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Journal articles on the topic 'Complexity of decision making'

Author: Grafiati

Published: 4 June 2021

Last updated: 17 February 2022

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1

Shedid, Daniel, and Edward C. Benzel. "DECISION MAKING PROCESS." Neurosurgery 60, suppl_1 (January 1, 2007): S1–166—S1–169. http://dx.doi.org/10.1227/01.neu.0000249279.79686.e3.

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Abstract CLINICAL PROBLEMS ARE often complex. Problems of great complexity are usually associated with a commensurately greater degree of difficulty with respect to the decision making process. This is most certainly true regarding the management of cervical spondylosis. Usually, clinicians make clinically appropriate decisions. However, more often than realized, suboptimal decisions may be made. Therefore, an assessment of the types of errors regarding clinical decision making are worthy of consideration. In this article, a scheme for decision making regarding the management of cervical spondylosis is presented.

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Gorzeń-Mitka, Iwona, and Małgorzata Okręglicka. "Improving Decision Making in Complexity Environment." Procedia Economics and Finance 16 (2014): 402–9. http://dx.doi.org/10.1016/s2212-5671(14)00819-3.

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Bossaerts, Peter, and Carsten Murawski. "Computational Complexity and Human Decision-Making." Trends in Cognitive Sciences 21, no. 12 (December 2017): 917–29. http://dx.doi.org/10.1016/j.tics.2017.09.005.

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Susskind, Lawrence. "Complexity Science and Collaborative Decision Making." Negotiation Journal 26, no. 3 (July 1, 2010): 367–70. http://dx.doi.org/10.1111/j.1571-9979.2010.00278.x.

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5

Chung, Kon Shing Kenneth. "Understanding Decision Making through Complexity in Professional Networks." Advances in Decision Sciences 2014 (December 11, 2014): 1–10. http://dx.doi.org/10.1155/2014/215218.

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The attitudes of general practitioners (GP) play an influential role in their decision making about patient treatment and care. Considering the GP-patient encounter as a complex system, the interactions between the GP and their personal network of peers give rise to “aggregate complexity,” which in turn influences the GP’s decisions about patient treatment. This study models aggregate complexity and its influence in decision making in primary care through the use of social network metrics. Professional network and attitudinal data on decision making responsibility from 107 rural GPs were analysed. Social network measures of “density” and “inclusiveness” were used for computing the “interrelatedness” of components within such a “complex system.” The “number of components” and “degree of interrelatedness” were used to determine the complexity profiles, which was then used to associate with responsibility in decision making for each GP. GPs in simple profiles (i.e., with low components and interactions) in contrast to those in nonsimple profiles, indicate a higher responsibility for the decisions they make in medical care. This study suggests that social networks-based complexity profiles are useful for understanding decision making in primary care as it accounts for the role of influence through the professional networks of GPs.

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Ravenwood, Clare, Graham Walton, and Derek Stephens. "Complexity in decision making: Determining university library opening hours." Journal of Librarianship and Information Science 51, no. 2 (August 28, 2017): 488–96. http://dx.doi.org/10.1177/0961000617726127.

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Making decisions on academic library opening hours is complex with many pressures on managers. This research surveys senior academic library managers from the UK, using a questionnaire to reveal views on library opening hours, the decision-making process, and the pressures which influenced their decisions. A variety of factors were found, in particular satisfying undergraduate demands. The research also revealed the sources of information important in making decisions on opening hours and the influence of ‘political’ issues in the decision-making process. Some institutions remove complexity by utilising 24/7 opening, though this is not an option for many.

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Rábová, I., V. Konečný, and A. Matiášová. "Decision making with support of artificial intelligence." Agricultural Economics (Zemědělská ekonomika) 51, No. 9 (February 20, 2012): 385–88. http://dx.doi.org/10.17221/5124-agricecon.

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  Development of software modules for decision support is currently a basic trend in the creation of enterprise Information Systems (IS). The IS is basically a support system of the enterprise Decision System, therefore we can regard it as a very important factor of the competition ability and enterprise prosperity. Conventional IS modules provide the enterprise managers a lot of useful information. Nevertheless, own decision process in view of difficulty, complexity or creation disability of decision process model is very often problematic. This contribution is oriented by its content to appropriate choice realization of modules for support decision processes by using of artificial intelligence methods.      

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Horowitz, Irwin A., Lynne ForsterLee, and Ian Brolly. "Effects of trial complexity on decision making." Journal of Applied Psychology 81, no. 6 (1996): 757–68. http://dx.doi.org/10.1037/0021-9010.81.6.757.

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Lai, Shih-Kung. "Plan-based decision making for urban complexity." Journal of Urban Management 5, no. 1 (June 2016): 1–2. http://dx.doi.org/10.1016/j.jum.2016.03.001.

