Agent-based Market Simulation Research Articles

Looking Beyond Membership: A Simulation Study of Market-entry Strategies for Two-sided Platforms under Competition

Organizations need to implement a proper market-entry strategy to successfully establish a two-sided digital platform. Following the right strategy becomes even more crucial if a competing platform already exists in the targeted market. In this case, organizations will find it more difficult to reach critical mass because users flock to the already established, larger platform due to network effects, which will result in a potential winner-take-all situation. While previous research proposes strategies, it has not discussed how to find the right strategy. This paper introduces an agent-based market simulation to comprehensively evaluate alternative strategies under competition that accounts for not only platform adoption for the entrant but also for transactions, earnings, and the need to weaken the incumbent. Through an example case parameterized with empirical data, I illustrate how one can apply the model. The findings suggest that entrants need to comprehensively evaluate market-entry strategies beyond just looking at membership figures because different strategies can have the most promise with regard to growing the entrant’s platform, weakening the incumbent, and boosting the entrant’s transactions and earnings.

An Agent-Based Market Simulation with Social Effects

In this paper an agent-based market has been investigated. To simulate the social effects, the social networks topologies popular in related researches were employed. Here agents choose one belief out of a set of beliefs, i.e. Fundamentalism, trend chasing and interrupting. Agents change their beliefs based on two factors, i.e. previous wealth of their own beliefs and other agents’ beliefs. To change the beliefs, a new opinion formation model was introduced. Here, the different decisions of agents guarantee the heterogeneity in Market. Results show the return for all the social networks met the stylized facts. Also, results reveal the social effects on price movement and market statistics.

Beaming market simulation to the future by combining agent-based modeling with scenario analysis

Agent-based simulation has become an established method for innovation and technology diffusion research. It extends traditional approaches by modeling diffusion processes from a micro-level perspective, which enables the consideration of various heterogeneous stakeholders and their diverse interactions. While such a simulation is well suited to capture the complex behavior of markets, its application is challenging when it comes to modeling future markets. Therefore, we propose a multi-method approach that combines scenario analysis that generates multiple “pictures of the future” with an agent-based market simulation that offers insight into the potential outcomes of today’s strategic (technological) decisions in each of these futures. Thus, simulation results can provide valuable decision support for corporate planners and industrial engineers when they are engaged in technology planning. This paper describes the novel approach and illustrates it through a sample application that is based on an industry-related research project on the development and market introduction of smart products.

An agent-based market simulation for enriching innovation management education

It is not easy for students or junior managers to obtain first-hand experience in innovation and technology management. Business gaming simulations can remedy this, as they provide an opportunity to acquire practical skills. We developed such a business gaming simulation that enables teams of participants—each managing a virtual company that competes with other companies in several markets—to implement technology strategies, make resource allocation decisions, and test marketing strategies for introducing its new products. The salient feature of this simulation is its agent-based market model, which accounts for consumers’ heterogeneity and social factors like word-of-mouth communication. In this paper, we describe the elements and dynamics of the market model, outline the didactic framework, and synthesize our experiences from using the simulation in classroom settings for several years. Overall, we find that using an agent-based model as the core of a business gaming simulation can facilitate experiential learning in management, particularly in fields that involve complex social system dynamics, as is the case in the diffusion of innovations.

Traditional versus fast fashion supply chains in the apparel industry: an agent-based simulation approach

In the past, most companies in the European apparel industry focused on minimizing manufacturing costs in the design of supply chains in conjunction with long-distance shipping from production sites in the Far East and relatively long production cycles. Today, for some market segments, the speed of production cycles is more important than the cost because short throughput time allows the flexibility to adjust to rapidly changing fashion trends in these market segments. Accordingly, choosing the most beneficial supply chain strategy has become an established research topic. However, apparel markets are complex systems. Therefore, attempts to reduce the underlying complexity in order to model these markets have limited existing research to the consideration of only selected aspects of markets (e.g., considering only homogeneous buyers, a single period, a single product, or a single manufacturer in the absence of competition) rather than taking a more comprehensive view. These limitations can be overcome by applying an agent-based simulation approach—an approach that can account for a wider range of factors, including several competing manufacturers utilizing different supply chain strategies, individual consumer preferences and behavior, word-of-mouth communication, normative social influence, and first-hand experience, as well as advertising. In this paper, the capability potential of such agent-based market simulation is demonstrated by investigating two supply chain strategies (fast fashion vs. traditional fashion) with varying product and communication strategies (product attributes and advertising) in several market scenarios.

