Relevant bibliographies by topics / Decisions

Academic literature on the topic 'Decisions'

Author: Grafiati
Published: 4 June 2021
Last updated: 29 July 2024

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Journal articles on the topic "Decisions"

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Owens, T. J. "Decision, Decisions, Decisions." Seismological Research Letters 76, no. 2 (March 1, 2005): 177. http://dx.doi.org/10.1785/gssrl.76.2.177-a.

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Natal, Gerald, and Barbara Saltzman. "Decisions, decisions, decisions: decision fatigue in academic librarianship." Journal of Academic Librarianship 48, no. 1 (January 2022): 102476. http://dx.doi.org/10.1016/j.acalib.2021.102476.

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Causer, Joe, and Paul R. Ford. "“Decisions, decisions, decisions”: transfer and specificity of decision-making skill between sports." Cognitive Processing 15, no. 3 (January 11, 2014): 385–89. http://dx.doi.org/10.1007/s10339-014-0598-0.

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Barksdale, Cheryl, and Anne D. Smith. "Decisions, Decisions . . . Resources and Tools for Complex Decision Making." Journal of Management Education 38, no. 6 (August 6, 2014): 894–98. http://dx.doi.org/10.1177/1052562914545226.

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Rigopoulos, Evangelos. "DECODING EDUCATIONAL DECISIONS: TRACING THE EVOLUTION OF DECISION-MAKING THEORIES." Global Multidisciplinary Journal 03, no. 03 (March 1, 2024): 01–06. http://dx.doi.org/10.55640/gmj-abc219.

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Decoding Educational Decisions: Tracing the Evolution of Decision-Making Theories explores the historical trajectory and development of decision-making theories within educational contexts. This paper provides a comprehensive examination of the key theories that have shaped decision-making processes in education over time, shedding light on their evolution, implications, and practical applications. Drawing upon a wide range of scholarly literature and historical perspectives, this study offers valuable insights into how decision-making frameworks have influenced educational practices and policies. By tracing the evolution of these theories, educators and policymakers can gain a deeper understanding of the factors influencing decision-making processes in education and make informed choices to enhance teaching, learning, and organizational effectiveness.
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Lawson, Stephanie J., Mark R. Gleim, and Michael D. Hartline. "Decisions, decisions: variations in decision-making for access-based consumption." Journal of Marketing Theory and Practice 29, no. 3 (January 10, 2021): 358–74. http://dx.doi.org/10.1080/10696679.2020.1855990.

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Smith, Claire, and Soomi Lee. "DECISIONS, DECISIONS: CHARACTERIZING WORKERS' DAILY DECISION PROCESSES DURING LEISURE TIME." Innovation in Aging 6, Supplement_1 (November 1, 2022): 14–15. http://dx.doi.org/10.1093/geroni/igac059.051.

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Abstract Decisions during adulthood set the foundation for healthy aging, but descriptions of healthy and unhealthy decision processes are missing. We extracted latent profiles of daily decision resources (energy and affect) and linked them to daily leisure activity. Diary data was collected from working adults (N=83; Mage=37 years) over the ten workdays (N=693). We identified three daily decision profiles consistent with the Decision Triangle – (1) logical (energetic, unemotional), (2) automatic (less energetic, unemotional), and (3) visceral (unenergetic, highly emotional) – and one additional profile, (4) mild visceral (moderately unenergetic, moderately emotional). Daily logical decision-making related to more “want” leisure activities (i.e., aligned with desires/interests) and the greatest variety in leisure activities. Automatic engaged in the most chores. Visceral engaged in the fewest social activities and least variety in leisure activities. Our findings advance understanding of specific decision processes during leisure, which may have consequences for health and well-being as a person ages.
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Bergeron, Caroline D., Daniela B. Friedman, S. Melinda Spencer, Susan C. Miller, DeAnne K. Hilfinger Messias, and Robert McKeever. "An Exploratory Survey of Older Women’s Post-Fall Decisions." Journal of Applied Gerontology 37, no. 9 (July 7, 2016): 1107–32. http://dx.doi.org/10.1177/0733464816653361.

