• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.169-196
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• 2017

The fourth industrial revolution represents a revolutionary change in the business environment and its ecosystem, which is a fusion of Information Technology (IT) and other industries. In line with these recent changes, the Ministry of Employment and Labor of South Korea announced 'the Fourth Industrial Revolution Leader Training Program,' which includes five key support areas such as (1) smart manufacturing, (2) Internet of Things (IoT), (3) big data including Artificial Intelligence (AI), (4) information security, and (5) bio innovation. Based on this program, we can get a glimpse of the South Korean government's efforts and willingness to emit leading human resource with advanced IT knowledge in various fusion technology-related and newly emerging industries. On the other hand, in order to nurture excellent IT manpower in preparation for the fourth industrial revolution, the role of educational institutions capable of providing high quality IT education services is most of importance. However, these days, most IT educational institutions have had difficulties in providing customized IT education services that meet the needs of consumers (i.e., learners), without breaking away from the traditional framework of providing supplier-oriented education services. From previous studies, it has been found that the provision of customized education services centered on learners leads to high satisfaction of learners, and that higher satisfaction increases not only task performance and the possibility of business application but also learners' recommendation intention. However, since research has not yet been conducted in a comprehensive way that consider both antecedent and consequent factors of the learner's satisfaction, more empirical research on this is highly desirable. With the advent of the fourth industrial revolution, a rising interest in various convergence technologies utilizing information technology (IT) has brought with the growing realization of the important role played by IT-related education services. However, research on the role of IT education service quality in the context of IT education is relatively scarce in spite of the fact that research on general education service quality and satisfaction has been actively conducted in various contexts. In this study, therefore, the five dimensions of IT education service quality (i.e., tangibles, reliability, responsiveness, assurance, and empathy) are derived from the context of IT education, based on the SERVPERF model and related previous studies. In addition, the effects of these detailed IT education service quality factors on learners' educational satisfaction and their work application/recommendation intentions are examined. Furthermore, the moderating roles of learner position (i.e., practitioner group vs. manager group) and participation motivation (i.e., voluntary participation vs. involuntary participation) in relationships between IT education service quality factors and learners' educational satisfaction, work application intention, and recommendation intention are also investigated. In an analysis using the structural equation model (SEM) technique based on a questionnaire given to 203 participants of IT education programs in an 'M' IT educational institution in Seoul, South Korea, tangibles, reliability, and assurance were found to have a significant effect on educational satisfaction. This educational satisfaction was found to have a significant effect on both work application intention and recommendation intention. Moreover, it was discovered that learner position and participation motivation have a partial moderating impact on the relationship between IT education service quality factors and educational satisfaction. This study holds academic implications in that it is one of the first studies to apply the SERVPERF model (rather than the SERVQUAL model, which has been widely adopted by prior studies) is to demonstrate the influence of IT education service quality on learners' educational satisfaction, work application intention, and recommendation intention in an IT education environment. The results of this study are expected to provide practical guidance for IT education service providers who wish to enhance learners' educational satisfaction and service management efficiency.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Journal of Distribution Research
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• v.17 no.1
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• pp.65-86
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• 2012