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Aggarwal, Rajesh. "Risk, Complexity, Decision Making, and Patient Care." JAMA Surgery 153, no. 3 (March 1, 2018): 208. http://dx.doi.org/10.1001/jamasurg.2017.3930.

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Morenz, Barry, and Bruce Sales. "Complexity of Ethical Decision Making in Psychiatry." Ethics & Behavior 7, no. 1 (March 1997): 1–14. http://dx.doi.org/10.1207/s15327019eb0701_1.

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Evans, Megan C., Federico Davila, Anne Toomey, and Carina Wyborn. "Embrace complexity to improve conservation decision making." Nature Ecology & Evolution 1, no. 11 (October 2, 2017): 1588. http://dx.doi.org/10.1038/s41559-017-0345-x.

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Hanif, Harliza Mohd, Daud Mohamad, and Rosma Mohd Dom. "Relative Complexity Index for Decision-Making Method." Mathematics and Statistics 9, no. 3 (May 2021): 233–42. http://dx.doi.org/10.13189/ms.2021.090304.

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Bruce, A. C., and J. E. V. Johnson. "Decision-Making under Risk: Effect of Complexity on Performance." Psychological Reports 79, no. 1 (August 1996): 67–76. http://dx.doi.org/10.2466/pr0.1996.79.1.67.

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This paper examined the effect of complexity on performance in decision-making under risk employing a database of 1161 randomly sampled betting decisions made during 1987 in offcourse horserace betting offices situated throughout the UK. The setting for the study is characterised by important ecological advantages over laboratory or alternative naturalistic settings. Complexity is defined in terms of both the number of alternatives in the decision-maker's choice set (number of horses in a race) and the complexity of the set of attributes for each horserace (handicap vs nonhandicap races). Performance was not adversely affected by an increase in the number of alternatives and only to a limited extent by an increase in attribute-based complexity. The robustness of the results is reinforced by adjustments which acknowledge and control for the differential random chance of correct decision-making across groups of events with differing complexity.

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Smith, Wayne W., Robert E. Pitts, Steve W. Litvin, and Deepti Agrawal. "Exploring the Length and Complexity of Couples Travel Decision Making." Cornell Hospitality Quarterly 58, no. 4 (April 19, 2017): 387–92. http://dx.doi.org/10.1177/1938965517704374.

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A quasi-experiment is used to examine the dynamics of the shared decision-making process by observing couples in real time as they make decisions about an overnight stay at a luxury resort. Observations and video recordings of the decision processes of 24 couples were coded and analyzed. The time to final decision, number, and type of tactics used were found to vary with couples’ length of experience with one another. Observation indicated that couples with greater travel experience together relied on “predealing” based on their experience together to avoid conflict, while less-experienced couples’ decisions were more likely to yield winners and losers. These findings and those related to the use of persuasive tactics by members of the couple dyads provide the basis for specific recommendations for marketing travel products.

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Badham, Stephen P., and Calum A. Hamilton. "Influences of complexity on decision making in young and older adults." Europe’s Journal of Psychology 16, no. 2 (May 29, 2020): 280–99. http://dx.doi.org/10.5964/ejop.v16i2.1958.

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Leading theory hypothesizes that age deficits in decision making may rise as the complexity of decision-related information increases. This suggests that older adults would benefit relative to young adults from simplification of information used to inform decision making. Participants indicated political, nutritional and medical preferences and then chose between politicians, foods and medicines. The amount of information presented was systematically varied but age differences were largely similar for simple and complex trials. Paradoxically, the data showed that decisions based on simpler information could be less aligned with participant’s preferences than decisions based on more complex information. Further analyses suggested that participants may have been responding purely on the basis of their most valued preferences and that when information about those preferences was not presented, decision making became poorer. Contrary to our expectations, simplification of information by exclusion may therefore hinder decision making and may not particularly help older adults.

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Askren, Annette, and Paula Leslie. "Complexity of Clinical Decision Making: Consent, Capacity, and Ethics." Seminars in Speech and Language 40, no. 03 (June 2019): 162–69. http://dx.doi.org/10.1055/s-0039-1688838.

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AbstractSpeech–language pathologists (SLPs), and really their patients, are often faced with challenging clinical decisions to be made. Patients may decline interventions recommended by the SLP and are often inappropriately labeled “noncompliant.” The inappropriateness of this label extends beyond the negative charge; the patient's right to refuse is, in fact, protected by law. Anecdotal exchanges, social media platforms, and American Speech-Language-Hearing Association forums have recently revealed that many SLPs are struggling with the patient's right to decline. Many are not comfortable with the informed consent process and what entails patients' capacity to make their own medical decisions. Here, we discuss the basics of clinical decision-making ethics with intent to minimize the clinician's discomfort with the right to refuse those thickened liquids and eliminate the practice of defensive medicine.

