The Role of Project and Organizational Context in Managing High‐tech R&D Projects

High‐tech organizations often struggle to manage different types of R&D projects. Evidence from research and practice suggests that managers frequently categorize and manage projects based on the extent of change triggered in product, process, technology, and market dimensions. However, this can create challenges in high‐tech organizations. This study investigates how high‐tech organizations manage R&D projects based on their learning goals. First, we argue for the benefits of categorizing R&D projects based on the degree of exploration and exploitation learning goals. A qualitative case study from four high‐tech business units involving 10 R&D projects helps understand the different types of projects based on their learning goals. The case study shows that R&D projects in high‐tech organizations typically fall into three categories based on their learning goals: Radical innovation projects, Incremental innovation projects, and Hybrid projects. Second, we iterate between literature and evidence from our qualitative data to theorize how project context and organizational context affect project performance depending on the type of project. The data for the empirical analysis come from a multilevel survey of 110 R&D projects across 34 high‐tech business units. Results show the importance of designing project and organizational context differently for the three types of R&D projects. Collectively, this study offers a new perspective on how to manage high‐tech R&D projects.     

Investment in Facility Changeover Flexibility for Early Entry into High‐Tech Markets

A model is introduced to analyze the manufacturing‐marketing interface for a firm in a high‐tech industry that produces a series of high‐volume products with short product life cycles on a single facility. The one‐time strategic decision regarding the firm's investment in changeover flexibility establishes the link between market opportunities and manufacturing capabilities. Specifically, the optimal changeover flexibility decision is determined in the context of the firm's market entry strategy for successive product generations, the changeover cost between generations, and the production efficiency of the facility. Moreover, the dynamic pricing policy for each product generation is obtained as a function of the firm's market entry strategy and manufacturing efficiency. Our findings provide insights linking internal manufacturing capabilities with external market forces for the high‐tech and high‐volume manufacturer of products with short life cycles. We show the impact of manufacturing efficiency and a firm's ability to benefit from volume‐based learning on the dynamic pricing policy for each product generation. The results demonstrate the benefits realized by a firm that works with its manufacturing equipment suppliers to develop more efficient and flexible technology. In addition, we explore how opportunities afforded by pioneer advantage enable a firm operating a less efficient facility to realize long term competitive advantage by deploying an earlier market entry strategy.     

Managing Knowledge Creation in High‐Tech R&D Projects: A Multimethod Study

R&D projects in high‐tech organizations bring together diverse knowledge domains to quickly develop new products and processes. The fast‐paced context of high‐tech organizations makes it challenging to create new knowledge and solve complex problems. Managing these R&D projects requires understanding both the mechanisms and the type of knowledge created to achieve project objectives. This research conducts a two‐phased multimethod study to understand knowledge creation in high‐tech R&D projects. The first phase uses qualitative data to develop a theory on knowledge creation in R&D projects. The second phase involves a survey that collects data from R&D projects to test the theory. Results from the case study find that R&D projects benefit from two types of knowledge – objective and intuitive. The case analyses show that intuitive and objective knowledge creation in high‐tech organizations occurs by creating not only diverse but also psychological safe project teams. The large‐scale survey finds that team diversity positively influences objective knowledge creation while psychological safety affects intuitive knowledge creation. Surprisingly, the results show that team diversity negatively affects intuitive knowledge creation. A post hoc analysis takes a more granular look at diversity and shows that different kinds of diversity have different effects on knowledge creation. This helps to better explain how to manage innovation across boundaries. Finally, the analysis shows that both objective and intuitive knowledge influence R&D project performance. Taken together, these results help explain how to manage innovation across functional boundaries to create knowledge and enhance R&D project performance.      

The Effect of Team Leader Characteristics on Learning,Knowledge Application,and Performance of Cross‐Functional New Product Development Teams

This study examines how leadership characteristics in new product development teams affect the learning, knowledge application, and subsequently the performance of these teams. Using data from a study of 229 members from 52 high‐tech new product projects, we empirically demonstrate that team learning has a strong positive effect on the innovativeness and speed to market of the new products. Moreover, a democratic leadership style, initiation of goal structure by the team leader, and his or her position within the organization were positively related to team learning. Managerial implications of these results are discussed.     

Divide and Conquer: Competing with Free Technology Under Network Effects

We study how a commercial firm competes with a free open source product. The market consists of two customer segments with different preferences and is characterized by positive network effects. The commercial firm makes product and pricing decisions to maximize its profit. The open source developers make product decisions to maximize the weighted sum of the segments' consumer surplus, in addition to their intrinsic motivation. The more importance open source developers attach to consumer surplus, the more effort they put into developing software features. Even if consumers do not end up adopting the open source product, it can act as a credible threat to the commercial firm, forcing the firm to lower its prices. If the open source developers' intrinsic motivation is high enough, they will develop software regardless of eventual market dynamics. If the open source product is available first, all participants are better off when the commercial and open source products are compatible. However, if the commercial firm can enter the market first, it can increase its profits and gain market share by being incompatible with its open source competitor, even if customers can later switch at zero cost. This first‐mover advantage does not arise because users are “locked in,” but because the commercial firm deploys a “divide and conquer” strategy to attract early adopters and exploit late adopters. To capitalize on its first‐mover advantage, the commercial firm must increase its development investment to improve its product features.     

