In this study, text mining was conducted on the product names of skirts, pants, shirts/ blouses, and dresses to analyze the characteristics of keywords appearing in online shopping product names. As a result of frequency analysis, the number of keywords that appeared 0.5% or more for each item was around 30, and the number of keywords that appeared 0.1% or more was around 150. The cumulative distribution rate of 150 terms was around 80%. Accordingly, information on 150 key terms was analyzed, from which item, clothing composition, and material information were the found to be the most important types of information (ranking in the top five of all items). In addition, fit and style information for skirts and pants and length information for skirts and dresses were also considered important information. Keywords representing clothing composition information were: banding, high waist, and split for skirts and pants; and V-neck, tie, long sleeves, and puff for shirts/blouses and dresses. It was possible to identify the current design characteristics preferred by consumers from this information. However, there were also problems with terminology that hindered the connection between sellers and consumers. The most common problems were the use of various terms with the same meaning and irregular use of Korean and English terms. However, as a result of using co-appearance frequency analysis, it can be interpreted that there is little intention for product exposure, so it is recommended to avoid it.

This research examines how inter-price relationships among base and add-on products affect the sales of a new add-on product in the mobile gaming context. Based on theories of price fairness, product familiarity and price-quality relationship, a research model was drawn and tested on a sample of 6,766 weekly observations derived from 74 base games and 514 add-on virtual goods. Our empirical results show that the relative price of a new add-on product, when compared to the base game price, is negatively related to the add-on product sales, but positively related to its sales, when compared to prices of existing add-on products. Furthermore, the inter-price relationships among base and add-on gaming products are moderated by visual richness and game genre. This study provides the implications for IS research and practice.

Digital channels have been rising to the major shopping paths from the past few years, yet it is interesting to notice that more and more digital retailers advance into offline channel nowadays due to the benefits. For example, the digital retailing giant Amazon opened its first bricks-and-mortar bookstore in 2015. Dell, which distributes its products only in the catalog and digital channels, entered the leading retail stores such as Best Buy and Walmart. The digital retailers’ strategy trend that moves into the real world reveals the unique and powerful capabilities of the offline distribution channel and the importance of launching products in the offline channel. Previous studies in marketing have investigated various complement and substitute impacts of offline channel introduction (i.e., Avery et al. 2012, Wang and Goldfarb 2017). However, most of the literature focus on the pc-based online channel and catalog, there is little research about the impact of offline channel introduction on smartphone-based mobile channel. Although mobile channel is similar to online channel in many ways (i.e., internet access and convenient shopping), it can be distinguished from online channel in terms of search and access, leading to a different interplay with offline channel. This research, therefore, aims to investigate how product launching in offline channel affects purchases in mobile channel versus online channel, and deepen the understanding by exploring the moderating effect of offline store intensity. Besides, we also explore the interaction between two digital channels: online channel and mobile channel. As most of the multi-channel retailers offer products in both online and mobile channels, it is incremental to know the interplay between these two digital channels. Using data from a representative multichannel retailer selling beauty products, we find the following three empirical results. First, product introduction in offline channel has a positive effect on online and mobile sales, and the effect is greater for mobile. Second, as offline store increases, the positive impact of offline product launch weakens on online channel, and even turns to negative once the number of offline stores reaches a threshold. However, the influence on mobile channel stays the same. The results reflect that the complementary interplay between offline and mobile channel is relatively stronger than between online channel. Finally, within the digital channels, online purchases only increase with the growth of sales performance within online channel, whereas mobile purchases are positively affected by both within mobile channel sales and across online channel sales. Our findings contribute critical academic and managerial implications for multichannel retailing.

This paper presents a way of classifying qualitative online consumer reviews (OCRs) in terms of functional and emotional dimensions and measures the direct and indirect impact of both volume and valence of OCRs on product sales. Utilizing four million online postings across 342 mobile games for thirty months, the authors use text analysis and word classification and identify 74 representative words to describe the various levels of functional OCRs consisting of product quality, product innovativeness, price acceptability, and product simplicity, and emotional OCRs including anger, fear, shame, love, contentment, and happiness. They combine the resulting OCR volumes with weekly sales, resulting in 1,835 observations for analysis with hierarchical Bayesian methods. Results suggest that the volume and valence of aggregated functional OCRs and the valence of aggregated emotional OCRs have the positive effects on sales. The volume and valence of functional OCR subcategories have mixed effects on sales and the link is moderated by the share of emotional OCR subcategories. Further, a sales forecasting model which includes 13 variables of OCR subcategories shows the best predictive validity.

