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Journal articles on the topic 'Decision implementation'

Author: Grafiati

Published: 4 June 2021

Last updated: 5 February 2022

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1

Parlindungan and HariSupriadi. "Implementation Decision Tree Algorithm for Ecommerce Website." International Journal of Psychosocial Rehabilitation 24, no. 02 (February 13, 2020): 3611–14. http://dx.doi.org/10.37200/ijpr/v24i2/pr200682.

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2

STRUHARIK, RASTISLAV J. R., and LADISLAV A. NOVAK. "HARDWARE IMPLEMENTATION OF DECISION TREE ENSEMBLES." Journal of Circuits, Systems and Computers 22, no. 05 (May 9, 2013): 1350032. http://dx.doi.org/10.1142/s0218126613500321.

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In this paper, several hardware architectures for the realization of ensembles of axis-parallel, oblique and nonlinear decision trees (DTs) are presented. Hardware architectures for the implementation of a number of ensemble combination rules are also presented. These architectures are universal and can be used to combine predictions from any type of classifiers, such as decision trees, artificial neural networks (ANNs) and support vector machines (SVMs). Proposed architectures are suitable for the implementation using Field Programmable Gate Arrays (FPGA) and Application Specific Integrated Circuits (ASIC). Experiment results obtained using 29 datasets from the standard UCI Machine Learning Repository database suggest that the FPGA implementations offer significant improvement in the classification time in comparison with the traditional software implementations. Greatest improvement can be achieved using the SP2-P architecture implemented on the FPGA achieving 416.53 times faster classification speed on average, compared with the software implementation. This result has been achieved on the FPGA working at 135.51 MHz on average, which is 33.21 times slower than the operating frequency of the general purpose computer on which the software implementation has been executed.

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3

STRUHARIK, RASTISLAV J. R., and LADISLAV A. NOVAK. "EVOLVING DECISION TREES IN HARDWARE." Journal of Circuits, Systems and Computers 18, no. 06 (October 2009): 1033–60. http://dx.doi.org/10.1142/s0218126609005526.

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This paper, according to the best of our knowledge, provides the very first solution to the hardware implementation of the complete decision tree inference algorithm. Evolving decision trees in hardware is motivated by a significant improvement in the evolution time compared to the time needed for software evolution and efficient use of decision trees in various embedded applications (robotic navigation systems, image processing systems, etc.), where run-time adaptive learning is of particular interest. Several architectures for the hardware evolution of single oblique or nonlinear decision trees and ensembles comprised from oblique or nonlinear decision trees are presented. Proposed architectures are suitable for the implementation using both Field Programmable Gate Arrays (FPGA) and Application Specific Integrated Circuits (ASIC). Results of experiments obtained using 29 datasets from the standard UCI Machine Learning Repository database suggest that the FPGA implementations offer significant improvement in inference time when compared with the traditional software implementations. In the case of single decision tree evolution, FPGA implementation of H_DTS2 architecture has on average 26 times shorter inference time when compared to the software implementation, whereas FPGA implementation of H_DTE2 architecture has on average 693 times shorter inference time than the software implementation.

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Amarini, Indriati. "IMPLEMENTATION OF JUDICIAL ACTIVISM IN JUDGE’S DECISION." Jurnal Hukum dan Peradilan 8, no. 1 (March 30, 2019): 21. http://dx.doi.org/10.25216/jhp.8.1.2019.21-38.

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The task of the judge in realizing justice is inseparable from the decisions that are made. A qualified judge's decision is obtained through the judge's thought process through a choice of judges that reflects judicial activism. The problem in this research is how judicial activism is used by judges in issuing decisions and how the implementation of judicial activism in decision making. Judicial Activism is the choice of decision making by judges in order to realize justice. Judicial activism in the Indonesian judicial system is regulated in Article 5 paragraph (1) of Law Number 48 of 2009 concerning Judicial Power. The law requires judges to explore the law and sense of justice that lives in society. The implementation of judicial activism is carried out by judges through means of legal discovery. Through means of legal discovery, judges play an active role in realizing justice as a law that lives in a dynamically developing society.

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5

Costeniuc, Marius, Michaela Schnetzer, and Luca Taschini. "Entry and Exit Decision Problem with Implementation Delay." Journal of Applied Probability 45, no. 04 (December 2008): 1039–59. http://dx.doi.org/10.1017/s0021900200004964.

