Innovations usually have an initial impact on very few people. The period of learning or early evaluation precedes the diffusion of the technology into the wider addressed population. More than a transfer, this is best characterized as communication of benefits, costs, and compatibility with earlier technologies and a relative assessment of the new state of the art. Innovation development by an organization or individual creates not just a device (i.e., process or tacit knowledge) but concomitantly a capacity on the part of other organizations or persons to use, adopt, replicate, enhance, or modify the technology, skills, or knowledge for their own purposes. How innovations actually diffuse is to understand the communication of progress, and this framing helps one to design innovations and also design the marketing and testing programs to ready innovations for market and launch them efficiently. Diffusion theory's main focus is on the flow of information within a social system, such as via mass media and word-of-mouth communications. This theory presents often in the form of mathematical models of innovation and imitation. Distinct from classical diffusion models, however, consumers are not all identical in how they connect to others within a market or how they respond to information. We examine the effects of various network structures and relational heterogeneity on innovation diffusion within market networks. Specifically, network topology (the structure of how individuals in the market are connected) and the strength of communication links between innovator and follower market segments (a form of relational heterogeneity) are studied. Several research questions concerning network heterogeneity are addressed with an agent-based modeling approach. The present study's findings are based on simulation results that show important effects of network structure on the diffusion process. The ability to speed diffusion varies significantly according to within-and cross-segment communications within a heterogeneous network structure. The implications of the present approach for new product diffusion are discussed, and future research directions are suggested that may add useful insights into the complex social networks inherent to diffusion. A simple summary is that discovery of significant prime communicator nodes in a network allows innovation development practices to be better calibrated to realistically multiple market segments.

Several studies have demonstrated an order-of-entry effect on market share, suggesting that pioneers outperform later entrants. However, other research has pointed out the limitations of these studies and found evidence that many pioneers fail or have low market share. Given this background, the purpose of this research is to understand the conditions under which pioneers are more likely and also less likely to have an advantage. We propose a game-theoretic model that includes important sources of pioneer advantages as well as disadvantages. Specifically, we incorporate a pioneer advantage due to preemption in markets with heterogeneous tastes. In addition, we incorporate a potential pioneer disadvantage due to technology vintage effects, where later entrants utilizing improved technology can have lower costs and higher quality. The model allows us to evaluate the extent of vintage effects necessary to overcome a pioneer's advantage. Key relationships are found between the magnitude of the pioneer advantage or disadvantage and consumer valuations of product attributes (e.g., variety and quality). We empirically validate the model with vintage effect data in 36 product categories, and measures of consumer valuations of product variety and quality for 12 of these 36 categories. The results show that pioneers do better in product categories where variety is more important and worse in categories where product quality is more important. Pioneers in categories with high vintage effects are shown to have lower market shares and higher failure rates. Similar results appear when analyzing persistence of market leadership over time, further validating our model's major implications. We also present two case studies that illustrate key elements of the model.Pioneering, Order of Entry

Company executives rely on new product development teams to carry out their directives and make decisions according to management's goals. However, team members bring their own motivational perspectives to strategic decisions. This research examines how individual and leadership motivations influence a dyadic team's new product decisions. Specifically, this article investigates how matching vs. mismatched motivations between team members affect new product number, type, and timing decisions. In addition, this study asks how effective leadership-provided motivations are in guiding teams' new product decisions. A set of hypotheses is developed using regulatory focus theory, which identifies basic motivational differences in individuals (i.e., promotion vs. prevention focus) and their effects on decision making. The hypotheses examine the effects of regulatory focus match vs. mismatch within teams on the likelihood to introduce new products, the timing of new product introductions, and the types of new products introduced. To test the hypotheses, a controlled, yet realistic product management simulation is employed. A total of 124 undergraduate seniors (83 women and 41 men) at a large public university enrolled in a marketing management capstone course participated in this study for partial course credit. Utilizing two-person teams engaged in a business simulation ensured an appropriate level of controlled complexity in the decision making task, while allowing the phenomena of interest to be isolated and tested. Results show that when dyads share the same motivational approach (regulatory focus match), leadership-prescribed goal pursuit strategies are largely ineffective. Only dyads that do not share the same motivational approach to decision making (regulatory focus mismatch) make new product decisions consistent with leadership-prescribed goal pursuit strategies. For regulatory focus match dyads, the results demonstrate that a promotion focus (when compared to a prevention focus) leads to greater numbers of new products introduced, faster new product introductions, and more novel new product introductions. For new product managers, these results carry important implications. Which new product opportunities to invest in and which to forgo is presumably determined by the strategic direction given to teams by top management. Results suggest that when team members share the same motivational approach, this not only influences new product decisions, but also diminishes or eliminates the influence top management can exert on new product decisions. Such ''isolation'' from leadership influences does not have to be detrimental. For example, companies that seek to insulate new product development teams from influences from the top, such as is the case in many new venture incubations, would be well served to staff those teams ensuring a promotion focus match.

The more "really new" a product is, the more difficult it is to predict consumer response. However, accurate forecasting of really new products is an essential element in a firm's innovation strategy. Therefore many leading firms are experimenting with the use of multimedia computers to present information to consumers so that these customers can react to a really new product as if it were now in the market of the future. We explore two aspects of best practice in this area of forecasting by examining the validity of a new multimedia forecasting methodology called "information acceleration" (IA) and lessons learned from eight real-world new-product applications of the methodology.We report two internal validations and one external validation of new product sales forecasts based upon IA. The internal validation for a new automobile suggests that a computer-simulation of an automobile showroom provides forecasts that are not significantly different from those obtained based on a physical showroom. The internal validation of a medical instrument suggests that a computer-simulation of a medical technician provides forecasts that are not significantly different from those based on allowing physicians to interact with real technicians. The external validation of a new camera product suggests that IA provides forecasts that are sufficiently accurate for managerial go/no go decisions. For that application we compare actual sales to the initial forecasts, made in 1992 for sales in 1993 and 1994, to adjusted forecasts based on the actual marketing plan, and to forecasts adjusted for an unforeseen negative Consumer Reports article. We close the paper with a summary of the lessons that we have learned during the past five years based on eight applications of IA to really new products.

