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DOI: 10.14569/IJACSA.2023.0140869
PDF

Enhancing Startup Efficiency: Multivariate DEA for Performance Recognition and Resource Optimization in a Dynamic Business Landscape

Author 1: K. N. Preethi
Author 2: Yousef A. Baker El-Ebiary
Author 3: Esther Rosa Saenz Arenas
Author 4: Kathari Santosh
Author 5: Ricardo Fernando Cosio Borda
Author 6: Anuradha. S
Author 7: R. Manikandan

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 8, 2023.

  • Abstract and Keywords
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Abstract: Startups encounter a variety of difficulties in maximising their performance and resource allocation in the dynamic business environment of today. This study employs a two-stage methodology to address the challenges faced by startups in optimizing their performance and resource allocation in the dynamic contemporary business environment. The research utilizes an advanced Data Envelopment Analysis (DEA) technique to identify the factors influencing startups' efficiency. In the first stage, the relative efficiency of startups is assessed by comparing their inputs and outputs through DEA, a non-parametric approach. This analysis not only reveals the successful startups but also establishes benchmarks for others to aspire to. By examining the efficiency scores, critical factors that significantly impact startup performance can be identified. In the second stage, a logistic approach is employed to predict the performance of startups based on these discovered factors. This prediction model can be valuable in making informed decisions regarding resource allocation, aiding startups in their survival and development endeavors. This study introduces a novel two-stage methodology, combining advanced Data Envelopment Analysis (DEA) with predictive modeling, to uncover the key factors influencing startup efficiency. By evaluating relative efficiency and predicting performance based on these factors, it offers a comprehensive approach for startups to strategically allocate resources and enhance overall performance in present dynamic business environment.

Keywords: Startup efficiency; data envelopment analysis; logistic approach; resource allocation; dynamic business landscape

K. N. Preethi, Yousef A. Baker El-Ebiary, Esther Rosa Saenz Arenas, Kathari Santosh, Ricardo Fernando Cosio Borda, Anuradha. S and R. Manikandan, “Enhancing Startup Efficiency: Multivariate DEA for Performance Recognition and Resource Optimization in a Dynamic Business Landscape” International Journal of Advanced Computer Science and Applications(IJACSA), 14(8), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140869

@article{Preethi2023,
title = {Enhancing Startup Efficiency: Multivariate DEA for Performance Recognition and Resource Optimization in a Dynamic Business Landscape},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140869},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140869},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {8},
author = {K. N. Preethi and Yousef A. Baker El-Ebiary and Esther Rosa Saenz Arenas and Kathari Santosh and Ricardo Fernando Cosio Borda and Anuradha. S and R. Manikandan}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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