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Cioffi, Jane, and Roslyn Markham. "Clinical decision‐making by midwives: managing case Complexity." Journal of Advanced Nursing 25, no. 2 (February 1997): 265–72. http://dx.doi.org/10.1046/j.1365-2648.1997.1997025265.x.

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Finucane, Melissa L., C. K. Mertz, Paul Slovic, and Elizabeth Scholze Schmidt. "Task Complexity and Older Adults' Decision-Making Competence." Psychology and Aging 20, no. 1 (2005): 71–84. http://dx.doi.org/10.1037/0882-7974.20.1.71.

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Osman, Hana, and Marion A. Becker. "Complexity of Decision-Making in a Nursing Home." Journal of Gerontological Social Work 42, no. 1 (May 14, 2004): 27–40. http://dx.doi.org/10.1300/j083v42n01_03.

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Antucheviciene, Jurgita, Madjid Tavana, Mehrbakhsh Nilashi, and Romualdas Bausys. "Managing Information Uncertainty and Complexity in Decision-Making." Complexity 2017 (2017): 1–3. http://dx.doi.org/10.1155/2017/1268980.

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Franklin, Amy, Ying Liu, Zhe Li, Vickie Nguyen, Todd R. Johnson, David Robinson, Nnaemeka Okafor, Brent King, Vimla L. Patel, and Jiajie Zhang. "Opportunistic decision making and complexity in emergency care." Journal of Biomedical Informatics 44, no. 3 (June 2011): 469–76. http://dx.doi.org/10.1016/j.jbi.2011.04.001.

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23

Diehl, Ernst, and John D. Sterman. "Effects of Feedback Complexity on Dynamic Decision Making." Organizational Behavior and Human Decision Processes 62, no. 2 (May 1995): 198–215. http://dx.doi.org/10.1006/obhd.1995.1043.

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24

Azadfallah, Mohammad. "Multi-Criteria Decision Making for Ranking Decision Making Units." International Journal of Productivity Management and Assessment Technologies 6, no. 1 (January 2018): 17–36. http://dx.doi.org/10.4018/ijpmat.2018010102.

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There is no doubt the Data Envelopment Analysis (DEA) is a powerful method for the efficiency evaluation of Decision Making Units (DMUs) with multiple inputs and outputs. Despite its usefulness, DEA has some notable limitations. A significant drawback with this approach is that inability to fully rank the DMUs. In the extant literature, different methods for this purpose have been suggested. While, in the traditional method the first step for the DEA approach is used, and results of this step are input for the DEA ranking method in the second step. To reduce the computational complexity of the traditional method, a new Multiple Criteria Decision Making (MCDM) approach is proposed in this article. In the proposed approaches, one step can achieve full ranking for all DMUs. The results show that although out of 20 DMUs are first in the final ranking ordered by the DEA, the author proposed methods can consider full ranking. Agreement of the proposed methods with the existing approaches are measured by the Spearman's rank correlation coefficient technique. The findings of this study reveal that TOPSIS, Neo-TOPSIS, and AHP ranking results are consistent with the DEA ranking method. Therefore, these proposed methods appear as the possible alternatives to the DEA and DEA ranking models.

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Daly, Barbara J., Sara L. Douglas, Elizabeth O’Toole, James Rowbottom, Alan Hoffer, Amy R. Lipson, and Christopher Burant. "Complexity Analysis of Decision-Making in the Critically Ill." Journal of Intensive Care Medicine 33, no. 10 (November 20, 2016): 557–66. http://dx.doi.org/10.1177/0885066616678394.

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Rationale: Despite multiple trials of interventions to improve end-of-life care of the critically ill, there is a persistent lack of understanding of factors associated with barriers to decision-making at the end of life. Objective: To apply the principles of complexity science in examining the extent to which transitions to end-of-life care can be predicted by physician, family, or patient characteristics; outcome expectations; and the evaluation of treatment effectiveness. Methods: A descriptive, longitudinal study was conducted in 3 adult intensive care units (ICUs). Two hundred sixty-four family surrogates of patients lacking decisional capacity and the physicians caring for the patients were interviewed every 5 days until ICU discharge or patient death. Measurements: Characteristics of patients, physicians, and family members; values and preferences of physicians and family; and evaluation of treatment effectiveness, expectations for patient outcomes, and relative priorities in treatment (comfort vs survival). The primary outcome, focus of care, was categorized as (1) maintaining a survival orientation (no treatment limitations), (2) transitioning to a stronger palliative focus (eg, some treatment limitations), or (3) transitioning to an explicit end-of-life, comfort-oriented care plan. Main Results: Physician expectations for survival and future cognitive status were the only variables consistently and significantly related to the focus of care. Neither physician or family evaluations of treatment effectiveness nor what was most important to physicians or family members was influential. Conclusion: Lack of influence of family and physician views, in comparison to the consistent effect of survival probabilities, suggests barriers to incorporation of individual values in treatment decisions.