The Impact of Outsourced Manufacturing on Timing of Entry in Uncertain Markets

Several firms are interested in manufacturing and selling new products based on a new process technology. Before manufacturing can begin, either these Original Equipment Manufacturers (OEMs), or a Contract Manufacturer (CM) needs to adopt the process technology, i. e., make a capacity investment in it. Due to market uncertainty, the timing of capacity investment is crucial. In such a setting, we investigate how the timing of process adoption, an important determinant of time‐to‐market, is impacted by the make/buy decision. We first characterize the optimal time for process adoption and show that this delay depends on competitive intensity, cost structure and the rate of forecast improvement. Due to differing cost structures, incentives and risks, an OEM and a CM may invest in a new process technology at different times. We show that while there are conditions where outsourced manufacturing can be advantageous for the OEM from a time‐to‐market perspective, there are also cases where the OEM would be disadvantaged. In these cases, the OEM can accelerate process adoption by risk sharing through joint investment. Finally, the right choice of CM is extremely important for an OEM that faces a short time window for product introduction: An efficient CM not only provides low costs but also rapid access to new process technologies, and therefore higher revenues.     

Competing on Time: An Integrated Framework to Optimize Dynamic Time‐to‐Market and Production Decisions

This study develops a comprehensive framework to optimize new product introduction timing and subsequent production decisions faced by a component supplier. Prior to market entry, the supplier performs process design activities, which improve manufacturing yield and the chances of getting qualified for the customer's product. However, a long delay in market entry allows competitors to enter the market and pass the customer's qualification process before the supplier, reducing the supplier's share of the customer's business. After entering the market and if qualified, the supplier also needs to decide how much to produce for a finite planning horizon by considering several factors such as manufacturing yield and stochastic demand, both of which depend on the earlier time‐to‐market decision. To capture this dependency, we develop a sequential, nested, two‐stage decision framework to optimize the time‐to‐market and production decisions in relation to each other. We show that the supplier's optimal market entry and qualification timing decision need to be revised in real time based on the number of qualified competitors at the time of market‐entry decision. We establish the optimality of a threshold policy. Following this policy, at the beginning of each decision epoch, the supplier should optimally stop preparing for qualification and decide whether to enter the market if her order among qualified competitors exceeds a predetermined threshold. We also prove that the supplier's optimal production policy is a state‐dependent, base‐stock policy, which depends on the time‐to‐market and qualification decisions. The proposed framework also enables a firm to quantify how market conditions (such as price and competitor entry behavior) and operating conditions (such as the rate of learning and inventory/production‐related costs) affect time‐to‐market strategy and post‐entry production decisions.     

Manufacturing Practices and Strategy Integration: Effects on Cost Efficiency,Flexibility, and Market‐Based Performance

Manufacturing plant managers have sought performance improvements through implementing best practices discussed in World Class Manufacturing literature. However, our collective understanding of linkages between practices and performance remains incomplete. This study seeks a more complete theory, advancing the idea that strategy integration and enhanced manufacturing capabilities such as cost efficiency and flexibility serve as intermediaries by which practices affect performance. Hypotheses related to this thesis are tested using data from 57 North American manufacturing plants that are past winners and finalists in Industry Week's“America's Best” competition ( Drickhamer, 2001 ). The results suggest that strategy integration plays a strong, central role in the creation of manufacturing cost efficiency and new product flexibility capabilities. Furthermore, strategy integration moderates the influences of product‐process development, supplier relationship management, workforce development, just‐in‐time flow, and process quality management practices on certain manufacturing capabilities. In turn, manufacturing cost efficiency and new product flexibility capabilities mediate the influence of strategy integration on market‐based performance. These findings have implications for practice and for future research.     

The Roles of Worker Expertise,Information Sharing Quality,and Psychological Safety in Manufacturing Process Innovation: An Intellectual Capital Perspective

This paper examines the roles of three elements of intellectual capital in implementing process innovations. Building upon prior literature, we develop a model describing how worker expertise, information sharing quality, and psychological safety work together as elements of the human, structural, and social dimensions of intellectual capital to influence the technical success of manufacturing process innovation (MPI) projects. Results of an analysis of data describing 179 MPI projects in US firms strongly support a multidimensional, process‐oriented view of intellectual capital's effects on MPI project technical performance. We also find that the incrementalness of an MPI project plays a moderating role over the relationship between worker expertise and MPI performance. Our study provides insights on how intellectual capital can be more effectively accumulated in a project environment.     

