Cooperative (co-op) advertising is an important instrument for aligning manufacturer and retailer decisions in supply chains. In this, the manufacturer announces a co-op advertising policy, i.e., a participation rate that specifies the percentage of the retailer's advertising expenditure that it will provide. In addition, it also announces the wholesale price. In response, the retailer chooses its optimal advertising and pricing policies. We model this supply chain problem as a stochastic Stackelberg differential game whose dynamics follows Sethi's stochastic sales-advertising model. We obtain the condition when offering co-op advertising is optimal for the manufacturer. We provide in feedback form the optimal advertising and pricing policies for the manufacturer and the retailer. We contrast the results with the advertising and price decisions of the vertically integrated channel, and suggest a method for coordinating the channel.

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This paper analyzes the capability of Japanese and European multinational companies (MNCs) to absorb technological knowledge from the United States through their R&D operation in the US. Employing the notion of “absorptive capacity” [10], we define the capability of a firm to absorb technological knowledge from abroad as “absorptive capability (AC).” We examine the components of AC and their inter-relationships using patent and sales data in the context of R&D management of Japanese and European MNCs at home and in the US.

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This paper provides a game-theoretic explanation for the puzzling behavior of large firms (incumbents) who, while sponsoring university research labs, require all inventions generated by the sponsored labs be licensed openly on a purely non-exclusive basis. Under certain conditions, this results in an intellectual property “commons” with the consequence that no firm has the incentive to innovate, despite the potential profitability of the new technology. The strategy of spoiling incentives to innovate by eliminating exclusive intellectual property rights - the strategy of the commons - is motivated by a fear of cannibalization and supported by a credible threat. The author shows that the degree of cannibalization to which the new technology exposes the old market is responsible for this market failure and the author characterizes the sub-game perfect equilibrium in which “the strategy of the commons” is played. Within this framework welfare implications as well as strategy and policy issues are also investigated.

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Although firms must upgrade their manufacturing capabilities to remain competitive over time, successful process improvement implementation is uncertain.  Furthermore, several internal characteristics such as the firm’s size and level of knowledge affect the magnitude and the certainty of the benefits realized.  A comprehensive stochastic model is introduced which yields managerial insights concerning the impact of firm size on appropriate process improvement and knowledge acquisition strategies.  Analytic results are derived linking firm size to relevant cost and efficiency advantages.  Manufacturing managers can utilize the model to tailor appropriate process improvement and knowledge acquisition strategies for their firms.

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Time-based strategy is becoming an important weapon to achieve competitive advantages in the current environment of fast-changing technology and customer requirements. Speed-to-market has become the mantra of both researchers and practitioners in new product development (NPD), but there is limited empirical research and inconsistent or conflicting findings on the relationship between speed-to-market and product performance. A more important question is whether faster is always better. In a study of 692 NPD projects, we examined the relationship between speed-to-market and new product success (NPS) under conditions of different uncertainties. Our results indicate that speed-to-market is generally positively associated with overall project success, but market turbulence moderates the direct effect. Speed-to-market is less important to NPS under conditions of low market turbulence. One important implication is that it is necessary to execute time-based strategy in a fast-changing market but not in an existing and stable marketing. Our results also suggest technological uncertainty does not affect the speed-success relationship. The limitations, and future research related to these results are discussed.

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When designing a new product or service, its developers must balance the expected profit of improving the design against the costs and time requirements of doing so. We propose to quantify this tradeoff by modeling a latter stage of development, prototyping, as a search process. The decision maker choose how many prototypes to build then observe the projected profit of each. Multiple parallel prototypes are modeled as n random draws from a continuous probability distribution. The model balances the cost of building and testing the parallel prototypes against improvements in expected profits. We also study the option to abandon the project when even the best prototype generates losses. Further, we investigate prototyping decisions for products consisting of independent components that must be compatible in order for the total system to be profitable. Process design also considers alternatives for improving particular process steps but is complicated by the need for compatibility between these improved process steps.

