Many methods for creating surrogate swing weights based only on the rank order of the attributes are proposed to avoid the cost and effort of eliciting weights in multiattribute decision analysis. We explore empirically how well eight different methods perform based on a large sample of real-world elicited weights. We use the Euclidean distance from the elicited weights to judge the quality of the surrogate weights as well as three other metrics. The sum reciprocal method gives results, on average, statistically closest to the elicited weights for all metrics used. The equal ratio method using a fixed ratio of 0.716 performs just as well on three of the metrics. The rank sum method, the simplest and one of the oldest methods, performs generally next best. The rank order centroid method, which does well in simulation studies, performs relatively poorly in this evaluation using real-world data.
{"title":"An Empirical Comparison of Rank-Based Surrogate Weights in Additive Multiattribute Decision Analysis","authors":"R. C. Burk, Richard M. Nehring","doi":"10.1287/deca.2022.0456","DOIUrl":"https://doi.org/10.1287/deca.2022.0456","url":null,"abstract":"Many methods for creating surrogate swing weights based only on the rank order of the attributes are proposed to avoid the cost and effort of eliciting weights in multiattribute decision analysis. We explore empirically how well eight different methods perform based on a large sample of real-world elicited weights. We use the Euclidean distance from the elicited weights to judge the quality of the surrogate weights as well as three other metrics. The sum reciprocal method gives results, on average, statistically closest to the elicited weights for all metrics used. The equal ratio method using a fixed ratio of 0.716 performs just as well on three of the metrics. The rank sum method, the simplest and one of the oldest methods, performs generally next best. The rank order centroid method, which does well in simulation studies, performs relatively poorly in this evaluation using real-world data.","PeriodicalId":46460,"journal":{"name":"Decision Analysis","volume":"85 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77142982","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}
Florian Methling, Steffen A. Borden, Deepak Veeraraghavan, Insa Sommer, J. Siebert, Rudiger von Nitzsch, Mark Seidler
Pharmaceutical companies have frequent portfolio reviews to monitor development progress and prioritize development assets. The earliest assets are drug candidates whose efficacy is unknown and whose effects on the human body have yet to be fully investigated. These assets are characterized by a high degree of uncertainty in reaching the market and in being used in clinical practice. In addition, not all potential applications are foreseen and can often be very different. In the absence of satisfactory methods for making decisions on resource allocation among early development assets, decision makers focus almost exclusively on assessments of an asset’s probability of technical success. This study proposes a more holistic methodology to support early-stage pharmaceutical development decisions using value-focused thinking and multicriteria decision making. The methodology operates within the decision quality framework and provides a consistent evaluation of various early development assets across a diverse set of disease areas. This combination of concepts and methodologies has been implemented and proven valuable at Bayer Pharmaceuticals, which needed a new, more robust decision-making process for early development. Thus, this study discusses how to enable concrete trade-offs at the level of corporate objectives to align, communicate, and translate corporate strategy into portfolio strategy. In addition, this study presents learnings for decision analysts and decision makers in the pharmaceutical industry on how to develop a set of fundamental objectives, how to create scales to operationalize these objectives, and how to take steps to debias an organizational decision-making process.
