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The existing approaches to identification of emerging technologies create a prominent opportunity for technology convergence and market growth potential. However, existing approaches either suffer from the time lag issue or have yet to explorethe assessment’s uncertainty and ambiguity. Based on a total of 14 years of mergers and acquisitions (M&A) activity data in the Health Care sector, the complex patterns between growth velocity and accelerating of M&A activities are analyzed with two quantitative indicators (Promising Index and Promising Index Sharpe Ratio) to identify emerging technological opportunities. The proposed integrative approach offers a mean to resolve the time lag issue, deal with market trend irregularity, and manage expectations of investors for emerging technology and industry. Specifically, this study aims to (i) provide a decision support system integrating M&A activity information for strategic investment planning and (ii) identify promising technologies in the Healthcare sector to manage the irregularities of market trend and investment outcome. This study is one of the first research that employs a prior data-based approach to delineate emerging technologies by analyzing the growth momentum properties of specific industry areas based on the M&A activity data.
Jinho Choi; Nina Shin; Yong Chang. Strategic Investment Decisions for Emerging Technology Fields in the Health Care Sector Based on M&A Analysis. Sustainability 2021, 13, 3644 .
AMA StyleJinho Choi, Nina Shin, Yong Chang. Strategic Investment Decisions for Emerging Technology Fields in the Health Care Sector Based on M&A Analysis. Sustainability. 2021; 13 (7):3644.
Chicago/Turabian StyleJinho Choi; Nina Shin; Yong Chang. 2021. "Strategic Investment Decisions for Emerging Technology Fields in the Health Care Sector Based on M&A Analysis." Sustainability 13, no. 7: 3644.
In this paper, we suggest a new methodology to identify promising technology areas by analyzing merger and acquisition (M&A) information. First, we present decision models for estimating the velocity and acceleration of M&A transactions to identify promising areas based on M&A information. Second, we identify the promising technology areas with longitudinal analyses of M&As over the entire period. Third, cross-sectional analysis is proposed to determine which technology areas are more promising through a relative comparison among technology areas within the IT sector for a specific period. The main significance of our research is that it is a prior data-based analytic method based on M&A transaction information to identify the growth of industry and technology. We hope this study will provide insights for R&D (Research&Development) policymakers and investment firms as a new approach that complements previous methods in exploring promising industry or technology areas.
Jinho Choi; Yong Sik Chang. Development of a New Methodology to Identity Promising Technology Areas Using M&A Information. Sustainability 2020, 12, 5606 .
AMA StyleJinho Choi, Yong Sik Chang. Development of a New Methodology to Identity Promising Technology Areas Using M&A Information. Sustainability. 2020; 12 (14):5606.
Chicago/Turabian StyleJinho Choi; Yong Sik Chang. 2020. "Development of a New Methodology to Identity Promising Technology Areas Using M&A Information." Sustainability 12, no. 14: 5606.
Companies today that seek to diversify their business are looking for opportunities in new markets by considering their core competencies. However, companies are struggling to diversify and grow their current businesses due to a lack of information concerning diversification and a low level of capability for future commercialization. In this study, we suggest a new methodology that identifies promising industry and technology areas by examining mergers and acquisitions (M&As) transaction data. Specifically, by analyzing the extent to which firms have engaged in M&A activities, the prediction of promising industries is derived from the relationships among specific industries, as well as the M&A transactions among technology areas within a focal industry. We first theoretically test whether all M&A transactions are related to promising areas. Second, we analyze the trends of global M&As by a time-series analysis of M&A transactions by sectors over the last 15 years. Lastly, we conduct an association analysis to identify the degree of M&A connections between industry and technology areas, respectively. We hope that our results provide insights for R&D policymakers and investors who need to decide on promising industries to cultivate or invest in, and researchers who want to identify overall M&A trends and promising industries and technology areas.
Jinho Choi; Sunghun Chung; Yong Sik Chang. Is M&A Information Useful for Exploring Promising Industries and Technologies? Sustainability 2019, 12, 139 .
AMA StyleJinho Choi, Sunghun Chung, Yong Sik Chang. Is M&A Information Useful for Exploring Promising Industries and Technologies? Sustainability. 2019; 12 (1):139.
Chicago/Turabian StyleJinho Choi; Sunghun Chung; Yong Sik Chang. 2019. "Is M&A Information Useful for Exploring Promising Industries and Technologies?" Sustainability 12, no. 1: 139.
