## 4 Research Methodology  
The study aims to identify and rank FM KPIs and barriers for the implementation of BI&A in healthcare FM. Therefore, AHP-PROMETHEE (multi-criteria decision-making--MCDM) method was considered as a research method to reveal orders. In the literature, there are many MCDM methods such as analytic hierarchy process (AHP), analytic network process (ANP), technique for order of preference by similarity to ideal solution (TOPSIS), elimination and choice translating reality English (ELECTRE), and preference ranking organization method for enrichment evaluations (PROMETHEE) [59]. The author stated that there is no superior method amongst these methods. However, the research method needs to be chosen according to the research aim. According to [PERSON] et al. [60], PROMETHEE GAIA analysis enables one to evaluate actions by considering different criteria or paired criteria, and to visualize the analysis results. However, the disadvantage of PROMETHEE analysis is the inability to calculate weights of criteria. Therefore, AHP and PROMETHEE methods were merged in the literature [61]. The concept map of the study is shown in Figure 1. In this study, AHP-PROMETHEE analysis is employed to obtain complete ranking of healthcare FM. The AHP method finds the widest application areas in decision-making, resource allocation, and conflict resolution studies. It is basically a theory of measurement to deliver ratio of scales through the paired comparison of continuous and discrete numbers. The paired comparison is performed with the actual measurements or relative strengths of preferences [62]. The PROMETHEE method was developed by [PERSON] [63], who introduced the PROMETHEE method as a new class of outranking method. In the method, criteria are used to discover outranking relationships between alternatives. Partial-order (PROMETHEE I) and complete order (PROMETHEE II) are possible with the PROMETHEE method. In PROMETHEE I, the collected data from the decision-maker is compared specific to each criterion. In PROMETHEE, there are six preference functions; usual function, U-shape function, V-shape function, level function, linear function, and Gaussian function. These functions are the powerful side of PROMETHEE since the method allows the decision-maker to use different types of preference functions for different criteria [59]. In this study, three conflicting criteria were considered to find out the importance level of defined FM KPIs. These criteria are:  
* Time: Depending on aging population and population growth, demands for healthcare services have increased [63]. Therefore, the length of patient care has decreased. Moreover, uninterrupted service in healthcare facilities is important, since services such as surgery activities can be interrupted or postponed [64, 65]. * Cost: Operational expenditure is five times more costly than capital expenditure [66, 67]. [PERSON] and [PERSON] [68] stated that hospitals are under financial pressures and one-third of hospitals have negative margins. Accordingly, FM budgets have been cut in hospitals. Therefore, cost criteria are important to decide activities that are performed in healthcare FM. * Quality: Patients are susceptible to indoor conditions in healthcare facilities. Therefore, patient curing quality needs to be handled with FM services quality [69]; patient preference for healthcare facilities is affected by FM quality. AHP integrated PROMETHEE method introduced by [PERSON] [59] was followed due to simplicity, clearness and stability [62]. It aims to rank alternatives by considering conflicting criteria [59, 70]. In a hybrid method, AHP is used to reveal weights of criteria. Results from AHP are used in the PROMETHEE method to refine the rank of alternatives. In addition to the PROMETHEE method, geometrical analysis for interactive aid (GAIA) was used to enable more understandable graphical representation of alternatives for FM decision-makers [71].