the predictive maintenance of sensor nodes. This model uses an Arduino Mega 2560 Rev3 microcontroller connected to different appliances and sensors. The data collected from different sensors and appliances are sent to the cloud and accessible to the user on their smartphone despite their location. A sensor fault prediction model based on a machine learning algorithm is proposed in this paper, where the k-nearest neighbors model achieved better performance with 99.63% accuracy, 99.59% F1-score, and 99.67% recall. The performance of both models, i.e., k-nearest neighbors and naive Bayes, was evaluated using different performance metrics such as precision, recall, F1-score, and accuracy. It is a reliable, continuous, and stable automation system that provides safety and convenience to smart office employees and improves their work efficiency while saving resources.
物联网(IoT)是一个管理日常生活任务，建立物与人之间互动的平台。它的应用之一，智能办公室，使用互联网监控电器和传感器数据使用自动化系统，在本研究中提出。现有办公自动化系统的一些局限性是用户界面不友好，缺乏物联网技术，成本高，或无线传输范围有限。因此，本文提出了一种基于物联网的办公自动化系统的设计和制造，该系统具有友好的智能手机界面。对传感器节点进行实时数据监控，进行预测性维护。该模型使用Arduino Mega 2560 Rev3微控制器连接到不同的设备和传感器。从不同的传感器和设备收集的数据被发送到云端，用户可以通过智能手机访问这些数据，尽管他们身处何处。本文提出了一种基于机器学习算法的传感器故障预测模型，其中k近邻模型的准确率为99.63%，f1分数为99.59%，召回率为99.67%。两种模型的性能，即k近邻和朴素贝叶斯，使用不同的性能指标，如精度，召回率，f1分数和准确性进行评估。它是一个可靠、连续、稳定的自动化系统，为智能办公员工提供安全、方便，提高工作效率，节约资源。
{"title":"A Real-Time Data Monitoring Framework for Predictive Maintenance Based on the Internet of Things","authors":"Mudita Uppal, Deepali Gupta, Nitin Goyal, A. Imoize, Arun C. S. Kumar, Stephen Ojo, S. Pani, Yongsung Kim, Jaeun Choi","doi":"10.1155/2023/9991029","DOIUrl":"https://doi.org/10.1155/2023/9991029","url":null,"abstract":"The Internet of Things (IoT) is a platform that manages daily life tasks to establish an interaction between things and humans. One of its applications, the smart office that uses the Internet to monitor electrical appliances and sensor data using an automation system, is presented in this study. Some of the limitations of the existing office automation system are an unfriendly user interface, lack of IoT technology, high cost, or restricted range of wireless transmission. Therefore, this paper presents the design and fabrication of an IoT-based office automation system with a user-friendly smartphone interface. Also, real-time data monitoring is conducted for the predictive maintenance of sensor nodes. This model uses an Arduino Mega 2560 Rev3 microcontroller connected to different appliances and sensors. The data collected from different sensors and appliances are sent to the cloud and accessible to the user on their smartphone despite their location. A sensor fault prediction model based on a machine learning algorithm is proposed in this paper, where the k-nearest neighbors model achieved better performance with 99.63% accuracy, 99.59% F1-score, and 99.67% recall. The performance of both models, i.e., k-nearest neighbors and naive Bayes, was evaluated using different performance metrics such as precision, recall, F1-score, and accuracy. It is a reliable, continuous, and stable automation system that provides safety and convenience to smart office employees and improves their work efficiency while saving resources.","PeriodicalId":72654,"journal":{"name":"Complex psychiatry","volume":"44 1","pages":"9991029:1-9991029:14"},"PeriodicalIF":0.0,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78138034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abozar Zare Khafri, A. Aboumasoudi, Shakiba Khademolqorani
Small- and medium-sized enterprises (SMEs) require less formalized project management methods than large corporations. However, project management can play a significant role in implementing innovations. Even though lean-agile project management offices (LAPMO) are becoming increasingly important for SMEs, each company’s performance varies significantly due to varying innovative capabilities and the dynamism of internal and external contexts. Based on a literature study, innovative capabilities, and LAPMO, we have developed a theoretical model with 11 assumption models. As a follow-up, we conducted empirical research, including critical variable metrics, data collection and analyses, validity tests, reliability tests, regression analysis, and structural equation modeling. The model developed in this study considers the many roles that innovation capacity and project agility play in enhancing corporate performance. LAPMO mediates the relationship between innovation and performance in small and medium-sized businesses. Organizational innovation, open innovation, and innovation capabilities affect companies’ performance. In small and medium businesses, they also affect LAPMO. For small and medium-sized businesses, LAPMO mediates the relationship between organizational innovation, open innovation, and innovation capabilities.
