Electronic Reverse Auctions: Spawning Procurement Innovation in the Context of Arab Culture

Government e-procurement initiatives have the potential to transform local institutions, but few studies have been published of strategies for implementing specific e-procurement tools, particularly involving procurement by a foreign government adapting to local culture in the Middle East/North Africa (MENA). This case describes procurement at a forward operating base (FOB) in Kuwait in support of operations in Iraq. The government procurers had to deal with a phenomenon unique to the MENA region: wasta. Wasta is a form of social capital that bestows power, influence, and connection to those who possess it, similar to guanxi in China. This study explores the value proposition and limitations of electronic reverse auctions (eRA) with the purpose of sharing best practices and lessons learned for government procurement in a MENA country. The public value framework provides valuable theoretical insights for the implementation of a new government e-procurement tool in a foreign country. In a culture dominated by wasta, the suppliers enjoyed the transparency and merit-based virtues of eRA’s that transferred successfully into the new cultural milieu: potential to increase transparency, competition, efficiency, and taxpayer savings. The practices provided herein are designed specifically to help buyers overcome structural barriers including training, organizational inertia, and a lack of eRA policy and guidance while implementing a new e-procurement tool in a foreign country

Agent-Based Computational Economics: A Constructive Approach to Economic Theory

This chapter explores the potential advantages and disadvantages of Agent-based Computational Economics (ACE) for the study of economic systems. General points are concretely illustrated using an ACE model of a two-sector decentralized market economy. Six issues are highlighted: Constructive understanding of production, pricing, and trade processes; the essential primacy of survival; strategic rivalry and market power; behavioral uncertainty and learning; the role of conventions and organizations; and the complex interactions among structural attributes, behaviors, and institutional arrangements. Extensive annotated pointers to ACE surveys, research, course materials, and software can be accessed here: http://www.econ.iastate.edu/tesfatsi/ace.htmagent-based computational economics; Learning; network formation; decentralized market economy

A Novel Intelligence-based e-Procurement System to offer Maximum Fairness Index in Ongoing Auction Process

A perfect auction policy is one of the most strategic elements that contribute to success factor for any e-Procurement system. An auction policy can be only term as an effective if it really offer win-win situation to both the bidder as well as to the merchant. After reviewing existing studies on e-Procurement system, it is found that there isno effective research work focusing on this point and maximum research contribution has limited its scope to certain application or case studis. Hence, the proposed system introduces a novel e-Procurement system which is equipped by an itelligence-building process for performing predictive analysis of ongoing auction process. A mathematical modelling is implemented where all teh variables have been formed using practical implementation of auction system and followed by optimization process using regression-based approach. The study outcome shows that proposed system offers better response time and higher predictive accuracy in contrast to existing approaches

Integration of Blockchain and Auction Models: A Survey, Some Applications, and Challenges

In recent years, blockchain has gained widespread attention as an emerging technology for decentralization, transparency, and immutability in advancing online activities over public networks. As an essential market process, auctions have been well studied and applied in many business fields due to their efficiency and contributions to fair trade. Complementary features between blockchain and auction models trigger a great potential for research and innovation. On the one hand, the decentralized nature of blockchain can provide a trustworthy, secure, and cost-effective mechanism to manage the auction process; on the other hand, auction models can be utilized to design incentive and consensus protocols in blockchain architectures. These opportunities have attracted enormous research and innovation activities in both academia and industry; however, there is a lack of an in-depth review of existing solutions and achievements. In this paper, we conduct a comprehensive state-of-the-art survey of these two research topics. We review the existing solutions for integrating blockchain and auction models, with some application-oriented taxonomies generated. Additionally, we highlight some open research challenges and future directions towards integrated blockchain-auction models

Which instruments to preserve forest biodiversity?

In general, neither the social norms nor market dynamics stimulate spontaneously activities and practices conducive to biodiversity. The nature of public good of biodiversity leads to its rapid erosion. Even if it can respond positively to social expectations and improve welfare in the long term2, taking into account biodiversity often leads to changes in the way we produce or how to exercise its property right. The consideration of biodiversity may determine production losses and income decreases.[...]

Reverse Auction in Pricing Model

Dynamic price discrimination adjusts prices based on the option value of future sales, which varies with time and units available. This paper surveys the theoretical literature on dynamic price discrimination, and confronts the theories with new data from airline pricing behavior, Consider a multiple booking class airline-seat inventory control problem that relates to either a single flight leg or to multiple flight legs. During the time before the flight, the airline may face the problems of (1) what are the suitable prices for the opened booking classes, and (2) when to close those opened booking classes. This work deals with these two problems by only using the pricing policy. In this paper, a dynamic pricing model is developed in which the demand for tickets is modeled as a discrete time stochastic process. An important result of this work is that the strategy for the ticket booking policy can be reduced to sets of critical decision periods, which eliminates the need for large amounts of data storage