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The purpose of this paper to examine how Chinese consumers’ perceived functional and symbolic values of lifestyle fashion stores (i.e. merchandise quality, price, convenience, emotional value, aesthetic value and social value) affect their shopping behaviors (i.e. repurchase intention (RI), impulse buying (IB) and time spent (TS)).

In total, 223 eligible responses were collected via an online questionnaire survey. The psychometric properties of the proposed CPV-shopping behavior research model were examined, and the multiple regression method was applied to test the hypotheses.

The findings show that Chinese consumers’ RIs toward and TS in lifestyle fashion stores are determined by their perceived merchandise quality value, price value, emotional value and aesthetic value of lifestyle fashion stores. In contrast, Chinese consumers’ perceived price value and emotional value trigger their IB in the lifestyle fashion stores. The perceived values show satisfactory explanatory power for the variances of Chinese consumers’ shopping behaviors (R²=55, 50 and 49 percent for RI, IB and TS, respectively).

A better understanding of the Chinese consumers’ shopping behaviors toward emerging lifestyle fashion stores may assist retailers in targeting China as the soon-to-be largest consumer market.

This study aims to examine the linkages between port aesthetics, destination image, tourist satisfaction and tourist loyalty in Hong Kong.

To achieve this objective, the authors surveyed 247 tourists in Hong Kong. Using factor analysis and structural equation model (SEM) to identify the constructs of port aesthetics and analyze its relationship with destination image, tourist satisfaction and tourist loyalty.

Five-port aesthetics constructs were identified, namely, leisure and culture, design and cognition, atmosphere, recreational facilities and memory. The results of SEM revealed the following: port aesthetics positively influenced destination image; destination image positively influenced tourist satisfaction; and tourist satisfaction had a positive influence on tourist loyalty. This research also found that the indirect effect of port aesthetics on tourist loyalty via destination image and tourist satisfaction.

While the environmental qualities of a port could potentially affect destination image, tourist satisfaction and loyalty, this study developed and validated a measurement instrument of perceived port aesthetics from a tourist’s perspective. Specifically, this research proposed a structural model to explain the relationships between port aesthetics, destination image, tourist satisfaction and loyalty.

The purpose of this paper is to empirically determine the key factors influencing the US consumers’ intentions to use apparel m-commerce.

An enhanced consumer’s apparel m-commerce adoption model was developed through integrating the existing e-commerce/m-commerce theories (i.e. theory of reasoned action, Technology acceptance model and diffusion of innovation theory). The investigated factors included nine independent variables – perceived usefulness (PU), perceived ease-of-use, subjective norm (SN), personal innovativeness traits, security and privacy concerns, compatibility, observability, trust and past non-store shopping experience (PE), and five control variables – age, gender, education level, income level and ethnicity. The dependent factor is consumer’s intention to use (IU) apparel m-commerce. The primary data were gathered by an online survey of US consumers via Amazon Mechanical Turk. In total, 317 eligible responses were received. The applied statistical techniques were factor analysis and multiple regression analysis.

The results show that the US consumer’s IU apparel m-commerce is significantly affected by PU, SN, compatibility and PE and education level. Overall, 67.3 percent of variation in the US consumer’s IU apparel m-commerce is explained by the developed model, which suggests a high explanatory power.

Companies should provide those functions and features on their mobile websites that enable consumers to easily find the products wanted and complete transactions efficiently. Companies should particularly target the consumers with innovativeness traits and/or those having prior non-store shopping experience. Enhancing the trust in m-commerce among the US consumers with higher education level could help companies attract more potential users. Elderly, female or lower income consumers could be the next business opportunities for apparel e-tailers.

As one of the first efforts made to understand the emerging apparel m-commerce phenomenon, this study empirically determined the key factors influencing the US consumer’s IU apparel m-commerce.

It is a crucial issue to eliminate cracks for selective laser melting (SLM) 7xxx series aluminum alloy. This paper aims to study the effect of silicon content on the cracking behavior and the mechanism of eliminating crack of SLMed Al7050 alloy.

Six different silicon contents were added to the Al7050 powder. The crack density and crack count measuring from optical micrographs were utilized to judge the cracking susceptibility. The low melting phases analyzing from Jmatpro and the microstructure observing by EPMA and SEM were used to discuss the mechanism of eliminating the crack.

