Marco A. Janssen

Innovation diffusion theory suggests that consumers differ concerning the number of contacts they have and the degree and the direction to which social influences determine their choice to adopt. To test the impacts of these factors on innovation diffusion, in particular the occurrence of hits and flops, a new agent-based model for innovation diffusion is introduced. This model departs from existing percolation models by using more realistic agents (both individual preferences and social influence) and more realistic networks (scale free with cost constraints). Furthermore, it allows consumers to weight the links they have, and it allows links to be directional. In this way this agent-based model tests the effect of VIPs who can have a relatively large impact on many consumers. Results indicate that markets with high social influence are more uncertain concerning the final success of the innovation and that it is more difficult for the innovation to take off. As consumers affect each other to adopt or not at the beginning of the diffusion, the new product has more difficulties to reach the critical mass that is necessary for the product to take off. In addition, results of the simulation experiments show under which conditions highly connected agents (VIPs) determine the final diffusion of the innovation. Although hubs are present in almost any network of consumers, their roles and their effects in different markets can be very different. Using a scale-free network with a cut-off parameter for the maximum number of connections a hub can have, the simulation results show that when hubs have limits to the maximum number of connections the innovation diffusion is severely hampered, and it becomes much more uncertain. However, it is found that the effect of VIPs on the diffusion curve is often overestimated. In fact when the influence of VIPs on the decision making of the consumers is strengthened compared with the influence of normal friends, the diffusion of the innovation is not substantially facilitated. It can be concluded that the importance of VIPs resides in their capacity to inform many consumers and not in a stronger persuasive power.

Many marketing efforts focus on promotional activities that support the launch of new products. Promotional strategies may play a crucial role in the early stages of the product life cycle, and determine to a large extent the diffusion of a new product. This paper proposes an agent-based model to simulate the efficacy of different promotional strategies that support the launch of a product. The article in particular concentrates on the targeting and the timing of the promotions. The results of the simulation experiments indicate that promotional activities highly affect diffusion dynamics. The findings indicate that: (1) the absence of promotional support and/or a wrong timing of the promotions may lead to a failure of product diffusion; (2) the optimal targeting strategy is to address distant, small and cohesive groups of consumers; and (3) the optimal timing of a promotion differs between durable categories (white goods, such as kitchens and laundry machines, versus brown goods, such as TVs and CDs players). These results contribute to the planning and the management of promotional strategies supporting new product launches.

Keywords: Diffusion of innovations; Agent-based model; Targeting strategies; Promotions; Takeoff of diffusions; Word-of-mouth; Social influence

Diffusions of new products and technologies through social networks can be formalized as spreading of infectious diseases. However, while epidemiological models describe infection in terms of transmissibility, we propose a diffusion model that explicitly includes consumer decision-making affected by social influences and word-of-mouth processes. In our agent-based model consumers’ probability of adoption depends on the external marketing effort and on the internal influence that each consumer perceives in his/her personal networks. Maintaining a given marketing effort and assuming its effect on the probability of adoption as linear, we can study how social processes affect diffusion dynamics and how the speed of the diffusion depends on the network structure and on consumer heterogeneity. First, we show that the speed of diffusion changes with the degree of randomness in the network. In markets with high social influence and in which consumers have a sufficiently large local network, the speed is low in regular networks, it increases in small-world networks and, contrarily to what epidemic models suggest, it becomes very low again in random networks. Second, we show that heterogeneity helps the diffusion. Ceteris paribus and varying the degree of heterogeneity in the population of agents simulation results show that the more heterogeneous the population, the faster the speed of the diffusion. These results can contribute to the development of marketing strategies for the launch and the dissemination of new products and technologies, especially in turbulent and fashionable markets.

Keywords: Innovation diffusion; Threshold models; Word-of-mouth; Social networks; Heterogeneous markets

Markets can show different types of dynamics, from quiet markets dominated by one or a few products, to markets with continual penetration of new and reintroduced products. In a previous article we explored the dynamics of markets from a psychological perspective using a multi-agent simulation model. The main results indicated that the behavioral rules dominating the artificial consumer’s decision making determine the resulting market dynamics, such as fashions, lock-in, and unstable renewal. Results also show the importance of psychological variables like social networks, preferences, and the need for identity to explain the dynamics of markets. In this article we extend this work in two directions. First, we will focus on a more systematic investigation of the effects of different network structures. The previous article was based on Watts and Strogatz’s approach, which describes the small-world and clustering characteristics in networks. More recent research demonstrated that many large networks display a scale-free power-law distribution for node connectivity. In terms of market dynamics this may imply that a small proportion of consumers may have an exceptional influence on the consumptive behavior of others (hubs, or early adapters). We show that market dynamics is a self-organized property depending on the interaction between the agents’ decision-making process (heuristics), the product characteristics (degree of satisfaction of unit of consumption, visibility), and the structure of interactions between agents (size of network and hubs in a social network).

