• 산업경영시스템학회지
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• 제43권4호
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• pp.93-106
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• 2020

This research explores how imported automobile companies can develop their strategies to improve the outcome of their recalls. For this, the researchers analyzed patterns of recall demand, classified recall types based on the demand patterns and examined response strategies, considering plans on how to procure parts and induce customers to visit workshops, recall execution capacity and costs. As a result, recalls are classified into four types: U-type, reverse U-type, L- type and reverse L-type. Also, as determinants of the types, the following factors are further categorized into four types and 12 sub-types of recalls: the height of maximum demand, which indicates the volatility of recall demand; the number of peaks, which are the patterns of demand variations; and the tail length of the demand curve, which indicates the speed of recalls. The classification resulted in the following: L-type, or customer-driven recall, is the most common type of recalls, taking up 25 out of the total 36 cases, followed by five U-type, four reverse L-type, and two reverse U-type cases. Prior studies show that the types of recalls are determined by factors influencing recall execution rates: severity, the number of cars to be recalled, recall execution rate, government policies, time since model launch, and recall costs, etc. As a component demand forecast model for automobile recalls, this study estimated the ARIMA model. ARIMA models were shown in three models: ARIMA (1,0,0), ARIMA (0,0,1) and ARIMA (0,0,0). These all three ARIMA models appear to be significant for all recall patterns, indicating that the ARIMA model is very valid as a predictive model for car recall patterns. Based on the classification of recall types, we drew some strategic implications for recall response according to types of recalls. The conclusion section of this research suggests the implications for several aspects: how to improve the recall outcome (execution rate), customer satisfaction, brand image, recall costs, and response to the regulatory authority.

• 생명과학회지
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• 제16권4호
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• pp.632-639
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• 2006

본 연구에서는 lacZ transcriptional fusion plasmid를 이용하여 광합성 세균인 Rhodobacter sphaeroides에서의 7가지 광합성유전자 (puf, puc, puhA, bchC, bchE, bchF, bchI) 발현의 경향과 조절을 조사하였다. R. sphaeroides에서 puhA와 bchI를 제외한 모든 광합성유전자들이 호기적 조건과 비교했을 때 혐기적 조건에서 더욱 강하게 발현되었다. puhA 유전자는 bchFNBHLM-RSP0290과 operon을 형성하며, bchI 유전자는 crtA와 operon을 이루는 것으로 나타났다. 광합성 조건에서 자란 R. sphaeroides의 puf, puc, bchCXYZ operon의 발현은 빛의 세기에 비례하는 반면, bchFNBHLM(RSP0290 puhA) operon의 발현은 빛의 세기에 반비례 하였다. bchEJG의 발현은 $10\;W/m^2$의 빛이 조사된 광합성 조건에서 제일 낮았으며, $100\;W/m^2$의 빛의 광합성 조건에서 가장 높았다. R. sphaeroides의 산소인지와 빛 인지에 관련된 세 가지 주요 조절기작에 의한 광합성유전자 조절은 다음과 같다. puf와 bchC는 PpsR repressor와 PrrBA two-component system에 의해 조절된다. 그리고 puc operon은 PpsR, FnrL, PrrBA system에 의해 조절된다. bchE의 발현은 FnrL과 PrrBA system에 의해 조절되는 반면, bchF는 오로지 PpsR에 의해서만 조절된다. PpsR repressor는 강한 세기의 빛 조건에서 bchf 발현억제의 원인이 되며, FnrL은 그 자체가 산소를 인지하는 기능 이외에도 세포질의 산화/환원 상태의 인지에 관련될 것으로 보인다.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1520-1520
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• 2001

Food adulteration is a serious consumer fraud and a potentially dangerous practice. Regulatory authorities and food processors require a rapid, non-destructive test to accurately confirm authenticity in a range of food products and raw materials. Olive oil is prime target for adulteration either on the basis of the processing treatments used for its extraction (extra virgin vs virgin vs ordinary oil) or its geographical origin (e.g. Greek vs Italian vs Spanish). As part of an investigation into this problem, some preliminary work focused on the ability of near infrared spectroscopy to discriminate between virgin olive oils from separate regions of the Mediterranean i. e. Crete and the Peloponese. A total of 46 oils were collected: 18 originated in Crete and 28 in the Peloponese. Oils were stored in a temperature-controlled room at 2$0^{\circ}C$ prior to spectral collection at room temperature (15-18$^{\circ}C$). Samples (approximately 0.5$m\ell$) were placed in the centre of the quartz window in a camlock reflectance cell; the gold-plated baking plate was then gently placed into the cell against the glass so as to minimize the formation of air bubbles. The rear of the camlock cell was then screwed into place producing a sample thickness of 0.5mm. Spectra were recorded between 400 and 2498nm at 2nm intervals on a NIR Systems 6500 scanning monochromator. Spectral collection took place over 2-3 days. Data were analysed using both WINISI and The Unscrambler software to investigate the possibility of discriminating between the oils from Crete and the Peloponese. A number of data pre-treatments were used and discriminant models were developed using discriminant PLS (WINISI & Unscrambler) and SIMCA (Unscrambler). Despite the small number of samples involved, a satisfactory discrimination between these two oil types was achieved. Graphical examination of principal component scores for each oil type also holds out the possibility of separating oils from either Crete and the Peloponese on the basis of districts within each region. These preliminary data suggest the potential of near infrared spectroscopy to act as a screening technique for the confirmation of geographic origin of extra virgin olive oils. The sample presentation strategy adopted uses only small volumes of material and produces high quality spectra.