Water pricing in Tunisia: Can an original rate structure achieve multiple objectives?

In the context of anthropic pressures, the Tunisian Water Utility tries to achieve three objectives: financial (achieving full-cost recovery), social (ensuring access for all), and environmental (incentivizing users to save a scarce resource). After a theoretical review of water pricing, the paper presents how successive reforms in Tunisia have gradually set up an original pricing structure that has become the main instrument of the sector's policy. Using different data and methods, we investigate how each of the three objectives is reached through pricing. We conclude that this pricing policy has led to a relatively stable but partial equilibrium.     

Cryptocurrency value formation: An empirical study leading to a cost of production model for valuing bitcoin

This paper aims to identify the likely determinants for cryptocurrency value formation, including for that of bitcoin. Due to Bitcoin’s growing popular appeal and merchant acceptance, it has become increasingly important to try to understand the factors that influence its value formation. Presently, the value of all bitcoins in existence represent approximately $7 billion, and more than $60 million of notional value changes hands each day. Having grown rapidly over the past few years, there is now a developing but vibrant marketplace for bitcoin, and a recognition of digital currencies as an emerging asset class. Not only is there a listed and over-the-counter market for bitcoin and other digital currencies, but also an emergent derivatives market. As such, the ability to value bitcoin and related cryptocurrencies is becoming critical to its establishment as a legitimate financial asset.Using cross-sectional empirical data examining 66 of the most widely used cryptocurrencies, a regression model was estimated that points to three main drivers of cryptocurrency value: the level of competition in the network of producers, the rate of unit production, and the difficulty of algorithm used to “mine” for the cryptocurrency. These amount to relative differences in the cost of production of one digital currency over another at the margin, pointing to differences in relative cost of production – electricity goes in, cryptocurrency comes out. Using that as a starting point, a no-arbitrage situation is established for Bitcoin-like cryptocurrencies followed by the formalization of a cost of production model to determine the fair value of a bitcoin.     

Multi-coefficients goal programming

In today’s increasingly competitive business environment, maintaining profit margins or quantities of goods sold is an important issue for businesses. Accordingly, more and more industries use group pricing discrimination strategy to attract potential customers in order to increase competitive advantage. Hence, to find ways maximize profit and to minimize total cost, group pricing discrimination strategy has become an important issue for decision makers. Unfortunately, these types of problems cannot be solved by any current goal programming models. The objective of this study is to deduce a new method, which we call the multi-coefficients goal programming, for group pricing discrimination problems. In addition, an example is given to illustrate the correctness and usefulness of the proposed model.     

Assessing the rebound effect using a natural experiment setting: Evidence from the private transportation sector in Israel

Subsidizing energy-efficient technologies is considered by energy and environmental organizations to be one of the most effective policies for decreasing energy consumption. In the transportation sector such policies are becoming ever more popular, and have been implemented in a considerable number of countries in recent years. Because these policies promote energy-efficient cars with lower usage costs, they may rebound and increase the distances traveled by households that have switched to energy-efficient cars. From an econometric perspective, a subsidization policy can be used as a valid instrument to identify the households’ choice of energy efficiency levels of the cars they own. This identification, in turn, can be utilized to account for endogeneity in the estimation of a rebound effect. The present study uses a natural experiment setting of such a policy implemented in Israel in 2009. The empirical results indicate a fairly large average rebound effect of 40%. The results also indicate that while the policy indeed encouraged the purchase of energy-efficient cars, households that bought a new or used car during the surveyed period did not generate a rebound effect of a different magnitude compared with other households that did not. We discuss the implications of our findings.     

