Any group that creates challenging goals also requires a strategy to achieve them and a process to review and improve this strategy over time. The University of British Columbia (UBC) set ambitious campus sustainability goals, including a reduction in its greenhouse gas emissions to 33% below the 2007 level by 2015, and 100% by 2050 (UBC, 2006). The University pursued these goals through a number of specific projects (such as major district energy upgrade and a bioenergy facility) and, more generally, through a “Campus as a Living Lab” (CLL) initiative to marry industry, campus operations, and research to drive innovative solutions. The CLL program has achieved significant successes while also demonstrating many opportunities for improvements and lessons learned. The aim of this study was to examine the UBC CLL program, to identify and formalize its operations, to extract key transferable characteristics, and to propose replicable processes that other universities and municipalities can follow to expand their sustainable practices in similar ways. There was a learning curve with implementing a CLL program at UBC; thus, the goal of this study was to potentially shorten this learning curve for others. The research involved an ethnographic approach in which researchers participated in the CLL process, conducted qualitative analysis, and captured the processes through a series of business process models. The research findings are shared in two parts: 1. generalized lessons learned through key transferrable characteristics; 2. a series of generic organizational charts and business process models (BPMs) culminated with learned strategies through defined processes that illustrate what was required to create a CLL program at UBC. A generalized future improvement plan for UBC CLL programs is defined, generic BPMs about CLL projects are evaluated, and the level of engagement of multiple stakeholders through phases of project life cycle given in the conclusion for future use of other Living Lab organizations.
Business Process Models Complexity Growth Analysis based on Scheduling Generated by Timetabling of Courses
