The design and use of performance measurement innovations and organizational outcomes in Nigerian listed companies


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Performance measurement innovations (PMI) provide frameworks for the improvement of organizational performance. While developed economies have widely accepted PMI, little is known about their design and use in developing economies. This study aimed to investigate the relationship between the design and use of PMI and organizational outcomes among listed firms in Nigeria. Partial least squares structural equation modeling was adopted for the analysis using cross-sectional survey data comprising 126 corporate managers in the sampled listed companies. The results showed that all the path coefficients for design of PMI and customer perspective (β = 0.325, p < 0.0001), financial (β = 0.314, p < 0.0001), internal business process (β = 0.346, p < 0.0001), and learning and growth perspectives (β = 0.367, p < 0.0001) were significantly positive. This suggests that designing performance measures to include a diversity of measurement incorporating financial and non-financial measures would positively affect organizational outcomes. Besides, diagnostic use was found to have a negative effect on customer perspective (β = –0.315, p < 0.01), while the interactive use (β = 0.411, p < 0.01) of PMI demonstrated a positive effect on it. This implies that using PMIs in a diagnostic manner brings about a negative image of the customer perspective, but it is divergent for interactive use.

The authors sincerely appreciate Covenant University, Nigeria, for sponsoring this publication.

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    • Figure 1. Final bootstrapped structural model showing the significance
    • Table 1. Summary of relevant studies on diagnostic and interactive uses, design of performance measurement innovations, and organizational outcomes
    • Table 2. Quality assessment for the final measurement model
    • Table 3. HTMT ratios
    • Table 4. Path coefficients for design and organizational outcomes
    • Table 5. Path coefficients for nature of use and organizational outcomes
    • Table 6. Coefficient of determination and predictive relevance
    • Table 7. Inner Variance Inflation Factor (VIF)
    • Table A1: List of Indicators in the Final Structural Model
    • Conceptualization
      Folashade Owolabi
    • Formal Analysis
      Folashade Owolabi
    • Methodology
      Folashade Owolabi
    • Software
      Folashade Owolabi
    • Validation
      Folashade Owolabi
    • Writing – original draft
      Folashade Owolabi
    • Writing – review & editing
      Folashade Owolabi, Uwalomwa Uwuigbe
    • Resources
      Solabomi Ajibolade, Uwalomwa Uwuigbe
    • Supervision
      Solabomi Ajibolade, Uwalomwa Uwuigbe
    • Visualization
      Solabomi Ajibolade