PURPOSES: The purpose of this study is to compare the advantages and disadvantages of 3D multichannel ground penetrating radar (GPR) equipment, which is mainly used for road cavity detection. The optimal signal analysis method was also proposed for 3D GPR data. METHODS: Four types of 3D GPR equipment were used to detect road cavities in a pilot road section in Seoul. The obtained GPR signals were evaluated in the time and frequency domain using raw data. In addition, various types of filters were applied to time domain (B-scan) data to examine the optimal signal processing. RESULTS: The time and frequency domain analysis of raw data showed that all the equipment produced reverse and strong signal reflections owing to the low dielectric permittivity of air in the cavity compared with neighbor materials. Also, the asymmetric parabolic curve was observed as well. The optimal signal processing method was determined to detect road cavities: zero-setting and background removal should be applied to all equipment. Bandpass filtering can be optionally applied to remove high-frequency noise or direct waves. CONCLUSIONS: Despite the different specifications of GPR equipment in terms of signal generation and bandwidth, the GPR signals were appropriate in terms of zero-setting, noise level, and depth of investigation. Therefore, all the multichannel GPR devices evaluated were found to be suitable to detect road cavities located at depths of 1.0 and 1.5 m after the application of proper filtering process.

Social interactions have been established as a means to help promotions and sales for manufacturers and retailers. Word-of-mouth (WOM), in particular, is proven to increase awareness and drive purchases. Given that small offline retailers have limited resources in marketing, online WOM can play a key role for their offline business performance. In this paper, we focus on two types of online WOM, public discussion and social referral, and study their generation processes by taking into account the multichannel context of both online purchases and offline consumption. To this end, we combine data from three sources: product (or deal)-level sales from a major deal site in South Korea, social interaction records collected by web crawling, and retail revenues at a district level from Korea National Statistical Office. We use a multivariate poison lognormal model to estimate three equations in the same structure with correlated errors, which only differs by the following dependent variables: number of product discussion, number of social referral, and the number of social coupons sold. Our empirical analyses suggest the following. First, the two types of WOM respond in opposite directions for the influencers in the multichannel sales context: the greater number of co-located online deals decreases public discussion but increases social referral. Next, the larger offline retail size increases public discussion, but has no significant effect on social referral. Finally, the results provide practical insights that small offline retailers can improve sales in the multichannel context by effectively managing the generation of different types of online WOM.

Multi-channel shopping, along with the arrival of smartphones, is the most significant change that has taken place in retail lately. Mobile shopping behaviors are considerably different from the shopping behaviors of other existing channels such as offline, TV, and the Internet. However, initially, Korean retail companies had trouble coping with this market change owing to a lack of understanding of mobile shopping behaviors. Therefore, they espoused big data analytics, expecting to obtain customer insights on not only mobile shopping behaviors but also multi-channel shopping behaviors. This case study discusses a trial made by a leading Korean multi-channel retail company to implement big data analytics in its marketing. The company was confronted with two issues, which prompted it to embrace big data marketing. First, the company recognized that it is extremely important to understand customer behavior across the entire shopping process and accordingly conduct the targeted marketing. Second, the company seeked to encourage the customers who used only a single channel to use diverse channels for sales as well as retention. The company thus tried to develop its rules for triggered marketing by analyzing the behavioral characteristics of multi-channel customers. For this, behavioral data for three years, covering about 10 million customers, were gathered and analyzed. Lastly, the company came up with detectable customer metrics that were expected to forecast the sales. In addition, customer segments were derived from data clustering based on customers’ shopping pattern, and marketing strategies were developed accordingly. Furthermore, the big data analytics revealed the importance of returning customers, and recommended modification to the royalty program and promotion of specific product categories. This case study proved the merits and demerits of big data analytics. On one hand, it helps in understanding the market trends of complex environments such as multichannel retail, and the significance of developing marketing strategies accordingly and reaping immediate benefits. On the other hand, it analyzes only the data of a given condition; therefore, it is hard to forecast the results if the condition, such as product-related offers, changes considerably. Big data marketing seems to work more effectively when it is used in combination with other qualitative research. This case study shows the status of big data marketing in a Korean multi-channel retail company and highlights its potentials as well as limits in this industry. change that has taken place in retail lately. Mobile shopping behaviors are considerably different from the shopping behaviors of other existing channels such as offline, TV, and the Internet. However, initially, Korean retail companies had trouble coping with this market change owing to a lack of understanding of mobile shopping behaviors. Therefore, they espoused big data analytics, expecting to obtain customer insights on not only mobile shopping behaviors but also multi-channel shopping behaviors. This case study discusses a trial made by a leading Korean multi-channel retail company to implement big data analytics in its marketing.

