Investment in tangible non-current assets and financial performance of food manufacturing firms in Nigeria

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Nigeria has a serious food crisis, which can be attributed to poor management of tangible non-current assets by food manufacturing companies, which leads to low productivity, product wastages, and ineffective processing and distribution of products culminating in low return on assets. Therefore, this study examined the effects of changes in tangible non-current assets on return on assets of food manufacturing firms in Nigeria. The study employed an ex-post facto research approach with data obtained from top food manufacturing companies quoted on the Nigerian Stock Exchange from 2008 to 2020. The finding revealed that tangible non-current assets play a very important role in the return on assets of food manufacturing companies in Nigeria. Specifically, the study revealed that changes in investment in land and buildings, plants and machineries and motor vehicles have a statistically significant influence on return on assets (ROA) of quoted food manufacturing companies (FMCs). It was concluded that an increase in tangible non-current assets enhances the return of assets of food manufacturing companies. In line with the findings of this study, it was recommended that considerable attention should be paid by the management of FMCs to efficient utilization of tangible non-current assets because it is only when non-current assets are efficiently utilized that they would have significant contributions to or implications for the return on assets of the business.

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    • Table 1. Changes in investment in land and buildings and return on assets
    • Table 2. Changes in investment in plants and machineries on return on assets
    • Table 3. Changes in investment in motor vehicles on return on assets
    • Table 4a. Model summary for hypothesis one
    • Table 4b. ANOVA result for hypothesis one
    • Table 4c. Coefficients result for hypothesis one
    • Table 5a. Model summary for hypothesis two
    • Table 5b. ANOVA result for hypothesis two
    • Table 5c. Coefficients result for hypothesis two
    • Table 6a. Model summary for hypothesis three
    • Table 6b. ANOVA result for hypothesis three
    • Table 6c. Coefficients result for hypothesis three
    • Conceptualization
      Marian Mukosolu Okobo, Robinson Onuoha Ugwoke, Ekom Etim Akpan
    • Data curation
      Marian Mukosolu Okobo, Robinson Onuoha Ugwoke, Ekom Etim Akpan
    • Formal Analysis
      Marian Mukosolu Okobo, Robinson Onuoha Ugwoke, Ekom Etim Akpan
    • Funding acquisition
      Marian Mukosolu Okobo, Ekom Etim Akpan
    • Investigation
      Marian Mukosolu Okobo, Robinson Onuoha Ugwoke, Ekom Etim Akpan
    • Methodology
      Marian Mukosolu Okobo, Robinson Onuoha Ugwoke, Ekom Etim Akpan
    • Project administration
      Marian Mukosolu Okobo, Robinson Onuoha Ugwoke, Ekom Etim Akpan
    • Resources
      Marian Mukosolu Okobo, Ekom Etim Akpan
    • Software
      Marian Mukosolu Okobo, Robinson Onuoha Ugwoke, Ekom Etim Akpan
    • Validation
      Marian Mukosolu Okobo, Robinson Onuoha Ugwoke, Ekom Etim Akpan
    • Visualization
      Marian Mukosolu Okobo, Robinson Onuoha Ugwoke, Ekom Etim Akpan
    • Writing – original draft
      Marian Mukosolu Okobo, Ekom Etim Akpan
    • Writing – review & editing
      Marian Mukosolu Okobo, Robinson Onuoha Ugwoke, Ekom Etim Akpan
    • Supervision
      Robinson Onuoha Ugwoke