{"title":"From the Editor: Belated Recognition for the 2021 Clemen–Kleinmuntz Decision Analysis Best Paper Award Winner and Finalist","authors":"V. Bier","doi":"10.1287/deca.2023.0477","DOIUrl":"https://doi.org/10.1287/deca.2023.0477","url":null,"abstract":"","PeriodicalId":46460,"journal":{"name":"Decision Analysis","volume":"44 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88362694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"From the Editor and Chair of the Award Committee: 2022 Clemen–Kleinmuntz Decision Analysis Best Paper Award","authors":"V. Bier, G. Montibeller","doi":"10.1287/deca.2023.0476","DOIUrl":"https://doi.org/10.1287/deca.2023.0476","url":null,"abstract":"","PeriodicalId":46460,"journal":{"name":"Decision Analysis","volume":"8 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85807033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Noise traders are a central idea in the modern theory of asset markets, yet there is not a standard model of such agents in contrast to the well-established representation of rational agents as expected utility maximizers. We propose the Hurwicz criterion, a classical criterion in decision analysis for choice under uncertainty, as a foundation for noise traders in asset markets. Hurwicz agents trade on optimism and pessimism and do not trade on information. A binary asset market is introduced with asymmetric information and heterogeneity both in rationality and in ambiguity attitudes. In this environment, noise trader behavior is endogenously positively correlated, the market is more efficient in low sentiment periods, and the favorite-longshot bias holds in equilibrium. The analysis demonstrates that aggregate market properties such as positive trading volume and the favorite longshot bias can be derived from the micro behavior of individual agents that have an axiomatic foundation.
{"title":"A Decision Theoretic Foundation for Noise Traders and Correlated Speculation","authors":"Mark Schneider, M. Nunez","doi":"10.1287/deca.2023.0473","DOIUrl":"https://doi.org/10.1287/deca.2023.0473","url":null,"abstract":"Noise traders are a central idea in the modern theory of asset markets, yet there is not a standard model of such agents in contrast to the well-established representation of rational agents as expected utility maximizers. We propose the Hurwicz criterion, a classical criterion in decision analysis for choice under uncertainty, as a foundation for noise traders in asset markets. Hurwicz agents trade on optimism and pessimism and do not trade on information. A binary asset market is introduced with asymmetric information and heterogeneity both in rationality and in ambiguity attitudes. In this environment, noise trader behavior is endogenously positively correlated, the market is more efficient in low sentiment periods, and the favorite-longshot bias holds in equilibrium. The analysis demonstrates that aggregate market properties such as positive trading volume and the favorite longshot bias can be derived from the micro behavior of individual agents that have an axiomatic foundation.","PeriodicalId":46460,"journal":{"name":"Decision Analysis","volume":"84 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72740612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"From the Editors: New Decision Analysis Journal Submission Requirements","authors":"V. Bier, S. French","doi":"10.1287/deca.2023.0475","DOIUrl":"https://doi.org/10.1287/deca.2023.0475","url":null,"abstract":"","PeriodicalId":46460,"journal":{"name":"Decision Analysis","volume":"64 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79874831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The value of information is a central concept in decision analysis, used to quantify how much the expected outcome of a decision would be improved if epistemic uncertainty could be resolved prior to committing to a course of action. One of the challenges, however, in quantitative analysis of the value of information is that the calculations are demanding, especially in requiring predictions of outcomes as a function of alternative actions and sources of uncertainty. However, the concept of value of information is important in early framing of some decisions, before such predictions are available. We propose a novel measure of the value of information based on constructed scales (CVOI), grounded in the algebra of the expected value of perfect information (EVPI), but requiring less of experts and analysts. The CVOI calculation decomposes EVPI into a contribution representing the relevance of the uncertainty to the decision and a contribution representing the magnitude of uncertainty; constructed ratio scales are then proposed for each contribution. We demonstrate the use of CVOI to identify research priorities related to migratory bird management in the face of climate change. Funding: This work was funded in part by the U.S. Geological Survey National Climate Adaptation Science Center.