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This research examined factors influencing older women’s post-fall decision making. We surveyed 130 independent older women from continuing care retirement communities and non-institutional homes. We categorized women’s post-fall decisions as medical, corrective, and social decisions, and examined the associations between post-fall decision categories, decisional conflict, number of post-fall changes, self-rated health, frequency of falls, severity of falls, health literacy, awareness and openness to long-term care institutional options, and demographics. Older women experienced greater decisional conflict when making medical decisions versus social ( p = .012) and corrective ( p = .047) decisions. Significant predictors of post-fall decisional conflict were awareness of institutional care options ( p = .001) and health literacy ( p = .001). Future educational interventions should address knowledge deficits and provide resources to enhance collaborative efforts to lower women’s post-fall decisional conflict and increase satisfaction in the decisions they make after a fall.
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Doak, Elaine. "Decisions, Decisions, Decisions." Journal of Electronic Resources Librarianship 14, no. 27 (May 29, 2002): 41–51. http://dx.doi.org/10.1300/j101v14n27_06.

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Stern, P. "Decisions, decisions, decisions..." Science 344, no. 6186 (May 22, 2014): i—868. http://dx.doi.org/10.1126/science.344.6186.868-i.

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Dissertations / Theses on the topic "Decisions"

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Tatlılıoğlu, Kasım. "DECISIONS AND DECISION MAKING STRATEGIES IN ADOLESCENTS." Thesis, Національний авіаційний університет, 2017. https://er.nau.edu.ua/handle/NAU/48998.

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Tatlılıoğlu, Kasım. "DECISIONS AND DECISION MAKING STRATEGIES IN ADOLESCENTS." Thesis, Національний авіаційний університет, 2017. http://er.nau.edu.ua/handle/NAU/30617.

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Vrba, Martin. "DECISIONS." Master's thesis, Vysoké učení technické v Brně. Fakulta výtvarných umění, 2017. http://www.nusl.cz/ntk/nusl-295732.

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Presented work tries to reflect the structure of human world, which is able to create an overman as an artificial intelligence through its self-destructive tendency. It investigates the possibilities of our imagination and if we are able to think about artificial intelligence as a sui generis continuation of human species. Hand in hand it tries to create a tension between particular ethico-political decisions and subsequent binding structure, which they implies.
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Snipes, Katherine Harwood. "Decisions, Decisions, Decisions: Recreation Site Choice with Expected Congestion and Social Interaction." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1242771608.

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Snipes, Katherine H. "Decisions, decisions, decisions recreation site choice with expected congestion and social interaction /." Columbus, Ohio : Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1242771608.

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Enoch, John. "Application of Decision Analytic Methods to Cloud Adoption Decisions." Thesis, Högskolan i Gävle, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-25560.

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This thesis gives an example of how decision analytic methods can be applied to choices in the adoption of cloud computing. The lifecycle of IT systems from planning to retirement is rapidly changing. Making a technology decision that can be justified and explained in terms of outcomes and benefits can be increasingly challenging without a systematic approach underlying the decision making process. It is proposed that better, more informed cloud adoption decisions would be taken if organisations used a structured approach to frame the problem to be solved and then applied trade-offs using an additive utility model. The trade-offs that can be made in the context of cloud adoption decisions are typically complex and rarely intuitively obvious. A structured approach is beneficial in that it enables decision makers to define and seek outcomes that deliver optimum benefits, aligned with their risk profile. The case study demonstrated that proven decision tools are helpful to decision makers faced with a complex cloud adoption decision but are likely to be more suited to the more intractable decision situations.
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Müller, Daniel [Verfasser]. "Decision support for liner shipping network decisions / Daniel Müller." Paderborn : Universitätsbibliothek, 2018. http://d-nb.info/1171897642/34.

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Platts, Danielle. "Patients' decision making processes for uncertain, risky medical decisions." Thesis, University of Sheffield, 2016. http://etheses.whiterose.ac.uk/17546/.

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O'REILLY, CAROLYN STOTZ. "SPECIAL EDUCATION PLACEMENT DECISIONS: A BEHAVIORAL DECISION THEORY PERSPECTIVE." Diss., The University of Arizona, 1986. http://hdl.handle.net/10150/183983.

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Despite the large number of special education eligibility determinations in which school psychologists are involved, and the great deal of integration and interpretation of information that these decisions require, few investigations of the cognitive strategies that school psychologists utilize in assessing placement candidates have been reported. The purpose of this study was to examine the susceptibility of school psychologists to placement decision bias. Specifically, the influence of referral information on school psychologists' subsequent evaluation and classification of a special education candidate was tested. Forty currently practicing school psychologists evaluated a bogus psychological report allegedly written about a child referred for either Gifted or Learning Disabilities (LD) placement consideration. Although all assessment data were identical, the school psychologists receiving a Gifted referral were more likely to classify the child as Gifted, and those receiving an LD referral were more likely to classify the child as LD. Additionally, the school psychologists recalled and weighted the importance of assessment data in a referral-consistent manner.
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Guerriere, Denise Noelle. "Measuring decisional conflict in substitute decision makers, mothers' decisions about initiating gastrostomy tube feeding in children." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape11/PQDD_0009/NQ41431.pdf.