The $20^{th}$ century was the era of manufacturer brands which built higher brand equity for consumers. Consumers moved from generic products of inconsistent quality produced by local factories in the $19^{th}$ century to branded products from global manufacturers and manufacturer brands reached consumers through distributors and retailers. Retailers were relatively small compared to their largest suppliers. However, sometime in the 1970s, things began to slowly change as retailers started to develop their own national chains and began international expansion, and consolidation of the retail industry from mom-and-pop stores to global players was well under way (Kumar and Steenkamp 2007, p.2) In South Korea, since the middle of the 1990s, the bulking up of retailers that started then has changed the balance of power between manufacturers and retailers. Retailer private labels, generally referred to as own labels, store brands, distributors own private-label, home brand or own label brand have also been performing strongly in every single local market (Bushman 1993; De Wulf et al. 2005). Private labels now account for one out of every five items sold every day in U.S. supermarkets, drug chains, and mass merchandisers (Kumar and Steenkamp 2007), and the market share in Western Europe is even larger (Euromonitor 2007). In the UK, grocery market share of private labels grew from 39% of sales in 2008 to 41% in 2010 (Marian 2010). Planet Retail (2007, p.1) recently concluded that "[PLs] are set for accelerated growth, with the majority of the world's leading grocers increasing their own label penetration." Private labels have gained wide attention both in the academic literature and popular business press and there is a glowing academic research to the perspective of manufacturers and retailers. Empirical research on private labels has mainly studies the factors explaining private labels market shares across product categories and/or retail chains (Dahr and Hoch 1997; Hoch and Banerji, 1993), factors influencing the private labels proneness of consumers (Baltas and Doyle 1998; Burton et al. 1998; Richardson et al. 1996) and factors how to react brand manufacturers towards PLs (Dunne and Narasimhan 1999; Hoch 1996; Quelch and Harding 1996; Verhoef et al. 2000). Nevertheless, empirical research on factors influencing the production in terms of a manufacturer-retailer is rather anecdotal than theory-based. The objective of this paper is to bridge the gap in these two types of research and explore the factors which influence on manufacturer's private label production based on two competing theories: S-C-P (Structure - Conduct - Performance) paradigm and resource-based theory. In order to do so, the authors used in-depth interview with marketing managers, reviewed retail press and research and presents the conceptual framework that integrates the major determinants of private labels production. From a manufacturer's perspective, supplying private labels often starts on a strategic basis. When a manufacturer engages in private labels, the manufacturer does not have to spend on advertising, retailer promotions or maintain a dedicated sales force. Moreover, if a manufacturer has weak marketing capabilities, the manufacturer can make use of retailer's marketing capability to produce private labels and lessen its marketing cost and increases its profit margin. Figure 1. is the theoretical framework based on a strategic market management perspective, integrated concept of both S-C-P paradigm and resource-based theory. The model includes one mediate variable, marketing capabilities, and the other moderate variable, competitive intensity. Manufacturer's national brand reputation, firm's marketing investment, and product portfolio, which are hypothesized to positively affected manufacturer's marketing capabilities. Then, marketing capabilities has negatively effected on private label production. Moderating effects of competitive intensity are hypothesized on the relationship between marketing capabilities and private label production. To verify the proposed research model and hypotheses, data were collected from 192 manufacturers (212 responses) who are producing private labels in South Korea. Cronbach's alpha test, explanatory / comfirmatory factor analysis, and correlation analysis were employed to validate hypotheses. The following results were drawing using structural equation modeling and all hypotheses are supported. Findings indicate that manufacturer's private label production is strongly related to its marketing capabilities. Consumer marketing capabilities, in turn, is directly connected with the 3 strategic factors (e.g., marketing investment, manufacturer's national brand reputation, and product portfolio). It is moderated by competitive intensity between marketing capabilities and private label production. In conclusion, this research may be the first study to investigate the reasons manufacturers engage in private labels based on two competing theoretic views, S-C-P paradigm and resource-based theory. The private label phenomenon has received growing attention by marketing scholars. In many industries, private labels represent formidable competition to manufacturer brands and manufacturers have a dilemma with selling to as well as competing with their retailers. The current study suggests key factors when manufacturers consider engaging in private label production.

