Will It Spread or Not? The Effects of Social Influences and Network Topology on Innovation Diffusion

Innovation diffusion theory suggests that consumers differ concerning the number of contacts they have and the degree and the direction to which social influences determine their choice to adopt. To test the impacts of these factors on innovation diffusion, in particular the occurrence of hits and flops, a new agent‐based model for innovation diffusion is introduced. This model departs from existing percolation models by using more realistic agents (both individual preferences and social influence) and more realistic networks (scale free with cost constraints). Furthermore, it allows consumers to weight the links they have, and it allows links to be directional. In this way this agent‐based model tests the effect of VIPs who can have a relatively large impact on many consumers. Results indicate that markets with high social influence are more uncertain concerning the final success of the innovation and that it is more difficult for the innovation to take off. As consumers affect each other to adopt or not at the beginning of the diffusion, the new product has more difficulties to reach the critical mass that is necessary for the product to take off. In addition, results of the simulation experiments show under which conditions highly connected agents (VIPs) determine the final diffusion of the innovation. Although hubs are present in almost any network of consumers, their roles and their effects in different markets can be very different. Using a scale‐free network with a cut‐off parameter for the maximum number of connections a hub can have, the simulation results show that when hubs have limits to the maximum number of connections the innovation diffusion is severely hampered, and it becomes much more uncertain. However, it is found that the effect of VIPs on the diffusion curve is often overestimated. In fact when the influence of VIPs on the decision making of the consumers is strengthened compared with the influence of normal friends, the diffusion of the innovation is not substantially facilitated. It can be concluded that the importance of VIPs resides in their capacity to inform many consumers and not in a stronger persuasive power.     

The Effects of Market Network Heterogeneity on Innovation Diffusion: An Agent‐Based Modeling Approach

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.     

Consequences of New Product Development Speed: A Meta‐Analysis

Five meta‐analyses previously have been published on the topic of new product development involving the concept of new product development speed. Three of these studies have investigated antecedents to new product development success, of which just one was new product development speed. The other two studies used new product development speed as the dependent variable, and analyzed antecedents to achieving speed. This article extends previous empirical generalizations in this domain by using a meta‐analytic methodology to understand the link between new product development speed and new product success at a more granular level. Specifically, it considers the relationship with different dimensions of success as measured overall or compositely, operationally (i.e., the process measures of decreasing development costs and proficiently managing market entry timing and the product measures of technical product performance and product competitive advantage), and relative to external success outcomes (i.e., customer based and financial success). While the results indicate that, in general, new product development speed is associated with improving success outcomes, those relationships may diminish or even disappear depending upon a number of methodological design decisions and research contexts. A subsequent meta‐analysis of the antecedents of development speed provides a more holistic picture of development speed. These results are broadly consistent with those produced by another recent meta‐analytic investigation of the issue. Together, these findings have important implications for academics pursuing further research in this domain, as well as for managers considering implementing a program to increase new product development speed.     

Should Firms Consider Employee Input in Reward System Design? The Effect of Participation on Market Orientation and New Product Performance

Will increasing employee participation in reward decisions increase new product performance by first increasing a firm's level of market orientation? Literature offers limited insight to the effects of listening to employees regarding reward system design and whether this may influence market orientation implementation and new product performance. This paper provides research to fill the gap by examining the relationship between participation‐based reward systems, market orientation, and new product performance. Based on expectancy theory, a conceptual model was developed suggesting that participation‐based rewards will increase market orientation by considering employees' desires regarding performance rewards. To test the model, a mixed method was used to collect data. First, in‐depth interviews were conducted with managers from 11 different firms to verify the proposed model. Then a multi‐industry sample of managers from 290 firms was surveyed to maximize generalizability of the results. Data were analyzed using structural equation modeling techniques to simultaneously fit the measurement and structural models. The findings show that market orientation significantly impacts objective new product performance and mediates the relationship between participation‐based rewards and objective new product performance. Participation‐based rewards positively affect market orientation but surprisingly affect new product performance negatively, while positively moderating the relationship between market orientation and new product performance. The results suggest that managers should include employee input in designing reward systems. However, managers should also be careful of how much input they allow employees in determining their rewards and goals as more input will improve market orientation or responding to information collected by, and disseminated throughout the firm, and that, in turn, will improve some types of new product performance. However, the direct effect of employee input can decrease new product performance suggesting that there may be a trade‐off between various success measures of new products developed and introduced by the firm.     

