Pub Date : 2024-02-06DOI: 10.1080/23270012.2024.2304540
Shoude Li
This paper explores a multiproduct firm’s process innovation of high-and low-quality goods with knowledge accumulation in a vertically differentiated monopoly. We show that: (i) the system admits a...
{"title":"Dynamic control of a firm’s process innovation with knowledge accumulation in a vertically differentiated monopoly","authors":"Shoude Li","doi":"10.1080/23270012.2024.2304540","DOIUrl":"https://doi.org/10.1080/23270012.2024.2304540","url":null,"abstract":"This paper explores a multiproduct firm’s process innovation of high-and low-quality goods with knowledge accumulation in a vertically differentiated monopoly. We show that: (i) the system admits a...","PeriodicalId":46290,"journal":{"name":"Journal of Management Analytics","volume":"170 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139766260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-06DOI: 10.1080/23270012.2023.2301709
Jorge Iván Pérez Rave, Carlos Mario Zapata Jaramillo, Gloria Patricia Jaramillo Álvarez
Mental disorders negatively affect employee well-being and organizational performance. Organizations face a challenge in terms of how to manage mental health. This paper clarifies three issues (und...
{"title":"Mental health in organizations from a healthcare analytics framework: taxonomic model, trends, and impact of COVID-19","authors":"Jorge Iván Pérez Rave, Carlos Mario Zapata Jaramillo, Gloria Patricia Jaramillo Álvarez","doi":"10.1080/23270012.2023.2301709","DOIUrl":"https://doi.org/10.1080/23270012.2023.2301709","url":null,"abstract":"Mental disorders negatively affect employee well-being and organizational performance. Organizations face a challenge in terms of how to manage mental health. This paper clarifies three issues (und...","PeriodicalId":46290,"journal":{"name":"Journal of Management Analytics","volume":"4 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139766694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-31DOI: 10.1080/23270012.2024.2301748
H. D. Arora, Anjali Naithani
Fuzzy entropy measures are valuable tools in decision-making when dealing with uncertain or imprecise information. There exist many entropy measures for Pythagorean Fuzzy Sets (PFS) in the literatu...
{"title":"On some new fuzzy entropy measure of Pythagorean fuzzy sets for decision-making based on an extended TOPSIS approach","authors":"H. D. Arora, Anjali Naithani","doi":"10.1080/23270012.2024.2301748","DOIUrl":"https://doi.org/10.1080/23270012.2024.2301748","url":null,"abstract":"Fuzzy entropy measures are valuable tools in decision-making when dealing with uncertain or imprecise information. There exist many entropy measures for Pythagorean Fuzzy Sets (PFS) in the literatu...","PeriodicalId":46290,"journal":{"name":"Journal of Management Analytics","volume":"12 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139766253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-27DOI: 10.1080/23270012.2023.2291835
Supriya Tiwari, Kunal Shah, Kajal Bhimani
The proposed study offers the first-of-its-kind economic production quantity model for deteriorating items having a demand rate to be price dependent under the effect of inflation and reliability w...
在通货膨胀和可靠性的影响下，本研究首次为需求率取决于价格的变质物品提供了经济生产量模型。
{"title":"EPQ model with the effect of inflation and reliability for partial trade credit under fuzzy and cloudy fuzzy environment","authors":"Supriya Tiwari, Kunal Shah, Kajal Bhimani","doi":"10.1080/23270012.2023.2291835","DOIUrl":"https://doi.org/10.1080/23270012.2023.2291835","url":null,"abstract":"The proposed study offers the first-of-its-kind economic production quantity model for deteriorating items having a demand rate to be price dependent under the effect of inflation and reliability w...","PeriodicalId":46290,"journal":{"name":"Journal of Management Analytics","volume":"37 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2023-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139056995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-27DOI: 10.1080/23270012.2023.2291836
Xiaojun Xu, Lu Wang, Xiaoli Wang
Due to the information asymmetry and imperfect supervision system, the problem of information service quality of e-commerce platforms is becoming increasingly prominent. Based on the perspective of...
由于信息不对称和监管体系不完善，电子商务平台的信息服务质量问题日益突出。基于...