• Korean Journal of Weed Science
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• v.15 no.4
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• pp.254-261
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• 1995

The nationwide weed survey was conducted in lowland rice fields over whole country of Korea in 1992 in order to determine a change of weed community and to identify a major dominant weed species and/or problem weed. Based on morphological characteristics of weeds, population ratio of broad leaf weed was 42.6%, grasses weed-9.0%, sedges-33.4% and others were 15.0%. Annual weed was 33.4% while perennial weed was 66.6% in terms of life cycle of weeds. Meanwhile, there was different weed occurrence as affected by planting method of the rice plant. In hand transplanted paddy fields predominant weed species was Sagittaria trifolia L., Monochoria vaginalis Presl., and Aneilema japonica Kunth. In machine transplanted rice fields of infant and young rice seedling Eleocharis kuroguwai Ohwi. and S. trifolia L. were more predominant. There was high occurrence of M. vaginalis, Echinochloa crus-galli L., and Leesia japonica Makino in water seeding while E. crus-galli and Cyperus serotinus Rottb. were predominant weed species in dry seeded rice. Monoculture of the rice plant would cause to high occurrence of E. kuroguwai, S. trifolia, M. vaginalis, E. crus-galli, and Sagittaria pygmaea Miq and there was higher population of S. trifolia, S. pygmaea, M. vaginalis, E crus-galli, and E. kuroguwai in double cropping system based on rice culture. In particular, there was high different weed occurrence under different transplanting times. E. kuroguwai, S. trifolia, S. pygmaea, M. vaginalis, and C. serotinus were higher population at the transplanting of 25 May and S. trifolia, E crus-galli, C. serotinus, and M. vaginalis at 10 June and S. pygmaea, E. kuroguwai, M. vaginalis, S. trifolia, and E. crusgalli at 25 June in Korea, respectively. Autumn tillage in terms of tillage time would cause more predominant weed species such as S. trifolia, E. kuroguwai, M. vaginalis, and S. pygmaea while spring tillage was higher population of E. kuroguwai, S. trifolia, E. crusgalli, M. vaginalis, and S. pygmaea. In plain area of paddy field there was higher occurrence of E. kuroguwai, S. trifolia, M. vaginalis, E. crus-galli, and S. pygmaea and in mid-mountainous area S. trifolia, E. kuroguwai, M. vaginalis, E. crus-galli, and Ludwigia prostrate Roxb. while in mountainous area S. trifolia, M. vaginalis, Potamogeton distinctus Ben., E. kuroguwai, and E. crus-galli were. In 1992 the most ten predominant weed species at the rice field of Korea based on summed dominant ratio(SDR) were E. kuroguwai > S. trifolia > E. crus-galli > M. vaginalis > S. pygmaea > C. serotinus > L. prostrate > P. distinctus > A. japonica > Scirpus juncoides Roxb.

• KDI Journal of Economic Policy
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• v.32 no.2
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• pp.93-143
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• 2010