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Asmussen, Jesper Normann, Jesper Kristensen, and Brian Vejrum Wæhrens. "Cost estimation accuracy in supply chain design." International Journal of Physical Distribution & Logistics Management 48, no. 10 (November 5, 2018): 995–1019. http://dx.doi.org/10.1108/ijpdlm-07-2018-0268.

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PurposeThe purpose of this paper is to investigate how management attention and supply chain complexity affect the decision-making process and cost estimation accuracy of supply chain design (SCD) decisions.Design/methodology/approachThe research follows an embedded case study design. Through the lens of the behavioural theory of the firm, the SCD decision process and realised outcomes are investigated through longitudinal data collection across ten embedded cases with varying degrees of supply chain decision-making complexity and management attention.FindingsThe findings suggest that as supply chain decision-making complexity increases, cost estimation accuracy decreases. The extent to which supply chain decision-making complexity is readily recognised influences the selection of strategies for information search and analysis and, thus, impacts resulting cost estimation errors. The paper further shows the importance of management attention for cost estimation accuracy, especially management attention based on conflicting goals induce behaviours that improve estimation ability.Research limitations/implicationsA framework proposing a balance between supply chain decision-making complexity and management attention in SCD decisions is proposed. However, as an embedded case study the research would benefit from replication to externally validate results.Originality/valueThe method used in this study can identify how supply chain complexity is related to cost estimation errors and how management attention is associated with behaviours that improve cost estimation accuracy, indicating the importance of management attention in complex supply chain decision-making.

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Settipane, Russell A., Don A. Bukstein, and Marc A. Riedl. "Hereditary angioedema and shared decision making." Allergy and Asthma Proceedings 41, no. 6 (November 1, 2020): S55—S60. http://dx.doi.org/10.2500/aap.2020.41.200057.

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Clinical decision-making in hereditary angioedema (HAE) management involves a high degree of complexity given the number of therapeutic agents that are available and the risk for significant morbidity and potential mortality attributable to the disease. Given this complexity, there is an opportunity to develop shared decision-making (SDM) aids and/or tools that would facilitate the interactive participation of practitioners and patients in the SDM process. This article reviews the general constructs of SDM, the unmet need for SDM in HAE, and the steps necessary to create a SDM tool specific for HAE, and outlines the challenges that must be navigated to guide the establishment and widespread implementation of SDM in the management of HAE.

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Magro, Anne M. "Contextual Features of Tax Decision-Making Settings." Journal of the American Taxation Association 21, s-1 (January 1, 1999): 63–73. http://dx.doi.org/10.2308/jata.1999.21.s-1.63.

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Prior research in psychology and accounting suggests that features of the decision-making task and context affect information processing, yet the decision-making context is often ignored in tax judgment and decision-making research. Two primary decision contexts in the tax setting are planning and compliance. If these two contexts differ on significant features, the information processing of tax professionals in the settings also is likely to differ. An analysis of the characteristics of tax planning and compliance contexts suggests that planning problems are generally characterized by greater complexity, ambiguity, and justifiability demands than are compliance problems. Experienced tax professionals' knowledge of these differences in complexity, ambiguity, and justifiability demands of problems in the planning and compliance contexts was tested in an experiment in which decision-making context was manipulated. Each participant rated the complexity, ambiguity, and justifiability demands of six research cases. As predicted, participants in the planning condition rated the cases as higher in complexity, ambiguity, and justifiability demands than did participants in the compliance condition. Behavioral implications of these differences were demonstrated in that managers in the planning context budgeted significantly more time for staff to complete tax research than did those in the compliance context.

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Hayes, J., A. Moore, G. Benwell, and B. L. W. Wong. "Identifying Decision Complexity Factors in Ambulance Command and Control." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 49, no. 3 (September 2005): 234–37. http://dx.doi.org/10.1177/154193120504900305.

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To understand the decision making processes of fourteen ambulance command and control (C2) operators, interviews employing the critical decision method were conducted in two ambulance C2 centres. An emergent themes analysis of the interview transcripts resulted in the identification of the strategies used by the operators when making dispatch decisions. To complement this work, factors that were considered to contribute to the complexity of the decision making task were identified and then rated by the operators to determine the extent of this contribution. As a result the researchers obtained quantitative data regarding the factors that were considered to contribute the greatest to the complexity of the dispatch task from the view point of the operators. The benefits of this approach include the identification of cognitive 'choke points' in the dispatch process that can be addressed during interface design.

