• Journal of Global Scholars of Marketing Science
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• v.19 no.4
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• pp.57-63
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• 2009

With an exponential increase in electronic commerce (e-commerce), marketers are attempting to gain a competitive advantage by emphasizing service quality and post interaction service aspects, which leads to customer satisfaction or behavioral consequence. Particularly for apparel, service quality is one of the key determinants in encouraging customer e-loyalty, and hence the success of apparel retailing in the context of electronic commerce. Therefore, this study explores e-service quality (E-SERVQUAL) factors and their unique effects on e-loyalty for apparel online shopping based on Parasuraman et al' s (2005) framework. Specific objectives of this study are to identify underlying dimension of E-SERVQUAL, and analyze a structural model for examining the effect of E-SERVQUAL on e-loyalty for online apparel shopping. For the theoretical framework of service quality in the context of online shopping, literatures on traditional and electronic service quality factors were comparatively reviewed, and two aspects of core and recovery services were identified. This study hypothesized that E-SERVQUAL has an effect on e-loyalty; customer satisfaction has a positive effect on e-service loyalty for apparel online shopping; and customer satisfaction mediates in the effect of E-SERVQUAL on e-loyalty for apparel online shopping. A self-administered questionnaire was developed based on literatures. A total of 252 usable questionnaires were obtained from online consumers who had purchase experience with online shopping for apparel products and reside in standard metropolitan areas, in the United States. Factor analysis (e.g., exploratory, confirmatory) was conducted to assess the validity and reliability and the structural equation model including measurement and structural models was estimated via LISREL 8.8 program. Findings showed that the E-SERVQUAL of shopping websites for apparel consisted of five factors: Compensation, Fulfillment, Efficiency, System Availability, and Responsiveness. This supports Parasuraman (2005)'s E-S-QUAL encompassing two aspects of core service (e.g., fulfillment, efficiency, system availability) and recovery related service (e.g., compensation, responsiveness) in the context of apparel shopping online. In the structural equation model, there are five exogenous latent variables for e-SERVQUAL factors; and two endogenous latent variables (e.g., customer satisfaction, e-loyalty). For the measurement model, the factor loadings for each respective construct were statistically significant and were greater than .60 and internal consistency reliabilities ranged from .85 to .88. In the estimated structural model of the e-SERVEQUAL factors, the system availability was found to have direct and positive effect on e-loyalty, whereas efficiency had a negative effect on e-loyalty for apparel online shopping. However, fulfillment was not a significant predictor for explaining consequences of E-SERVQUAL for apparel online shopping. This finding implies that perceived service quality of system available was likely to increase customer satisfaction for apparel online shopping. However, it was not supported that e-loyalty was determined by service quality, because service quality has an indirect effect on e-loyalty (i.e., repurchase intention) by mediating effect of value or satisfaction in the context of online shopping for apparel. In addition, both compensation and responsiveness were found to have a significant impact on customer satisfaction, which influenced e-loyalty for apparel online shopping. Thus, there was significant indirect effect of compensation and responsiveness on e-loyalty. This suggests that the recovery-specific service factors play an important role in maximizing customer satisfaction levels and then maintaining customer loyalty to the online shopping site for apparel. The findings have both managerial and research implications. Fashion marketers can establish long-term relationship with their customers based on continuously measuring customer perceptions for recovery-related service quality, such as quick responses to problem and returns, and compensation for customers' problem after their purchases. In order to maintain e-loyalty, recovery services play an important role in the first choice websites for consumers to purchase clothing. Given that online consumers may shop anywhere, a marketing strategy for improving competitive advantages is to provide better service quality, maximize satisfaction, and turn to creating customers' e-loyalty for apparel online shopping. From a researcher's perspective, there are some limitations of this research that should be considered when interpreting its findings. For future research, findings provide a basis for the further study of this important topic along both theoretical and empirical dimensions. Based on the findings, more comprehensive models for predicting E-SERVQUAL's consequences can be developed and tested. For global fashion marketing, this study can expand to a cross-cultural approach into e-service quality for apparel by including multinational samples.

