• 한국의류학회지
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• 제44권6호
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• pp.1053-1069
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• 2020

This study examined the sales pattern relationship with respect to product attributes to propose sales forecasting for fashion products. We analyzed 537 SKU sales data of T-shirts in the domestic sports brand using SAS program. The sales pattern of fashion products fluctuated and were influenced by exogenous factors; therefore, we removed the influence of exogenous factors found to be price discounts and holiday effects as a result of regression analysis. In addition, it was difficult to predict sales using the sales patterns of the same product since fashion products were released as new products every year. Therefore, the forecasting model was proposed using sales patterns of related product attributes when attributes were considered descriptive variables. We classified sales patterns using K-means clustering in order to explain the relationship between sales patterns and product attributes along with creating a decision tree classifier using attributes as input and sales patterns as output. As a result, the sales patterns of T-shirts were clustered into six types that featured the characteristic shape of peak and slope. It was also associated with the combination of product attributes and their values in regards to the proposed sales pattern prediction model.

• 유통과학연구
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• 제17권5호
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• pp.85-94
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• 2019

Purpose - The purpose of this study is to analyze the impact of customer's communication on sales performance in the online market. Research design, data, and methodology - This study uses linear regression analysis to examine the effects of product review characteristics which are the result of customer's communication, on sales performance by using product reviews of online marketplace Amazon. Result - The increase in the number of product reviews positively affected sales performance. An increase in extreme opinions in the product review has a positive effect on sales performance. The product review length has a negative effect on sales performance. Conclusions - This study has shown the online marketplace customers' communication can influence sales performance using product review big data. This study contributed to the theoretical completeness by analyzing all the products of the book category in Amazon online market. This research will complement the theories regard to the customer behavior affecting sales performance. We expect the empirical analysis result will provide empirical help to sellers, online marketplace operators, and customers. In particular, the number of letters in the product may negatively affect sales performance, so sellers need to consider this effect carefully when exposing product reviews.

• 한국정보시스템학회지:정보시스템연구
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• 제31권2호
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• pp.159-177
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• 2022

Purpose Online reviews are critical for sales of online shopping platforms because they provide useful information to consumers. As the eCommerce market grows rapidly, the role of online reviews is becoming more important. The purpose of this study is to analyze how online reviews written by domestic consumers affect product sales by classifying the types of products. Design/methodology/approach This study analyzed how the effects of review characteristics(reviewer reputation, reviewer exposure, review length, time, rating, image, and emotional score) on the usefulness of online reviews differ depending on the product types. Subsequently, how the impact of review attributes (review usefulness, number of reviews, ratings, and emotional scores) on product sales differs according to each product type was compared. Based on the FCB Grid model, the product type was classified into high involvement-rational, high involvement-emotional, low involvement -rational, and low involvement-emotional product types. Findings According to the analysis result, the characteristics of reviews useful to consumers were different for each product type, and the review attributes affecting product sales were also different for each product type. This study confirmed that it revealed that product characteristics are major consideration in evaluating the review usefulness and the factors affecting product sales.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2006년도 추계학술대회
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• pp.161-164
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• 2006

The sales of consumer durables are composed of first time purchases and replacement purchases. Since the sales for most mature durable products are dominated by replacement sales, it is necessary to develop a model incorporating replacement component of sales in order to forecast total sales accurately. Several single product diffusion models incorporating replacement demand have been developed, but research addressing the multi-product diffusion models has not considered replacement sales. In this paper, we propose a model based on consumer choice behavior that simultaneously captures the diffusion and the replacement process for multi-product relationships. The proposed model enables the division of replacement sales into repurchase by previous users and transition purchase by users of different products. As a result, the model allows the partitioning of the total sales according to the customer groups (first-time buyers, repurchase buyers, and transition buyers), which allows companies to develop their production and marketing plans based on their customer mix. We apply the proposed model to the Korean automobile market, and compare the fitting and forecasting performance with other Bass-type multi-product models.

• 산업경영시스템학회지
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• 제44권3호
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• pp.240-247
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• 2021

As competition among companies has intensified and the life cycle of products has been shortened, strong innovation is needed to meet consumers' needs. In addition, it is necessary to shorten the life cycle of the product and reduce the time required for technology development for the competitive advantage of the product. In particular, venture companies where new technologies and ideas are important require more innovative capabilities than others companies. Therefore, this study analyzed the impact of technology innovation capabilities (product development process capability, human resource capability and financial capability) on sales by technology development for small and medium venture companies and analyzed moderating effect of technology development period on the relationship between technology innovation capabilities and sales by technology development. The data of 'Small and Medium Business Technology Statistics' collected by the government every year were used for analysis. Technology-intensive ventures were extracted from this data. In addition, the moderating effect was analyzed through hierarchical regression analysis. This study shows that product planning capability, test capability, and R&D expenditure have a positive impact on sales by technology development. In this study, the product development period showed a positive moderating effect on product development capability and sales performance. On the other hand, the product development period showed a negative moderating effect on R&D expenditure and sales by technology development.