Joint optimisation of tracking capability and price in a supply chain with endogenous pricing

Tracking systems have been widely used to resolve the issues of product recall and food safety. Thus far, few researches have been done on designing the tracking capability from the perspective of supply chain. In this paper, using the traceable unit size at the manufacturer level to measure the tracking capability, we propose a non-convex non-linear programming to jointly optimise the tracking capability and price considering the tracking cost and recall cost in a supply chain with endogenous pricing. Results show that, in both centralised and decentralised supply chains, there is a unique tracking capability and retailing/wholesale price with closed-form solutions to optimise the supply chain profit. When the cost ratio (unit tracking cost/unit recall cost) is sufficiently large and small, the optimal tracking strategy is barcode tracking and unit tracking, respectively, and otherwise, the optimal tracking strategy is batch tracking with an economic traceable unit size which depends on the cost ratio, quality inspection threshold, supply defection rate and the supplier’s tracking capability. Furthermore, in the context of large and small cost ratio, we find that improving tracking capability will enlarge and mitigate the effect of double marginalisation, respectively. In particular, we find that the strict tracking regulation policy is more robust than the subsidy policy to improve the supply chain tracking capability.     

摇珠法在工程招投标过程中的报价分析

按照综合评估法中摇珠法的运作原则对投标竞争环境进行了分析,利用概率统计的方法研究并得出了各个不同级别的投标单位的最佳投标报价策略,以期为相关单位的竞标提供一些参考。     

英国输电过网费定价机制分析

输电定价是电力市场中的关键环节,也是我国当前电力市场改革的重要任务。对英国的输电过网费形成机制进行了深入的研究。对相关的模型进行了介绍,对过网费的组成、过网费在发电机和负荷之间的分摊、参考节点的选择及修正常数的影响等问题进行了深入的分析。利用IEEE 14节点标准系统算例对参考节点的选取问题进行了分析,利用7节点算例对英国输电过网费定价机制引导发电机和负荷投资的有效性进行了分析。英国输电过网费的定价机制可以为发电和用户投资提供较好的经济信息,且分区定价方法灵活,可为我国输配电定价提供借鉴。     

OFDMA认知无线电网络中面向需求的频谱共享

从满足次网络通信需求的角度,设计一个两阶段模型,求解OFDMA 认知无线电网络中频谱租赁与分配问题。模型第1阶段,次基站收集次网络通信需求,向多个主基站租用频谱资源。运用Bertrand博弈对主、次基站的交易行为进行建模,并将纳什均衡作为最终定价方案。第2阶段,基于纳什议价方案,将次基站子载波和功率分配问题定义成非线性规划问题,并通过拉格朗日乘数法进行求解。仿真实验表明,相对于其他频谱共享方案,所提方案高效地满足每个次用户的通信需求。     

5G网络中DR-OC型D2D通信收益模型及定价研究

Device-to-Device(D2D)通信是下一代(5G)移动网络的重要组成部分。D2D设备间在不依赖基站的情况下直接进行数据传输,并通过重复使用蜂窝小区的频率资源从而提高移动通信系统的容量。为了激励蜂窝网络用户参与到D2D通信,运营商对D2D通信的定价是一个很关键的问题。文中首先介绍了D2D的基本概念及其四种主要类型,并就其中DR-OC型D2D通信定价提出了运营商和D2D设备的收益模型,然后仿真分析了网络中谱单价和奖励带宽对双方收益的影响。仿真结果显示运营商可以通过调整奖励带宽来协调双方收益以激励更多的用户参与到D2D通信。     

Rational under‐pricing in bidding strategy: a real options model

Under‐pricing in construction tenders is a common phenomenon and is commonly explained by the need of cash flows and penetration strategy. However, these explanations involve profit cutting and therefore are not plausible in explaining a long‐term persistent phenomenon of under‐pricing. A real options model is proposed and using the binomial lattice method a real‐life construction project tender was analysed to examine how management flexibility and uncertainty provide real options value. When uncertainties of cost items in a tender exist and choices are available to defer and switch modes of construction, then a valuable option is available to the bidders. It amounts to about 4% of the lump sum tendered in our case. The under‐priced portion is the options value which the bidder is willing to pay for the flexibility and the uncertainty. These findings enable contractors to be more competitive and to estimate construction costs more accurately in devising their bid strategies.