Download or read book An Analysis of the Integration of Decision Making Modeling with Statistical Quantitative Background for Master s Level Analytical Courses written by Murat Ozdemir and published by . This book was released on 2000-06-01 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this thesis is to integrate statistical/quantitative background material with Master's level analytical courses. This thesis first identifies the requirements for management education in terms of AACSB and NASPAA standards. Then, based on a comparative analysis of the country's top master's of business administration (MBA) programs and Naval Postgraduate School's current Systems Management curricula, and a survey conducted among SM faculty members, it integrates the decision-making modeling with statistical/ quantitative background material for master's level analytical courses. The structure of the MS in Management at NPS, while satisfying the requirements of both AACSB and NASPAA is similar to the top management schools' MBA programs in the United States. However, top management schools' statistical/quantitative course sequence generally has four courses, providing more statistic al/ quantitative background material than those three of NPS. Additionally, the contents of these three courses are not offered in adequate depth and some topics are duplicated. The new sequence and the contents of these courses are proposed based on a survey conducted among SM faculty members.
Download or read book Mathematics of Decision Making written by and published by Springer. This book was released on 2005-11-30 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In 2005, GERAD celebrates its 25th anniversary with these ten volumes covering most of the Center's research areas of expertise: Essays and Surveys in Global Optimization, edited by C. Audet, P. Hansen and G. Savard; Graph Theory and Combinatorial Optimization, edited by D. Avis, A. Hertz and O. Marcotte; Numerical Methods in Finance, edited by H. Ben-Ameur and M. Breton; Analysis, Control and Optimization of Complex Dynamic Systems, edited by E.K. Boukas and R. Malhamé; Column Generation, edited by G. Desaulniers, J. Desrosiers and M.M. Solomon; Statistical Modeling and Analysis for Complex Data Problems, edited by P. Duchesne and B. Rémillard; Performance Evaluation and Planning Methods for the Next Generation Internet, edited by A. Girard, B. Sansò, and F. Vásquez-Abad; Dynamic Games: Theory and Applications, edited by A. Haurie and G. Zaccour; Logistics Systems: Design and Optimization, edited by A. Langevin and D. Riopel; Energy and Environment, edited by R. Loulou, J.-P. Waaub and G. Zaccour.
Download or read book Modeling for Insight written by Stephen G. Powell and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for Modeling for Insight "Most books on modeling are either too theoretical or too focused on the mechanics of programming. Powell and Batt's emphasis on using simple spreadsheet models to gain business insight (which is, after all, the name of the game) is what makes this book stand head and shoulders above the rest. This clear and practical book deserves a place on the shelf of every business analyst." —Jonathan Koomey, PhD, Lawrence Berkeley National Laboratory and Stanford University, author of Turning Numbers into Knowledge: Mastering the Art of Problem Solving Most business analysts are familiar with using spreadsheets to organize data and build routine models. However, analysts often struggle when faced with examining new and ill-structured problems. Modeling for Insight is a one-of-a-kind guide to building effective spreadsheet models and using them to generate insights. With its hands-on approach, this book provides readers with an effective modeling process and specific modeling tools to become a master modeler. The authors provide a structured approach to problem-solving using four main steps: frame the problem, diagram the problem, build a model, and generate insights. Extensive examples, graduated in difficulty, help readers to internalize this modeling process, while also demonstrating the application of important modeling tools, including: Influence diagrams Spreadsheet engineering Parameterization Sensitivity analysis Strategy analysis Iterative modeling The real-world examples found in the book are drawn from a wide range of fields such as financial planning, insurance, pharmaceuticals, advertising, and manufacturing. Each chapter concludes with a discussion on how to use the insights drawn from these models to create an effective business presentation. Microsoft Office Excel and PowerPoint are used throughout the book, along with the add-ins Premium Solver, Crystal Ball, and Sensitivity Toolkit. Detailed appendices guide readers through the use of these software packages, and the spreadsheet models discussed in the book are available to download via the book's related Web site. Modeling for Insight is an ideal book for courses in engineering, operations research, and management science at the upper-undergraduate and graduate levels. It is also a valuable resource for consultants and business analysts who often use spreadsheets to better understand complex problems.