{"title":"Supporting Innovation in Early-Stage Pharmaceutical Development Decisions","authors":"Florian Methling, Steffen A. Borden, Deepak Veeraraghavan, Insa Sommer, J. Siebert, Rudiger von Nitzsch, Mark Seidler","doi":"10.1287/deca.2022.0452","DOIUrl":"https://doi.org/10.1287/deca.2022.0452","url":null,"abstract":"Pharmaceutical companies have frequent portfolio reviews to monitor development progress and prioritize development assets. The earliest assets are drug candidates whose efficacy is unknown and whose effects on the human body have yet to be fully investigated. These assets are characterized by a high degree of uncertainty in reaching the market and in being used in clinical practice. In addition, not all potential applications are foreseen and can often be very different. In the absence of satisfactory methods for making decisions on resource allocation among early development assets, decision makers focus almost exclusively on assessments of an asset’s probability of technical success. This study proposes a more holistic methodology to support early-stage pharmaceutical development decisions using value-focused thinking and multicriteria decision making. The methodology operates within the decision quality framework and provides a consistent evaluation of various early development assets across a diverse set of disease areas. This combination of concepts and methodologies has been implemented and proven valuable at Bayer Pharmaceuticals, which needed a new, more robust decision-making process for early development. Thus, this study discusses how to enable concrete trade-offs at the level of corporate objectives to align, communicate, and translate corporate strategy into portfolio strategy. In addition, this study presents learnings for decision analysts and decision makers in the pharmaceutical industry on how to develop a set of fundamental objectives, how to create scales to operationalize these objectives, and how to take steps to debias an organizational decision-making process.","PeriodicalId":46460,"journal":{"name":"Decision Analysis","volume":"12 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76786109","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}
Abdullah Gökçınar, M. Çakanyıldırım, Theodore John Price, Meredith C. B. Adams
In the backdrop of the opioid epidemic, opioid prescribing has distinct medical and social challenges. Overprescribing contributes to the ongoing opioid epidemic, whereas underprescribing yields inadequate pain relief. Moreover, opioids have serious adverse effects including tolerance and increased sensitivity to pain, paradoxically inducing more pain. Prescribing trade-offs are recognized but not modeled in the literature. We study the prescribing decisions for chronic, acute, and persistent pain types to minimize the cumulative pain that incorporates opioid adverse effects (discomfort and dependence) and the risk of tolerance or hypersensitivity (THS) developed with opioid use. After finding closed-form solutions for each pain type, we analytically investigate the sensitivity of acute pain prescriptions and examine policies on incorporation of THS, patient handover, and adaptive treatments. Our analyses show that the role of adverse effects in prescribing decisions is as critical as that of the pain level. Interestingly, we find that the optimal prescription duration is not necessarily increasing with the recovery time. We show that not incorporating THS or information curtailment at patient handovers leads to overprescribing that can be mitigated by adaptive treatments. Last, using real-life pain and opioid use data from two sources, we estimate THS parameters and discuss the proximity of our model to clinical practice. This paper has a pain management framework that leads to tractable models. These models can potentially support balanced opioid prescribing after their validation in a clinical setting. Then, they can be helpful to policy makers in assessment of prescription policies and of the controversy around over- and underprescribing.
{"title":"Balanced Opioid Prescribing via a Clinical Trade-Off: Pain Relief vs. Adverse Effects of Discomfort, Dependence, and Tolerance/Hypersensitivity","authors":"Abdullah Gökçınar, M. Çakanyıldırım, Theodore John Price, Meredith C. B. Adams","doi":"10.1287/deca.2021.0447","DOIUrl":"https://doi.org/10.1287/deca.2021.0447","url":null,"abstract":"In the backdrop of the opioid epidemic, opioid prescribing has distinct medical and social challenges. Overprescribing contributes to the ongoing opioid epidemic, whereas underprescribing yields inadequate pain relief. Moreover, opioids have serious adverse effects including tolerance and increased sensitivity to pain, paradoxically inducing more pain. Prescribing trade-offs are recognized but not modeled in the literature. We study the prescribing decisions for chronic, acute, and persistent pain types to minimize the cumulative pain that incorporates opioid adverse effects (discomfort and dependence) and the risk of tolerance or hypersensitivity (THS) developed with opioid use. After finding closed-form solutions for each pain type, we analytically investigate the sensitivity of acute pain prescriptions and examine policies on incorporation of