{"title":"The Effect of Innovation on the Company's Performance in Small and Medium-Sized Businesses with the Mediating Role of Lean: Agile Project Management Office (LAPMO)","authors":"Abozar Zare Khafri, A. Aboumasoudi, Shakiba Khademolqorani","doi":"10.1155/2023/4820636","DOIUrl":"https://doi.org/10.1155/2023/4820636","url":null,"abstract":"Small- and medium-sized enterprises (SMEs) require less formalized project management methods than large corporations. However, project management can play a significant role in implementing innovations. Even though lean-agile project management offices (LAPMO) are becoming increasingly important for SMEs, each company’s performance varies significantly due to varying innovative capabilities and the dynamism of internal and external contexts. Based on a literature study, innovative capabilities, and LAPMO, we have developed a theoretical model with 11 assumption models. As a follow-up, we conducted empirical research, including critical variable metrics, data collection and analyses, validity tests, reliability tests, regression analysis, and structural equation modeling. The model developed in this study considers the many roles that innovation capacity and project agility play in enhancing corporate performance. LAPMO mediates the relationship between innovation and performance in small and medium-sized businesses. Organizational innovation, open innovation, and innovation capabilities affect companies’ performance. In small and medium businesses, they also affect LAPMO. For small and medium-sized businesses, LAPMO mediates the relationship between organizational innovation, open innovation, and innovation capabilities.","PeriodicalId":72654,"journal":{"name":"Complex psychiatry","volume":"30 1","pages":"4820636:1-4820636:26"},"PeriodicalIF":0.0,"publicationDate":"2023-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88455041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kelong Li, Chi Xie, Ying Ouyang, Tingcheng Mo, Z. Zeng
Several public events have drawn renewed attention to the connectedness of the international stock market since the financial crisis of 2008. We investigate systemic and regional connectedness among stock markets around the world at major public events by constructing correlation networks for 46 markets based on the dynamic time-warping method. We find that (i) geographic regionalization is typically observed in the stock market network, in which France is dominant, (ii) Europe has the greatest and the Middle East and Africa the least within-region connectedness, (iii) the correlation network structure is highly integrated and compact at major public events, and global events influence the international stock market more significantly than regional events do, and (iv) the importance of China reaches its peak during the era of Sino-US trade friction, showing that public events have enormous impacts on the countries involved.
{"title":"Connectedness of International Stock Market at Major Public Events: Empirical Study via Dynamic Time Warping-Based Network","authors":"Kelong Li, Chi Xie, Ying Ouyang, Tingcheng Mo, Z. Zeng","doi":"10.1155/2023/3172181","DOIUrl":"https://doi.org/10.1155/2023/3172181","url":null,"abstract":"Several public events have drawn renewed attention to the connectedness of the international stock market since the financial crisis of 2008. We investigate systemic and regional connectedness among stock markets around the world at major public events by constructing correlation networks for 46 markets based on the dynamic time-warping method. We find that (i) geographic regionalization is typically observed in the stock market network, in which France is dominant, (ii) Europe has the greatest and the Middle East and Africa the least within-region connectedness, (iii) the correlation network structure is highly integrated and compact at major public events, and global events influence the international stock market more significantly than regional events do, and (iv) the importance of China reaches its peak during the era of Sino-US trade friction, showing that public events have enormous impacts on the countries involved.","PeriodicalId":72654,"journal":{"name":"Complex psychiatry","volume":"13 1","pages":"3172181:1-3172181:17"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82305099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper demonstrates the use of an agent-based model (ABM) to study the mechanism of social influence in the diffusion of new energy vehicles. We introduce the “consumat” cognition model so that agents with different need satisfaction thresholds have different cognitive processes. In addition, supported by survey data, our study considers more characteristics of opinion leaders, such as innovative behavior, lower sensitivity to price influence, and a better ability to judge the product quality. Through the primary group and control group experiments, the simulations demonstrated that the opinion leaders play a significant role in the spread of information and the percentage of product adoption. The results indicate that targeting opinion leaders will be a valuable marketing strategy for new energy vehicles. It also provides some advice for assessing policies that promote sustainable behaviors.