{"title":"A Simplified Method for Value of Information Using Constructed Scales","authors":"","doi":"10.1287/deca.2023.0474","DOIUrl":"https://doi.org/10.1287/deca.2023.0474","url":null,"abstract":"The value of information is a central concept in decision analysis, used to quantify how much the expected outcome of a decision would be improved if epistemic uncertainty could be resolved prior to committing to a course of action. One of the challenges, however, in quantitative analysis of the value of information is that the calculations are demanding, especially in requiring predictions of outcomes as a function of alternative actions and sources of uncertainty. However, the concept of value of information is important in early framing of some decisions, before such predictions are available. We propose a novel measure of the value of information based on constructed scales (CVOI), grounded in the algebra of the expected value of perfect information (EVPI), but requiring less of experts and analysts. The CVOI calculation decomposes EVPI into a contribution representing the relevance of the uncertainty to the decision and a contribution representing the magnitude of uncertainty; constructed ratio scales are then proposed for each contribution. We demonstrate the use of CVOI to identify research priorities related to migratory bird management in the face of climate change. Funding: This work was funded in part by the U.S. Geological Survey National Climate Adaptation Science Center.","PeriodicalId":46460,"journal":{"name":"Decision Analysis","volume":"57 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78126475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Laura M. Keating, L. Randall, R. Stanton, Casey McCormack, M. Lucid, T. Seaborn, S. Converse, S. Canessa, A. Moehrenschlager
Conservation translocations, intentional movements of species to protect against extinction, have become widespread in recent decades and are projected to increase further as biodiversity loss continues worldwide. The literature abounds with analyses to inform translocations and assess whether they are successful, but the fundamental question of whether they should be initiated at all is rarely addressed formally. We used decision analysis to assess northern leopard frog reintroduction in northern Idaho, with success defined as a population that persists for at least 50 years. The Idaho Department of Fish and Game was the decision maker (i.e., the agency that will use this assessment to inform their decisions). Stakeholders from government, indigenous groups, academia, land management agencies, and conservation organizations also participated. We built an age-structured population model to predict how management alternatives would affect probability of success. In the model, we explicitly represented epistemic uncertainty around a success criterion (probability of persistence) characterized by aleatory uncertainty. For the leading alternative, the mean probability of persistence was 40%. The distribution of the modelling results was bimodal, with most parameter combinations resulting in either very low (<5%) or relatively high (>95%) probabilities of success. Along with other considerations, including cost, the Idaho Department of Fish and Game will use this assessment to inform a decision regarding reintroduction of northern leopard frogs. Conservation translocations may benefit greatly from more widespread use of decision analysis to counter the complexity and uncertainty inherent in these decisions. History: This paper has been accepted for the Decision Analysis Special Issue on Further Environmental Sustainability. Funding: This work was supported by the Wilder Institute/Calgary Zoo, the U.S. Fish and Wildlife Service [Grant F18AS00095], the NSF Idaho EPSCoR Program and the National Science Foundation [Grant OIA-1757324], and the Hunt Family Foundation. Supplemental Material: The online appendix is available at https://doi.org/10.1287/deca.2023.0472 .