• 디지털융복합연구
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• 제18권3호
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• pp.71-81
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• 2020

본 연구는 화장품 제조판매원과 화장품 전문 제조원의 명성 및 제품유형이 지각된 품질에 미치는 영향에 대해 검증해 보고자 하였다. 이를 위해 2×2×2 요인설계를 이용하여 8개 집단을 대상으로 실험을 진행했다. 연구결과 첫째, 제조판매원의 명성과 제조원의 명성은 고 명성이 저 명성에 비해 지각된 품질을 보다 높게 인식하는 것으로 나타났다. 둘째, 제조판매원과 제조원의 명성은 지각된 품질에 상호작용 효과를 나타내는 것으로 확인되었다. 셋째, 제조판매원과 제품유형은 지각된 품질에 상호작용 효과를 나타내는 것으로 확인되었다. 마지막으로 제조원과 제품유형은 지각된 품질에 상호작용 효과를 나타내는 것으로 확인되었다. 이러한 결과는 화장품 업계에 있어 제조판매원의 명성 뿐 아니라 제조원의 명성 또한 매우 중요하다는 사실을 실증적으로 보여줌으로써 제조판매원과 제조원의 제품생산 및 마케팅 전략방안 모색에 매우 유용한 정보를 제공해 줄 수 있을 것으로 기대한다.

• 기술혁신연구
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• 제24권1호
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• pp.85-111
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• 2016

본 연구에서는 온라인 쇼핑몰 상황에서 이전사업경험, 제품속성과 온라인 고객의견이 신제품 매출성과에 미친 영향을 살펴보았다. 인터넷 쇼핑몰에서 제품 성과에 대한 연구들은 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 유의한 영향관계나 나타나지 않았다. 본 연구에서는 온라인 쇼핑몰 상황에서 신제품 매출성과 향상을 위한 이론적 실무적 의의를 제시하고 향후 연구과제들을 제시하였다.

• 유통과학연구
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• 제22권3호
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• pp.113-124
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• 2024

Purpose: This study is a quantitative study and analyzes the effect of evaluating the extreme and usefulness of product reviews on sales performance by using text mining techniques based on product review big data. We investigate whether the perceived helpfulness of product reviews serves as a mediating factor in the impact of product review extremity on sales performance. Research design, data and methodology: The analysis emphasizes customer interaction factors associated with both product review helpfulness and sales performance. Out of the 8.26 million Amazon product reviews in the book category collected by He & McAuley (2016), text mining using natural language processing methodology was performed on 300,000 product reviews, and the hypothesis was verified through hierarchical regression analysis. Results: The extremity of product reviews exhibited a negative impact on the evaluation of helpfulness. And the helpfulness played a mediating role between the extremity of product reviews and sales performance. Conclusion: Increased inclusion of extreme content in the product review's text correlates with a diminished evaluation of helpfulness. The evaluation of helpfulness exerts a negative mediating effect on sales performance. This study offers empirical insights for digital market distributors and sellers, contributing to the research field related to product reviews based on review ratings.

• Asia pacific journal of information systems
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• 제25권4호
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• pp.763-783
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• 2015

Online customer reviews (i.e., electronic word-of-mouth) has gained considerable interest over the past years. However, a knowledge gap exists in explaining the mechanisms among the factors that determine the product sales in online retailing environment. To fill the gap, this study adopts a principal-agent perspective to investigate the effect of customer reviews and customer incentives on product sales in online retail stores. Two customer review factors (i.e., average review ratings and the number of reviews) and two customer incentive factors (i.e., price discounts and special shipping offers) are used to predict product sales in regression analysis. The sales ranking data collected from the video game titles at Amazon.com are used to analyze the direct effects of the four factors and the interaction effects between customer review and customer incentive factors to product sales. Result reveals that most relationships exist as hypothesized. The findings support both the direct and interaction effects of customer reviews and incentive factors on product sales. Based on the findings, discussions are provided with regard to the academic and practical contributions.

• Asia pacific journal of information systems
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• 제15권3호
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• pp.209-221
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• 2005

One of the most fundamental problems in business is to evaluate the value of each product. The difficulty is that the profit of one product not only comes from its own sales, but also its influence on the sales of other products, i.e., the "cross-selling effect". This study integrates a measure for cross selling and an algorithm for profit estimation. Sales transaction data and post sales survey data from on-line and off-line shopping mall is used to show the effectiveness of the method against other heuristic for profit estimation based on product-specific profitability. We show that with the use of the new method we are able to identify the cross-selling potential of each product and use the information for better product selection.