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We study investment and disinvestment decisions in situations where there is a time lagd> 0 from the timetwhen the decision is taken to the timet+dwhen the decision is implemented. In this paper we apply the probabilistic approach to the combined entry and exit decisions under the Parisian implementation delay. In particular, we prove the independence between Parisian stopping times and a general Brownian motion with drift stopped at the stopping time. Relying on this result, we solve the constrained maximization problem, obtaining an analytic solution to the optimal ‘starting’ and ‘stopping’ levels. We compare our results with the instantaneous entry and exit situation, and show that an increase in the uncertainty of the underlying process hastens the decision to invest or disinvest, extending a result of Bar-Ilan and Strange (1996).

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Costeniuc, Marius, Michaela Schnetzer, and Luca Taschini. "Entry and Exit Decision Problem with Implementation Delay." Journal of Applied Probability 45, no. 4 (December 2008): 1039–59. http://dx.doi.org/10.1239/jap/1231340232.

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We study investment and disinvestment decisions in situations where there is a time lagd> 0 from the timetwhen the decision is taken to the timet+dwhen the decision is implemented. In this paper we apply the probabilistic approach to the combined entry and exit decisions under the Parisian implementation delay. In particular, we prove the independence between Parisian stopping times and a general Brownian motion with drift stopped at the stopping time. Relying on this result, we solve the constrained maximization problem, obtaining an analytic solution to the optimal ‘starting’ and ‘stopping’ levels. We compare our results with the instantaneous entry and exit situation, and show that an increase in the uncertainty of the underlying process hastens the decision to invest or disinvest, extending a result of Bar-Ilan and Strange (1996).

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7

Moustaid, Bouzekri, and Mohamed Fakir. "Implementation of Business Intelligence For Sales Management." IAES International Journal of Artificial Intelligence (IJ-AI) 5, no. 1 (March 1, 2016): 22. http://dx.doi.org/10.11591/ijai.v5.i1.pp22-34.

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<p>Today's company operates in a socio-economic environment increasingly demanding. In such a context, it is obliged to adopt a competitive approach by exploiting at best the information that it possesses for developing appropriate action plans and taking effective decisions. The decision support systems provide to the enterprise the tools that help it for decision-making based on techniques and methodologies coming from domain of applied mathematics such as optimization, statistics and theory of the decision. The decision support systems are composed of various components such as data warehouses, ETL tools and reporting and analysis tools.</p>

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8

Ervin, Kaye E., Irene Blackberry, and Helen Haines. "Implementation of Shared Decision-Making in Australia." Asia Pacific Journal of Health Management 11, no. 2 (July 1, 2016): 10–11. http://dx.doi.org/10.24083/apjhm.v11i2.177.

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Shared decision-making (SDM) is the process of clinicians and patients participating jointly in making healthcare decisions, having discussed evidence-based treatment options and the potential risks and benefits of each option, taking into consideration the patient’s individual preferences and values. SDM is ubiquitous in Australian healthcare policy. While there is good evidence for utilising SDM, clinicians’ knowledge of SDM, the current uptake, effectiveness and acceptability of SDM in Australia is largely unknown. The challenges perceived by clinicians to implementing SDM in clinical practice and potential moral, legal and ethical dilemmas require further debate and consideration. Abbreviations: SDM – Shared Decision-Making.

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9

Erokhina, O. V. "Implementation of Machine Learning Methods to solve Political Problems." Humanities and Social Sciences. Bulletin of the Financial University 10, no. 3 (November 2, 2020): 67–73. http://dx.doi.org/10.26794/2226-7867-2020-10-3-67-73.

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The political reality described by non-linearity of processes and significant influence of informal mechanisms of interaction of decision-making subjects-political elites and leaders. One of the most promising areas that open up new opportunities for studying political problems is the synthesis of “traditional” methodology of political analysis and methods of artificial intelligence. The purpose of this work is to build a methodological model in the form of a “decision tree” and use it to analyze the process of making personnel decisions concerning the heads of the subjects of the Russian Federation. Chronological limits: 2000–2020 years. It is necessary to solve the following tasks to achieve such a goal. 1. Study the main trends and priorities of the Federal centre’s personnel policy in relation to regional heads in the period under review. 2. Identification of key factors affecting the political positions of the leaders of regions of the Russian Federation based on the analysis of data on the performance parameters of the regional executive power. 3. Generalization of data on personnel decisions made in 2000–2018 and the construction of a “decision tree” that provides grounds for predicting future personnel decisions following the selected algorithm. The article substantiates the adequacy of using the decision tree for analyzing and predicting political decisions on the example of the personnel policy of federal government structures in relation to the regions of the Russian Federation. Based on the results of the work, 13 formal and informal criteria for assessing the stability of political positions of governors with varying degrees of probability of their use in the process of making personnel decisions were formulated. The author proposes to use these criteria as attributes for training the decision tree. Due to the significant amount of data, the paper presents a fragment of the decision tree that clearly illustrates the possibility of using the C 4.5 algorithm to solve political problems.

