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, APPENDIX A: Experimental Typology ARTIFICIAL
, Artificial simulation experiments serve various purposes. For example, they provide essential insights on the quality and effectiveness of methods, models, and policies. More precisely, simulations allow investigating scenarios that have proved difficult to analyse analytically, such as emerging IT phenomena. These artificial experiments provide significant theoretical and practical contributions
, s trajectory. In particular, control plays a crucial role. Of course, the results may lack external validity, but they provide significant insights that explain behavioural phenomena otherwise merely empirically unattainable. Students as a standard group of subjects and performance-based incentives are encouraged as good experimental practices, This type of laboratory experiments -generally referred to as behavioural experiments in the IS literature -focuses primarily on Smith, 1994.
, Neuroeconomics and neuroscience methods are used, as well as pre-and post-session questionnaires to collect self-measured data. The main objective is to reveal mental processes "that are difficult or even impossible to measure with existing measurement methods and tools, 2011.
, In general, participants are randomly assigned to control or treatment groups. In most cases, computer prototypes or web-based protocols are developed for study in order to provide technological realism
, In this type of laboratory experiments, the experimental materials are designed to be as realistic as possible in order to simulate the real situation. Hypothetical scenarios (also called vignettes) are used to avoid the influence of external variables. Vignettes are generally stories that were created by researchers and evaluated by participants. The independent variable remains under control of researchers, 1976.
, Simulation games allow players to take on different roles and play as a team or against another participant. Researchers create and control artificial conditions and contexts that simulate real environments (for example, organisational settings) in which participants are free to behave. As a result, they can create additional events that the experimenters cannot control. However, these types of experimental environments provide good technological and task realism. These simulation game experiments are also called free simulations, 1976.
, Quantitative data can also be collected through questionnaires, etc. Scenario settings and role-plays and teamwork tasks provide technological realism, 1994.
, Participants are randomly assigned to a group and perform a brainstorming task. Therefore, the data comes mostly from brainstorming sessions, but quantitative methods can be used to obtain quantitative data (e.g., questionnaires). Experimenters usually create scenarios to contextualize the experiment, vol.14
, Researchers are experimentally manipulating independent computer variables with a view to using participant-analysed decision-making scenarios. «The strength of the conjoint approach is that it combines the control of a laboratory experiment with the external validity of a survey, 2007.
, Subjects are randomly assigned to one of the conditions/groups and instructed to explore and use IT solutions. This category refers to those experiments where scenarios, games, etc. have not been used in order to simulate the real event, This does not preclude other types of field experiments from being randomised
, Techniques and principles of experimental economics in field environments
, Randomised field experiments using scenarios as in laboratory settings
, However, participants are generally real users, such as professionals. Post and pre-scenario surveys are usually used for data collection
, Randomised field experiments as in experiments based on simulation games in a laboratory environment
, The quasi-experiment shares resemblances with traditional randomised experiments, but in particular, the element of random assignment to treatment or control is missing (Cook and Campbell, 1979). Generally, this research experimentation encompasses a medium-long term period
,
, Online field experiments are randomised field experiments whose setting is an online environment. This experimental design may be characterised by less control than the laboratory and field settings, as the experimenter is not physically present during the session. However, the researcher can analyse the decision-making process of a real user in its real environment
, Scenario-based experiments, similar to those in laboratory and field experiments
, Randomised experiments such as experiments based on simulation games in a laboratory or field environment but the setting is online or virtual
, This empirical study investigates the effects of natural or unplanned comparison. Consequentially, conditions are manipulated by nature rather than by researchers. By being a natural setting, the experiment reflects real life, and ecological validity is one of its strengths