Background: Scaffolds are one of the three most important elements constituting the basic concept of regenerative medicine, and are included in the core technology of regenerative medicine along with stem cells and tissue engineering. Stem cells are very important technology because they are directly responsible for the regenerative treatment of the disease and the damaged tissue, but with regards to the technology and the products that use stem cells exclusively, there is a technical limitation of limited survival rate and the engraftment rate of the transplanted cell, and rather than recovering the damaged tissue fundamentally, there is a limit that the concept is more of just another medicine treatment using cells. A scaffold is a natural or synthetic biocompatible material transplanted into a human body to be used as the exclusive treatment or as an assisted method of another treatment of a disease and for the recovery of damaged tissue. Therefore, according to the characteristics of the tissue to be applied, scaffolds must have the characteristics such as the excellent biocompatibility, biodegradability, minimum immunity and inflammation, proper mechanical strength and interaction between the material and the cells. Results: The world stem cell market was approximately 2.715 billion dollars in 2010, and with a growth rate of 16.8% annually, a market of 6.877 billion dollars will be formed in 2016. From 2017, the expected annual growth rate is 10.6%, which would expand the market to 11.38 billion dollars by 2021. Meanwhile, the world scaffold element technology market was approximately 4.57 million dollars in 2013, and by increasing 13.4% annually, it is estimated to expand to 10.63 million dollars by 2020. The Korean scaffold element technology market was about 22 million dollars in 2013, and with a steady growth of approximately 13.4% every year, it is prospected to be about 52 million dollars by 2020. Conclusions: In comparison to the medical material and medicine sales growth rate, the future scaffold element technology market is judged to be higher in growth possibility.

Research objective of our study is to find the effect of technology and market dynamism on the business performances by small- and medium-sized enterprises (SME) supporting services. Technology and market dynamism have been introduced as moderating variables, utilisation degree of information provided by SME supporting services was selected as an independent variable and contribution degree to SME business performances such as revenue, export, employment and so on were selected as dependent variables. Structural equation modeling was established to analyse moderating and mediating effects on SME business performances by SME supporting services using Smart PLS programme. The SME supporting services had a direct effect on SME business performances and also indirectly influenced SME business performances via contribution degree to decision-making of SME executives. Technology and market dynamism significantly moderated the effect of decision-making of SME executives on SME business performances. It could be seen that technology and market dynamism had a mediated-moderating effect on SME business performances.

The research objective of our study is to find the route how the information provided in small- and medium-sized enterprise (SME) supporting services in South Korea affects business performances. Investigation into business performances from SME supporting services was conducted by a survey method. The survey data was statistically analysed by using SPSS program. A research model was designed by using a mediation model. In our research model, information utilisation of SME supporting services was selected as an independent variable; contribution degree to decision-making, growth of information competitiveness and customer satisfaction were introduced as mediating variables; and SME business performances, such as contribution degree to growth of current revenue, future revenue, future export and current employment, were used as dependent variables. Correlation and regression were analysed to investigate the relationship between two variables such as independent variables versus mediating variables, independent variables versus dependent variables and mediating variables versus dependent variables. The route from information provision in SME supporting services to business performances was clarified by using Baron and Kenny’s mediation model.

This research seeks to answer the basic question, “What would be the most determining factors if I perform regression analysis using several independent variables?” This paper suggests the way to estimate the proper royalty rate and up-front payment using multiple data I can get simply as input. This research analyzes the dataset, including the royalty-related data like running royalty rate (back-end payments) and up-front payment (up-front fee + milestones), regarding drug candidates for specific drug class of anticancer by regression analysis. Then, the formula to predict royalty-related data is derived using the attrition rate for the corresponding development phase of the drug candidate for the license deal, TCT (Technology Cycle Time) median value for the IPC code (IP) of the IP, Market size of the technology, CAGR (Compound Annual Growth Rate) of the corresponding market and the revenue data of the license buyer (licensee). For the anticancer (antineoplastics) drug classes, the formula to predict the royalty rate and up-front payment is as follows. $$ \mathrm{Royalty}\ \mathrm{Rate} = 9.997 + 0.063\ *\ \mathrm{Attrition}\ \mathrm{Rate} + 1.655\ *\ \mathrm{Licensee}\ \mathrm{Revenue}\ \hbox{-}\ 0.410\ *\ \mathrm{T}\mathrm{C}\mathrm{T}\ \mathrm{Median} $$ $$ \hbox{-} 1.090\ *\ \mathrm{Market}\ \mathrm{Size}\ \hbox{-}\ 0.230\ *\ \mathrm{CAGR}\ \left(\mathrm{Formula}\ 1\right) $$ $$ \begin{array}{l}\mathrm{Up}\hbox{-} \mathrm{Front}\ \mathrm{Payment}\ \left(\mathrm{Up}\hbox{-} \mathrm{front} + \mathrm{Milestones}\right) = 2.909\ \hbox{-}\ 0.006\ *\ \mathrm{Attrition}\ \mathrm{Rate} + 0.306\ *\ \\ {}\mathrm{Licensee}\ \mathrm{Revenue}\ \hbox{-}\ 0.74\ *\ \mathrm{T}\mathrm{C}\mathrm{T}\ \mathrm{Median}\ \hbox{-}\ 0.113\ *\ \mathrm{Market}\ \mathrm{Size}\ \hbox{-}\ 0.009\ *\ \mathrm{C}\mathrm{AGR}\ \left(\mathrm{Formula}\ 2\right)\end{array} $$ In the case of Equations Equation 1 to estimate the royalty rate, it is statistically meaningful at the significance level of 1 % (P-Value: 0.001); however, in the case of Equations Equation 2 to estimate the up-front payment it is statistically not meaningful (P-Value: 0.288), thus requiring further study. This research is limited to the relationship between multiple input variables and royalty-related data in one drug class of anticancer (antineoplastics). Valuation for the drug candidate within a specific drug class can be possible, and the royalty rate can be a variable according to drug class and licensee revenue.

This study was conducted with a team of senior managers at a Korean shipyard in an effort to elicit particular motivators for implementing management by walking around (MBWA). To identify the key motivators and communication issues associated with them, a theoretical framework was produced based on the key tensions of social psychology of communication and upward communication as well as modern organizational theories. For this qualitative research analysis, 12 semi-structured interviews were conducted face-to-face with the executives; the data were then supplemented by five field observations during MBWAs at the shipyard. Coding frame was used to organize modal salient themes for thematic analysis. The organizational and individual motivators identified were then analyzed in-depth to elicit communicational factors underlying these motivators. While identifying 10 salient motivators as organizing themes, the research concludes that MBWA is a contingent management strategy intended to promote upward communication within organizations.