High frequency traders in a simulated market

Purpose An agent-based market simulation is utilized to examine the impact of high frequency trading (HFT) on various aspects of the stock market. This study aims to provide a baseline understanding of the effect of HFT on markets by using a paradigm of zero-intelligence traders and examining the resulting structural changes. Design/methodology/approach A continuous double auction setting with zero-intelligence traders is used by adapting the model of Gode and Sunder (1993) to include algorithmic high frequency (HF) traders who retrade by marking up their shares by a fixed percentage. The simulation examines the effects of two independent factors, the number of HF traders and their markup percentage, on several dependent variables, principally volume, market efficiency, trader surplus and volatility. Results of the simulations are tested with two-way ANOVA and Tukey’s post hoc tests. Findings In the simulation results, trading volume, efficiency and total surplus vary directly with the number of traders employing HFT. Results also reveal that market volatility increased with the number of HF traders. Research limitations/implications Increases in volume, efficiency and total surplus represent market improvements due to the trading activities of HF traders. However, the increase in volatility is worrisome, and some of the surplus increase appears to come at the expense of long-term-oriented investors. However, the relatively recent development of HFT and dearth of appropriate data make direct calibration of any model difficult. Originality/value The simulation study focuses on the structural impact of HF traders on several aspects of the simulated market, with the effects isolated from other noise and problems with empirical data. A baseline for comparison and suggestions for future research are established.

A Framework for Incorporating Market Interactions in an Agent Based Model for Freight Transport

A model is sketched that allows to display the reaction of the supply side in the freight transport market on changes in demand and on policy measures. Considerations are made on how to include the concept of monopolistic competition into an agent based market simulation. Methods of price formation and rules for entries and exits of suppliers in the market are given.

Ein Konzept für handelbare Flächennutzungs-zertifikate in der Schweiz und Resultate einer agentenbasierten Marktsimulation

The revision of the federal act on spatial planning in 2013 and the adoption of the popular initiative on second homes in 2012 reveal – among other issues – that the Swiss population is concerned about land use developments. There is a widespread claim for stricter legal enforcement, further regulations and innovative instruments to tackle land-use problems. This paper presents a concept of the market-oriented planning instrument of Transferable Development Rights (TDR) adapted to Switzerland, which could be used to reduce land-use problems, in particular those associated with the abundant building zones. First, we present a possible TDR market concept for Switzerland, second, we present the empirically calibrated agent-based TDR market simulation, and third, we show and discuss detailed simulation results.The results show that with the introduction of TDR, it would be possible to reduce both the overall building zone area and the problem of severe spatial imbalances in supply and demand for these zones. For example, it can be shown that through TDR trade, it would be possible to downzone 11.4 km2 of building zone land for which there is no demand, and to develop 7.4 km2 of new building zone land by the year 2018. In addition, the obtained simulation results reveal that TDR prices would be comparable with existing land prices in Switzerland, i.e. the cost of developing land would not rise.

Results of an Agent-Based Market Simulation for Transferable Development Rights (TDR) in Switzerland

Transferable development rights (TDR) are discussed or applied in various countries for a wide variety of purposes: Notably to increase building densities, preserve natural areas, compensate reduced development possibilities, and control land use in rural areas. In Switzerland, TDR, a market-oriented planning instrument, might be used to reduce the land-use problems related to the unsustainable development of the settlement areas and to manage problems with the spatially imbalanced supply and demand of existing undeveloped building zones. Our aim is to briefly introduce a TDR market concept for Switzerland, present an empirically calibrated agent-based TDR market simulation, and finally analyze the detailed simulation results. We ran the simulation with four different settings which allowed an analysis of relevant political and economic questions for Switzerland. The results show that the TDR prices were comparable with existing land prices in Switzerland. In addition, we are able to show that with the trade of TDR it would be possible to downzone 11.4 km2 of building zone land for which there is no demand and to develop 7.4 km2 of new building zone land up to the year 2018. Consequently, the defined building zone area would decrease, which would be in line with political objectives.