Recently, more and more consumers have changed from shopping in a single channel to multi-channel. Therefore, maintaining a long-term customer relationship becomes an important issue for retailers in this complex shopping circumstance. This study decides to understand how online retailers keep their valuable consumers in current store and even duplicate the original relationship to an extended channel.

With the diffusion of smart-phones and mobile equipment, as well as the emergence of consumption patterns like showrooming and reverse showrooming, not only online shopping, but also offline stores are becoming important. For this reason, a multichannel which simultaneously runs both offline and online channels is getting the spotlight. A multichannel means a series of activities related to selling goods and services to consumers via more than one channel (Levy & Weitz, 2011). To adapt to this change of the retail environment, the Dongdaemun market, the source of Korean mass fashion, is introducing a multichannel to manage online and offline channels together. ‘Style Nanda’, based on Dongdaemun, is a representative branding case. Having starting with an online shopping mall, ‘Style Nanda’ is now running offline stores and is planning to enter overseas markets. Another example is that of Roompacker which has grown up from an offline store in the Dongdaemun Doota Shopping Mall launched in 2005 and is now emerging as the online and offline powerful actor in the market. As mentioned above, Dongdaemun fashion market-based brands are competitive when they have a multichannel to simultaneously run offline channels, online, and mobile channels. The existing Dongdaemun fashion market-related research has been limited to the analysis of Dongdaemun market’s structural characteristics or the consumer perception of the shopping conditions (Hong & Lee, 2007; Choi & Choo, 2005). Also, most multi-channel studies have focused on the consumer perceptions depending on the channel characteristics; therefore, the studies that measured consumer responses depending on the brand characteristics are very scarce. With the change in the retail environment and the increase in the necessity of revitalizing Dongdaemun commercial districts, a study on the multi-channel properties of the Dongdaemun brands would provide many useful implications. In this context, this research aims to analyze the characteristics of the Dongdaemun market, which is offline-optimized, as well as the utilities and attributes of multichannel shopping services of Dongdaemun fashion brands. Our second aim is to provide implications for marketing. In particular, this research is focused on the effects of these attributes on value equity, relationship equity, and brand equity which are customer equity drivers of Dongdaemun fashion brand consumers. Furthermore, this research explores the effects of customer equity drivers on customer satisfaction and purchase intention. A total of 200 samples were collected to examine the effects on customer equity drivers of Dongdaemun multichannel attributions by consumers in Dongdaemun Fashion Market. The collected data were then analyzed statistically (exploratory factor analysis, reliability analysis, and descriptive statistics) with SPSS 21.0. Furthermore, AMOS 18.0 was used for confirmatory factor analysis and multiple group analysis. The results of this research will serve as a foundation for a distribution channel research to measure the characteristics of Dongdaemun and customer equity regarding a multichannel. They will also be practically helpful in establishing a strategy to introduce a multichannel of offline-centered brands.

