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We consider a manager who invests in knowledge development of a product and a process design team as well as knowledge transfer between teams throughout a new product development (NPD) [...]

In various industries end-product manufacturers acquire core subsystems from upstream technology provider firms and focus primarily on efficient end-product integration. We examine the strategic interactions between a technology firm that introduces a new subsystem and the respective end-product manufacturers ('integrators'). We analyze how the fraction of end-product functionalities prepackaged into the subsystem impacts the optimal introduction strategy and the relative value appropriation power across the industries. Offering a subsystem that performs many end-product functions has a dual effect on the provider's profits. On the positive side, the provider extracts a higher ease-of-use rent from the integrators because of the easier/cheaper integration. On the negative side, such subsystems may curtail the adopters' ability for competitive differentiation and render adoption less valuable. We discuss the role of subsystem functionality in value appropriation in technology markets, and we highlight the perils of subsystem overintegration. Key words: technology introduction; technology licensing; technological value appropriation; subsystem functionality History: Received February 19, 2009; accepted February 21, 2012, by Kamalini Ramdas, entrepreneurship and innovation. Published online in Articles in Advance November 5, 2012., 1. Introduction Many industries exhibit a trend of disintegration over time. They start off vertically integrated, and gradually they evolve toward a multitier disintegrated structure (Christensen 1994, Christensen et al. [...]

Although managers invest in new technology to improve performance, often the benefits sought are elusive while the costs incurred far exceed expectations. The literature offers insights to help explain this [...]

The first step in transforming strategy from a hopeful statement about the future into an operational reality is to allocate resources to innovation and new product development (NPD) programs in a portfolio. Resource allocation and NPD portfolio decisions often span multiple levels of the organization's hierarchy, leading to questions about how much authority to bestow on managers and how to structure incentives for NPD. In this study, we explore how funding authority and incentives affect a manager's allocation of resources between existing product improvement (relatively incremental projects) and new product development (more radical projects). Funding may be either fixed or variable depending on the extent to which the manager has the authority to use revenue derived from existing product sales to fund NPD efforts. We find that the use of variable funding drives higher effort toward improving existing products and developing new products. However, variable funding has a subtle side effect: it induces the manager to focus on existing product improvement to a greater degree than new product development, and the relative balance in the NPD portfolio shifts toward incremental innovation. In addition, we highlight a substitution effect between explicit incentives (compensation parameters) and implicit incentives (career concerns). Explicit incentives are reduced as career concerns become more salient. Key words: innovation; new product development; authority; incentives; resource allocation; portfolio History: Received November 28, 2006; accepted March 22, 2009, by Christian Terwiesch, guest department editor, technological innovation, product development, and entrepreneurship. Published online in Articles in Advance July 10, 2009., 1. Introduction The question of which innovation programs to pursue is critical to a firm's success and is often cited as a key competitive dimension (Roussel et al. 1991, Wheelwright [...]

A firm's ability to manage its knowledge-based resource capabilities has become increasingly important as a result of performance threats triggered by technology change and intense competition. At the manufacturing plant level, we focus on three repositories of knowledge that drive performance. First, the physical production or information systems represent knowledge embedded in the plant's technical systems. Second, the plant's workforce has knowledge, including diverse scientific information and skills, to effectively operate the technical systems. Third, the firm's managerial systems embody knowledge in the form of goals, reward systems, and control and coordination systems. Taken together, we consider the technical systems, workforce knowledge, and the managerial systems as the plant's knowledge-based resource capability. Two normative models are introduced offering insight on how plant performance is impacted by investments in workforce knowledge (training) or the technical systems (process change). The models explicitly recognize that the outcome of investments in knowledge-based change is uncertain due to factors including technical problems, worker resistance, and limited financial resources. Also, we recognize that workforce knowledge may be deployed to mitigate the outcome uncertainty encountered with process change. Investments in knowledge-based change cannot be fully understood in isolation of the managerial systems. In one model, the plant manager is motivated by an incentive system that rewards the realization of a threshold goal, whereas in the other model the incentive system emphasizes the realization of meeting a particular target goal. We also investigate the impact of the manager's view of uncertainty (her willingness to absorb risk), which is influenced by the managerial systems. Results show that different characterizations of the managerial systems have a profound effect on managerial behavior and plant-level performance. Key words: knowledge-based resource capabilities; process change; workforce training; knowledge management; managerial systems; uncertainty, 1. Introduction In response to performance threats such as those driven by technological change and competition, firms must frequently assess and modify their resource capabilities. Barney (1991) defines a firm's [...]

Forces such as technology change and increased competition provide opportunities and challenges that drive a firm to continuously evaluate and modify its resource capabilities. As a consequence, a firm's process change strategy is of paramount importance for sustained manufacturing success. However, fundamental elements of process change strategy are not well understood. Long term performance benefits associated with potential process change alternatives are often unclear. Moreover, uncertainty exists regarding the actual benefits that may be attained from various types of process change. Critical issues impacting the proper implementation of process change are frequently underestimated or largely ignored. Therefore, despite the improved performance sought, process change often leads to lower productivity, excessive equipment downtime, and deterioration in quality. As the authors review the relevant empirical and normative literature, a framework emerges that characterizes the salient features of a firm's process change strategy. The underlying dynamics of process change are explored and strategies are discussed to reduce the short-term disruption and enhance the long-term gain. In particular, the authors demonstrate the importance of creating and applying knowledge to improve the outcome of process change. They describe managerial actions that can be taken to reduce various sources of uncertainty associated with process change. Moreover, they identify key contributions as well as limitations of the existing normative literature on process change. Insights from the empirical literature are given that both support elements of the existing normative models and provide direction for future normative research. Thus, the authors seek to aid practicing managers and researchers alike to better understand the full scope and implications of process change. Index Terms--Dynamics, implementation and disruption, knowledge management, managerial practice, process change, uncertainty.