The Estimation of a Cusp Model to Describe the Adoption of Word for Windows*

This article revisits earlier work in this journal by Paul Herbig (1991) that proposed a catastrophe model of industrial product adoption under certain conditions. Catastrophe models are useful for modeling situations where organizations can exhibit both smooth and abrupt adoption behavior. It extends Herbig's work by focusing on organizations' adoption of new products when network externalities are an important part of the decision process, and it presents an empirical estimation of the model. Network externalities occur when firms do not want to adopt a new innovation or product unless other firms do. The reason is that they do not want to end up with an innovation that ends up not being a standard of some sort. Mistakes of this nature can be costly as the firm must invest twice and loses time relative to competitors who have not made such a mistake. However, when such externalities exist, for example with regard to technological adoptions, then normal diffusion gives way to sudden discontinuous shifts as all firms seemingly act together an move to a new technology. Since, technology is an area where the authors expect network externalities to exist, that is the focus of this article. The specific application is developed from two sets of panel data on the organizational adoptions of Microsoft's (MS) Word for Windows software by organizations that previously were using either Word for DOS or Word for Macintosh (Mac). The theoretical framework for the analysis is based on work in the economics literature on network externalities. However, the organization and new product development catastrophe model comes primarily from Herbig (1991) . The article focuses on an area of organizational adoption where relatively little empirical research has been done, namely organizational adoption “for use.” Longitudinal data provided by Techtel Corporation is used to develop the estimations. Results of the empirical analysis are consistent with the theoretical framework suggested in Herbig's article and in those found in economics and catastrophe theory literatures. This lends clear support to the idea that organizations will adopt a bandwagon‐type behavior when network externalities are present. It further suggests that in such markets, the standard S‐shaped diffusion curve is not an appropriate model for examining organizational behavior. From a managerial perspective, it means that buyers and sellers may face nonstandard diffusion curves. Instead of S‐shaped curves, the actual curves have a break or rift where sales end, and there is a sudden shift to a new product that is relatively high very early on. Clearly, for new product development (NPD), it suggest that organizations' “for‐use” purchases may be similar to regular consumers and may change rapidly from one product to another almost instantly, as in the case of the switch from vinyl records to compact discs (CDs). From an old product seller's viewpoint, the market is here today and gone tomorrow, while for the new seller it is a sudden deluge of sales requests. To put it in more everyday terms, sudden changes in adoption behavior are a September 11‐type experience for the market. It is the day the world changes.     

Managing Diffusion Barriers When Launching New Products

In recent years there has been a growing interest in the link between new product launch activities and market success. So far, most empirical research has focused on launch activities that target customer adoption barriers. However, with such a focus the influence of other stakeholders on innovation diffusion is not taken into account. A review of diffusion research and stakeholder theory serves as a basis for discussing the influence of different stakeholder groups such as customers, dealers, suppliers, and competitors on innovation diffusion. Essentially, it is expected that addressing multiple diffusion barriers during new product launch will have a positive impact on market success. The new concept for launch activities addressing multiple diffusion barriers is tested with data on new product launches in industrial markets using a multiple‐informant approach. The results lend support to the notion that a successful launch requires activities addressing diffusion barriers related to different stakeholder groups. Specifically, barriers related to customers, suppliers, and stakeholders of the further firm environment need to be lowered during market launch. For the group of competitors, a balanced launch approach including measures to both lowering and erecting entry and diffusion barriers will increase the market success of new products. The subsequent investigation of the influence of technological turbulence, market turbulence, and product complexity on the performance relationships shows that under high uncertainty managing multiple‐diffusion barriers is of higher relevance than in more unambiguous, clear‐cut contexts. Thus, the results demonstrate that a careful management of diffusion barriers related to multiple stakeholders is a relevant task when launching a new product. The paper concludes with implications for management practice and avenues for future academic research.     

