Firms design products that appeal to consumers and are feasible to produce. The resulting marketing and engineering design goals are driven by consumer preferences and engineering capabilities, two issues that conveniently are addressed in isolation from one another. This convenient isolation, however, typically will not result in optimal product decisions when the two problems are interrelated. A method new to the marketing community, analytical target cascading (ATC), is adopted here to explore such interrelationships and to formalize the process of coordinating marketing and engineering design problems in a way that is proven to yield the joint optimal solution. The ATC model is built atop well-established marketing methodologies, such as conjoint, discrete choice modeling and demand forecasting. The method is demonstrated in the design of dial-readout household scales, using real conjoint choice data and a parametric engineering product design model. Results indicate that the most profitable achievable product can fall short of predictions based on marketing alone but well ahead of what engineering may produce based on original marketing target specifications. A number of extensions can be accomplished

The management of new service development (NSD) has become an important competitive concern in many service industries. However, NSD remains among the least studied and understood topics in the service management literature. As a result, our current understanding of the critical resources and activities to develop new services is inadequate given NSD’s importance as a service competitiveness driver. Until recently, the generally accepted principle behind NSD was that “new services happen ” rather than occurring through formal development processes. Recent efforts to address this debate have been inconclusive. Thus, additional research is needed to validate or discredit the belief that new services happen as a result of intuition, flair, and luck. Relying upon the general distinctions between research exploitation and exploration, this paper describes areas in NSD research that deserve further leveraging and refinement (i.e. exploitation) and identifies areas requiring discovery or new study (i.e. exploration). We discuss the critical substantive and research design issues facing NSD scholars such as defining new services, choice in focusing on the NSD process or performance (or both), and specification of unit of analysis. We also examine what can be exploited from the study of new product development to further understanding of NSD. Finally, we explore one important area for future NSD research exploration: the impact of the Internet on the design

Given the crucial role of process modeling in product development (PD) project management research and practice, and the variety of models proposed in the literature, a survey of the PD process modeling literature is timely and valuable. In this work, we focus on the activity network-based process models that support PD project management and present a comprehensive survey of the literature published in the last decade. To organize our survey, we use a framework based on the

This paper addresses the strategic impact of modular design on the optimal length and price of a differentiatedproduct line. We represent consumer demand with a Bayesian logit model. We also break operations costs into product design and production components. Our analysis shows that reducing product development costs via modular design always makes it attractive to offer greater product variety. However, reducing production costs can sometimes motivate a reduction in variety for a risk-averse producer in a multiple-segment market. We also characterize the impacts of degree of modularity and production cost on price markup and market share. Finally, we show that the optimal product line length is monotonic in risk attitude and the monotonic weak majorization, partial order on product assortment.

Early research on new product development (NPD) has produced descriptive frameworks and models that view the process as a linear system with sequential and discrete stages. More recently, recursive and chaotic frameworks of NPD have been developed, both of which acknowledge that NPD progresses through a series of stages, but with overlaps, feedback loops, and resulting behaviors that resist reductionism and linear analysis. This article extends the linear, recursive, and chaotic frameworks by viewing NPD as a complex adaptive system (CAS) governed by three levels of decision making—in-stage, review, and strategic—and the accompanying decision rules. The research develops and presents propositions that predict how the configuration and organization of NPD decision-making agents will influence the potential for three mutually dependent CAS phenomena: nonlinearity, selforganization, and emergence. Together these phenomena underpin the potential for NPD process adaptability and congruence. To support and to verify the propositions, this study uses comparative case studies, which show that NPD process adaptability occurs and that it is dependent on the number and variety of agents, their corresponding connections and interactions, and the ordering or disordering effect of the decision levels and rules. Thus, the CAS framework developed within this article maintains a fit among descriptive stance, system behavior, and innovation type, as it considers individual NPD processes to be capable of switching or toggling between different behaviors—linear to chaotic—to produce corresponding innovation outputs that range from incremental to radical in accord with market expectations.