The paper’s contributions include closed-form solutions for the case of Uniformly and Gumbel-distributed profits, insights into the benefits of conducting multiple experiments in parallel versus sequentially, and the valuation of options to abandon projects. It develops insight into the interactions between multiple components of a complex product or manufacturing process as they affect prototyping policy.
 

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This paper presents the research on the development of a new concept and methodology called Technology Development Envelope (TDE). TDE approach is applied for identifying the optimum path in developing a technology roadmap in which technology strategies and business strategies are combined. TDE allows the executive level decision makers in corporations, as well as the policy level decision makers in governments to incorporate disruptive technologies and radical innovations in the development of technology strategies. The combination of Delphi method and hierarchical decision (AHP) is used as a foundation for building the TDE concept. The judgments from technology developers and technology implementers are utilized in the process to assure that the technology strategies are in full support of corporate goals and objectives.

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The Integrated Circuit (IC) manufacturing technologies have been evolving continuously since their invention. The semiconductor foundry industry, whose core business is IC manufacturing, is greatly influenced and shaped by the flow of these newly arriving technologies. This research applies the Analytic Hierarchy Process (AHP) model to evaluate the strategic impact of new IC manufacturing technologies in the semiconductor foundry industry in Taiwan where the industry is in a global leadership position. The model incorporates the levels of overall competitive success, competitive goals, technology strategies and emerging technologies. Relative impacts of elements in one level on its upper level are obtained by utilizing the inputs from experts of Taiwan’s semiconductor foundry industry. The results show the relative importance of competitive goals in the semiconductor foundry industry. Each competitive goal is aligned to the technology strategies as well as emerging technologies in the prioritized orders.

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Many companies lack efficient management of the early phases of new product development (NPD) - the so-called fuzzy front end (FFE). Rather than on structured methods, decision makers rely on “gut–feel” or “guessing”. In an attempt to “educate the guess,” this paper discusses the activities and challenges of the FFE, as well as strategies to manage them successfully. It then briefly presents traditional and recent approaches to front-end management support. Based on the identified strengths and weaknesses of existing front-end solutions, the framework of a new management support system for the FFE is presented. Conceptually, the system is based on psychological findings about the process of action-regulation in complex decision environments. Methodologically, it uses Fuzzy Cognitive Maps (FCM) for modeling and simulation.

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The paper empirically concludes that a key to success for heavy users of advanced manufacturing technology is to improve the infrastructure (worker empowerment, training, self-managed teams, quality leadership and inter-functional design teams), to emphasize decentralized preventive maintenance, and to develop a manufacturing strategy where flexibility is an important capability.

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The purpose of this study is to explore an alternative mechanism of problem solving that focuses on broadcasting problems to diverse and peripheral problem solvers, what I call broadcast search. Broadcasting problems is a radical departure from traditional problem solving as it involve problem holders engaging in as little problem-solving as possible - instead they attempt to interest a heterogeneous set of external actors in creating solutions to internal problems. Analysis of 166 previously unsolved science problems, originating from the R&D labs of 26 firms, revealed a 29.5% resolution rate via broadcast search. The probability of a problem being solved was significantly correlated with the heterogeneity in the scientific interests of the solvers submitting solutions and their relative specialization. Broadcast search also appears to be an economically efficient problem solving mechanism. It involves low costs for solution seekers relative to the costs of internal R&D. Most of the solvers based their submissions, partially or fully, on previously developed solutions from their own and/or someone else’s work, implying an efficient re-use and transformation of existing knowledge and solutions.

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Building on emerging research on knowledge partitioning and an information processing view of product development, this study examines the impact of task uncertainty on the knowledge boundary between manufacturers and suppliers in automobile industry. Using successfully applied patents in automobile emission control technologies from 1970 to 1998, this research shows that manufacturers expand their inhouse R&D capabilities beyond architectural knowledge and into component innovation whenever they encountered task uncertainties. Moreover, and unlike what was anticipated, manufacturers’ endeavor in building up inhouse component innovation was shown to increase over time, indicating a growing importance of component knowledge for manufacturers in times of task uncertainties, even after the establishment of dominant designs. This study also provides a large scale empirical test for the theoretical claims that effective knowledge management for both architectural and component knowledge is a key factor influencing firms’ competitiveness in the inter-firm product developments.