Download or read book Analytical Methods for Dynamics Modelers written by Hazhir Rahmandad and published by . This book was released on 2015 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Model Based Decision Support Methodology with Environmental Applications written by Andrzej P. Wierzbicki and published by Springer. This book was released on 2010-12-15 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The complexity of issues requiring rational decision making grows and thus such decisions are becoming more and more difficult, despite advances in methodology and tools for decision support and in other areas of research. Globalization, interlinks between environmental, industrial, social and political issues, and rapid speed of change all contribute to the increase of this complexity. Specialized knowledge about decision-making processes and their support is increasing, but a large spectrum of approaches presented in the literature is typically illustrated only by simple examples. Moreover, the integration of model-based decision support methodologies and tools with specialized model-based knowledge developed for handling real problems in environmental, engineering, industrial, economical, social and political activities is often not satisfactory. Therefore, there is a need to present the state of art of methodology and tools for development of model-based decision support systems, and illustrate this state by applications to various complex real-world decision problems. The monograph reports many years of experience of many researchers, who have not only contributed to the developments in operations research but also succeeded to integrate knowledge and craft of various disciplines into several modern decision support systems which have been applied to actual complex decision-making processes in various fields of policy making. The experience presented in this book will be of value to researchers and practitioners in various fields. The issues discussed in this book gain in importance with the development of the new era of the information society, where information, knowledge, and ways of processing them become a decisive part of human activities. The examples presented in this book illustrate how how various methods and tools of model-based decision support can actually be used for helping modern decision makers that face complex problems. Overview of the contents: The first part of this three-part book presents the methodological background and characteristics of modern decision-making environment, and the value of model-based decision support thus addressing current challenges of decision support. It also provides the methodology of building and analyzing mathematical models that represent underlying physical and economic processes, and that are useful for modern decision makers at various stages of decision making. These methods support not only the analysis of Pareto-efficient solutions that correspond best to decision maker preferences but also allow the use of other modeling concepts like soft constraints, soft simulation, or inverse simulation. The second part describes various types of tools that are used for the development of decision support systems. These include tools for modeling, simulation, optimization, tools supporting choice and user interfaces. The described tools are both standard, commercially available, and nonstandard, public domain or shareware software, which are robust enough to be used also for complex applications. All four environmental applications (regional water quality management, land use planning, cost-effective policies aimed at improving the European air quality, energy planning with environmental implications) presented in the third part of the book rely on many years of cooperation between the authors of the book with several IIASA's projects, and with many researchers from the wide IIASA network of collaborating institutions. All these applications are characterized by an intensive use of model-based decision support. Finally, the appendix contains a short description of some of the tools described in the book that are available from IIASA, free of charge, for research and educational purposes. The experiences reported in this book indicate that the development of DSSs for strategic environmental decision making should be a joint effort involving experts in the subject area, modelers, and decision support experts. For the other experiences discussed in this book, the authors stress the importance of good data bases, and good libraries of tools. One of the most important requirements is a modular structure of a DSS that enhances the reusability of system modules. In such modular structures, user interfaces play an important role. The book shows how modern achievements in mathematical programming and computer sciences may be exploited for supporting decision making, especially about strategic environmental problems. It presents the methodological background of various methods for model-based decision support and reviews methods and tools for model development and analysis. The methods and tools are amply illustrated with extensive applications. Audience: This book will be of interest to researchers and practitioners in the fields of model development and analysis, model-based decision analysis and support, (particularly in the environment, economics, agriculture, engineering, and negotiations areas) and mathematical programming. For understanding of some parts of the text a background in mathematics and operational research is required but several chapters of the book will be of value also for readers without such a background. The monograph is also suitable for use as a text book for courses on advanced (Master and Ph.D.) levels for programs on Operations Research, decision analysis, decision support and various environmental studies (depending on the program different parts of the book may be emphasized).
