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Studies focusing on learning based on foreign sources of knowledge

2. Literature review and conceptual framework: technological learning among

2.4. Reviewing the literature on latecomer learning for LCE technology

2.4.2. Studies focusing on learning based on foreign sources of knowledge

This section reviews the literature on international transfer of LCE technologies to firms in low and middle-income countries with a focus on whether and how it takes into consideration the concepts of technological capabilities and learning described in this Chapter. As previously discussed, international technology transfer offers latecomer firms the opportunity to access advanced technological knowledge for the development of their capabilities. The importance of international LCE technology transfer is widely acknowledged and has received much scholarly attention (e.g., Kirchherr and Urban, 2018; Lema and Lema, 2012; Ockwell and Mallett, 2012; Watson et al., 2015).

The empirical literature that focuses on international flows of LCE technology to latecomer firms in low and middle-income countries can be divided into two camps: in- depth case studies on firm-level capability accumulation and studies based on large-N approaches based on quantitative indicators. The former camp is summarised in Table 6 above. Most of these studies highlight the importance of foreign knowledge as a source for learning. They offer detailed insights about the kinds of organisational arrangement types through which local firms have accessed foreign knowledge. As they typically adopt the perspective of the latecomer firm, the studies offer detailed insights about the ways in which the latecomers integrate external knowledge and how this adds to their capability stocks.

The second camp of literature on flows of LCE technologies to latecomers is based on large-N approaches using quantitative indicators. This includes studies which use data on total inward trade or foreign direct investment (FDI) and estimate the effects that these have on aggregate carbon dioxide emissions or energy intensities at the level of the economy (e.g., Cole and Elliott, 2003; Hubler and Keller, 2010; Managi et al., 2009; Omri and Kahouli, 2014). Others collect data on trade (Glachant et al., 2013; Glachant and Dechezleprêtre, 2017) or FDI volumes (Glachant and Dechezleprêtre, 2017; UNCTAD, 2010) for specific LCE technologies and use this as a measure of technology transfer. All of these studies are limited because they focus on only a single or a limited number of indicators for international technology transfer. Moreover, they are based on relatively coarse scales. As such, they do not provide much useful insight into the dynamics of technological capability formation based on foreign sources of knowledge.

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Another set of studies uses patents to construct indicators of technology flows. This includes indicators based on counts of patented international co-inventions (Hascic et al., 2012) and counts of so-called non-resident patent filings, where the home country of the inventor is used as the country of origin of the technology (Dechezleprêtre et al., 2015, 2011; Glachant and Dechezleprêtre, 2017; Hascic and Johnstone, 2011).7 Using patent-based indicators as measures for innovation and technological diffusion has a number of well-documented limitations (e.g., see Arundel and Kemp, 2009; Hascic and Migotto, 2015). While a thorough discussion of these is beyond the scope of this thesis, it is worth mentioning that patents only capture a narrow aspect of the innovative activities that take place in practice. This is because propensities to patent differ across countries and are likely to be relatively low in countries that have poor intellectual property right enforcement measures in place. Moreover, patents only capture the output of R&D-based activities that result in inventions which meet patentability criteria. They do not capture the multitude of innovative activities that are critical for technological catch-up in latecomer firms, such as minor adaptations undertaken on externally accessed equipment or firm-internally achieved incremental innovation (Ariffin, 2010).

Yet another strand of literature uses statements pertaining to technology flows contained in the publicly available documentation of CDM projects to construct measures of international technology transfers. This includes a large number of studies that has been cited widely in the academic and grey literature (Ambec, 2017; De Coninck et al., 2007; Dechezleprêtre et al., 2009, 2008; Haites et al., 2012, 2006; Marconi, 2011; Murphy et al., 2015; Schmid, 2012; Seres et al., 2009; UNFCCC, 2010; Weitzel et al., 2015; Xie et al., 2013). This approach is limited because it only allows for the development of simplistic measures of technology transfers for individual projects (as also pointed out by Bell [2012, p.23-24]). These are mostly binary - technology transfer vs. no technology transfer - and sometimes distinguish between the poorly defined categories of equipment transfer, knowledge transfer, and equipment and knowledge transfer. Another problem with this approach is that the project developers’ statements on technology transfer, which are contained in the project documentation, are not based on any agreed upon definitions.

7 Dechezleprêtre et al. (2011) argue that non-resident patent filings can be used as a measure of international

technology transfer because inventors are likely to only patent inventions in foreign markets if they expect there to be a market for the technology. This is because patents are costly to prepare and because they become published in the local language after they have been filed, which increases the risk of imitation. For these reasons, inventors are unlikely to file patents indiscriminately.

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As such, the statements are inconsistent across projects, which raises serious doubts about their suitability as a basis for comparisons of technology transfers. Finally, this approach does not differentiate between transfers that occur for different types of technologies that are installed as part of a single CDM project.

A few studies have used social survey approaches to study how international LCE technology transfers have contributed to the formation of capability stocks at latecomer firms (Doranova et al., 2011; Gandenberger et al., 2016). While these studies can of course not go into the same level of detail about capabilities and learning mechanisms as the case study literature, they have perhaps the greatest potential to provide insights that are generalizable and that take into consideration at least some of the intricacies of the technological capability framework presented in this chapter. Unfortunately, these studies suffer from limitations with regards to their data collection procedures. In particular, they suffer from relatively low response rates and the associated risk of bias.

In conclusion, the existing literature on international transfers of LCE technology falls within one of two camps. On the one hand, there is the case study literature that provides detailed insights into capability formation dynamics among latecomers. While providing rich insights, the case study nature of this literature limits the generalizability of its conclusions. One the other hand, there are the studies that have used a variety of data sources to arrive at more generalizable results, but which either pay little attention to the issue of capability formation among latecomers or suffer from other data-related problems. There are a few exceptions that study both large numbers of firms and account for the capability framework. For example, Doranova, (2010) and Lema and Lema (2016, 2013) adopt the technological capability perspective and combine it with quantitative approaches at the firm and project-level to provide insights into the role of international technology transfer for capability formation among latecomers. In conclusion, there appears to be a need for more research which builds on the latecomer capability framework outlined in Section 2.1 and 2.2 of this chapter and which, at the same time, adopts a methodological approach which offers at least some degree of generalizability. This calls for an approach which provides micro-level insights into technological learning processes for a relatively large number of projects and/or firms. As the following section explains, this is the goal of Chapter 5.

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