• 동아시아경상학회지
• /
• 제12권1호
• /
• pp.1-11
• /
• 2024

Purpose: This study empirically examines the relations among corporate performance, technology, and corporate capabilities for service companies to find factors that could affect the competitiveness of the service industry. Most study on technology in the service industry have been conducted in developed countries, and yet there exist not sufficient empirical reviews. Research design, data and methodology: This paper, using rare empirical data, examines Korea's service industry and aims to make an academic and managerial contribution to the understanding of the relation between corporate competence and performance. This study analyzes 567 Korean Domestic Companies in Non-manufacturing and Service Industry, using the 2020 Detailed Survey of Venture Businesses (2500) data. Frequency analysis, correlation analysis, and regression analysis are performed. Results: Results show, Hypothesis 1 that internal competence has positive influence on technological strength, is supported. However, Hypothesis 2 that technological strength mediates between internal competence and business performance, Hypothesis 3 that external competence has positive influence on technological strength and Hypothesis 4 that technological strength mediates between external competence and business performance are all partially supported/rejected. Conclusions: This study suggests that technological strength is an important factor that affects both market share and sales. And mediating effect of technology strength emphasized in market share. However, in managing sales, more cautious approach and a more detailed analysis are needed..

• Computers and Concrete
• /
• 제16권6호
• /
• pp.919-932
• /
• 2015

This paper presents a new method for assessing the three-point-bending (3PB) strength of mortar beams in a non-destructive manner, based on neural network (NN) models. The models are based on the radial basis function (RBF) architecture and the fuzzy means algorithm is employed for training, in order to boost the prediction accuracy. Data for training the models were collected based on a series of experiments, where the cement mortar beams were subjected to various bending mechanical loads and the resulting pressure stimulated currents (PSCs) were recorded. The input variables to the NN models were then calculated by describing the PSC relaxation process through a generalization of Boltzmannn-Gibbs statistical physics, known as non-extensive statistical physics (NESP). The NN predictions were evaluated using k-fold cross-validation and new data that were kept independent from training; it can be seen that the proposed method can successfully form the basis of a non-destructive tool for assessing the bending strength. A comparison with a different NN architecture confirms the superiority of the proposed approach.

• Geomechanics and Engineering
• /
• 제25권4호
• /
• pp.317-330
• /
• 2021

This paper reports the results of advanced data analysis involving artificial neural networks for the prediction of the unconfined compressive strength of granite using only two non-destructive test indexes. A data-independent site-independent unbiased database comprising 182 datasets from non-destructive tests reported in the literature was compiled and used to train and develop artificial neural networks for the prediction of the unconfined compressive strength of granite. The results show that the optimum artificial network developed in this research predicts the unconfined compressive strength of weak to very strong granites (20.3-198.15 MPa) with less than ±20% deviation from the experimental data for 70% of the specimen and significantly outperforms a number of available models available in the literature. The results also raise interesting questions with regards to the suitability of the Pearson correlation coefficient in assessing the prediction accuracy of models.

• Geomechanics and Engineering
• /
• 제1권1호
• /
• pp.35-52
• /
• 2009

A significantly thick zone of steep slopes is commonly encountered above groundwater table and the soils within this zone are unsaturated with negative pore-water pressures (i.e., matric suction). Matric suction contributes significantly to the shear strength of soil and to the factor of safety of unsaturated slopes. However, infiltration during rainfall increases the pore-water pressure in soil resulting in a decrease in the matric suction and the shear strength of the soil. As a result, rainfall infiltration may eventually trigger a slope failure. Therefore, understanding of shear strength characteristics of saturated and unsaturated soils under shearing-infiltration (SI) conditions have direct implications in assessment of slope stability under rainfall conditions. This paper presents results from a series of consolidated drained (CD) and shearing-infiltration (SI) tests. Results show that the failure envelope obtained from the shearing-infiltration tests is independent of the infiltration rate. Failure envelopes obtained from CD and SI tests appear to be similar. For practical purposes the shear strength parameters from the CD tests can be used in stability analyses of slopes under rainfall conditions. The SI tests might be performed to obtain more conservative shear strength parameters and to study the pore-water pressure changes during infiltration.

• 한국건설관리학회논문집
• /
• 제6권1호
• /
• pp.133-139
• /
• 2005

선진국 건설업체에 대한 경쟁우위 확보와 건설수요의 대형화 및 복합공종의 고도기술 요구에 따라, 국내건설업 기술력 제고의 필요성이 더욱 높아지고 있다. 기술경쟁력 제고를 위해서는 기술의 연구 및 개발이 이루어져야 하며, 개발된 기술을 적극적으로 활용하여 기술축적에 의한 내실을 기해야만 기술경쟁력 확보가 가능하다. 건설업의 경우, 광범위한 기술개발 대상과 기술개발에 소요되는 대규모의 투자와 장기성 때문에, 각 기업의 주어진 여건에 맞는 기술경쟁력 제고 방향의 설정은 기업의 성장을 좌우할 수 있는 중요한 열쇠가 될 것이다. 따라서 기술개발추진 방향은 각 기업의 장기경영 전략에 맞추어서 설정되어야 한다. 본 연구는 건설업계 측면에서 효율적으로 기술개발을 추진할 수 있는 구체적인 방안을 제시한다. 기술경쟁력확보를 위해서는 기본적으로 단계적 건설경영 확대, 특화사업분야 핵심기술 보유, 기술개발체계 확립, 탄력적 조직 운영 등의 체계가 구축되어야 한다.

