Dynamic adaptive decision support for strategic decision-making in healthcare organizations

被引:0
作者
Aarninkhof-Kamphuis, Anke [1 ]
Voordijk, Hans [1 ]
Dewulf, Geert [1 ]
机构
[1] Univ Twente, Fac Engn Technol, Dept Civil Engn & Management, Enschede, Netherlands
关键词
Strategic decision-making; Healthcare organization; Dynamic adaptive decision support; Corporate real estate management; SYSTEMS; UNCERTAINTY;
D O I
10.1108/JHOM-07-2023-0229
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
PurposeThe main objective of this study was to design a dynamic adaptive decision support model for healthcare organizations facing deep uncertainties by considering promising dynamic adaptive approaches. The main argument for this is that healthcare organizations have to make strategic decisions under deep uncertainty, but lack an approach to deal with this.Design/methodology/approachA Dynamic Adaptive Decision Support model (DADS) is designed using the Design Science Research methodology. The evaluation of an initial model leads, through two case studies on ongoing and strategic decision-making, to the final design of this needed model for healthcare organizations.FindingsThe research reveals the relevance of the designed dynamic and adaptive tool to support strategic decision-making for healthcare organizations. The final design of DADS innovates Decision Making under Deep Uncertainty (DMDU) approaches in an organizational context for ongoing and strategic decision-making.Originality/valueThe designed model applies the Dynamic Adaptive Policy Pathways approach in an organizational context and more specifically in health care organizations. It further integrates Corporate Real Estate Management knowledge and experience to develop a most needed tool for decision-makers in healthcare. This is the first DADS designed for an organization facing deep uncertainties in a rapidly changing healthcare environment and dealing with ongoing and strategic decision-making.
引用
收藏
页码:638 / 661
页数:24
相关论文
共 42 条
[1]   Coping with uncertainties: challenges for decision makers in healthcare [J].
Aarninkhof-Kamphuis, Anke ;
Voordijk, Hans ;
Dewulf, Geert .
JOURNAL OF FACILITIES MANAGEMENT, 2023, :883-899
[2]  
Abbadi A., 2021, INT C MODELLING SIMU, P377
[3]  
[Anonymous], 2003, Shaping the Next One Hunderd Years-New Methods for Quantitative Long-Term Policy Analysis
[4]   Resource dependency and strategy in healthcare organizations during a time of scarce resources: evidence from the metropolitan area of cologne [J].
Ansmann, Lena ;
Vennedey, Vera ;
Hillen, Hendrik Ansgar ;
Stock, Stephanie ;
Kuntz, Ludwig ;
Pfaff, Holger ;
Mannion, Russell ;
Hower, Kira Isabel .
JOURNAL OF HEALTH ORGANIZATION AND MANAGEMENT, 2021, 35 (09) :211-227
[5]  
Beckers R., 2016, LEARNING SPACE ODYSS
[6]   An integrated approach for planning a long-term care network with uncertainty, strategic policy and equity considerations [J].
Cardoso, Teresa ;
Oliveira, Monica Duarte ;
Barbosa-Povoa, Ana ;
Nickel, Stefan .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2015, 247 (01) :321-334
[7]  
Coccia M., 2018, Journal of Social and Administrative Sciences JSAS, V4, P291, DOI [DOI 10.1453/JSAS.V4I4.1518, 10.1453/jsas.v4i4.1518]
[8]  
de Neufville R., 2019, Decision making under deep uncertainty: from theory to practice, P117, DOI [DOI 10.1007/978-3-030-05252-2_6, 10.1007/978-3-030-05252-2_6]
[9]  
Den Heijer Alexandra., 2011, MANAGING U CAMPUS IN
[10]   Making sense of future uncertainties using real options and scenario planning [J].
Dortland, Maartje Van Reedt ;
Voordijk, Hans ;
Dewulf, Geert .
FUTURES, 2014, 55 :15-31