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Books on the topic "Decisions"

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Bucciarelli, Edgardo, Shu-Heng Chen, and Juan Manuel Corchado, eds. Decision Economics: Complexity of Decisions and Decisions for Complexity. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38227-8.

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Schumacher, Julie. Decisions, decisions. Logan, Iowa: Perfection Learning Corp., 2000.

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Bowers, Barbara. Decisions, decisions. Agincourt, Ont: Dominie Press, 1985.

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Kelleher, Anne. Decisions decisions. London: Channel Four Television, 1993.

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Ranta, Ronald. Political Decision Making and Non-Decisions. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137447999.

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Brännback, Malin. Strategic decisions and decision support systems. Åbo: Åbo Akademis förlag, 1996.

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Gaynor, Gerard H. Decisions. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781119020264.

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Bright, Freda. Decisions. Thorndike, Me: Thorndike Press, 1988.

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William, Kate. Decisions. London: Bantam Bks., 1988.

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Bright, Freda. Decisions. Thorndike, Me., U.S.A: Thorndike-Magna, 1987.

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Book chapters on the topic "Decisions"

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Meloy, Judith M. "Decisions, Decisions, Decisions." In Twenty-first Century Learning by Doing, 53–99. Rotterdam: SensePublishers, 2012. http://dx.doi.org/10.1007/978-94-6209-098-9_3.

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Sproull, Bob. "Decisions, Decisions, Decisions." In The Problem-Solving, Problem-Prevention, and Decision-Making Guide, 193–202. New York : Taylor & Francis, [2018]: Productivity Press, 2018. http://dx.doi.org/10.4324/9781351116268-24.

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Tanner, Ken. "Decisions, Decisions, Decisions." In Common Sense, 81–90. Berkeley, CA: Apress, 2013. http://dx.doi.org/10.1007/978-1-4302-4153-9_6.

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Atanasiu, Radu. "Decisions, Decisions, Decisions." In Management for Professionals, 67–91. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73600-2_7.

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Bowman, Charles F. "Decisions, Decisions, Decisions …" In Confessions of an Enterprise Architect, 81–100. Boca Raton: Auerbach Publications, 2023. http://dx.doi.org/10.1201/9781003414285-4.

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Gosling, P. E. "Decisions, Decisions." In Mastering Computer Programming, 25–36. London: Macmillan Education UK, 1990. http://dx.doi.org/10.1007/978-1-349-11094-0_3.

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Cvitkovic, Emilio. "Decisions, Decisions." In Competition, 91–117. London: Palgrave Macmillan UK, 1993. http://dx.doi.org/10.1007/978-1-349-12857-0_5.

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Hicks, Michael J. "Decisions, decisions!" In Problem Solving in Business and Management, 26–33. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4899-7148-7_3.

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Friedman, Mark T., Kamille A. West, Peyman Bizargity, Kyle Annen, and Jeffrey S. Jhang. "Decisions, Decisions!" In Immunohematology and Transfusion Medicine, 161–66. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-90960-8_28.

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Talati, Jamsheer. "Decisions! Decisions!" In The Management of Lithiasis, 79–83. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-011-5396-6_9.

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Conference papers on the topic "Decisions"

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Liang, Jenny. "Decisions decisions plant vessels." In the 2007 conference. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1314161.1314208.

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"UNFADING DECISIONS - A Position Paper on Decision Reconstruction." In International Conference on Knowledge Engineering and Ontology Development. SciTePress - Science and and Technology Publications, 2010. http://dx.doi.org/10.5220/0003080503740377.

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Huang, Sieh-Chuen, Hsuan-Lei Shao, and Robert B. Leflar. "Applying decision tree analysis to family court decisions." In ICAIL '21: Eighteenth International Conference for Artificial Intelligence and Law. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3462757.3466076.

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Yin, Linzi, Xuemei Xu, Jiafeng Ding, Zhaohui Jiang, and Kehui Sun. "A three-way decisions model for decision tables." In 2017 29th Chinese Control And Decision Conference (CCDC). IEEE, 2017. http://dx.doi.org/10.1109/ccdc.2017.7978102.

