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This study aims to provide empirical insights into how sustainability (ESG) and broad-based indices are affected by risk indicators such as VIX, CDS, and FX volatility index. Germany ESG-X, CDAX, France ESG-X, CAC All, Indonesia SRI-KEHATI, IDX Composite, BIST (Borsa Istanbul) Sustainability, and BIST All price indices have been examined. The daily data between November 4, 2014, and December 5, 2019 are used. Vector autoregression (VAR), Granger causality and impulse response test are employed in the analysis. The results of the study revealed that companies which are included in the Germany ESG-X, France ESG-X, and SRI-KEHATI are affected by shocks less than the companies included in broad-based indices of each country. In contrast to this result, BIST Sustainability is affected more by the shocks than BIST All. Stocks with higher ESG exposure in terms of quantity, quality, and credibility tend to have a lower risk. Causality test results revealed that VIX causes broad-based and ESG indices more than any other risk indicators.

This paper study a new approximation model to solving stochastic data envelopment analysis (SDEA) problem. The proposed approach is based on problems that might occur in everyday life. This paper discusses the approach in determining the efficiency and super efficiency ratings of a decision making unit (DMU) in the DEA model with stochastic data. In determining efficiency, SDEA is first transformed into an equivalent deterministic DEA by changing its chance constraints in such a way that the SDEA problem can be solved easily. The author proposes an approach technique called a sample median approximation (SMA) to change the chance constraints so that it will be easy to get the optimal solution in determining the efficiency of DMUs. In the process, the data to be processed first is determined by the median average which will later be considered to represent the actual sample average. As a numerical example, the author resolves the vendor selection problem as presented by Wu and Olson (2006) in their paper. By taking the same parameter value (α = 0.2 and beta = 0.9), the efficiency score and super efficiency of the problem are obtained.

As a system, the emergency department reveals detailed and dynamic complexity of its interaction between inter-departmental units and intra-departmental elements. Discrete-event simulation (DES) has been recognised for its ability to comprehend operational problems with detailed complexity. Whilst using DES to model the complexities of the integrated emergency department system, we also use system dynamics (SD) to capture the interdependency relationships between the emergency department and other subunits in a hospital. This paper presents the integration of DES and SD modelling approach, hereby named as hybrid simulation, to better understand emergency department operations from a whole system perspective.

This paper is concerned with the optimal control of inventory-production system subject to Gumbel distributed deterioration items with applications to optimal control theory. We successfully formulated the model as a linear optimal control problem and obtained an explicit solution using Pontryagin maximum principle. The optimality conditions are derived in this case. It is then illustrated with the help of examples.

AbstractThe paper studies the production inventory problem of minimizing the expected discounted present value of production cost control in manufacturing systems with degenerate stochastic demand. We have developed the optimal inventory production control problem by deriving the dynamics of the inventory-demand ratio that evolves according to a stochastic neoclassical differential equation through Ito's Lemma. We have also established the Riccati based solution of the reduced (one- dimensional) HJB equation corresponding to production inventory control problem through the technique of dynamic programming principle. Finally, the optimal control is shown to exist from the optimality conditions in the HJB equation.