This paper presents an exploratory investigation of the Manufacturing/Marketing (hereafter M/M) interface. From the literature and prior empirical work in M/M strategies, we propose a path model for assessing the mediating impact of the M/M interface harmony on M/M morale and business performance. Using two convenience samples of executives, we empirically test the direct and indirect influence of predisposing factors (antecedents) and performance outcomes (consequences) that are expected theoretically to influence or be influenced by M/M interface harmony, which we operationalize as the functions ’ ability to work together. We find that 11 of the 13 hypothesized direct effects are significant at the.012 level or below; and attesting to the mediating influence of the M/M ability to work together, 11 of the 12 indirect effects were significant at the.02 level or below. Increasing the emphasis on either or both of the importance of marketing or manufacturing improves the odds of both functions’ ability to work harmoniously, which in turn impacts M/M morale. Notably, interfunctional harmony appears to have a stronger influence on each function’s morale than the importance

This paper explores the performance of coupled development tasks subject to a deadline constraint by proposing a performance generation model (PGM). The goal of the PGM is to develop insights about optimal strategies (i.e. sequential, concurrent, or overlapped) to manage coupled design tasks that share fixed amount of engineering resources subject to performance and deadline constraints. Model analysis characterizes the solution space for the coupled development problem. The solution space is used to explore the generation of product performance and the associated dynamic forces affecting concurrent development practices. We use these forces to explain conditions under which concurrency is a desirable strategy.

Small and medium enterprises (SMEs) are considered as an engine for economic growth all over the world and especially for developing countries. During the past decade, new product development (NPD) has increasingly been recognized as a critical factor in ensuring the continued survival of SMEs. On the other hand, the rapid rate of market and technological changes has accelerated in the past decade, so this turbulent environment requires new methods and techniques to bring successful new products to the marketplace. Virtual team can be a solution to answer the requested demand. However, literature have shown no significant differences between traditional NPD and virtual NPD in general, whereas NPD in SME’s virtual team has not been systematically investigated in developing countries. This paper aims to bridge this gap by first reviewing the NPD and its relationship with virtuality and then identifies the critical factors of NPD in virtual teams. The statistical method was utilized to perform the required analysis of data from the survey. The results were achieved through factor analysis at the perspective of NPD in some Malaysian and Iranian manufacturing firms (N = 191). The 20 new product development factors were grouped into five higher level constructs. It gives valuable insight and guidelines, which hopefully will help managers of firms in developing countries to consider the main factors in NPD. Key words: Survey findings, new product development, factor analysis, virtual team.

Genome-wide association and linkage analyses of hemostatic factors and hematological phenotypes in the Framingham Heart

Highly regulated industries such as pharmaceuticals and agrochemicals face the challenge of maintaining a 0continuous stream of new products. This is difficult because of low probabilities of technical success, high development costs, uncertain market impact, a scarcity of good new product ideas, and limited human and capital resources available to develop them. The problem of evaluating and selecting which new products to develop and then of sequencing or of scheduling them is complicated further by the presence of dependencies between products both in the market place and in the development process itself. This study proposes a portfolio management approach that selects a sequence of projects, which maximizes the expected economic returns at an acceptable level of risk for a given level of resources in a new product development pipeline. A probabilistic network model of distinct activities is used to capture all the activities and resources required in the ‘‘process’ ’ of developing a new drug. A prioritization scheme suggesting sequences for developing new independent drug candidates with unlimited resources is generated with a conventional bubble chart approach. These sequences initiate a genetic algorithm (GA)-based search for the optimal sequence in the presence of product dependencies and limited resources. By statistically evaluating the sequences generated during the GA search using a discrete event simulation model, it is possible to construct an economic reward-risk frontier that illustrates the trade-offs between expected rewards and risks. The model ideally is suited to answer various ‘‘what if’ ’ questions relative to changes in the resource level on pipeline performance. The methodology is illustrated with an industrially motivated case study, involv-ing nine interdependent new product candidates targeting three diseases. The dra-matic results yield a candidate sequence with an expected return 28 percent higher than the sequence suggested by the bubble chart approach at almost the same level of risk. The synergism among the candidate dependencies, pipeline resources, and economic and technical uncertainties demonstrates the necessity of a computation-ally intensive approach if the best development strategy is to be realized.