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In 1978, the once powerful US apparel industry was on the cusp of change, and the consulting firm KSA conducted a Delphi survey of apparel executives’ predictions into the 2000s. The purpose of this paper is to compare actual changes over the subsequent decades with these 1978 expert predictions and explore the accuracy/inaccuracy of these “educated guesses” (KSA, 1978, p. 1).

The chorographic method was used to analyze the report and document historical data. Chorography is “concerned with significance of place, regional characterization, [and] local history […]” (Rohl, 2012, p.1) and includes contextual settings and researcher input. Primary data were examined during each decade and included: industry literature, government documents and labor data. The researchers used content analysis to reduce and organize data.

Findings cover three decades of Southeast US apparel industry data including imports, employment, number of plants, size of plants and productivity. Predictions were inaccurate about imports, predicted to be minor in comparison with domestic production, which they actually surpassed. Predicted decrease in employment was similar to actual decrease but reasons were inaccurate. Change in number and size of plants were over-predicted and under-predicted. Reasons given by experts were automation and government intervention; in actuality, limited automation occurred with insignificant impact in contrast to outsourcing, which decimated employment in US plants. Steady increase in productivity was predicted when productivity often decreased.

Previous studies focus on the textile sector; studies of the apparel sector tend to be regional or topical. This study is more expansive and provides insight into predictions and changes made in the US apparel industry at a critical time in its near demise. With the current climate of global change and increased market uncertainty, insights from this study may provide direction for rethinking of the domestic apparel industry for the USA and other developed countries.

Virtual try-on (VTO) technology with three-dimensional (3D) body scanning in a mobile application is a relatively new technique for selling custom-fit apparel. VTO involves scanning and measuring one's body and visualizing the fit of a garment on a 3D avatar. The purpose of this study is to explore consumers' experiences toward the custom-fit T-shirts and online mass customization (MC) services using the VTO technology found in online consumer reviews (OCRs).

A total of 297 OCRs were collected from the Amazon's Made for You site that uses VTO technology for the MC process. A qualitative content analysis, within a mixed method research process, was used to determine systematically the meanings within qualitative data with quantitative results. In the qualitative approach, combinations of two coding processes were employed, which were concept-driven (i.e., deductive/a priori) and data-driven (i.e., inductive/emergent) coding processes. In the quantitative approach, the prevalence of each coding in terms of its valence was calculated based on frequencies. Intercoder reliability reached 96 per cent.

In OCRs of customized apparel products and online MC services using VTO technology, consumers described expectations, perceived performance, dis/confirmation, dis/satisfaction, outcomes of dis/satisfaction and descriptive information. Those with expectations often expressed skepticism about the product and the MC process using VTO technology at the pre-consumption stage. In OCRs, they used four product dimensions and two service dimensions of perceived performance. Consumers had positive (negative) confirmation when the performance of the T-shirts and/or services worked better (worse) than their expectations. The OCRs also included dis/satisfaction with a product and/or service, its outcomes and descriptive information.

This study identified a resulting framework to identify the content in OCRs of the custom-fit T-shirts and online MC services that use VTO technology. This study extends the expectation confirmation theory by adding multiple dimensions (i.e., four product dimensions and two service dimensions) as well as more outcomes of dis/satisfaction (not limited to repurchase intentions). This study provides practical suggestions for online MC companies who are using or planning to use VTO technology on how to improve consumers' satisfaction with customized T-shirts using VTO technology.

The purpose of this study was to examine the effects of product image at three stages of the consumer decision process for apparel products: alternative evaluation, purchase and post‐purchase stages. The three specific objectives of the study were to examine at the alternative evaluation stage the effect of product image on perceived quality and performance expectation, at the purchase stage the effect of product image on purchase intention and the price the consumer was willing to pay, and at the post‐purchase stage the effect of product image on consumer satisfaction and the effect of product image with product consumption performance on consumer satisfaction. The experimental design was used to determine the cause‐and‐effect relationships between the treatment variables (independent variables) and the dependent variables. Sweatshirts were used as the sample product category and 120 university students were recruited as participants. Results showed that at the alternative evaluation stage, product image significantly and positively influenced perceived quality and performance expectation. At the purchase stage, product image was not a determinant of purchase intention, but significantly and positively influenced the price participants were willing to pay for the product. At the post‐purchase stage, product image did not directly influence participants’ satisfaction, but product image with product consumption performance significantly affected satisfaction. When consumption performance was good, product image significantly and positively influenced satisfaction. When consumption performance was poor, product image significantly and negatively influenced satisfaction.

The apparel manufacturers that service apparel products, also known as fashion products, have been challenged by turbulent and volatile changes within the market over the past 30 years. Changes in the business environment in the U.S. apparel manufacturing industry and the reactions of associated firms have continued to affect the profile of this industry. In this research, we documented the historical changes in the U.S. apparel manufacturing industry, from 1973 to 2005, and examined the impact of the business environment on strategies during this time. A mixture of positivism and phenomenology techniques was used within the scope of the historical review to achieve the study's purposes. The conceptual framework developed from theories about environmental determinism or adaptation provided support for data collection and organization. The results present an in-depth exploration of three environmental factors (i.e., globalization, technology, consumer) for the U.S. apparel manufacturing industry, a listing of the implemented business strategies for U.S. apparel manufacturing firms, and the interrelation of the environmental factors to these resultant strategies.