{"title":"An Agent-Based Model to Simulate the Diffusion of New Energy Vehicles","authors":"Hao Zhang, Peifeng Zhu, Zhichao Yao","doi":"10.1155/2023/6773087","DOIUrl":"https://doi.org/10.1155/2023/6773087","url":null,"abstract":"This paper demonstrates the use of an agent-based model (ABM) to study the mechanism of social influence in the diffusion of new energy vehicles. We introduce the “consumat” cognition model so that agents with different need satisfaction thresholds have different cognitive processes. In addition, supported by survey data, our study considers more characteristics of opinion leaders, such as innovative behavior, lower sensitivity to price influence, and a better ability to judge the product quality. Through the primary group and control group experiments, the simulations demonstrated that the opinion leaders play a significant role in the spread of information and the percentage of product adoption. The results indicate that targeting opinion leaders will be a valuable marketing strategy for new energy vehicles. It also provides some advice for assessing policies that promote sustainable behaviors.","PeriodicalId":72654,"journal":{"name":"Complex psychiatry","volume":"99 1","pages":"6773087:1-6773087:9"},"PeriodicalIF":0.0,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86091345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Luzhou Lin, Yuezhe Gao, Bingxin Cao, Z. Wang, Cai Jia
Accurately predicting passenger flow at rail stations is an effective way to reduce operation and maintenance costs, improve the quality of passenger travel while meeting future passenger travel demand. The improvement of data acquisition capability allows fine-grained and large-scale built environment data to be extracted. Therefore, this paper focuses on investigating the relationship between the built environment around the station and the station passenger flow and discusses whether the built environment data can be applied to the station passenger flow prediction. Firstly, the evaluation system of station passenger flow influencing factors is built based on multisource data. The inner relationship between built environment factors and station passenger flow is investigated using the Pearson correlation analysis. Based on this, a multilayer perceptron (MLP)-based passenger flow prediction model was developed to predict the passenger flow at key stations. The study results show that the built environment factors impact station passenger flow, and the MLP prediction model has better prediction accuracy and applicability. The results of the study can be applied to predict the passenger flow scale of rail stations without historical passenger flow data and thus are also applicable to new rail stations.
{"title":"Passenger Flow Scale Prediction of Urban Rail Transit Stations Based on Multilayer Perceptron (MLP)","authors":"Luzhou Lin, Yuezhe Gao, Bingxin Cao, Z. Wang, Cai Jia","doi":"10.1155/2023/1430449","DOIUrl":"https://doi.org/10.1155/2023/1430449","url":null,"abstract":"Accurately predicting passenger flow at rail stations is an effective way to reduce operation and maintenance costs, improve the quality of passenger travel while meeting future passenger travel demand. The improvement of data acquisition capability allows fine-grained and large-scale built environment data to be extracted. Therefore, this paper focuses on investigating the relationship between the built environment around the station and the station passenger flow and discusses whether the built environment data can be applied to the station passenger flow prediction. Firstly, the evaluation system of station passenger flow influencing factors is built based on multisource data. The inner relationship between built environment factors and station passenger flow is investigated using the Pearson correlation analysis. Based on this, a multilayer perceptron (MLP)-based passenger flow prediction model was developed to predict the passenger flow at key stations. The study results show that the built environment factors impact station passenger flow, and the MLP prediction model has better prediction accuracy and applicability. The results of the study can be applied to predict the passenger flow scale of rail stations without historical passenger flow data and thus are also applicable to new rail stations.","PeriodicalId":72654,"journal":{"name":"Complex psychiatry","volume":"30 1","pages":"1430449:1-1430449:19"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73304835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With fast learning speed and high accuracy, extreme learning machine (ELM) has achieved great success in pattern recognition and machine learning. Unfortunately, it will fail in the circumstance where plenty of labeled samples for training model are insufficient. The labeled samples are difficult to obtain due to their high cost. In this paper, we solve this problem with transfer learning and propose joint transfer extreme learning machine (JTELM). First, it applies cross-domain mean approximation (CDMA) to minimize the discrepancy between domains, thus obtaining one ELM model. Second, subspace alignment (sa) and weight approximation are together introduced into the output layer to enhance the capability of knowledge transfer and learn another ELM model. Third, the prediction of test samples is dominated by the two learned ELM models. Finally, a series of experiments are carried out to investigate the performance of JTELM, and the results show that it achieves efficiently the task of transfer learning and performs better than the traditional ELM and other transfer or nontransfer learning methods.