목 적 : 신호대 잡음비는 자기공명영상 장치의 성능과 영상의 질을 평가하기 위한 객관적인 정보를 제공하는 중요한 척도이며 이를 측정하기 위한 많은 방법들이 제안되고 있다. 그 중 두 영역 측정방법은 측정방법이 간단하고 시간이 짧기 때문에 가장 흔히 사용되고 있다. 본 연구에서는 다중채널코일과 병렬영상기법 적용 시 두 영역측정방법에 의해 산출된 신호대 잡음비의 정확성에 대해 알아보고자 하였다. 대상 및 방법 : 장비는 Philips 3.0T MRI(Achieva, Philips medical system, Netherlands)과 transmit receive head coil, SENSE 8 channel head coil을 사용하였으며 MR sequence는 spin echo T1, T2 강조영상을 사용하여 축상면으로 ACR phantom 영상을 획득하였다. Transmit receive head coil을 사용한 두 영역 측정방법, AAPM, NEMA, Philips에서 제안한 측정방법, 다중채널코일과 병렬영상기법 적용 시 두 영역 측정방법의 신호대 잡음비 측정 조건에 따라 T1, T2 강조영상을 각각 30번씩 획득하였으며 Image J를 사용하여 각 영상의 동일한 위치에서 ROI 크기를 10 mm2으로 하여 신호대 잡음비를 측정하였다. 결 과 : T1 강조영상의 경우 AAPM에서 제안한 방법이 가장 균일한 신호대 잡음비를 나타내었으며 transmit receive head coil을 사용한 두 영역 측정방법과 NEMA는 10% 내외의 상대 표준 편차를 가짐으로써 균질한 값을 보였다. 하지만 다중 채널 코일과 병렬 영상 기법을 적용한 두 영역 측정방법의 경우 20% 이상의 상대 표준 편차를 보여 각 실험마다 신호대 잡음비의 큰 차이를 나타내었고 NEMA와 transmit receive head coil을 사용한 두 영역 측정방법에 비해 신호대 잡음비를 측정한 각각의 영역에서 차이를 나타내었다. T2 강조영상의 경우 transmit receive head coil을 사용한 두 영역 측정방법, AAPM, NEMA, Philips 모두 10% 내외의 상대 표준 편차를 가져 균일한 SNR을 나타내었지만 다중채널코일과 병렬영상기법을 적용한 두 영역측정방법의 경우 20% 이상의 상대 표준 편차를 보여 신호대 잡음비의 차이를 나타내었다. 결 론 : 다중 채널 코일과 병렬 영상 기법 적용 시 잡음의 공간적, 통계적 분포에 영향을 미치기 때문에 두 영역 측정방법으로 산출한 신호대 잡음비는 정확성이 감소하게 된다. 따라서 다중 채널 코일과 병렬 영상 기법을 적용한 영상에서 좀 더 정확한 신호대 잡음비를 산출하기 위해 AAPM, NEMA, Philips에서 제안되는 방법을 이용해야 한다.

Using multiple channels along the buying process is common for today’s consumers. Research suggests that additional channels enhance customer satisfaction and ultimately customer loyalty. However, research that focuses on the relationship between satisfaction with multichannel performance and behavioral consequences is relatively sparse. As this topic is of tremendous importance for retail practice this study attempts to investigate main drivers of consumer satisfaction in a multichannel environment and the consequences concerning consumer behavior and loyalty. Therefore we take on an approach of Renoux (1973) that considers explicitly the aspect of the consumer decision stage in order to explain satisfaction with a multichannel retailer. The study focuses on satisfaction in the pre-purchase and purchase stage. Furthermore, it is investigated whether the perceived integration of channels has an influence on satisfaction with a multichannel retailer. Results of a structural equation model based on a survey among 171 German multichannel shoppers show that satisfaction in the pre-purchase stage is a crucial predictor of consumer’s overall satisfaction with a multichannel retailer. It has also a strong impact on satisfaction in purchase stage and can therefore influence the buying decision. To add, perception of the integration of channels positively influences the overall satisfaction with the multichannel retailer. Satisfaction, in turn, can lead to loyalty to the multichannel retailer and thereby influences repurchase and supplementary purchase intention, and recommendation intention. The study concludes with managerial implications and suggests directions for further research.

The multiplicity of channels and the ubiquitous access to product information represent major service innovations that new technologies have incorporated into the purchase process. This research analyzes how consumer and seller recommendations affect the consumer’s purchase decision and confidence in a multichannel service context based on an online-offline sequence.