QUALITY,TECHNOLOGY, AND GLOBAL MANUFACTURING

It has been more than a decade since the quality movement was reborn in U.S. industry, and there is widespread dissatisfaction with the results of some of these programs. At the same time, product and service R&D is on the rise. These trends are incorporated here into an extension of the Utterback-Abernathy model to examine the quality, technology, and performance relationship. Six hundred durable goods firms in 20 countries were surveyed and it was found that technology significantly moderated the association of R&D intensity and total quality management (tqm) with market share, controlling for industry category. In high technology firms, R&D intensity was significantly associated with market share; in low technology firms, tqm was significantly associated with market share. R&D intensity and tqm were significantly and inversely related, while R&D intensity and computer-aided manufacturing (cam) were significantly and directly related.     

Linking CIO–CMO Communication and Product Innovation via Virtual Customer Environment Engagement: A Moderated Mediation Study

Intuitively, we would expect that CIO–CMO communication plays a minimal role in product innovation performance, because product innovation is primarily driven by firms’ market orientation, knowledge of customer needs and cross-functional integration among marketing, R&D and operations management. In a sharp contrast to this perspective, we propose that CIO–CMO communication increases product innovation performance through enhancing virtual customer environment (VCE) engagement. Such proposed effects are supported by two studies with different samples (i.e. MBA alumni in Study 1 and a representative sample in Study 2) and different performance measures (i.e. subjective ratings in Study 1 and objective sales data in Study 2). Furthermore, the effect of CIO–CMO communication on product innovation performance via VCE engagement is contingent upon two situational factors, namely marketing–IT integration policy and market uncertainty. The effect of CIO–CMO communication on product innovation performance via VCE engagement is positive and significant when marketing–IT integration policy is strong or when market uncertainty is high, but not when marketing–IT integration policy is weak or when market uncertainty is low. Theoretical contributions and managerial implications of these findings are discussed, especially on how managers can capitalize on CIO–CMO communication and VCE engagement to enhance the success of new product innovation.     

Managing Cross-Functional Cooperation for New Product Development Success

This article focuses on conditions that make cross-functional cooperation in new product development projects more or less productive. We investigate 40 NPD projects in the consumer electronics and pharmaceuticals industries in which R&D and marketing played key roles. We find that the contributions of cross-functional cooperation to NPD success are contingent on the type of market and technology opportunities being pursued. More specifically, our results suggest that when a project team pursues an opportunity characterized by high levels of technological and market risks, investments in high levels of cross-functional cooperation are warranted to increase NPD success. We do not find evidence that cross-functional cooperation moderates the relationship between the openness of an NPD project towards external information and knowledge and its performance. This suggests that less integrated project teams could achieve similar results as more integrated teams in terms of processing large quantities of information and knowledge without incurring the costs that may stem from high levels of cross-functional cooperation.     

A Risk Analysis Model in Concurrent Engineering Product Development

Concurrent engineering has been widely accepted as a viable strategy for companies to reduce time to market and achieve overall cost savings. This article analyzes various risks and challenges in product development under the concurrent engineering environment. A three‐dimensional early warning approach for product development risk management is proposed by integrating graphical evaluation and review technique (GERT) and failure modes and effects analysis (FMEA). Simulation models are created to solve our proposed concurrent engineering product development risk management model. Solutions lead to identification of key risk controlling points. This article demonstrates the value of our approach to risk analysis as a means to monitor various risks typical in the manufacturing sector. This article has three main contributions. First, we establish a conceptual framework to classify various risks in concurrent engineering (CE) product development (PD). Second, we propose use of existing quantitative approaches for PD risk analysis purposes: GERT, FMEA, and product database management (PDM). Based on quantitative tools, we create our approach for risk management of CE PD and discuss solutions of the models. Third, we demonstrate the value of applying our approach using data from a typical Chinese motor company.     

基于实物期权的研发项目动态投资决策模型

本文基于实物期权理论,针对研发项目阶段性特点,结合博弈论的思想,分析了多个研发项目组成的投资状态组合,构建了研发项目动态选择模型。首先,根据研发项目多阶段的特征,利用孪生证券的思想,基于实物期权理论,建立了项目中止决策准则;在此基础上分析研发项目的投资决策状态,建立了二十五个状态的切换场景;然后通过实际算例对模型进行验证和分析,得出了研发项目投资的影响范围概念图,最终实现两个项目的最优投资决策目标。     

The diffusion of advanced manufacturing technology in multiplant,multidivisional corporations

This study examines several factors which act as significant predictors of successful intra-firm advanced manufacturing technology (AMT) diffusion. Our findings suggest that the following factors positively impact the diffusion process: previously successful AMT implementations, advanced manufacturing centers, AMT workshops, informal networks, simultaneous R&D of products and processes, and the significance of the impact of AMT on operating performance. One factor—cost and time overruns with previous implementation projects—emerged as a deterrent to successful AMT diffusion. Our results also indicate that the use of an outside consultant as a major source of transfer expertise significantly contributes to AMT diffusion success.     