In this paper we argue that simulating complex systems involving human behaviour requires agent rules based on a theoretically rooted structure that captures basic behavioural processes. Essential components of such a structure involve needs, decision-making processes and learning. Such a structure should be based on state-of-the-art behavioural theories and validated on the micro-level using experimental or field data of individual behaviour. We provide some experiences we had working with such a structure, which involve the possibility to relate the results of simulations on different topics, the ease of building in extra factors for specific research questions and the possibility to use empirical data in calibrating the model. A disadvantage we experienced is the lack of suiting empirical data, which necessitates in our view the combined use of empirical and simulation research.

An approach is introduced to combine survey data with multi-agent simulation models of consumer behaviour to study the diffusion process of organic food consumption. This methodology is based on rough set theory, which is able to translate survey data into behavioural rules. The topic of rule induction has been extensively investigated in other fields and in particular in learning machine, where several efficient algorithms have been proposed. However, the peculiarity of the rough set approach is that the inconsistencies in a data set about consumer behaviour are not aggregated or corrected since lower and upper approximation are computed. Thus, we expect that rough sets theory is suitable to extract knowledge in the form of rules within a consistent theoretical framework of consumer behaviour.

We report on a series of computer simulation experiments regarding the management of a common resource. We were particularly interested in the effects of uncertainty and satisfaction on the harvesting behaviour of simulated agents. The experimental study of long-term dynamics of threatened resources can hardly be carried out using human subjects. We therefore experimented with simulated consumers, the so-called consumats, whose properties are derived from a comprehensive, multitheoretical model of consumer behaviour. A consumat is equipped with needs and abilities, and may engage in different cognitive processes, such as deliberation, social comparison, imitation, and repetition of previous behaviour. In a first simulation experiment we show as to how uncertainty may stimulate an imitation effect that promotes over-harvesting. In two subsequent series of experiments, we show that increased uncertainty results in an increased ‘optimism’ of consumats regarding future outcomes, an increased likelihood of imitative behaviour, and a lesser adaptation of harvesting behaviour during resource depletion. These ‘process-effects’ promote higher levels of harvesting from a collective resource. The main experimental conclusions and the issue of validating simulation results are discussed.

Markets can show different types of dynamics, from quiet markets dominated by one or few products, to markets with constant penetration of new and reintroduced products. This paper explores the dynamics of markets from a psychological perspective using a multi-agent simulation model. The behavioural rules of the artificial consumers, the consumats, are based on a conceptual meta-theory from psychology. The artificial consumers have to choose each period between similar products. Products remain in the market as long as they maintain a minimum level of market share, else they will be replaced by a new product. Assuming a population of consumats with different preferences, and social networks, the model simulates adoption of new products for alternative assumptions on behavioural rules. Furthermore, the consequences of changing preferences and the size of social networks are explored. Results show that the behavioural rules that dominate the artificial consumer’s decision making determine the resulting market dynamics, such as fashions, lock-in and unstable renewal. Results also show the importance of psychological variables like social networks, preferences and the need for identity to explain the dynamics of markets.

Keywords: Social networks; Changing preferences; Consumer behaviour; Lock-in

Despite the abundance of empirical data on household energy consumption, it is hard to predict future developments because of the complexity of the household system. Multi-agent simulation offers a tool to get a better understanding of the relevant behavioural dynamics of the household system. This would allow for an early diagnosis and response to unwanted developments. A computer simulation of consumer behaviour has been developed on the basis of a meta-model of behaviour, which integrates various relevant behavioural theories. This so-called consumat approach has been applied to issues such as the lock-in of consumption patterns and the management of a common resource, and has been applied in an integrated ecological-economic model. This paper discusses the basic principles of the consumat approach, summarises some results, and draws conclusions with respect to the application of this approach in the domain of household consumption.

Keywords: behavioural dynamics; consumat; consumer behaviour; household consumption; modelling; multi-agent simulation.

Ecosystem management requires the explicit treatment of interactions between humans and ecosystems. An exploratory model for integrating social and ecological dynamics was introduced to study ecosystem management strategies. This paper focuses on the management of lake eutrophication. The model was developed to include the dynamics of the lake, the behaviour of agents using phosphorus for agricultural purposes, and the interactions between ecosystem and farmers. Analyses with the model showed that the dominating type of cognitive processing was a relevant factor in the response to uncertainty and policy measures. A higher target level for returns on the use of phosphorus was found to lead to a more intensive use of phosphorus and to higher levels of phosphorus in the lake. Simulated farmers used phosphorus more intensively in situations with high natural variability. A tax on phosphorus had little effect on the behaviour of the farmers when they felt uncertain and had low target levels for returns.