While convergent technology has been booming recently, drones are being applied in various fields of industry and are expected to be used as a commercial delivery method. In a delivery system, routing becomes one of the major issues, and several studies have attempted to solve drone-based routing problems. In this study, we focus on finding an effective delivery route for trucks carrying drones. To put it concretely, we propose a new approach on a nonlinear programming model to find shift-weights that move the centers of clusters to make for wider drone-delivery areas along shorter truck-route after initial K-means clustering and TSP (Traveling Salesman Problem) modeling. In order to verify the effectiveness of the proposed model with shift-weights, we compare it with two other delivery route approaches. One is a route without shift-weights after K-means clustering and TSP modeling, and the other is a route by TSP for all delivery locations without K-means clustering. Through experimental results of paired t-tests on randomly generated delivery locations, we show that our proposed model is more effective than the other two models.
Yong Sik Chang; Hyun Jung Lee. Optimal delivery routing with wider drone-delivery areas along a shorter truck-route. Expert Systems with Applications 2018, 104, 307 -317.
AMA StyleYong Sik Chang, Hyun Jung Lee. Optimal delivery routing with wider drone-delivery areas along a shorter truck-route. Expert Systems with Applications. 2018; 104 ():307-317.
Chicago/Turabian StyleYong Sik Chang; Hyun Jung Lee. 2018. "Optimal delivery routing with wider drone-delivery areas along a shorter truck-route." Expert Systems with Applications 104, no. : 307-317.
Hyun Jung Lee; Yong Sik Chang. A Coexistence Model in a Dynamic Platform with ICT-based Multi-Value Chains: focusing on Healthcare Service. Journal of Intelligence and Information Systems 2017, 23, 69 -93.
AMA StyleHyun Jung Lee, Yong Sik Chang. A Coexistence Model in a Dynamic Platform with ICT-based Multi-Value Chains: focusing on Healthcare Service. Journal of Intelligence and Information Systems. 2017; 23 (1):69-93.
Chicago/Turabian StyleHyun Jung Lee; Yong Sik Chang. 2017. "A Coexistence Model in a Dynamic Platform with ICT-based Multi-Value Chains: focusing on Healthcare Service." Journal of Intelligence and Information Systems 23, no. 1: 69-93.
Consumers in the online shopping environment have had difficulties in selecting an optimal supplier. This is caused by the fact that current comparison shopping services have limitations in considering supplier’s various pricing strategies. Current Comparison Shopping Model (CSM) including these limitations may enable online consumers to select a non-optimal supplier. To overcome these problems, we proposed a Comparison Shopping Optimization Model based on Suppliers’ Pricing Contexts (CSOM-SPC), which gives online consumers effective price-sorted suppliers. Through illustrative experimentation and paired t-test, we show that CSOM-SPC provides more realistic and effective comparison prices compared with current CSM.
Yong Sik Chang; Kyoung Jun Lee. A comparison shopping optimization model based on suppliers’ pricing contexts. Expert Systems with Applications 2010, 37, 5736 -5744.
AMA StyleYong Sik Chang, Kyoung Jun Lee. A comparison shopping optimization model based on suppliers’ pricing contexts. Expert Systems with Applications. 2010; 37 (8):5736-5744.
Chicago/Turabian StyleYong Sik Chang; Kyoung Jun Lee. 2010. "A comparison shopping optimization model based on suppliers’ pricing contexts." Expert Systems with Applications 37, no. 8: 5736-5744.
This study proposes a new and highly efficient dynamic combinatorial auction mechanism—the NN-bilateral optimized combinatorial auction (NN-BOCA). NN-BOCA is a flexible iterative combinatorial auction model that offers more optimized trading for multiple suppliers and purchasers in the supply chain than one-sided combinatorial auction. We design the NN-BOCA model from the perspectives of market architecture, trading rules, and decision strategy for winner determination, the decision strategy for winner determination needs flexible optimization modeling capability. Thus rule-based reasoning was applied for reflecting the flexible decision strategies. We also show the viability of NN-BOCA through Paired Samples TT-test experimentation. It shows that NN-BOCA yields higher purchase efficiency and effectiveness than the one-auctioneer to multi-bidders (1-to-NN) combinatorial auction mechanism.