This paper estimates the impact of Japan's economic sanction on DPRK trade in the 2000s. It conceptualizes the effects of sanction on DPRK trade, econometrically tests whether such effects exist in case of Japan's sanction using currently available DPRK trade statistics, and measures the size of the effects by correcting and reconfiguring the deficiencies of the currently available DPRK trade statistics. The main findings of the paper are as follows. First, Japan's sanction can have two different effects on DPRK trade: 'Sanction Country Effect' and "Third Country Effect.' The former means that the sanction diminishes DPRK trade with Japan while the latter refers to the effects on DPRK trade with other countries as well. The third country effect can arise not simply because the DPRK changes its trade routes to circumvent the sanction, but because the sanction forces the DPRK to readjust its major trade items and patterns. Second, currently no official DPRK trade statistics are available. Thus, the so-called mirror data referring to DPRK trading partners' statistics should be employed for the analysis of the sanction effects. However, all currently available mirror data suffer from three fundamental problems: 1) they may omit the real trade partners of the DPRK; 2) they may confuse ROK trade with DPRK trade; 3) they cannot distinguish non-commercial trade from commercial trade, whereas only the latter concerns Japan's sanction. Considering those problems, we have to adopt the following method in order to reach a reasonable conclusion about the sanction effect. That is, we should repeat the same analysis using all different mirror data currently available, which include KOTRA, IMF and UN Commodity Trade Statistics, and then discuss only the common results from them. Third, currently available mirror data make the following points. 1) DPRK trade is well explained by the gravity model. 2) Japan's sanction has not only the sanction country effect but also the third country effect on DPRK trade. 3) The third country effect occurs differently on DPRK export and import. In case of export, the mirror statistics reveal positive (+) third country effects on all of the major trade partners of the DPRK, including South Korea, China and Thailand. However, on DPRK import, such third country effects are not statistically significant even for South Korea and China. 4) This suggests that Japan's sanction has greater effects on DPRK import rather than its export. Fourth, as far as DPRK export is concerned, it is possible to resolve the abovementioned fundamental problems of mirror data and thus reconstruct more accurate statistics on DPRK trade. Those reconstructed statistics lead us to following conclusions. 1) Japan's economic sanction diminished DPRK's export to Japan from 2004 to 2006 by 103 million dollars on annual average (Sanction Country Effect). It comprises around 60 percent of DPRK's export to Japan in 2003. 2) However, for the same period, the DPRK diverted its exports to other countries to cope up with Japan's sanction, and as a result its export to other countries increased by 85 million dollars on annual average (Third Country Effect). 3) This means that more than 80 per cent of the sanction country effect was made up for by the third country effect. And the actual size of impact that Japan's sanction made on DPRK export in total was merely 30 million dollars on annual average. 4) The third country effect occurred mostly in inter-Korean trade. In fact, Japan's sanction increased DPRK export to the ROK by 72 million dollars on annual average. In contrast, there was no statistically significant increase in DPRK export to China caused by Japan's sanction. 5) It means that the DPRK confronted Japan's sanction and mitigated its impact primarily by using inter-Korean trade and thus the ROK. Fifth, two things should be noted concerning the fourth results above. 1) The results capture the third country effect caused only by trade transfer. Facing Japan's sanction, the DPRK could transfer its existing trade with Japan to other countries. Also it could change its main export items and increase the export of those new items to other countries as mentioned in the first result. However, the fourth results above reflect only the former, not the latter. 2) Although Japan's sanction did not make a huge impact on DPRK export, it might not be necessarily true for DPRK import. Indeed the currently available mirror statistics suggest that Japan's sanction has greater effects on DPRK import. Hence it would not be wise to argue that Japan's sanction did not have much impact on DPRK trade in general, simply using the fourth result above.

• The Journal of Dong Guk Oriental Medicine
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• v.8 no.2
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• pp.155-173
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• 2000

The diagnosis in Oriental medicine is done by inspection, auscultation and olfaction, interrogation, four diagnostics of pulse feeling and palpation, and various system of identification like identification according to Qi(vital energy), Xue and body fluids, identification according to fair principles, identification according to principles of Wei, Qi, Ying and Xue, identification according to Sanjiao(the triple heater), identification according to four type physical constitution. Sometimes, symptoms and diagnosis techniques according to symptoms is selectively applied for the diagnosis. Among them the pulse feeling and palpation diagnosis technique using the sense of finger and palm of the hand is divided into feeling of pulse and palpation and pressing maneuver. Pressing maneuver is a diagnosis technique pressing and rubbing the affected part in order to attain data of identification including inside and outside condition of the body with regard to the nature, condition and relative seriousness of disease. There are palpation of the skin, palpation the hand and foot, palpation the chest and the abdomen, palpation shu points in pressing maneuver. The diagnosis of the Back Shu points is a technique to examine the change of disease condition from pressure ache, spontaneous ache, tension, relaxation, solidification revealed through channels and collaterals. I investigates starting disease and an attack of disease of twelve pulse and pulse condition through the study relative to the substance and technique of pressing maneuver, and adjusts diagnosis techniques of a region for acupuncture and matters to be attended. The conclusions are as follows. 1. The Shu or stream points in which pathogenic factors go are important to medical treatment of dormant diseases like bowels disease, cold symptom complex and insufficiency symptom complex. 2. Disease classified by system is diagnosed by the condition of process part like pro-trusion, cave-in, tension, relaxation, pressure ache through palpating the Shu or stream points, that is pressing upward or downward left and right sides of the backbone process by hands. 3. In real clinic pressing maneuver of one's back side is very important to patient's diagnosis treatment. Thus, pressing maneuver of one's back side have to be done without omission. 4. Diagnosis must be accomplished through the perception about the diversity of diagnosis technique of bowels disease, the exact knowledge about pressing maneuver of one's back side for enlargement of treatment range and rising of treatment rate, and pressing maneuver of the Shu or the stream points.