{"title":"Evolutionary game analysis of information service quality control of e-commerce platforms under information ecology","authors":"Xiaojun Xu, Lu Wang, Xiaoli Wang","doi":"10.1080/23270012.2023.2291836","DOIUrl":"https://doi.org/10.1080/23270012.2023.2291836","url":null,"abstract":"Due to the information asymmetry and imperfect supervision system, the problem of information service quality of e-commerce platforms is becoming increasingly prominent. Based on the perspective of...","PeriodicalId":46290,"journal":{"name":"Journal of Management Analytics","volume":"6 2 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2023-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139068320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-08DOI: 10.1080/23270012.2023.2264294
Jun Ye, Shigui Du, Rui Yong
AbstractMotivated based on the trigonometric t-norm and t-conorm, the aims of this article are to present the trigonometric t-norm and t-conorm operational laws of SvNNs and then to propose the SvNN trigonometric weighted average and geometric aggregation operators for the modelling of a multiple criteria decision making (MCDM) technique in an inconsistent and indeterminate circumstance. To realize the aims, this paper first proposes the trigonometric t-norm and t-conorm operational laws of SvNNs, which contain the hybrid operations of the tangent and arctangent functions and the cotangent and inverse cotangent functions, and presents the SvNN trigonometric weighted average and geometric operators and their properties. Next, a MCDM technique is proposed in view of the presented two aggregation operators in the circumstance of SvNNs. In the end, an actual case of the choice issue of slope treatment schemes is provided to indicate the practicability and effectivity of the proposed MCDM technique.Keywords: Single-valued neutrosophic numbertrigonometric t-norm and t-conormtrigonometric weighted aggregation operatordecision making Data availabilityAll data are included in this study.Disclosure statementNo potential conflict of interest was reported by the author(s).
{"title":"MCDM technique using single-valued neutrosophic trigonometric weighted aggregation operators","authors":"Jun Ye, Shigui Du, Rui Yong","doi":"10.1080/23270012.2023.2264294","DOIUrl":"https://doi.org/10.1080/23270012.2023.2264294","url":null,"abstract":"AbstractMotivated based on the trigonometric t-norm and t-conorm, the aims of this article are to present the trigonometric t-norm and t-conorm operational laws of SvNNs and then to propose the SvNN trigonometric weighted average and geometric aggregation operators for the modelling of a multiple criteria decision making (MCDM) technique in an inconsistent and indeterminate circumstance. To realize the aims, this paper first proposes the trigonometric t-norm and t-conorm operational laws of SvNNs, which contain the hybrid operations of the tangent and arctangent functions and the cotangent and inverse cotangent functions, and presents the SvNN trigonometric weighted average and geometric operators and their properties. Next, a MCDM technique is proposed in view of the presented two aggregation operators in the circumstance of SvNNs. In the end, an actual case of the choice issue of slope treatment schemes is provided to indicate the practicability and effectivity of the proposed MCDM technique.Keywords: Single-valued neutrosophic numbertrigonometric t-norm and t-conormtrigonometric weighted aggregation operatordecision making Data availabilityAll data are included in this study.Disclosure statementNo potential conflict of interest was reported by the author(s).","PeriodicalId":46290,"journal":{"name":"Journal of Management Analytics","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135198087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-21DOI: 10.1080/23270012.2023.2258376
Chenxia Jin, Fachao Li, Yuqing Xia, Sohail S. Chaudhry
AbstractThe existing shelf layout methods do not explicitly consider the attention and relevancy of the commodity systematically and thus have failed to capture the invalid associations, resulting in poor sales impact and customer satisfaction. For such shortcomings, in this paper, we propose a mathematical programming approach for shelf layout problems based on comprehensive related value. First, we introduce the concepts of related value considering both attention and relevancy; second, we give the concept of adjacent utility value and the freedom of placement, and further analyze the impact of the same commodity on surrounding commodities due to different placement positions; third, we establish a new comprehensive related value-based commodity layout optimization model (CRV-CL) and provide the solution steps integrating with a genetic algorithm. Finally, we analyze the characteristics of CRV-CL through a specific case. The simulation results indicate the overall relevancy after applying the CRV-CL model.Keywords: Shelf layoutcomprehensive related valuefreedom of placementadjacent utility valuegenetic algorithm Disclosure statementNo potential conflict of interest was reported by the author(s).Ethical approvalThis article does not contain any studies with human participants or animals performed by any of the authors.Additional informationFundingThis work was supported by the National Natural Science Foundation of China under Grant (72101082); the Natural Science Foundation of Hebei Province under Grant (F2021208011). The research of Sohail S. Chaudhry was partially supported through a research sabbatical leave from Villanova University.
