• The Journal of Bigdata
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• v.3 no.2
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• pp.87-99
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• 2018

This study analyze the factors affecting the number of bidders in public contracts by collecting contract data such as purchase of goods, service and facility construction through KONEPS among various forms of public contracts. The reason why the number of bidders is important in public contracts is that it can be a minimum criterion for judging whether to enter into a rational contract through fair competition and is closely related to the budget reduction of the ordering organization or the profitability of the bidders. The purpose of this study is to analyze the factors that determine the participation of bidders in public contracts and to present the problems and policy implications of bidders' participation in public contracts. This research distinguishes the existing sampling based research by analyzing and analyzing many contracts such as purchasing, service and facility construction of 4.35 million items in which 50,000 public institutions have been placed as national markets and 300,000 individual companies and corporations participated. As a research model, the number of announcement days, budget amount, contract method and winning bid is used as independent variables and the number of bidders is used as a dependent variable. Big data and multidimensional analysis techniques are used for survey analysis. The conclusions are as follows: First, the larger the budget amount of public works projects, the smaller the number of participants. Second, in the contract method, restricted competition has more participants than general competition. Third, the duration of bidding notice did not significantly affect the number of bidders. Fourth, in the winning bid method, the qualification examination bidding system has more bidders than the lowest bidding system.

• Information Systems Review
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• v.10 no.2
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• pp.269-289
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• 2008

It is very difficult problem to estimate and evaluate the performance of e-government system which scope and size are large and its effectiveness can not be seen shortly but reveals after several years. It is because the previous offline processes can not be transformed to online ones fully and shortly. For such e-transformation cases, the performance evaluation model should be adjusted and modified gradually as time passes. This paper propose new EEM(E-transformation Evaluation Model) model and methodology to evaluate G2B system that is one of large e-government project. EEM model can derive monetary value of e-transformatized business process areas(online areas). It also estimate the expected effect of offline area that is not yet transformed to online. EEM model consists of standard model, verification model and estimation model with some variables such as evaluation year, evaluation area and data type. By using survey data and database data together it can validate the correctness of the model and derive the effect of the system introduction. This paper also propose EEM evaluation methodology consisting of 5 stages and 10 sub processes to evaluate online and offline effect efficiently. To show the usefulness of this study, we evaluate the performance of Korea G2B system named KONEPS which is famous as a successful e-government case in the world by using the proposed model and methodology. The proposed model and methodology can be applied to different similar areas including e-government projects and large scale information system introduction in private sectors. This study can be also used for establishing appropriate policies about e-government project and informatization issues.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.239-248
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• 2023

The purpose of this study is to analyze the factors for service contracts that affect the successful bid price rate, focusing on the case of the country market. In the study, ordering organizations and bidders differentiated themselves from existing studies by analyzing service contracts that affect the successful bid price rate in a wide range of country markets. Comparative analysis of the awarding price ratio for services, this work provides a comparable result to the existing results in the previous literature. The analytical model used five independent variables such as budget, contract method, the days of the public notice, the awarding method, and the lowest awarding ratio. In the survey and analysis, big data was collected using text mining for service bids for Nara Market over the past 18 years and data was analyzed in a multi-dimensional way. The results of the analysis are as follows, (1) if budget does not determine the awarding price ratio. This is not the case in small amounts. (2) The contract method affects the awarding price ratio. (3) The days of the public notice increase, the awarding price ratio decrease. (4) the awarding method affects the awarding price ratio. (5) The lowest awarding ratio determines the awarding price ratio. Based on the results of empirical analysis, policy implications were sought.