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Berkhout, Matthijs, and Koen Smit. "Utilizing Algorithms for Decision Mining Discovery." In Digital Restructuring and Human (Re)action. University of Maribor Press, 2022. http://dx.doi.org/10.18690/um.fov.4.2022.21.

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Organizations are executing operational decisions in fast changing environments, which increases the necessity for managing these decisions adequately. Information systems store information about such decisions in decision- and event logs that could be used for analyzing decisions. This study aims to find relevant algorithms that could be used to mine decisions from such decision- and event logs, which is called decision mining. By conducting a literature review, together with interviews conducted with experts with a scientific background as well as participants with a commercial background, relevant classifier algorithms and requirements for mining decisions are identified and mapped to find algorithms that could be used for the discovery of decisions. Five of the twelve algorithms identified have a lot of potential to use for decision mining, with small adaptations, while six out of the twelve do have potential but the required adaptation would demand too many alterations to their core design. One of the twelve was not suitable for the discovery of decisions.
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Chen, Weiyan, Nan Lin, and Ying Zhou. "Trade Credit Term Decisions under Centralized Decisions." In Fifth International Conference on Transportation Engineering. Reston, VA: American Society of Civil Engineers, 2015. http://dx.doi.org/10.1061/9780784479384.238.

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Hildebrandt, Michael. "From decisions in time to temporal decisions." In the 13th Eurpoean conference. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1274892.1274925.

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Pandey, Vijitashwa, and Deborah Thurston. "Metric for Disassembly and Reuse Decisions: Formulation and Validation." In ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/detc2008-49878.

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Design for disassembly and reuse focuses on developing methods to minimize difficulty in disassembly for maintenance or reuse. These methods can gain substantially if the relationship between component attributes (material mix, ease of disassembly etc.) and their likelihood of reuse or disposal is understood. For products already in the marketplace, a feedback approach that evaluates willingness of manufacturers or customers (decision makers) to reuse a component can reveal how attributes of a component affect reuse decisions. This paper introduces some metrics and combines them with ones proposed in literature into a measure that captures the overall value of a decision made by the decision makers. The premise is that the decision makers would choose a decision that has the maximum value. Four decisions are considered regarding a component’s fate after recovery ranging from direct reuse to disposal. A method on the lines of discrete choice theory is utilized that uses maximum likelihood estimates to determine the parameters that define the value function. The maximum likelihood method can take inputs from actual decisions made by the decision makers to assess the value function. This function can be used to determine the likelihood that the component takes a certain path (one of the four decisions), taking as input its attributes, which can facilitate long range planning and also help determine ways reuse decisions can be influenced.
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Pandey, Vijitashwa, and Zissimos P. Mourelatos. "A New Method for Design Decisions Using Decision Topologies." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12360.

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This paper shows how reliability block diagrams can be used as a decision making tool. The premise behind the idea is that classical decision analysis while very powerful, does not provide tractability in assessing utility functions and their use in making decisions. Our recent work has shown that visual representation of systems using a reliability block diagram can be used to describe a decision situation. In decision making, we called these block diagrams decision topologies. We show that decision topologies can be used to make many engineering decisions and can replace decision analysis for most decisions. The paper proves that at the limit, using decision topologies is entirely consistent with decision analysis for both single attribute and multiattribute cases. The main advantages of the proposed method are that (1) it provides a visual representation of a decision situation, (2) it can easily model tradeoffs, (3) it allows binary attributes, (4) it can be used when limited information is available, and (5) it can be used in a low-fidelity sense to quickly make a decision. The paper details the theoretical basis of the proposed method and highlights its benefits. An example is used to demonstrate how decision topologies can be used in practice.
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Hsiao, Chuck, and Richard Malak. "Modeling Information Gathering Decisions in Systems Engineering Projects." In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-34854.