The cracking susceptibility of SLMed Al7050 alloy decreases with the increase of adding silicon content. When adding silicon, two new low-melting phases appeared: Mg2Si and Al5Cu2Mg8Si6. These low-melting phases offer much liquid feeding along the grain boundary and decrease the cracking susceptibility. Moreover, the grains are obviously refined after adding silicon. The fine grain can increase the total surface area of the grain boundary, which can reinforce the matrix and decrease the cracking susceptibility. High silicon content results in more low-melting phases and fine grains, which decreases the cracking susceptibility.

The investigation results can help to obtain crack-free SLMed Al7050 parts and deep knowledge on eliminating cracking mechanism of high-strength aluminum alloy fabricated by SLM.

The purpose of this paper is to propose and examine a consumer-perceived value (CPV) formation model in the context of Hawaiian attire (aloha attire). The effects of key socio-demographic factors on perceived values of aloha attire were empirically determined.

CPV is conceptualized as a multi-dimensional construct including emotional value, social value, quality value, and price value. The investigated socio-demographic factors included residential status, age, gender, ethnicity, education level, income level, and type of retailers from which consumers usually purchase aloha attire. The primary data were gathered by a questionnaire survey of US consumers. Using 330 survey returns, factor analysis and multiple regression analysis were utilized for data analysis and hypothesis testing.

The proposed model was proven valid and the four value constructs cumulatively accounted for 68.6 percent of the variance in CPV of aloha attire. Majority of variances of perceived values (social value at 74 percent, emotional value at 70 percent, price value at 67 percent, and quality value at 65 percent, respectively) can be accounted for by investigated socio-demographic factors. Gender and ethnicity significantly affected perceived social and emotional values. Income level and education level significantly affected all perceived values. Residential status only affected perceived price and emotional values, while retailer type significantly affected perceived social, emotional, and quality values.

Incorporation of gender, ethnicity, income level, education level, residential status, and retailer type information in developing marketing strategies and promotional programs can help companies more effectively convey desired values of aloha attire to target consumers.

This empirical study responded to the need for better understanding of consumer desired values for aloha attire to support more effective product development and marketing. The knowledge gained from this study provides valuable insights for both academicians and industrial practitioners.

This study aims to take a strategic approach to analyze how the US technical textile companies manage their business operations and to determine whether there are differences on competitive priorities between high‐ and low‐performing companies.

A competitive priority model consisting of four latent constructs – low cost, quality, delivery performance, and flexibility – was utilized to construct the analysis. Primary data were collected through a survey of senior executives in the US technical textile companies. Using 202 eligible survey returns, exploratory factor analysis and confirmatory factor analysis within structural equation modeling were carried out to assess adequacy of the measurements and validity of the model.

The competitive priority model is proven valid and the four constructs account for the most variance in corporate competitive strategies. High‐performing companies placed greater emphasis on quality and delivery performance strategies than low cost strategy in order to build capabilities for product or service differentiation; in contrast, low‐performing companies gave equal weight to all four competitive capabilities. The lack of clear emphasis on strategies could be one of the reasons for a relatively low business performance.

The study provides a springboard for future studies of corporate competitive strategies and its relationships with other key decisions and outcomes.

The deployment of appropriate strategies is imperative to achieve superior business performance and, perhaps, just to survive.

The paper represents the first empirical investigation into corporate strategy issues in the US technical textile sector. The methodology may be transferred to other industrial sectors.

The purpose of this paper is to propose and empirically examine a consumer perceived value (CPV) formation model in the context of the US casual sportswear market. The effects of investigated contingency factors on perceived values are empirically determined.

CPV was measured by four dimensions: price, quality, social and emotional values. The investigated contingency factors included gender, age, race, income level, and retailer type. The primary data were gathered by a nation‐wide survey of US consumers and the applied statistical techniques were exploratory factor analysis, confirmatory factor analysis, and multiple regression analysis.

The statistical analysis of 4,949 eligible survey responses shows that four value dimensions accounted for 77 percent of CPV variance. For the effects of contingency factors, race did not significantly affect the formation of any perceived values. In contrast, gender, income level, and retailer type significantly affected perceived price and emotional values, while perceived quality value was significantly affected by all contingency factors except race, and perceived social value was only significantly affected by age and income level.