• Computers and Concrete
• /
• 제25권5호
• /
• pp.479-484
• /
• 2020

This work performed to analyses the impact of hooked end steel fibres on the mechanical properties of high performance concrete. The mechanical properties considered incorporate compressive strength, split tensile strength and flexural strength. Taking in to thought parameters, such as, volume fraction of fibres, fibre aspect ratio and grade of concrete, a logical strategy called Taguchi technique was utilized to discover the ideal blend of factors. L9 Orthogonal Array (OA) of Taguchi network comprising of three variables and three dimensions is utilized in this work. The evaluations of concrete considered were M60, M80 and M100. M60 contained 15% of metakaolin as bond swap though for M80 it was 5% of metakaolin and for M100 it was 10% metakaolin and 10% of silica smolder. The volume portion of fiber was fluctuated by 0.5%; 1% and 1.5% and the viewpoints proportions considered were 50, 60 and 80. The test outcomes demonstrate that incorporation of steel fibres enhance significantly the the strength characteristics of concrete, predominantly the splitting tensile strength and flexural strength. In light of relapse investigation of the test information scientific models were produced for compressive strength, split tensile strength and flexural strength of the steel fibre-reinforced high performance concrete.

• Computers and Concrete
• /
• 제24권4호
• /
• pp.329-345
• /
• 2019

Despite the extensive use of mortar materials in constructions over the last decades, there is not yet a robust quantitative method, available in the literature, which can reliably predict mortar strength based on its mix components. This limitation is due to the highly nonlinear relation between the mortar's compressive strength and the mixed components. In this paper, the application of artificial neural networks for predicting the compressive strength of mortars has been investigated. Specifically, surrogate models (such as artificial neural network models) have been used for the prediction of the compressive strength of mortars (based on experimental data available in the literature). Furthermore, compressive strength maps are presented for the first time, aiming to facilitate mortar mix design. The comparison of the derived results with the experimental findings demonstrates the ability of artificial neural networks to approximate the compressive strength of mortars in a reliable and robust manner.

• International Journal of Concrete Structures and Materials
• /
• 제6권4호
• /
• pp.239-246
• /
• 2012

Pervious concrete is a tailored-property concrete with high water permeability which allow the passage of water to flow through easily through the existing interconnected large pore structure. This paper reports the results of an experimental investigation into the development of pervious concrete with reduced cement content and recycled concrete aggregate for sustainable permeable pavement construction. High fineness ground granulated blast furnace slag was used to replace up to 70 % cement by weight. The properties of the pervious concrete were evaluated by determining the compressive strength at 7 and 28 days, void content and water permeability under falling head. The compressive strength of pervious concrete increased with a reduction in the maximum aggregate size from 20 to 13 mm. The relationship between 28-day compressive strength and porosity for pervious concrete was adversely affected by the use of recycled concrete aggregate instead of natural aggregate. However, the binder materials type, age, aggregate size and test specimen shape had marginal effect on the strength-porosity relationship. The results also showed that the water permeability of pervious concrete is primarily influenced by the porosity and not affected by the use of recycled concrete aggregate in place of natural aggregate. The empirical inter-relationships developed among porosity, compressive strength and water permeability could be used in the mix design of pervious concrete with either natural or recycled concrete aggregates to meet the specification requirements of compressive strength and water permeability.

• 유통과학연구
• /
• 제10권8호
• /
• pp.15-23
• /
• 2012

This study is an attempt to explore the nature and characteristics of strategic impact of green strategy by environmental capital, corporate reputation, and technology strengths on the firm's performance across countries. The main question addressed in this paper relates to how corporate sustainability, corporate reputation, technology strength, and capabilities influence the firm's economic performance with respect to diverse dimensions of performance measures including sustained growth through the leading firms across countries in the United States, Canada, Europe, and Asia-Pacific countries. Particularly, this study attempts to empirically explore the directions and magnitudes of the operational links between new emerging strategic core competencies (e.g., sustainability green strategy by environmental focus for more sustainable path, corporate reputation by corporate social responsibility and image enhancement, and technology strengths to develop a new product and market) and the firm's economic performance with respect to diverse dimensions of performance such as accounting (ROE and EOA) - and market-based performance (Market value and Tobin's q). Considering all possible limitations that might exist with regard to selected samples and methods, this study demonstrates that environmental sustainability, corporate reputation, technological capabilities and competencies through R&D intensity and patent are most likely to be significantly associated with most market-based performance measures, but the strategic significance of other variables such as capital intensity, leverage, and administrative cost efficiency on performance tends to be different depending on which performance measure is used across different countries with diverse economic and business contexts.

• Journal of Industrial and Engineering Chemistry
• /
• 제67권
• /
• pp.156-163
• /
• 2018

High-performance mixed-matrix membranes that comprise both zeolitic imidazolate framework-8 (ZIF-8) and graphene oxide (GO) were synthesized with a solution casting technique to realize excellent $CO_2/CH_4$ separation. The incorporation of ZIF-8 nanocrystals alone in ODPA-TMPDA polyimide can be used to significantly enhance $CO_2$ permeability compared with that of pure ODPA-TMPDA. Meanwhile, the addition of a GO nanostack alone in ODPA-TMPDA contributes to improved $CO_2/CH_4$ selectivity. Hence, a composite membrane that contains both fillers displays significant enhancements in $CO_2$ permeability (up to 60%) and $CO_2/CH_4$ selectivity (up to 28%) compared with those of pure polymeric membrane. Furthermore, in contrast to the ZIF-8 mixed-matrix membrane, which showed decreased mechanical stability, it was found that the incorporation of GO could improve the mechanical strength of mixed-matrix membranes. Overall, the synergistic effects of the use of both fillers together are successfully demonstrated in this paper. Such significant improvements in the mixed-matrix membrane's $CO_2/CH_4$ separation performance and mechanical strength suggest a feasible and effective approach for potential biogas upgrading and natural gas purification.