Relevant bibliographies by topics / Management science

Academic literature on the topic 'Management science'

Author: Grafiati
Published: 4 June 2021
Last updated: 30 July 2024

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Journal articles on the topic "Management science"

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Sułkowski, Łukasz. "Management – Forecasting the Future Cognitive Challenges in Management Science 3." Przedsiebiorczosc i Zarzadzanie 16, no. 1 (March 1, 2015): 173–80. http://dx.doi.org/10.1515/eam-2015-0011.

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AbstractThis paper is the third publication from the series of three articles about cognitive challenges in management science. It is the result of the further discussions and reflections concerning the cognitive problems of management after publication of the books about epistemology of management. The paper is a trial to forecast the main cognitive trends and tendencies on the basis of the diagnosis made in two papers in series “Cognitive challenges in management science”. The chosen trends in development of management sciences are: expansion of natural sciences, growing inter-disciplinarity of research, growing specialization, net-marketing in management discourse, challenge of cultural relativism, growing criticism and reflexivity. Response of management sciences to the challenges connected to: interdisciplinary nature, growing specialization, and expansion of natural history can lead to further development of our discipline, but the possibility of disintegration also should not be ruled out. Deepening specialization, lack of long-range theory, and growing significance of natural history could lead to disintegration of our discipline, whose fields would be incorporated by other domains. I think that in order to avoid this possibility it would be desirable to uphold the cohesion of management sciences through deepening the cognitive reflection and openness to inspirations originating in other areas of science. But future is difficult to predict and maybe other trends that are not too visible now will change management sciences in future.
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Moore, Philip, John Hallett, and Andrew W. Shogan. "Management Science." Journal of the Operational Research Society 40, no. 3 (March 1989): 304. http://dx.doi.org/10.2307/2583345.

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Wilkinson, M. D. "Management science." British Dental Journal 166, no. 8 (April 1989): 299–302. http://dx.doi.org/10.1038/sj.bdj.4806810.

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Moore, Philip, and John Hallett. "Management Science." Journal of the Operational Research Society 40, no. 3 (March 1989): 304–5. http://dx.doi.org/10.1057/jors.1989.42.

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Fildes, Robert. "Management science." International Journal of Forecasting 4, no. 3 (January 1988): 510–11. http://dx.doi.org/10.1016/0169-2070(88)90122-7.

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Collopy, Fred, and J. Scott Armstrong. "Management science." International Journal of Forecasting 8, no. 2 (October 1992): 277–79. http://dx.doi.org/10.1016/0169-2070(92)90128-v.

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Fildes, Robert. "Management science." International Journal of Forecasting 9, no. 4 (December 1993): 585–86. http://dx.doi.org/10.1016/0169-2070(93)90087-4.

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Gregory, G. "Management science." European Journal of Operational Research 25, no. 2 (May 1986): 301–2. http://dx.doi.org/10.1016/0377-2217(86)90094-9.

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Kersten, H. M. P. "Micro management science: Microcomputer Applications of management science." European Journal of Operational Research 28, no. 1 (January 1987): 108–9. http://dx.doi.org/10.1016/0377-2217(87)90178-0.

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Charnes, A., W. W. Cooper, D. B. Learner, and F. Y. Phillips. "Management Science and Marketing Management." Journal of Marketing 49, no. 2 (1985): 93. http://dx.doi.org/10.2307/1251568.

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Dissertations / Theses on the topic "Management science"

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Chada, Daniel de Magalhães. "From cognitive science to management science: two computational contributions." reponame:Repositório Institucional do FGV, 2011. http://hdl.handle.net/10438/17053.

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This work is composed of two contributions. One borrows from the work of Charles Kemp and Joshua Tenenbaum, concerning the discovery of structural form: their model is used to study the Business Week Rankings of U.S. Business Schools, and to investigate how other structural forms (structured visualizations) of the same information used to generate the rankings can bring insights into the space of business schools in the U.S., and into rankings in general. The other essay is purely theoretical in nature. It is a study to develop a model of human memory that does not exceed our (human) psychological short-term memory limitations. This study is based on Pentti Kanerva’s Sparse Distributed Memory, in which human memories are registered into a vast (but virtual) memory space, and this registration occurs in massively parallel and distributed fashion, in ideal neurons.
Este trabalho é composto de duas contribuições. Uma se usa do trabalhode Charles Kemp e Joshua Tenenbaum sobre a descoberta da forma estrutural: o seu modelo é usado para estudar os rankings da revista Business Week sobre escolas de administração, e para investigar como outras formas estruturais (visualizações estruturadas) da mesma informação usada para gerar os rankings pode trazer discernimento no espaço de escolas de negócios nos Estados Unidos e em rankings em geral. O outro ensaio é de natureza puramente teórica. Ele é um estudo no desenvolvimento de um modelo de memória que não excede os nossos (humanos) limites de memória de curto-prazo. Este estudo se baseia na Sparse Distributed Memory (Memória Esparsa e Distribuida) de Pentti Kanerva, na qual memórias humanas são registradas em um vasto (mas virtual) espaço, e este registro ocorre de forma maciçamente paralela e distribuida, em neurons ideais.
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Yan, Kwan-shing, and 甄君成. "Management science: quenes in cinemas." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1996. http://hub.hku.hk/bib/B31267798.

