• Steel and Composite Structures
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• 제44권1호
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• pp.119-139
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• 2022

This paper aims to use the artificial intelligence approach to develop a new model for predicting the ultimate axial strength of the circular concrete-filled steel tubular (CFST) stub columns. For this, the results of 314 experimentally tested circular CFST stub columns were employed in the generation of the design model. Since the influence of the column diameter, steel tube thickness, concrete compressive strength, steel tube yield strength, and column length on the ultimate axial strengths of columns were investigated in these experimental studies, here, in the development of the design model, these variables were taken into account as input parameters. The model was developed using the backpropagation algorithm named Bayesian Regularization. The accuracy, reliability, and consistency of the developed model were evaluated statistically, and also the design formulae given in the codes (EC4, ACI, AS, AIJ, and AISC) and the previous empirical formulations proposed by other researchers were used for the validation and comparison purposes. Based on this evaluation, it can be expressed that the developed design model has a strong and reliable prediction performance with a considerably high coefficient of determination (R-squared) value of 0.9994 and a low average percent error of 4.61. Besides, the sensitivity of the developed model was also monitored in terms of dimensional properties of columns and mechanical characteristics of materials. As a consequence, it can be stated that for the design of the ultimate axial capacity of the circular CFST stub columns, a novel artificial intelligence-based design model with a good and robust prediction performance was proposed herein.

• The Journal of Asian Finance, Economics and Business
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• 제9권9호
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• pp.157-166
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• 2022

The purpose of this paper is to explain the process of developing and validating the instrument to measure the university's organizational core values and sub-values known as ESI iDART. The three core values are excellence, synergy, and integrity, while the five sub-values comprise knowledge, discipline, trustworthiness, diligence, and responsibility that all staff should understand and practice. These values must be measured to examine the extent to which the staff has practiced them in their work life. With regard to methodology, the research instrument used in the study was developed using a focus group study involving 39 university staff from various departments and campuses. The instrument was later refined and validated by a group of experts from the university. In the main study, the instrument was distributed to all 17,969 university staff from all over the country. After one month, a total of 11,688 university staff participated in the survey indicating a 66% response rate. Using descriptive analysis, reliability analysis, and ANOVA, the results indicate that instrument is considered valid and reliable to be used. The major findings from the study show that organizational values increase over time. Some theoretical and managerial implications are also discussed.

• Asia Marketing Journal
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• 제21권2호
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• pp.99-115
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• 2019

Branding strategy is important in the hyper-competitive luxury industry. In digitalized market environments, it is critical for luxury brands to transfer their established brand equity from the offline market to the online market. The purpose of this study is to examine the causal relationships between offline brand equity (i.e., brand awareness, brand image, and perceived quality)toward online consumer responses, including satisfaction and loyalty, in the context of luxury brands. In addition, this study investigates the moderating effects of offline brand trust on the relationship between offline brand equity and online satisfaction and loyalty. Data was collected via online surveys. For empirical validation of the proposed hypotheses, a structural equation modeling technique was employed. The results show that offline luxury brand awareness, brand image, and perceived quality have a positive effect on consumers' online satisfaction. Also, offline brand image has a positive effect on online consumer loyalty. The results indicate that there is a significant moderating effect of offline brand trust on the relationship between brand image and e-loyalty. The results of the present study provide implications for luxury brand managers and retailers to develop effective online sales strategies.

• Journal of Distribution Science
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• 제20권4호
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• pp.33-50
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• 2022

Purpose: This pilot study aims to conceptualize a new green marketing mix for retail consumers based on Stimulus-Organism-Response (SOR) model. Moreover, it also aims to conceptualize a testable research model of new green marketing mix with consumers' green purchasing behavior, and to validate the measurement model with traditional as well as modern suggested validating techniques. Research design, data and methodology: A pilot test data from 75 respondents of retail buyers of energy-efficient electric appliances in Pakistan were tested for the confirmatory factor analysis (CFA) by examining a measurement model of the construct through different validation techniques (like Composite Reliability, McDonald's Omega (ω), rho (ρA), HTMT, etc.) as heretofore these scales were not validated through these modern methods. Results: The results revealed that the instrument has a certain degree of reliability and validity through different validating techniques. All the measurement items reach the suggested threshold values. Conclusions: Therefore, this study conceptualized an integrated framework of all the three stakeholders of the environment (government, companies, and public or consumers) to achieve environmental sustainability. Hence, future studies can extend these findings and conduct a full-scale study to establish an empirical relationship between the 5G's of green marketing for retailing businesses and consumers' green purchase behavior.

