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Implementation of Enterprise Risk Management as a Strategy for Increasing Competitive Advantage: Study at Companies in Central Kalimantan
Get PDFThis research investigated the impact of Enterprise Risk Management (ERM) and organizational culture on competitive advantage (CA) in cigarette companies in Kalimantan. Through in-depth interviews with three key informants (a branch manager, a sales supervisor, and a finance account manager), the study revealed that effective ERM, particularly in managing external risks like regulatory changes and market fluctuations and internal risks such as operational challenges and HR issues, is crucial for achieving CA. Additionally, an organizational culture that fosters innovation, risk-based performance assessment, and effective HR management significantly contributes to the success of ERM and strengthens CA. Companies can better manage risks and enhance their competitive position by adapting to market changes and embracing innovation. While this research offers valuable insights, its generalizability may be limited due to its focus on cigarette companies in Central Kalimantan and its relatively small sample size. Future research could broaden the scope to include a broader range of companies and regions to gain a more comprehensive understanding. This study's original contribution lies in exploring the interplay between ERM and organizational culture in the context of CA in the cigarette industry. The findings emphasize the importance of integrating risk management and organizational culture as a strategic approach to maintain and strengthen competitive advantage, providing valuable implications for research and practice in this fiel
Multi-Objective Portfolio Optimization Strategy using the SPEA-II Algorithm
Get PDFIn the finance world, the precise selection and optimization of stock portfolios are of paramount importance. This study explores the application of intelligent algorithms, particularly the multi-objective of Strength Pareto Evolutionary Algorithm II (SPEA-II), alongside traditional methods to determine optimal portfolios. Using the monthly stock prices, the Markowitz model is developed, focusing on the return and semi-variance criteria. Realistic constraints are applied to formulate a multi-objective optimization problem. SPEA-II and traditional multi-objective optimization methods are used to solve this problem, resulting in a set of optimal portfolios. The results show that the SPEA-II algorithm can generate portfolios with higher returns and lower risks compared to the Markowitz model and traditional methods, taking into account the complex and nonlinear conditions of the capital market. In addition, the SPEA- II algorithm showed significant efficiency and stability across different frequencies and time periods. The study highlights that the SPEA-II algorithm can serve as an effective and efficient method for stock portfolio selection and optimization, helping investors to identify portfolios with lower risk and higher retur