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Yan, Kwan-shing. "Management science : quenes in cinemas /." Hong Kong : University of Hong Kong, 1996. http://sunzi.lib.hku.hk/hkuto/record.jsp?B18024646.

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Brogliato, Marcelo Salhab. "Essays in computational management science." reponame:Repositório Institucional do FGV, 2018. http://hdl.handle.net/10438/24615.

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A presente tese é formada por três trabalhos científicos na área de Management Science Computacional. A gestão moderna e a alta tecnologia interagem em múltiplas e profundas formas. O professor Andre Ng diz aos seus estudantes na Escola de Negócios de Stanford que “Inteligência Artificial é a nova eletricidade”, como sua forma hiperbólica de enfatizar o potencial transformador da tecnologia. O primeiro trabalho é inspirado na possibilidade de que haverá alguma forma de dinheiro digital e estuda ledger distribuídas, propondo e analisando o Hathor, uma arquitetura alternativa para criptomoedas escaláveis. O segundo trabalho pode ser um item crucial no entendimento de tomadas de decisão, nos trazendo um modelo formal de recognition-primed decisions. Situada na intersecção entre psicologia cognitiva, ciência da computação, neuro-ciência e inteligência artifical, ele apresenta um framework open-source, multi-plataforma e altamente paralelo da Sparse Distributed Memory e analisa a dinâmica da memória e algumas aplicações. O terceiro e último trabalho se situa na intersecção entre marketing, difusão de inovação tecnologica e modelagem, extendendo o famoso modelo de Bass para levar em consideração usuário que, após adotar a tecnologia por um tempo, decidiram rejeitá-la.
This thesis presents three specific, self-contained, scientific papers in the Computational Management Science area. Modern management and high technology interact in multiple, profound, ways. Professor Andrew Ng tells students at Stanford’s Graduate School of Business that “AI is the new electricity”, as his hyperbolic way to emphasize the potential transformational power of the technology. The first paper is inspired by the possibility that there will be some form of purely digital money and studies distributed ledgers, proposing and analyzing Hathor, an alternative architecture towards a scalable cryptocurrency. The second paper may be a crucial item in understanding human decision making, perhaps, bringing us a formal model of recognition-primed decision. Lying at the intersection of cognitive psychology, computer science, neuroscience, and artificial intelligence, it presents an open-source, cross-platform, and highly parallel framework of the Sparse Distributed Memory and analyzes the dynamics of the memory with some applications. Last but not least, the third paper lies at the intersection of marketing, diffusion of technological innovation, and modeling, extending the famous Bass model to account for users who, after adopting the innovation for a while, decide to reject it later on.
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Huang, Jianyuan. "Computer science graduate project management system." CSUSB ScholarWorks, 2007. https://scholarworks.lib.csusb.edu/etd-project/3250.

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This project is a development and tracking system for graduate students in the Department of Computer Science of CSUSB. This project will cover front-end web site development, back-end database design and security. This website provides secure access to information about ideas for projects, status on on-going projects, and reports of finished projects using My SQL and Apache Tomcat.
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Medema, Wietske. "Integrated water resources management and adaptive management : shaping science and practice." Thesis, Cranfield University, 2008. http://dspace.lib.cranfield.ac.uk/handle/1826/3531.