A model is introduced to guide a profit maximizing firm in its quest to enhance performance through process change. The key benefit sought from process change is a long term increase in effective capacity. However, realizing success from process change is not trivial. First, while process change may increase effective capacity in the long run, the disruptions during implementation typically reduce short term capacity. Second, competitive forces such as decreasing revenue streams and shrinking product life cycles complicate the implementation of process change. Third, while knowledge may enhance the ultimate benefits derived from process change, the correct timing and means of knowledge creation are difficult to discern. Lastly, a variety of trade-offs must be evaluated when selecting the particular process change to pursue. For example, choices range from hardware and software replacements to modification of manufacturing procedures. The model introduced here explicitly considers both the short term loss due to disruption and the long term gain in effective capacity associated with the process change. In addition, investments in the accumulation of knowledge are investigated for their potential to enhance process change effectiveness. Knowledge is generated from investment in preparation and training (learning-before-doing) and as a by-product of process change (learning-by-doing). Analysis of the model provides managerial recommendations for several key decisions relating to process change implementation including: (i) the selection of an appropriate process change alternative, (ii) the rate and timing for investment in process change, and (iii) the rate and timing for investment in preparation and training. New results are reported reflecting the important relationship between process change and knowledge. For example, we show that under certain conditions, a firm should optimally delay investment in process change until sufficient accumulation of knowledge is achieved. More generally, we identify conditions whereby investment in process change occurs at an increasing rate over time. This result is particularly important since it demonstrates a limitation of the existing literature where process change always occurs at a decreasing rate., 1. Introduction The importance of effectively aligning a firm's manufacturing capabilities with its overall corporate strategy is well established, (see Skinner 1969). Process change is a practical means by which [...]

Companies planning information technology system purchases should consider the needs of the employees who are expected to use the equipment to improve their output. The time lag for training skilled employees to use the new systems and the preferences of those employees should be considered.

A model is presented for the planning and scheduling of production batches in a flexible manufacturing system environment in which setup costs and times are nonnegligible and alternate routings are possible. The formulation is an integer program with a multicommodity flow network structure. A heuristic procedure based on price-directive decomposition using column generation is used to obtain solutions. Numerical experimentation is performed to assess the quality of the heuristic versus optimal solutions, and to determine the impact of routing flexibility on total cost, inventory levels, bottlenecks, capacity utilization, throughput time, number of setups and split lots. Important cost-benefit trade-off implications are shown for the design of flexible manufacturing systems.

: A multiproduct, multiperiod, multistage network model is presented for the planning of ord release and production scheduling in a flexible manufacturing system environment under the existence alternate routings. It is assumed that premanufacturing decisions such as machine grouping and tool loading have been made, so that setup costs and setup times are negligible and can be included in th processing times. The decision process addressed by the model is the disaggregation of weekly produc requirements to daily production requirements, the determination of production batch sizes for each operation of each part type, and the daily assignment of each batch to machine groups given the flexibility of alternate routings. The model also provides the interface and linkage between an MRP component planning system and the shop scheduling system. The model is solved using a price-directiv decomposition technique with column generation. Experimentation is performed with the model for varying problem sizes to determine the impact of shop flexibility on total cost, inventory levels, e of bottlenecks, shop utilization, and the number of setups and split lot production. The results ind important cost-benefit trade-off implications for system design and acquisition. For example, if in setup costs and times are nonnegligible, then it is shown that increasing the routing flexibility of without a parallel decrease in setup costs and times is unlikely to reap significant benefits., A multiproduct, multiperiod, multistage network model can enhance routing flexibility and production scheduling in a flexible manufacturing system. Assuming the existence of altrnate routings and no setup time considerations, this model breaks down weekly production requirements to daily total production needs, sets the daily production quota for each operation of each part type and allocates the production quotas to machine groups given the flexibility of alternate routings.

Rapid changes in technology and intense competition have led to shorter product life cycles in both high-technology industries and industries not commonly regarded as high-technology. As a result of short product life cycles, firms are faced with the challenge of planning for facilities whose useful lives are much longer than the life cycle of any individual product it manufactures. This paper develops a model to analyze the critical trade-offs associated with determining the best level of flexibility for a facility that manufactures a series of high-volume products, sequentially over each product's life cycle. Our analysis considers the benefits associated with more flexible facilities including reduced changeover costs and earlier market entry, versus the higher initial investment and higher production costs typically encountered. Keywords: Capacity planning flexibility; product life cycle, Increasingly shorter production life cycles have reached the point where the life cycles are shorter than the manufacturing facility life cycle. This requires that manufacturing facilities be endowed with the capability to produce other products with the minimum of modifications or costs. A model was developed for the evaluation of the optimum level of production machinery flexibility based on the product life cycle. The model considers other factors such as product values, average production costs, changeover costs and discount rates.

SETHI, SURESH P., GERALD L. THOMPSON. 2000. Optimal Control Theory: Applications to Management Science and Economics, 2nd ed. Kluwer Academic Publishers, Dordrecht, The Netherlands. 528 pp. $135.00. Optimal Control Theory, [...]

Automation incentives include: improved productivity, labor cost reductions, and offsetting a limited manpower supply. Given these incentives, the optimal mix of automation and staffing levels is modeled after examination of long-range productivity goals, wage factors and costs associated with implementing automated processes. The optimization problems are solved using dynamic programming methods.