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In this paper, the objective is to perform mathematical modeling to optimize the steady-state availability of a multi-state repairable crushing system of a sugar plant using the evolutionary algorithm of Particle Swarm Optimization (PSO). The system availability is optimized by evaluating the optimal values of failure and repair rate parameters concerned with the subsystem of the system.

Mathematical modeling of the multi-state repairable system is performed to develop the first-order differential equations based on the exponential distribution of the failure and repair rates. These differential equations are recursively solved to obtain the availability under normalizing conditions. The availability of the system is optimized by using the PSO algorithm. The results obtained by PSO are validated by using the Genetic Algorithm (GA).

The availability analysis of the system concludes that the cane preparation (F1) is critical of the crushing system and the optimized availability of the system using PSO is achieved as high as 87.12%.

A crushing system of the sugar plant is evaluated as it is the main system of the sugar plant. The maintenance data associated with failure and repair rate parameters were analyzed with the help of maintenance records/logbook and by conducting personal meetings with maintenance executives of the plant. The results obtained in the paper helped them to plan maintenance strategies accordingly to get optimal system availability.

This paper deals with the performance optimization and sensitivity analysis for crystallization system of a sugar plant.

Crystallization system comprises of five subsystems, namely crystallizer, centrifugal pump and sugar grader. The Chapman–Kolmogorov differential equations are derived from the transition diagram of the crystallization system using mnemonic rule. These equations are solved to compute reliability and steady state availability by putting the appropriate combinations of failure and repair rates using normalizing and initial boundary conditions. The performance optimization is carried out by varying number of generations, population size, crossover and mutation probabilities. Finally, sensitivity analysis is performed to analyze the effect of change in failure rates of each subsystem on availability, mean time to failure (MTBF) and mean time to repair (MTTR).

The highest performance observed is 96.95% at crossover probability of 0.3 and sugar grader subsystem comes out to be the most critical and sensitive subsystem.

The findings of the paper highlights the optimum value of performance level at failure and repair rates for subsystems and also helps identify the most sensitive subsystem. These findings are highly beneficial for the maintenance personnel of the plant to plan the maintenance strategies accordingly.

The study aims to examine the relationship between retailer's performance and corporate social responsibility (CSR) practices in Indian context. The article introduces a new conceptual model considering the parameters as per the stakeholder theory perspective.

The authors conducted empirical research with CSR practices (CSRP) and other parameters to evaluate the retailers' performance using stakeholder theory. The authors present the results from 292 valid responses from the Indian retailers. The study used structured equation modeling (SEM) to present the analysis and the results.

Findings indicate that CSRP along with additional constructs loyalty (L), reputation (R), customer satisfaction (CS) and competitive advantage (CA) have positive and significant impact on organizational performance (OP).

The framework will serve as a guiding tool to the management of the retail outlets to examine carefully the link among CSRP with other variables presented in the study and subsequently to the retail outlet performance. The retailers must be more focused on the expectations and demands of the customers concerning products and services for better growth of the firms.

The uniqueness of the study lies in “CSR practices enabled integrated model” to examine the performance of the organizations. The proposed theoretical model would add value to the existing literature to help the retailers in process of their performance improvement.

This paper investigates the determinants of the capital structure of large corporations headquartered in the United States and Korea. We consider five explanatory variables: profit, company size, non‐debt tax shields, growth, and business‐risk, along with several industry indicator variables as independent variables and examine, for each country, the relationship to market value based leverage ratio. With our rigid criteria for inclusion in the study, we study the top thirteen companies (by size) in each of seven industries. The majority of our findings indicate that we can generalize to Korea what has been found for Japanese companies/industries relative to the U.S.