COMPETITIVE ANALYSIS OF U.S. FOOD PROCESSING PLANTS

This paper presents a model-based approach for competitive analysis of manufacturing plants in the U. S. food processing industry. As part of this approach, plant competitiveness is measured using Operational Competitiveness Ratings Analysis (OCRA) -- a new non-parametric method of computing relative inefficiency. Drivers of competitiveness are identified in terms of policies related to plant structure and infrastructure. Policies related to plant structure are those decisions that are related with "bricks and mortar" and have long term implications, such as decisions related to plant size and capacity. Policies related to plant infrastructure are decisions related to how the " bricks and mortar" are used. These policies are typically under the direct control of the operations managers and have a short-term orientation, such as decisions related to equipment, quality, inventory, workforce and confusion-engendering activities (e.g. new product introductions and product variety). The empirical analysis is based on detailed cross-sectional data on 20 processed food manufacturing plants. With respect to plant structure, the results suggest that small sized food processing plants are competitive, and both capacity underutilization and overutilization are detrimental to plant competitiveness. Among the significant results with respect to plant infrastructure, equipment maintenance, quality management programs, packaging supplies inventory, workforce training and product variety are positively associated with plant competitiveness. The results also suggest that introduction of new products disrupts plant operations, at least in the short run, and is negatively associated with plant competitiveness.Agribusiness,

COMPETITIVE ANALYSIS OF U.S. FOOD PROCESSING PLANTS

This paper presents a model-based approach for competitive analysis of manufacturing plants in the U. S. food processing industry. As part of this approach, plant competitiveness is measured using Operational Competitiveness Ratings Analysis (OCRA) -- a new non-parametric method of computing relative inefficiency. Drivers of competitiveness are identified in terms of policies related to plant structure and infrastructure. Policies related to plant structure are those decisions that are related with "bricks and mortar" and have long term implications, such as decisions related to plant size and capacity. Policies related to plant infrastructure are decisions related to how the " bricks and mortar" are used. These policies are typically under the direct control of the operations managers and have a short-term orientation, such as decisions related to equipment, quality, inventory, workforce and confusion-engendering activities (e.g. new product introductions and product variety). The empirical analysis is based on detailed cross-sectional data on 20 processed food manufacturing plants. With respect to plant structure, the results suggest that small sized food processing plants are competitive, and both capacity underutilization and overutilization are detrimental to plant competitiveness. Among the significant results with respect to plant infrastructure, equipment maintenance, quality management programs, packaging supplies inventory, workforce training and product variety are positively associated with plant competitiveness. The results also suggest that introduction of new products disrupts plant operations, at least in the short run, and is negatively associated with plant competitiveness

COMPETITIVE ANALYSIS OF U.S. FOOD PROCESSING PLANTS

This paper presents a model-based approach for competitive analysis of manufacturing plants in the U. S. food processing industry. As part of this approach, plant competitiveness is measured using Operational Competitiveness Ratings Analysis (OCRA) -- a new non-parametric method of computing relative inefficiency. Drivers of competitiveness are identified in terms of policies related to plant structure and infrastructure. Policies related to plant structure are those decisions that are related with "bricks and mortar" and have long term implications, such as decisions related to plant size and capacity. Policies related to plant infrastructure are decisions related to how the " bricks and mortar" are used. These policies are typically under the direct control of the operations managers and have a short-term orientation, such as decisions related to equipment, quality, inventory, workforce and confusion-engendering activities (e.g. new product introductions and product variety). The empirical analysis is based on detailed cross-sectional data on 20 processed food manufacturing plants. With respect to plant structure, the results suggest that small sized food processing plants are competitive, and both capacity underutilization and overutilization are detrimental to plant competitiveness. Among the significant results with respect to plant infrastructure, equipment maintenance, quality management programs, packaging supplies inventory, workforce training and product variety are positively associated with plant competitiveness. The results also suggest that introduction of new products disrupts plant operations, at least in the short run, and is negatively associated with plant competitiveness.

Strategic Resource Dynamics of Manufacturing Firms

We conceptualize strategic decision-making processes within a manufacturing firm as streams of resources allocated to short- and long-term changes. The analogous ecological model, referred to as the Lotka-Volterra model, captures this dynamic tension between decisions made by the firm and its manufacturing operations. This representation leads to evolutionarily stable manufacturing strategies (ESMSs), which contribute to a firm's competitive advantage in different ways. Using a random sample of 30 firms from the U.S. semiconductor industry, we estimate parameters of the model and arrive at four ESMSs or strategic manufacturing groups that reflect theoretically and empirically distinctive adaptation patterns through their dynamic resource allocations. We observe that a majority of the firms were classified in one of the four groups, with relatively fewer firms in the other three. Notably, our classification based on ecology models agrees well with taxonomies in manufacturing and business strategy theory. Furthermore, our analysis shows significant differences among manufacturing practices and competitive capabilities of the four strategic groups. Managerially, these insights could provide the foundation to implement strategic changes that enable firms to leapfrog from one ESMS to another. This study also paves the way for development of a meso theory of the dynamics of manufacturing strategy.manufacturing strategy, resources, dynamics, competitive capabilities, ecology, complexity