Incorporation of gender, income level, and retailer type information in developing marketing strategies can help companies more effectively convey price and emotional values to consumers. In contrast, information relating to gender, age, income level, and retailer type should be considered in marketing quality value to consumers, while age and income level information is more critical for properly marketing social value to consumers.

Companies need to know, more than ever, about how consumers are redefining their values, as the current economic crisis has dramatically changed consumer preference. This study responded to this emerging need and provided timely empirical evidence.

This paper aims to present an exploratory investigation into ten‐year (1995‐2004) patterns of trade specialization among Eastern European and former Soviet Union Nations, assessing patterns of comparative advantage across the textile machinery, man‐made fiber, textile, and apparel sectors of the textile complex to determine whether these conform with both trade specialization and industry evolution theories.

A revealed symmetric comparative advantage index is employed to evaluate international competitiveness for 27 Eastern European and former Soviet Union Nations over a ten‐year period. Repeated measures ANOVA is used to determine the significance of the observed patterns across four income‐defined groups of nations.

Overall, the pattern of export development and RSCA generally reflects expectations regarding factor proportions theory and industry evolution models. The RMANOVA partially confirms the observations. The analysis indicates that income group does not independently affect comparative advantage; however, the nature of products is the significant factor influencing national comparative advantage.

The established models may be better at understanding those nations which have established relatively stable politic and economic environment, and been experiencing earlier stages of industry development, but appear less useful in predicting development patterns for those nations experiencing dramatic transitions from regulated to de‐regulated markets.

The patterns of national comparative advantage in a vertical textile complex are identified for Eastern European and former Soviet Union Nations. The dynamics of change over a ten‐year period following economic reforms are revealed.

This study aims to quantitatively identify the impact of major economic and political factors on the US apparel imports from its 15 major trading partners between 1995 and 2006.

Ordinary‐least‐square (OLS) regression under a gravity model framework was utilized to construct the analysis. The determinants of US apparel imports were determined and their significance and direction of change over the period were quantified.

First, the growths of GDP and population both in the USA and within its trading partners have been drivers of US apparel import growth, while greater geographic distance between a trading partner and the USA significantly impedes its exports to the USA. Second, the positive impact on the US apparel imports from the supplying country's infrastructure development, literacy rate and its language commonality with the USA shows that these factors are pivotal to being a competitive US apparel supplier. Finally, preferential market access is proven to be crucial for suppliers to increase apparel exports to the USA.

In future work, the impact of these factors on disaggregated apparel categories could be investigated. Some emerging issues such as non‐tariff barriers could be exploited.

The findings reveal that the US apparel sourcing decisions are made on the basis of many different costs, not only labour cost, but also economic condition, government policy, infrastructure, transport time and cost, language/culture commonality etc.

The study provides a springboard for empirically analyzing the US apparel imports under a gravity model framework. The conclusions are drawn based on solid quantitative evidence.

This paper aims to present an exploratory investigation into long‐term patterns of trade specialization among leading textile and apparel exporting nations, assessing patterns of comparative advantage across the textile machinery, man‐made fiber, textiles and apparel sectors of the textile complex to determine whether these conform with both trade specialization and industry evolution theories. A model of evolutionary change in intra complex specialization is defined and evaluated.

A revealed comparative advantage index is employed to evaluate international competitiveness for 30‐nations over a 42‐year period. Repeated measures of ANOVA are used to determine the significance of the observed patterns across five income‐defined groups of nations.

Long‐term patterns of specialization broadly reflect expectations of factor proportions theory and industry evolution models. Product and income group characteristics combine to influence comparative advantage. Higher income nations generally remain stronger in more capital‐intensive sectors, while lower income countries have emerged to dominate labor‐intensive sectors. However, inclusion of a more complex array of variables is necessary to obtain a fuller understanding of international competitiveness.

Established theory remains a useful but limited guide to understanding the dynamics of international competitiveness in the context of the changing business environment. Improved understanding of patterns of change can assist strategic planning.

By embracing a long‐term time frame, a broad array of nations, and a vertical textile complex perspective to identify shifting patterns of competitiveness, this paper highlights key dynamics in the global textile complex over the last four decades.