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10

Simonian, Armen I., and Jason H. Lam. "Implementation of clinical decision support rules." American Journal of Health-System Pharmacy 73, no. 7 (April 1, 2016): 436–39. http://dx.doi.org/10.2146/ajhp150122.

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11

Blaskovich, Jennifer L., and Brian P. McAllister. "Organizational Reasons For Decision Aid Implementation." Review of Business Information Systems (RBIS) 11, no. 3 (July 1, 2007): 53–58. http://dx.doi.org/10.19030/rbis.v11i3.4416.

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12

Sananda, Vikash, and Austin Melton. "Decision and Implementation Models for Outsourcing." Global Studies Journal 2, no. 3 (2009): 49–58. http://dx.doi.org/10.18848/1835-4432/cgp/v02i03/40629.

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13

Murphy, Sean D. "U.S. Implementation of lCJ's LaGrand Decision." American Journal of International Law 97, no. 1 (January 2003): 180–82. http://dx.doi.org/10.2307/3087117.

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14

Sepucha, Karen R., and Albert G. Mulley. "Extending decision support: preparation and implementation." Patient Education and Counseling 50, no. 3 (July 2003): 269–71. http://dx.doi.org/10.1016/s0738-3991(03)00048-x.

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15

Massey, Aaron K., Paul N. Otto, and Annie I. Antn. "Evaluating Legal Implementation Readiness Decision-Making." IEEE Transactions on Software Engineering 41, no. 6 (June 1, 2015): 545–64. http://dx.doi.org/10.1109/tse.2014.2383374.

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16

Sarkar, Sudipto, and Chuanqian Zhang. "Implementation lag and the investment decision." Economics Letters 119, no. 2 (May 2013): 136–40. http://dx.doi.org/10.1016/j.econlet.2013.02.018.

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17

Tippett, Donald D., and Rodney G. Grubb. "Environmental remediation technology implementation decision patterns." Journal of Technology Transfer 21, no. 1-2 (March 1996): 22–26. http://dx.doi.org/10.1007/bf02220303.

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18

Ungureanu, Sebastian. "Implementation Cost Calculation Using ABC Method." International conference KNOWLEDGE-BASED ORGANIZATION 21, no. 2 (June 1, 2015): 360–65. http://dx.doi.org/10.1515/kbo-2015-0060.

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Abstract The cost information system plays an important role in every organization in the decision making process. An important task of management is to ensure control of the operations, processes, sectors of activity and not finally, on costs. Although the objectives of an organization contributes with more control systems (production control, quality control etc.), the cost information system is important because it monitors the results of others. The detailed analysis of costs, production cost calculation, quantification of losses, the work efficiency estimation provide a solid basis for financial control. Knowledge of cost is a decisive factor in taking decisions and planning future activities. Managers are concerned about the costs that will appear in the future, their level underpinning the supply and production decisions and pricing policies. An important factor is the cost efficiency of the information system so that the information provided by it is useful for decision support and planning the activities.

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19

Romanova, Elena. "Modeling an Individual and Group Decision on the Implementation of a Real Estate Development Project." MATEC Web of Conferences 251 (2018): 05007. http://dx.doi.org/10.1051/matecconf/201825105007.

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The implementation of the real estate development project are accompanied many management decisions. These decisions can be made by one person or a project team. The article describes the advantages and disadvantages of individual and group decisions. The results of a comparative research of decision-making by one person and a group using computer decision support systems and without them. It is shown that using of automation tools facilitates decision making and increases confidence in its correctness. It has been experimentally proved that the individual solution is based on a smaller number of factors, is accepted more quickly and more satisfied by the person making the decision, in comparison with the group decision. Further the difficulties in implementing computer decision support systems in the work of a development company and acquired benefits are listed.

