• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.190-198
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• 2023

To enhance customer satisfaction for higher profits, an e-commerce sector can establish a continuous relationship and acquire new customers. Utilize machine-learning models to analyse their customer's behavioural evidence to produce their competitive advantage to the e-commerce platform by helping to improve overall satisfaction. These models will forecast customers who will churn and churn causes. Forecasts are used to build unique business strategies and services offers. This work is intended to develop a machine-learning model that can accurately forecast retainable customers of the entire e-commerce customer data. Developing predictive models classifying different imbalanced data effectively is a major challenge in collected data and machine learning algorithms. Build a machine learning model for solving class imbalance and forecast customers. The satisfaction accuracy is used for this research as evaluation metrics. This paper aims to enable to evaluate the use of different machine learning models utilized to forecast satisfaction. For this research paper are selected three analytical methods come from various classifications of learning. Classifier Selection, the efficiency of various classifiers like Random Forest, Logistic Regression, SVM, and Gradient Boosting Algorithm. Models have been used for a dataset of 8000 records of e-commerce websites and apps. Results indicate the best accuracy in determining satisfaction class with both gradient-boosting algorithm classifications. The results showed maximum accuracy compared to other algorithms, including Gradient Boosting Algorithm, Support Vector Machine Algorithm, Random Forest Algorithm, and logistic regression Algorithm. The best model developed for this paper to forecast satisfaction customers and accuracy achieve 88 %.

• Journal of Korea Port Economic Association
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• v.30 no.3
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• pp.231-257
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• 2014

In general, furniture industry, with its high foreign dependency, has serious logistics issues that are commonly raised in such countries as Korea, China and Japan. This leads to my different possibilities & ways of rationalizing the logistics systems that utilize port hinterlands. Thus the purpose of the present paper is to create new logistics systems which will work effectively across the three countries. In this research study, we came up with 2 logistics models in which the port hinterland of Busan serves as the distribution center for furniture industry, and the models were suggested as the cooperative logistics business systems for the North-east asian region. In the proposed models, 'Busan furniture logistics center' has the dual functions of 'the cross-docking center from China to Japan' and 'the assembly & delivery center for furniture imported by Japan'. To have this logistics business center materialized, we propose that policy-level supports from the relevant port authorities be provided in the following three aspects: overseas investment promotion focused on the furniture industry of Japan, protection & enhancement of competitiveness for the port of Busan, and uilization plans for the new port hinterland of the city.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.57-64
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• 2021

This research attempts to formulate a new mean-risk model to replace the Markowitz mean-variance model by altering the risk measurement using ARCH variance instead of the original variance. In building the portfolio, samples used are closing prices of Indonesia Composite Stock Index and Indonesia Composite Bonds Index from 2013 to 2018. This study is a qualitative study using secondary data from the Indonesia Stock Exchange and Indonesia Bonds Pricing Agency. This research found that Markowitz's model is still superior when utilized in daily data, while the mean-ARCH model is appropriate with wider gap data like monthly observation. The Historical return has also proven to be more appropriate as a benchmark in selecting an optimal portfolio rather than a risk-free rate in an inefficient market. Therefore Mean-ARCH is more appropriate when utilized under data that have a wider gap between the period. The research findings show that the portfolio combination produced is inefficient due to the market inefficiency indicated by the meager return of the stock, while bears notable standard deviation. Therefore, the researcher of this study proposed to replace the risk-free rate as a benchmark with the historical return. The Historical return proved to be more realistic than the risk-free rate in inefficient market conditions.

• Korea Trade Review
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• v.47 no.3
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• pp.57-73
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• 2022

The process and change of convergence in the economy and industry with the development of digital technology and combining with new technologies is called Digital Transformation. Specifically, it refers to innovating existing businesses and services by utilizing information and communication technologies such as big data analysis, Internet of Things, cloud computing, and artificial intelligence. Digital transformation is changing the shape of business and has a wide impact on businesses and consumers in all industries. Among them, the big data and analytics market is emerging as one of the most important growth drivers of digital transformation. Integrating intelligent data into an existing business is one of the key tasks of digital transformation, and it is important to collect and monitor data and learn from the collected data in order to efficiently operate a data-based business. In developed countries overseas, research on new business models using various data accumulated at the level of government and private companies is being actively conducted. However, although the trade and import/export data collected in the domestic public sector is being accumulated in various types and ranges, the establishment of an analysis and utilization model is still in its infancy. Currently, we are living in an era of massive amounts of big data. We intend to discuss the value of trade big data possessed from the past to the present, and suggest a strategy to activate trade big data for trade digital transformation and a new direction for future trade big data research.

• Land and Housing Review
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• v.5 no.3
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• pp.193-201
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• 2014

Around 80% of the 63 million people in the UK live in urban areas where demand for affordable housing is highest. Supply of new dwellings is a long way short of demand and with an average annual replacement rate of 0.5% more than 80% of the existing residential housing stock will still be in use by 2050. A high proportion of owner-occupiers, a weak private rental sector and lack of sustainable financing models render England's housing market one of the least responsive in the developed world. As an exploratory research the purpose of this paper is to examine the provision of social housing in the United Kingdom with a particular focus on England, and to set out implications for housing associations delivering sustainable community development. The paper is based on an analysis of historical data series (Census data), current macro-economic data and population projections to 2033. The paper identifies a chronic undersupply of affordable housing in England which is likely to be exacerbated by demographic development, changes in household composition and reduced availability of finance to develop new homes. Based on the housing market trends analysed in this paper opportunities are identified for policy makers to remove barriers to the delivery of new affordable homes and for social housing providers to evolve their business models by taking a wider role in sustainable community development.

