Search results

The purpose of this paper is to highlight the own brand strategies undertaken by Japanese apparel manufacturers, and illuminate the characteristics of those apparel manufacturers who adopt the SPA business model.

A questionnaire survey was sent to 4,417 apparel manufacturers in Japan of which a total of 1,211 were deemed usable (response rate of 27.47 percent). Logit regression analysis was then employed to identify factors affecting the own brand strategies adopted by Japanese apparel manufacturers.

The main findings are as follows: apparel manufacturers having access to external designers, and who collect information relating to consumer needs for production planning tend to have their own brands; apparel manufacturers located in Tokyo have added benefits associated with launching their own brands than those located in other cities; the size of the company behind the brand development is insignificant; and therefore, SME apparel manufacturers have equal opportunities in developing their own brands, which could flourish in the future.

The present study is limited in that it focuses solely on exogenous factors. Strategic decision-making processes, typical of the distribution structures of apparel industries, influence the apparel relationship between retailers, wholesalers, and manufacturers. Thus, the distribution structure and the relationships require further investigation studies.

Because of a lack of published data, no empirical studies investigating the effectiveness of own brand strategies developed by Japanese apparel manufacturers currently exist. The present study aims to address this by conducting questionnaire surveys with all Japanese apparel manufacturers and then using logit regression analysis, identify the primary factors influencing own brand strategy. This study clarifies the situation regarding the survival of SMEs in the apparel market, considering only those apparel manufacturers who intend to launch their own brands.

This paper aims to examine how Chinese apparel retailers manage their production outsourcing risks and why they elect to manage those risks in a particular manner.

The investigation used the case study approach to explore factors driving two Chinese apparel retailers operating in different market environments to manage their production outsourcing risks.

The selection of production outsourcing risk management strategies hinges on what apparel retailers view as the most important value their products provide to customers. Product values were linked to specific product characteristics as well as the market environment in which the apparel retailers operated. The retailer that regarded product quality as a key value driver was found to place emphasis on manufacturer selection and use of a formal contract for process control. The retailer that viewed newness and variety as a value driver opted to cultivate a strong, committed business relationship based on Guanxi to achieve speed‐to‐market.

As a case study research, the findings of this study have their limitations in generalisability. Given that one of the retailers did not invoke Guanxi to cultivate a long‐term business relationship with its outsourced manufacturers, the role of Guanxi in outsourcing risk management in China deserves further exploration, as businesses in China become more globalised.

This study grounds mainstream outsourcing strategy literature on operational practice through case studies. It highlights the influence of both product characteristics and market environment in dictating the choice of outsourcing risk management strategies in apparel manufacturing.

The study views outsourcing risk management from the perspective of minimizing outsourcing failures, rather than achieving outsourcing success. It reveals that risk management behavior of apparel retailers was linked to the notion of value protection, which varied according to what they considered as their principal product value drivers.

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.

According to literature research and conversations with apparel manufacturers' specialists, there is not any common analytic method for demand forecasting in apparel industry and to the authors' knowledge, there is not adequate number of study in literature to forecast the demand with adaptive network-based fuzzy inference system (ANFIS) for apparel manufacturers. The purpose of this paper is constructing an effective demand forecasting system for apparel manufacturers.

The ANFIS is used forecasting the demand for apparel manufacturers.

The results of the proposed study showed that an ANFIS-based demand forecasting system can help apparel manufacturers to forecast demand accurately, effectively and simply.

ANFIS is a new technique for demand forecasting, combines the learning capability of the neural networks and the generalization capability of the fuzzy logic. In this study, the demand is forecasted in terms of apparel manufacturers by using ANFIS. The input and output criteria are determined based on apparel manufacturers' requirements and via literature research and the forecasting horizon is about one month. The study includes the real-life application of the proposed system, and the proposed system is tested by using real demand values for apparel manufacturers.

The purpose of this paper is to identify and prioritise social responsible mechanisms in apparel supply chains to extend social responsibility from large retailers in developed countries to producers in developing nations.

A framework that consists of supplier qualification and supplier relational mechanisms as two socially responsible mechanisms, with five factors and 18 dimensions is proposed. To prioritise the dimensions, analytic hierarchy process is employed by using a case study methodology of a major Australian retailer sourcing from Bangladesh manufacturers.

Results indicate that at the mechanism level, both retailer and manufacturers perceive qualification of manufacturer as by far the most critical element compared to the relational mechanism. However, substantial differences exist at the factor level; namely, that the social factor is critical for the retailer, whereas the economic factor is critical for the manufacturer. Within the relational mechanism, evaluation helps retailers to enforce social responsibility, while manufacturers believe collaboration helps.

The major limitation of this study is the generalisation of the findings. The results obtained by focusing on a particular context in the Australian retail sector importing from Bangladesh, may not be applicable to other nations.

By highlighting the difference of opinion, this study assists managers in developing guidelines to better understand the socially responsible mechanisms in the retailer-manufacturer dyadic relationship and to propose strategies to address the differences.