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Tsekeris, Charalambos, and Nicolas Demertzis. "Inclusion of People in Decision-Making." Politička misao 57, no. 4 (February 25, 2021): 60–77. http://dx.doi.org/10.20901/pm.57.4.03.

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Reflecting on the May 2019 European Parliament elections, the EU democratic ‎institutions are in need of efficiently responding to the discrepancies between‎ public agendas and policy-making (as shown in the Macedonia naming‎ dispute), and the threatening dynamics of authoritarian populism, as well as‎ to unpredictable reactions from diverse groups and citizens, especially from ‎the neglected, excluded and marginal ones. These citizens cannot handle complexity‎ and react by voting for protest candidates/movements and supporting ‎radical, yet oversimplified and inadequate, solutions to complex problems.‎ Given the potentiality of crisis cascades and that an over-standardized “one‎ size fits all” approach does not work anymore, the EU policy-making experts ‎should arguably turn their analytic attention to existing drivers of political ‎destabilisation by adopting new knowledge bases and sources. This pertains‎ to a fresh theoretical understanding of nonlinear sociopolitical phenomena‎(from populist reactions of any kind to social media behaviours), that is, a‎ deeper, complexity-friendly approach drawn from new scientific advancements‎ and coupled with innovative policy designs, aimed to rebalance the‎ system and to defend the European project against further failures.‎

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Jansson, Kaisu, Juha Tuunainen, and Tuija Mainela. "Concealing paradoxes in decision-making during hospital hybridization – a systems theoretical analysis." Journal of Health Organization and Management 35, no. 2 (February 11, 2021): 195–211. http://dx.doi.org/10.1108/jhom-08-2020-0334.

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PurposeWhile previous health-care-related hybridity research has focused on macro- and micro-level investigations, this paper aims to study hybridization at the organizational level, with a specific focus on decision-making. The authors investigate how new politico-economic expectations toward a university hospital as a hybrid organization become internalized via organizational decision-making, resulting in the establishment of a new business collaboration and innovation-oriented unit.Design/methodology/approachThe authors employed a social systems theoretical framework to explore organizational decision-making processes involved in the establishment of the new hybrid hospital unit. Drawing on 15 interviews and nine organizational documents, the authors describe and analyze three decision-making cycles using the concepts of complexity, decision and justification.FindingsThe findings reveal the challenging nature of decision-making during hybridization, as decisions regarding unprecedented organizational structures and activities cannot be justified by traditional decision premises. The authors show that decision-makers use a combination of novel justification strategies, namely, justification by problems, by examples and by obligations, to legitimize decisions oriented at non-traditional activities. Further, the analysis reveals how expectations of several societal systems, i.e. health care, education, science, law, economy and politics, are considered in decision-making taking place in hybrid organizations.Originality/valueThe study draws attention to the complexity of decision-making in a hybrid context and highlights the role of justification strategies in partially reducing complexity by concealing the paradoxical nature of decision-making and ensuring the credibility of resulting decisions. Also, the study presents a move beyond the dualism inherent in many previous hybridity studies by illustrating the involvement of several societal systems in hybridization.

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Baghbanian, Abdolvahab, Ian Hughes, Ali Kebriaei, and Freidoon A. Khavarpour. "Adaptive decision-making: how Australian healthcare managers decide." Australian Health Review 36, no. 1 (2012): 49. http://dx.doi.org/10.1071/ah10971.

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Despite many calls for the utilisation of research evidence in health policy-making, it is not widely practised, and little is known about how decision-makers in healthcare organisations actually make decisions. We recruited a purposive sample of Australian healthcare decision-makers to complete a web-based survey. We then took a sub-sample from willing respondents for individual interviews. All interviews were audio-recorded, transcribed verbatim and coded thematically. We found that resource allocation decision-making varied greatly across the Australian healthcare system. Decision-making was highly dependent on the operational context in time, place and purpose, and that research evidence was rarely exploited to its full potential. Decision-making involved a multifaceted interplay of elements in situation of inquiry. All decisions were made by networks or collectives of people; and no instance of individual decision-making was reported. This varied, social and contextual nature of decision-making points to a complexity that is not reflected in systematic evidence-based reviews or evidence-based models for decision-making, and we did not discover an appropriate model to reflect this complexity in the health- related literature. We developed a model of ‘adaptive decision-making’ that has potential to guide robust decision-making in complex situations, and could have some value as an explanatory or theoretical model for teaching and practice. What is known about the topic? The topic is certainly novel and original, relevant and timely for academics and healthcare decision-makers. Despite increasing calls for the use of systematic evidence-based reviews including economic evaluations, the way in which decision-makers arrive at their allocation decisions and how such decisions reflect concern for economic efficiency is often blurred. This topic is an important one for its relevance to the current difficulties in the complex situation of healthcare. What does this paper add? This paper shows that decision-makers acknowledged the integration of economic principles as contextual realities into their decision-making activities, rather than utilising the results of ever-more seemingly ‘technically sound’ economic evaluations, which cannot address the inherent uncertainty attached to complex decision-making activities. We developed a novel adaptive model of decision-making generated by the interplay of multiple behaviours and factors in the situation of inquiry. The model is new and takes into account the complexity of the context in time, place, purpose and administrative location. What are the implications for practitioners? This paper should be of interest to a broad readership including those interested in health economics, public health policy, healthcare delivery, healthcare resource allocation and decision-making. The adaptive decision-making model designed in this study has the potential as a guide or heuristic device for teaching and practice. Healthcare decision-makers need to be prepared for complexity and ambiguity and cannot expect the data to tell them everything they need to know. We expect to see a shift in the literature on healthcare decision-making, not away from evidence-based practice and economic evaluation, but towards contextualising these methods in broader, adaptive models of decision-making.