{"title":"Using Decision Analysis to Determine the Feasibility of a Conservation Translocation","authors":"Laura M. Keating, L. Randall, R. Stanton, Casey McCormack, M. Lucid, T. Seaborn, S. Converse, S. Canessa, A. Moehrenschlager","doi":"10.1287/deca.2023.0472","DOIUrl":"https://doi.org/10.1287/deca.2023.0472","url":null,"abstract":"Conservation translocations, intentional movements of species to protect against extinction, have become widespread in recent decades and are projected to increase further as biodiversity loss continues worldwide. The literature abounds with analyses to inform translocations and assess whether they are successful, but the fundamental question of whether they should be initiated at all is rarely addressed formally. We used decision analysis to assess northern leopard frog reintroduction in northern Idaho, with success defined as a population that persists for at least 50 years. The Idaho Department of Fish and Game was the decision maker (i.e., the agency that will use this assessment to inform their decisions). Stakeholders from government, indigenous groups, academia, land management agencies, and conservation organizations also participated. We built an age-structured population model to predict how management alternatives would affect probability of success. In the model, we explicitly represented epistemic uncertainty around a success criterion (probability of persistence) characterized by aleatory uncertainty. For the leading alternative, the mean probability of persistence was 40%. The distribution of the modelling results was bimodal, with most parameter combinations resulting in either very low (<5%) or relatively high (>95%) probabilities of success. Along with other considerations, including cost, the Idaho Department of Fish and Game will use this assessment to inform a decision regarding reintroduction of northern leopard frogs. Conservation translocations may benefit greatly from more widespread use of decision analysis to counter the complexity and uncertainty inherent in these decisions. History: This paper has been accepted for the Decision Analysis Special Issue on Further Environmental Sustainability. Funding: This work was supported by the Wilder Institute/Calgary Zoo, the U.S. Fish and Wildlife Service [Grant F18AS00095], the NSF Idaho EPSCoR Program and the National Science Foundation [Grant OIA-1757324], and the Hunt Family Foundation. Supplemental Material: The online appendix is available at https://doi.org/10.1287/deca.2023.0472 .","PeriodicalId":46460,"journal":{"name":"Decision Analysis","volume":"145 1 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89357454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents the results of four lottery-type experiments that investigate the effects of incentive structures on decision-making under uncertainty. We compare choices made with and without incentives, with fixed targets, with binary targets, and with four-outcome targets that are discretized from a logistic distribution. The results of the behavioral experiments (i) validate theoretical findings of utility functions induced by fixed and uncertain targets. Further, the behavioral results show that (ii) individuals’ choices are indeed affected by incentive structures, which we quantify by several deviation measures. (iii) Defined consistency measures show that choices under uncertain targets become less consistent as the number of uncertain target outcomes increases. The results of these experiments provide insights into the effects of setting incentive structures on decision-making behavior.
{"title":"Experimental Assessment of Utility Functions Induced by Fixed and Uncertain Targets","authors":"M. Zellner, A. Abbas","doi":"10.1287/deca.2023.0470","DOIUrl":"https://doi.org/10.1287/deca.2023.0470","url":null,"abstract":"This paper presents the results of four lottery-type experiments that investigate the effects of incentive structures on decision-making under uncertainty. We compare choices made with and without incentives, with fixed targets, with binary targets, and with four-outcome targets that are discretized from a logistic distribution. The results of the behavioral experiments (i) validate theoretical findings of utility functions induced by fixed and uncertain targets. Further, the behavioral results show that (ii) individuals’ choices are indeed affected by incentive structures, which we quantify by several deviation measures. (iii) Defined consistency measures show that choices under uncertain targets become less consistent as the number of uncertain target outcomes increases. The results of these experiments provide insights into the effects of setting incentive structures on decision-making behavior.","PeriodicalId":46460,"journal":{"name":"Decision Analysis","volume":"44 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89798357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Muhammad Ejaz, Nisho Rani, Dr Muhammad Ramzan Sheikh
Bidders’ bidding behavior is analyzed in first price sealed-bid (FPSB) auctions using an adversarial risk analysis (ARA) framework. However, using nonstrategic play and level-k thinking solution concepts, modeling is performed by assuming only two bidders. Also, the aleatory and concept uncertainties have not been yet taken into account by using an ARA framework for these auctions. In this paper, we apply an ARA approach to model bidders’ bidding behavior in a more realistic way for FPSB auctions. We assume n bidders that may have different wealth and heterogeneous risk behaviors. We use nonstrategic play and level-k thinking solution concepts, and we take into account aleatory uncertainty in addition to epistemic uncertainty. Finally, concept uncertainty is taken into account to find ARA solutions for these auctions. We also provide numerical examples to illustrate our methodology.
