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

From commercial travellers to sales representatives: the evolution of the sales profession in Britain, 1930s to 1960s

In analysing the development of modern marketing, business historians have focused on the late nineteenth and early twentieth centuries in the United States and Europe. This paper reviews the debates about the sources and timing of key changes in relation to the role of commercial travellers or travelling salesmen in Britain. It explores the later evolution from the 1930s to the 1960s with the transition to sales representatives, highlighting the gradual process of change and the hesitant, often negative, attitudes of managers and salesmen towards new ways of working

Revenue Management and Demand Fulfillment: Matching Applications, Models, and Software

Recent years have seen great successes of revenue management, notably in the airline, hotel, and car rental business. Currently, an increasing number of industries, including manufacturers and retailers, are exploring ways to adopt similar concepts. Software companies are taking an active role in promoting the broadening range of applications. Also technological advances, including smart shelves and radio frequency identification (RFID), are removing many of the barriers to extended revenue management. The rapid developments in Supply Chain Planning and Revenue Management software solutions, scientific models, and industry applications have created a complex picture, which appears not yet to be well understood. It is not evident which scientific models fit which industry applications and which aspects are still missing. The relation between available software solutions and applications as well as scientific models appears equally unclear. The goal of this paper is to help overcome this confusion. To this end, we structure and review three dimensions, namely applications, models, and software. Subsequently, we relate these dimensions to each other and highlight commonalities and discrepancies. This comparison also provides a basis for identifying future research needs.Manufacturing;Revenue Management;Software;Advanced Planning Systems;Demand Fulfillment

The effects of the lack of coordination within the supply chain

The present article refers to the bullwhip effect that negatively influences the supply chain performance. This effect is experienced by various industries, from fast moving consumer goods to IT products. The consequences for the supply chain members are the following: increased costs, lower profitability, longer lead times and lower product availability. The main factors that generate this effect are the types of incentives provided by suppliers to the downstream customers, the information distortion, the order placing practices, the pricing policies encouraging the forward buying and the specific behavior of the supply chain members focused on local optimization. The only way in which supply chain members may eradicate the bullwhip effect is to enhance coordination among the subsequent stages. Some of the strategies to be considered are the alignment of goals and objectives, data sharing among members, single stage control of replenishment, strategies for the improvement of the operational performance, stabilizing orders with appropriate pricing strategies and building strategic partnerships and trust. The incidence and amplitude of the bullwhip effect may be reduced by strategies and decisions that are harmonized along the stages of the supply chain. The key words in the endeavor to diminish the bullwhip effect are cooperation, coordination, communication and trust.bullwhip effect, logistics, supply chain, coordination, information distortion

Lost in Translation: Interpreting the Brazilian Electric Power Privatisation Failure.

Did Latin American privatisation polices fail because of flawed implementation of fundamentally sound policies or because privatisation policies were themselves seriously flawed?Using the Brazilian electric power reforms as a narrative tool, this paper examines the causal chain assumed by large-scale privatisation policies implemented as part of structural reformand adjustment programmes. The paper concludes that many privatisation policies and the economic stabilisation programmes within which they were embedded were not mutually reinforcingas policymakers had expected and that in their application, much of what privatisation theories claimed was lost in translation.Brazil;privatisation;infrastructure;electric power

Modeling customer bounded rationality in operations management: A review and research opportunities

Many studies in operations management started to explicitly model customer behavior. However, it is typically assumed that customers are fully rational decision-makers and maximize their utility perfectly. Recently, modeling customer bounded rationality has been gaining increasing attention and interest. This paper summarizes various approaches of modeling customer bounded rationality, surveys how they are applied to relevant operations management settings, and presents the new insights obtained. We also suggest future research opportunities in this important area

