• Journal of KIISE
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• v.43 no.9
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• pp.983-997
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• 2016

Many available online product reviews for any given product makes it difficult for a consumer to locate the helpful reviews. The purpose of this study was to investigate automatic helpfulness evaluation of online product reviews according to review information types based on the target of information. The underlying assumption was that consumers find reviews containing specific information related to the product itself or the reliability of reviewers more helpful than peripheral information, such as shipping or customer service. Therefore, each sentence was categorized by given information types, which reduced the semantic space of review sentences. Subsequently, we extracted specific information from sentences by using a topic-based representation of the sentences and a clustering algorithm. Review ranking experiments indicated more effective results than other comparable approaches.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.2
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• pp.222-226
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• 2010

With the continuously increasing volume of e-commerce transactions, it is now popular to buy some products and to evaluate them on the World Wide Web. The product reviews are very useful to customers because they can make better decisions based on the indirect experiences obtainable through these reviews. However, since online shopping malls do not provide ranking results, it is not easy for users to read all the relevant review documents effectively. Product reviews include subjective and emotional opinions. Thus, the review search is different from the general web search in terms of ranking strategy. In this paper, we propose an effective method of ranking the reviews that can reflect user's intention by using opinion mining techniques. The proposed method analyzes product reviews with query words, and sentimental polarity of subjective opinions. Through diverse experiments, we show that our proposed method outperforms conventional ones.

• Asia pacific journal of information systems
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• v.25 no.4
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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.

• Korean Management Science Review
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• v.11 no.2
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• pp.237-253
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• 1994

Technology measurement is related with how to construct indicators of technological change and relative ranking of technological sophistication. Many attempts have been made to understand the measurement of technology. However, technology measurement still remains little understood problem in spite of its importance. This article is concerned with improving the measurement of technology by introducing market factors into the model. It illustrate a simple approach to the measurement of technology. This approach is based on the characteristic-space paradigm of technology. A relative ranking of technological sophistication for a product is measurable as a set of characteristics. The main feature of the proposed approach is the combination of technical factors and market factors. Technical factors are reflected in the definition of technological sophistication. Market factors are embraced in the determination of the relative importance assigned to each technology defining characteristics. Thus, the weight is determined by technical factors and market factors, which differentiates the study from the past based on judgmental technique such as experts' opinion.

• Journal of KIISE:Software and Applications
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• v.35 no.6
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• pp.392-403
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• 2008

User reviews are valuable information that can be used for various purposes. In particular, the product reviews on online shopping sites are important information which can directly affect the purchasing decision of the customers. In this paper, we present our design and implementation of a system for summarizing the customer's opinion and the features of each product by analyzing reviews on a commercial shopping site. During the analysis process, several natural language processing(NLP) techniques and the semantic dictionary were used. The semantic dictionary contains vocabularies that are used to express product features and customer's opinions. And it was constructed in semi-automatic way with the help of the tool we implemented. Furthermore, we discuss how to handle the vocabularies that have different meanings according to the context. We analyzed 1796 reviews about 20 products of 2 categories collected from an actual shopping site and implemented a novel ranking system. We obtained 88.94% for precision and 47.92% for recall on extracting opinion expression, which means our system can be applicable for real use.

• Korea Trade Review
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• v.46 no.2
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• pp.141-160
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• 2021

The scale of global FDI has been decreasing since 2016 due to the ongoing US-China trade dispute, the strengthening of FDI inflow screening regulations with concern over strategic technology leaks, and the spread of reshoring trends due to the reinforcement of national preferences. Eventually, the competition to attract FDI between countries is expected to become more intense. Therefore, in order to attract high-quality FDI for Korea that will contribute to the development of the national economy, it is pressing to evaluate and improve the domestic FDI attraction environment. This study aims to analyze which areas of Korea's economic and non-economic environments need improvement for gaining advantage amid the fierce competition to attract FDI between countries, by the relative comparison between Korea and the U.S., and based on the ranking indicated in key FDI attractiveness indices. As a result, improvement is needed in the following areas. First, according to IMD's "World Competitiveness Ranking 2020," Korea was inferior to the US in terms of business efficiency, productivity, finance and business legislation in terms of government efficiency. Second, according to INSEAD's "Global Talent Competitiveness Index 2020," Korea was inferior to the US in terms of internal openness, external openness, employability, lifelong learning, access to growth opportunity, and business and labor landscapes. Third, according to WEF's "Global Competitiveness Index 2019", Korea was inferior to the US in terms of product market, labor market, business dynamism and workforce skills.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1277-1298
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• 2017