{"title":"First Price Sealed-Bid Auctions with Bidders’ Heterogeneous Risk Behavior: An Adversarial Risk Analysis Approach","authors":"Muhammad Ejaz, Nisho Rani, Dr Muhammad Ramzan Sheikh","doi":"10.1287/deca.2023.0469","DOIUrl":"https://doi.org/10.1287/deca.2023.0469","url":null,"abstract":"Bidders’ bidding behavior is analyzed in first price sealed-bid (FPSB) auctions using an adversarial risk analysis (ARA) framework. However, using nonstrategic play and level-k thinking solution concepts, modeling is performed by assuming only two bidders. Also, the aleatory and concept uncertainties have not been yet taken into account by using an ARA framework for these auctions. In this paper, we apply an ARA approach to model bidders’ bidding behavior in a more realistic way for FPSB auctions. We assume n bidders that may have different wealth and heterogeneous risk behaviors. We use nonstrategic play and level-k thinking solution concepts, and we take into account aleatory uncertainty in addition to epistemic uncertainty. Finally, concept uncertainty is taken into account to find ARA solutions for these auctions. We also provide numerical examples to illustrate our methodology.","PeriodicalId":46460,"journal":{"name":"Decision Analysis","volume":"5 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86169069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Dillon, V. Bier, R. S. John, Abdullah Althenayyan
Decision analysis (DA) is an explicitly prescriptive discipline that separates beliefs about uncertainties from value preferences in modeling to support decision making. Researchers have been advancing DA tools for the last 60 years to support decision makers handling complex decisions requiring subjective judgments. Recently, some DA researchers and practitioners wondered whether the difficult decisions made during the COVID-19 pandemic regarding testing, masking, closing and reopening businesses, allocating ventilators, and prioritizing vaccines would have been improved with more DA involvement. With its focus on quantifying uncertainties, value trade-offs, and risk attitudes, DA should have been a valuable tool for decision makers during the pandemic. To influence decisions, DA applications require interactions with policymakers and experts to construct formal representations of the decision frame, elicit uncertainties, and assess risk tolerances and trade-offs among competing objectives. Unfortunately, such involvement of decision analysts in the process of decision making and policy setting did not occur during much of the COVID-19 pandemic. This lack of participation may have been partly because many decision makers were unaware of when DA could be valuable in helping with the challenges of the COVID-19 pandemic. In addition, decision analysts were perhaps not sufficiently adept at inserting themselves into the policy process at critical junctures when their expertise could have been helpful. Funding: This research was partially supported by the U.S. Department of Homeland Security through the Center for Accelerating Operational Efficiency at Arizona State University.
{"title":"Closing the Gap Between Decision Analysis and Policy Analysts Before the Next Pandemic","authors":"R. Dillon, V. Bier, R. S. John, Abdullah Althenayyan","doi":"10.1287/deca.2023.0468","DOIUrl":"https://doi.org/10.1287/deca.2023.0468","url":null,"abstract":"Decision analysis (DA) is an explicitly prescriptive discipline that separates beliefs about uncertainties from value preferences in modeling to support decision making. Researchers have been advancing DA tools for the last 60 years to support decision makers handling complex decisions requiring subjective judgments. Recently, some DA researchers and practitioners wondered whether the difficult decisions made during the COVID-19 pandemic regarding testing, masking, closing and reopening businesses, allocating ventilators, and prioritizing vaccines would have been improved with more DA involvement. With its focus on quantifying uncertainties, value trade-offs, and risk attitudes, DA should have been a valuable tool for decision makers during the pandemic. To influence decisions, DA applications require interactions with policymakers and experts to construct formal representations of the decision frame, elicit uncertainties, and assess risk tolerances and trade-offs among competing objectives. Unfortunately, such involvement of decision analysts in the process of decision making and policy setting did not occur during much of the COVID-19 pandemic. This lack of