Stimulators of third-party logistics performance of supply chains in the Nigerian manufacturing industry
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DOIhttp://dx.doi.org/10.21511/ppm.21(3).2023.14
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Article InfoVolume 21 2023, Issue #3, pp. 176-188
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Creative Commons Attribution 4.0 International License
The COVID-19 disruption of supply chains has motivated manufacturing companies in Nigeria to build and maintain supply chain visibility, robustness, and resilience to remain third-party logistics providers. It is vital to have an adequate understanding of third-party logistics performance drivers. Most studies have concentrated on third-party logistics capability, while few others explored the impact of relational governance structures on performance. However, studies examining the synergy between third-party logistics capability and relationship management are scarce. The purpose of this study is to investigate the stimulators of third-party logistics performance in the Nigerian manufacturing industry. A descriptive survey, e-mail questionnaire, and PLS-SEM approach was used to collect and analyze the data from a sample of 364 manufacturing companies in Nigeria. The findings indicated that relationship management has a significant positive association with third-party logistics capability (β= 0.785, t = 3.457, p < 0.001); relationship management has a significant negative association with supply chain risk (β= –0.209, t = 4.149, p < 0.001); third-party logistics capability has a significant negative association with supply chain risk (β = –0.620, t = 3.199, p < 0.001); supply chain risk has a significant negative association with logistics performance (β= –0.695 t = 5.396, p < 0.001). Hence, relationship management, third-party logistics capability, and supply chain risk are drivers of third-party logistics performance. Therefore, supply chain partners should manage their relationships to strengthen third-party logistics capability and reduce all kinds of uncertainties and risks.
- Keywords
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JEL Classification (Paper profile tab)M11, L25
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References63
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Tables3
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Figures2
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- Figure 1. Proposed research model
- Figure 2. PLS-SEM output of hypothesized relationships and the structural model
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- Table 1. Items’ factor loadings, reliability, and validity (AVE)
- Table 2. Construct correlations and discriminant validity
- Table 3. Estimated results of the structural model and hypotheses tests outputs
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