Download or read book Operational Leadership Using Quantitative Decision Making written by Deandra Cassone and published by Springer Nature. This book was released on with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Decision Modeling and Behavior in Complex and Uncertain Environments written by Tamar Kugler and published by Springer Science & Business Media. This book was released on 2008-07-20 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text examines new research at the interface of operations research, behavioral and cognitive sciences, and decision analysis. From the cognitive behaviorist who collects empirical evidence as to how people make decisions to the engineer and economist who are the consumers of such understanding, the reader encounters the familiar Traveling Salesman Problem and Prisoner's dilemma, how agricultural decisions are made in Argentina's Pampas region, and some social goals that come into play as an element of rational decision-making. In these 14 self-contained chapters, broad topics covered include the integration of decision analysis and behavioral models, innovations in behavioral models, exploring descriptive behavior models, and experimental studies.
Download or read book Courses Catalog University of Illinois at Urbana Champaign written by University of Illinois at Urbana-Champaign and published by . This book was released on 2000 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Includes undergraduate and graduate courses.
Download or read book Decision Analytics Applications in Industry written by P. K. Kapur and published by Springer. This book was released on 2020-05-28 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a range of qualitative and quantitative analyses in areas such as cybersecurity, sustainability, multivariate analysis, customer satisfaction, parametric programming, software reliability growth modeling, and blockchain technology, to name but a few. It also highlights integrated methods and practices in the areas of machine learning and genetic algorithms. After discussing applications in supply chains and logistics, cloud computing, six sigma, production management, big data analysis, satellite imaging, game theory, biometric systems, quality, and system performance, the book examines the latest developments and breakthroughs in the field of science and technology, and provides novel problem-solving methods. The themes discussed in the book link contributions by researchers and practitioners from different branches of engineering and management, and hailing from around the globe. These contributions provide scholars with a platform to derive maximum utility in the area of analytics by subscribing to the idea of managing business through system sciences, operations, and management. Managers and decision-makers can learn a great deal from the respective chapters, which will help them devise their own business strategies and find real-world solutions to complex industrial problems.
Download or read book Multi Level Decision Making written by Guangquan Zhang and published by Springer. This book was released on 2015-03-10 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph presents new developments in multi-level decision-making theory, technique and method in both modeling and solution issues. It especially presents how a decision support system can support managers in reaching a solution to a multi-level decision problem in practice. This monograph combines decision theories, methods, algorithms and applications effectively. It discusses in detail the models and solution algorithms of each issue of bi-level and tri-level decision-making, such as multi-leaders, multi-followers, multi-objectives, rule-set-based, and fuzzy parameters. Potential readers include organizational managers and practicing professionals, who can use the methods and software provided to solve their real decision problems; PhD students and researchers in the areas of bi-level and multi-level decision-making and decision support systems; students at an advanced undergraduate, master’s level in information systems, business administration, or the application of computer science.
Download or read book Analytical Methods for Dynamic Modelers written by Hazhir Rahmandad and published by National Geographic Books. This book was released on 2015-11-13 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A user-friendly introduction to some of the most useful analytical tools for model building, estimation, and analysis, presenting key methods and examples. Simulation modeling is increasingly integrated into research and policy analysis of complex sociotechnical systems in a variety of domains. Model-based analysis and policy design inform a range of applications in fields from economics to engineering to health care. This book offers a hands-on introduction to key analytical methods for dynamic modeling. Bringing together tools and methodologies from fields as diverse as computational statistics, econometrics, and operations research in a single text, the book can be used for graduate-level courses and as a reference for dynamic modelers who want to expand their methodological toolbox. The focus is on quantitative techniques for use by dynamic modelers during model construction and analysis, and the material presented is accessible to readers with a background in college-level calculus and statistics. Each chapter describes a key method, presenting an introduction that emphasizes the basic intuition behind each method, tutorial style examples, references to key literature, and exercises. The chapter authors are all experts in the tools and methods they present. The book covers estimation of model parameters using quantitative data; understanding the links between model structure and its behavior; and decision support and optimization. An online appendix offers computer code for applications, models, and solutions to exercises. Contributors Wenyi An, Edward G. Anderson Jr., Yaman Barlas, Nishesh Chalise, Robert Eberlein, Hamed Ghoddusi, Winfried Grassmann, Peter S. Hovmand, Mohammad S. Jalali, Nitin Joglekar, David Keith, Juxin Liu, Erling Moxnes, Rogelio Oliva, Nathaniel D. Osgood, Hazhir Rahmandad, Raymond Spiteri, John Sterman, Jeroen Struben, Burcu Tan, Karen Yee, Gönenç Yücel