摘要现有的货架布置方法没有系统地明确考虑商品的关注度和相关性，未能捕捉到无效的关联，导致销售影响和顾客满意度较差。针对这些不足，本文提出了一种基于综合相关值的货架布置问题的数学规划方法。首先，我们引入了相关价值的概念，同时考虑了注意力和相关性;其次，给出相邻效用价值和放置自由度的概念，进一步分析同一商品由于放置位置不同对周边商品的影响;第三，建立了基于价值的综合相关商品布局优化模型(CRV-CL)，并结合遗传算法给出了求解步骤。最后，通过具体案例分析CRV-CL的特点。仿真结果表明，采用CRV-CL模型后，总体上具有相关性。关键词:货架布置图综合相关价值放置自由相邻效用价值遗传算法披露声明作者未报告潜在利益冲突。伦理批准本文不包含任何作者进行的任何人类参与者或动物研究。项目资助:国家自然科学基金资助项目(72101082);河北省自然科学基金项目(F2021208011);Sohail S. Chaudhry的研究得到了Villanova大学的研究休假的部分支持。
{"title":"Commodity layout in supermarkets: using the integration of the comprehensive related value method and genetic algorithm","authors":"Chenxia Jin, Fachao Li, Yuqing Xia, Sohail S. Chaudhry","doi":"10.1080/23270012.2023.2258376","DOIUrl":"https://doi.org/10.1080/23270012.2023.2258376","url":null,"abstract":"AbstractThe existing shelf layout methods do not explicitly consider the attention and relevancy of the commodity systematically and thus have failed to capture the invalid associations, resulting in poor sales impact and customer satisfaction. For such shortcomings, in this paper, we propose a mathematical programming approach for shelf layout problems based on comprehensive related value. First, we introduce the concepts of related value considering both attention and relevancy; second, we give the concept of adjacent utility value and the freedom of placement, and further analyze the impact of the same commodity on surrounding commodities due to different placement positions; third, we establish a new comprehensive related value-based commodity layout optimization model (CRV-CL) and provide the solution steps integrating with a genetic algorithm. Finally, we analyze the characteristics of CRV-CL through a specific case. The simulation results indicate the overall relevancy after applying the CRV-CL model.Keywords: Shelf layoutcomprehensive related valuefreedom of placementadjacent utility valuegenetic algorithm Disclosure statementNo potential conflict of interest was reported by the author(s).Ethical approvalThis article does not contain any studies with human participants or animals performed by any of the authors.Additional informationFundingThis work was supported by the National Natural Science Foundation of China under Grant (72101082); the Natural Science Foundation of Hebei Province under Grant (F2021208011). The research of Sohail S. Chaudhry was partially supported through a research sabbatical leave from Villanova University.","PeriodicalId":46290,"journal":{"name":"Journal of Management Analytics","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136154828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-14DOI: 10.1080/23270012.2023.2258372
Siqi Pan, Qiang Ye, Wen Shi
AbstractOur research focuses on detecting financial reporting misconduct and derives a comprehensive misconduct sample using AAERs and intentional restatements. We develop a novel ensemble learning method, Multi-LightGBM, for highly imbalanced classification learning. We adopt a human-machine cooperation feature selection method, which can mitigate the limitation of incomplete theories, enhance the model performance, and guide researchers to develop new theories. We propose a cost-based measure, expected benefits of classification, to evaluate the economic performance of a model. The out-of-sample tests show that Multi-LightGBM, coupled with the features we selected, outperforms other predictive models. The finding that introducing intentional material restatements into our predictive model does not reduce the effectiveness of capturing AAERs has important implications for research on AAERs detection. Moreover, we can identify more misconduct firms with fewer resources by the misconduct sample relative to the standalone AAERs sample, which is quite beneficial for most model users.Keywords: financial reporting misconductensemble learningfeature selectionLightGBM Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by National Natural Science Foundation of China under [grant numbers 72071038, 72121001].