Supply chain management (SCM) in the apparel industry was empirically examined through a quantitative research design. The objectives of the study were to identify the level of SCM activities and to examine the relationship of selected company characteristics for a set of US apparel manufacturers. Through the literature review, six dimensions of SCM (i.e. partnership, information technology, operational flexibility, performance measurement, management commitment, demand characterization) were identified. US apparel manufacturer groups, based on their SCM activity levels, showed statistically significant differences in company characteristics including product fashion level, fabric supplier delivery performance, relationship with fabric suppliers and retail customers and relative size of retail customers. For example, a high level of SCM activity implementation is closely related with the characteristics of more basic goods production, higher delivery performance of fabric supplier, and relatively big retailers. These manufacturers also had more partnership‐like relationship with their supply chain members.

The purpose of this paper is to develop a luxury brand management (LBM) framework that accounts for the changing luxury environment (i.e. heterogeneous consumer populations, operations within markets of varying maturity, need for seamless customer experiences, and Omni-channel retailing). Framework set within this new luxury business environment and environmental phenomena unique to the fashion industry (i.e. fashion adoption, zeitgeist).

Case study of leading luxury conglomerate, Louis Vuitton Möet Hennessy (LVMH), combined with in-depth historical review of luxury industry. Primary and secondary data sources yielded thick descriptions of brands in LVMH portfolio and larger luxury industry, in which conglomerate is the predominant organizational structure. Content analysis of data-tracked relationships and emergent patterns. Recontextualization techniques were employed to identify key dimensions of brand management operations for sample company and further explicated indicators, sub-variables, and measurements. Macro and micro dimensions were combined for the final framework.

Findings revealed a LBM framework with specific dimensions at the micro or company level that are combined with variables and indicators in the macro-business environment. Strategic management response was also identified as a tool companies can use to synthesize brand management strategies throughout company and remain adaptive to environment.

Contributes to company-based luxury research. Holistic findings; framework was constructed from the micro-company level within a macro-environmental context, increasing its relevancy for firms. Potential to be employed in strategic brand management decisions of luxury companies, regardless of their corporate structure, size, or age.

To investigate consumers' characteristics during internet shopping for customized products in order to reduce the distance between a manufacturer and consumers.

Qualitative methods were conducted with longitudinal interviewing with 20 participants. For the shopping experiment, a web site was used by participants to order two pair of customized shoes based on each participant's needs.

Four groups were identified during the shopping experiments. The result suggested that each group of participants had different priorities for a satisfying shopping experience in terms of customized products.

This paper identified the relationship between a manufacturer and consumers by ordering customized products through online.

In response to international competition and pressure from retailers, US apparel manufacturers and their suppliers initiated the Quick Response (QR) program. QR seeks to provide retailers with the exact stock‐keeping units (SKUs) which consumers demand and to deliver these SKUs quickly. An effective QR program requires rapid transmission of data throughout the value chain, from the retailer back to apparel manufacturers, fabric producers and fibre manufacturers. Therefore, electronic data interchange (EDI) is a key component of QR and should be tightly linked with other information systems at each level of the value chain. This research is an empirical study of the degree to which EDI has been implemented by US apparel manufacturers and the extent to which EDI is integrated with other information systems. It was found that apparel manufacturers use EDI to establish tight linkages with their customers, the retailers. Manufacturers are less likely to increase their own efficiencies by linking EDI with internal information systems or by establishing EDI linkages with suppliers. The lack of supplier linkages may reduce manufacturers' ability to replenish retail inventories quickly, which is the primary objective of QR.

The purpose of this study is to provide detailed information about the shopping behaviors and brand/product preferences of college students. To accomplish this purpose the following objectives were proposed: to identify college student segments’ underlying clothing shopping orientations; to profile these consumers by demographics and brand/product preferences; and to use apparel expenditures to further characterize the market segments.

A survey of college students at a major university was conducted. After adopting the listwise deletion method, 185 useable questionnaires were available for analysis. For data analysis, descriptive statistics, K‐means cluster analysis, Chi‐square, ANOVA, and Dunnett T3 tests were employed. Results showed that three segments were identified (i.e. apathetic price‐forward shoppers, hedonic fashion‐forward shoppers, involved price‐forward shoppers), and the three hypotheses were supported.

The paper shows that the three segments can be characterized by distinct profiles of demographics and brand/product preferences. Marketing and merchandising strategies for retailers are provided.

Few studies have examined college students’ specific brand/product preferences even though information about these consumer preferences can be directly and practically utilized by apparel retailers for their merchandise planning. There is also a lack of studies that examined college students' clothing behavior based on their major. With the increasing importance of brand as a marketing tool, this information is important to academic researchers and retailers.

Firms in the apparel industry seek operational information on ways to implement mass customization. The purpose of this research is to investigate the potential for concurrent engineering (CE) to realign the traditional, linear apparel product development process to a more concurrent and consumer‐focused process in order to facilitate the implementation of the new supply chain process (i.e. mass customization) with sensitivity to time‐to‐market demands.

The case study method was used with three non‐competing apparel firms. Survey instruments and focus group feedback were utilized, which allowed the researchers to collect in‐depth information about the apparel product development process, often considered proprietary in many industries.

Product development activities in the lengthy apparel product development process were realigned with many activities being ranked as early or middle activities. This realignment into a compressed and nearly simultaneous process supports activities that must be done early and often simultaneously rather than late to support a mass customization strategy.

The case study approach and apparel‐oriented sample reduces generalizability of findings; however, realignment of activities and provided operational information encourage future research to document the findings for apparel and other industries.

Suggested movement of activities can be used as a guide for designers and manufacturers when trying to improve their product development process.

The paper provides needed detailed or operational information about implementation of mass customization in the apparel industry.