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Complexity of challenges associated with water resources management is increasing due to factors such as climate variability and uncertainty, increased regulatory requirements, changes in planning horizons, and trans-boundary considerations. Integrated Water Resources Management (IWRM) and Adaptive Management (AM) are widely publicized approaches developed and proposed to deal with this complexity. Both concepts have a history reaching back decades, but have been facing difficulties in their transfer from theory into practice. There is a clear need to look in more detail at the process of transforming IWRM and AM theory into practice and this research investigates this process and the factors that mediate it. A conceptual framework was developed - characterizing the process for transfer of theory into practice - that formed the basis for development of the research questions. The research approach focused on analyzing the implementation pathways of IWRM and AM in four case studies, whose selection was informed by the need to explore a context with extensive history of IWRM and AM practice. Data collection took place through semi-structured interviews aiming to uncover how those involved in planning and implementation of IWRM and AM experienced these processes. Besides aiming to understand the ‘lived experiences’, a more abstract framework of the process, factors and dynamics was derived, grounded in the views of the respondents. The findings indicate different types of factors that influence the theory to practice process for IWRM and AM, relating to: (a) theory and its use in practice; (b) the environment that can complicate or facilitate the implementation process; (c) the way cooperation and decision-making processes are organized; and (d) individual attributes of those involved. Incorporating lessons from past into current initiatives are vital to more effective implementation of IWRM and AM. This research gives greater insight into the mediating factors and dynamics, providing this through empirical evidence into design of IWRM and AM planning and implementation. It also provides a thorough discussion on what IWRM and AM exactly mean, proposing a new definition for both concepts.
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Shearn, Peter Anthony. "Making science visible : new forms of science and technology management and evaluation." Thesis, University of Manchester, 2002. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.500670.

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Wason, Jasmin Lesley. "Automating data management in science and engineering." Thesis, University of Southampton, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.396143.

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Morgan, Edward. "Science & Sustainability: The Use of Science and the Science–Policy Interface in Sustainable Water Resource Management." Thesis, Griffith University, 2015. http://hdl.handle.net/10072/367995.

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This thesis explores the use of scientific knowledge in policy-making. It is widely recognised that use of natural resources, such as water, is unsustainable across much of the world. In response, there is a desire for and expectation that science should be used to help improve natural resource management and contribute to the pursuit of sustainability. This research is centred on a comparative case study analysis of the use of science in water resource management policies for Southeast Queensland, Australia. A framework model of the interface between science and policy is developed and applied to the case studies and a range of different uses for science in policy-making are synthesised in the analysis. The relationship between these uses and the need for boundary work to make the science effective is analysed. The findings explore the key factors that influence how science can be used to create effective, efficient and appropriate policies. The research revealed that science can be used in a number of different ways, from simply providing knowledge through to being used in a co-learning process to create a shared understanding. The results show that co-learning is likely to be the most effective use of science, especially when the science is uncertain, but this use requires strong social capital and collaborative governance arrangements. More direct knowledge provision is simpler to implement, but is likely to require shared values and more certain science. In controversial policy issues, where there are conflicting values, science is likely to be used in advocacy and this limits its ability to directly influence outcomes. Hence, the use of science is strongly influenced by the policy context and governance arrangements, but generally strong social capital is likely to support the most effective use of science. This adds further support to calls for stronger social capital and more collaborative governance in sustainability and natural resource management policy.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
Griffith School of Environment
Science, Environment, Engineering and Technology
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Bates, Anthony Shawn. "The Trilogy of Science: Filling the Knowledge Management Gap with Knowledge Science and Theory." ScholarWorks, 2017. https://scholarworks.waldenu.edu/dissertations/3977.

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The international knowledge management field has different ways of investigating, developing, believing, and studying knowledge management. Knowledge management (KM) is distinguished deductively by know-how, and its intangible nature establishes different approaches to KM concepts, practices, and developments. Exploratory research and theoretical principles have formed functional intelligences from 1896 to 2013, leading to a knowledge management knowledge science (KMKS) concept that derived a grounded theory of knowledge activity (KAT). This study addressed the impact of knowledge production problems on KM practice. The purpose of this qualitative meta-analysis study was to fit KM practice within the framework of knowledge science (KS) study. Themed questions and research variables focused on field mechanisms, operative functions, principle theory, and relationships of KMKS. The action research used by American practitioners has not established a formal structure for KS. The meta-data-analysis examined 385 transdisciplinary peer-reviewed articles using social science, service science, and systems science databases, with a selection of interdisciplinary studies that had a practice-research-theory framework. Key attributes utilizing Boolean limiters, words, phrases and publication dates, along with triangulation, language analysis and coding through analytic software identified commonalities of the data under study. Findings reflect that KM has not become a theoretically saturated field. KS as the forensic science of KM creates a paradigm shift, causes social change that averts rapid shifts in management direction and uncertainty, and connects KM philosophy and science of knowledge. These findings have social change implications by informing the work of managers and academics to generate a methodical applied science.
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Books on the topic "Management science"

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Shogan, Andrew. Management Science. New Jersey: Prentice-Hall, 1988.