Download or read book Decision Analysis Uncertainty Theories and Aggregation Operators in Financial Selection Problems written by Binyamin Yusoff and published by . This book was released on 2017 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: The complexity of financial analysis, particularly on selection process or decision making problems, has increased rapidly over several decades. As a result, much attention has been focused on developing and implementing the efficient mathematical models for supporting this kind of problems. Multiple criteria decision analysis, an advanced field of operations research provides analysts or decision makers a broad range of methodologies, which are all suited to the complexity of financial decision analysis. In the financial modeling, uncertainty problems are inevitable, owing to the fact that the consequences of events are not precisely known. In addition, human judgments as part of analysis also contribute to it intricacy. Correspondingly, many studies have been concentrated on integrating uncertainty theories in modeling the real financial problems. One area of interest is on the inclusion of the element of human behavior or attitudinal character of decision makers. Aggregation operator in this case can offer a wide spectrum of analysis or flexibility in modeling the human behavior in financial decision analysis. In general, the main purpose of this work is on the study of financial selection problems from the perspective of decision analysis, uncertainty theories and aggregation operators. To be specific, the decision problems under a finite or discrete case and multidimensional factors are studied. The emphasis is given on the group decision making models, notably, the Dempster-Shafer theory (DST) of belief structure, the analytic hierarchy process (AHP) and the technique for order performance by similarity to ideal solution (TOPSIS). Moreover, the uncertainty theories based on fuzzy set theory and imprecise probability are employed, together with information fusion based on the ordered weighted average (OWA) operators. Quantitative and qualitative preferences, decision strategies based on the attitudinal character of decision makers, and majority concepts for group consensus are highlighted. The specific contributions of this work are summarized as the following: ·The first contribution is on developing the multi-expert multi-criteria decision making (ME-MCDM) model with respect to two-stage aggregation processes. In specific, the aggregation of criteria is based on the integration of weighted arithmetic mean (WA) and OWA. The main attention is given on the proposed alternative OWAWA operator as an extension of immediate WA and OWAWA operators. Two approaches for modeling the majority opinion of experts are studied, in which based on the induced OWA (IOWA) operators. Some modifications to the support functions are suggested as to derive the order inducing variables. The analysis of ME-MCDM model based on these aggregation processes then is conducted. In this study the selection of investment strategy is used as to exemplify the model. ·The weighted-selective aggregated majority-OWA operator may be considered as the second contribution. It is as an extension of the SAM-OWA operator, where the reliability of information sources is considered. The WSAM-OWA then is generalized to the quantified WSAM-OWA by incorporating the concept of linguistic quantifier, mainly for the group fusion strategy. The QWSAM-IOWA with an ordering step is proposed for the individual fusion strategy. These aggregation operators are then implemented to the case of alternative scheme of heterogeneous group decision analysis, in particular for a selection of investment problem. ·Third contribution is represented by the development of linguistic group decision making with Dempster-Shafer belief structure. Different type of linguistic aggregation operator such as the 2-tuple induced linguistic OWA operator is suggested. Specifically, it is based on order-inducing variables in which the ordering of the arguments and uncertain situations can be assessed with linguistic information. Then, by using the 2-TILOWA in the D-S framework, the belief structure-2-TILOWA operator can be formed. Some of its main properties are studied. This model is applied in a selection of financial strategies. · The extension of AHP for group decision making model is given as the fourth contribution, notably, based on the inclusion of IOWA operators. Two-stage aggregation processes used in the AHP-GDM model are extended. Firstly, a generalization of weighted maximal entropy OWA under the IOWA operator is proposed as to aggregate the