Search results

Chinese tourists have become the greatest driving force behind global tourism. An increasing number of luxury fashion brands regard these tourists as a potentially significant segment of status-conscious consumers. Yet a limited number of marketing studies have addressed the significance of the intrinsic motivation that drives these tourist consumers to consume luxury goods. This study investigates the significant intrinsic factors that affect the luxury goods buying behavior of tourist consumers. Data are collected from 284 tourist consumers and analyzed by using the exploratory factor analysis (EFA) and cluster analysis. The EFA purified the measurement instruments to four factor attributes, namely, self-satisfaction, possession obsessiveness, status consciousness and personal differentness. The cluster analysis identified three groups of tourist consumers with distinctive behavioral segmentation criteria: ‘shopping hedonists’, ‘ego-defended achievers’ and ‘conspicuous fashionistas’. These findings provide managerial implications for building sustainable luxury businesses and competitive strategies tailored for tourist consumers.

The purpose of this paper is to investigate market segmentation of affluent Chinese consumers and develop profiles of identified segments for potential target markets for luxury fashion goods.

The data are from the 2006 edition of an annual survey called the “China's New Rich Study”. The respondents form a representative sample of affluent consumers, 18 to 45 years old, residing in China's 12 largest cities. A psychographic segmentation approach is employed to classify these consumers.

Five distinct market segments of affluent Chinese consumers are identified and profiled. Of these segments, three seem the most promising target markets for luxury fashion goods.

When companies understand the similarities and differences between consumer segments as well as the unique characteristics of segments, they have a meaningful basis for selecting receptive target markets and formulating and implementing effective marketing strategies. The findings of this study can be useful not only to companies that offer luxury fashion goods, but also to those targeting the upscale market with a plethora of products and services like yachts, luxury cars, high‐end electronics, resort vacations, and credit cards and other financial services.

This is the first study on segmentation of Chinese consumers for potential target markets for luxury fashion goods. Results reveal heterogeneity among affluent urban Chinese consumers. Strategies for marketing luxury fashion goods to promising target markets in China are outlined on the basis of segment profiles and culturally based motivations for purchasing such goods.

Previous researches have considered that the impact of fashion change and fashion consumption is linear. Therefore, one reason was found as the ultimate source to explain why a fashion style/ trend was spread to the mass market. However, the existing market is complex and difficult to find out the holistic reason to explain fashion consumption. In this study, the chaotic perspective is taken into account to investigate the relationship between fashion change and fashion consumption. By using the grounded theory method, 33 in‐depth interviews were conducted. A chaotic fashion consumption model is developed from the findings to explain how different fashions are consumed and rejected while fashion changes. It is found that the interaction of being fashionable, perceived fashionability and system participation affects the ultimate decision on fashion consumption. It is also found that a pattern can be traced to forecast the degree of fashion consumption even when the fashion change phenomenon is chaotic. Thus, it is similar to the principle of chaos theory that short‐term prediction is possible in relation to the degree of fashion acceptance among consumers. Marketing implications are suggested with reference to the chaotic fashion consumption model.

Discusses the 6th ITCRR, its breadth of textile and clothing research activity, plus the encouragement given to workers in this field and its related areas. States that, within the newer research areas under the microscope of the community involved, technical textiles focuses on new, ‘smart’ garments and the initiatives in this field in both the UK and the international community at large. Covers this subject at length.

The aerodynamic load caused by high-speed train operation may lead to severe vibration of the pedestrian bridge, thus causing great safety hazards. Therefore, this study aims to investigate the aerodynamic loading characteristics of a pedestrian bridge when a high-speed train passes over the bridge, as well as to evaluate the vibration response of the aerodynamic loads on the bridge structure.

High-speed trains are operated at three different speeds. The aerodynamic pressure load characteristics of high-speed trains crossing a pedestrian bridge are investigated by combining a nonconstant numerical simulation method with a dynamic modeling test method, and the vibration response of the bridge is analyzed.

The results show that when a high-speed train passes through the pedestrian bridge, the pedestrian bridge interferes with the attenuation of the pressure around the train, so that the pressure spreads along the bridge bottom, and the maximum positive and negative pressure peaks appear in the center area of the bridge bottom, while the pressure fluctuations in the bridge entrance and exit areas are smaller and change more slowly, and the pressure attenuation of the bridge bottom perpendicular to the direction of the train’s operation is faster. In addition, the pressure fluctuation generated by the high-speed train will lead to a larger vertical response of the bridge structure in the mid-span position, and the main vibration frequency of the bridge structure ranges from 8 to 10 Hz, and the maximum value of the vertical deformation amplitude is located in the mid-span region of the bridge.

This paper analyzes the flow field distribution around the train and at the bottom of the bridge for the evolution of the flow field when the train passes through the bridge at high speed, and conducts a finite element dynamic analysis of the bridge structure to calculate the vibration response of the bridge when the train passes through at high speed, and to evaluate the comfort of the passengers passing through the high-speed railroad bridge.

