• Journal of Distribution Science
• /
• v.21 no.9
• /
• pp.35-42
• /
• 2023

Purpose: The research aims at examining the impact of marketer capabilities and persistence on marketer performance and distribution of agricultural product facilities. Research design, data, and methodology: The research employs quantitative methods using a cross-sectional design survey by analyzing the marketer of agricultural production facilities. Sampling was done using the purposive sampling technique and data were taken from 235 respondents. The data were then processed using SEM-PLS. Results: The findings reveal that both marketer capabilities and marketer persistence significantly impact the performance of agricultural product facility marketers. Notably, marketer persistence exerts a more dominant influence on marketer performance than marketer capabilities. Effective communication and coordination between the sales team and the distribution center emerge as crucial factors determining the success of distributing agricultural equipment to reach farmers' land at the optimal time. Conclusions: The findings offer valuable managerial insights for agricultural product facility companies seeking to enhance marketer performance. To achieve this, companies should focus on increasing marketer persistence, with an emphasis on nurture-focused persistence rather than closure-focused persistence. Additionally, improving marketer capabilities is crucial, starting with relationship development, followed by trust building, customer retention, responsiveness, and acquisition. These strategies can collectively contribute to boosting marketer performance within the organization.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.18 no.5
• /
• pp.233-240
• /
• 2023

Nutrition information about food is written on the label paper, which is very inconvenient for visually impaired people to recognize. In order to solve the inconvenience of visually impaired people with nutritional information recognition, this paper proposes a product nutrition information guide system for visually impaired people. In the proposed system, user's image data input through UI, and object recognition is carried out through YOLO v5. The proposed system is a system that provides voice guidance on the names and nutrition information of recognized products. This paper constructs a new dataset that augments the 319 classes of canned/late-night snack product image data using rotate matrix techniques, pepper noise, and salt noise techniques. The proposed system compared and analyzed the performance of YOLO v5n, YOLO v5m, and YOLO v5l models through hyperparameter tuning and learned the dataset built with YOLO v5n models. This paper compares and analyzes the performance of the proposed system with that of previous studies.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.4
• /
• pp.390-395
• /
• 2004

A semiconductor manufacturing process is the complicate and dynamic process, and consists of many sub-processes. An etching process is the most important process in the semiconductor fabrication. In this paper, the decision support system based upon data mining and knowledge discovery is an important factor to improve the productivity and yield. The proposed decision support system consists of a neural network model and an inference system based on fuzzy logic Firstly, the product results are predicted by the neural network model constructed by the product patterns that represent the quality of the etching process. And the product patters are classified by expert's knowledge. Finally, the product conditions are estimated by the fuzzy inference system using the rules extracted from the classified patterns. Prediction of product qualities can be linked to each input and process variables. We employ data mining and intelligent techniques to find the best condition of the etching process. The proposed decision support system is efficient and easy to be implemented for the process management based upon expert's knowledge.

• Journal of Digital Contents Society
• /
• v.13 no.3
• /
• pp.385-392
• /
• 2012

The definition of the product market in a supplier's point of view can cause various problems in the market activities of companies because specific situations are excluded and the consideration for discontinuity is lacking by identifying segmented markets with processes, raw materials, the similarity of product functions and so forth. Furthermore, as this definition is static and general, it is difficult to express and predict the dynamic market changes. Meanwhile, customer-oriented market segment can be obtained by grouping substitutable products and related customers in the situation pursuing specific benefits. This definition of the product market enables us to find threats and opportunities emerging in markets and promotes effective performance assessments and resource allocation. The purpose of this paper is suggesting a framework to select data mining techniques proper for the customer data characteristics to identify customer oriented product market.

• Journal of Navigation and Port Research
• /
• v.35 no.6
• /
• pp.489-494
• /
• 2011

Present study introduces an implementation of product data management (PDM) that can be applied to the design of ship propulsion system. The PDM system is developed based on both object oriented software development environment and Open Scene Graph (OSG) library while the system architecture is modeled by the unified modeling language (UML). Suggested PDM system also integrates the modeling & simulation components required to estimate the performance of ship propulsion system as the product information is represented based on the 3-dimensional digital mock-up (DMU). Finally, functions of the implemented PDM system that is integrated with the M&S softwares are illustrated in order to suggest a practical guidance for the efficient design of ship propulsion system.

