This paper investigates the impact of disclosure activity on the stock market liquidity under the Regulation Fair Disclosure in Korea. Economic theories generally support that more disclosures reduce the level of information asymmetry, increase stock liquidity, and thus decrease the costs of equity capital. A series of empirical studies examine the impact of disclosure policy, however, they mainly focus on the relationship between disclosure and costs of equity capital, but not on the relationship between disclosure and liquidity especially in Korea. Since the disclosure theory is driven with a joint hypotheses, it is needed to investigate the relationships by stage. Using various measures of market liquidity, this study finds that disclosure activity is positively related with market liquidity. And the comparative analysis shows that both SMEs and large firms have disclosure impacts, but they affect this relation differently. Various sensitivity tests show that the relation is robust. The findings of this paper have an implication that the impact of liquidity and also the impact of information environment (i.e., SMEs vs. large firms) should be considered in examining the relation between disclosure and costs of equity capital.

The purpose of this paper is to identify the suitable variables for the financial distress prediction models and compare the accuracy of MDA (multiple discriminant analysis), LA (logit analysis) and ANNs (artificial neural networks) for the early warning signal of SMEs (small and medium enterprises) start-ups in renewable energy industries. The research methods are MDA, LA and ANN which have been widely used in the world. Dataset was composed of 100 renewable energy SMEs in KOSDAQ and under the act of external audit of stock companies. The financial data of each company over the period from 2006 to 2013 were collected from KIS-Value.
We found the result that 4 financial ratios were statistically significant and the accuracy of MDA is 92.9%, while that of LA and ANN are 94.3%, 87.5% respectively for the one year before the bankruptcy in 2013. The accuracy rate of bankruptcy prediction for the “one year before(T-1)” is better than for the “two year before (T-2)” to all 3 models. The importance of this study was to demonstrate empirically that financial distress prediction models are applicable to the SMEs start-ups in Korea renewable energy industry as an early signal of bankruptcy.

An industrial cluster has been widely accepted as a territorial agglomeration of firms, which is effective for knowledge diffusion contributing to the national innovation system and regional development in an economy. Accordingly, a growing number of empirical works support the positive impact of industrial clusters on firm innovation or performance mainly by investigating differences in innovation and performance between clustering and non-clustering firms. These works have mainly focused on figuring out exogenous factors of clusters, such as infrastructural resources, labor pools, and local endowments, originating externally. However, the success of clustering firms also depends on endogenous factors including formal economic transactions and social interactions for the exchange of knowledge and information among members within industrial clusters.
Although previous study has argued that firms are able to benefit from the knowledge spillover of the clusters, referring to learning regions, it is unreasonable to simply assume that positioning in the clusters would lead to active knowledge exchange among cluster members. In this context, organizational leaning is regarded as an effective instrument allowing firms to acquire, exploit, and refine external knowledge contributing to business performance. Despite the importance of organizational learning in clustering firms, our understanding of which learning initiatives are needed for small and medium-sized enterprises (SMEs) to take advantage of the spillover effect of industrial clusters has fallen short of practical and research demands.
The primary purpose of this study is to empirically examine the possible linkages among industrial cluster involvement, organizational learning capability, and firm performance of clustering SMEs. Starting from reviewing the literature and its limitations, we propose research hypotheses as two fold: (1) clustering SMEs possessing high levels of industrial cluster involvement and organizational learning capability would produce better performance in business than those who do not, and (2) clustering firms’ capability for organizational learning would play a pathway linking between their involvement in industrial cluster and performance. In a sample of 258 SMEs within industrial clusters in Korea, we tested the structured research model consisting of traded and untraded interdependences for industrial cluster involvement, absorptive and transformative capability for organizational learning capability, and firm performance through hierarchical regression analysis.
The results revealed that traded and untraded interdependences, the two constructs of industrial cluster involvement had positive effect on firm performance. The positive linkage of organizational learning capability, represented by absorptive and transformative capability, with firm performance was also confirmed. It was notable that organizational learning capability mediated fully the positive linkage between firms’ involvement in industrial clusters and performance. The primary contribution of this study is its attempt to provide a comprehensive approach in analyzing SMEs’ industrial cluster involvement in terms of their traded and untraded interdependences. Moreover, this study expands upon the importance of enhancing organizational learning and relevant capabilities from the perspective of clustering SMEs. Detailed implication and contribution of this study are discussed in the conclusions.

This paper analyzes the effect of SME-large firm relationships on SMEs’ investment in a Schumpeterian framework, and discusses the potential role of financial sector in tackling the problem given relevant information such as the Win-win growth index of Korea. Due to the hold-up issues caused by relationship-specific investment of SMEs, large firms have a strong incentive to behave opportunistically by slashing the ex post price of SME’s intermediate product. This tendency has become stronger as the time span of SME-large firm relationship has gotten shorter and shorter due to rapid changes in technologies and globalization. In analyses using a Schumpeterian growth model and related simulations, this hold-up problem significantly reduces SMEs’ incentive to undertake both equipment investment and R&D, which, in turn, reduces the revenue basis of the financial sector. Therefore, financial sector potentially has a strong incentive to solve this problem as long as they have access to relevant information such as the fairness in price settings and contracts which are intended to be provided by Korea’s Win-win growth index.

Capital market is imperfect in reality. All firms including both large corporations and small and medium enterprises (SMEs) are subject to financial constraints. Hence they hold cash or cashable assets that yield almost zero returns. Among others, precautionary motive or pecking order theory seem to be most appropriate for explaining SMEs’ cash holdings since cash holding has an insurance effect. In this study, we empirically show that ROE or ROA is higher for SMEs, when they hold more cash. From the results we can infer that SMEs can enjoy higher chance of protection of poor performance through the insurance effect of cash holdings.