Abstract: Recent years have seen an increasing number of patent disputes due to excessive competition in the global market and a reduced technology life-cycle; this has increased the risk of investment in technology development. While many global companies have started developing a methodology to identify promising technologies and assess for decisions, the existing methodology still has some limitations. Post hoc assessments of the new technology are not being performed, especially to determine whether the suggested technologies turned out to be promising. For example, in existing quantitative patent analysis, a patent’s citation information has served as an important metric for quality assessment, but this analysis cannot be applied to recently registered patents because such information accumulates over time. Therefore, we propose a new technology assessment model that can replace citation information and positively affect technological development based on post hoc analysis of the patents for promising technologies. Additionally, we collect customer reviews on a target technology to extract keywords that show the customers’ needs, and we determine how many keywords are covered in the new technology. Finally, we construct a portfolio (based on a technology assessment from patent information) and a customer-based marketability assessment (based on review data), and we use them to visualize the characteristics of the new technologies.
Abstract: As technology-based service industries grow
drastically worldwide; companies are recognizing the importance of
market preoccupancy and have made an effort to capture a large
market to gain the upper hand. To this end, a focus on patents can be
used to determine the properties of a technology, as well as to capture
advantages in technical skills, in comparison with the firm’s
competitors. However, technology-based services largely depend not
only on their technological value but also their economic value, due
to the recognized worth that is passed to a plurality of users. Thus, it
is important to determine whether there are any competitors in the
target areas and what services they provide in any field. Despite this
importance, little effort has been made to systematically benchmark
competitors in order to identify business opportunities. Thus, this
study aims to not only identify each position of technology-centered
service companies in complex market dynamics, but also to discover
new business opportunities. For this, we try to consider both
technology and market environments simultaneously by utilizing
patent data as a representative proxy for technology and trademark
dates as an index for a firm’s target goods and services. Theoretically,
this is one of the earliest attempts to combine patent data and
trademark data to analyze corporate strategies. In practice, the
research results are expected to be used as a decision criterion to
diagnose the economic value that companies can obtain by entering
the market, as well as the technological value to be passed onto their
customers. Thus, the proposed approach can be useful to support
effective technology and business strategies in a firm.
Abstract: This research proposes a methodology for patent-citation-based technology input-output analysis by applying the patent information to input-output analysis developed for the dependencies among different industries. For this analysis, a technology relationship matrix and its components, as well as input and technology inducement coefficients, are constructed using patent information. Then, a technology inducement coefficient is calculated by normalizing the degree of citation from certain IPCs to the different IPCs (International patent classification) or to the same IPCs. Finally, we construct a Dependency Structure Matrix (DSM) based on the technology inducement coefficient to suggest a useful application for this methodology.
Abstract: The goal of this research is discovering the
determinants of the success or failure of external cooperation in small
and medium enterprises (SMEs). For this, a survey was given to 190
SMEs that experienced external cooperation within the last 3 years. A
logistic regression model was used to derive organizational or strategic
characteristics that significantly influence whether external
collaboration of domestic SMEs is successful or not. Results suggest
that research and development (R&D) features in general
characteristics (both idea creation and discovering market
opportunities) that focused on and emphasized indirected-market
stakeholders (such as complementary companies and affiliates) and
strategies in innovative strategic characteristics raise the probability of
successful external cooperation. This can be used meaningfully to
build a policy or strategy for inducing successful external cooperation
or to understand the innovation of SMEs.