• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.268-273
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• 2005

We propose the specialized product-line development methodology for developing the embedded system of an MSDFS (Multi Sensor Data Fusion System : called MSDFS). The product-line methodology provides a simultaneous design between software and hardware, high level reusability. However this is insufficient in requirement analysis stage due to be focused on software architecture, detailed design and code. Thus we apply the business model based on IDEF0 technique to traditional methodology. In this paper, we describe the processes of developing Core-Asset, which are requirement analysis, feature modeling, validation. The proposed model gives the efficient result for eliciting features, and ensures the high level reusability of modules performing on embedded system.

• The Journal of Economics, Marketing and Management
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• v.11 no.4
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• pp.77-87
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• 2023

Purpose: In a business, it is very important to be able to pay attention to consumers. When making a purchase, consumers will first evaluate until they make a purchase decision. This study was conducted to analyze the effects of price, promotion, and product quality on consumer purchasing decisions on poultry feed. Research design, data, and methodology: The research was conducted quantitatively using the Google Form Survey instrument to collect respondent data. The population of this research is poultry feed consumers in Indonesia. Ninety-two respondents participated in this study. Results: The findings revealed that all the independent variables used in this research contribute significantly to determining customer purchase decisions. Conclusions: The results of the study found that price, promotion, and product quality had positive and significant effects on consumer purchasing decisions for poultry products

• Journal of the Korean Society of Clothing and Textiles
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• v.23 no.7
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• pp.1007-1018
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• 1999

The purpose of this study were : 1) to examine the apparel product purchasing tendency of PC communication and internet users in home shopping 2) to analyze the difference of apparel product purchasing tendency accordint to consumer factors. The data was administered to 160 subjects who had communicated the PC communication and internet. And the data was collected from May through August in 1998. SPSS package was used for analysis and the following methods such as Means Percentage Frequencies Factor analysis Crosstabulation analysis t-test and one-way ANOVA, The results of this study were as follows : 1) The users of PC communication and internet were young and high-education level and a metropolitan area dwellers. They received a purchase offer through catalog PC communication and internet cable TV and paid out credit card Experience to purchasing apparel product of home shopping was very low but intention to purchasing was relative high. item that consumer wanted to buy using home shopping were casual clothing and fashion goods which were not important to fit and without regard to style. 2) Between purchasing apparel product of home shopping and mainly consideration factors were shown to have the significant differences according to age residential quarters whether or not marriage. income level. A metropolitan area dwellers the low-age unmarried and the low-income groups thought much of convenience shopping time and effort's saving. A person of the higher-income and the married thought much of the facility of an exchange or returned goods. A region dwellers were to purchase a speciality product or gift goods. 3) Between purchasing apparel product of home shopping and satisfaction degree were shown to have significant differences according to sex whether or not marriage education level an occupation. The woman than the man was satisfied with the benefit of the shopping time and effort's saving. And the unmarried than the married was satisfied with the benefit of the home shopping's convenience. The higher-education level than the lower-education level was satisfied with the quality guarantee of the product.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.3_4
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• pp.548-559
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• 2002

Value is one of the most useful variable for achieving marketing concept that satisfy consumer needs. The issue related to which value consumers have when they're shopping and which effect this shopping value has on the process of consumer satisfaction formation, would be helpful to understand the post-purchase behavior as well as the process of pre-purchase decision making. Therefore, the objective of this study was to clarify differences in the process of satisfaction formation in relation to the type of shopping value. The study was conducted in three steps. Through the two steps, measurement instruments were developed. At the last step, judgement sampling method were utilized to collect the data and subjects were 614 university students. Factor analysis, cluster analysis, frequencies, t-test, and structural equation model analysis were used to analyze the data. Two groups regarding shopping value were found, which included consumers with hedonic shopping value and consumers with utilitarian shopping value. Overall, the results revealed a similar tendency in the process of satisfaction formation between two groups. But the tendency, which expressive product performance was related to the positive consumption emotion more than instrumental product performance was and instrumental product performance was related to the negative consumption emotion more than expressive product performance was, was clearer in consumers with utilitarian shopping value than in those with hedonic shopping value. In consumers with utilitarian shopping value, expressive product performance has a greater effect on satisfaction than instrumental product performance did, but in consumers with utilitarian shopping value, expressive product performance showed a similar effect on satisfaction with instrumental product performance. Understanding of the post-purchase behavior of the consumers with hedonic shopping value and the consumers with utilitarian shopping value and practical administration of the differences of the two groups would contribute to build useful marketing strategies.

• Journal of Fashion Business
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• v.27 no.3
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• pp.50-62
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• 2023

The e-commerce fashion market has experienced a remarkable growth, leading to an overwhelming availability of shared information and numerous choices for users. In light of this, chatbots have emerged as a promising technological solution to enhance personalized services in this context. This study aimed to develop user-product attributes for a chatbot-based personalized fashion recommendation service using big data text mining techniques. To accomplish this, over one million consumer reviews from Coupang, an e-commerce platform, were collected and analyzed using frequency analyses to identify the upper-level attributes of users and products. Attribute terms were then assigned to each user-product attribute, including user body shape (body proportion, BMI), user needs (functional, expressive, aesthetic), user TPO (time, place, occasion), product design elements (fit, color, material, detail), product size (label, measurement), and product care (laundry, maintenance). The classification of user-product attributes was found to be applicable to the knowledge graph of the Conversational Path Reasoning model. A testing environment was established to evaluate the usefulness of attributes based on real e-commerce users and purchased product information. This study is significant in proposing a new research methodology in the field of Fashion Informatics for constructing the knowledge base of a chatbot based on text mining analysis. The proposed research methodology is expected to enhance fashion technology and improve personalized fashion recommendation service and user experience with a chatbot in the e-commerce market.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.1101-1121
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• 2024

