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The purpose of this study is to investigate the influence of light intensity and sources of carbon and nitrogen on the cultivation of Spirulina maxima.

Cultures were carried out in a modified Zarrouk medium using urea, sodium acetate and glycerol. A Taguchi experimental design was used to evaluate the effect on the production of biocompounds: productivities in biomass, carbohydrates, phycocyanin and biochar were analyzed.

Statistical data analysis revealed that light intensity and sodium acetate concentration were the most important factors, being significant in three of the four response variables studied. The highest productivities in biomass (46.94 mg.L⁻¹.d⁻¹), carbohydrates (6.11 mg.L⁻¹.d⁻¹), phycocyanin (3.62 mg.L⁻¹.d⁻¹) and biochar (22, 48 mg.L⁻¹.d⁻¹) were achieved in experiment 4 of the Taguchi matrix, highlighting as the ideal condition for the production of biomass, carbohydrates and phycocyanin.

Sodium acetate and urea can be considered, respectively, as potential sources of carbon and nitrogen to increase Spirulina maxima productivity. From the results, an optimized cultivation condition for the sustainable production of bioproducts was obtained.

This work focuses on the study of the influence of light intensity and the use of alternative sources of nitrogen and carbon on the growth of Spirulina maxima, as well as on the influence on the productivity of biomass and biocompounds. There are few studies in the literature focused on the phycocyanin production from microalgae, justifying the need to deepen the subject.

The purpose of this study is to determine the enablers of the quality of work life (QWL) of employees working in the Garment industries.

The study was carried out in a fivefold step. In the first step, the enablers of QWL were identified through an exhaustive literature survey, in the second step identified vital few components through Pareto analysis. Then the third step was followed by exploratory factor analysis (EFA) to further, to identify the precise components and validate the same using confirmatory factor analysis in fourth step. The final step included interpretive structural modeling and Cross-Impact Matrix Multiplication Applied to Classification analysis to model the validated components and determine the interrelationships and linkages.

Predominant QWL enablers of employees working in the garment industries are training and development, satisfaction in job, compensation and rewards, relation and co-operation, grievance handling, work environment, job nature, job security and facilities.

In this study, the interpretive structural model is designed based on the opinion of the experts who are working in the garment industry considering the responses from employees in garment sectors. The framework can be extended further to the other sectors.

In future, the researchers in QWL may develop a model to quantify the level of employees’ QWL who are working in different sectors. Enablers of QWL are essential, and based on this further statistical analysis can be carried out. This study will provide limelight to the researchers in choosing the valid and reliable set of enablers for the empirical studies. Organizations can get benefit by implementing the outcome of this research for the enhancement of the QWL of employees.

The study was carried out in 133 garment industries where 851 workers constituted the final valid responses that were considered for analysis. The outcomes from the study help administrators, policy and decision-takers in taking decisions to enhance QWL.