We extend previous work evaluating the quality versus time-to-market trade-off for a single product generation to the case of multiple generations. While a single generation framework is appropriate when either the technology is not extendable or when additional launch costs outweigh benefits, we find that it is important to recognize whether a technology is extendable and explicitly consider the potential for multiple generations. We evaluate the factors determining optimal development-cycle length and intensity using a forward-looking model that allows for multiple product generations. Comparisons are made with restricted versions of the model that reflect pure single generation and sequential single generation approaches. Against an active competitor, the multiple generation approach is much more profitable, with the greatest differences in fast-moving industries. More total time is spent in development when a multiple generation model is used. Further, this time is dedicated to the more frequent introduction of improved product generations---a "rapid inch-up" strategy---resulting in more, higher quality products over time. Factors affecting optimal time-to-market differ substantially for the single versus multiple generation approaches. A key difference is that faster rates of quality improvement lead to longer development cycles for the single and sequential single generation models, but shorter cycles with the forward-looking multiple generation model. With a single generation, variable costs have the biggest impact on cycle length (higher costs shorten cycles), but with multiple generations, fixed costs have the biggest impact on cycle length (higher costs lead to longer cycles).New Product Development, Development-Cycle Time, Development Intensity
A critical decision facing firms across industries is the selection of a mix of products to offer in the marketplace. Both in practice and in the academic literature. the product line design problem has typically been considered from a marketing perspective, with a focus on how alternative sets of products interact and compete in the marketplace. The operational implications of product line decisions have been largely ignored, even while the importance and complexity of interactions among products in the manufacturing environment increase with broadening product lines. Furthermore. consideration of manufacturing synergies among products in product line design is increasingly beneficial given efforts in many industries to improve co-ordination of manufacturing activities across products. In this work we examine the benefits of integrating marketing implications of product mix with more detailed manufacturing cost implications. Traditional product line models are extended to capture both individual product costs and relevant cost interactions among products. The relevant marketing and manufacturing elements are considered in a mathematical programming formulation that identifies a profit maximizing mix of products. The resulting normative model of the product line design problem is used to generate insights into important cross-functional issues in product line management. Specifically, we examine the impact of alternative manufacturing environment characteristics on the composition of the optimal product line.
Interactions with managers in the automobile industry indicate that efforts to bring potentially profitable new technologies into production are often frustrated by the traditional unit cost‐based approach that is used for evaluating new technologies. Opportunities for timely introduction of valuable or even preemptive technologies can be missed because unit cost comparisons, typically applied to a limited set of vehicle configurations with volumes based on current demand figures, invariably favor incumbent over new technologies. In this research, we develop a more complete technology adoption decision model that integrates product mix and technology adoption decisions. Specifically, we recognize that product mix and volume are important variables in determining the cost effectiveness of new technologies, and include in the model customer demand projections that reflect market trends (e.g. growing demand for increasingly sophisticated features and functions in vehicles). Anticipated experience benefits are then applied to the appropriate production volumes to more accurately predict the profit impact of adopting new technologies. The introduction of automotive multiplexing, a technology that is characteristic of current technological advances in the industry, provides a context for considering insights that can be derived from the decision model. Our interaction with a global Tier I automotive systems supplier allowed us to obtain representative cost data and other information relevant to the technology adoption decision.
Global business frequently requires the expatriation and repatriation of managers and skilled workers. Previous research has focused on cultural and demographic factors that lead to success with this process. This study goes beyond the cultural and demographic issues to examine implications of operational and technology‐related factors, including use of standard practices, degree of technical sophistication of operations, and technical orientation of the employee. Our results indicate that the technical sophistication of operations abroad, use of standard practices at home, technical orientation of the individual, and increased responsibility and promotion all positively contribute to expatriate satisfaction. Repatriate satisfaction is primarily influenced by difficulty in finding a suitable position upon relocation home. The technical orientation of the individual, in turn, has important implications for repatriation success. This research identifies important new operational and technology‐related factors that should be considered by global firms in management of their internationally located operations.
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