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20

ABZALBEKOVA, Maral T., Roza M. ZHAMIYEVA, and Bakytzhan A. ZHAKUPOV. "Principles of Acceptance and Mistakes in the Implementation of Criminal Procedural Decisions." Journal of Advanced Research in Law and Economics 9, no. 5 (June 5, 2019): 1519. http://dx.doi.org/10.14505//jarle.v9.5(35).01.

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The relevance of the study problem is caused by the need to ensure the legality, validity and substantiation of criminal procedural decisions, which ultimately leads to the achievement of goals and objectives of criminal proceedings. Purpose of the article: the purpose of the article is to develop the principles of decision-making by the subject of criminal procedural activity, as well as identifying the typical mistakes in their implementation. Study methods: The basis of problem solving in terms of criminal procedural decision-making and implementation is the system-based and activity approach and the methodological provisions of the decision-making theory, which allowed to identify patterns in the process of criminal procedural decision-making and implementation by the representative of criminal proceeding bodies and other participants of the proceeding. Study results: The principle systems of decision-making by the subject of criminal procedural activity is provided; the levels and stages of procedural decision-making and implementation are outlined, typical mistakes made by the subject of criminal procedural decision are determined taking into account the level of decision-making and the violated principle. Practical relevance: The identified patterns, principles, stages and levels of decision-making, as well as the typical mistakes formulated, will have a significant impact on improving the viability of decisions made in the criminal proceedings, and recommendations based on them contribute to ensuring the rule of law in the activities of judges, investigators, prosecutors and other participants in the proceedings.

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21

., Faisal, Muhammad Ridwan, and Mardawati . "The Expert Choice Implementation in Selecting the Electronic Voting Software." International Journal of Engineering & Technology 7, no. 2.29 (May 22, 2018): 811. http://dx.doi.org/10.14419/ijet.v7i2.29.14262.

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The voting service process conducted today is still done manually so that it becomes a decision to utilize the electronic voting. The electronic voting greatly reduces human control and human direct influence on this voting process. Problems faced by end users in the selection are there are so many choices of electronic voting software. Decision making, essentially a form of election of the various alternatives of action or multi-criteria decision making that can be selected. Decision support system in this research is used to select the type of electronic voting software. The method used in this research is the multi criteria decision making and analytical hierarchy process using expert choice software. And aims to make decisions that can make certain parties to take the best decision in choosing the type of electronic voting software. From the data processing is concluded that the first sequence is online voting 58.3%, express vote 17.2%, simply voting 17% and ballot online 7.5%. Processing of data obtained from the respondent expert inconsistencies value ratio is less than 0.1, thus the combined geometric calculation result data is fairly consistent.

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22

Omolayec, P. O. "Implementation of University Result Decision Support Systems." International Journal for Research in Applied Science and Engineering Technology 6, no. 7 (July 31, 2018): 537–45. http://dx.doi.org/10.22214/ijraset.2018.7092.

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23

Vanrolleghem, Peter A. "Decision Support for Water Framework Directive Implementation." Water Intelligence Online 10 (2011): 9781780400976. http://dx.doi.org/10.2166/9781780400976.

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24

Fritsch, G., W. Haider, P. Hofer, J. K. Hohenberg, and V. Karg. "Implementation of decision support systems in Austria." Kerntechnik 72, no. 4 (August 2007): 187–90. http://dx.doi.org/10.3139/124.100339.

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25

CHAO, LI-CHUNG, and MIROSLAW J. SKIBNIEWSKI. "DECISION ANALYSIS FOR NEW CONSTRUCTION TECHNOLOGY IMPLEMENTATION." Civil Engineering Systems 12, no. 1 (April 1995): 67–82. http://dx.doi.org/10.1080/02630259508970159.

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26

Calloway, Stacy. "Implementation of a Clinical Decision Support System." Hospital Pharmacy 48, Supplement 2 (March 2013): S10—S14. http://dx.doi.org/10.1310/hpj4803-s10.

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27

Murphy, Sean D. "U.S. Implementation of WTO Turtle/Shrimp Decision." American Journal of International Law 94, no. 2 (April 2000): 361–63. http://dx.doi.org/10.1017/s000293000075771x.

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28

Gordon, Bonita M., Theresa Frissora Wnek, Nancy Glorius, Carmen Hasdorff, Joyce Shiverski, and Janet Ginn. "Post-Fall Decision Tree Development and Implementation." Journal of Nursing Care Quality 25, no. 4 (2010): 358–65. http://dx.doi.org/10.1097/ncq.0b013e3181e35da2.