The aerodynamic differences between the head car (HC) and tail car (TC) of a high-speed maglev train are significant, resulting in control difficulties and safety challenges in operation. The arch structure has a significant effect on the improvement of the aerodynamic lift of the HC and TC of the maglev train. Therefore, this study aims to investigate the effect of a streamlined arch structure on the aerodynamic performance of a 600 km/h maglev train.

Three typical streamlined arch structures for maglev trains are selected, i.e. single-arch, double-arch and triple-arch maglev trains. The vortex structure, pressure of train surface, boundary layer, slipstream and aerodynamic forces of the maglev trains with different arch structures are compared by adopting improved delayed detached eddy simulation numerical calculation method. The effects of the arch structures on the aerodynamic performance of the maglev train are analyzed.

The dynamic topological structure of the wake flow shows that a change in arch structure can reduce the vortex size in the wake region; the vortex size with double-arch and triple-arch maglev trains is reduced by 15.9% and 23%, respectively, compared with a single-arch maglev train. The peak slipstream decreases with an increase in arch structures; double-arch and triple-arch maglev trains reduce it by 8.89% and 16.67%, respectively, compared with a single-arch maglev train. The aerodynamic force indicates that arch structures improve the lift imbalance between the HC and TC of a maglev train; double-arch and triple-arch maglev trains improve it by 22.4% and 36.8%, respectively, compared to a single-arch maglev train.

This study compares the effects of a streamlined arch structure on a maglev train and its surrounding flow field. The results of the study provide data support for the design and safe operation of high-speed maglev trains.

The ability to forecast a trend is very important in energy consumption prediction and energy production planning. The principle, under which the grey systems theory is applied in our energy consumption prediction, is that the forecasting system can be considered as a grey system. In such a system, unknown system's information can be determined by using known information. Here, the known information consists of energy consumption data, development trend in the consumption system. Based on our study, we eventually make forecast and decisions regarding possible future development. Our method is a whitenization process of a grey course. The model developed is based on the division method established for general data modelling and estimation of parameters of GM(1,1) its standard error coefficient that was applied to judge the accuracy height of the model was put forward; further, the function transform to forecast energy consuming trend and assess GM(1, 1) parameter was established. These two models need not pre‐process the primitive data. It was not only suited for equal interval data modeling, but also for non‐equal interval data modeling. Its calculation was simple and used conveniently, and the oil consumption per unit output analysis was taken as an example. The example showed that the two models were simple and practical, it was worth expanding and applying in the energy consuming prediction and energy programming.

The purpose of this paper is to investigate the effects of various catalyst contents, resin solid contents, catalyst species and wood extract on urea‐formaldehyde (UF) curing by differential scanning calorimetry (DSC) technique. The finding obtained would benefit the manufacturers of UF‐bonded composite panels.

The UF curing rate under each condition in terms of DSC peak temperature was measured by high‐pressure DSC at a heating rate of 15°C/min; the correlations of peak temperature with catalyst content, resin solid content, catalyst species and wood extract, respectively, were regressed via a model equation, which described the curing characteristics of the UF bonding system.

A model equation, T_p=A · EXP(−B · CC per cent)+D, was proposed to characterise the DSC peak temperatures or the rate of UF curing with regressing coefficients greater than 0.97 (commonly greater than 0.99). The constants A and B in the model equation were found to correspond to kinetic characteristics of UF resin curing reaction. The constant D in the model equation is believed to be associated with the utmost peak temperature, which implies that the DSC peak temperature will finally reach a maximum with catalyst content increasing. It was also found that the wood extracts having higher pH value and base buffer capacity had stronger catalyses on UF curing.

The catalysts commonly used in medium density fibreboard plants or particleboard plants are those having the utmost peak temperature of about 90‐95°C; the catalyses of wood extracts were much weaker than that of catalyst NH₄Cl.

The model equation could be used to predict the peak temperature or the curing rate of UF resin, and to quantify the effects of wood extracts on UF curing.

The study developed a model equation that can well characterise the UF curing, and quantified the effects of wood extracts on UF curing.

The purpose of this paper is to propose a research model exploring the link between open innovation, customer knowledge management and radical innovation. It seeks to answer these research questions: is there any difference among the effects of different types of open innovation activities on radical innovation? How does the organizational learning ability influence the impact of customer knowledge management on radical innovation?

The paper is based on the data collected from a sample of 165 modern service enterprises located in the Yangtze River Delta region. The authors conducted a structural equation modeling analysis using SPSS and MPLUS to test the proposed hypotheses.

The results showed that different kinds of open innovation activities had different impacts on the path to radical innovation. Inbound open innovation activities directly influenced radical innovation while the effect of outbound open innovation activities on radical innovation combined with the organizational exploitative learning ability is indirect. Similarly, the empirical results also proved that customer knowledge management had an indirect effect on radical innovation through the organizational learning ability, and the influence of the exploratory learning ability was more prominent.

Under the background of the national innovation driven by the development strategy, this paper studies the impact mechanism of radical innovation from the perspectives of open innovation and customer knowledge management. Therefore, it is suggested that the enterprise should adopt open innovation activities to foster innovation performance, formulate a customer-oriented innovation strategy and invest information and communication technologies to enhance the organizational learning ability of the enterprise.