Jin Ho Choi; Yong Sik Chang; Ingoo Han. The empirical analysis of the N-bilateral optimized combinatorial auction model. Omega 2009, 37, 482 -493.
AMA StyleJin Ho Choi, Yong Sik Chang, Ingoo Han. The empirical analysis of the N-bilateral optimized combinatorial auction model. Omega. 2009; 37 (2):482-493.
Chicago/Turabian StyleJin Ho Choi; Yong Sik Chang; Ingoo Han. 2009. "The empirical analysis of the N-bilateral optimized combinatorial auction model." Omega 37, no. 2: 482-493.
Jae Lee Kyu; Yong Chang Sik. A Framework of Optimization Agent for Supply Chain Management. Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications 2006, 155 -178.
AMA StyleJae Lee Kyu, Yong Chang Sik. A Framework of Optimization Agent for Supply Chain Management. Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications. 2006; ():155-178.
Chicago/Turabian StyleJae Lee Kyu; Yong Chang Sik. 2006. "A Framework of Optimization Agent for Supply Chain Management." Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications , no. : 155-178.
The eProcurement planning is crucial to reduce purchase cost while selecting the right suppliers and it contributes to improve corporate competitiveness. This eProcurement planning research describes a framework for the integration of a knowledge-based system capable of identifying a goal model from a Primitive Model. The Primitive Model is screened by the screening factors reflecting the purchase strategy. As a result, by using the framework for supplier selection and allocation (SSA), a purchaser is able to reduce the costs and time required to select the right suppliers and to alleviate anxiety for ‘out-of-favor’ suppliers. This approach is based on two-phased semantic optimization model modification that semantically builds a goal model through model identification and candidate supplier screening based on model identification rules and supplier screening rules. This approach contributes significantly to construction of an optimization model from the perspective of model management and it provides a useful environment for efficient eProcurement from the perspective of a purchaser.
Jin Ho Choi; Yong Sik Chang. A two-phased semantic optimization modeling approach on supplier selection in eProcurement. Expert Systems with Applications 2006, 31, 137 -144.
AMA StyleJin Ho Choi, Yong Sik Chang. A two-phased semantic optimization modeling approach on supplier selection in eProcurement. Expert Systems with Applications. 2006; 31 (1):137-144.
Chicago/Turabian StyleJin Ho Choi; Yong Sik Chang. 2006. "A two-phased semantic optimization modeling approach on supplier selection in eProcurement." Expert Systems with Applications 31, no. 1: 137-144.
Virtual manufacturing has 2 characteristics as an agent-based electronic commerce environment: dynamic nature of resource status and variety of agents' decision-making (i.e., scheduling) model. To reflect the characteristics, a relevant negotiation protocol should be designed and an appropriate decision-making model should be developed. In this article, from the perspective of a sales agent that is a middle man between customers and manufacturers in a virtual manufacturing environment, we provide a case study that suggests a time-bound framework for external negotiation between sales agents and customer agents, and internal cooperation between sales agents and manufacturing agents. We assume a job shop as the production model of a virtual manufacturing enterprise and formulate the optimal order selection problem with mixed integer programming, but its computation time is not acceptable for real-world problems. For this time-constrained decision making, we develop a genetic algorithm as an anytime problem-solving method for the scheduling of the production model, which shows a reasonable computation time for real-world cases and good incremental problem-solving capability.
Kyoung Jun Lee; Yong Sik Chang; Hyung Rim Choi; Hyun Soo Kim; Young Jae Park; Byung Joo Park. A Time-Bound Framework for Negotiation and Decision Making of Virtual Manufacturing Enterprise. Journal of Organizational Computing and Electronic Commerce 2004, 14, 27 -41.
AMA StyleKyoung Jun Lee, Yong Sik Chang, Hyung Rim Choi, Hyun Soo Kim, Young Jae Park, Byung Joo Park. A Time-Bound Framework for Negotiation and Decision Making of Virtual Manufacturing Enterprise. Journal of Organizational Computing and Electronic Commerce. 2004; 14 (1):27-41.
Chicago/Turabian StyleKyoung Jun Lee; Yong Sik Chang; Hyung Rim Choi; Hyun Soo Kim; Young Jae Park; Byung Joo Park. 2004. "A Time-Bound Framework for Negotiation and Decision Making of Virtual Manufacturing Enterprise." Journal of Organizational Computing and Electronic Commerce 14, no. 1: 27-41.