• Journal of Korean Society of Environmental Engineers
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• v.31 no.2
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• pp.79-89
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• 2009

Naphthalene is a volatile, hydrophobic, and possibly carcinogenic compound that is known to have a severe detrimental effect to aquatic ecosystem. Our research examined the effects of various operating conditions (temperature, pH, initial concentration, and frequency and type of ultrasound) on the sonochemical degradation of naphthalene and OH radical production. The MDL (Method detection limit) determined by LC/FLD (1200 series, Agilient) using C-18 reversed column is measured up to 0.01 ppm. Naphthalene vapor produced from ultrasound irradiation was detected under 0.05 ppm. Comparison of naphthalene sonodegradion efficiency tested under open and closed reactor cover fell within less than 1% of difference. Increasing the reaction temperature from $15^{\circ}C$ to $40^{\circ}C$ resulted in reduction of naphthalene degradation efficiency ($15^{\circ}C$: 95% ${\rightarrow}$ $40^{\circ}C$: 85%), and altering pH from 12 to 3 increased the effect (pH 12: 84% ${\rightarrow}$pH 3: 95.6%). Pseudo first-order constants ($k_1$) of sonodegradation of naphthalene decreased as initial concentration of naphthalene increased (2.5 ppm: $27.3{\times}10^{-3}\;min^{-3}\;{\rightarrow}$ 10 ppm : $19.3{\times}10^{-3}\;min^{-3}$). Degradation efficiency of 2.5 ppm of naphthalene subjected to 28 kHz of ultrasonic irradiation was found to be 1.46 times as much as when exposed under 132 kHz (132 kHz: 56%, 28 kHz: 82.7%). Additionally, its $k_1$ constant was increased by 2.3 times (132 kHz: $2.4{\times}10^{-3}\;min^{-1}$, 28 kHz: $5.0{\times}10^{-3}\;min^{-1}$). $H_2O_2$ concentration measured 10 minutes after the exposure to 132 kHz of ultrasound, when compared with the measurement under frequency of 28 kHz, was 7.2 times as much. The concentration measured after 90 minutes, however, showed the difference of only 10%. (concentration of $H_2O_2$ under 28 kHz being 1.1 times greater than that under 132 kHz.) The $H_2O_2$ concentration resulting from 2.5 ppm naphthalene after 90 minutes of sonication at 24 kHz and 132 kHz were lower by 0.05 and 0.1 ppm, respectively, than the concentration measured from the irradiated M.Q. water (no naphthalene added.) Degradation efficiency of horn type (24 kHz) and bath type (28 kHz) ultrasound was found to be 87% and 82.7%, respectively, and $k_1$ was calculated into $22.8{\times}10^{-3}\;min^{-1}$ and $18.7{\times}10^{-3}\;min^{-1}$ respectively. Using the multi- frequency and mixed type of ultrasound system (28 kHz bath type + 24 kHz horn type) simultaneously resulted in combined efficiency of 88.1%, while $H_2O_2$ concentration increased 3.5 times (28 kHz + 24 kHz: 2.37 ppm, 24 kHz: 0.7 ppm.) Therefore, the multi-frequency and mixed type of ultrasound system procedure might be most effectively used for removing the substances that are easily oxidized by the OH radical.