THS, patient handover, and adaptive treatments. Our analyses show that the role of adverse effects in prescribing decisions is as critical as that of the pain level. Interestingly, we find that the optimal prescription duration is not necessarily increasing with the recovery time. We show that not incorporating THS or information curtailment at patient handovers leads to overprescribing that can be mitigated by adaptive treatments. Last, using real-life pain and opioid use data from two sources, we estimate THS parameters and discuss the proximity of our model to clinical practice. This paper has a pain management framework that leads to tractable models. These models can potentially support balanced opioid prescribing after their validation in a clinical setting. Then, they can be helpful to policy makers in assessment of prescription policies and of the controversy around over- and underprescribing.","PeriodicalId":46460,"journal":{"name":"Decision Analysis","volume":"11 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2022-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74744210","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}
During the COVID-19 pandemic, staying home proved to be an effective way to mitigate the spread of the virus. Stay-at-home orders and guidelines were issued by governments across the globe and were followed by a large portion of the population in the early stages of the outbreak when there was a lack of COVID-specific medical knowledge. The decision of whether to stay home came with many trade-offs, such as risking personal exposure to the virus when leaving home or facing financial and mental health burdens when remaining home. In this research, we study how individuals make strategic decisions to balance these conflicting outcomes. We present a model to study individuals’ decision making based on decision and prospect theory, and we conduct sensitivity analysis to study the fluctuations in optimal strategies when there are changes made to the model’s parameters. A Monte Carlo simulation is implemented to further study the performance of our model, and we compare our simulation results with real data that captures individuals’ stay-at-home decisions. Overall, this research models and analyzes the behaviors of individuals during the COVID-19 pandemic and can help support decision making regarding control measures and policy development when public health emergencies appear in the future.
{"title":"Stay Home or Not? Modeling Individuals’ Decisions During the COVID-19 Pandemic","authors":"Qifeng Wan, Xuan-hua Xu, Kyle Hunt, J. Zhuang","doi":"10.1287/deca.2021.0437","DOIUrl":"https://doi.org/10.1287/deca.2021.0437","url":null,"abstract":"During the COVID-19 pandemic, staying home proved to be an effective way to mitigate the spread of the virus. Stay-at-home orders and guidelines were issued by governments across the globe and were followed by a large portion of the population in the early stages of the outbreak when there was a lack of COVID-specific medical knowledge. The decision of whether to stay home came with many trade-offs, such as risking personal exposure to the virus when leaving home or facing financial and mental health burdens when remaining home. In this research, we study how individuals make strategic decisions to balance these conflicting outcomes. We present a model to study individuals’ decision making based on decision and prospect theory, and we conduct sensitivity analysis to study the fluctuations in optimal strategies when there are changes made to the model’s parameters. A Monte Carlo simulation is implemented to further study the performance of our model, and we compare our simulation results with real data that captures individuals’ stay-at-home decisions. Overall, this research models and analyzes the behaviors of individuals during the COVID-19 pandemic and can help support decision making regarding control measures and policy development when public health emergencies appear in the future.","PeriodicalId":46460,"journal":{"name":"Decision Analysis","volume":"10 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86902254","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}
Our first two articles address decisions involving the passage of time. First, Steven A. Lippman and John W. Mamer explore the question of whether making “Exploding Offers” is beneficial to an employer seeking to hire or, in a more general framing of the question, to a purchaser of an asset. Next, in “Dynamic Purchase Decisions Under Regret: Price and Availability,” Enrico Diecidue, Nils Rudi, and Wenjie Tang examine situations in which a person can make a forward purchase in period 1 or a spot purchase in period 2. Our next two articles involve game theoretic models. In our third article, Steven A. Lippman and Kevin F. McCardle model joint decision making (motivated by dividing up a fortune) via “Embedded Nash Bargaining: Risk Aversion and Impatience.” The fourth article is “Robust Adversarial Risk Analysis: A Level-k Approach,” by Laura McLay, Casey Rothschild, and Seth Guikema. The final article is on “A Framework for Solving Hybrid Influence Diagrams Containing Deterministic Conditional Distributions,” by Yijing Li and Prakash P. Shenoy.