criteria. Further, the majority concept based on the IOWA and Minkowski OWA-based similarity measure is suggested to determine a consensus among experts. This model provides a variant of decision strategies for analyzing the individual and the majority of experts. The application in investment selection problem is presented to test the reliability of the model. · The fifth contribution is on the integration of heavy ordered weighted geometric (HOWG) aggregation operators in AHP-GDM model. In the sense of heavy OWA operator (HOWA), the heavy weighted geometric (HWG) and HOWG are introduced as extensions of the normal weighted geometric mean (WG) and the OWG by relaxing the constraints on the associated weighting vector. These HWG and HOWG operators then are utilized in the aggregation process of AHP-GDM, specifically on the aggregation of individual judgments procedure. The main advantage of the model, besides the complete overlapping of information such in classical methods, is that it can also accommodate partial and non-overlapping information in the formulation. An investment selection problem is applied to demonstrate the model. ·The extension of TOPSIS for group decision making model by the inclusion of majority concept may be considered as the sixth contribution. The majority concept is derived based on the induced generalized OWA (IGOWA) operators. Two fusion schemes in TOPSIS model are designed. First, an external fusion scheme to aggregate the experts' judgments with respect to the concept of majority opinion on each criterion is suggested. Then, an internal fusion scheme of ideal and anti-ideal solutions that represents the majority of experts is proposed using the Minkowski OWA distance measures. The comparison of the proposed model with some other TOPSIS models with respect to distance measures is presented. Here, a general case of selection problem is presented, specifically on the human resource selection problem. ·Finally, the group decision making model based on conflicting bifuzzy sets (CBFS) is proposed. Precisely, the subjective judgments of experts, mainly from positive and negative aspects are considered simultaneously in the analysis. Moreover, the weighting method for the attribute (or sub-attribute) is subject to the integration of subjective and objective weights. The synthesis of CBFS in the model is naturally done by extending the fuzzy evaluation in parallel with the intuitionistic fuzzy set. A new technique to compute the similarity measure is proposed, in which, being the degree of agreement between the experts. The model then is applied in the case study of flood control project selection problem. To sum up, the presented thesis dealt with the extension of multi-criteria decision analysis models for the financial selection problems (as a specific scope) and also the general selection problems with the inclusion of attitudinal character, majority concept and fuzzy set theory. In particular, the group decision making model, Dempster-Shafer belief structure, AHP and TOPSIS are proposed to overcome the shortcoming of the existing models, i.e., related to the financial decision analysis. The applicability and robustness of the developed models have been demonstrated and some sensitivity analyses are also provided. The main advantages of the proposed models are to provide a more general and flexible models for a wider analysis of the decision problems.
Download or read book Decision and Simulation Modeling in Systematic Reviews written by U. S. Department Human Services and published by Createspace Independent Publishing Platform. This book was released on 2013-05-17 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: PURPOSE: The purpose of this study is to provide guidance for determining when incorporating a decision-analytic model alongside a systemic review would be of added value for decision making purposes. The purpose of systematic reviews is to synthesize the current scientific literature on a particular topic in the form of evidence reports and technology assessments to assist public and private organizations in developing strategies that improve the quality of health care and decision making. However, there is often not enough evidence to fully address the questions that are relevant for decision makers. Decision models may provide added value alongside systematic reviews by adding a formal structure, which can be informed by the evidence. METHODS: Our framework is informed by two sets of interviews and a focus group discussion; literature reviews to summarize best modeling practices and to profile the modeling literature; and an exploration of the feasibility of developing a database of published models. We interviewed Evidence-based Practice Center (EPC) members, some of whom have successfully incorporated models in EPC reports, to document lessons learned from those experiences. We also interviewed members of the U.S. Preventive Services Task Force (USPSTF) and cancer modelers who were involved in the recent efforts to use modeling with a systematic review to update USPSTF cancer screening guidelines, to evaluate the process of conducting a simultaneous systematic review and modeling exercise, and to evaluate stakeholder-perceived needs and whether needs were met. We reviewed and summarized the literature on best practices for modeling. This was supplemented by a focus group discussion with modeling experts to elicit, characterize, and precisely qualify best practices in decision and simulation