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We introduce a new formulation of the problem of project selection and budget allocation for R&D portfolios. Due to R&D budget constraints and limited resources, firms are often forced to select a subset of all potential idea/products to carry on the development process. In the formulation presented we make a distinction between budget constraints during the development phase and the commercialization phase by arguing that the latter constraints are not hard constraints. Firms that succeed in developing promising and breakthrough products have little difficulty in securing resources for their commercialization. The portfolio selection at the commercialization phase therefore can appropriately be treated as an instance of selection among a set of financial instruments and the rich theory of financial portfolio formation can be utilized. Optimal selection of projects at the development phase, on the other hand, needs to be performed with the optimal selection at the commercialization phase taken into account. Following this line of argument, we formulate a two stage optimal project selection and budget allocation problem. Properties of the solution and the implications of adopting this formulation are discussed. Project interdependencies at both stages of development and commercialization are considered and illustrated via examples.

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Multiparty international strategic alliances are becoming popular vehicles through which firms access resources, share risk, and learn. They are particularly useful in technology-based industries where products are becoming more complex and risk of failure is high. However, firms are profit maximizing actors who may behave opportunistically or defect in order to gain a larger share of the returns. This paper argues that power and interdependence between members, and between the firm and the alliance are key to determining a member’s capability to act against its partners’ or alliance’s interests. The more powerful and less dependent the firm, the greater its freedom to act. The case of Ballard’s alliance with DaimlerChrysler and Ford finds that alliances “construct” interdependence to balance the asymmetries in their relationships and tie the firms more closely together.

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Technological forecasting is premised on a certain orderliness of the innovation process. Myriad studies of technological substitution, diffusion, and transfer processes have yielded conceptual models of what matters for successful innovation. Yet most technological forecasts key on limited empirical measures quite divorced from those innovation process models. We glean a number of concepts from various innovation models, then present an array of bibliometric measures that offer promise of operationalizing these concepts. Judicious combination of such bibliometrics with other forms of evidence offers an enriched form of technological forecasting that we name “innovation forecasting.” This provides a good means to combine technological trends, mapping of technological interdependencies, and competitive intelligence to produce a viable forecast. We illustrate by assessing prospects for ceramic engine technologies.

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A model based on information theory, which allows technology managers to choose the optimal strategies for yield management in the semiconductor industry, is presented. The knowledge extraction rate per experimentation cycle and knowledge extraction rate per unit time serve as benchmarking metrics for yield learning. They enable managers to make objective comparisons of apparently unrelated technologies. Combinations of four yield analysis tools -- electrical testing, automatic defect classification, spatial signature analysis and wafer position analysis -- are examined in detail to determine an optimal yield management strategy for both the R&D and volume production environments.

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O.Ugur Yildirim, Yeditepe University, Istanbul, Turkey
Co-Authors: A. Nuri Basoglu, Bogazici University, Turkey
 

Technology Processes Management Capability Profiles Model (TPMCPM) integrates normative, strategic, and operational technology management levels with technology management subprocesses (identification, selection, acquisition, exploitation, protection, and abandonment of technology). This research aims to assess technology management capabilities and draw capability profiles of the machine manufacturing industry in Turkey.

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When a make-to-order manufacturing company commits a delivery due date for an order, we call it a commit-to-delivery business mode. In this mode, the manufacturing company is responsible for the shipping cost and selecting a shipping mode which is usually provided by a third party logistics company. Generally, shipping cost is higher when the selected shipping mode requires shorter shipping time. How should a company schedule production in production lines for all accepted orders so that the company can leave enough shipping time for orders to take slow shipping modes to reduce the shipping cost? We study the production and transportation integration technology for a make-to-order manufacturing company with a commit-todelivery business mode. In the distribution scenario where partial delivery is allowed, we provide an optimal production schedule which minimizes the total shipping costs for all finished orders. When partial delivery is not allowed, we provide a near-optimal heuristic algorithm which is proved to be efficient and effective by numerical tests.

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