我们的前两篇文章讨论了涉及时间流逝的决策。首先，Steven a . Lippman和John W. Mamer探讨了这样一个问题，即“爆炸性报价”是否对寻求招聘的雇主有利，或者从更一般的角度来看，对资产的购买者有利。接下来，在“后悔下的动态购买决策:价格和可得性”一文中，Enrico Diecidue, Nils Rudi和Wenjie Tang研究了一个人可以在第一阶段进行远期购买或在第二阶段进行现货购买的情况。我们接下来的两篇文章涉及博弈论模型。在我们的第三篇文章中，Steven a . Lippman和Kevin F. McCardle通过“嵌入式纳什议价:风险厌恶和不耐烦”对共同决策(由分割财富驱动)进行了建模。第四篇文章是Laura McLay、Casey Rothschild和Seth Guikema撰写的“稳健的对抗性风险分析:Level-k方法”。最后一篇文章是关于“解决包含确定性条件分布的混合影响图的框架”，作者是Yijing Li和Prakash P. Shenoy。
{"title":"From the Editor---Decisions over Time (Exploding Offers or Purchase Regret), in Game Settings (Embedded Nash Bargaining or Adversarial Games), and in Influence Diagrams","authors":"L. R. Keller","doi":"10.1287/DECA.1110.0229","DOIUrl":"https://doi.org/10.1287/DECA.1110.0229","url":null,"abstract":"Our first two articles address decisions involving the passage of time. First, Steven A. Lippman and John W. Mamer explore the question of whether making “Exploding Offers” is beneficial to an employer seeking to hire or, in a more general framing of the question, to a purchaser of an asset. Next, in “Dynamic Purchase Decisions Under Regret: Price and Availability,” Enrico Diecidue, Nils Rudi, and Wenjie Tang examine situations in which a person can make a forward purchase in period 1 or a spot purchase in period 2. Our next two articles involve game theoretic models. In our third article, Steven A. Lippman and Kevin F. McCardle model joint decision making (motivated by dividing up a fortune) via “Embedded Nash Bargaining: Risk Aversion and Impatience.” The fourth article is “Robust Adversarial Risk Analysis: A Level-k Approach,” by Laura McLay, Casey Rothschild, and Seth Guikema. The final article is on “A Framework for Solving Hybrid Influence Diagrams Containing Deterministic Conditional Distributions,” by Yijing Li and Prakash P. Shenoy.","PeriodicalId":46460,"journal":{"name":"Decision Analysis","volume":"18 1","pages":"1-5"},"PeriodicalIF":1.9,"publicationDate":"2012-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88794660","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}
L. R. Keller, R. Soyer, F. Ruggeri, Jason R. W. Merrick
The objective of the special issue is to introduce a new theme, the use of game theory and decision theory in reliability analysis and risk analysis. The special issue aims to bring together novel research from disciplines that have the potential to contribute to this theme, including (but not limited to) economics, engineering, finance, mathematics, medical sciences, military sciences, probability, and statistics. Papers must tackle a problem in risk or reliability using the tools of decision theory or game theory (or both). The issue will not only consider papers presented at the Second Symposium on Games and Decisions in Reliability and Risk, to be held at the Hotel Villa Carlotta, Belgirate (VB), Lake Maggiore, Italy, May 19–21, 2011 (http://www.mi.imati.cnr.it/conferences/gdrr11.html), but will also be open to the public for submission of papers relevant to the theme. The deadline for submission of papers is April 25, 2011. Papers limited to 12 double-spaced pages (including references and figures/tables) should be submitted at http://mc.manuscriptcentral.com/deca and should follow the Decision Analysis author submission guidelines given at http://www.informs.org/Pubs/DA/ Submission-Guidelines. All submissions will go through the standard review process of Decision Analysis. Submitting authors should indicate their desire to be considered for the special issue in the cover letter to Editor-in-Chief L. Robin Keller, completed during the submission process. Technical questions about submissions may be directed to Managing Editor Kelly M. Kophazi (kelly.kophazi@informs.org). For more information about the special issue, please contact:
