• International Commerce and Information Review
• /
• v.11 no.1
• /
• pp.139-155
• /
• 2009

This study investigates empirically the export competitiveness of Korea and Japan in America by calculating 4 indexes such as market share index(MSI), export similarity index(ESI), market comparative adventage index(MCAI) and market share expansion ratio(MSER)-export similarity deepening ratio(ESDR). The empirical finding of this analysis shows that Korea is competitive in the labor-intensive products and Japan in the technology-intensive products. This result also meets the general understandings that Japan is superior to Korea in the export competitiveness such as value added of goods, etc. Therefore, in order to strengthen the export competitiveness of Korea in the US market, it's desirable for our firms and government to improve the quality of product ranges by developing technologies focused on the higher value-added products.

• Knowledge Management Research
• /
• v.20 no.1
• /
• pp.175-194
• /
• 2019

In order to overcome the limitation of market orientation concept, Narver et al. (2004) have extended the original concept into two dimensions, responsive market orientation (RMO) and proactive market orientation (PMO), respectively. Yet, there has been very limited empirical studies that analyzed the differential effects of each market orientation on firm outcomes, especially in the Korean context. We analyze the impact of RMO and PMO on the new product performance in the perspective of SMEs and examine the moderating effect of external factors such as environmental uncertainty and market similarity. The results of this study show that both RMO and PMO have a significant positive effect on the new product performance of SMEs. Also, environment uncertainty shows a negative moderating effect on the relationship between RMO and new product performance, whereas it has positive moderation with PMO. This suggests that focusing on potential customers' needs rather than current needs helps improve firm performance as the competitive environment surrounding the firm becomes more uncertain. Lastly, market similarity showed a positive moderating effect on the relationship between RMO and new product performance, but not on PMO.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.4
• /
• pp.113-124
• /
• 2021

The study investigates how financial markets respond to a shock to tone and semantic similarity of the Bank of Thailand press releases. The techniques in natural language processing are employed to quantify the tone and the semantic similarity of 69 press releases from 2010 to 2018. The corpus of the press releases is accessible to the general public. Stock market returns and bond yields are measured by logged return on SET50 and short-term and long-term government bonds, respectively. Data are daily from January 4, 2010, to August 8, 2019. The study uses the Structural Vector Auto Regressive model (SVAR) to analyze the effects of unanticipated and temporary shocks to the tone and the semantic similarity on bond yields and stock market returns. Impulse response functions are also constructed for the analysis. The results show that 1-month, 3-month, 6-month and 1-year bond yields significantly increase in response to a positive shock to the tone of press releases and 1-month, 3-month, 6-month, 1-year and 25-year bond yields significantly increase in response to a positive shock to the semantic similarity. Interestingly, stock market returns obtained from the SET50 index insignificantly respond to the shocks from the tone and the semantic similarity of the press releases.

• Journal of Korean Institute of Industrial Engineers
• /
• v.41 no.2
• /
• pp.150-161
• /
• 2015

This paper proposes a new approach to technology valuation, the market-replacement cost approach which integrates the cost-based approach and market-based approach. The proposed approach estimates the market-replacement cost of a target technology using R&D costs of similar R&D projects previously conducted. Similar R&D projects are extracted from project database based on document similarity between project proposals and technology description of the target technology. R&D costs of similar R&D projects are adjusted by mirroring the rate of technological obsolescence and inflation. Market-replacement cost of the technology is then derived by calculating the weighted average of adjusted costs and similarity values of similar R&D projects. A case of "Prevention method and system for the diffusion of mobile malicious code" is presented to illustrate the proposed approach.

• Asian Journal of Innovation and Policy
• /
• v.2 no.1
• /
• pp.97-122
• /
• 2013

This study secured comparable sales transaction information of technology transfer corresponding to an active market conditions and proposes a method to assess the similarity of technologies with regard to comparability of technology transfer based on these cases information. In order to analyze the association and similarity between target technology and sales transactions, it proposes the significant factors affecting royalty decision and the cosine coefficient method by industry categories. It also proposes the method to adjust royalty, which means that this method unlike the conventional method provides clear standards to valuators in order to revise royalty. Therefore, it offers a solution to the difficulties of applying the market approach for a lot of valuators that have wanted to apply it and objective method to enhance the reliability of the value of intangible asset evaluated by the market approach.

• The Journal of Industrial Distribution & Business
• /
• v.9 no.8
• /
• pp.17-26
• /
• 2018

Purpose - Indonesian economy often receives negative impact from external factors, particularly through trade linkage. To mitigate that impact, the export market and product diversification should be established. Latin America is one of the potential regions to augment the Indonesian export market. Research design, data, and methodology - This study attempts to classify the potential market and product for Indonesian export, particularly in Latin America, by using panel regression, trade complementarity, and export similarity index over the period 2000-2015. Regression was also used to examine whether the presence of the Indonesian Trade Promotion Center (ITPC) can support diversification. Results - Based on regression results, those indexes established Chile, Uruguay, Suriname, and Ecuador as the priority countries with the products: animal and vegetable oils, fats and waxes; chemicals and related products; miscellaneous manufactured articles; commodities and transactions. Conclusions - The results of the regression concludes that the trade complementarity index gave a significant positive effect to boost Indonesian export, whereas, the export similarity index gave a significant negative effect. The regression also conclude that ITPC gave a significant positive impact on Indonesian export. For instance, the government should prioritize those countries and products and also develop ITPC there to optimize Indonesian export.