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29

Kiss, Andreea Noemi, and Pamela S. Barr. "Strategic decision implementation speed and firm performance." Academy of Management Proceedings 2012, no. 1 (July 2012): 15753. http://dx.doi.org/10.5465/ambpp.2012.15753abstract.

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30

Ranerup, Agneta. "Decision Support Systems for Public Policy Implementation." Social Science Computer Review 26, no. 4 (December 18, 2007): 428–45. http://dx.doi.org/10.1177/0894439307312632.

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31

Nekka, Fahima, Chantal Csajka, Mélanie Wilbaux, Sachin Sanduja, Jun Li, and Marc Pfister. "Pharmacometrics-based decision tools facilitate mHealth implementation." Expert Review of Clinical Pharmacology 10, no. 1 (November 24, 2016): 39–46. http://dx.doi.org/10.1080/17512433.2017.1251837.

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32

Medlin, Richard, Carlton Moore, and Javed Mostafa. "An open source decision support system implementation." ACM SIGHIT Record 2, no. 1 (March 2012): 18. http://dx.doi.org/10.1145/2180796.2180810.

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33

Struharik, R. J. R., and L. A. Novak. "Intellectual property core implementation of decision trees." IET Computers & Digital Techniques 3, no. 3 (2009): 259. http://dx.doi.org/10.1049/iet-cdt.2008.0055.

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34

Nakamura, T., L. J. B. Vlacic, and Y. Ogiwara. "Multiattribute-based CIE/CIM implementation decision model." Computer Integrated Manufacturing Systems 9, no. 2 (May 1996): 73–89. http://dx.doi.org/10.1016/0951-5240(95)00035-6.

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35

Borges, Marcos R. S., José A. Pino, and Carla Valle. "Support for decision implementation and follow-up." European Journal of Operational Research 160, no. 2 (January 2005): 336–52. http://dx.doi.org/10.1016/j.ejor.2003.09.005.

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36

Casimir, Rommert J. "Characteristics and implementation of decision support systems." Information & Management 14, no. 1 (January 1988): 1–7. http://dx.doi.org/10.1016/0378-7206(88)90062-6.

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37

de Souza, Renan Rodrigues, and José Roberto C. Piqueira. "Implementation of quantum gates using decision diagrams." Computers & Electrical Engineering 95 (October 2021): 107426. http://dx.doi.org/10.1016/j.compeleceng.2021.107426.

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38

Sasmito, Hasto. "Implementation Of Decisions And Obstacles Administrative Court - Implementation Obstacles." Jurnal Daulat Hukum 1, no. 2 (June 15, 2018): 391. http://dx.doi.org/10.30659/jdh.v1i2.3279.

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Indonesia is a country of law. The rule of law means in our country is the law that has significance especially in all aspects of community life. Everything implementation carried out by the state through its government should be appropriate and according to the channels that have been determined in advance by law. Judicial Administration is a special court, which was given the authority to resolve disputes that arise in the field of administration and personnel or disputes that occur between administration officials with a person or body of civil law as a result of the issuance or issuance of a decision. Act no. 5 of 1986 on State Administration aims to provide a container or a space for people and civil legal entity to file a lawsuit to the Administrative Court (PTUN) for the issuance of an administrative decision (KTUN), then his rights to feel disturbed or harmed but in practice administrative court ruling will not necessarily be implemented because of constraints exist that impede the implementation of the decision of the Administrative Court. Thus the presence of the administrative court as an institution that is expected to be a means of enforcement and legal protection in the field of administration can not be carried out effectively and still needed revision of the law.Keywords: State Administrative Court (PTUN).

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39

Vlăduţescu, Ştefan, Claudiu Marian Bunăiașu, and Alexandru Constantin Strungă. "Decision Communication in Education Management." International Letters of Social and Humanistic Sciences 44 (December 2014): 53–60. http://dx.doi.org/10.18052/www.scipress.com/ilshs.44.53.

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In the decision making process in education management, the communicational component has an important role. Communication is the sine qua non factor of the decision. Since it takes place in the decision situation, the type of communication that permeates the processes of making and implementation of managerial decisions was named decision communication.