• The Journal of Asian Finance, Economics and Business
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• 제9권1호
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• pp.13-24
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• 2022

The main goal of this study is to look at how South Korea can catch up to the rest of the world through policy-driven structural change and manufacturing revolutions. To achieve the objective, this study used annual data on real exports and real GDP from the World Development Indicator WDI of South Korea for the period 1960 to 2019. The study's goal is to use econometrics to detect this policy-driven structural change trend. Multiple nonlinear Granger causality test was used to accomplish this. The findings revealed structural breaks and nonlinearities in the dynamic link between South Korea's real GDP and real exports. Furthermore, results also show evidence of multiple structural breaks in South Korean data. South Korea's economic catch-up was the result of a constant reevaluation of industrial policies, readjustment, and structural change to constantly explore and utilize comparative advantage, realizing economies of scale at the global level, and reallocating and redistribution of resources towards productive sectors with high value-added output, according to econometric analysis. If South Korea would have not done this structural change this miracle to escape the middle-income trap would not have been possible. These findings support the descriptive evidence of structural change in favor of manufacturing revolutions and value addition industry development in South Korea.

• Steel and Composite Structures
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• 제44권5호
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• pp.691-705
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• 2022

Shear failure in reinforced concrete (RC) structures is very hazardous. This failure is rarely predicted and may occur without any prior signs. Accurate shear strength prediction of the RC members is challenging, and traditional methods have difficulty solving it. This study develops a JAYA-GBRT model based on the JAYA algorithm and the gradient boosting regression tree (GBRT) to predict the shear strength of RC slender beams without stirrups. Firstly, 484 tests are carefully collected and divided into training and test sets. Then, the hyperparameters of the GBRT model are determined using the JAYA algorithm and 10-fold cross-validation. The performance of the JAYA-GBRT model is compared with five well-known empirical models. The comparative results show that the JAYA-GBRT model (R² = 0.982, RMSE = 9.466 kN, MAE = 6.299 kN, µ = 1.018, and Cov = 0.116) outperforms the other models. Moreover, the predictions of the JAYA-GBRT model are globally and locally explained using the Shapley Additive exPlanation (SHAP) method. The effective depth is determined as the most crucial parameter influencing the shear strength through the SHAP method. Finally, a Graphic User Interface (GUI) tool and a web application (WA) are developed to apply the JAYA-GBRT model for rapidly predicting the shear strength of RC slender beams without stirrups.

• Asia pacific journal of information systems
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• 제32권3호
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• pp.601-629
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• 2022

Social networking sites (SNSs) have become an essential part of people's lives. It is thus crucial to understand how individuals use these platforms. Previous literature has divided usage into numerous activities and then grouped them into dimensions to avoid excessive granularity. However, these categories have not been derived from a uniform theoretical background; consequently, these dimensions are dispersed, overlapping, and disconnected from each other. This study argues that "SNS usage" is a complex phenomenon consisting of multiple activities that can be grouped into dimensions under the umbrella of communication theories and these dimensions are related to each other in a particular multi-dimensional architecture. "SNS usage" is conceptualized as a third-order construct formed by "producing," "consuming," and "communicating." "Producing," in turn, is proposed as a second-order construct manifested by "commenting," "general information sharing," and "self-disclosure." The proposed model was assessed with data collected from 414 USA adult users and PLS-SEM technique. The results show empirical support for the theorized model. SNS providers now have this architecture that clarifies the role of each dimension of use, which will allow them to design effective strategies to encourage the use of these networks.