{"title":"Using a novel ensemble learning framework to detect financial reporting misconduct","authors":"Siqi Pan, Qiang Ye, Wen Shi","doi":"10.1080/23270012.2023.2258372","DOIUrl":"https://doi.org/10.1080/23270012.2023.2258372","url":null,"abstract":"AbstractOur research focuses on detecting financial reporting misconduct and derives a comprehensive misconduct sample using AAERs and intentional restatements. We develop a novel ensemble learning method, Multi-LightGBM, for highly imbalanced classification learning. We adopt a human-machine cooperation feature selection method, which can mitigate the limitation of incomplete theories, enhance the model performance, and guide researchers to develop new theories. We propose a cost-based measure, expected benefits of classification, to evaluate the economic performance of a model. The out-of-sample tests show that Multi-LightGBM, coupled with the features we selected, outperforms other predictive models. The finding that introducing intentional material restatements into our predictive model does not reduce the effectiveness of capturing AAERs has important implications for research on AAERs detection. Moreover, we can identify more misconduct firms with fewer resources by the misconduct sample relative to the standalone AAERs sample, which is quite beneficial for most model users.Keywords: financial reporting misconductensemble learningfeature selectionLightGBM Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by National Natural Science Foundation of China under [grant numbers 72071038, 72121001].","PeriodicalId":46290,"journal":{"name":"Journal of Management Analytics","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134970106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-10DOI: 10.1080/23270012.2023.2244503
Xuemei Li, Alexander Sigov, Leonid Ratkin, Leonid A. Ivanov, Ling Li
AbstractFinance is in our daily life. We invest, borrow, lend, budget, and save money. Finance also provides guidelines for corporation and government spending and revenue collection. Traditional statistical solutions such as regression, PCA, and CFA have been widely used in financial forecasting and analysis. With the increasing interest in artificial intelligence in recent years, this paper reviews the Artificial Intelligence (AI) techniques in the finance domain systematically and attempts to identify the current AI technologies used, major applications, challenges, and trends in Finance. It explores AI-related articles in Finance in IEEE Xplore and EI compendex databases. Findings suggest AI has been engaged in Finance in financial forecasting, financial protection, and financial analysis and decision-making areas. Financial forecasting is one of the main sub-fields of Finance affected by AI technology. Major AI technology used is the supervised learning. Deep learning has gained popular in recent years. AI could be used to address some emerging topics.Keywords: machine learning; artificial intelligencefinance Disclosure statementNo potential conflict of interest was reported by the author(s).
{"title":"Artificial intelligence applications in finance: a survey","authors":"Xuemei Li, Alexander Sigov, Leonid Ratkin, Leonid A. Ivanov, Ling Li","doi":"10.1080/23270012.2023.2244503","DOIUrl":"https://doi.org/10.1080/23270012.2023.2244503","url":null,"abstract":"AbstractFinance is in our daily life. We invest, borrow, lend, budget, and save money. Finance also provides guidelines for corporation and government spending and revenue collection. Traditional statistical solutions such as regression, PCA, and CFA have been widely used in financial forecasting and analysis. With the increasing interest in artificial intelligence in recent years, this paper reviews the Artificial Intelligence (AI) techniques in the finance domain systematically and attempts to identify the current AI technologies used, major applications, challenges, and trends in Finance. It explores AI-related articles in Finance in IEEE Xplore and EI compendex databases. Findings suggest AI has been engaged in Finance in financial forecasting, financial protection, and financial analysis and decision-making areas. Financial forecasting is one of the main sub-fields of Finance affected by AI technology. Major AI technology used is the supervised learning. Deep learning has gained popular in recent years. AI could be used to address some emerging topics.Keywords: machine learning; artificial intelligencefinance Disclosure statementNo potential conflict of interest was reported by the author(s).","PeriodicalId":46290,"journal":{"name":"Journal of Management Analytics","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135553759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-31DOI: 10.1080/23270012.2023.2239818
B. Karthick
{"title":"An inventory analysis in a multi-echelon supply chain system under asymmetry fuzzy demand: a fmincon optimization","authors":"B. Karthick","doi":"10.1080/23270012.2023.2239818","DOIUrl":"https://doi.org/10.1080/23270012.2023.2239818","url":null,"abstract":"","PeriodicalId":46290,"journal":{"name":"Journal of Management Analytics","volume":" ","pages":""},"PeriodicalIF":5.9,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45124069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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