• Tuberculosis and Respiratory Diseases
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• v.48 no.6
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• pp.922-931
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• 2000

Background : It has been well known that bronchia1 asthma is a chronic airway inflammatory disorder. Recently, sputum induced with hypertonic saline was introduced as a simple and useful nonivasive medium to investigate airway inflammation and symptom severity in patients with asthma. We examined the eosinophil, eosinophil cationic protein (ECP), interleukin(IL)-3, IL-5, granulocyte-macrophage colony-stimulating facta (GM-CSF), and nitric oxide (NO) derivatives in induced sputum from patients with bronchia1 asthma in order to determine the role of NO and various inflammatory cytokines as a useful markers of airway inflammation or changes in pulmonary function tests and symptoms. Methods : A total 30 patients with bronchia1 asthma received oral prednisolone 30 mg daily for 2 weeks. Forced expiratory volume in one second ($FEV_1$), total blood eosinophil count and induced sputum eosinophil count, ECP, IL-3, IL-5, GM-CSF, and NO derivatives were determined before and after the administration of prednisolone. Results : Of the 30 patients, 13 (43.3%) were male and 17 (56.7%) were female. The mean age of patients was 41.8 years (range 19-64 years). Two patients could not produce sputum at the second study and 3 could not be followed up after their first visit. Two weeks after the prednisolone administration, there was a significant increase in $FEV_1$ (% of predicted value) from 78.1$\pm$20.6 % to 90.3$\pm$ 18.3 % (P<0.001). The eosinophil percentages in induced sputum were significantly decreased after treatment with prednisolone, with values of 56.1$\pm$27.2 % versus 29.6$\pm$21.3 % (P<0.001), and ECP were $134.5\pm68.1\;{\mu}g/L$ versus $41.5\pm42.4\;{\mu}g/L$ (P<0.001) respectively. After the prednisolone treatments, the eotaxin concentration also showed a decreasing tendency from 26.7$\pm$12.8 pg/ml to 21.7$\pm$8.7 pg/ml. There was a decreasing tendency but no significant differences in total blood eosinophil count (425.7$\pm$265.9 vs 287.7$\pm$294.7) and in the concentration of NO derivatives ($70.4\pm44.6{\mu}mol/L$ vs $91.5\pm48.3\;{\mu}mol/L$) after the prednisolone treatments. IL-3, IL-5, GM-CSF were undetectable in the sputum of most subjects either before the prednisolone treatments or after the treatments. Before the prednisolone treatments, a significant inverse correlation was observed between FEV1 and sputum ECP (r=-D.364, P<0.05) and there was a significant correlation between sputum eosinophils and eotaxin (r=0.369, P<0.05) Conclusion : The eotaxin and ECP concentration in induced sputum may be used as markers of airway inflammation after treatments in bronchia1 asthma. In addition, the measurement of sputum eosinophil percent ages is believed to be a simple method displaying the degree of airway inflammation and airway obstruction before and after the prednisolone treatment in bronchia1 asthma. However, unlike exhaled NO, the examination of NO derivatives with Griess reaction in induced sputum is considered an ineffective marker of changing airway inflammation and obstructing symptoms.

• Journal of Global Scholars of Marketing Science
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• v.18 no.1
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• pp.33-58
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• 2008

