Just in time strategy and profitability analysis in financial statements

Research output: Chapter in Book/InformChapterResearch

3 Scopus citations

Abstract

The purpose of this paper is to describe some links between Just in Time (JIT) manufacturing strategy and performance financial analysis in financial statements. A rational, deductive, analytical and objective method was used; based on previous findings, a series of functions along with pre-post and linear regression analyses models are described as explicative of the relationships between JIT and financial statements analysis. Results show that Dirac function, value transformation function and transform kernel provide the foundations for a conceptual link between JIT and company performance in financial statements. Besides, the JIT relationship to business performance is explained by the following three models, selected from literature: a) pre-post model, explains changes in inventory and asset turnover, and their relationship to JIT; b) two-stage self-selection regression analysis model, explains how sales, inventory, company size and JIT adoption influence ROA changes; and c) lean manufacturing model, including JIT, allows explaining firm's financial data. The conclusion is that JIT is part of a financial sequence of analysis strongly related to the structure of financial statements and company performance.

Original languageEnglish (US)
Title of host publicationIEOM 2017- Proceedings of the International Conference on Industrial Engineering and Operations Management
PublisherSouthfield - IEOM Society International
Pages1363-1372
Number of pages10
ISBN (Print)978-1-5323-5943-9
StatePublished - Oct 25 2017
EventIEOM Bogota Conference / 1st South American Congress 2017 - Bogota, Colombia
Duration: Oct 25 2016Oct 26 2016

Conference

ConferenceIEOM Bogota Conference / 1st South American Congress 2017
Country/TerritoryColombia
CityBogota
Period10/25/1610/26/16

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

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