scholarly journals Enterprise Resource Planning And Its Future Relationship To Decision Support System

2011 ◽  
Vol 4 (12) ◽  
Author(s):  
Mohammad Shariat ◽  
Hudson Nwakanma
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Enterprise Resource Planning ◽  
Data Warehousing ◽  
Resource Planning ◽  
Font Size ◽  
Transfer Of Skills ◽  
The Future ◽  
Two Sides

<p class="ForMoreInfoHeader" style="text-align: justify; margin: 0in 34.2pt 0pt 0.5in;"><span style="font-style: normal; font-size: 10pt;" lang="EN-GB"><span style="font-family: Times New Roman;">This paper looks at the development of ERP and DSS, with a focus on the differences between the two systems in terms of their evolution and applications and the potential for convergence in the future. For the most part, ERP and DSS have evolved in parallel, and as a result those organizations, which have already implemented ERP, are now having problems integrating DSS and data warehousing into their system. ERP vendors hold the opinion that it is comparatively simple to add on DDS applications, but this tends to be contradicted by the fact that most ERP specialists are not experienced in DSS or in data warehousing. Software analysts from both sides of the industry agree that convergence is inevitable, but differ in their views as to how this should be achieved. It would seem that a greater degree of collaboration, and the transfer of skills between the two sides, is the most practical option, coupled with a case-by-case approach to the requirements of individual customers rather than trying to find blanket solutions. </span></span></p>

scholarly journals A Sensor Data-Driven Decision Support System for Liquefied Petroleum Gas Suppliers

2021 ◽  
Vol 11 (8) ◽  
pp. 3474
Author(s):  
Michał Kozielski ◽  
Joanna Henzel ◽  
Łukasz Wróbel ◽  
Zbigniew Łaskarzewski ◽  
Marek Sikora
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Enterprise Resource Planning ◽  
Resource Planning ◽  
Sensor Data ◽  
Liquefied Petroleum Gas ◽  
Sensory Data ◽  
Demand Prediction

Currently, efficiency in the supply domain and the ability to make quick and accurate decisions and to assess risk properly play a crucial role. The role of a decision support system (DSS) is to support the decision-making process in the enterprise, and for this, it is yet not enough to have up-to-date data; reliable predictions are necessary. Each application area has its own specificity, and so far, no dedicated DSS for liquefied petroleum gas (LPG) supply has been presented. This study presents a decision support system dedicated to support the LPG supply process from the perspective of gas demand analysis. This perspective includes a short- and medium-term gas demand prediction, as well as the definition and monitoring of key performance indicators. The analysis performed within the system is based exclusively on the collected sensory data; no data from any external enterprise resource planning (ERP) systems are used. Examples of forecasts and KPIs presented in the study show what kind of analysis can be implemented in the proposed system and prove its usefulness. This study, showing the overall workflow and the results for the use cases, which outperform the typical trivial approaches, could be a valuable direction for future works in the field of LPG and other fuel supply.

scholarly journals Sistem Pendukung Keputusan Rekomendasi Emiten Saham Menggunakan Metode Simple Additive Weighting

2021 ◽  
Vol 2 (3) ◽  
pp. 321
Author(s):  
Renny Puspita Sari ◽  
Muhamad Rabil Maulana
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Decision Makers ◽  
Financial Ratios ◽  
Weighting Method ◽  
Stock Recommendations ◽  
The Future ◽  
Simple Additive Weighting ◽  
The Many

In the current era, stock investing is an instrument that is currently popular with Indonesian youth, stock investing is one of the many investment options that are increasingly in demand by various groups. Investing in stocks is an activity to refrain from enjoying the present for more enjoyment in the future, this investment often brings someone to be wiser in managing their finances, choosing good stocks is not an easy thing for some investors it takes many factors and ratios - financial ratios to choose stocks that can provide financing by the initial investment objectives. Therefore we need a system to help these problems. The system is a decision support system that can assist in making decisions from the available options. This Stock Issuer Recommendation Decision Support System Using the Simple Additive Weighting Method is here to assist decision-makers to choose good issuers or stocks to collect so that they can provide good profits in the future. The results of the calculation on the system using the Simple Additive Weighting method will show the best suitable stock recommendations for the user based on the data they enter.

Construction and resource short-term planning using a BIM-based ontological decision support system

2021 ◽  
Vol 48 (1) ◽  
pp. 75-88
Author(s):  
Mehdi Tavakolan ◽  
Sina Mohammadi ◽  
Banafsheh Zahraie
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Construction Projects ◽  
Planning Process ◽  
Resource Planning ◽  
Project Planning ◽  
Short Term ◽  
Planning And Control ◽  
Intelligent Information

The dynamic nature and increasing complexity of the construction projects impose many challenges for project planning and control. As a project progresses, more information becomes available and the level of uncertainty decreases. It can be used to proactively check the validity of the previous decisions and develop revised and more detailed plans for the upcoming activities in construction planning meetings. For this purpose, this study implements ontological knowledge representation and semantic reasoning techniques to propose an intelligent information collection and decision support system framework for short-term collaborative construction and resource planning. Moreover, a new approach is suggested that allows for incorporating resource specifications and limitations, and complex multi-factor constraints in the ontological planning process. The framework was tested based on a real-world construction project and different application cases were discussed. The framework showed a promising performance for analyzing different scenarios and help the planners making informative decisions.

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