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Decisions in systems engineering projects commonly are made under significant amounts of uncertainty. This uncertainty can exist in many areas such as the performance of subsystems, interactions between subsystems, or project resource requirements such as budget or personnel. System engineers often can choose to gather information that reduces uncertainty, which allows for potentially better decisions, but at the cost of resources expended in acquiring the information. However, our understanding of how to analyze situations involving gathering information is limited, and thus heuristics, intuition, or deadlines are often used to judge the amount of information gathering needed in a decision. System engineers would benefit from a better understanding of how to determine the amount of information gathering needed to support a decision. This paper introduces Partially Observable Markov Decision Processes (POMDPs) as a formalism for modeling information-gathering decisions in systems engineering. A POMDP can model different states, alternatives, outcomes, and probabilities of outcomes to represent a decision maker’s beliefs about his situation. It also can represent sequential decisions in a compact format, avoiding the combinatorial explosion of decision trees and similar representations. The solution of a POMDP, in the form of value functions, prescribes the best course of action based on a decision maker’s beliefs about his situation. The value functions also determine if more information gathering is needed. Sophisticated computational solvers for POMDPs have been developed in recent years, allowing for a straightforward analysis of different alternatives, and determining the optimal course of action in a given situation. This paper demonstrates using a POMDP to model a systems engineering problem, and compares this approach with other approaches that account for information gathering in decision making.
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Reports on the topic "Decisions"

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Marr, John J. The Military Decision Making Process: Making Better Decisions Versus Making Decisions Better. Fort Belvoir, VA: Defense Technical Information Center, January 2001. http://dx.doi.org/10.21236/ada392009.

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Jung, Kooyul, Yong-Cheol Kim, and Rene Stulz. Investment Opportunities, Managerial Decisions, and the Security Issue Decision. Cambridge, MA: National Bureau of Economic Research, October 1994. http://dx.doi.org/10.3386/w4907.

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Boyce, Stephen G. Forestry Decisions. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station, 1985. http://dx.doi.org/10.2737/se-gtr-35.

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Klimack, William K., Christopher B. Bassham, Kenneth W. Bauer, and Jr. Application of Decision Analysis to Automatic Target Recognition Programmatic Decisions. Fort Belvoir, VA: Defense Technical Information Center, April 2002. http://dx.doi.org/10.21236/ada401738.

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Hardie, T. Alternative Decision Making Processes for Consensus-Blocked Decisions in the IETF. RFC Editor, October 2004. http://dx.doi.org/10.17487/rfc3929.

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Givens, Corey A. Strategic and Operational Decision-Making: Does Military Weakness Affect Decisions Made? Fort Belvoir, VA: Defense Technical Information Center, May 2011. http://dx.doi.org/10.21236/ada545824.

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Barberá, Salvador. Designing Decisions Rules for Transnational Infrastructure Projects. Inter-American Development Bank, May 2003. http://dx.doi.org/10.18235/0011226.

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This article discusses the implications of decision rules in the governance structures of transnational infrastructure projects. It stresses that decision rules strongly affect the performance of the partnership and that, consequently, attention should be given to their design at the initial stage. The article also stresses the fact that partners must not only agree on how to make ordinary decisions, but also special ones such as, for example, changing the rules along the way or making changes to the membership of the group. This paper makes the following specific points. First, the choice of partners is a key variable, which affects the choice of decision rules and, in turn, is influenced by the conditions for new entrants. Second, the choice of decision rules can crucially affect the degree of confidence and the level of cooperation among partners, as well as the speed at which the partnership adopts new decisions. Third, agreements on how to eventually change the initial set of rules and partners should be part of the design of a well established decision system.
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Marguet, Natalie. Detect, reflect and adapt: factors influencing critical project decisions. Association for Project Management, April 2021. http://dx.doi.org/10.61175/vinp8647.

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This report takes the first step in building a clear picture of the ways that critical project decisions are made in practice. The intention is to suggest ways to enhance practitioner understanding of how decision-making effectiveness can be improved through simple techniques that can be embedded into daily practices. The study asks: what are the factors that influence decision-making in practice and how can project professionals ensure that critical project decisions are as effective as they can be. The research results from several data collection methods that sought to understand how decisions are made in practice from the perspective of project professionals these include: a survey of 430 responses that captured decision-making styles and perceptions of UK project professionals, 30 semi-structured interviews to further understand the experiences of project professionals and three simulation workshops to validate the previous findings and provide in-depth practical insights.
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Dewulf, Art R. P. J. Taking meaningful decisions : sensemaking and decision-making in water and climate governance. Wageningen: Wageningen University & Research, 2016. http://dx.doi.org/10.18174/471091.

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Field, Richard, and Michael Darling. A Decision Theoretic Approach To Optimizing Machine Learning Decisions with Prediction Uncertainty. Office of Scientific and Technical Information (OSTI), November 2022. http://dx.doi.org/10.2172/1899419.

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