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40

Stacey, Dawn, France Légaré, Laura Boland, Krystina B. Lewis, Marie-Chantal Loiselle, Lauren Hoefel, Mirjam Garvelink, and Annette O’Connor. "20th Anniversary Ottawa Decision Support Framework: Part 3 Overview of Systematic Reviews and Updated Framework." Medical Decision Making 40, no. 3 (April 2020): 379–98. http://dx.doi.org/10.1177/0272989x20911870.

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Introduction. The Ottawa Decision Support Framework (ODSF) has guided practitioners and patients facing difficult decisions for 20 years. It asserts that decision support interventions that address patients’ decisional needs improve decision quality. Purpose. To update the ODSF based on a synthesis of evidence. Methods. We conducted an overview of systematic reviews, searching 9 electronic databases. Eligible reviews included decisional needs assessments, decision support interventions, and decisional outcome measures guided by the ODSF. We extracted data and synthesized results narratively. Eight ODSF developers/expert users from 4 disciplines revised the ODSF. Results. Of 4656 citations, we identified 4 eligible reviews (>250 studies, >100 different decisions, >50,000 patients, 18 countries, 5 continents). They reported current ODSF decisional needs and their most frequent manifestations in the areas of inadequate knowledge/information, unclear values, decisional conflict/uncertainty, and inadequate support. They uncovered 11 new manifestations of 6 decisional needs. Using the Decisional Conflict Scale (DCS) to assess decisional needs, average scores were elevated at baseline and declined shortly after decision making, even without information interventions. Patient decision aids were superior to usual care in reducing total DCS scores and improving decision quality. We revised the ODSF by refining definitions of 6 decisional needs and adding new interventions to address 4 needs. We added a decision process outcome and eliminated secondary outcomes unlikely to improve across a range of decisions, retaining the implementation/continuance of the chosen option and appropriate use/costs of health services. Conclusions. We updated the ODSF to reflect the current evidence and identified implications for practice and further research.

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41

van Tol-Geerdink, Julia J., Inge M. van Oort, Diederik M. Somford, Carl J. Wijburg, Arno Geboers, Cornelia F. van Uden-Kraan, Marieke de Vries, and Peep FM Stalmeier. "Implementation of a decision aid for localized prostate cancer in routine care: A successful implementation strategy." Health Informatics Journal 26, no. 2 (September 30, 2019): 1194–207. http://dx.doi.org/10.1177/1460458219873528.

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For the treatment choice of localized prostate cancer, effective patient decision aids have been developed. The implementation of decision aids in routine care, however, lags behind. Main known barriers are lack of confidence in the tool, lack of training on its use, lack of resources and lack of time. A new implementation strategy addresses these barriers. Using this implementation strategy, the implementation rate of a decision aid was measured in eight hospitals and questionnaires were filled out by 24 care providers and 255 patients. The average implementation rate was 60 per cent (range 31%–100%). Hardly any barriers remained for care providers. Patients who did not use the decision aid appeared to be more unwilling than unable to use the decision aid. By addressing known barriers, that is, informing care providers on the effectiveness of the decision aid, providing instructions on its use, embedding it in the existing workflow and making it available free of charge, a successful implementation of a prostate cancer decision aid was reached.

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42

Haricha, Karim, Azeddine Khiat, Yassine Issaoui, Ayoub Bahnasse, and Hassan Ouajji. "Towards smart manufacturing: Implementation and benefits." Journal of Ubiquitous Systems and Pervasive Networks 15, no. 02 (March 1, 2021): 25–31. http://dx.doi.org/10.5383/juspn.15.02.004.

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Production activities is generating a large amount of data in different types (i.e., text, images), that is not well exploited. This data can be translated easily to knowledge that can help to predict all the risks that can impact the business, solve problems, promote efficiency of the manufacture to the maximum, make the production more flexible and improving the quality of making smart decisions, however, implementing the Smart Manufacturing(SM) concept provides this opportunity supported by the new generation of the technologies. Internet Of Things (IoT) for more connectivity and getting data in real time, Big Data to store the huge volume of data and Deep Learning algorithms(DL) to learn from the historical and real time data to generate knowledge, that can be used, predict all the risks, problem solving, and better decision-making. In this paper, we will introduce SM and the main technologies to success the implementation, the benefits, and the challenges.

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43

Goslar, Martin D., Gary I. Green, and Terry H. Hughes. "Applications and Implementation DECISION SUPPORT SYSTEMS: AN EMPIRICAL ASSESSMENT FOR DECISION MAKING." Decision Sciences 17, no. 1 (January 1986): 79–91. http://dx.doi.org/10.1111/j.1540-5915.1986.tb00214.x.