The virtual customer

Communication and information technologies are adding new capabilities for rapid and inexpensive customer input to all stages of the product development (PD) process. In this article we review six web‐based methods of customer input as examples of the improved Internet capabilities of communication, conceptualization, and computation. For each method we give examples of user‐interfaces, initial applications, and validity tests. We critique the applicability of the methods for use in the various stages of PD and discuss how they complement existing methods. For example, during the fuzzy front end of PD the information pump enables customers to interact with each other in a web‐based game that provides incentives for truth‐telling and thinking hard, thus providing new ways for customers to verbalize the product features that are important to them. Fast polyhedral adaptive conjoint estimation enables PD teams to screen larger numbers of product features inexpensively to identify and measure the importance of the most promising features for further development. Meanwhile, interactive web‐based conjoint analysis interfaces are moving this proven set of methods to the web while exploiting new capabilities to present products, features, product use, and marketing elements in streaming multimedia representations. User design exploits the interactivity of the web to enable users to design their own virtual products thus enabling the PD team to understand complex feature interactions and enabling customers to learn their own preferences for new products. These methods can be valuable for identifying opportunities, improving the design and engineering of products, and testing ideas and concepts much earlier in the process when less time and money is at risk. As products move toward pretesting and testing, virtual concept testing on the web enables PD teams to test concepts without actually building the product. Further, by combining virtual concepts and the ability of customers to interact with one another in a stock‐market‐like game, securities trading of concepts provides a novel way to identify winning concepts. Prototypes of all six methods are available and have been tested with real products and real customers. These tests demonstrate reliability for web‐based conjoint analysis, polyhedral methods, virtual concept testing, and stock‐market‐like trading; external validity for web‐based conjoint analysis and polyhedral methods; and consistency for web‐based conjoint analysis versus user design. We report on these tests, commercial applications, and other evaluations. © 2002 Elsevier Science Inc. All rights reserved.     

A MULTI‐TASK PRINCIPAL‐AGENT APPROACH TO ORGANIZATIONAL FORM*

This paper studies the choice of organizational forms in a multi‐task principal‐agent model. We compare a functional organization in which the firm is organized into functional departments such as marketing and R&D to a product‐based organization in which the firm is organized into product lines. Managers' compensation can be based on noisy measures of product‐line profits. Measures of a functional area's contribution to total profits are not available, however. This effect favors the product organization. However, if there are significant asymmetries between functional area contributions to organizational success and cross‐product externalities within functions, organizing along functional lines may dominate the product organization. The functional organization can also dominate when a function is characterized by strong externalities while the other is not.     

Exploring Portfolio Decision‐Making Processes*

Portfolio management is the set of activities that allows a firm to select, develop, and commercialize a pipeline of new products aligned with the firm's strategy that will enable it to continue to grow profitably over the long term. To appropriately manage the firm's new product portfolio, decisions must be made about which projects to fund, to what levels, at what point in time. Previous research has investigated portfolio management decisions as individually discrete decisions. Significant streams of research have investigated both project selection and project termination decisions. This research project shows, however, that portfolio decision making may be better understood if it is considered as an integrated system of processes that considers these decisions simultaneously, along with other decisions such as those to continue a project with reduced funding. Using in‐depth data from four diverse case studies, we use a grounded theory approach to develop a general model of how firms make new product portfolio decisions. According to the findings from these cases, effective portfolio decision‐making processes produce a portfolio mindset, focus effort on the right projects, and allow agile decision making across the portfolio's set of projects. Effective portfolio decision making is the result of the interaction between three types of decision‐making processes that managers use in making decisions: evidence‐, power‐, and opinion‐based. Being able to use each of these types of processes to make decisions depends upon having the data inputs that they require. Three domain‐based decision input‐generating processes (i.e., cross‐functional collaboration, practices of critical thinking, and practices of market immersion) are associated with making evidence‐based portfolio decisions. In addition, organizational politics produces the inputs that are associated with power‐based portfolio decision making, while managerial intuition is associated with opinion‐based portfolio decision making. Firm cultural factors, including trust, collective ambition, and leadership style, are associated with how these evidence‐, power‐ and opinion‐based processes are combined into an overall portfolio decision making process, and whether the firm's processes are more rational and objectively made, or more politically and intuitively made. The article presents propositions for how the decision‐making processes interact in their associations with decision‐making effectiveness.     

The Interplay of Customer and Product Innovation Dynamics: An Exploratory Study

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.     