Cross-functional product development teams (CFPDTs) are receiving increasing attention as a fundamental mechanism for achieving greater interfunctional integration in the product development process. However, little is known about how team members' interactional fairness perception-fairness perception based on the quality of interpersonal treatment received from the project manager during the new product development process-affects cross-functional communication and the performance of CFPDTs. This study examines the effects of interactional fairness on both team members' performance and team performance as a whole. It was predicted that interactional fairness in CFPDTs would significantly affect team members' task performance, both task-and person-focused interpersonal citizenship behaviors, as well as team performance. Additionally, commitment would partially mediate the effects of interactional fairness on these performance outcomes. Analyzing survey responses from two student samples of CFPDTs with hierarchical linear modeling techniques, it was demonstrated that team members' task performance, interpersonal citizenship behavior, and team performance are enhanced when team members are dedicated to both the team and the project, and such dedication is fostered when project managers are fair to team members in an interpersonal way.

In this study, the feasibility of using representative box wing adaptive structures for static aeroelastic control is examined. A deformable typical section is uti lized to derive the optimal and suboptimal relations for induced strain actuated adaptive wings, and the relations developed are used to design representative adaptive lifting sur faces which are assessed in trade studies. The optimal relations developed showed that op timal adaptive airfoil designs are possible for some realistic configurations, and effective sub-optimal designs can be achieved for others. In addition, the important parameters associated with inducing curvature and twist, thereby altering the lifting forces on the air foil, are determined. The most important of which were found to be the airfoil thickness ratio, the actuation strain produced by the induced strain actuators, and the relative stiff ness ratio of the actuator to the wing skin for both camber and twist control. The stiffness coupling parameter and the wing aspect ratio were also found to be important for twist control. The potential benefits of using adaptive airfoils for aeroelastic control, rather than conventional articulated control surfaces, is demonstrated in trade studies. It was found that greater control authority along with a lower weight penalty is achievable using adap tive aeroelastic structures for a variety of wing designs. Thus, strain actuated adaptive wings may be used rather than conventional lifting surfaces to increase performance while reducing weight, decreasing loads in critical areas, improving the radar cross section, and maximizing the lift-to-drag ratio for many flight conditions.

The challenges of successfully developing radical or really new products have received considerable attention from a variety of marketing, strategic, and organizational perspectives. Previous research has stressed the importance of a market‐driven customer orientation, the resolution of market and technological uncertainty, and organizational processes such as cross‐functional teams and organizational learning. However, several fundamental issues have not been addressed. From a customer's perspective, a more innovative product tends to have uncertain benefits and requires customers to learn new behaviors. Customer preferences can, therefore, change as product experience and learning increase. From a firm's perspective, it is unclear how to be customer‐oriented under such dynamic preferences, and product strategies using evolving technologies will tend to interact with how customers learn about an innovation. This research focuses on identifying unresolved issues about these customer and product innovation dynamics. A conceptual framework and series of propositions are presented that relate both changing technology and customer learning to a firm's strategic decisions in developing and launching really new products. The framework is based on in‐depth interviews with high‐tech product managers across several sectors, focusing on the business‐to‐business context. The propositions resulting from the framework highlight the need to consider relevant customer dynamics as integral to a firm's product innovation process. Successful innovation strategies and future research challenges are discussed, and applications to better understanding customer needs and theories of disruptive innovation are examined. Several key insights for innovation success hinge on a broad, downstream orientation to customer needs and product innovation dynamics. To be effective innovators, firms must know their customers' customers and competitors as well as or better than their immediate customers do. Market research must extend downstream for a comprehensive understanding of customer needs dynamics. In the context of disruptive innovation, new dimensions of customer needs may become more valuable based on perceived downstream customer trends. Firms may also innovate on secondary needs because mainstream customers do not always give firms the design freedom to radically innovate on primary features. Understanding customer commitments and how they develop under evolving needs can help firms focus resources on innovative efforts more likely to be accepted by customers.

This study investigates how people's satisfaction judgments are modified after they interact with other group members. It integrates research on customer satisfaction and social influence to develop hypotheses about how an individual's satisfaction is influenced by discrepancies between her expectations about the satisfaction of other group members and their actual opinions as revealed in group discussion. It also considers how this effect is moderated by the individual's susceptibility to social influence and perceptions of group cohesiveness. Two empirical studies demonstrate significant social influence effects on satisfaction judgments in groups. Study One analyzes group satisfaction data collected over time using a mixed-effects regression. It shows that an individual's perceived discrepancy between others' satisfaction judgments and expected group satisfaction has an important influence on her postdiscussion satisfaction judgments. Moreover, individuals discount the prediscussion satisfaction judgments of other group members in favor of perceived satisfaction and its discrepancy with expectations. Group cohesiveness accentuates the perceived discrepancy with expected group satisfaction. Study Two analyzes survey data from dyads drawn from a cross-sectional sample of organizational buyers who purchase from the same supplier. It models the decision maker's satisfaction with a service supplier as a function of end-user satisfaction. It shows that social influence effects exist in purchasing groups within organizations. Both studies demonstrate that individual-level postdiscussion satisfaction judgments tend to become more extreme, a phenomenon we call .satisfaction, social influence, organizational buying decisions, group cohesiveness, escalation