Depreciation and transfer of knowledge: an empirical exploration of a shipbuilding process

Abstract

It is well known from the psychological literature that knowledge acquisition (learning) and knowledge depreciation (unlearning) are governed by quite different rules. We propose a new learning curve model that measures acquisition of knowledge and depreciation in a single framework but governed by two different rules. The model considers that knowledge is acquired both by doing and from the experience of others. It also assumes that knowledge depreciates, if it does, continuously over time. We empirically demonstrate the applicability of our model using a dataset based on the construction of homogeneous ships in sixteen different shipways of a shipyard. It is observed that learning by doing (or direct learning) is the major source of productivity growth. Learning from others (or indirect learning) is also found to be sizable. The potential contribution to productivity of indirect learning is about 40% of the contribution of direct learning. It is also observed that knowledge indeed depreciates and it does so rapidly. Only about three quarters of knowledge available at the beginning of a month would remain by the end of the month due to forgetting. Therefore, if depreciation of knowledge or indirect learning (the transfer of knowledge) in a learning curve analysis is ignored, estimation of production rates and costs would be seriously biased.

The effect of worker learning on manual order picking processes

“…Learning that results from repetitive manual work in industrial settings has been studied in empirical works, see for example Ittner et al (2001), Macher and Mowery (2003) and Nembhard (2000), who studied manual assembly production processes. Further empirical evidence for learning in production can be found in Hinze and Olbina (2009) and Thomas et al (1986), who studied construction processes, and in Kim and Seo (2009), who analyzed shipbuilding processes. Works that investigated learning in laboratory settings are the ones of Kvålseth (1978), Bailey (1989) and Shtub et al (1993), for example.…”

Sources and Consequences of Knowledge Depreciation

“…Such high rates of knowledge depreciation basically imply that after a year only 0% to 5% percent of the original knowledge of an organization remains. Kim and Seo (2009) arrive at similar high depreciation rates of some 26% per month in their analysis of Liberty ships manufacture during WWII (even if earlier studies on the same case, e.g. Thompson (2007) report much lower rates of 4% to 6% per month, highlighting the large uncertainty and challenges involved in estimating knowledge and its depreciation rates).…”

Intra-network knowledge roles and division performance in multi-business firms

“…The receiver divisions are, therefore, usually the beneficiaries of devaluated knowledge resources which are probably subjected to spillovers to competitors (Kogut and Zander, 1992). Existing empirical studies on learning curves indicate that the rate of knowledge depreciation is generally high in contexts as diverse as shipbuilding (Kim and Seo, 2009) or pizza retailing (Darr et al, 1995), but the problem of knowledge depreciation is exacerbated at even higher rates when knowledge is transferred. In a study of the telecommunications industry, Williams (2007) finds that the value of knowledge that is transferred depreciates quickly just after the inter-unit transference takes place.…”