• Korean Management Science Review
• /
• v.23 no.2
• /
• pp.1-16
• /
• 2006

With the diffusion of the Internet, firms try to electronically collaborate with their partners in order to cut costs and gain profits. This, electronic Partnership, called 'Collaborative IT' is quite popular between large purchase enterprises and small-to-medium sized sub-contractors. This study investigates such relations. This study proposes three groups of research variables-interorganizational relationship, collaborative IT activity, and firm performance. the interorganizational relationship consists of trust, commitment, and asymmetry of commitment. Collaborative IT activity is composed of information sharing and workflow integration. The ultimate dependent variable is firm performance. It is hypothesized that the relationship factors influence the level of collaborative IT activity, while the latter in turn affects the firm performance. The relationship factors nay also directly affect the dependent variable. In addition, collaborative IT motive, as a moderating variable, may influence the causal relationship. By means of survey, ore hundred and eighty-two responses were obtained. Most sample companies are small-sized, in the manufacturing sector. The analysis of data reveals that both trust and commitment positively affects the level of collaborative IT activity, while asymmetry of commitment has negative effects. The workflow integration is significantly related with firm performance. Information sharing, however, has no signific3nt effects. Furthermore, asymmetry of commitment shows reverse relationship with firm performance. Collaborative IT motive works as a moderating variable between information sharing and firm performance. Finally, workflow integration is believed to mediate between relationship factors and firm performance.

• Journal of the Korean Institute of Plant Engineering
• /
• v.23 no.4
• /
• pp.57-64
• /
• 2018

User-based collaborative filtering is a method of recommending an item to a user based on the preference of the neighbor users who have similar purchasing history to the target user. User-based collaborative filtering is based on the fact that users are strongly influenced by the opinions of other users with similar interests. Item-based collaborative filtering is a method of recommending an item by comparing the similarity of the user's previously preferred items. In this study, we create a recommendation model using user-based collaborative filtering and item-based collaborative filtering with consumer's consumption data. Collaborative filtering is performed by using RFM (recency, frequency, and monetary) technique with purchasing data to recommend items with high purchase potential. We compared the performance of the recommendation system with the purchase amount and the performance when applying the RFM method. The performance of recommendation system using RFM technique is better.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.34 no.3
• /
• pp.85-104
• /
• 2009

Managers have come to realized that a large and increasing amount of sources for a corporate competitive advantage can be found in their company's supply chain. At a fundamental level, there is a similar consensus that building a collaborative supply management is a more effective way of managing firms' supply chains. This paper is an attempt to examine the effects of collaborative supply management by probing a mechanism which shows how competences and/or performance are transferred from suppliers to markets through the supply chains. Research hypotheses regarding the relationships between collaborative supply management, supplier Performance, buyer internal performance (new product development and operational performance), and buyer market performance were empirically validated by utilizing a structural equation modeling analysis. The research result Indicates the positive impacts of a collaborative supply chain on supply performance as well as buyer internal and market performance, which also well illustrate how the improved competence and/or performance of suppliers engendered from the supplier-buyer collaboration flows throughout the entire supply chain.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.10A
• /
• pp.984-991
• /
• 2007

Cognitive Radio is an advanced enabling techlology for efficient utilization of under-utilized spectrum since it is able to sense the temporally available spectrum and adapt its parameters to fully utilize the frequency band. Recent investigation suggests that spectrum sensing is compromised when a cognitive radio user suffers from the environment with fading or shadowing. In order to combat the effect, collaborative sensing is considered to be a promising way, which combines the sensing result of each user to achieve good performance. However, the conventional collaborative sensing is not efficient when users suffer different fading environments. In this paper, we propose a weighted-collaborative scheme that considers using the weights of each collaborative CR user, which can achieve better sensing performance under both fast and slow fading environments. The analysis of the simulation resultsproves that the weighted-collaborative scheme improves sensing performance obviously and outperforms the conventional method.

