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1. Introduction and research problem Small firms are effective in exploring and recognizing new business opportunities, but are unable to build a strong foundation for exploiting future competitive advantage, whereas large firms are effective at exploiting competitive advantage but are less effective in exploring and recognizing new entrepreneurial opportunities (Ireland et Al., 2003). To be able effectively pursue exploratory & exploitative innovation simultaneously, a strong foundation of strategic resource must be managed, bundled and leveraged (Sirmon & Hitt, 2003; Sirmon et. al., 2007) also known as Strategic Entrepreneurship (SE.). SE. is firm-s capability to exploit current competitive advantage and explore new opportunity for future competitive advantage simultaneously (Hitt et. al., 2011). This research was conducted on real estate firms in Indonesia, which is a sector that makes an important contribution to Indonesias GDP (BPS, 2017). In the past, property industry experienced several severe crises which caused many real estate firms to go bankrupt. Nevertheless, some companies could survive the crisis and even revive. It was believed that the capability of Strategic Entrepreneurship that makes the real estate firms are able to survive. This research will try to find answers to the formulation of the problem of this research, namely how Resource Management affects explorative innovation and exploitative innovation, and whether explorative and exploitative innovation or their integration affect firm-s performance. 2. Methods This research is a quantitative research, with analysis unit is real estate firms in Indonesia. The respondent is individual who presents the firms. The time for the survey was approximately 4 months; June - September 2016. Four latent variables are used in this theoretical model. One dependent latent variable is firm-s performance and 3 independent latent variables are resource management, exploratory innovation and exploitative innovation. Six hyphotesis were constructed (H1 – H6). The questionnaires were then analysed as follow; first, factor analysis, which is the process of grouping latent variables formed by a number of operational questions, followed by bivariate correlation analysis to examine the relationship between latent variables (H1 – H4). The next stage will be inferential analysis in the form of multiple regression and overall model analysis using the seemingly causal model (SCM) method to examine the causal relationship of several variables according to the hypothesis developed (H5 – H6). All stages of the analysis above will use e-views software. 3. Results and findings From 250 questionnaires distributed, 56 proper questionnaires (24%) returned. Results of bivariate correlation analysis show that data support the hypothesis H1 – H4 at the significance level  : 0.01. Next, the result based on the statistical test F : F0 = 33,0603 with df = (3.50) and the val