Previous research has presupposed that the evaluation of consumer who received any recovery after experiencing product failure should be better than the evaluation of consumer who did not receive any recovery. The major purposes of this article are to examine impacts of product defect failures rather than service failures, and to explore effects of recovery on postrecovery product attitudes. First, this article deals with the occurrence of severe and unsevere failure and corresponding service recovery toward tangible products rather than intangible services. Contrary to intangible services, purchase and usage are separable for tangible products. This difference makes it clear that executing an recovery strategy toward tangible products is not plausible right after consumers find out product failures. The consumers may think about backgrounds and causes for the unpleasant events during the time gap between product failure and recovery. The deliberation may dilutes positive effects of recovery efforts. The recovery strategies which are provided to consumers experiencing product failures can be classified into three types. A recovery strategy can be implemented to provide consumers with a new product replacing the old defective product, a complimentary product for free, a discount at the time of the failure incident, or a coupon that can be used on the next visit. This strategy is defined as "a rewarding effort." Meanwhile a product failure may arise in exchange for its benefit. Then the product provider can suggest a detail explanation that the defect is hard to escape since it relates highly to the specific advantage to the product. The strategy may be called as "a strengthening effort." Another possible strategy is to recover negative attitude toward own brand by giving prominence to the disadvantages of a competing brand rather than the advantages of its own brand. The strategy is reflected as "a weakening effort." This paper emphasizes that, in order to confirm its effectiveness, a recovery strategy should be compared to being nothing done in response to the product failure. So the three types of recovery efforts is discussed in comparison to the situation involving no recovery effort. The strengthening strategy is to claim high relatedness of the product failure with another advantage, and expects the two-sidedness to ease consumers' complaints. The weakening strategy is to emphasize non-aversiveness of product failure, even if consumers choose another competitive brand. The two strategies can be effective in restoring to the original state, by providing plausible motives to accept the condition of product failure or by informing consumers of non-responsibility in the failure case. However the two may be less effective strategies than the rewarding strategy, since it tries to take care of the rehabilitation needs of consumers. Especially, the relative effect between the strengthening effort and the weakening effort may differ in terms of the severity of the product failure. A consumer who realizes a highly severe failure is likely to attach importance to the property which caused the failure. This implies that the strengthening effort would be less effective under the condition of high product severity. Meanwhile, the failing property is not diagnostic information in the condition of low failure severity. Consumers would not pay attention to non-diagnostic information, and with which they are not likely to change their attitudes. This implies that the strengthening effort would be more effective under the condition of low product severity. A 2 (product failure severity: high or low) X 4 (recovery strategies: rewarding, strengthening, weakening, or doing nothing) between-subjects design was employed. The particular levels of product failure severity and the types of recovery strategies were determined after a series of expert interviews. The dependent variable was product attitude after the recovery effort was provided. Subjects were 284 consumers who had an experience of cosmetics. Subjects were first given a product failure scenario and were asked to rate the comprehensibility of the failure scenario, the probability of raising complaints against the failure, and the subjective severity of the failure. After a recovery scenario was presented, its comprehensibility and overall evaluation were measured. The subjects assigned to the condition of no recovery effort were exposed to a short news article on the cosmetic industry. Next, subjects answered filler questions: 42 items of the need for cognitive closure and 16 items of need-to-evaluate. In the succeeding page a subject's product attitude was measured on an five-item, six-point scale, and a subject's repurchase intention on an three-item, six-point scale. After demographic variables of age and sex were asked, ten items of the subject's objective knowledge was checked. The results showed that the subjects formed more favorable evaluations after receiving rewarding efforts than after receiving either strengthening or weakening efforts. This is consistent with Hoffman, Kelley, and Rotalsky (1995) in that a tangible service recovery could be more effective that intangible efforts. Strengthening and weakening efforts also were effective compared to no recovery effort. So we found that generally any recovery increased products attitudes. The results hint us that a recovery strategy such as strengthening or weakening efforts, although it does not contain a specific reward, may have an effect on consumers experiencing severe unsatisfaction and strong complaint. Meanwhile, strengthening and weakening efforts were not expected to increase product attitudes under the condition of low severity of product failure. We can conclude that only a physical recovery effort may be recognized favorably as a firm's willingness to recover its fault by consumers experiencing low involvements. Results of the present experiment are explained in terms of the attribution theory. This article has a limitation that it utilized fictitious scenarios. Future research deserves to test a realistic effect of recovery for actual consumers. Recovery involves a direct, firsthand experience of ex-users. Recovery does not apply to non-users. The experience of receiving recovery efforts can be relatively more salient and accessible for the ex-users than for non-users. A recovery effort might be more likely to improve product attitude for the ex-users than for non-users. Also the present experiment did not include consumers who did not have an experience of the products and who did not perceive the occurrence of product failure. For the non-users and the ignorant consumers, the recovery efforts might lead to decreased product attitude and purchase intention. This is because the recovery trials may give an opportunity for them to notice the product failure.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.79-96
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• 2012

As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.