Customer‐Base Concentration and Inventory Efficiencies: Evidence from the Manufacturing Sector

What is the link between customer‐base concentration and inventory efficiencies in the manufacturing sector? Using hand‐collected data from 10‐K Filings, we find that manufacturers with more concentrated customer bases hold fewer inventories for less time and are less likely to end up with excess inventories, as indicated by the lower likelihood and magnitude of inventory write‐downs and reversals. Using disaggregated inventory disclosures, we find that inventory efficiencies primarily flow through the finished goods inventory account, while raw material efficiencies are offset by higher work‐in‐process holdings and longer work‐in‐process cycles. In additional analysis, we document a valuation premium for more concentrated manufacturers after controlling for other firm characteristics, including default risk and cost of capital estimates. We conclude that investors trade off the costs and benefits of relationships with a limited number of major customers and, on balance, consider customer‐base concentration as a net positive for firm valuation. Overall, our study adds to interdisciplinary research in accounting and operations management by shedding new light on the relevance of major customer disclosures for fundamental analysis and valuation in the manufacturing sector.     

Managing Supply Risk for Vertically Differentiated Co‐Products

The manufacturing complexity of many high‐tech products results in a substantial variation in the quality of the units produced. After manufacturing, the units are classified into vertically differentiated products. These products are typically obtained in uncontrollable fractions, leading to mismatches between their demand and supply. We focus on product stockouts due to the supply–demand mismatches. Existing literature suggests that when faced with product stockouts, firms should satisfy all unmet demand of a low‐end product by downgrading excess units of a high‐end product (downward substitution). However, this policy may be suboptimal if it is likely that low‐end customers will substitute with a higher quality product and pay the higher price (upward substitution). In this study, we investigate whether and how much downward substitution firms should perform. We also investigate whether and how much low‐end inventory firms should withhold to strategically divert some low‐end demand to the high‐end product. We first establish the existence of regions of co‐production technology and willingness of customers to substitute upward where firms adopt different substitution/withholding strategies. Then, we develop a managerial framework to determine the optimal selling strategy during the life cycle of technology products as profit margins shrink, manufacturing technology improves, and more capacity becomes available. Consistent trends exist for exogenous and endogenous prices.     

日本制造企业新产品开发过程中模糊前端创新的效果分析

本文对日本制造企业新产品开发(NPD)过程中模糊前端(FFE)创新成功的关键因素进行了大样本分析,开发并构建了FFE创新要素与NPD项目绩效之间的因果关系模型.根据513家日本制造企业NPD项目的调查数据,运用AMOS验证因果关系模型,我们得出两个重要结论:在FFE阶段,技术和市场的不确定性减少越多,NPD项目的效率越高;开发前项目初始规划强度越大,开发过程中市场和技术的不确定性就越少.而且相对服务企业而言,制造企业的管理层更容易做出对降低市场不确定性有重大影响的初始规划.     

How market entry order mediates the influence of firm resources on new product performance

Building from the resource-based view of the firm and the first-mover advantage literature, this paper asserts that the entry order in a new product-market affects how the firm's resources and capabilities influence the product's performance. This proposition is tested on a sample of 136 product launches by Spanish manufacturing firms. The empirical analysis reveals that firms with superior managerial and R&D resources achieve superior new product performance when an early-entry strategy is adopted. Manufacturing resources also contribute positively to the success of new products, but this effect is weakened by the difficulties and inconveniences that firms with advantages in operations face when they attempt to pioneer a new market. The results regarding the influence of marketing resources on new product performance are not conclusive.     

PRODUCT OFFERING,PRICING, AND MAKE‐TO‐STOCK/MAKE‐TO‐ORDER DECISIONS WITH SHARED CAPACITY

In an era of mass customization, many firms continue to expand their product lines to remain competitive. These broader product lines may help to increase market share and may allow higher prices to be charged, but they also cause challenges associated with diseconomies of scope. To investigate this tradeoff, we considered a monopolist who faces demand curves, which for each of its potential products, decline with both price and response time (time to deliver the product). The firm must decide which products to offer, how to price them, whether each should be make‐to‐stock (mts) or make‐to‐order (mto), and how often to produce them. The offered products share a single manufacturing facility. Setup times introduce disceonomies of scope and setup costs introduce economies of scale. We provide motivating problem scenarios, model the monopolist's problem as a non‐linear, integer programming problem, characterize of the optimal policy, develop near‐optimal procedures, and discuss managerial insights.