participation may have been partly because many decision makers were unaware of when DA could be valuable in helping with the challenges of the COVID-19 pandemic. In addition, decision analysts were perhaps not sufficiently adept at inserting themselves into the policy process at critical junctures when their expertise could have been helpful. Funding: This research was partially supported by the U.S. Department of Homeland Security through the Center for Accelerating Operational Efficiency at Arizona State University.","PeriodicalId":46460,"journal":{"name":"Decision Analysis","volume":"3 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89974744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cybersecurity planning supports the selection of and implementation of security controls in resource-constrained settings to manage risk. Doing so requires considering adaptive adversaries with different levels of strategic sophistication in modeling efforts to support risk management. However, most models in the literature only consider rational or nonstrategic adversaries. Therefore, we study how to inform defensive decision making to mitigate the risk from boundedly rational players, with a particular focus on making integrated, interdependent planning decisions. To achieve this goal, we introduce a modeling framework for selecting a portfolio of security mitigations that interdict adversarial attack plans that uses a structured approach for risk analysis. Our approach adapts adversarial risk analysis and cognitive hierarchy theory to consider a maximum-reliability path interdiction problem with a single defender and multiple attackers who have different goals and levels of strategic sophistication. Instead of enumerating all possible attacks and defenses, we introduce a solution technique based on integer programming and approximation algorithms to iteratively solve the defender’s and attackers’ problems. A case study illustrates the proposed models and provides insights into defensive planning. Funding: A. Peper and L. A. Albert were supported in part by the National Science Foundation [Grant 2000986].
网络安全规划支持在资源受限的环境中选择和实施安全控制措施，以管理风险。这样做需要在建模工作中考虑具有不同战略成熟度级别的自适应对手，以支持风险管理。然而，文献中的大多数模型只考虑理性的或非战略性的对手。因此，我们研究如何为防御性决策提供信息，以减轻有限理性参与者的风险，并特别关注制定综合的、相互依赖的规划决策。为了实现这一目标，我们引入了一个建模框架，用于选择一组安全缓解措施，以阻止使用结构化方法进行风险分析的对抗性攻击计划。我们的方法采用对抗风险分析和认知层次理论来考虑具有不同目标和战略复杂程度的单个防御者和多个攻击者的最大可靠性路径拦截问题。我们不是列举所有可能的攻击和防御，而是引入一种基于整数规划和近似算法的求解技术来迭代解决防御者和攻击者的问题。一个案例研究说明了所提出的模型，并提供了对防御计划的见解。资助:A. Peper和L. A. Albert得到了美国国家科学基金会的部分支持[Grant 2000986]。
{"title":"Interdicting Attack Plans with Boundedly Rational Players and Multiple Attackers: An Adversarial Risk Analysis Approach","authors":"Eric B. DuBois, Ashley Peper, Laura A. Albert","doi":"10.1287/deca.2023.0471","DOIUrl":"https://doi.org/10.1287/deca.2023.0471","url":null,"abstract":"Cybersecurity planning supports the selection of and implementation of security controls in resource-constrained settings to manage risk. Doing so requires considering adaptive adversaries with different levels of strategic sophistication in modeling efforts to support risk management. However, most models in the literature only consider rational or nonstrategic adversaries. Therefore, we study how to inform defensive decision making to mitigate the risk from boundedly rational players, with a particular focus on making integrated, interdependent planning decisions. To achieve this goal, we introduce a modeling framework for selecting a portfolio of security mitigations that interdict adversarial attack plans that uses a structured approach for risk analysis. Our approach adapts adversarial risk analysis and cognitive hierarchy theory to consider a maximum-reliability path interdiction problem with a single defender and multiple attackers who have different goals and levels of strategic sophistication. Instead of enumerating all possible attacks and defenses, we introduce a solution technique based on integer programming and approximation algorithms to iteratively solve the defender’s and attackers’ problems. A case study illustrates the proposed models and provides insights into defensive planning. Funding: A. Peper and L. A. Albert were supported in part by the National Science Foundation [Grant 2000986].","PeriodicalId":46460,"journal":{"name":"Decision Analysis","volume":"57 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78453746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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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