Purpose: Through the resource-based view (RBV) and contingency theory, this study empirically investigates the impacts of smart manufacturing systems' maturity levels on the performance of small and medium-sized enterprises (SMEs). Moreover, it aims to examine how industry types (i.e. high- and low-tech industries) and human-resource factors (i.e. the proportion of production workers to total workers) as contingency factors influence the effects of smart manufacturing systems.Design/methodology/approach: The study conducted an empirical investigation of a sample of 163 Korean manufacturing SMEs. This study used an ordinary least squares regression to examine the impacts of the maturity levels of smart manufacturing systems on financial performance. Moreover, the impacts on operational efficiency were analysed using data envelopment analysis based on bootstrap methods and Tobit regression.Findings: The RBV results indicate that the higher the maturity levels of smart manufacturing systems, the higher the financial performance and operational efficiency. Moreover, based on contingency theory, this study reveals that the effect of the maturity levels of smart manufacturing systems on financial performance and operational efficiency depends on firms' industry types and the proportion of production workers.Research limitations/implications: This study shows that the introduction of smart manufacturing systems can help SMEs achieve better financial performance and operational efficiency. However, their effectiveness is contingent on firms' industry types and the characteristics of their human resources.Practical implications: Since the effects of the maturity levels of smart manufacturing systems on SME performance differ depending on their industries and the characteristics of human resources, managers need to consider them when introducing or investing in smart manufacturing systems.Originality/value: Based on the RBV and contingency theory, this is the first empirical study to examine the moderating effects of industry types and the proportion of production workers on the impacts of the maturity levels of smart manufacturing systems on the financial performance and operational efficiency of SMEs.

Purpose: This study examines how employee participation in the performance measurement system affects the relationship between authentic leadership and job satisfaction.Design/methodology/approach: Survey data for this study were obtained from 322 employees in South Korea. Structural equation modeling and bootstrapping method were applied to test the proposed hypotheses.Findings: This study first confirmed that authentic leadership positively affects job satisfaction. In addition, the results showed that employees' participation in developing performance measures partially mediated the relationship between authentic leadership and job satisfaction.Practical implications: The findings imply that employees' participation in developing performance measures, which is promoted by authentic leadership, can be a strategy for enhancing job satisfaction. Therefore, in order to increase employees' job satisfaction, organizations need to promote employee participation in the performance measurement system and develop authenticity in leaders.Originality/value: Employees' participation in developing performance measures has not been investigated sufficiently from the leadership perspective. This study expands the literature on the influence of employee participation in the performance measurement system on work-related outcomes by demonstrating that employees' participation in developing performance measures partially mediates the effect of authentic leadership on employee job satisfaction.

This study aims to identify the changes in the economic relations between industries resulting from the dissemination of renewable energy in Korea. Although previous studies have examined the ripple effect of renewable energy using an input-output table, there are limited studies that have performed an accurate analysis due to the absence of real economic transaction data for renewable energy and other industries. Thus, an input-output analysis was performed using actual data for 2010 and 2015 as well as 2020 estimated by RAS method. Backward and forward linkage effects and inducement effects were estimated. Specifically, the renewable energy value chain industries were classified into Raw material, Machine part, Infra structure, and End product. The main findings are: (1) the effect ratio of renewable energy industry decreased to 0.9572 reaching a similar level to the existing electric power industry; (2) the production inducement effects were 1.1278(2010), 0.7016(2015), and 0.7203(2030), and value-added inducement effects were 0.6043(2010), 0.3860(2015), and 0.4069(2020); and (3) the proportion of inducement effect on the service industry decreased approximately from 40% to 34%. These findings show how the renewable energy industry has changed from the early stages to the present and its economic importance in other industries resulting from renewable energy production and distribution. This study provides basic data for diagnosing the economic spillover and establishing energy policies due to the dissemination of renewable energy.

This study investigates the R&D persistence with different external conditions based on US listed manufacturing firms for the period 2011–2019. Specifically, we analyze whether the fluctuation of R&D investment is related to short-term changes in sales, and how industrial technological intensity and competitive environment influence the relationship. We used the cost asymmetry model to identify the changes in R&D investment by sales behaviour. The results showed that the R&D investment of high-tech firms was stickier when sales declined as compared to low-tech firms. Therefore, R&D persistence tends to be strong in high-tech firms. In addition, R&D persistence was weakened by the competitive environment, and this finding was more pronounced for high-tech firms than for low-tech firms. This study has academic implications in the empirical analysis of the relationship between R&D persistence and external characteristics from a dynamic perspective.

SMEs need to protect their innovation outcomes and increase profits from their innovations in order to make their growth sustainable. The appropriability regime enables SMEs to secure financial returns on their R&D investment so that SMEs can continuously invest in innovation and obtain financial gains. However, the appropriability regime can change the effects of protecting innovation outcomes depending on the capacity of knowledge exploration, especially for SMEs, and previous studies have not discussed these issues. Thus, the main objective of this paper is to explore how the knowledge exploration capacity affects the relationship between different types of appropriability regimes and innovation performance. Multivariate regression is used to analyze the manufacturing SMEs sampled from the Korea Innovation Survey 2007 (KIS 2007). Our results demonstrate that both formal and informal appropriability regimes can improve firm’s innovation performance. Furthermore, although both inventive and absorptive capacity have positive moderating effects on the relationship between the informal appropriability regime and innovation performance, the inventive capacity moderates negatively the relationship between the formal appropriability regime and innovation performance. As a whole, the significance of this paper lies in providing further understanding of the different types of appropriability regimes and knowledge exploration capacity in SMEs.