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44

Ważna, Lilianna, and Tadeusz Krupa. "The Multicriteria Assessment Methodology of the Decision Support System Implementation Effectiveness." Foundations of Management 2, no. 2 (January 1, 2010): 81–100. http://dx.doi.org/10.2478/v10238-012-0030-y.

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The Multicriteria Assessment Methodology of the Decision Support System Implementation EffectivenessThe multi-criteria assessment methodology of implementation effectiveness of information systems illustrated by an example of decision support system (DSS) realized in w information technologies is presented in the article. The assessment of DSS under consideration takes place using the knowledge recorded in the form of fuzzy neural network, collected in an enterprise, on the basis of earlier realized implementations of other information systems. A model of retrieved DSS is expressed by means of a set of functionalities serving business processes of the enterprise under consideration. A model of implementation undertaking determined by means of a set of preparatory actions for the implementation and a set of directly implementation and exploitation actions is built for the retrieved DSS as well. Furthermore, a vector determining a current and planned implementation state of a set of DSS functionalities in the enterprise at time moments, before and after the commencement of planned implementation of the retrieved DSS is built. A concept of trapezoidal fuzzy numbers is used in building DSS models. An adjustment of fuzzy parameters of DSS models takes place by means of geometrical method of maximum absolute error points. A presented methodology enables to execute a multi-criteria effectiveness assessment of planned undertaking in relation to subjective criteria established by the enterprise (preferred time, cost and values of priority indexes). Additionally, the knowledge collected on the basis of earlier realized implementations of information systems and applied imprecise description of parameters taking into account errors made in their estimation in the past is used.

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Briukhovetska, M. S. "MANAGEMENT DECISIONS AND FACTORS THAT INFLUENCE THE PROCESS OF ITS ADOPTION AND IMPLEMENTATION." Actual problems of native jurisprudence, no. 4 (August 30, 2019): 3–6. http://dx.doi.org/10.15421/391901.

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The study evaluated the decision-making processes and determined that the factors that influence the administrative decision-making processes can be divided into рersonal and material aspects. The main purpose of the article was to identify ways to improve the decision-making process by identifying the factors that influence it. It is found that the concept of "underfunding" is relative. Management decisions are not attributed to the category of expenditures. They are unrelated to the purchase of technology and new equipment. The main factor, however, is the organizational culture and the management system. After all, knowledge in the field of management and administration, appropriate training and development of innovations in the field of management is important for most managers. It is emphasized that an important element of decision making is to ensure that it is properly substantiated. It should properly inform those who are interested in its adoption. The decision should outline the key aspects under consideration and the underlying considerations. It should contain a detailed statement of all the essential issues. The basic prerequisites for making an effective management decision are identified: they must make a clear strategy, resource allocation and risk identification; the ideas put forward by decision makers should be taken into account; the decision-making procedure must be fast in order not to lose its relevance; the decision should not contradict the decisions of other management structures, as there must be consistency between them for the implementation of the functions entrusted to the institution. It is proved that several steps are needed to make a decision: first, to identify the problem to be solved and the goals to be achieved, secondly, to identify the alternatives that lead to the proposed goals, and to evaluate whether the alternatives meet the expected the result, thirdly, to take all necessary measures to implement the solution. It is concluded that an effective managerial decision must be pragmatic, since it is an important step in its implementation. If the solution does not translate into work and a concrete result, it is not the decision, it is the intention.

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Peng, Guang Yu. "Marketing Decision and Decision Support System Design Based on Web." Advanced Materials Research 850-851 (December 2013): 1048–51. http://dx.doi.org/10.4028/www.scientific.net/amr.850-851.1048.

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This paper analyzes the DSS characteristics about the marketing under the internet as well as the influencing factors of the market decisions, Studying the decision-making functions of marketing decision support system DSS. It proposed the marketing DSS design, logical structure and its implementation based on a data warehouse as the center, online analysis processing and data mining as a means.

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Carolina, Irmawati, Fitra Hariman Hakim, and Adi Supriyatna. "Implementation Of The SAW Method For Selection Of Best Operational Vehicles." JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING 4, no. 1 (July 20, 2020): 67–75. http://dx.doi.org/10.31289/jite.v4i1.3790.