• The Journal of Asian Finance, Economics and Business
• /
• v.6 no.4
• /
• pp.179-187
• /
• 2019

This study aims to investigate the effects of market commonality and resource similarity on price competition and the recursive consequences in the Korean lodging market. Price comparison among hotels in the same geographic market has been facilitated through the development of information technology, rendering little search cost of consumers. While the literature implies the heterogeneous price attack and response among hotels, a limited number of empirical researches focus on the asymmetric and recursive pattern in the competitive dynamics. This study empirically examines the price interactions in the Korean lodging market based on the theoretical framework of competitive price interactions and countervailing power. Demonstrating superiority to the spatial lag model and the ordinary least squares in the estimation, the results from spatial error model suggest that the hotels with longer operational history pose an asymmetric impact on the price of the newer hotels. The asymmetry is also found in chain hotels over the independent, further implying the possibility of predatory pricing. The findings of this study provide the evidence of a hierarchical structure in the price competition, with different countervailing power by the resources of the hotels. Theoretical and managerial implications are discussed, with suggestions for future study.

• The Journal of Information Systems
• /
• v.26 no.3
• /
• pp.63-90
• /
• 2017

Purpose This study proposes a novel system trading model using case-based reasoning (CBR) based on absolute similarity threshold. The proposed model is designed to optimize the absolute similarity threshold, feature selection, and instance selection of CBR by using genetic algorithm (GA). With these mechanisms, it enables us to yield higher returns from stock market trading. Design/Methodology/Approach The proposed CBR model uses the absolute similarity threshold varying from 0 to 1, which serves as a criterion for selecting appropriate neighbors in the nearest neighbor (NN) algorithm. Since it determines the nearest neighbors on an absolute basis, it fails to select the appropriate neighbors from time to time. In system trading, it is interpreted as the signal of 'hold'. That is, the system trading model proposed in this study makes trading decisions such as 'buy' or 'sell' only if the model produces a clear signal for stock market prediction. Also, in order to improve the prediction accuracy and the rate of return, the proposed model adopts optimal feature selection and instance selection, which are known to be very effective in enhancing the performance of CBR. To validate the usefulness of the proposed model, we applied it to the index trading of KOSPI200 from 2009 to 2016. Findings Experimental results showed that the proposed model with optimal feature or instance selection could yield higher returns compared to the benchmark as well as the various comparison models (including logistic regression, multiple discriminant analysis, artificial neural network, support vector machine, and traditional CBR). In particular, the proposed model with optimal instance selection showed the best rate of return among all the models. This implies that the application of CBR with the absolute similarity threshold as well as the optimal instance selection may be effective in system trading from the perspective of returns.

• Korean Management Science Review
• /
• v.28 no.1
• /
• pp.61-74
• /
• 2011

Not only the preference data but also the similarity data can be used for developing effective marketing strategies. Hahn et al.[10] proposes a methodology of representing a brand(focal brand)'s competitors in a single map called the Preference-Similarity Map, according to their relative preference to and similarity with the focal brand. They also proposes a way to derive the relative preference and similarity values from the survey collecting the choice data from differing choice sets. This study identifies the limitations of the preference and similarity measures proposed by Hahn et al.[10] and shows how these measures can be revised. This study also proposes how to implement the revised measures and analyze brands' positioning strategies. Based on the results of the previous studies on the effect of inter brand similarity on brand evaluations, this study assumes that it is important to analyze how much a specific brand is preferred to its close competitors when evaluating the effectiveness of the brand's positioning in the market. This study applies the proposed measures to the data used in Hahn et al.[10] and also show how the proposed measures are related to the parameters of the choice model proposed by Batsell and Polking[1].

• International conference on construction engineering and project management
• /
• 2015.10a
• /
• pp.463-467
• /
• 2015

Mega-shock means a sporadic event such as the earning shock, which occurred by sudden market changes, and it can cause serious problems of profit loss of international construction projects. Therefore, the early response and prevention by analyzing and predicting the Mega-shock is critical for successful project delivery. This research is preliminary study to develop a prediction model that supports market condition analysis and Mega-shock forecasting. To avoid disadvantages of classic statistical approaches that assume the market factors are linear and independent and thus have limitations to explain complex interrelationship among a range of international market factors, the research team explored the Fractal Theory that can explain self-similarity and recursiveness of construction market changes. The research first found out correlation of the major market factors by statistically analyzing time-series data. The research then conducted a base of the Fractal analysis to distinguish features of fractal from data. The outcome will have potential to contribute to building up a foundation of the early shock warning system for the strategic international project management.