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Van Gils, Marcel, and Erik-Hans Klijn. "Complexity in Decision Making: The Case of the Rotterdam Harbour Expansion. Connecting Decisions, Arenas and Actors in Spatial Decision Making." Planning Theory & Practice 8, no. 2 (June 2007): 139–59. http://dx.doi.org/10.1080/14649350701324359.

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Samuelson, Marissa, Franziska Trede, and Joy Higgs. "Engaging with Diversity and Complexity using Collaborative Approaches to Decision Making." Critical Dietetics 3, no. 2 (December 31, 2016): 43–55. http://dx.doi.org/10.32920/cd.v3i2.1011.

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A key challenge in contemporary dietetic practice is making collaborative decisions about dietary behaviours with a diverse range of patients. Contemporary decision making frameworks for clinical dietetic practice give value to working in a collaborative manner with patients, however, there remains uncertainty with regards to how and when dietitians might apply this approach in their practice.In this doctoral research project, Author 1 used a philosophical hermeneutic approach to deepen understanding of a collaborative approach to decision making in dietetic practice. She also explored the core capabilities required to enact such an approach in early career dietetic practice. The experiences and perceptions of patients and dietitians were explored using in depth interviews and individualized reflective practice activities.The findings suggest that collaborative decision making in dietetic practice is situational and requires the development of a caring and trusting professional relationship to be effective. Other core capabilities needed to enact this approach relate to developing self awareness, establishing an open and transparent dialogue, identifying and exploring common ground and finding the time to think and talk.The final product of the research, the Interpretive Engagement Model of Collaborative Decision Making (Author 1, 2013), can be used as a framework to help practitioners to reflect on their decision making practice.Early exposure in tertiary education to critical dialogues and questioning current practices will cultivate early career dietitians’ capabilities to develop their collaborative decision making practice in future.

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Bloom, Laura A., and Bernard S. Bloom. "DECISION ANALYTIC MODELING IN HEALTH CARE DECISION MAKING." International Journal of Technology Assessment in Health Care 15, no. 2 (May 1999): 332–39. http://dx.doi.org/10.1017/s0266462399015251.

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The need to choose among alternatives instead of allowing the market to make choices has led health care professionals to rely on scientific information as an aid in decision making. Mathematical modeling is one of the increasingly common tools used over the past three decades to produce new information. But we have used almost exclusively noncomplex models to help analyze complex systems problems. The need to integrate the complexity of the interactions of clinical, quality of life, and economic attributes into such models can no longer be ignored. The opportunity is available to use existing complex systems modeling techniques for health care questions to improve the quality of study outputs, which can, in turn, help produce more rational decisions.

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Zhang, Yanzhu, and Alfred Posch. "The Wickedness and Complexity of Decision Making in Geoengineering." Challenges 5, no. 2 (November 6, 2014): 390–408. http://dx.doi.org/10.3390/challe5020390.

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Harz, Markus. "Cancer, Computers and Complexity: Decision Making for the Patient." European Review 25, no. 1 (February 2017): 96–106. http://dx.doi.org/10.1017/s106279871600048x.

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In health care, a trend may be noted to fundamentally question some of today’s assumptions about the traditional roles of medical disciplines, the doctor–patient relationship, the feasibility of medical studies, and about the role of computers as an aid or replacement of doctors. Diagnostics and therapy decision-making become more complex, and no end is in sight. Amounts of health-related data are being collected individually, and through the health care systems. On the example of breast cancer care, technological advances and societal changes can be observed as they take place concurrently, and patterns and hypotheses emerge that will be the focus of this article. In particular, three key changes are to be considered: (1) the growing appreciation of the uniqueness of diseases and the impact of this notion on the future of evidence-based medicine; (2) the acknowledgment of a ‘big data’ problem in today’s medical practice and science, and the role of computers; and (3) the societal demand for ‘P4 medicine’ (predictive, preventive, participatory, personalized), and its impact on the roles of doctors and patients.