Markdowns in Seasonal Conspicuous Goods

In common parlance, luxury and markdowns are, in many respects, contradictory concepts. Markdowns decrease product exclusivity and hence consumers’ willingness to pay (i.e., snob effect) since most consumers purchasing luxury desire uniqueness. Markdowns also encourage strategic (forward-looking) consumers to wait for lower prices (i.e., strategic effect). Yet, luxury retailers frequently adopt markdowns in practice to stimulate the demand for their seasonal products (i.e., sales effect). To study the impact of these three countervailing effects on a luxury retailer’s markdown policy and rationing strategy, this paper develops a game-theoretic model with strategic and exclusivity-seeking consumers who have heterogeneous (high and low) valuations. We characterize a luxury retailer’s equilibrium markdown and rationing strategies, and find that the retailer induces a buying frenzy (i.e., selling deliberately less than the demand) to increase consumers’ willingness to pay when they are sufficiently exclusivity-seeking. We show that the retailer’s markdown policy depends on consumers’ desire for exclusivity when the proportion of consumers with high valuation is not too high or too low. Interestingly, we find that, in such cases, consumers’ higher desire for exclusivity does not motivate the retailer to increase exclusivity and to adopt uniform pricing. To the contrary, it motivates the retailer to decrease the exclusivity and to adopt markdowns. By doing so, we identify exclusivity-seeking consumer behavior as another rationale behind markdown pricing. Lastly, we find that, when selling to exclusivity-seeking consumers, the negative impact of strategic consumer behavior is lower; however, ignoring it can be more costly

The Impact of Technology and Regulation on the Geographical Scope of Banking

We review how technological advances and changes in regulation may shape the (future) geographical scope of banking. We first review how both physical distance and the presence of borders currently affect bank lending conditions (loan pricing and credit availability) and market presence (branching and servicing). Next we discuss how technology and regulation have altered this impact and analyse the current state of the European banking sector. We discuss both theoretical contributions and empirical work and highlight open questions along the way. We draw three main lessons from the current theoretical and empirical literature: (1) Bank lending to small businesses in Europe may be characterized both by (local) spatial pricing and resilient (regional and/or national) market segmentation; (2) Because of informational asymmetries in the retail market, bank mergers and acquisitions seem the optimal route of entering another market, long before cross-border servicing or direct entry are economically feasible; (3) Current technological and regulatory developments may to a large extent remain impotent in further dismantling the various residual but mutually reinforcing frictions in the retail banking markets in Europe. We conclude the paper by offering pertinent policy recommendations based on these three lessons.geographical scope, banking, lending relationships, technology, and regulation.

Modeling strategic customers using simulations - with examples from airline revenue management

AbstractA condition for airline revenue management is the possibility of identifying and differentiating customer segments (refer to Chiang et al. (2007) for a state of the art). Traditionally, customer differentiation has been realized by the time of request in days before departure as well as by restrictions connected to the tickets sold. Customer segments have been regarded to be fixed over time, based on myopic customer behavior. With the market transparency increased through the Internet as well as the rise of no-frills offers and flat-rates, customer behavior has changed during the last decades. Strategic customer behavior describes a tendency to remember previous buying experiences, adapt expectations and observe the market over longer periods of time before deciding on what (and whether) to buy. The empirical consequences of strategic customer behavior for traditional as well as state-of-the-art revenue management have been little examined. A major reason for this is that measuring the degree of strategic versus myopic tendencies of demand in real customers is difficult and expensive. In this paper, we formulate a mathematical model of strategic customer behavior including parameters defining the propensity to delay buying as well as learning and communicating. We test the empirical consequences of our model using a stochastic simulation, in which customers act as agents deciding whether and when to buy. Thereby, we provide first results on how different ways of strategic behavior affect the success of methods of revenue management, highlighting the possible weaknesses and strengths of approaches when confronted with strategic customers. Of course, strategic customer behavior is not limited to airline revenue management. Useful models of strategic behavior as implemented in the simulation can be applied to analyze a wide range of situations: conditions for this transfer as well as examples are provided as part of the outlook

The Role of Surge Pricing on a Service Platform with Self-Scheduling Capacity

Recent platforms, like Uber and Lyft, offer service to consumers via “self-scheduling” providers who decide for themselves how often to work. These platforms may charge consumers prices and pay providers wages that both adjust based on prevailing demand conditions. For example, Uber uses a “surge pricing” policy, which pays providers a fixed commission of its dynamic price. With a stylized model that yields analytical and numerical results, we study several pricing schemes that could be implemented on a service platform, including surge pricing. We find that the optimal contract substantially increases the platform’s profit relative to contracts that have a fixed price or fixed wage (or both), and although surge pricing is not optimal, it generally achieves nearly the optimal profit. Despite its merits for the platform, surge pricing has been criticized because of concerns for the welfare of providers and consumers. In our model, as labor becomes more expensive, providers and consumers are better off with surge pricing because providers are better utilized and consumers benefit both from lower prices during normal demand and expanded access to service during peak demand. We conclude, in contrast to popular criticism, that all stakeholders can benefit from the use of surge pricing on a platform with self-scheduling capacity