Pricing and capacity allocation for shared services

We study the pricing and capacity allocation problem of a service provider who serves two distinct customer classes. Customers within each class are inherently heterogeneous in their willingness to pay for service, but their utilities are also affected by the presence of other customers in the system. Specifically, customer utilities depend on how many customers are in the system at the time of service as well as who these other customers are. We find that if the service provider can price discriminate between customer classes, pricing out a class, i.e., operating an exclusive system, can sometimes be optimal and that depends only on classes’ perceptions of each other. If the provider must charge a single price, an exclusive system is even more likely. We extend our analysis to a service provider who can prevent class interaction by allocating separate capacity segments to the two customer classes. Under price discrimination, allocating capacity is optimal if the “net appreciation” between classes, as defined in the paper, is negative. However, under a single–price policy, allocating capacity can be optimal even if this net appreciation is positive. We describe in detail how the nature of asymmetry in classes’ perception of each other determines the optimal strategy

Analyzing the Financial Relationship between Railway Industry Players in Shared Railway Systems: The Train Operator’s Perspective

Capacity pricing and allocation play an important role in efficient management of railway corridors, especially shared ones. This paper analyzes how Train Operators (TOs) would respond to different track-access charges, as a first step to understand the relationship between Train Operators and Infrastructure Manger (IM) in railway systems with some level of vertical separation. By modeling a corridor whose users are long-distance high-speed trains and freight trains along the entire corridor, and commuter trains offering services around large urban areas in the corridor, this paper narrows down the focus on each individual operator, looking at the factors that drive each operator's ultimate service levels. Assuming an environment where the TOs are competing for capacity, financial goals and boundary conditions of each TO are derived, and a number of sensitivity analyses for various typical and extreme conditions are performed. This model allows to anticipate how TOs would respond to track-access charges, and can thus help the government, the regulators, and the IMs in the design of appropriate capacity pricing and allocation schemes

Persediaan kerjaya pelajar tahun akhir diploma akauntansi Politeknik dalam melahirkan K-Workes : satu tinjauan

This research was conducted to identify Polytechnic's Diploma in Accountancy final year students' career preparation before enter the working environment to be k-workers. The sample in this study consisted of 48 final year students of Diploma in Accountancy Politeknik Sultan Haji Ahmad Shah (POLISAS), Kuantan. Questionnaire has been chosen as an instrument to get the data. The data was analyzed by using the Statistical Package For Social Sciences (SPSS) package to derive the percentages and mean. The results revealed the Diploma of Accountancy final year students are quite prepared to enter the working environment. Although the students performed very well for their career preparation, there are still dissatisfaction in other two aspects i.e. they lack of information career opportunity and communication in English. Therefore, the career guideline have been proposed to give an exposure for the students to be k-workers in their career in the future

ERA: A Framework for Economic Resource Allocation for the Cloud

Cloud computing has reached significant maturity from a systems perspective, but currently deployed solutions rely on rather basic economics mechanisms that yield suboptimal allocation of the costly hardware resources. In this paper we present Economic Resource Allocation (ERA), a complete framework for scheduling and pricing cloud resources, aimed at increasing the efficiency of cloud resources usage by allocating resources according to economic principles. The ERA architecture carefully abstracts the underlying cloud infrastructure, enabling the development of scheduling and pricing algorithms independently of the concrete lower-level cloud infrastructure and independently of its concerns. Specifically, ERA is designed as a flexible layer that can sit on top of any cloud system and interfaces with both the cloud resource manager and with the users who reserve resources to run their jobs. The jobs are scheduled based on prices that are dynamically calculated according to the predicted demand. Additionally, ERA provides a key internal API to pluggable algorithmic modules that include scheduling, pricing and demand prediction. We provide a proof-of-concept software and demonstrate the effectiveness of the architecture by testing ERA over both public and private cloud systems -- Azure Batch of Microsoft and Hadoop/YARN. A broader intent of our work is to foster collaborations between economics and system communities. To that end, we have developed a simulation platform via which economics and system experts can test their algorithmic implementations

Trade & Cap: A Customer-Managed, Market-Based System for Trading Bandwidth Allowances at a Shared Link

We propose Trade & Cap (T&C), an economics-inspired mechanism that incentivizes users to voluntarily coordinate their consumption of the bandwidth of a shared resource (e.g., a DSLAM link) so as to converge on what they perceive to be an equitable allocation, while ensuring efficient resource utilization. Under T&C, rather than acting as an arbiter, an Internet Service Provider (ISP) acts as an enforcer of what the community of rational users sharing the resource decides is a fair allocation of that resource. Our T&C mechanism proceeds in two phases. In the first, software agents acting on behalf of users engage in a strategic trading game in which each user agent selfishly chooses bandwidth slots to reserve in support of primary, interactive network usage activities. In the second phase, each user is allowed to acquire additional bandwidth slots in support of presumed open-ended need for fluid bandwidth, catering to secondary applications. The acquisition of this fluid bandwidth is subject to the remaining "buying power" of each user and by prevalent "market prices" – both of which are determined by the results of the trading phase and a desirable aggregate cap on link utilization. We present analytical results that establish the underpinnings of our T&C mechanism, including game-theoretic results pertaining to the trading phase, and pricing of fluid bandwidth allocation pertaining to the capping phase. Using real network traces, we present extensive experimental results that demonstrate the benefits of our scheme, which we also show to be practical by highlighting the salient features of an efficient implementation architecture.National Science Foundation (CCF-0820138, CSR-0720604, EFRI-0735974, CNS-0524477, and CNS-0520166); Universidad Pontificia Bolivariana and COLCIENCIAS–Instituto Colombiano para el Desarrollo de la Ciencia y la Tecnología “Francisco Jose ́ de Caldas”

A stochastic user-operator assignment game for microtransit service evaluation: A case study of Kussbus in Luxembourg

This paper proposes a stochastic variant of the stable matching model from Rasulkhani and Chow [1] which allows microtransit operators to evaluate their operation policy and resource allocations. The proposed model takes into account the stochastic nature of users' travel utility perception, resulting in a probabilistic stable operation cost allocation outcome to design ticket price and ridership forecasting. We applied the model for the operation policy evaluation of a microtransit service in Luxembourg and its border area. The methodology for the model parameters estimation and calibration is developed. The results provide useful insights for the operator and the government to improve the ridership of the service.Comment: arXiv admin note: substantial text overlap with arXiv:1912.0198