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Daellenbach, Hans G., and Donald C. McNickle. Management Science. London: Macmillan Education UK, 2005. http://dx.doi.org/10.1007/978-0-230-80203-2.

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Daellenbach, Hans, Donald McNickle, and Shane Dye. Management Science. London: Macmillan Education UK, 2012. http://dx.doi.org/10.1007/978-1-137-07512-3.

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Machado, Carolina, and J. Paulo Davim, eds. Management Science. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-13229-3.

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Mathur, Kamlesh. Management science. London: Prentice-Hall International, 1994.

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W, Shannon Patrick, ed. Management science. San Francisco, Calif: Dellen Pub. Co., 1992.

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B, Dennis Laurie, ed. Management science. St. Paul: West Pub. Co., 1991.

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Moore, Laurence J. Management science. 4th ed. Boston: Allyn and Bacon, 1993.

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Dennis, Terry L. Management science. St. Paul, Minn: West Publishing Company, 1991.

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Lee, Sang M. Management science. 2nd ed. Boston: Allyn and Bacon, 1985.

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Book chapters on the topic "Management science"

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Harris, John. "Management Science." In An Introduction to Fuzzy Logic Applications, 170–97. Dordrecht: Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-010-9042-1_7.

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Marcus, Frederick B. "Science Management." In Bioinformatics and Systems Biology, 215–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-78353-4_10.

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Sulkowski, Lukasz. "Science management." In Managing the Digital University, 145–54. New York: Routledge, 2023. http://dx.doi.org/10.4324/9781003366409-14.

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Jupiter, Stacy, Chris M. Roelfsema, and Stuart R. Phinn. "Science and Management." In Coral Reef Remote Sensing, 403–27. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-90-481-9292-2_15.

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Salonen, Arto O., and Jani Siirilä. "Sustainability Science." In Encyclopedia of Sustainable Management, 1–5. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-02006-4_70-1.

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Salonen, Arto O., and Jani Siirilä. "Sustainability Science." In Encyclopedia of Sustainable Management, 3382–86. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-25984-5_70.

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Salonen, Arto O., and Jani Siirilä. "Sustainability Science." In Encyclopedia of Sustainable Management, 1–5. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-02006-4_70-1.

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Barrow, Chris. "Environmental management and science." In Environmental Management, 27–49. 3rd ed. London: Routledge, 2024. http://dx.doi.org/10.4324/9781003189985-4.

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Maximini, Dominik. "Starting With Science." In Management for Professionals, 181–85. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73842-0_17.

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Boutellier, Roman, and Mareike Heinzen. "Science-Driven Industry." In Management for Professionals, 107–20. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-04016-5_9.

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Conference papers on the topic "Management science"

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MACHLIS, GARY E. "SCIENCE DURING CRISIS: THE ROLE OF SCIENCE IN DISASTER RESPONSE." In DISASTER MANAGEMENT 2019. Southampton UK: WIT Press, 2019. http://dx.doi.org/10.2495/dman190091.

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Zhao, Rongying, Limin Xu, and Yuehua Zhao. "From the Knowledge Management to Knowledge Management Science." In 2010 International Conference on Management and Service Science (MASS 2010). IEEE, 2010. http://dx.doi.org/10.1109/icmss.2010.5576954.

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Venturi, Valerio, Federico Stagni, Alberto Gianoli, Andrea Ceccanti, and Vincenzo Ciaschini. "Virtual Organization Management Across Middleware Boundaries." In Third IEEE International Conference on e-Science and Grid Computing (e-Science 2007). IEEE, 2007. http://dx.doi.org/10.1109/e-science.2007.84.

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Parashar, Manish. "Data-Management for Extreme Science." In HPDC '22: The 31st International Symposium on High-Performance Parallel and Distributed Computing. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3502181.3537771.

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Djemame, Karim, Iain Gourlay, James Padgett, Georg Birkenheuer, Matthias Hovestadt, Odej Kao, and Kerstin Voss. "Introducing Risk Management into the Grid." In 2006 Second IEEE International Conference on e-Science and Grid Computing (e-Science'06). IEEE, 2006. http://dx.doi.org/10.1109/e-science.2006.261112.

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Hui-Fen Li, Jian-Jun Wang, Hong-Lei Yu, and De-Li Yang. "Services science, management, and engineering: A literature review in the perspective of management science." In 2007 IEEE International Conference on Industrial Engineering and Engineering Management. IEEE, 2007. http://dx.doi.org/10.1109/ieem.2007.4419430.