Thorough understanding of user demands and formulation of product development strategies are crucial in product design, and can effectively stimulate consumer behavior. Scientific categorization and classification of demands contribute to accurate design development, design efficiency, and success rates. In recent years, e-commerce has become important consumption platforms for smart wearable products. However, there are few studies on product design and development among those related to promoting platform product services and sales. Meanwhile, design strategies focusing on real consumer needs are scarce among smart wearable product design studies. Therefore, an empirical consumer demand analysis method is proposed and design development strategies are formulated based on a categorized interpretation of demands. Using representative smart bracelets from wearable smart products as a case, this paper classifies consumer demands with three methods: big data semantic analysis, KANO model analysis, and satisfaction analysis. The results reveal that analysis methods proposed herein can effectively classify consumer demands and confirm that differences in consumer demand categories have varying impacts on consumer behavior. On this basis, corresponding design strategies are proposed based on four categories of consumer demands, aiming to make product design the leading factor and promote consumer behavior on e-commerce platforms. This research further enriches demand research on smart wearable products on e-commerce platforms, and optimizes products from a design perspective, thereby promoting consumption. In future research, different data analysis methods will be tried to compare and analyze changes in consumer demands and influencing factors, thus improving research on impact factors of product design in e-commerce.

• International Journal of Quality Innovation
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• v.4 no.1
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• pp.213-219
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• 2003

This paper proposes an efficient and effective BOM management scheme for small and medium manufacturing (SME) companies that produce automobile parts. Automobile part's manufacturers produce very various products due to various automobile characteristics such as types, colors, and options of cars. These products are classified into product groups with common parts and like this product groups with commonality are regarded as product family. This paper proposes a BOM data model for product family structures and implements the practical EXCEL-based BOM management system for real small and medium manufacturing (SU) companies that produces automobile parts.

• Journal of Industrial Convergence
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• v.1 no.1
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• pp.115-126
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• 2003

In order to examine the determinants of new product success, winning products are analyzed with a focus on merchantability. The specific dimensions of product advantage have not been studied as yet. As results of the analysis, the determinants are classified into function, aesthetics, economy, safety, usability, reliability, brand image, assurance, distribution channel, advertisement, DEF(design for the environment). This study augmented the data set through questionnaire survey to marketing professor in University. The results of this study would be a cue to the future direction of new product development and to management of exist product.

• Asia pacific journal of information systems
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• v.17 no.2
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• pp.1-28
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• 2007

The success of new product development is a key factor for getting competitive advantages. Marketing research has been investigating marketing capability, manufacturing technical capability, cross-functional integration, market knowledge competence, market orientation, and competitive environment as the key success factors of new product development. Recently, the role of IT infrastructure in enhancing new product advantage is assumed in the literature. However, the empirical studies on the role of IT infrastructure are lacking. The purpose of this study is to empirically exam the impacts of IT infrastructure on new product competitive advantage. In this study, IT infrastructure is conceptualized as the flexibility of IT infrastructure. Based on previous research, a conceptual model is established by incorporating the direct impact of IT infrastructure flexibility and its indirect impact through the key success factors on new product development. To empirically test the research model, data are surveyed from a pair of IS department and Marketing department of 92 consumer goods manufacturers. By employing PLS technique, the measurement reliability and reliability of research variables are tested and the path analysis is conducted to do the hypothesis testing. The path analysis shows that IT infrastructure flexibility has no direct effect on new product advantage, However, the indirect effect of IT infrastructure is found, which is mediated by marketing capability, manufacturing technical capability, cross-functional integration, and market orientation respectively. Hence, The flexible IT infrastructure increases cross-functional integration (H1), market orientation (H3), marketing capability (H5), and manufacturing technical capability (H6). All success factors of new product development excepts for competitive environment have a positive association with new product competitive advantages (from H10 to H14). Finally, the path from IT infrastructure flexibility to cross-functional integration, to market orientation, to market knowledge capability, and to new product advantage is found as the strongest path. These results indicate that the flexible IT infrastructure enhances information sharing with multiple departments and collaboration within a distributed innovation environment. The collaboration among departments positively affects the level of customer and competitor intelligence. The ability to obtain knowledge about customers and competitors makes firms to adapt to a changing environment quickly and to respond to customers' demands adequately. The flexible IT infrastructure also enhances the capability of organization to more rapidly respond to the changes in product design resulting in faster product development and reduced costs. In addition to, it enhances marketing capability by the two-way communications with customers and the analyses of various kinds of customer data. In brief, the finding of this study suggests that the flexible IT infrastructure allows many firms to pursue sustained new product competitive advantages. This study advances research on IT infrastructure in two important aspects. First, by Integrating marketing research and IS research, this study develops a conceptual model on the role of IT infrastructure in enhancing new product advantage. Second, it empirically finds the indirect impacts of IT infrastructure on new product advantage, which confirms the potential for the IS field to contribute to new product development research. The limitations of this study are also discussed to provide research directions for future research.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.63-82
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• 2016

Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.