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TAKEMURA, KAZUHISA. "Personal involvement, task complexity, and the decision making process." Japanese Psychological Research 36, no. 1 (1994): 41–48. http://dx.doi.org/10.4992/psycholres1954.36.41.

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Koerner, JoEllen. "Insight: The Application of Complexity Science to Decision Making." Creative Nursing 15, no. 4 (November 2009): 165–71. http://dx.doi.org/10.1891/1078-4535.15.4.165.

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Hughes, Katharine Kostbade, and Wendy B. Young. "The relationship between task complexity and decision-making consistency." Research in Nursing & Health 13, no. 3 (June 1990): 189–97. http://dx.doi.org/10.1002/nur.4770130308.

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MOYER, LAURA P. "The Role of Case Complexity in Judicial Decision Making." Law & Policy 34, no. 3 (February 15, 2012): 291–312. http://dx.doi.org/10.1111/j.1467-9930.2012.00362.x.

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So, Stella, and Malcolm Smith. "Colour graphics and task complexity in multivariate decision making." Accounting, Auditing & Accountability Journal 15, no. 4 (October 2002): 565–93. http://dx.doi.org/10.1108/09513570210440603.

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Juavinett, Ashley L., Jeffrey C. Erlich, and Anne K. Churchland. "Decision-making behaviors: weighing ethology, complexity, and sensorimotor compatibility." Current Opinion in Neurobiology 49 (April 2018): 42–50. http://dx.doi.org/10.1016/j.conb.2017.11.001.

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Lewis, Marsha L. "Decision-Making Task Complexity: Model Development and Initial Testing." Journal of Nursing Education 36, no. 3 (March 1997): 114–20. http://dx.doi.org/10.3928/0148-4834-19970301-06.

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Damnjanović, Kaja, Sandra Ilić, Irena Pavlović, and Vera Novković. "Refinement of outcome bias measurement in the parental decision-making context." Europe’s Journal of Psychology 15, no. 1 (February 28, 2019): 41–58. http://dx.doi.org/10.5964/ejop.v15i1.1698.

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The aim of this study was twofold: one was to test the impact of the involvement on the parental outcome bias, and the second was to refine the measurement of outcome bias, normally reported as the difference between evaluations of a single decision, with different outcomes assigned to it. We introduced the evaluation of a decision without an outcome, to induce theoretically normative evaluation, unbiased by outcome, from which the evaluation shift could be calculated in either direction. To test this refinement in the parental decision-making context, we produced childcare dilemmas with varying levels of complexity, since the rise of complexity induces stronger bias. Complexity was determined by the particular combination of two factors: parental involvement in a decision - the amount of motivation, interest and drive evoked by it – and whether the decision was health-related or not. We presented parents with the decisions for evaluation, followed by a positive and a negative outcome, and without an outcome. The results confirm the interaction between involvement and domain on decision evaluation. Highly involving decisions yielded weaker outcome bias than low-involvement decisions in both health and non-health domain. Results also confirm the validity of the proposed way of measuring OB, revealing that in some situations positive outcomes skew evaluations more than negative outcomes. Also, a highly-involving dilemma followed by negative outcome did not produce significantly different evaluation compared to evaluation of a decision without outcome. Thus, adding a neutral position rendered OB measurement more precise and our involvement-related insights more nuanced.

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Shi, Qianqian, Marcel Hertogh, Marian Bosch-Rekveldt, Jianbo Zhu, and Zhaohan Sheng. "Exploring Decision-Making Complexity in Major Infrastructure Projects: A Case Study From China." Project Management Journal 51, no. 6 (May 8, 2020): 617–32. http://dx.doi.org/10.1177/8756972820919205.

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The goal of this study is to identify, classify, explore, and understand decision-making complexity elements in major infrastructure projects (MIPs). This article puts forward systematic definitions of decision making, decision-making quality, and decision-making complexity. Based on literature reviews and an in-depth case analysis of Hong Kong-Zhuhai-Macao Bridge (HZMB), a comprehensive framework of decision-making complexity is developed, which divides the elements into six dimensions: technical, social, financial, legal, organizational, and time. The links between different dimensions are also illustrated. This article is expected to deepen our current understanding of decision-making complexity and to provide a fundamental point of reference in the front-end phase of MIPs.

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MCLAIN, DAVID L., and RAMON J. ALDAG. "COMPLEXITY AND FAMILIARITY WITH COMPUTER ASSISTANCE WHEN MAKING ILL-STRUCTURED BUSINESS DECISIONS." International Journal of Information Technology & Decision Making 08, no. 03 (September 2009): 407–26. http://dx.doi.org/10.1142/s0219622009003491.

