scholarly journals Business Analytics using Dynamic Pricing based on Customer Entry-Exit Rates Tradeoff

2020 ◽  
Vol 8 (1) ◽  
pp. 272-280
Author(s):  
Hamed Fazlollahtabar ◽  
Minoo Talebi Ashoori

This paper concerns with an integrated business process to be applied as a decision support for market analysis and decision making. The proposed business intelligence and analytics system makes use of an extract, transform and load mechanism for data collection and purification. As a mathematical decision optimization, dynamic pricing is formulated based on customer entry-exit rates in a history-based pricing model. The optimal prices for products are obtained so that aggregated profit is maximized. A case study is reported to show the effectiveness of the approach. Also, analytical investigations on the impacts of the sensitive parameters of the pricing model are given.

Author(s):  
Shah J. Miah

The Australian farm-based businesses can be benefited from specially designed applications for cost-effective operation while maximizing profits to survive in economic and environmental crises. For decision support, existing business intelligence systems (BIS) approaches scarcely deal with specific user's provisions to adjust changing situations in decision making, without extra technical exertions. In this chapter, the authors describe a conceptual framework of tailorable BIS solution that is based on case study findings in that the highlighted requirements are relevant to address changing situations through enhancing end user's engagement. The activities of end user's engagement supported through the use of tailorable features that reinforce a shift from the traditional BIS process to a new provision where business owners can actively involve in adjusting their features to their decision support.


Author(s):  
Shah J. Miah

The Australian farm-based businesses can be benefited from specially designed applications for cost-effective operation while maximizing profits to survive in economic and environmental crises. For decision support, existing business intelligence systems (BIS) approaches scarcely deal with specific user's provisions to adjust changing situations in decision making, without extra technical exertions. In this chapter, the authors describe a conceptual framework of tailorable BIS solution that is based on case study findings in that the highlighted requirements are relevant to address changing situations through enhancing end user's engagement. The activities of end user's engagement supported through the use of tailorable features that reinforce a shift from the traditional BIS process to a new provision where business owners can actively involve in adjusting their features to their decision support.


Author(s):  
Shah J. Miah

The Australian farm-based businesses can be benefited from specially designed applications for cost-effective operation while maximizing profits to survive in economic and environmental crises. For decision support, existing business intelligence systems (BIS) approaches scarcely deal with specific user's provisions to adjust changing situations in decision making, without extra technical exertions. In this chapter, the authors describe a conceptual framework of tailorable BIS solution that is based on case study findings in that the highlighted requirements are relevant to address changing situations through enhancing end user's engagement. The activities of end user's engagement supported through the use of tailorable features that reinforce a shift from the traditional BIS process to a new provision where business owners can actively involve in adjusting their features to their decision support.


2017 ◽  
Vol 9 (2) ◽  
Author(s):  
Sekar Sari Wiradarma ◽  
Ken Dhita Tania ◽  
Dinna Yunika Hardiyanti

AbstractBusiness Intelligence (BI) is a collection of theories, methodologies, processes, architectures, and technologies that convert raw data into quality information for business purposes. BI can handle a large amount of information that can help in identifying problems and developing new opportunities. In designing and implementing Business Intelligence (BI) concept for monitoring banking product service using reference business intelligence roadmap approach. Business intelligence roadmap is one example of BI development that can be emulated because of its agile and adaptive nature and is intended to support the development of BI. By utilizing Business Intelligence application on transaction history of banking product data, it is hoped able to produce information that can support in giving recommendation and decision making appropriately. The data and information generated also become more accessible and easier to understand (user friendly).Keywords: business intelligence, business intelligence roadmap, OLAP, banking products


Author(s):  
Jean-Fabrice Lebraty ◽  
Cécile Godé

This article explores the ability of a decision support system (DSS) to improve the quality of decision making in extreme environment. This DSS is actually based on a networked information system. Academic literature commonly mentions models of fit to explore the relationship between technology and performance, reckoning users' evaluations as a relevant measurement technique for Information System (IS) success. Although effective contributions have been achieved in measurement and exploration of fit, there have been few attempts to investigate the triangulation of fit between “Task-DSS-Decision Maker” under stressful and uncertain circumstances. This article provides new insights regarding the advantages provided by networked IS for making relevant decisions. An original case study has been conducted. It is focused on a networked decision support system called Link 16 that is used during aerial missions. This case study shows that the system improves decision making on an individual basis. Our result suggest the importance of three main fit criteria – Compliance, Complementarity and Conformity – to measure DSS performance under extreme environment and display a preliminary decisional fit model.


Data Mining ◽  
2013 ◽  
pp. 550-566 ◽  
Author(s):  
Zaidoun Alzoabi ◽  
Faek Diko ◽  
Saiid Hanna

BI is playing a major role in achieving competitive advantage in almost every sector of the market, and the higher education sector is no exception. Universities, in general, maintain huge databases comprising data of students, human resources, researches, facilities, and others. Data in these databases may contain decisive information for decision making. In this chapter we will describe a data mining approach as one of the business intelligence methodologies for possible use in higher education. The importance of the model arises from the reality that it starts from a system approach to university management, looking at the university as input, processing, output, and feedback, and then applies different business intelligence tools and methods to every part of the system in order to enhance the business decision making process. The chapter also shows an application of the suggested model on a real case study at the Arab International University.


Author(s):  
Tanushri Banerjee ◽  
Arindam Banerjee

There are several challenges faced by decision makers while deploying Business Analytics in their organization. There may not be one resolution approach that is suitable for creating a Business Analytics culture in all organizations. However, it is easy to perceive that most India-based organizations may have similar issues of data organization that may be impeding their progression in the field of Analytics. Based on their research, the authors have proposed a framework for adoption of Analytics in Indian firms in their book “Weaving Analytics for Effective Decision Making” by SAGE. They propose to use that model for explaining certain domain specific adoption of Business Analytics in organizations in India. They have used a case study of a Global Bank which is in the process of establishing its consumer lending USA operations, an offshore captive operation, in India to describe the process of building an Analytics team in an organization in India. Data processed using R has been added as screenshots for supporting the findings.


Author(s):  
Alberto Turón ◽  
Juan Aguarón ◽  
María Teresa Escobar ◽  
José María Moreno-Jiménez

The Precise Consistency Consensus Matrix (PCCM) is a decisional tool for AHP-Group Decision Making (AHP-GDM). Based on the initial pairwise comparison matrices of the individuals, the PCCM constructs a consensus matrix for the group using the concept of consistency. This paper presents a decision support system (PRIOR-PCCM) that facilitates the construction of the PCCM in the context of AHP-GDM, and the calculus of four indicators that allows comparison of the behaviour of group consensus matrices. PRIOR-PCCM incorporates the possibility of considering different weights for the decision makers and includes a module that permits the extension of the initial PCCM which can achieve the minimum number of non-null entries required for deriving priorities or establishing a complete PCCM matrix. It also includes two cardinal indicators for measuring consistency and compatibility and two ordinal indicators for evaluating the number of violations of consistency and priority. The paper introduces some new visualisation tools that improve comprehension of the process followed for obtaining the PCCM matrix and allow the cognitive exploitation of the results. These original contributions are illustrated with a case study.


Author(s):  
Frédéric Adam ◽  
Jean-Charles Pomerol ◽  
Patrick Brézillon

In this article, a newspaper company which has implemented a computerised editorial system is studied in an attempt to understand the impact that groupware systems can have on the decision making processes of an organisation. First, the case study protocol is presented, and the findings of the case are described in detail. Conclusions are then presented which pertain both to this case and to the implementation of decision support systems that have a groupware dimension.


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