Decision-Support System for Integration of Transactional Systems and Analytical Models in the Pharmaceutical Industry

2016 ◽  
pp. 177-186
Author(s):  
Edrisi Muñoz ◽  
Elisabet Capón-García ◽  
José Miguel Laínez-Aguirre ◽  
Antonio Espuña ◽  
Luis Puigjaner
Keyword(s):  
Decision Support ◽  
Pharmaceutical Industry ◽  
Decision Support System ◽  
Support System ◽  
Analytical Models

INFORMATION ANALYSIS DECISION SUPPORT SYSTEM FOR STRATEGIC PLANNING OF REGIONAL AND URBAN DEVELOPMENT

2020 ◽  
Vol 1 (11) ◽  
pp. 55-66
Author(s):  
Angela A. Shvetsova ◽  
◽  
Anna V. Zviagintseva ◽  
Keyword(s):  
Decision Support ◽  
Strategic Planning ◽  
Decision Support System ◽  
Support System ◽  
Equations Of State ◽  
Analytical Models ◽  
Information Analysis ◽  
Practical Applications ◽  
Computing Platform ◽  
Computational Procedures

In practical applications, the tasks of strategic planning are complex and require many variant calculations when studying various scenarios, which are characterized by significant uncertainty in the forecast estimates. In this regard, the use of a complex of various means of information and analytical support for the activities of analysts and experts is relevant. Within the framework of this question, an information and analytical decision support system is proposed, focused on automating computational procedures in strategic planning. The system is organized on the basis of the Statistica computing platform and includes the platform's software tools, developed macros for describing and presenting statistical and analytical models, as well as decision support modules. The capabilities of the system are shown by specific examples of establishing patterns of development of Russian regions and cities in the real sector of the economy. The corresponding generalized models characterizing the state and development of regions by seven specific indicators in the period from 2012 to 2018 and by four specific indicators characterizing the development of cities in the period from 2003 to 2017 are obtained. It is established that the obtained models of collective behavior, presented in the form of equations of state, do not depend on time, but are determined only by the values of the achieved indicators. The proposed system allows you to increase the efficiency of the decisionmaking process, reduce the time and cost of developing strategic planning documents

scholarly journals Decision Support System Applications for Scheduling in Professional Team Sport. The Team's Perspective

2021 ◽  
Vol 3 ◽  
Author(s):  
Xavier Schelling ◽  
Jose Fernández ◽  
Patrick Ward ◽  
Javier Fernández ◽  
Sam Robertson
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Team Sports ◽  
Simulation Models ◽  
Process Efficiency ◽  
Analytical Models ◽  
Scheduling Problems ◽  
Practice Schedule ◽  
Professional Team Sports

Background: Periodization implies the systematic planning of training and competition with the goal of reaching the best possible performance in the most important competition. In team sports, this consists of finding a flight-and-practice schedule that maximizes the opportunities to perform the periodized contents (e.g., trips, practices, games, and days off). This process is conducted whilst considering known constraints (e.g., competitive schedule, roster availability, weather, especial events, holidays, or emotional effect of days away). The way a scheduling decision support system (DSS) leads users to make a decision should allow for flexibility, whilst minimizing users' confusion and facilitating the understanding of the recommendation given by the scheduling decision support system. Traditional approaches to solving scheduling problems use either simulation models, analytical models, heuristic approaches or a combination of these methods. When it comes to evaluate how the scheduling DSS is performing, three overarching aspects need to be reviewed: context satisfaction, process efficiency, and output quality. Appropriate training periodization and scheduling of trips and training sessions are critical for teams to optimize training and recovery processes in order to maximize health and performance. This article presents a methodological framework for designing decision-support systems for scheduling in professional team sports.

scholarly journals Support System of Solutions for Planning Sales Activities in the Tourism Industry

2019 ◽  
Vol 8 (6) ◽  
pp. 3979-3983
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Tourism Industry ◽  
Analytical Models ◽  
Similar Data ◽  
Managerial Accounting ◽  
Adaptive Planning ◽  
Marketing Planning ◽  
Operational Activities

The problems of creating methodologies and analytical models for decision support for planning and forecasting operational activities are compounded by the vast majority of tourism companies due to industry specifics and are currently not fully developed due to the current level of business planning, the traditional commitment of company management to administer and situational management, the prevalence of a retrospective approach to analysis over-promising, low quality and similar data of managerial accounting for the formation of a reliable operational "fact", as well as weak formalization and automation of the in-house process of financial and economic planning and forecasting based on information and analytical systems. The developed decision support system for marketing planning in the tourism industry and the supporting algorithm incorporates the functionality of sliding adaptive planning of daily revenue, which can significantly reduce the information gap between the strategic and operational levels of tourism company management and significantly improve the quality of the generally accepted process of budget marketing of sales. As a result, the decision support system not only takes into account the features of the typical process of corporate marketing planning but also allows you to design a system of dynamic planning and to forecast the marketing activities of a travel company with improved properties of efficiency, accuracy and adaptability.

Decision Support System Development Based On Android Using Analytical Hierarchy Process (AHP) Method For Determining The Middle Small Business Development Priority In Sorong City

2019 ◽  
Vol 5 (2) ◽  
pp. 25-39
Author(s):  
Luluk Suryani ◽  
Raditya Faisal Waliulu ◽  
Ery Murniyasih
Keyword(s):  
Decision Support ◽  
Small Business ◽  
Decision Support System ◽  
Support System ◽  
Analytical Hierarchy Process ◽  
System Development ◽  
Business Development ◽  
Ahp Method ◽  
Small Business Development ◽  
Hierarchy Process

Usaha Kecil Menengah (UKM) adalah salah satu penggerak perekonomian suatu daerah, termasuk Kota Sorong. UKM di Kota Sorong belum berkembang secara optimal. Ada beberapa penyebab diantaranya adalah mengenai finansial, lokasi, bahan baku dan lain-lain. Untuk menyelesaikan permasalah tersebut peneliti terdorong untuk melakukan pengembangan Aplikasi yang dapat membantu menentukan prioritas UKM yang sesuai dengan kondisi pelaku usaha. Pada penelitian ini akan digunakan metode Analitycal Hierarchy Process (AHP), untuk pengambilan keputusannya. Metode AHP dipilih karena mampu menyeleksi dan menentukan alternatif terbaik dari sejumlah alternatif yang tersedia. Dalam hal ini alternatif yang dimaksudkan yaitu UKM terbaik yang dapat dipilih oleh pelaku usaha sesuai dengan kriteria yang telah ditentukan. Penelitian dilakukan dengan mencari nilai bobot untuk setiap atribut, kemudian dilakukan proses perankingan yang akan menentukan alternatif yang optimal, yaitu UKM. Aplikasi Sistem Pendukung Keputusan yang dikembangkan berbasis Android, dimana pengguna akan mudah menggunakannya sewaktu-waktu jika terjadi perubahan bobot pada kriteria atau intensitas.  Hasil akhir menunjukkan bahwa metode AHP berhasil diterapkan pada Aplikasi Penentuan Prioritas Pengembangan UKM.

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