• Journal of the Korea Convergence Society
• /
• v.12 no.9
• /
• pp.39-47
• /
• 2021

This study was conducted to propose a product planning prediction model using logistic regression algorithm to predict seasonal factors and rapidly changing product trends. First, we collected unstructured data of consumers in portal sites and online markets using web crawling, and analyzed meaningful information about products through preprocessing for transformation of standardized data. The datasets of 11,200 were analyzed by Logistic Regression to analyze consumer satisfaction, frequency analysis, and advantages and disadvantages of products. The result of analysis showed that the satisfaction of consumers was 92% and the defective issues of products were confirmed through frequency analysis. The results of analysis on the use satisfaction, system efficiency, and system effectiveness items of the developed product planning prediction program showed that the satisfaction was high. Defective issues are very meaningful data in that they provide information necessary for quickly recognizing the current problem of products and establishing improvement strategies.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.42 no.2
• /
• pp.69-77
• /
• 2019

As information technology advances, the penetration of smart devices connected to the Internet, such as smart phone and tablet PC, has rapidly expanded, and as sensor prices have fallen the Internet of Things has begun to be introduced in the industry. Today's industry is rapidly changing and evolving, requiring companies to respond to the new paradigm of business. In this situation, companies need to actively manage and maintain customer relationships in order to acquire loyal customers who bring them a high return. The purpose of this study is to suggest a method to manage customer relationship using real time IoT data including IoT product usage data, customer characteristics and transaction data. This study proposes a method of segmenting customers through RFM analysis and transition index analysis. In addition, a real-time monitoring through control charts is used to identify abnormalities in product use and suggest ways of differentiating marketing for each group. In the study, 44 samples were classified as 9 churn customers, 10 potential customers, and 25 active customers. This study suggested ways to induce active customers by providing after-sales benefit for product reuse to a group of churn customers and to promote the advantages or necessity of using the product by setting the goal of increasing the frequency of use to a group of potential customers. Finally, since the active customer group is a loyal customer, this study proposed an one-on-one marketing to improve product satisfaction.

• The Journal of the Korea Contents Association
• /
• v.22 no.5
• /
• pp.1-15
• /
• 2022

In this study, text analysis was performed on the mealkit product review data to identify factors affecting the evaluation of the mealkit product. The data used for the analysis were collected by scraping 334,498 reviews of mealkit products in Naver shopping site. After preprocessing the text data, wordclouds and sentiment analyses based on word frequency and normalized TF-IDF were performed. Logistic regression model was applied to predict the polarity of reviews on mealkit products. From the logistic regression models derived for each product category, the main factors that caused positive and negative emotions were identified. As a result, it was verified that text analysis can be a useful tool that provides a basis for maximizing positive factors for a specific category, menu, and material and removing negative risk factors when developing a mealkit product.

• Publications of The Korean Astronomical Society
• /
• v.27 no.1
• /
• pp.1-16
• /
• 2012

In this paper, we describe the installation of VLBI Correlation Subsystem (VCS) main product and its performance at the Korea-Japan Correlation Center (KJCC). The VCS main product was installed at KJCC in August 2009. For the overall performance evaluation of VCS, playbacks, Raw VLBI Data Buffer (RVDB) system, and Data Archive (DA) system were installed together. The VCS main product was connected between RVDB and DA, and the correlation results were put into the DA to confirm the normal operation of VCS 16 station mode configuration. The evaluation test was first performed with 4 station mode, same as the factory test of VCS main product. Based on the results of 4 station mode, the same evaluation test was conducted for 16 station mode of VCS. We found that the correlation results of VCS were almost similarly compared to those of the Mitaka FX Correlator. Through the test results, we confirmed that the problems such as spectrum errors, delay parameter processing module and field programmable gate array errors in antenna unit, which were generated at the factory test of VCS main product, were clearly solved. And we verified the performance and connectivity of VCS by obtaining the expected correlation results and we also confirmed that the performance of VCS was sufficient for real VLBI observation data in both 4 and 16 station modes.

• Journal of Intelligence and Information Systems
• /
• v.11 no.1
• /
• pp.191-205
• /
• 2005

This paper presents a novel product recommender system as a tool fur differentiated marketing service of online shopping malls. Ihe proposed model uses genetic algorithnt one of popular global optimization techniques, to construct a personalized product recommender systen The genetic algorinun may be useful to recommendation engine in product recommender system because it produces optimal or near-optimal recommendation rules using the customer profile and transaction data. In this study, we develop a prototype of WeLbased personalized product recommender system using the recommendation rules fi:om the genetic algorithnL In addition, this study evaluates usefulness of the proposed model through the test fur user satisfaction in real world.