Online advertisers use multiple channels to reach consumers on the Internet. However, little is known on the interplay between online advertising channels. To fill this gap, this study provides a comprehensive overview of interaction effects in online advertising for individual consumers, including not only site visits, but also exposures that do not directly lead to a click. Based on a large cookie-based individual-level data set the authors analyze interaction effects within and between channel groups on purchase behavior. By classifying online marketing channels along the dimensions of initiation locus and previous brand awareness, they find significant interactions between contacts within and across channel types. While clicks following contacts in customer-initiated channels that require brand awareness overall have a negative effect on purchase propensity, previous clicks in firm-initiated channels positively interact with clicks in customer-initiated channels. The results can help managers to coordinate marketing strategies, optimize campaigns, and develop individualized marketing and targeting approaches.

본 연구에서는 2종류의 다채널 알루미나 세라믹 정밀여과막으로 호소수를 처리할 경우, 질소 역세척 시간(BT) 및 막간압력차(TMP) 영향과 최적운전조건을 규명하였다. 정상여과시간(FT)은 8분, 유량 2.0 L/min, 역세척 압력 2.0 bar로 고정하였고, BT는 10∼60초, TMP는 0.6~2.0 bar로 변화시켰다. 또한, 최적운전조건은 막오염에 의한 저항 (Rf), 무차원한 투과선속 (J/Jo), 투과선속 (J), 총여과부피VT의 측면에서 고찰하였다. 그 결과, 0.4 μm의 평균기공 크기를 갖고 있는 HC04 분리막의 최적 역세척 조건은 BT=10초, 1.0 μm의 평균기공인 HC10 분리막에서는 20초임을 알 수 있었다. 한편, TMP가 증가할수록 구동력의 증가로 보다 많은 VT를 얻을 수 있었다. 오염물질 제거율은 탁도(Turbidity) 95.4% 이상, 화학적 산소 요구량 (CODMn) 12.7∼20.1%, 암모니아성 질소(NH3-N) 0.0∼6.4%, 총질소 (T-N) 1.9∼4.6%, 총인 (T-P) 34.9∼88.4%의 제거 율을 보였다.

다중채널 탄성파 자료를 이용하여 낙동강 하구 삼각주 지역 연약지반의 지반 특성을 구하기 위하여 S파 속도와 Qs-1 구조를 구하고 이를 시추조사 결과와 비교하였다. 다중채널 신호의 분산곡선을 역산하여 S파 속도구조를 구하고 감쇠지수(attenuation coefficient)를 구하였다. 다중채널 신호 중 음원에서 가장 가까운 신호를 기준 신호로 정하고 10 Hz에서 45 Hz 사이의 주파수에 대하여 거리에 따라 기준 신호에 대한 진폭의 비가 감소하는 정도를 나타내는 기울기를 구하여 감쇠지수를 결정하였다. 이 감쇠지수를 역산하여 지반 최상부 8 m 층의 S파 속도와 함께 Qs-1를 구하였다. 이 지역의 시추조사에 의하면 이 지역의 지층은 크게 상부 4 m 실트질 모래층과 하부 4 m 실트질 점토층으로 나누어진다. 표면파 역산에 의해 구해진 S파 속도와Qs-1를 시추조사 결과와 비교해보면, 상부 실트질 모래층에서 S파 속도의 공간적 해상도는 약 80m/sec로 하부 실트질 점토층의 속도 40m/sec보다 상대적으로 높은 값을 보인다. 각 층에서 S파 속도의 공간적 해상도는 뚜렷하다. Qs-1의 공간구조는 상부 실트질 모래층에서 약 0.02를 보이고 하부 실트질 점토층에서 0.03으로 증가하는 양상을 보인다. Qs-1의 공간적 해상도는 상부 약 5 m 구간에서는 양호하나 그 보다 깊은 곳에서는 공간적 해상도가 아주 낮아지는 것을 볼 수 있다. 이 조사지역에서는 실트질 모래층에서 실트질 점토층보다 높은 S파 속도가 나타나고 낮은 Qs-1 값을 보인다. 그러나, 지반의 S파 속도와 Qs-1를 결정하는 다른 많은 요인들이 있으므로 이를 일반화하기 위해서는 연약지반의 S파 속도와Qs-1에 관한 자료와 연구가 집적되어야 할 것이다.