Quick Response Adoption in the Apparel Manufacturing Industry: competitive advantage of innovation

In recent years, off-shore apparel manufacturers have significantly eroded the U.S. market share of domestic firms. For example, whereas the dollar value of apparel imports almost doubled between 1985 and 1992, accounting for 50 percent of U.S. retail sales, the number of people employed by U.S. apparel manufacturers declined almost 20 percent from 1980 to 1992 (Barrett, Ramey, and Ostroff 1996; U.S. Bureau of the Census 1993). The apparel manufacturing industry is especially vulnerable to off-shore competition because historically it has been comprised primarily of small and medium-size firms (Hunter 1989). Such firms, especially those of small size, often lack the resources and capital that make it possible to compete on a broader scale. This circumstance is paradoxical in that traditionally the flexibility that allowed small firms to respond quickly to fashion change was considered a competitive advantage rather than a weakness. Without the resources to compete, however, flexibility is inconsequential. A business can gain sustainable competitive advantage by innovations in technology or concepts as well as in products. Quick Response (QR), a program developed by textile and apparel manufacturers and retailers around 1985 as a way to cope with problems challenging the apparel industry, uses a combination of strategies to reduce inventory levels, improve merchandise quality, increase worker productivity, increase stock turnover, and reduce merchandise markdowns and inventory costs (Kurt Salmon Associates 1990). Fundamentally, QR is a way to gather information about consumer preferences and to reflect them in production decisions in a timely manner. To comply with consumers' needs, QR relies on sales data. Through computerized information systems, sales data are transmitted and transformed as useful information that reveals consumers' preferences and reactions, and decisions are then made promptly to respond to what consumers want. With QR, cooperative relationships are established among textile mills, apparel manufacturers, and retailers to allow faster movement of information and products from design to retail sale. However, while Acs and Audretsch (1993) have suggested that small and new enterprises can make important contributions to innovation, Davig anti Brown (1992) have indicated that small manufacturing firms focus more on operations than on marketing when developing firm strategies. This suggests that the use of QR strategies relative to manufacturing or marketing may differ among small, medium-size, and large apparel manufacturing firms. This is of particular interest since small (fewer than 50 employees) and medium-size (50 to 250 employees) firms comprise the majority of U.S. apparel manufacturers, although large apparel firms account for a disproportionate share of the total volume of apparel shipments (U.S. Bureau of the Census 1995; Ko 1993; Hunter 1989). An examination of QR adoption by small, medium-size, and large apparel manufacturers might shed light on whether QR strategies are perceived to sustain and increase competitive advantage for small apparel manufacturing firms. Theoretical Framework: Diffusion of Innovation The theoretical framework of this study is based on diffusion of innovation, a process that communicates a change - a new object, concept, or technology - to members of a social system over a period of time (Rogers 1983). According to Mahajan, Muller, and Bass (1990), the diffusion process includes four key elements: innovation, communication channels, time, and social systems. For this study, the change or innovation is QR and the social system is the apparel manufacturing industry. According to Rogers (1983), the diffusion process assumes that within a social system an innovation is introduced, communicated, evaluated, and consequently either adopted or rejected. In earlier diffusion studies related to this topic, researchers examined how certain variables - characteristics of the adopters, perceived attributes of an innovation, and communication channels (by stages) in the innovation-adoption decision process - affected the adoption process (Rogers 1983). …