Can we apply Serious Gaming as an alternative to Stated Preference Experiments? – A Freight Modelling Case Study
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In Serious Gaming (SG) participants take up a specific role and react in different situations opposed to them by a simulated environment. Specifically, the definition of serious gaming is given by Duke (1980) as ‘a conscious endeavour to reproduce the central characteristics of a system in order to understand, experiment with and/or predict the behaviour of that system’ (Duke and Geurts, 2004). SG applications have been used to raise awareness, to introduce innovations and to train employees. On the other hand, the majority of studies based in the development of choice models are based on the results of Stated Preference (SP) scenarios (Hess and Rose, 2009). Each respondent is asked to choose between different alternatives with modified attribute levels for each alternative. SP approaches may be therefore applied to test the introduction of new policies though the design of realistic scenarios for new policies. However, one of the biggest disadvantages of SP is the hypothetical design of experiments. Sometimes respondents are asked to state their opinions in unfamiliar situations resulting in making choices limited by lack of information or understanding (Whitehead et al., 2007). In addition, SP surveys when combined questions aiming at the collection of socioeconomic and Revealed Preference (RP) data, can be quiet long and time-consuming resulting in low response rates (Sanko, 2001). This paper investigates the possibility to use SG applications as a survey instrument when studying individual behavior. The results from a game were applied as data input to develop discrete choice models studying the behavior of planners involved in freight transportation. In addition, this research aims at investigating the limitations for the application of this method as an alternative to stated preference scenarios and reflects on the appropriate gaming designs for survey use. For the purpose of this research a game called SynchroMania has been used. SynchroMania aims at demonstrating to employees in the logistics sector how synchromodal planning works and to which choices are made during the shipment of goods from an origin to its final destination. Synchromodal transportation refers to the flexible use of multiple modes, routes and services when planning goods transportation. Hence, shipments can dynamically switch between the different modes and routes to cope with possible disturbances in the network. The promotion of synchromodality however, demands a behavioural change from managers, clients and planners. In the game, players take over the role of the planner and they are asked to optimally place orders, coming from three different customers, into three modes of transport (truck, rail and barge) based on customer’s demands, mode’s services and space availability. Each gaming session consists of three rounds. In each round limited time to assign the orders to the specific route and the modality dictated by the client is given. After the end of every round additional degrees of freedom, in the forms of action cards purchased to increase flexibility, are provided to the players. At the end of every round environmental and transport cost performance indicators are measured to evaluate players performance.The scores are compared and can be discussed the chosen tactics. Based on the insights thus obtained fit the players their tactics in the next round (Lebesque, 2015). The data used in this paper are derived from four gaming sessions played with employees from logistic service provider companies. In total a sample of 65 respondents completed 195 gaming rounds. From a methodological point of view we apply disaggregate mode choice models based on the answers of the respondents from the various sessions. Apart from the respondents characteristics, such as age, years of experience and size of the company cost related mode characteristics and availability constraints were inserted in the models. Based on which card was chosen by the player the degrees of freedom were also introduced as explanatory variable in the models. This work tries to explore the practical implementation of SG techniques as a survey instrument in the area of freight transportation. More specifically, after carrying out games sessions with employees in the logistics sector we treat the gaming outputs as SP experiments and develop the respective mode choice models. In addition we extensively discuss the limitations of this method on designing efficient experiments that can provide is with data allowing to estimate model parameters with low standard errors. Finally, we propose a methodological framework that could help pave the way for other research groups to take advantage of the fancier SG as survey techniques. References Duke, R.(1980). A paradigm for game design. Simulation Gaming, vol.11, is.3, pp. 364–377. http://sag.sagepub.com/content/11/3/364.full.pdf Duke, R., Geurts, J. (2004). Policy games for strategic management. Rozenberg, Amsterdam Hess, S. and Rose, J. (2009). Some lessons in stated choice survey design. Association of European Transport and Contributors. Lebesque L. (2015). Synchromodality experience with logistics serious game. TNO-Experience for Life. https://www.tno.nl/nl/over-tno/nieuws/2015/8/synchromodaliteit-ervaren-met-een-logistieke-serious-game/ . [Last accessed on September 29 th , 2017] Sanko, N. (2001). Guidelines for stated preference experiment design. Dissertation for Bussiness Administrarion Master, Ecole nationale de Ponts et Chaussees. Whitehead, J., Pattanayak, S., van Houtven, G. and Gelso, B. (2008). Combining revealed and stated preference data to estimate the nonmarket value of ecological services: and assessment of the state of science. 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