Related to the maximum vector problem, a skyline query is to discover dominating tuples from a set of tuples, where each defines an object (such as a hotel) in several dimensions (such as the price and the distance to the beach). A tuple, an instance of an object, dominates another tuple if it is equally good or better in all dimensions and better in at least one dimension. Traditionally, skyline queries are defined upon single-instance data or upon objects each of which is associated with an instance. However, in some cases, an object is not associated with a single instance but rather by multiple instances. For example, on a review website, many users assign scores to a product or a service, and a user's score is an instance of the object representing the product or the service. Such data is an example of multi-instance data. Unlike most (if not all) others considering the traditional setting, we consider skyline queries defined upon multi-instance data. We define the dominance calculation and propose an algorithm to reduce its computational cost. We use synthetic and real data to evaluate the proposed methods, and the results demonstrate their utility.

• Information Systems Review
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• v.18 no.1
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• pp.125-140
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• 2016

Mobile applications (apps) play a significant role in the proliferation of smartphones. According to statistics from Apple, 100 million apps were downloaded in 2008. Since then, the number of cumulative app downloads have increased exponentially. By October 2014, 85 billion apps had been downloaded worldwide. Many studies have attempted to determine the factors that drive app downloads. However, unlike previous studies, we examine the effects of app updates on app rankings. To achieve this goal, we collected data on rankings (gross rankings and category rankings), update contents, reviewer ratings, and number of reviews on apps listed in the App Store. We then categorized app updates into functionality, reliability, and convenience updates following the buying hierarchy model. We found that functionality updates had a positive effect on app gross ranking whereas reliability updates had a positive effect on category ranking. Our study is the first to explore the effects of update content on app ranking. Moreover, our study provides a practical implication for mobile app developers, who should consider app updates in their product development strategy.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.6
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• pp.867-878
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• 2020

A significant proportion of the African continent is conducive for animal agricultural production, due to its historical experience and available resources to accommodate and nurture various indigenous and exotic animal species and breeds. With food security being a global challenge, animal products can play an important role as nutrient dense food sources in human diets, particularly in Africa. However, this does not seem to reach its full potential in practice, due to numerous reasons that have not been adequately addressed. Animal welfare reservations can be highlighted as one of the major contributing factors to the curbed progress. The consequences have been scientifically proven to affect product quality and market access. However, in the African community, the concept of animal welfare has not been fully embraced. While there are international animal welfare standards in the developed world, there are inherent factors that hinder adoption of such initiatives in most developing regions, particularly among communal farmers. These include cultural norms and practices, social ranking, socio-economic status, available resources, information dissemination and monitoring tools. Therefore, there is need to harmonize what is internationally required and what is feasible to accommodate global variability. The protocols followed to ensure and evaluate farm animal welfare require regular investigation, innovation and a sustainable approach to enhance animal productivity, efficiency and product quality. Additionally, investing in animal wellbeing and health, as well as empowering communities with significant knowledge, has a potential to improve African livelihoods and contribute to food security. This review seeks to highlight the concept of animal welfare in relation to livestock and food production in African conditions.

• World Technopolis Review
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• v.8 no.1
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• pp.21-42
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• 2019

The purpose of this research was to investigate the factors influencing global expansion/scalability of Kenyan Small and Medium Enterprises (SMEs). Factor analysis and multiple/multivariate regression analysis to determine the functional relationship between independent variables (factors) and the dependent variable was used. The independent variables were: innovation & technology, fitness/appropriateness of management, global marketing strategy; and support environment and the dependent variable, global expansion/scalability. Data was collected from a survey of randomly selected firms of 205, drawn from a population of 440 firms from Kenya Manufacturers Directory, with 175 firms responding. The key findings from the research in relation to Kenyan SMEs were that: there is a functional relationship between global market strategy and global expansion; there is a functional relationship between innovation and technology orientation and global expansion, there is no significant functional relationship between supportive environment of firms and their global expansion; and there is no significant functional relationship between fitness/appropriateness of management and global expansion/scalability. The implications for practice is that the ranking of the factors in order of priority supports focusing concern on the orientation of business strategy toward global market strategy, market research geared at obtaining foreign market intelligence, innovation and technology, product adaptation, service orientation, collaborative ventures, and long-range vision as key factors in making Kenyan firms successful in the international market. The implication for policy and practice is that there is need for collaboration between industry and government in pursuing policies for global expansion/scalability and among SMEs and large enterprises particularly in areas of rapid technological change.