Keywords: Lake management; Social psychology; Resilience; Eutrophication; Multi-agent modelling; Integrated modeling.

Die Lenkung der gegenwärtigen konsum- und produktionsmuster in eine nach- haltigere richtung erfordert eine ausführliche studie des menschlichen Verhal- tens. um dessen komplexität angemessen zu berücksichtigen, wird hier ein multi-agenten-ansatz vorgeschlagen, der erkenntnisse der sozialpsychologie integriert. am Beispiel des Übergangs von einer fischerei- zu einer Bergbauge- sellschaft wird gezeigt, wie sich unterschiedliche Verhaltensannahmen auf die mensch-umwelt-Beziehungen auswirken.

Markets can show different types of dynamics, ranging from stable markets dominated by one or a few products, to fluctuating markets where products are frequently being replaced by new versions. This paper explores the dynamics of markets from a psychological perspective using a multi-agent simulation model. The behavioural rules of the artificial consumers, the consumats, are based on a conceptual meta-theory from psychology. The artificial consumers have to choose each period between different products. Products remain on the market for as long as their market share exceeds a minimum level. If not, it will be replaced by a new product.

Simulation experiments are being performed with a population of consumats having different preferences. Results show that the dominating type of cognitive (choice) process has large consequences for the resulting market dynamics. Moreover, the size of the social network affects the market dynamics too.

Keywords: social networks; consumer behaviour; market dynamics.

In mainstream economy, behaviour is often formalised following the rational actor-approach. However, in real life the behaviour of people is typified by multidimensional optimisation. To realise this, people engage in cognitive processes such as social comparison, imitation and repetitive behaviour (habits) so as to efficiently use their limited cognitive resources. A multi-agent simulation program is being developed to study how such micro-level processes affect macro-level outcomes. Sixteen agents are placed in a micro-world, consisting of a lake and a gold mine. Each agent’s task is to satisfy its personal needs by fishing and/or mining, whereby they find themselves in a commons dilemma facing the risk of resource depletion. Homo economicus and Homo psychologicus are formalised to study the effects of different cognitive processes on the agents’ behaviour. Results show that for the H. psychologicus the transition from a fishing to a mining society is more complete than for the H. economicus. Moreover, introducing diversity in agents’ abilities causes the H. economicus on the average to decrease its time spent working, whereas for the H. psychologicus we observe an increase in the time spent working. These results confirm that macro-level indicators of sustainability, such as pollution and fish-harvest, are strongly and predictably affected by behavioural processes at the micro-level. It is concluded that the incorporation of a micro-level perspective on human behaviour within integrated models of the environment yields a better understanding and eventual management of the processes involved in environmental degradation.

Keywords: Commons dilemma; Resource; Consumat; Simulation; Multi-agent; Dynamics; Psychology.

Lock-in denotes a phenomenon of monopolistic dominating technologies or consumer goods in a certain market. These lock-ins cannot be explained by superior characteristics of the good or technology. Previous studies mainly used probabilistic models to study lock-in effects. In this paper an integrated conceptual model of consumer behaviour is used to identify relevant processes of lock-in dynamics of consumption patterns. An agent-based model is developed to simulate consumats, artificial consumers, who are confronted with two similar products. We found two types of lock-in, namely, a spatial lock-in and a global level lock-in. The spatial lock-in related to the spatial patterns that occur in consumption patterns and relates to the satisfaction of the need for identity. The global lock-in relates to price effects and occurs only if individual preferences are not significantly weighted in the cognitive processing.

Keywords: Lock-in, multi-agent modelling, social psychology, need satisfaction, consumer behavior.

In this paper we apply the updated consumat approach to the case of diffusion of electric cars. We will discuss how data from a large sample can be used to parameterize a number of main behavioural drivers, and how these relate to behavioural processes. At this stage we explain how the data fit in the framework, and whereas a model is currently under development, first simulation results are to be available first during the ESSA conference.

Keywords: diffusion; electric cars; agent based modeling; human behavior; decision making; needs; consumat

Multi agent simulation (MAS) is a tool that can be used to explore the dynamics of different systems. Considering that many demographic phenomena have roots in individual choice behaviour and social interactions it is important that this behaviour is being translated in agent rules. Several behaviour theories are relevant in this context, and hence there is a necessity of using a meta-theory of behaviour as a framework for the development of agent rules. The consumat approach provides a basis for such a framework, as is demonstrated with a discussion of modelling the diffusion of contraceptives. These diffusion processes are strongly influenced by social processes and cognitive strategies. Different possible research lines are discussed which might be addressed with a multi-agent approach like the consumats.