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Operational Vehicle is one of the assets owned by the company to help transportation that aims to facilitate the carrying out of a job. With the existence of operational vehicles can increase company productivity. The problems that exist in the process of selecting the best operational vehicles are still simple or depend on the company's budget. The purpose of this study is to obtain a decision in determining the selection of operational vehicles using several criteria and can provide solutions to determine the best choice of operational vehicles for company management. The method used by the author is Simple Additive Weighting (SAW) which can help in making decisions to overcome a complex problem. The results of this study are the decision support system can be used as a tool for decision making recommendations for companies in determining the selection of operational vehicles using the Simple Additive Weighting (SAW) method, in addition to providing an alternative form of decision support systems to help and facilitate the company's stakeholders in decide on operational vehicles.Keywords: Decision Support System, Operational Vehicle, SAW Method.

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ANTONIK, ADAM, MICHAEL HUTH, KIM G. LARSEN, ULRIK NYMAN, and ANDRZEJ WĄSOWSKI. "Modal and mixed specifications: key decision problems and their complexities." Mathematical Structures in Computer Science 20, no. 1 (February 2010): 75–103. http://dx.doi.org/10.1017/s0960129509990260.

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Modal and mixed transition systems are specification formalisms that allow the mixing of over- and under-approximation. We discuss three fundamental decision problems for such specifications: —whether a set of specifications has a common implementation;—whether an individual specification has an implementation; and—whether all implementations of an individual specification are implementations of another one. For each of these decision problems we investigate the worst-case computational complexity for the modal and mixed cases. We show that the first decision problem is EXPTIME-complete for both modal and mixed specifications. We prove that the second decision problem is EXPTIME-complete for mixed specifications (it is known to be trivial for modal ones). The third decision problem is also shown to be EXPTIME-complete for mixed specifications.

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Mackie, S. I., S. H. Begg, C. Smith, and M. B. Welsh. "DECISION TYPE—A KEY TO REALISING THE POTENTIAL OF DECISION MAKING UNDER UNCERTAINTY." APPEA Journal 47, no. 1 (2007): 309. http://dx.doi.org/10.1071/aj06022.

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Business underperformance in the upstream oil and gas industry, and the failure of many decisions to return expected results, has led to a growing interest over the past few years in understanding the impacts of decisionmaking tools and processes and their relationship to decision outcomes. A primary observation is that different decision types require different decision-making approaches to achieve optimal outcomes.Optimal decision making relies on understanding the types of decisions being made and tailoring the type of decision with the appropriate tools and processes. Yet the industry lacks both a definition of decision types and any guidelines as to what tools and processes should be used for what decisions types. We argue that maximising the chances of a good outcome in real-world decisions requires the implementation of such tailoring.

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Hsu, Clarissa, David T. Liss, Dominick L. Frosch, Emily O. Westbrook, and David Arterburn. "Exploring Provider Reactions to Decision Aid Distribution and Shared Decision Making." Medical Decision Making 37, no. 1 (October 7, 2016): 113–26. http://dx.doi.org/10.1177/0272989x16671933.

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Background. A critical component of shared decision making (SDM) is the role played by health care providers in distributing decision aids (DAs) and initiating SDM conversations. Existing literature indicates that decisions about designing and implementing DAs must take provider perspectives into account. However, little is known about how differences in provider attitudes across specialties may impact DA implementation and how provider attitudes may shift after DA implementation. Group Health’s Decision Aid Implementation project was carried out in six specialties using 12 video-based DAs for preference-sensitive conditions; this study focused on two of the six specialties. Design. In-depth, qualitative interviews with specialty care providers in two specialties—orthopedics and cardiology—at two time points during DA implementation. Data were analyzed using a thematic analysis approach. Results. We interviewed 19 care providers in orthopedics and cardiology. All respondents believed that providing patients with accurate information on their health conditions and treatment options was important and that most patients wanted an active role in decision making. However, respondents diverged in decision-making styles and views on the practicality and appropriateness of using the DAs and SDM. For example, cardiology specialists were ambivalent about DAs for coronary artery disease because many viewed DAs and SDM as unnecessary or inappropriate for this clinical condition. Provider attitudes towards DAs and SDM were generally stable over two years. Limitations. Limitations include a lack of patient perspectives, social desirability bias, and possible selection bias. Conclusions. Successfully implementing DAs in clinical practice to promote SDM requires addressing individual provider attitudes, beliefs, and knowledge of SDM by specialty. During DA development and implementation, providers should be asked for input about the specific conditions and care processes that are most appropriate for SDM.

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