Sales Forecasting in High-Technology Markets: A Utility-Based Approach

Accurate sales projections are of vital importance to the profitability and long‐term survival of high‐tech companies. This is especially true in the growth stage of product innovation, because major investments and marketing decisions are made in this phase. By examining recent empirical studies focusing on consumer behavior in high‐technology markets, several factors are identified that can affect individual buying decisions and aggregate sales, namely, interpersonal communication, democratization of innovation, direct and indirect network effects, forward‐looking behavior, and consumer heterogeneity. Against this background the diffusion‐modeling and the utility‐based approach are reviewed in terms of their basic conception and their applicability to the markets concerned. Based on this investigation a sales forecasting model for high‐tech products, specifically in the growth stage, is developed. The model has a utility‐theoretic background and a logistic structure. Since data are scarce in this early stage of the product life cycle two versions of the new approach are discussed, an extended version considering forward‐looking behavior and a more parsimonious (“myopic”) one. The performance of the new model is demonstrated using real sales data on the CD player, the DVD player/recorder, and the digital camera market. The empirical comparisons include alternative specifications of the Bass diffusion model as well as a proportional hazard model and consist of two steps. First, the models are checked as to whether they are able to represent the sales data at all. It is shown that both versions of the proposed model are at least equivalent, if not superior, to the models used as benchmarks in terms of fit. In the next step, the models are applied to predict future sales in the three markets. The resulting forecasts show that the proposed model performs significantly better than its benchmarks. Its parsimony enables reliable predictions, even in cases, where only short time series are available for parameter estimation. The model is able to anticipate decreasing diffusion rates as they occur at the end of the growth stage and, thus, helps to avoid overoptimistic sales forecasts, which may cause severe economic damages. The new approach is easy to calibrate and can be applied without specialized econometric expertise.     

Technological diversity,related diversification,and firm performance

Previous findings that related diversification creates value have been called into question over concerns about methodology and measures. Reviewing existing theory to consider how a firm's knowledge base interacts with its product market activity, I address several of these concerns by creating a measure of technological diversity based on citation‐weighted patents. The measure indicates a firm's opportunity for corporate diversification based on economies of scope in valuable knowledge assets, is defined for both single‐ and multibusiness firms, and is not correlated with more fundamental aspects of diversification, such as the number of businesses in the corporate portfolio. Evidence from a large sample of firms shows the positive relationship between diversification based on technological diversity and market‐based measures of performance, controlling for R&D intensity and capital intensity as further indicators of the type of assets underlying diversification. Results hold when controlling for the endogeneity of diversification and performance in a cross‐sectional sample or when controlling for unobserved factors using panel data. Copyright © 2006 John Wiley & Sons, Ltd.     

Antecedents and Contingent Effects of Organizational Adaptive Capability on Firm Product Innovativeness

Organizational adaptive capability is a broad term and was studied from different perspectives, such as market, technology, and management system, in the management literature. However, the simultaneous effects of these different perspectives and their related adaptive capability constructs on a firm's product innovativeness have yet to be addressed. Additionally, an empirical study of the influence of informal structural dimensions, such as loose coupling, multiplexity, and redundancy, on the organizational adaptive capability, as antecedents, is also missing in the technology and innovation management (TIM) literature. By studying 153 firms, we found that (1) market‐, technology‐, and management system‐related adaptive capability constructs simultaneously and positively impact firm product innovativeness; (2) under the loose coupling construct, autonomous behaviors of departments positively impact technology and management system adaptive capability, loose management style influences market and management system adaptive capability, and uneven/slow information travel in organizations negatively affects technology and management system adaptive capability; (3) multiplexity positively influences all organizational adaptive capability constructs; and (4) under the redundancy construct, information distribution redundancy has an “∩” shape relationship with technology adaptive capability. We also demonstrated that the impact of informal structural constructs on adaptive capability is contingent upon environmental turbulence, e.g., rapid or unanticipated changes in market and technology. We found that the influence of loose management style on technology adaptive capability decreases with increased rate of market turbulence, and the effect of resource slack, as a part of the redundancy construct, on technology adaptive capability changes quadratically, an “∩” shaped curve, with an increased rate of market turbulence. We further found that the effect of the autonomous behaviors of departments on market adaptive capability increases with an increased level of technology turbulence. The role of resource slack on the market adaptive capability was also found to change quadratically, an “∩” shaped curve, with an increased rate of technology turbulence. Interestingly, the impact of the information distribution redundancy on market adaptive capability changes nonlinearly, a “U” shaped curve, with an increased rate of technology turbulence. Further, we showed that the influence of organizational technology adaptive capability on product innovativeness increases with increased level of technology turbulence. This study concludes with several theoretical and managerial implications.     