This study advances the literature on inter-organisational relationship to retailer-manufacturer dyad for the implementation of social responsibility by including supplier qualification along with supplier relational mechanism.

The purpose of this study was to explore the impact of business type upon the adoption process for quick response (QR) technologies in the apparel industry. Using Rogers’ (1983) innovation decision process model as our conceptual basis, we empirically investigated three stages of that process as it pertains to QR adoption: persuasion, decision, and implementation. In our study of 103 US apparel manufacturers, we found business type to impact significantly the firms’ perceptions of benefits to be derived from QR. The perceptions of these benefits, in turn, affected the apparel manufacturers’ adoption of a QR strategy which, in turn, influenced their use of various QR technologies.

Past research has shown that consumers believe there is a strong relationship between price and quality; they also believe there is a strong relationship between brand and quality. Therefore, when comparing similar pieces of apparel, items with a designer brand or a higher price are perceived, by most customers, to be of higher quality. The purpose of this study was to compare the pricing and quality of identical designer merchandise sold in department stores and manufacturers’ outlet stores. The researchers found no significant differences in the quality of apparel sold in the two retail formats; however, there was a significant difference in the price. The department store merchandise was 31 per cent higher in price than the outlet store merchandise.

The purpose of this paper is to confirm empirically the existence of a US apparel import intermediary (AII) identity crisis, and to provide a detailed descriptive profile of AIIs, differentiating them from apparel firms not primarily engaged in importing activities.

A survey study was conducted using a national sample of US AIIs. Based on these firms' executives' responses, a firm identity issue was analyzed and a detailed profile of these firms' business characteristics was developed, using frequency comparisons.

The study confirmed that US AIIs are currently experiencing an identity crisis, as nearly half of the study respondents misclassified themselves as apparel manufacturers or other business types, suggesting a significant distortion in US Economic Census data. The study also provided a descriptive profile of US AIIs, including geographic location and other business operation characteristics.

Three fourths of the survey respondents were located in the state of New York. Whether most US AIIs truly reside in New York cannot be known with certainty. Generalization of the study findings to a greater population should be cautious.

Confirmation of an AII identity crisis suggests both aggregate and individual firm‐level impacts on import activities. The study offers a new term, “intermediary”, to replace the US Census Bureau term “wholesaler” to accurately reflect the industry's transformation.

The study provides the first empirical support for a US AII identity crisis. The detailed profile of US AIIs offers industry data not available prior to this study.

The redesign of a product supply chain, in terms of production, cost and delivery capabilities can be effectively accomplished by mapping, analyzing and simulating the changes in the supply chain prior to implementation. The case being discussed pertains to the apparel industry in the USA. The beginning of 2005 marked the end of a 30‐year old quota on the apparel market in the USA. This has led many western apparel manufacturers to outsource their production to low‐labor cost countries. This in‐turn has led to increased customer lead‐times. This paper aims to discuss how the implementation of proper IT systems and supply chain measures can reduce lead‐times and also reduce total cost.

An integrated approach is utilized to model the impact of apparel outsourcing added to a US apparel producer supply chain by studying the process map, data analysis, and simulation of the supply chain using Visio, Excel and @Risk simulation software. Using Monte Carlo simulation, the hypotheses on responsiveness and relative costs were tested with and without the outsourcing feature in the US apparel producer supply chain.

The cost savings through outsourcing in the low‐cost labor countries in Asia for the US apparel producer supply chain can be huge and the lead‐time is quite substantial. Thus, outsourcing is not a viable solution for meeting short‐term market demands. However, for large seasonal orders, outsourcing could be an enormous cost‐saver. The lead‐time of the US apparel producer supply chain could be improved if certain controllable factors such as order processing could be made more efficient.

Recent studies by Acaccia, Conte, Maina and Michelini as well as the Leadership for European Apparel Production From Research along Original Guidelines (LEAPFROG, www.leapfrog‐eu.org/), were reviewed. However, no recent study that uses Monte Carlo simulation to measure the supply chain in the apparel market for the USA was traceable in the existing literature except one done by Naylor, Burdick and Sasser at Duke University in 1967. The process modeling of the US apparel producer supply chain with the outsourcing feature will be a useful decision analysis tool. With more data and better understanding of the industry, this simulation model can be easily expanded to obtain a more in depth understanding of any US apparel producer supply chain with an outsourcing capability. Even with making some realistic assumptions in the model, one can easily see the potential benefits of outsourcing. The study found that the customer lead‐time was averaging around 57 days at three‐fourths of the original cost with the minimum customer lead‐time being 41 days. Improved IT and logistics capabilities can minimize the variability recognized in major components of customer lead‐time, such as ocean freight transportation time, order processing time and manufacturing time.

The contribution of the research results from the apparel industry application, where simulation studies of this kind have recently not been executed for a US apparel manufacturer. It also showcases an innovative approach in analyzing outsourcing strategies for a US apparel producer supply chain. The study makes a business case that process improvement can be effectively accomplished with an integrated approach of using widely available inexpensive and user‐friendly computer‐based tools.

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.