The purpose of this paper is to examine the relationships between internal process improvement investments, applied channel logistics knowledge, and financial performance for make‐to‐order (MTO) and make‐to‐stock (MTS) manufacturers. This study takes the position that knowledge, specifically tacit or applied knowledge, may serve as a key indicator of organizational performance. In this study, the tacit knowledge exhibited in intentional logistics integration activities is captured in the construct applied channel logistics knowledge.
A structural equation model, controlling for firm size and demand uncertainty, is used to examine these relationships. A sampling frame of 1,264 senior manufacturing “executives” provided 222 usable surveys representing 210 firms.
The results show that for MTO firms, higher investments in internal process improvement relate to higher applied channel logistics knowledge, whereas for MTS firms, the relationship does not hold, and this difference is significant. In addition, the results indicate a positive relationship between internal process improvement investment and financial performance for MTO firms, whereas again the relationship does not hold for MTS firms. Both MTO and MTS firms show increased financial performance when applied channel logistics knowledge increases, although the increase in financial performance is significantly greater for MTO firms.
Historically, the success of integration strategies has been postulated to be equally effective for MTO and MTS firms, a “one‐size‐fits‐all” approach to improving system effectiveness. However, given the inherent differences in these manufacturing strategies, this speculation deserves further investigation and serves as the focus of this research. The use of the tacit knowledge construct applied channel logistics knowledge is also unique and of value in understanding supply chain relationships.
Birou, L., Germain, R.N. and Christensen, W.J. (2011), "Applied logistics knowledge impact on financial performance", International Journal of Operations & Production Management, Vol. 31 No. 8, pp. 816-834. https://doi.org/10.1108/01443571111153058
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