这期特刊的目的是介绍一个新的主题，即博弈论和决策理论在可靠性分析和风险分析中的应用。本期特刊旨在汇集有可能对这一主题做出贡献的学科的新研究，包括(但不限于)经济学、工程学、金融学、数学、医学、军事科学、概率论和统计学。论文必须使用决策理论或博弈论(或两者兼而有之)的工具来解决风险或可靠性问题。该问题不仅将考虑在2011年5月19日至21日在意大利Maggiore湖的Belgirate Villa Carlotta酒店(VB)举行的关于可靠性和风险的游戏和决策的第二届研讨会(http://www.mi.imati.cnr.it/conferences/gdrr11.html)上发表的论文，而且还将向公众开放提交与主题相关的论文。论文提交截止日期为2011年4月25日。论文不超过12页，双倍行距(包括参考文献和图表/表格)，应提交至http://mc.manuscriptcentral.com/deca，并应遵循http://www.informs.org/Pubs/DA/提交指南中给出的决策分析作者提交指南。所有提交的文件将通过决策分析的标准审查程序。投稿作者应在投稿过程中给主编L. Robin Keller的封面信中表明他们希望被特刊考虑的愿望。有关提交的技术问题可直接向总编辑Kelly M. Kophazi (kelly.kophazi@informs.org)询问。有关特刊的详情，请联络:
{"title":"Call for Papers---Special Issue of Decision Analysis on Games and Decisions in Reliability and Risk: Deadline: April 25, 2011","authors":"L. R. Keller, R. Soyer, F. Ruggeri, Jason R. W. Merrick","doi":"10.1287/DECA.1110.0200","DOIUrl":"https://doi.org/10.1287/DECA.1110.0200","url":null,"abstract":"The objective of the special issue is to introduce a new theme, the use of game theory and decision theory in reliability analysis and risk analysis. The special issue aims to bring together novel research from disciplines that have the potential to contribute to this theme, including (but not limited to) economics, engineering, finance, mathematics, medical sciences, military sciences, probability, and statistics. Papers must tackle a problem in risk or reliability using the tools of decision theory or game theory (or both). The issue will not only consider papers presented at the Second Symposium on Games and Decisions in Reliability and Risk, to be held at the Hotel Villa Carlotta, Belgirate (VB), Lake Maggiore, Italy, May 19–21, 2011 (http://www.mi.imati.cnr.it/conferences/gdrr11.html), but will also be open to the public for submission of papers relevant to the theme. The deadline for submission of papers is April 25, 2011. Papers limited to 12 double-spaced pages (including references and figures/tables) should be submitted at http://mc.manuscriptcentral.com/deca and should follow the Decision Analysis author submission guidelines given at http://www.informs.org/Pubs/DA/ Submission-Guidelines. All submissions will go through the standard review process of Decision Analysis. Submitting authors should indicate their desire to be considered for the special issue in the cover letter to Editor-in-Chief L. Robin Keller, completed during the submission process. Technical questions about submissions may be directed to Managing Editor Kelly M. Kophazi (kelly.kophazi@informs.org). For more information about the special issue, please contact:","PeriodicalId":46460,"journal":{"name":"Decision Analysis","volume":"12 1","pages":"82-82"},"PeriodicalIF":1.9,"publicationDate":"2011-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83379712","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}
Pub Date : 2004-03-01DOI: 10.1287/DECA.1.1.25.17849
S. Cantor
The author provides a comment to the companion literature review, focusing on clinical applications of decision analysis. The theory and application of clinical decision analysis has decreased in the management science and operations research literature, but has become a field in and of itself, with contributions to the medical and analytical communities. Decision scientists should be aware of methodological contributions in the health decision science literature.