• Electronics and Telecommunications Trends
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• v.38 no.2
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• pp.26-35
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• 2023

Energy efficiency is an important factor toward sustainable future mobile network systems. As the size of the 5G mobile network system increases, the consumption and costs of energy increase. Accordingly, energy-saving optimization has become a major process in network systems, and various related technologies for energy saving are being developed. We provide a brief review of the technical trends in energy saving in 3GPP 5G & 5G Advanced systems and O-RAN systems. We focus on power models and energy-saving technologies in various resource domains of 3GPP 5G & 5G Advanced systems and energy-saving use cases of O-RAN systems.

• Computational Structural Engineering : An International Journal
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• v.2 no.1
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• pp.33-42
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• 2002

A computationally efficient stiffness design method for building structures is proposed in which dynamic soil-structure interaction based on the wave-propagation theory is taken into account. A sway-rocking shear building model with appropriate ground impedances derived from the cone models due to Meek and Wolf (1994) is used as a simplified design model. Two representative models, i.e. a structure on a homogeneous half-space ground and a structure on a soil layer on rigid rock, are considered. Super-structure stiffness satisfying a desired stiffness performance condition are determined via an inverse problem formulation for a prescribed ground-surface response spectrum. It is shown through a simple yet reasonably accurate model that the ground conditions, e.g. homogeneous half-space or soil layer on rigid rock (frequency-dependence of impedance functions), ground properties (shear wave velocity), depth of surface ground, have extensive influence on the super-structure design.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.3
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• pp.393-398
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• 2015

City or Community-scale Energy Management System(CEMS) is used to reduce the total energy consumed in the city by arranging the energy resources efficiently at the planning stage and controlling them economically at the operating stage. Of the operational functions of the CEMS, generation forecasting of renewable energy resources is an essential feature for the effective supply scheduling. This is because it can develop daily operating schedules of controllable generators in the city (e.g. diesel turbine, micro-gas turbine, ESS, CHP and so on) in order to minimize the inflow of the external power supply system, considering the amount of power generated by the uncontrollable renewable energy resources. This paper is written to introduce numerical models for photo-voltaic power generation prediction based on the weather forecasting information. Unlike the conventional methods using the average radiation or average utilization rate, the proposed models are developed for CEMS applications using the realtime weather forecast information provided by the National Weather Service.

• International Journal of Railway
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• v.1 no.3
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• pp.106-112
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• 2008

Rolling-sliding, cyclic contact of wheel and rail progressively alters the microstructure of the contacting steels, eventually leading to micro-scale crack initiation, wear and macro-scale crack growth in the railhead. Relating the microstructural changes to subsequent wear and cracking is being accomplished through modelling at three spatial scales: (i) bulk material (ii) multi-grain and (iii) sub-grain. The models incorporate detailed information from metallurgical examinations of used rails and tested rail material. The initial 2-dimensional models representing the rail material are being further developed into 3-dimensional models. Modelling is taking account of thermal effects, and traffic patterns to which the rails are exposed.

• Steel and Composite Structures
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• v.29 no.4
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• pp.423-435
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• 2018

There are presently two general ways of accounting for hazardous metal creep in structural fire analyses: either we incorporate creep strains implicitly in hardening model ('implicit-creep' plasticity) or we account for creep explicitly ('explicit-creep' plasticity). The first approach is simpler and usually used for fast engineering applications, e.g., following proposals of EN 1993-1-2. Prioritizing this approach without consideration of its limitations, however, may lead to significant error. So far the possible levels of such error have been demonstrated by few researchers for individual structural elements (i.e., beams and columns). This paper, however, presents analyses also for selected beam-girder assemblies. Special numerical models are developed correspondingly and they are validated and verified. Their important novelty is that they do not only account for creep in individual members but also for creep in between-member connections. The paper finally shows that outside the declared applicability limits of the implicit-creep plasticity models, the failure times predicted by the applied alternative explicit-creep models can be as much as 40% shorter. Within the limits, however, the discrepancies might be negligible for majority of cases with the exception of about 20% discrepancies found in one analysed example.

