A Model Proposal for Smart Campus Investment Prioritization by Using Data Envelopment Analysis

Smart campus (SC), one of the most highlighted concepts in the education system, is the utilization and combination of smart physical-digital spaces to provide improved, intelligent, and responsive services in a sustainable, productive, and creative environment for universities. Considering its multi-dimensional structure, investment in this area is a crucial strategic decision with many conflicting aspects. On the other hand, Data envelopment analysis (DEA) is a linear programming (LP) technique that quantifies the relative efficiency of decision-making unit (DMU) inputs into their outputs through a trial-and-error model. Through that, in this paper, by using the capability of the DEA model, an SC investment efficiency problem is considered in multiple ways. According to the literature review and experts’ evaluations, four cost-based inputs are determined for the SC ecosystem. Based on the six outcomes, an application for the SC investment problem is carried out. Based on the results obtained, investments prioritized with the spending on classes and online teaching fulfilled the efficient rate input have the efficiency rate with one for all scenarios. Moreover, a scenario with equally distributed investments has the desired efficient rate equal to one.