{"title":"Clinical Applications in the Decision Analysis Literature (Comment on Keefer et al. 2004)","authors":"S. Cantor","doi":"10.1287/DECA.1.1.25.17849","DOIUrl":"https://doi.org/10.1287/DECA.1.1.25.17849","url":null,"abstract":"The author provides a comment to the companion literature review, focusing on clinical applications of decision analysis. The theory and application of clinical decision analysis has decreased in the management science and operations research literature, but has become a field in and of itself, with contributions to the medical and analytical communities. Decision scientists should be aware of methodological contributions in the health decision science literature.","PeriodicalId":46460,"journal":{"name":"Decision Analysis","volume":"59 6","pages":"25-28"},"PeriodicalIF":1.9,"publicationDate":"2004-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72461007","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}
Pub Date : 2004-03-01DOI: 10.1287/DECA.1.1.29.17846
R. Hämäläinen
This paper looks into the strengths, weaknesses, opportunities, and threats (SWOT) of the field of the applications based on DA techniques; focusing especially on MAVT. The need for best practices and bias-resistant analysis procedures is pointed out. In most application papers there are no reports on the verification or testing of the procedures used. The Internet provides great opportunities in the delivery of DA software and e-learning material. Public sites such as Decisionarium (www.decisionarium.hut.fi) provide encouragement and a low entry level to try value tree analysis in new applications. There are also great opportunities in reaching out the other MCDA communities such as AHP practitioners. Today the need and demand for decision support is perhaps growing most rapidly in environmental problems. A clear trend is also the integration of DA into GIS and other models. Many of the applications are now published in non-OR/MS subject area journals.
{"title":"Reversing the Perspective on the Applications of Decision Analysis (Comment on Keefer et al. 2004)","authors":"R. Hämäläinen","doi":"10.1287/DECA.1.1.29.17846","DOIUrl":"https://doi.org/10.1287/DECA.1.1.29.17846","url":null,"abstract":"This paper looks into the strengths, weaknesses, opportunities, and threats (SWOT) of the field of the applications based on DA techniques; focusing especially on MAVT. The need for best practices and bias-resistant analysis procedures is pointed out. In most application papers there are no reports on the verification or testing of the procedures used. The Internet provides great opportunities in the delivery of DA software and e-learning material. Public sites such as Decisionarium (www.decisionarium.hut.fi) provide encouragement and a low entry level to try value tree analysis in new applications. There are also great opportunities in reaching out the other MCDA communities such as AHP practitioners. Today the need and demand for decision support is perhaps growing most rapidly in environmental problems. A clear trend is also the integration of DA into GIS and other models. Many of the applications are now published in non-OR/MS subject area journals.","PeriodicalId":46460,"journal":{"name":"Decision Analysis","volume":"35 1","pages":"29-35"},"PeriodicalIF":1.9,"publicationDate":"2004-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81341475","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}
Pub Date : 2004-03-01DOI: 10.1287/DECA.1.1.36.17843
D. Keefer, C. Kirkwood, J. Corner
Our article "Perspective on Decision Analysis Applications, 1990--2001" provides a comprehensive listing of decision analysis applications published between 1990 and 2001 in the 16 journals that we surveyed and uses this together with results from a previous survey to identify, and provide perspective on, trends and developments in decision analysis applications. Cantor (2004) and HA¤mA¤lA¤inen (2004) provide useful comments and additional references that supplement the material in our article, and we agree with many of their comments. However, we do not agree with their view that our definition of "decision analysis" is too restrictive. We believe that, after 35 years, the core of decision analysis is now well established and that we have used the generally understood definition in selecting the applications included in our article.
{"title":"Response to Comments on Keefer et al. (2004)","authors":"D. Keefer, C. Kirkwood, J. Corner","doi":"10.1287/DECA.1.1.36.17843","DOIUrl":"https://doi.org/10.1287/DECA.1.1.36.17843","url":null,"abstract":"Our article \"Perspective on Decision Analysis Applications, 1990--2001\" provides a comprehensive listing of decision analysis applications published between 1990 and 2001 in the 16 journals that we surveyed and uses this together with results from a previous survey to identify, and provide perspective on, trends and developments in decision analysis applications. Cantor (2004) and HA¤mA¤lA¤inen (2004) provide useful comments and additional references that supplement the material in our article, and we agree with many of their comments. However, we do not agree with their view that our definition of \"decision analysis\" is too restrictive. We believe that, after 35 years, the core of decision analysis is now well established and that we have used the generally understood definition in selecting the applications included in our article.","PeriodicalId":46460,"journal":{"name":"Decision Analysis","volume":"33 1","pages":"36-38"},"PeriodicalIF":1.9,"publicationDate":"2004-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80204939","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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