• Steel and Composite Structures
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• v.42 no.6
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• pp.733-745
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• 2022

This study proposed a robust artificial intelligence (AI) model based on the social behaviour of the imperialist competitive algorithm (ICA) and artificial neural network (ANN) for modelling the deflection of reinforced concrete beams, abbreviated as ICA-ANN model. Accordingly, the ICA was used to adjust and optimize the parameters of an ANN model (i.e., weights and biases) aiming to improve the accuracy of the ANN model in modelling the deflection reinforced concrete beams. A total of 120 experimental datasets of reinforced concrete beams were employed for this aim. Therein, applied load, tensile reinforcement strength and the reinforcement percentage were used to simulate the deflection of reinforced concrete beams. Besides, five other AI models, such as ANN, SVM (support vector machine), GLMNET (lasso and elastic-net regularized generalized linear models), CART (classification and regression tree) and KNN (k-nearest neighbours), were also used for the comprehensive assessment of the proposed model (i.e., ICA-ANN). The comparison of the derived results with the experimental findings demonstrates that among the developed models the ICA-ANN model is that can approximate the reinforced concrete beams deflection in a more reliable and robust manner.

• Journal of Information Technology Services
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• v.11 no.2
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• pp.339-353
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• 2012

Mobile communication technology is advancing forward to deliver more connected devices and richer content and applications. The number of subscriptions continues to grow along with an explosive increase in the mobile data traffic demand. Thereby, it creates a significant network capacity shortage concerns for mobile network operators. In order to address this problem, it is essential to increase the network capacity at a low additional cost. The device-to-device (D2D) communication based proximity service is believed to have a promising future mobile communication technology that is capable to create new mobile service opportunities and offload traffic to the eNB. In addition, it is also required to develop new mobile communication services and its business models not only to accommodate the increasing mobile traffic demand but also to foster profitability of mobile business service providers such as the network providers, contents providers and platform providers. In this article, we first analyze current mobile business eco-system in the context of CPNT based value chain. Then, propose service development framework and business model creation methodologies for the device-to-device communication based services in the beyond LTE/LTE-Advanced systems.

• Natural Product Sciences
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• v.10 no.1
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• pp.24-28
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• 2004

The effects of aqueous extract of Artemisia iwayomogi (Compositae) (AIAE) on the mast cell-dependent allergic and inflammatory reactions were investigated. AIAE (0.05 to 1 g/kg) dose-dependently inhibited systemic allergic reaction induced by compound 48/80 in mice. AIAE (0.1 and 1 g/kg) also significantly inhibited local allergic reaction activated by anti-DNP IgE. AIAE (0.001 to 1 mg/ml) dose-dependently inhibited the histamine release from rat peritoneal mast cells (RPMC) activated by compound 48/80. Moreover, AIAE inhibited the secretion of interleukin (IL)-6 in phorbol 12-myristate 13-acetate (PMA) plus calcium ionophore A23187-stimulated human mast cell line (HMC-1) cells. These results provide evidence that AIAE may be beneficial in the treatment of allergic diseases.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.2
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• pp.77-86
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• 2000

Consumers facing a large number of brands to choose from are known to use simplified heuristic to screen a set of relevant brands called the consideration set from the whole alternatives, Purchase decisions are then made from the brands in the consideration set, Two approaches have been suggested to model the two-stage choice process., One is to treat the con-sideration set as a crisp set (e.g Roberts and Lattin 1991) The other is to treat the set as a fuzzy set (e.g. Fortheringham 1988) The paper empirically compares the two types of models using data for soft drinks sneakers and departments. The results show that a model employing the crisp set approach fits the data better than that with the fuzzy set approach and better than a single-stage choice logit model.