본 연구에서는 온라인 쇼핑몰 상황에서 이전사업경험, 제품속성과 온라인 고객 의견이 신제품 매출성과에 미친 영향을 살펴보았다. 인터넷 쇼핑몰에서 제품 성과에 대한 연 구들은 선진국 온라인 쇼핑몰을 중심으로 고객들의 구전효과에 초점을 두고 연구를 진행해 왔으며 상대적으로 기업특성이나 제품속성에 대한 연구는 미흡하였다. 본 연구에서는 중국 인터넷 쇼핑몰에서 판매중인 총 407개 TV모델들을 대상으로 기업특성, 제품속성 및 온라인 고객의견이 제품 매출성과에 미친 영향을 살펴보았다. 기업특성에서는 이전TV제조업체들의 제품이 신규 진입기업들의 제품들보다 매출성과가 높았다. 제품속성에서는 경쟁제품 대비 초기 가격수준이 낮을수록 성과가 높으며 가격할인율이 높은 경우에는 오히려 매출성과가 낮았다. 전반적인 제품의 기술경쟁력 수준이 높을수록 판매성과가 높으며 신기능의 특성에 따라 매출성과에 미친 효과는 다르게 나타났다. 제품별 온라인 고객평가 의견수가 많을수록 해당 제품의 매출성과는 높은 것으로 나타난 반면, 온라인 고객평가 점수는 매출성과에 유의 한 영향관계나 나타나지 않았다. 본 연구에서는 온라인 쇼핑몰 상황에서 신제품 매출성과 향 상을 위한 이론적 실무적 의의를 제시하고 향후 연구과제들을 제시하였다.

신제품 또는 신기술의 개발은 기업의 생존과 직결한 문제로써 급변하는 경영환 경과 심화하는 경쟁 속에서 성과 창출과 향상에 대한 관심이 증대하고 있다. 그러나 중소기 업은 국가 경제에서 차지하는 위상에 비해 규모와 보유자원 등의 한계를 가지므로 국가에서 는 다양한 정책적 지원을 제공한다. 조직수명주기에 관한 연구에 따르면 성장단계별로 기업 의 한계와 애로사항이 다르므로 차별적 지원이 이루어져야 할 필요가 있음을 알 수 있다. ‘2011년 중소기업기술통계’에 응답한 2,575개 기업 자료를 대상으로 기술개발공정의 기술 능력 수준과 편차가 R&D 매출성과에 어떤 영향을 끼치는지 검증하였다. 분석 결과, 기술능 력 수준은 R&D 매출성과에 정(+)의 영향을 끼쳤다. 또한, 기술능력의 편차와 R&D 매출성과 간에 관계를 정부지원이 조절하는 것을 알 수 있었다. 하지만, 정부지원이 기술수준이 R&D 매출성과에 미치는 영향을 성장단계별로 다르게 조절할 것이라는 가설에 대한 실증 분석 결 과 성장단계별로 조절효과가 유의적으로 각각 다르게 나타났다. 연구의 이론적인 시사점은 성장단계를 고려하지 않은 단순한 역학관계를 떠나 좀 더 실제 로 복잡한 중소기업 환경을 직시할 수 있는 현실적인 인과 모형을 제시하였고, 따라서 다양 성을 다각적인 방법으로 측정하여 연구변수로 활용해야하는 당위성을 마련하였다. 또한 실 무적 시사점은 성장단계별 정부지원에 대한 정책을 차별적으로 수립할 수 있고, 각자 다른 성장단계에 있는 중소기업으로 하여금 맞춤식의 정책을 순응하도록 하여 정부지원금의 효과 적으로 사용할 수 있는 가이드라인을 제시하였다는 것이다.