Foreign entry strategies: strategic adaptation to various facets of the institutional environment

In this paper we develop a comprehensive model of MNEs' foreign entry strategies and theorize how and how much the entry strategy is likely to be determined in the interface between internal and external pressures for both conformity and legitimacy. We develop an adaptation argument, in contrast to a selection rationale, through which we enhance our understanding of the various facets of the institutional environment and the constraints international managers encounter in their internationalization strategies.Fundação para a Ciência e Tecnologia - Portugal (grant SFRH/BD/880/2000

Resource Mobilization and Business Incubation : The Case of Korean Incubators

The rapid expansion of business incubators in Korea is one of the most important phenomena affecting the high-tech industries in Korea. This paper presents the current conditions of Korean incubators and proposes what factors are important for their continual development. First, we present how rapidly this new organizational model, business incubation, expanded in Korea after the IMF bailout crisis. Second, we explore factors that lead these incubators to perform better. We emphasize that better qualified technical, managerial, and administrative support of incubators are important success factors. However, we also argue that better networked incubators perform better. By better networked incubators, we mean the incubators that can provide the incubatees (start-ups) with effective internal networking (e.g., alliance among incubatees) and sufficient external networking as well (e.g., technical support from outside experts, professional assistance from outside consultants, support from the central and local governments, etc.). We agree to the earlier literature that encouraging networking among incubatees is an important success factor for incubators. In this paper, we also suggest that external networking and outsourcing are significant components in the case of Korea where most of incubators are not self-sufficient in providing services and support to incubatees.This research project was supported by the Research Support Grant from the Center for International Business Education and Research (CIBER) of the David Eccles School of Business, the University of Utah

Engaging social activities prevent stroke and myocardial infraction by raising awareness of warning symptoms: A cross-sectional survey study

BackgroundStroke and myocardial infarction (MI) are medical emergencies, and early treatment within the golden hour is crucial for good prognosis. Adequate knowledge about the warning symptoms can shorten the onset-to-door time. Various factors affect the level of awareness, including social activity. This study aimed to determine if engaging in social activity is associated with the awareness of the warning symptoms of stroke and MI.MethodsThis cross-sectional study analyzed 451,793 participants from the 2017 and 2019 Korea Community Health Survey. Based on five questions for each of stroke and MI symptoms, participants were divided into an awareness group (replied “Yes” to all five questions) and unawareness group. Engagement in social activities (i.e., religious, friendship, leisure, and volunteer activity) was evaluated through a questionnaire. Multiple logistic regression analysis was performed to evaluate the relation between social activity and awareness of warning symptoms.ResultsOverall, 52.6% participants were aware of the warning symptoms of stroke, and 45.8% of MI. Regular engagement in at least one social activity, particularly friendship or volunteer activity, was associated with better awareness of the warning symptoms, both stroke (OR: 1.21, 95% CI: 1.20–1.23) and MI (OR: 1.22, 95% CI: 1.20–1.24). Additionally, more diverse types of social activities were associated with higher levels of awareness. Relationship between social activity and awareness showed positive association with participants older than 60 years, rural residents, or with low socioeconomic status.ConclusionEngagement in social activity was significantly associated with better knowledge about the warning symptoms of stroke and MI. For early hospital treatment after symptom onset, participation in social activities could be beneficial

Discrimination of cultivation ages and cultivars of ginseng leaves using Fourier transform infrared spectroscopy combined with multivariate analysis

AbstractTo determine whether Fourier transform (FT)-IR spectral analysis combined with multivariate analysis of whole-cell extracts from ginseng leaves can be applied as a high-throughput discrimination system of cultivation ages and cultivars, a total of total 480 leaf samples belonging to 12 categories corresponding to four different cultivars (Yunpung, Kumpung, Chunpung, and an open-pollinated variety) and three different cultivation ages (1 yr, 2 yr, and 3 yr) were subjected to FT-IR. The spectral data were analyzed by principal component analysis and partial least squares-discriminant analysis. A dendrogram based on hierarchical clustering analysis of the FT-IR spectral data on ginseng leaves showed that leaf samples were initially segregated into three groups in a cultivation age-dependent manner. Then, within the same cultivation age group, leaf samples were clustered into four subgroups in a cultivar-dependent manner. The overall prediction accuracy for discrimination of cultivars and cultivation ages was 94.8% in a cross-validation test. These results clearly show that the FT-IR spectra combined with multivariate analysis from ginseng leaves can be applied as an alternative tool for discriminating of ginseng cultivars and cultivation ages. Therefore, we suggest that this result could be used as a rapid and reliable F1 hybrid seed-screening tool for accelerating the conventional breeding of ginseng

Predictive Solution for Radiation Toxicity Based on Big Data

Radiotherapy is a treatment method using radiation for cancer treatment based on a patient treatment planning for each radiotherapy machine. At this time, the dose, volume, device setting information, complication, tumor control probability, etc. are considered as a single-patient treatment for each fraction during radiotherapy process. Thus, these filed-up big data for a long time and numerous patients’ cases are inevitably suitable to produce optimal treatment and minimize the radiation toxicity and complication. Thus, we are going to handle up prostate, lung, head, and neck cancer cases using machine learning algorithm in radiation oncology. And, the promising algorithms as the support vector machine, decision tree, and neural network, etc. will be introduced in machine learning. In conclusion, we explain a predictive solution of radiation toxicity based on the big data as treatment planning decision support system

Prediction of Cancer Patient Outcomes Based on Artificial Intelligence

Knowledge-based outcome predictions are common before radiotherapy. Because there are various treatment techniques, numerous factors must be considered in predicting cancer patient outcomes. As expectations surrounding personalized radiotherapy using complex data have increased, studies on outcome predictions using artificial intelligence have also increased. Representative artificial intelligence techniques used to predict the outcomes of cancer patients in the field of radiation oncology include collecting and processing big data, text mining of clinical literature, and machine learning for implementing prediction models. Here, methods of data preparation and model construction to predict rates of survival and toxicity using artificial intelligence are described

Cavernous Hemangioma of the Tympanic Membrane

Cavernous hemangioma seems to most frequently arise in the posterior portion of the external auditory canal. However, they rarely occur in the tympanic membrane. A 49-year-old male patient was referred for evaluation of right-sided pulsatile tinnitus that he'd experienced for the previous 2 years. Temporal bone computerized tomography showed an isolated soft tissue mass just lateral to the tympanic membrane. There was no evidence of bony erosion or middle ear invasion. The patient underwent excision of the mass using a postauricular approach. The mass was removed en bloc and the defect of the tympanic membrane was repaired by tympanoplasty type I. There was no recurrence after 1 year of follow-up

Versatile poly(diallyl dimethyl ammonium chloride)-layered nanocomposites for removal of cesium in water purification

In this work, we elucidate polymer-layered hollow Prussian blue-coated magnetic nanocomposites as an adsorbent to remove radioactive cesium from environmentally contaminated water. To do this, Fe3O4 nanoparticles prepared using a coprecipitation method were thickly covered with a layer of cationic polymer to attach hollow Prussian blue through a self-assembly process. The as-synthesized adsorbent was confirmed through various analytical techniques. The adsorbent showed a high surface area (166.16 m2/g) with an excellent cesium adsorbent capacity and removal efficiency of 32.8 mg/g and 99.69%, respectively. Moreover, the superparamagnetism allows effective recovery of the adsorbent using an external magnetic field after the adsorption process. Therefore, the magnetic adsorbent with a high adsorption efficiency and convenient recovery is expected to be effectively used for rapid remediation of radioactive contamination