{"title":"Joint Transfer Extreme Learning Machine with Cross-Domain Mean Approximation and Output Weight Alignment","authors":"Shaofei Zang, Dongqing Li, Chao Ma, Jianwei Ma","doi":"10.1155/2023/5072247","DOIUrl":"https://doi.org/10.1155/2023/5072247","url":null,"abstract":"With fast learning speed and high accuracy, extreme learning machine (ELM) has achieved great success in pattern recognition and machine learning. Unfortunately, it will fail in the circumstance where plenty of labeled samples for training model are insufficient. The labeled samples are difficult to obtain due to their high cost. In this paper, we solve this problem with transfer learning and propose joint transfer extreme learning machine (JTELM). First, it applies cross-domain mean approximation (CDMA) to minimize the discrepancy between domains, thus obtaining one ELM model. Second, subspace alignment (sa) and weight approximation are together introduced into the output layer to enhance the capability of knowledge transfer and learn another ELM model. Third, the prediction of test samples is dominated by the two learned ELM models. Finally, a series of experiments are carried out to investigate the performance of JTELM, and the results show that it achieves efficiently the task of transfer learning and performs better than the traditional ELM and other transfer or nontransfer learning methods.","PeriodicalId":72654,"journal":{"name":"Complex psychiatry","volume":"15 1","pages":"5072247:1-5072247:12"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78300921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The community structure in fully signed networks that considers both node attributes and edge signs is important in computational social science; however, its physical description still requires further exploration, and the corresponding measurement remains lacking. In this paper, we present a generalized framework of community structure in fully signed networks, based on which a variant of modularity is designed. An optimization algorithm that maximizes modularity to detect potential communities is also proposed. Experiments show that the proposed method can efficiently optimize the objective function and perform effective community detection.
{"title":"A Generalized Modularity for Computing Community Structure in Fully Signed Networks","authors":"Xiaochen He, Ruochen Zhang, Bin Zhu","doi":"10.1155/2023/8767131","DOIUrl":"https://doi.org/10.1155/2023/8767131","url":null,"abstract":"The community structure in fully signed networks that considers both node attributes and edge signs is important in computational social science; however, its physical description still requires further exploration, and the corresponding measurement remains lacking. In this paper, we present a generalized framework of community structure in fully signed networks, based on which a variant of modularity is designed. An optimization algorithm that maximizes modularity to detect potential communities is also proposed. Experiments show that the proposed method can efficiently optimize the objective function and perform effective community detection.","PeriodicalId":72654,"journal":{"name":"Complex psychiatry","volume":"37 1","pages":"8767131:1-8767131:20"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89333188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We believe that the ongoing global pandemic has highlighted the need for comprehensive approaches to address issues that transcend geographical and cultural boundaries. Therefore, this article aims to provide a general but abstract review to allow readers of a broad spectrum to learn the basic principles of three related concepts: systems, cybernetics, and complexity. Additionally, to better exemplify these concepts, we offer a review of works from the last decade that use systems theory, complexity, and cybernetics for their development. In this context, the result of this review will allow for breaking down the barriers of reductionist silos of knowledge and fostering a multidisciplinary and interdisciplinary dialogue.
{"title":"A Brief Review of Systems, Cybernetics, and Complexity","authors":"Jorge Tabilo Alvarez, P. Ramírez-Correa","doi":"10.1155/2023/8205320","DOIUrl":"https://doi.org/10.1155/2023/8205320","url":null,"abstract":"We believe that the ongoing global pandemic has highlighted the need for comprehensive approaches to address issues that transcend geographical and cultural boundaries. Therefore, this article aims to provide a general but abstract review to allow readers of a broad spectrum to learn the basic principles of three related concepts: systems, cybernetics, and complexity. Additionally, to better exemplify these concepts, we offer a review of works from the last decade that use systems theory, complexity, and cybernetics for their development. In this context, the result of this review will allow for breaking down the barriers of reductionist silos of knowledge and fostering a multidisciplinary and interdisciplinary dialogue.","PeriodicalId":72654,"journal":{"name":"Complex psychiatry","volume":"2023 1","pages":"8205320:1-8205320:22"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85343359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Zeb, Fakhrud Din, Muhammad Fayaz, Gulzar Mehmood, K. Z. Zamli
Swarm intelligence algorithms are metaheuristics inspired by the collective behavior of species such as birds, fish, bees, and ants. They are used in many optimization problems due to their simplicity, flexibility, and scalability. These algorithms get the desired convergence during the search by balancing the exploration and exploitation processes. These metaheuristics have applications in various domains such as global optimization, bioinformatics, power engineering, networking, machine learning, image processing, and environmental applications. This paper presents a systematic literature review (SLR) on applications of four swarm intelligence algorithms i.e., grey wolf optimization (GWO), whale optimization algorithms (WOA), Harris hawks optimizer (HHO), and moth-flame optimizer (MFO) in the field of software engineering. It presents an in-depth study of these metaheuristics’ adoption in the field of software engineering. This SLR is mainly comprised of three phases such as planning, conducting, and reporting. This study covers all related studies published from 2014 up to 2022. The study shows that applications of the selected metaheuristics have been utilized in various fields of software engineering especially software testing, software defect prediction, and software reliability. The study also points out some of the areas where applications of these swarm intelligence algorithms can be utilized. This study may act as a guideline for researchers in improving the current state-of-the-art on generally adopting these metaheuristics in software engineering.