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Sulistio, Anthony, Kyong Hoon Kim, and Rajkumar Buyya. "Using Revenue Management to Determine Pricing of Reservations." In Third IEEE International Conference on e-Science and Grid Computing (e-Science 2007). IEEE, 2007. http://dx.doi.org/10.1109/e-science.2007.83.

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YOTSOV, ELEONORE (NORA) D., and DOUGLAS C. STOLZ. "INCORPORATING CLIMATE SCIENCE INTO DISASTER MANAGEMENT PROGRAMS." In DISASTER MANAGEMENT 2019. Southampton UK: WIT Press, 2019. http://dx.doi.org/10.2495/dman190101.

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Goldman, Charles R., John E. Reuter, Alan D. Jassby, M. Levant Kavvas, Alan C. Heyvaert, Geoffrey Schladow, and Theodore J. Swift. "Science-Based Decision Making in the Lake Tahoe Watershed." In Watershed Management and Operations Management Conferences 2000. Reston, VA: American Society of Civil Engineers, 2001. http://dx.doi.org/10.1061/40499(2000)121.

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Kucinskiene, Jurga, Egle Brezgyte, Gintaras Kucinskas, and Marina Weck. "The Role of Open Science in Open Innovation Environment:The Case of Knowledge Management Model." In 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1003883.

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This article aims to contribute to a better understanding of the role of open science and its impact on knowledge management in the open innovation environment. The main premise of open innovation in the Europe Commission’s vision for Europe is to open the innovation process to all stakeholders from academia, business, government, and society. Owing to that, knowledge may create investment opportunities for innovative products and services as well as competitiveness in new markets. Open science is a relatively new approach to the scientific process, which is based on collaboration and advanced ways of spreading knowledge by using digital technologies and new tools. Open Science affects the entire process expanding its boundaries and permitting knowledge to be widely and quickly shared as well as easily updated. The idea is to make a profound change in science and research - moving from the traditional and well-established practice of disseminating research results in academic journals, seminars, and conferences to open sharing of the acquired knowledge and bringing it closer to the earlier stages of the innovation process. Open Science also involves a shift towards more open knowledge management in the open innovation environment. To ensure that knowledge management should be based on the principles of open science. This requires considerations of such critical factors as relevance, authenticity, and security of data sources while using the readily available results of open science. This article analyses the proposed open knowledge management framework reflecting on the impact of open sciences principles.
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Reports on the topic "Management science"

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Mount, Richard P. The Office of Science Data-Management Challenge. Office of Scientific and Technical Information (OSTI), October 2005. http://dx.doi.org/10.2172/878079.

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Arnold, William A., and Edward L. Cussler. Environmental Management Science Program (EMSP) Annual Report. Office of Scientific and Technical Information (OSTI), June 2003. http://dx.doi.org/10.2172/835480.

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Carrigan, C. R. Environmental management science program FY1997 progress report. Office of Scientific and Technical Information (OSTI), January 1998. http://dx.doi.org/10.2172/2872.

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Brodie-Brown, H., T. Svensson, and I. Macdonald. The science behind Ontario's water quantity management review. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2018. http://dx.doi.org/10.4095/306487.

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Kostoff, Ronald N. Science and Technology Text Mining: Management Decision Aids. Fort Belvoir, VA: Defense Technical Information Center, July 2003. http://dx.doi.org/10.21236/ada415501.

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Maltzahn, Carlos. Science-Driven Data Management for Multi-Tiered Storage. Office of Scientific and Technical Information (OSTI), January 2020. http://dx.doi.org/10.2172/1594174.

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Cordell, H. Ken, and Linda Caldwell. Integrating Social Science and Ecosystem Management: A National Challenge. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station, 1995. http://dx.doi.org/10.2737/srs-gtr-17.

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Parashar, Manish. SIRIUS: Science-Driven Data Management for Multi-Tiered Storage. Office of Scientific and Technical Information (OSTI), November 2018. http://dx.doi.org/10.2172/1736017.

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Zavarin, M. Area V: Waste Management and Subsurface Science Q3 Report. Office of Scientific and Technical Information (OSTI), July 2023. http://dx.doi.org/10.2172/1989082.

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Bussod, Gilles, Philip Stauffer, Hakim Boukhalfa, Suzanne Bourret, Nathan Hayes-Rich, Cody Cockreham, Ravid Rosenzweig, et al. FY21 FINAL REPORT, NNSA-IAEC SCIENCE AREA V, ENVIRONMENTAL ISR, WASTE MANAGEMENT AND SUBSURFACE SCIENCE. Office of Scientific and Technical Information (OSTI), November 2021. http://dx.doi.org/10.2172/1830566.

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