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This research addresses the contribution that technical skills and cognitive abilities make toward technological efficiency in small and medium enterprises. While most of the literature on skill-biased technological change focuses on large corporations, this exploratory research tries to close the gap in the literature and addresses the impact of technical training, age, and educational level of the workforce on the fit between technological change and organizational innovation in small and medium-sized enterprises. The results suggest that the impact of the workforce structure on efficiency is a function of the level of technological change.

The most recent technological transformation of modern economies is the adoption of information technology (IT). A central question in management theory is how to deal with organizational adaptation to IT-led technological change. A growing body of empirical evidence shows that proper adaptation to this technological change has a positive impact on firms' efficiency (Dedrick, Gurbaxani, & Kraemer, 2003). However, heterogeneity in organizational characteristics can explain the differences in the outcomes of this adaptation process (Bresnahan et al., 2002 and Brynjolfsson and Hitt, 2000). Starting with the paper by Milgrom and Roberts (1990), a large body of literature supports the complementarity hypothesis between technology, skills and organization, and suggests that modern technological and organizational changes are complementary with skilled workers. The main aim of this study is to understand the nature of the skill-biased technological change (SBTC) in small and medium enterprises (SMEs). While several studies explain the complementarities between technological change, organizational innovation and skills for large organizations, few studies address the role of these complementarities in SMEs. SMEs are enterprises which employ fewer than 250 persons and whose annual turnover does not exceed EUR 50 million, or whose annual balance-sheet total does not exceed EUR 43 million (European Commission, 2003). These small businesses make a significant contribution to gross domestic product (GDP) and employment in many economies of the world. The differences between SMEs and large corporations in terms of resources and organizational sophistication cast some doubts on the applicability of previous SBTC research on SMEs. Compared to large firms, small businesses tend to have simple and centralized structures, lower levels of specialization, less standardized procedures, less financial resources and less managerial and professional expertise (Thong, Yap, & Raman, 1996). These limitations suggest that SMEs do not have the same skills and capabilities to profit from SBTC. The main contribution of this paper is the study of the impact on SMEs' efficiency of the complementarities between skills and technological change. The main hypothesis of this research is that technology adoption and the skill composition of the workforce of SMEs are complementary factors in the production function. More specifically, this study proposes that technological change in SMEs causes a shift in the demand for both cognitive and technical skills. Technological change reduces the costs of communication and supervision, fosters organizational innovations, and flattens organizational structures (Bertschek and Kaiser, 2004, Bresnahan et al., 2002, Brynjolfsson and Hitt, 1998 and Garicano and Rossi-Hansberg, 2006). In these flattened organizations, workers are less likely to perform repetitive, specialized tasks, but rather are responsible for a wider range of tasks within teams. Further, the decentralization of organizational decision-making increases the tasks' variability and complexity. Following technological change, the redefinition of tasks and responsibilities fosters firms' demand for cognitive and technical skills (Bartel et al., 2007, Black and Lynch, 2001, Bresnahan et al., 2002 and Nielsen and Lassen, 2012). More advanced technical skills facilitate the absorption of new technology, while cognitive abilities help workers to make better decisions through more accurate mental models. Consequently, these new skills affect the impact of technological change on firm's performance (Acemoglu, 2002, Autor et al., 2003 and Garicano and Rossi-Hansberg, 2006). However, previous literature provides little evidence of the effect of technological change, and cognitive and technical skills on the efficiency of SMEs. To close this gap in the literature, the main contribution of this paper is to explore the interactions between cognitive and technical skills and IT-led technological change in SMEs. The next section reviews the key literature dealing with the fit between skills and technological change with a special focus on SMEs. Section 3 describes the data and the empirical methodology. Section 4 presents the results obtained and Section 5 discusses the results. Finally, Section 6 presents the main conclusions of this research.

SMEs are a crucial component of economic growth but curiously understudied in management research (Tansky & Heneman, 2003). This study tests how skills shape the impact of technological change on SMEs' efficiency. From a theoretical point of view, the study brings out the debate on the unexplored relationship between the intensity of technological change, the skills and abilities of the workforce and the returns on technological change. This research suggests that SMEs should refocus recruiting and training practices according to the specific intensity of technological change. In fact, this research shows that highly educated workforces may have a negative impact on the returns on technological change for moderate levels of technological change. The research also provides empirical evidence on the role played by age on the returns on technological change. The negative contribution of young workforces for high levels of technological change suggests that the literature on human models and the research stream on managerial decision-making may provide useful insights. Limitations of this study mean that some caution should be exercised in interpreting its results. First, data sources do not provide detailed information on the organizational innovations. Second, the AMETIC survey is not built as a panel, which prevents longitudinal analysis and the study of delayed effects of technological change and organizational innovations. The specific nature of Spanish economy, with a serious problem of over-qualification and a labor force with low technical skills (Marzo-Navarro, 2007), may introduce some bias in the results of this study. Finally, SABI does not provide reliable data to compute ROI, ROA or Value Added as other measures of productivity. With a few exceptions (Bartel et al., 2007) most of the research on SBTC and productivity treats cognitive skills as a black box. Given the importance of understanding the role of cognitive skills in the productivity impact of technological change for human resource practices such as recruiting or training and public policies, future research would benefit from a careful study of the effect of specific categories of cognitive skills on the productivity impact of SBTC. Another fruitful avenue for future research is the attempt to explain the roots of the differences between large and small firms in terms of substitution parameters between skilled workers and capital. The lack of robust data related to the stock and flow of technical skills provides an opportunity for future research to examine the actual contribution of technical training to productivity. Finally, this research puts forward the need for further research on the current foundations of age-biased technological change.