• Agribusiness and Information Management
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• v.6 no.2
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• pp.13-23
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• 2014

The world is in the process of a structural change related to ICT convergence knowledge industries. ICT is leading to the creation of new products and services, and is making our lives more convenient, safer, and more efficient. In advanced countries, many studies have been conducted with the goal of developing new business models converged with ICT, and this is also the case in the food industry. Korea possesses world-leading ICT, and if this ICT is applied to the food industry, a world-class new business model can be developed. The u-Food System, which is in the process of development in Korea, is a next-generation food system that can allow food providers, consumers, and distributors to access various types of information about food products, including traceability, distribution, safety, quality, and freshness, and manage this information. It is a future food system that converges ICT, biotechnology and sensing technology with food. Based on the u-Food System, this paper will introduce the status of current smart quality distribution technologies that converge ICT (such as sensor tag, sensor network, LBS, GIS, and CDMA) with food technologies (such as traceability, quality, distribution management) to manage the safety and quality of fresh food in the distribution process.

• Current Photovoltaic Research
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• v.11 no.4
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• pp.124-133
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• 2023

In order to deploy the large-scale energy storage (ES) service in the various industry, it is very important to develop a business model with high technological and economic feasibility through detailed valuation of cost and expected benefits. In relation to this, this paper established an optimal scheduling plan for electric vehicle charging stations connected with photovoltaic (PV) and ES technologies in Korea using the distributed energy resource valuation tool and analyzed the feasibility of the project. In addition, the impact of incentives such as REC (Renewable Energy Certificate) to be given to electric vehicle charging stations in accordance with the relevant laws to be revised in the future was analyzed. As a results, the methodology presented in this paper are expected to be used in various ways to analyze the feasibility of various business models linked to renewable energy and ES technologies as well as the electric vehicle market.

• The Journal of Society for e-Business Studies
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• v.10 no.1
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• pp.61-80
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• 2005

Business Process Management (BPM) System is a software system to support an efficient execution, control and management of business processes. The system automates complex business processes and manages them effectively to raise productivity. Traditional commercial systems mainly focus on automating processes and do not have methods for enhancing process performances and task performer's efficiency. Therefore, there is room for enhancement of task performers' productivities and efficiency of business processes. In this paper, we propose a new method of executing business processes more efficiently in that a whole process is scheduled considering the degree of participants' workload. The method allows managing the largest constraints among constituent resources of the process. This method is based on the DBR (Drum-Buffer-Rope) in TOC (Theory of Constraints) concepts. We first consider the differences between business process models and DBR application models, and then develop the modified drum, buffer and rope. This leads us to develop BP-DBR (Business Process-DBR) that can control the proper size of task performers' work list and arrival rate of process instances. Use of BP-DBR improves the efficiency of the whole process as well as participants' working condition. We then carry out a set of simulation experiments and compare the effectiveness of our approach with that of the scheduling techniques used in existing systems.

• The Korean Journal of Archival Studies
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• no.14
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• pp.153-190
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• 2006

Externally, business environment in public institution has being changed as government business reference model(BRM) appeared and business management systems for transparency of a policy decision process are introduced. After Records Automation System started its operation, dissatisfaction grows because of inadequacy in system function and the problems about authenticity of electronic records. With these backgrounds, National Archives and Records Service had carried out 'Information Strategy Planning for Reform to Records Management System' for 5 months from September, 2005. As result, this project reengineers current records management processes and presents the world-class system model. After Records and Archives Management Act was made, the records management in public institution has propelled the concept that paper records are handled by means of the electric data management. In this reformed model, however, we concentrates on the electric records, which have gradually replaced the paper records and investigate on the management methodology considering attributes of electric records. According to this new paradigm, the electric records management raises a new issue in the records management territory. As the major contents of the models connecting with electric records management were analyzed and their significance and bounds were closely reviewed, the aim of this paper is the understanding of the future bearings of the management system. Before the analysis of the reformed models, issues in new business environments and their records management were reviewed. The government's BRM and Business management system prepared the general basis that can manage government's whole results on the online and classify them according to its function. In this points, the model is innovative. However considering the records management, problems such as division into Records Classification, definitions and capturing methods of records management objects, limitations of Records Automation System and so on was identified. For solving these problems, the reformed models that has a records classification system based on the business classification, extended electronic records filing system, added functions for strengthening electric records management and so on was proposed. As regards dramatically improving the role of records center in public institution, searching for the basic management methodology of the records management object from various agency and introducing the detail design to keep documents' authenticity, this model forms the basis of the electric records management system. In spite of these innovations, however, the proposed system for real electric records management era is still in its beginning. In near feature, when the studies is concentrated upon the progress of qualified classifications, records capturing plans for foreign records structures such like administration information system, the further study of the previous preservation technology, the developed prospective of electric records management system will be very bright.

• The KIPS Transactions:PartD
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• v.15D no.5
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• pp.621-628
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• 2008

Many of today's businesses need IT system's flexibility for on-demand business which can be rapidly adapted to environment changes. Service oriented architecture (SOA) provides the infrastructure which makes business flexibility possible under the on-demand operating environment. Therefore, to satisfy these requirements, new approach for assuring business flexibility and enhancing reuse is needed. In this paper, we propose an approach for developing a business process family model (BPFM) in which the variabilities in business process family can be explicitly represented by using the variability analysis method of software product line. In addition, we describe the supporting tool for this approach. It can model the BPFM and generate automatically BPMs through decision and pruning process from BPFM. By using our approach, the business and its IT system can correspond to business environment changes rapidly and efficiently.