• Journal of Navigation and Port Research
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• 제48권2호
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• pp.78-87
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• 2024

To quantitatively assess the correlation between subsystems within a port cluster and the overall coordinated development of the port group, the current paper evaluates the coordinated development of port clusters. First, we construct an evaluation index system for the coupling and coordination of port clusters. Next, we introduce the contribution index of port subsystems, coupling degree, and coupling coordination degree functions to formulate a coupling coordination evaluation model for the port cluster. Finally, we use the Yangtze River Delta port cluster as a case study for validation, specifically using empirical data from 2012 to 2021. The findings reveal distinct phased characteristics in the coupling and coordination of port clusters in the Yangtze River Delta, marked by a notable transition from "maladjustment" to "coordination." Further, sustained high coupling values over a decade indicate a significant level of competition and cooperation among ports within the Yangtze River Delta port cluster. Over time, this competitive and collaborative dynamic has progressively evolved toward a more positive and structured direction. Lastly, it is expected that the evaluation model proposed in this paper can be extrapolated to other port clusters to gauge the extent of coordinated development, thereby facilitating horizontal comparisons and vertical analyses.

• Journal of Korean Society for Quality Management
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• 제52권1호
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• pp.115-133
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• 2024

Purpose: The purpose of research is to explore the factors influencing the intention to adopt altcoin investments, based on the Unified Theory of Acceptance and Use of Technology. Through this, it seeks to elucidate the key factors impacting altcoin investment adoption, and provide a comprehensive understanding of the crypto-currency market and investor behavior. Methods: This study analyzed factors affecting altcoin investment intentions using frequency and descriptive analyses, and verified socio-demographic differences with t-tests and ANOVA. Exploratory factor and correlation analyses were conducted for research tool validity and relationship assessment among variables. Hypotheses were tested through regression analysis, integrating control, independent, and moderating variables, along with interaction terms, to establish the model and examine moderating effects. Results: As a result, it is revealed that higher age and experience in crypto-currency investment are associated with intention to invest. Among the independent variables, performance expectancy, social influence, facilitating conditions, and personal innovativeness have positive effects to investment intention to invest, while effort expectancy had a negative effect. The moderating variable, perceived risk, also negatively affected the intention to invest. Notably, significant moderating effects of perceived risk were observed in the relationships between investment intention and both performance expectancy and personal innovativeness. Conclusion: This study provides empirical verification into consumers' intentions to invest in altcoins, offering insights into investors' behavior and decision-making processes based on a practical understanding of altcoin investment acceptance.

• Korean Journal of Remote Sensing
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• 제36권2_2호
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• pp.309-323
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• 2020

Estimation of chlorophyll a concentration (CHL) on coastal areas using remote sensing has been mostly performed through multi-spectral satellite image analysis. Recently, various studies using hyperspectral imagery have been attempted. In particular, airborne hyperspectral imagery is composed of hundreds of bands with a narrow band width and high spatial resolution, and thus may be more effective in coastal areas than estimation of CHL through conventional satellite image. In this study, comparative analysis of hyperspectral and satellite-based CHL images was performed to estimate CHL in coastal areas. As a result of analyzing CHL and seawater spectrum data obtained by field survey conducted on the south coast of Korea, the seawater spectrum with high CHL peaked near the wavelength bands of 570 and 680 nm. Using this spectral feature, a new band ratio of 570 / 490 nm for estimating CHL was proposed. Through regression analysis between band ratio and the measured CHL were generated new CHL empirical formula. Validation of new empirical formula using the measured CHL showed valid results, with R² of 0.70, RMSE of 2.43 mg m^-3, and mean bias of 3.46 mg m^-3. As a result of applying the new empirical formula to hyperspectral and satellite images, the average RMSE between hyperspectral imagery and the measured CHL was 0.12 mg m^-3, making it possible to estimate CHL with higher accuracy than multi-spectral satellite images. Through these results, it is expected that it is possible to provide more accurate and precise spatial distribution information of CHL in coastal areas by utilizing hyperspectral imagery.