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Using high-level tasks typical of managerial decisions, this experimental study examined the influence of computer assistance on solving ill-structured problems. Of specific interest were the influences of complex and simple assistance on decision performance and decision maker attitudes. Our findings suggest that performance and user attitudes can be enhanced by technology that provides clear and simple instruction in good problem-solving practices. However, when that technology adds a complex array of technical options and features, the assistance may fail to improve or/and may even diminish performance and damage user attitudes. Familiarization with such complex technology may not improve these outcomes. The findings regarding the relationship between assistance complexity and decision performance are consistent with those of studies that suggest complexity has a curvilinear influence on performance. When considering the application of technological assistance to ill-structured decision tasks, the complexity of the assistance should not be ignored.

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Vincent, Kristen, Robert E. Roth, Sarah A. Moore, Qunying Huang, Nick Lally, Carl M. Sack, Eric Nost, and Heather Rosenfeld. "Improving spatial decision making using interactive maps: An empirical study on interface complexity and decision complexity in the North American hazardous waste trade." Environment and Planning B: Urban Analytics and City Science 46, no. 9 (April 4, 2018): 1706–23. http://dx.doi.org/10.1177/2399808318764122.

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Spatial decisions increasingly are made by both professional and citizen stakeholders using interactive maps, yet few empirically-derived guidelines exist for designing interactive maps that support complex reasoning and decision making across problem contexts. We address this gap through an online map study with 122 participants with varying expertise. The study required participants to assume two hypothetical scenarios in the North American hazardous waste trade, review geographic information on environmental justice impacts using a different interactive map for each scenario, and arrive at an optimal decision outcome. This study followed a 2 × 2 factorial design, varying interface complexity (the number of supported interaction operators) and decision complexity (the number of decision criteria) as the independent variables and controlling for participant expertise with the hazardous waste trade and other aspects of cartographic design. Our findings indicate that interface complexity, not decision complexity, influenced decision outcomes, with participants arriving at better decisions using the simpler interface. However, expertise was a moderating effect, with experts and non-experts using different interaction strategies to arrive at their decisions. The research contributes to cartography, geovisualization, spatial decision science, urban planning, and visual analytics as well as to scholarship on environmental justice, the geography of hazardous waste, and participatory mapping.

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Owens, Edward H., and Gary A. Sergy. "THE SHORELINE RESPONSE DECISION-MAKING PROCESS." International Oil Spill Conference Proceedings 2008, no. 1 (May 1, 2008): 443–49. http://dx.doi.org/10.7901/2169-3358-2008-1-443.

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ABSTRACT The decision process that generates oil spill response objectives, strategies and tactics at regional and site-specific scales is a form of risk management. Typically this decision process involves an analysis of the probabilities and consequences of events and the selection of actions to achieve the defined objective(s). Coastal marine, lake and river oil spills frequently are the more difficult ones to manage due to the dynamics and complexity of the environment in terms of physical processes, ecosystem variability and sensitivity, and human use activities. The development of a systematic approach to decision-making is intended to address and reduce the complexity of these issues. This can be achieved by the identification of the elemental components of a response operation in terms of four phases: preplanning; reactive response; planned response; and the completion and monitoring response phase. The framework of the decision process within each of the three response phases is a logical and systematic sequence of nine integrated steps. This discussion explains the purpose and actions that are involved in each step and the manner in which the different components relate to each other.

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Bossaerts, Peter, Nitin Yadav, and Carsten Murawski. "Uncertainty and computational complexity." Philosophical Transactions of the Royal Society B: Biological Sciences 374, no. 1766 (December 31, 2018): 20180138. http://dx.doi.org/10.1098/rstb.2018.0138.

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Modern theories of decision-making typically model uncertainty about decision options using the tools of probability theory. This is exemplified by the Savage framework, the most popular framework in decision-making research. There, decision-makers are assumed to choose from among available decision options as if they maximized subjective expected utility, which is given by the utilities of outcomes in different states weighted with subjective beliefs about the occurrence of those states. Beliefs are captured by probabilities and new information is incorporated using Bayes’ Law. The primary concern of the Savage framework is to ensure that decision-makers’ choices are rational . Here, we use concepts from computational complexity theory to expose two major weaknesses of the framework. Firstly, we argue that in most situations, subjective utility maximization is computationally intractable, which means that the Savage axioms are implausible. We discuss empirical evidence supporting this claim. Secondly, we argue that there exist many decision situations in which the nature of uncertainty is such that (random) sampling in combination with Bayes’ Law is an ineffective strategy to reduce uncertainty. We discuss several implications of these weaknesses from both an empirical and a normative perspective. This article is part of the theme issue ‘Risk taking and impulsive behaviour: fundamental discoveries, theoretical perspectives and clinical implications’.

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