• Journal of Distribution Science
• /
• v.11 no.4
• /
• pp.51-60
• /
• 2013

Purpose - The objective of this paper is to investigate the effect of asset specificity, the level of information sharing, the importance of information sharing, and an integrated collaborative environment on supply chain performance. Research design, data, and methodology - Data collection was implemented as follows: questionnaires were distributed to 250 companies that have business ties with Halla Climate Control Corporation. The empirical study to test our hypothesis was based on statistical analysis (using SPSS 18.0 and AMOS 18.0). The hypothesis of this paper is that the asset specificity variable has positive effects on the following variables: Level of information sharing, the importance of information sharing, and integrated collaborative environment. Moreover the variables, the level of information sharing, and the importance of information sharing are strongly influenced by the variable integrated collaborative environment, and these when combined, have an effect on the dependent variable, supply chain performance. We tested our hypothesized model utilizing path analysis with latent variables. Results - According to the results of our analysis, hypothesis H1, which tests whether there is a relationship between asset specificity and the integrated collaborative environment, is supported at the 0.01 level. Hypotheses H2 and H3 were also confirmed, and asset specificity had positive effects (+) on the level of information sharing variable. The importance of the information sharing variable was statistically significant at the 0.01 level. Hypotheses H4 and H5 posited that the integrated collaborative environment variable would have a positive effect on the level of information sharing; the importance of information sharing variable was strongly supported statistically, with a significant p-value below. Moreover, the level of information sharing (H6), and the importance of information sharing (H7) variables also had a statistically relevant influence on supply chain performance. As a result, existence of a collaborative system between companies would influence supply chain performance by strengthening real-time information access and information sharing. Thus, it is important to construct a collaborative environment where information sharing among companies and cooperation is possible. Conclusions - First, with rapid changes in the business environment, it becomes necessary for enterprises to acquire the right information in order to properly implement SCM. For successful SCM, firms should understand the importance of collaboration with supply chain partners and an internally built collaboration system, which in turn will better promote a partnership commitment with suppliers as well as collaborative integration with buyers. A collaborative system, as we suggest in this paper, facilitates the maintenance of a long-term relationship of trust, and can help reinforce information sharing. Second, it is necessary to increase information sharing over time via a collaborative system so that employees of the suppliers become aware of the system. The more proactive and positive attitudes are towards such a collaborative system by the managerial group, the higher the level of information sharing will be among the users. Successful SCM performance is achieved by information sharing through a collaborative environment rather than by investing only in setting up an information system.

• Journal of Information Technology Services
• /
• v.14 no.2
• /
• pp.253-273
• /
• 2015

Cloud computing is provided on demand service via the internet, allowing users to pay for the service they actually use. Categorized as one kind of cloud computing, SaaS is computing resource and software sharing model with can be accessed via the internet. Based on virtualization technology, SaaS is expected to improve the efficiency and quality of the IT service level and performance in company. Therefore this research limited cloud services to SaaS especially focused on collaborative application service, and attempts to identify the factors which impact the performance of collaboration and intention to use. This study adopts technological factors of cloud SaaS services and factors of task characteristics to explore the determinants of collaborative performance and intention to use. An experimental study using student subjects with Google Apps provided empirical validation for our proposed model. Based on 337 data collected from respondents, the major findings are following. First, the characteristics of cloud computing services such as collaboration support, service reliability, and ease of use have positive effects on perceived usefulness of collaborative application while accessability, service reliability, and ease to use have positive effects on intention to use. Second, task interdependence has a positive effects on collaborative performance while task ambiguity factor has not. Third, perceived usefulness of collaborative application have positive effects on intention to use.