{"title":"A Systematic Literature Review on Robust Swarm Intelligence Algorithms in Search-Based Software Engineering","authors":"A. Zeb, Fakhrud Din, Muhammad Fayaz, Gulzar Mehmood, K. Z. Zamli","doi":"10.1155/2023/4577581","DOIUrl":"https://doi.org/10.1155/2023/4577581","url":null,"abstract":"Swarm intelligence algorithms are metaheuristics inspired by the collective behavior of species such as birds, fish, bees, and ants. They are used in many optimization problems due to their simplicity, flexibility, and scalability. These algorithms get the desired convergence during the search by balancing the exploration and exploitation processes. These metaheuristics have applications in various domains such as global optimization, bioinformatics, power engineering, networking, machine learning, image processing, and environmental applications. This paper presents a systematic literature review (SLR) on applications of four swarm intelligence algorithms i.e., grey wolf optimization (GWO), whale optimization algorithms (WOA), Harris hawks optimizer (HHO), and moth-flame optimizer (MFO) in the field of software engineering. It presents an in-depth study of these metaheuristics’ adoption in the field of software engineering. This SLR is mainly comprised of three phases such as planning, conducting, and reporting. This study covers all related studies published from 2014 up to 2022. The study shows that applications of the selected metaheuristics have been utilized in various fields of software engineering especially software testing, software defect prediction, and software reliability. The study also points out some of the areas where applications of these swarm intelligence algorithms can be utilized. This study may act as a guideline for researchers in improving the current state-of-the-art on generally adopting these metaheuristics in software engineering.","PeriodicalId":72654,"journal":{"name":"Complex psychiatry","volume":"17 1","pages":"4577581:1-4577581:22"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80658743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Traditional supply chain literature on contracting only considers agents’ economic motivation. Nowadays, with the development of behavioral economics, social preference theory has been widely used in supply chain research. These social preferences are distinct from economic motivation and will influence agents’ behaviors in the supply chain. Agents will make decisions based on not only self-interests but also the interests of others, reciprocity, and fairness. This paper introduces the relationship and status preferences in the utility function. We aim to analyze the impact of social preference on individual competition intensity in the supply chain. A Stackelberg game model (tacit collusion) is used as the theoretical framework of the choice behavior between competition and cooperation. The theoretical results and numerical simulation analysis show that under some conditions, suppliers and retailers who take the social preference factors into account can realize multiple-stage channel coordination through revenue sharing. Moreover, social preference factors will influence the choice behavior of agents in competition and cooperation. Specifically, the relationship preference promotes close cooperation among enterprises and significantly improves the supply chain and individual performance. Status preference causes fierce competition among enterprises and adversely affects supply chain performance and individual performance, making it more unstable. These findings can provide useful insights for supply chain coordination.
{"title":"The Impact of Social Preferences on Supply Chain Performance: An Application of the Game Theory Model","authors":"A. Majeed, Yao Wang, Muniba, Mollah Aminul Islam","doi":"10.1155/2023/4911514","DOIUrl":"https://doi.org/10.1155/2023/4911514","url":null,"abstract":"Traditional supply chain literature on contracting only considers agents’ economic motivation. Nowadays, with the development of behavioral economics, social preference theory has been widely used in supply chain research. These social preferences are distinct from economic motivation and will influence agents’ behaviors in the supply chain. Agents will make decisions based on not only self-interests but also the interests of others, reciprocity, and fairness. This paper introduces the relationship and status preferences in the utility function. We aim to analyze the impact of social preference on individual competition intensity in the supply chain. A Stackelberg game model (tacit collusion) is used as the theoretical framework of the choice behavior between competition and cooperation. The theoretical results and numerical simulation analysis show that under some conditions, suppliers and retailers who take the social preference factors into account can realize multiple-stage channel coordination through revenue sharing. Moreover, social preference factors will influence the choice behavior of agents in competition and cooperation. Specifically, the relationship preference promotes close cooperation among enterprises and significantly improves the supply chain and individual performance. Status preference causes fierce competition among enterprises and adversely affects supply chain performance and individual performance, making it more unstable. These findings can provide useful insights for supply chain coordination.","PeriodicalId":72654,"journal":{"name":"Complex psychiatry","volume":"23 1","pages":"4911514:1-4911514:12"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79255900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：