Selecting Telecommunication Carriers to Obtain Volume Discounts

During 2001 many European markets for mobile phones reached saturation. Hence, mobile phone operators have shifted their focus from growth and market share to cutting costs. One way of doing so is to reduce spending on international calls, which are routed via network operating companies (carriers). These carriers charge per call-minute for each destination and may use a discount on total business volume to price their services. We developed a software system that supports decisions on allocating destinations to carriers. The core of this system is a min-cost flow routine that is embedded in a branch-and-bound framework. Our system solves the operational problem to optimality and performs what-if analyses and sensitivity analyses. A major telecommunication services provider implemented the system, realizing two benefits: it has structured the business process of allocating carriers to destinations and cut the costs of routing international calls

Exact algorithms for procurement problems under a total quantity discount structure.

In this paper, we study the procurement problem faced by a buyer who needs to purchase a variety of goods from suppliers applying a so-called total quantity discount policy. This policy implies that every supplier announces a number of volume intervals and that the volume interval in which the total amount ordered lies determines the discount. Moreover, the discounted prices apply to all goods bought from the supplier, not only to those goods exceeding the volume threshold. We refer to this cost-minimization problem as the TQD problem. We give a mathematical formulation for this problem and argue that not only it is NP-hard, but also that there exists no polynomial-time approximation algorithm with a constant ratio (unless P = NP). Apart from the basic form of the TQD problem, we describe three variants. In a first variant, the market share that one or more suppliers can obtain is constrained. Another variant allows the buyer to procure more goods than strictly needed, in order to reach a lower total cost. In a third variant, the number of winning suppliers is limited. We show that the TQD problem and its variants can be solved by solving a series of min-cost flow problems. Finally, we investigate the performance of three exact algorithms (min-cost flow based branch-and-bound, linear programming based branch-and-bound, and branch-and-cut) on randomly generated instances involving 50 suppliers and 100 goods. It turns out that even the large instances of the basic problem are solved to optimality within a limited amount of time. However, we find that different algorithms perform best in terms of computation time for different variants.Algorithms; Approximation; Branch-and-bound; Complexity; Cost; Exact algorithm; Intervals; Linear programming; Market; Min-cost flow; Order; Performance; Policy; Prices; Problems; Procurement; Reverse auction; Structure; Studies; Suppliers; Time; Volume discounts;

The Telecommunications Act of 1996: Predicting the Winners and Losers

The Telecommunications Act of 1996 has created substantial upheaval across the telecommunications landscape. On one hand, the 1996 Act created broad deregulatory and market entry opportunities for new market players; on the other hand, those implementing the Act have presumed that incumbent carriers will cooperate with new market entrants thereby accelerating the loss of market share, but gaining new market entry opportunities once competition begins to flourish. This Article analyzes the Various different factions that are likely to benefit from the Act, as well as those that are likely to suffer losses from telecommunications deregulation. The author concludes that the big future winners will be those who have exploited market entry opportunities or who successfully mitigate the financial consequences of market entry and heightened competition. The author also concludes that the future losers will be those enterprises that have exploited legal and regulatory barriers to competition, and have not adequately responded to changed circumstances and the prospects for new facilities-based and resale competition

ACUTA eNews March 1992, Vol. 21, No. 3

In This Issue OSP violators fined President\u27s column Non-dominant carriers face tariffs Resource Manager joins staf

Multi-period supplier selection under price uncertainty

Cataloged from PDF version of article.We consider a problem faced by a procurement manager who needs to purchase a large volume of multiple items over multiple periods from multiple suppliers that provide base prices and discounts. Discounts are contingent on meeting various conditions on total volume or spend, and some are tied to future realizations of random events that can be mutually verified. We formulate a scenario-based multi-stage stochastic optimization model that allows us to consider random events such as a drop in price because of the most favoured customer clauses, a price change in the spot market or a new discount offer. We propose certainty-equivalent heuristics and evaluate the regret of using them. We use our model for three bidding events of a large manufacturing company. The results show that considering most favored customer clauses in supplier offers may create substantial savings that may surpass the savings from regular discount offers

ACUTA eNews September 1993, Vol. 22, No. 9

In This Issue Emergency phones President\u27s message FCC opens up local loop CWRU cuts phone bill by 20% Staff repor

Customer Churn Prediction in Telecom Sector: A Survey and way a head

© 2021 International Journal of Scientific & Technology Research. This work is licensed under a Creative Commons Attribution 4.0 International License.The telecommunication (telecom)industry is a highly technological domain has rapidly developed over the previous decades as a result of the commercial success in mobile communication and the internet. Due to the strong competition in the telecom industry market, companies use a business strategy to better understand their customers’ needs and measure their satisfaction. This helps telecom companies to improve their retention power and reduces the probability to churn. Knowing the reasons behind customer churn and the use of Machine Learning (ML) approaches for analyzing customers' information can be of great value for churn management. This paper aims to study the importance of Customer Churn Prediction (CCP) and recent research in the field of CCP. Challenges and open issues that need further research and development to CCP in the telecom sector are exploredPeer reviewe