Analysis of the Financial Efficiency of Companies in the Industrial Sector during COVID-19: Case Study in Peru

Lucero Sovero Rivera, Nicole Ninamango Origuela, Grimaldo Quispe Santivanez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The pandemic has created an environment of considerable uncertainty, forcing companies to efficiently manage their resources to optimize their profits, prevent falling revenues, sustain the chain of payments and preserve employment. The objective of this research is to apply the Data Envelopment Analysis (DEA) method to know the financial impact of the COVID-19 crisis on Peruvian companies in the industrial sector, which are listed on the Bolsa de Valores de Lima. Multi-criteria model and correlation analysis were used for the validation of financial ratios, DEA method was used to evaluate efficiencies and Malmquist Productivity Index (MPI) to analyze changes in performance by quarter. Results indicate that 77% of companies are inefficient, equity items and administrative expenses are the most crucial for these companies to improve their performance; in addition, there is a deterioration of-31.5% in the total productivity of the sector mainly caused by the decrease in technological progress. This research offers decision-makers a tool that allows them to devise strategies to face the continuing financial crisis and promote investment in the use of technologies that may contribute to the improvement of productivity. copy; 2022 IEEE.

Original languageAmerican English
Title of host publication2022 IEEE World AI IoT Congress, AIIoT 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages59-64
Number of pages6
ISBN (Electronic)9781665484534
DOIs
StatePublished - 2022
Event2022 IEEE World AI IoT Congress, AIIoT 2022 - Seattle, United States
Duration: 6 Jun 20229 Jun 2022

Publication series

Name2022 IEEE World AI IoT Congress, AIIoT 2022

Conference

Conference2022 IEEE World AI IoT Congress, AIIoT 2022
Country/TerritoryUnited States
CitySeattle
Period6/06/229/06/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

  • COVID-19
  • data envelopment analysis
  • financial efficiency
  • industrial sector

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