• The Journal of Industrial Distribution & Business
• /
• v.12 no.5
• /
• pp.27-36
• /
• 2021

Purpose: This study empirically investigates the effect of collaborative communication and information sharing on the supply chain performance of South Korean pharmaceutical companies. Specifically, it understands the importance collaborative communication and suggests a method for investigating communication in academic research on the pharmaceutical industry. Investigating this sector is crucial because the importance of the pharmaceutical industry is increasing globally against the background of the Covid-19 pandemic. Research design, data, and methodology: A questionnaire was administered to employees of South Korean pharmaceutical companies and 244 valid responses were used for the statistical analysis. Additionally, structural equation modeling was used to measure the relationships between the observed and latent variables. Results: Collaborative communication has a positive effect on information sharing. However, information sharing, unlike collaborative communication, does not exhibit a significant positive relationship with supply chain performance. These results indicate that it is important to communicate effectively in the supply chain rather than strive for the right type of information sharing. Conclusions: Consumers and retailers within the supply chain should continue to strive for candid communication. This study is meaningful, as it empirically tests the relationships between collaborative communication, information sharing, and supply chain performance in the South Korean pharmaceutical industry.

• Management Science and Financial Engineering
• /
• v.11 no.3
• /
• pp.19-45
• /
• 2005

Collaborative filtering is one of the most common methods that e-commerce sites and Internet information services use to personalize recommendations. Collaborative filtering has the advantage of being able to use even sparse evaluation data to predict preference scores for new products. To date, however, no in-depth investigation has been conducted on how the data sparsity effect in customers' evaluation data affects collaborative filtering-based recommendation performance. In this study, we analyzed the sparsity effect and used a hybrid method based on customers' evaluations and purchases collected from an online bookstore. Results indicated that recommendation performance decreased monotonically as sparsity increased, and that performance was more sensitive to sparsity in evaluation data rather than in purchase data. Results also indicated that the hybrid use of two different types of data (customers' evaluations and purchases) helped to improve the recommendation performance when evaluation data were highly sparse.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.11
• /
• pp.121-126
• /
• 2016

In recommender systems based on collaborative filtering, measuring similarity is very critical for determining the range of recommenders. Data sparsity problem is fundamental in collaborative filtering systems, which is partly solved by Jaccard coefficient combined with traditional similarity measures. This study proposes a new coefficient for improving performance of Jaccard coefficient by compensating for its drawbacks. We conducted experiments using datasets of various characteristics for performance analysis. As a result of comparison between the proposed and the similarity metric of Pearson correlation widely used up to date, it is found that the two metrics yielded competitive performance on a dense dataset while the proposed showed much better performance on a sparser dataset. Also, the result of comparing the proposed with Jaccard coefficient showed that the proposed yielded far better performance as the dataset is denser. Overall, the proposed coefficient demonstrated the best prediction and recommendation performance among the experimented metrics.

• Journal of Korea Society of Industrial Information Systems
• /
• v.22 no.4
• /
• pp.97-115
• /
• 2017

The Purpose of this is to Examine the Effects of Collaborative Relations of Supplier- Buyer, Sustainable Supply Chain Management(SCM) Sctivities, and Collaborative Performance in Automobile-part Companies. The Proposed Research Model is Tested using Structural Equation Modeling for Hypotheses based on the Data Collected from 274 Firms. The Results Indicate that Collaborative Relations of Supplier-buyer Positively Affect Sustainable SCM Activities. In Addition, Sustainable SCM Activities Positively Affects Collaborative Performance. The Results of the Study Show that Collaborative Relations of Supplier-buyer is Positively Associated with Sustainable SCM Activities in both Supplier and Buyer Firms. Sustainable SCM Activities have a Significant Impact on Collaborative Performance in both Parts. In Addition, Collaborative Relations of Supplier-buyer have a Significant Impact on Collaborative Performance of Buyer Firms but Supplier. This Study would Provide Useful Information for Collaboration between Supplier and Buyer to have a Long-term Strategic Relationship on Sustainable SCM Activities, which Impact on Collaborative Performance and Competitive Advantages.