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Modeling influence of business excellence parameters on sustainable high performance of organizations

Abstract

Organizations aspire to have sustainable high performance in order to have competitive advantage in the market. Business excellence models provide frameworks to be applied by organizations in order to develop thoughts, so that adequate actions be taken in a systematic and structured way to accomplish sustainable high financial as well as non-financial performance. Various business excellence models proposed by organizations as well as researchers are discussed. In this paper a mathematical model is proposed in which independent variables are: top management team characteristic, mission vision and core values, technology and innovation, and customer focus. Motivation and culture are moderating variables. Government policies and global economy are intervening variables. The financial and non-financial performance, are dependent variables. The proposed model would yield corresponding regression equations, representing stated hypotheses to be tested for the collected data from the field for the chosen business organization. Further correlation coefficient can also be computed to check the relationship between variables. From the estimated regression equations, through various tests, the elasticity of the coefficients of model parameters and their statistical significance can be investigated. Adequate recommendations can then be made to achieve the sustainable high performance for the selected organization.

Corporate Social Responsibility ReportingEnvironmental Sustainability in BusinessExcellenceRegression analysisCompetitive advantageStructural equation modelingVariablesOrder (exchange)Government (linguistics)BusinessOperational excellenceEconomics
Citations
1
FWCI
0.22
field-weighted impact
References
2
Percentile
69%
vs. same field & year
References
Importance of moderating and intervening variables on the relationship between independent and dependent variables
International Journal of Statistics and Applied Mathematics · 2019 · 17 citations
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