A kinetic model for an agent based market simulation

A kinetic model for a specific agent based simulation to generate the sales curves of successive generations of high-end computer chips is developed. The resulting continuum market model consists of transport equations in two variables, representing the availability of money and the desire to buy a new chip. In lieu of typical collision terms in the kinetic equations that discontinuously change the attributes of an agent, discontinuous changes are initiated via boundary conditions between sets of partial differential equations. A scaling analysis of the transport equations determines the different time scales that constitute the market forces, characterizing different sales scenarios. It is argued that the resulting model can be adjusted to generic markets of multi-generational technology products where the innovation time scale is an important driver of the market.

Assessing the value of storage in a future energy system with a high share of renewable electricity generation

Increasing the share of intermittent renewable electricity generation will require additional flexibility in the electricity system. While energy storage can provide such flexibility, studies about the economics of power storage often conclude that there is no business case for large-scale storage applications. In this paper, we present a new approach on how to assess the benefits of energy storage. Key improvements have been made in two areas: Firstly, the agent-based market simulation model PowerACE has been enhanced to make use of optimization methods (MILP) for the unit commitment of the agents, enabling us to quantify the economic benefit of flexibility at supply-agent level. Secondly, we have considerably extended the common unit commitment problem (Carrion and Arroyo, IEEE Trans Power Syst 21(3):1371–1378, 2006), so that we can now model the provision of positive and negative balancing power and the dispatch of storage units. We compare the flexibility offered by thermal power plants to that offered by storage units for the four major German electricity generating companies under two different scenarios. The results for 2030 indicate that it would be more profitable to build up to 4,800 MW storage capacity in the German market rather than investing in flexible combined cycle gas turbine plants or hard coal-fired units. The increasingly fluctuating residual load implies that inflexible power plants will be penalized. Using storage units, the power plants of an existing portfolio can be dispatched in a more efficient way, i.e. with less operation in part load and avoiding start-up or shutdown events.

Impacts of emission trading and renewable energy support schemes on electricity market operation

In order to mitigate Greenhouse Gas emissions, emission trading and renewable energy support schemes have been or are going to be implemented in some developed countries or regions. Inevitably, the implementation of these two schemes would bring some new problems to electricity market operation. Given this background, with the implementation of these two schemes, an agent-based market simulation method is proposed in this study for analysing the gaming behaviours of generation companies in an electricity market environment. Replicator dynamics algorithm is employed to simulate the bidding strategies of agents (generation companies) for profit maximisation. The operation process of a specified electricity market is simulated over a studied time horizon and some indices are employed to evaluate the market operation performance. A numerical example is served for demonstrating the feasibility of the proposed model and methodology. The impacts of the two schemes on the electricity market operation are examined through the comparisons of the indices in different scenarios.

AN AGENT-BASED LABOR MARKET SIMULATION WITH ENDOGENOUS SKILL-DEMAND

This paper considers an agent-based labor market simulation to examine the influence of skills on wages and unemployment rates. Therefore less and highly skilled workers as well as less and highly productive vacancies are implemented. The skill distribution is exogenous whereas the distribution of the less and highly productive vacancies is endogenous. The different opportunities of the skill groups on the labor market are established by skill requirements. This means that a highly productive vacancy can only be filled by a highly skilled unemployed. Different skill distributions, which can also be interpreted as skill-biased technological change, are simulated by incrementing the skill level of highly skilled persons exogenously. This simulation also provides a microeconomic foundation of the matching function often used in theoretical approaches.