From a methodology point of view, most Behavioural Operations Management (BOM) studies have employed experiments. However, no reason, either theoretical or practical, exists to limit BOM to experimental research. In this chapter, I discuss my conviction that methodologies coming from complexity science have the proper characteristics to be successfully applied in BOM research, since real operating systems, such as processes, factories, organisations and supply chains, are complex adaptive systems (CASs) where human behaviour is the central driver. Moving from this assumption, I suggest applying complexity science in order to study operating systems in diverse OM contexts and I also propose research questions coherent with a complexity science approach. They concern how operating systems behave, adapt and show new orders in terms of processes, structures and performances. Then, I suggest the adoption of a simulation tool to study CASs to develop BOM models, i.e. NK fitness landscape. After reviewing the methodology and its main applications in organisational contexts, I propose how different OM contexts can be modelled and how behavioural factors both at an individual and at a population level might be operationalised through the methodology proposed. Finally, I formulate research questions that might be addressed by applying NK fitness landscape.
|Titolo:||Complex Systems Methodologies for Behavioural Research in Operations Management: NK Fitness Landscape|
|Titolo del libro:||Behavioral Issues in Operations Management : New Trends in Design, Management, and Methodologies|
|Data di pubblicazione:||2013|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1007/978-1-4471-4878-4_2|
|Appare nelle tipologie:||2.1 Contributo in volume (Capitolo o Saggio)|