Location Efficiencies of Host Countries for Strategic Offshoring Decisions Amid Wealth Creation Opportunities and Supply Chain Risks
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- Journal of Korea Trade
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- v.25 no.3
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- pp.21-47
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- 2021
Purpose - Offshoring has emerged as one of the major trends in international trade and has become one of the strategies for achieving competitiveness in the global market. In spite of this, the expected gains of offshoring can be offset by hidden costs and risks, such as those associated with the COVID-19 pandemic, the trade war between the USA and China, and the ongoing trade dispute between Korea and Japan. To obviate such business failure and prevent critical business blunders, offshoring strategies that efficiently consider both risk elements and potential wealth creation are urgently need. The first purpose of this study is to contribute to the development of more advanced offshoring strategies to help host countries select the best locations to manage supply chain risks and create unique value. The second purpose is to specifically analyze the current status of Korea and provide Korean companies with implications to be considered when deciding whether to offshore or re-shore. Design/methodology - A Network DEA model was applied to measure the comparative location efficiency of national competencies for offshoring strategy from perspectives of wealth creation opportunities (profitability and marketability) and supply chain risk management. The location efficiencies are compared among a total 70 countries selected from the Global Competitiveness Index (GCI) and globally attractive locations outlined by Kearney (2017). For the secondary analysis of efficiency, a t-test examining the nature of competitive advantage and the level of sophistication in production processes was implemented in three divisions. We then analyzed differences in offshoring performance in terms of the identified national traits. Moreover, Tobit regression analysis is conducted to investigate the correlation between value-added business activities and each divisional efficiency, seeking to determine how each degree of value-added business activity influences the increase in offshoring productivity. Findings - Regarding overall location efficiency for offshoring performance, only the USA and Italy were identified as being efficient as host countries for offshoring, under circumstances of advanced development, such as productivity and risk management. Korea ranks 13th among 70 countries. The determinants of national competitiveness depend on national traits (the nature of competitive advantage and business sophistication). Countries with labor/resource advantages and labor-intensive industries are more competitive in terms of marketability than others. In contrast, countries with strong technology-intensive industries benefit offshoring companies, particularly in the technology sector, with the added advantage of supply chain risk management. As the perception of a value chain is broader in a country, it can achieve both production sophistication and competitive advantages such as marketability and SCRM. Originality/value - Existing studies focus on offshoring effectiveness from a company perspective. This paper contributes to comparing country efficiency in producing core competencies related to an offshoring strategy and also segments countries into three performance-based considerations associated with the global offshoring market. It also details Korea's position as an offshoring location according to national efficiency and competency.
Internet computing is a disruptive IT innovation. Semantic Web can be considered as an IT innovation because the Semantic Web technology possesses the potential to reduce information overload and enable semantic integration, using capabilities such as semantics and machine-processability. How should organizations adopt the Semantic Web? What factors affect the adoption and diffusion of Semantic Web innovation? Most studies on adoption and diffusion of innovation use empirical analysis as a quantitative research methodology in the post-implementation stage. There is criticism that the positivist requiring theoretical rigor can sacrifice relevance to practice. Rapid advances in technology require studies relevant to practice. In particular, it is realistically impossible to conduct quantitative approach for factors affecting adoption of the Semantic Web because the Semantic Web is in its infancy. However, in an early stage of introduction of the Semantic Web, it is necessary to give a model and some guidelines and for adoption and diffusion of the technology innovation to practitioners and researchers. Thus, the purpose of this study is to present a model of adoption and diffusion of the Semantic Web and to offer propositions as guidelines for successful adoption through a qualitative research method including multiple case studies and in-depth interviews. The researcher conducted interviews with 15 people based on face-to face and 2 interviews by telephone and e-mail to collect data to saturate the categories. Nine interviews including 2 telephone interviews were from nine user organizations adopting the technology innovation and the others were from three supply organizations. Semi-structured interviews were used to collect data. The interviews were recorded on digital voice recorder memory and subsequently transcribed verbatim. 196 pages of transcripts were obtained from about 12 hours interviews. Triangulation of evidence was achieved by examining each organization website and various documents, such as brochures and white papers. The researcher read the transcripts several times and underlined core words, phrases, or sentences. Then, data analysis used the procedure of open coding, in which the researcher forms initial categories of information about the phenomenon being studied by segmenting information. QSR NVivo version 8.0 was used to categorize sentences including similar concepts. 47 categories derived from interview data were grouped into 21 categories from which six factors were named. Five factors affecting adoption of the Semantic Web were identified. The first factor is demand pull including requirements for improving search and integration services of the existing systems and for creating new services. Second, environmental conduciveness, reference models, uncertainty, technology maturity, potential business value, government sponsorship programs, promising prospects for technology demand, complexity and trialability affect the adoption of the Semantic Web from the perspective of technology push. Third, absorptive capacity is an important role of the adoption. Fourth, suppler's competence includes communication with and training for users, and absorptive capacity of supply organization. Fifth, over-expectance which results in the gap between user's expectation level and perceived benefits has a negative impact on the adoption of the Semantic Web. Finally, the factor including critical mass of ontology, budget. visible effects is identified as a determinant affecting routinization and infusion. The researcher suggested a model of adoption and diffusion of the Semantic Web, representing relationships between six factors and adoption/diffusion as dependent variables. Six propositions are derived from the adoption/diffusion model to offer some guidelines to practitioners and a research model to further studies. Proposition 1 : Demand pull has an influence on the adoption of the Semantic Web. Proposition 1-1 : The stronger the degree of requirements for improving existing services, the more successfully the Semantic Web is adopted. Proposition 1-2 : The stronger the degree of requirements for new services, the more successfully the Semantic Web is adopted. Proposition 2 : Technology push has an influence on the adoption of the Semantic Web. Proposition 2-1 : From the perceptive of user organizations, the technology push forces such as environmental conduciveness, reference models, potential business value, and government sponsorship programs have a positive impact on the adoption of the Semantic Web while uncertainty and lower technology maturity have a negative impact on its adoption. Proposition 2-2 : From the perceptive of suppliers, the technology push forces such as environmental conduciveness, reference models, potential business value, government sponsorship programs, and promising prospects for technology demand have a positive impact on the adoption of the Semantic Web while uncertainty, lower technology maturity, complexity and lower trialability have a negative impact on its adoption. Proposition 3 : The absorptive capacities such as organizational formal support systems, officer's or manager's competency analyzing technology characteristics, their passion or willingness, and top management support are positively associated with successful adoption of the Semantic Web innovation from the perceptive of user organizations. Proposition 4 : Supplier's competence has a positive impact on the absorptive capacities of user organizations and technology push forces. Proposition 5 : The greater the gap of expectation between users and suppliers, the later the Semantic Web is adopted. Proposition 6 : The post-adoption activities such as budget allocation, reaching critical mass, and sharing ontology to offer sustainable services are positively associated with successful routinization and infusion of the Semantic Web innovation from the perceptive of user organizations.