modeling. These included: model formulation and characterization, model development and construction, handling and presentation of modeling assumptions, definition and presentation of parameters, outcomes to incorporate into the model, model analysis, model testing, validation, and implementation (including results presentation and communication). We developed a profile of the current modeling literature by conducting a systematic review of the medical literature and the grey literature to document publications that used a decision model and for what purpose (e.g., disease of interest, interventions evaluated). We also developed a prototype database to serve as a preliminary step in developing a resource that could be used to determine if, and how many, models exist on a particular disease of interest. RESULTS: The resulting report consists of six chapters. Decision and Simulation Modeling Alongside Systematic Reviews provides an overview of models and describes the differences and synergies between systematic reviews and decision analysis. In Overview of Decision Models Used in Research, we provide a "scan" of the medical literature over the past 5 years in terms of the use of models in studies that compare intervention strategies using multiple sources of data. Use of Modeling in Systematic Reviews: The EPC Perspective documents the extent to which EPCs have incorporated models into data and presents results from key informant interviews with EPC members. We present a framework for deciding when a decision model can inform decisionmaking alongside a systematic review in Suggested Framework for Deciding When a Modeling Effort Should Be Added to a Systematic Review. Potential Modeling Resources explores several possible approaches to use when undertaking a modeling effort and discusses some of the challenges. Lastly, Best Practices for Decision and Simulation Modeling reviews the literature on best practices for modeling, supplemented by a focus group discussion with modeling experts, and lessons learned about the process of conducting a modeling exercise alongside a systematic review using recent experience with the USPSTF. CONCLUSIONS: We suggest a process for deciding when conducting a decision analysis in conjunction with a systematic review would be of value to decision makers.
Download or read book Social Science Research written by Anol Bhattacherjee and published by CreateSpace. This book was released on 2012-04-01 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.
Download or read book Bulletin of the Atomic Scientists written by and published by . This book was released on 1970-06 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Bulletin of the Atomic Scientists is the premier public resource on scientific and technological developments that impact global security. Founded by Manhattan Project Scientists, the Bulletin's iconic "Doomsday Clock" stimulates solutions for a safer world.
Download or read book An Archetypal Analysis for the Development of a Generalized Decision Making Model in Groups as a Prerequisite for Productive Government and Leadership written by George S. Spais and published by . This book was released on 2007 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The original cultural roots of Economics, Informatics and Decision Sciences are related to its genesis, mythology, and prehistory and, of course, to its proto-foundations as a scientific discipline. The knowledge of the cultural roots of the Economics and Decision Sciences will promote our understanding of this vital topic and will deepen our thinking about its importance and usefulness, both as a practical and theoretical ergon/engagement discipline. Under this prism, the present work is examining the contributory role of god Hermes to the effectiveness and efficiency of the Olympian Style of Management in the ancient Greek society. So, the major objective of this work is to propose an integrated model for productive (= effective + efficient) decision-making in groups. Group decision-making is the process of arriving at a judgment based upon the feedback of multiple individuals. Such decision-making is a key component to the functioning of an organization, because organizational performance involves more than just individual action. Due to the importance of the group decision-making process, decision-making models can be used to establish a systematic means of developing effective group decision-making. In our study, we have examined twenty-two (22) ancient Greek works. Our intention is to understand god Hermes' personality traits and activities, as an indicator of the level of knowledge of Ancient Greeks on management science and their perceptions on the value of information and knowledge management in a group decision-making process. The authors propose that rational decision-making in all levels, in both government and entrepreneurship; prerequisites high quality of data, integrated information, convergence and consistency. The major implication of this study is related to the raising challenge for the next years, where academics must promote the systemic, multidisciplinary way of thinking to business students from economics, management and informatics fields.
Download or read book Catalogs of Courses written by University of California, Berkeley and published by . This book was released on 1994 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: Includes general and summer catalogs issued between 1878/1879 and 1995/1997.