Modularity and intellectual property protection

Modularity is a means of partitioning technical knowledge about a product or process. When state‐sanctioned intellectual property (IP) rights are ineffective or costly to enforce, modularity can be used to hide information and thus protect IP. We investigate the impact of modularity on IP protection by formally modeling the threat of expropriation by agents. The principal has three options to address this threat: trust, licensing, and paying agents to stay loyal. We show how the principal can influence the value of these options by modularizing the system and by hiring clans of agents, thus exploiting relationships among them. Extensions address screening and signaling in hiring, the effects of an imperfect legal system, and social norms of fairness. We illustrate our arguments with examples from practice.© 2014 The Authors. Strategic Management Journal published by John Wiley & Sons Ltd.     

New Product Preannouncement as a Signaling Strategy: An Audience‐Specific Review and Analysis*

Firms in various industries with highly competitive environments use new product preannouncement (NPP) as one of the most effective and popular signaling tools. Preannouncements can bring both benefits and costs to firms. Extant research has studied NPP from different perspectives and tackled the questions, “Should a new product be preannounced and when?” and “What information should be preannounced and why?” However, the benefits and costs of preannouncements from an audience‐specific perspective are less well understood. It is important to notice that benefits and costs of a preannouncement vary among different audiences and firms need to apply group‐specific weights in assessing the overall benefits and costs prior to making new product preannouncements. The purpose of this article is to review the existing literature on new product preannouncements for commonly observed marketing problems and to develop a general approach focusing on the target audiences and the incentives in sending signals to each audience and the impacts of these signals. This paper first reviews the literature on marketing‐related NPP issues as well as the determinants and effects of various factors on NPP decisions. Then, it discusses the phenomenon of new product preannouncements linked to other marketing and economics problems: (1) product development and positioning; (2) product diffusion and adoption; (3) firm value; (4) vaporware and antitrust litigations; and (5) consumer welfare. In addition, this paper divides the target audience of the new product preannouncement into four groups: customers, competitors, investors, and distributors. Based on current signaling theory, it proposes an audience‐specific framework to analyze the determinants, incentives, and impact of new product preannouncements. The proposed approach may provide more comprehensive insights on NPP strategies to managers and industrial decision makers. Finally, the paper suggests a number of future research directions from four different perspectives (i.e., customer, firm, government/industry, and methodology).     

The double‐edged sword of recombination in breakthrough innovation

We explore the double‐edged sword of recombination in generating breakthrough innovation: recombination of distant or diverse knowledge is needed because knowledge in a narrow domain might trigger myopia, but recombination can be counterproductive when local search is needed to identify anomalies. We take into account how creativity shapes both the cognitive novelty of the idea and the subsequent realization of economic value. We develop a text‐based measure of novel ideas in patents using topic modeling to identify those patents that originate new topics in a body of knowledge. We find that, counter to theories of recombination, patents that originate new topics are more likely to be associated with local search, while economic value is the product of broader recombinations as well as novelty. Copyright © 2014 John Wiley & Sons, Ltd.     

Comments on the Model Testing by Goodwin and Meeran (2012): Comparison of the Utility‐based and the Gompertz Curve Approach for High‐technology Product Sales Forecasting

Starting from a comprehensive examination of recent empirical studies focusing on consumer behavior in high‐technology markets and the resulting identification of factors probably affecting individual buying decisions as well as aggregate product sales, Decker and Gnibba‐Yukawa developed and empirically verified a utility‐based sales forecasting approach in their earlier work. Based on data for 14 consumer electronic products and using the Gompertz curve as a benchmark, Goodwin and Meeran carried out a “more extensive testing” of this proposal. However, at least from a practical point of view, the plausibility of their testing framework regarding the market potential m is not unquestionable. This paper, therefore, first discusses some theoretical aspects of both approaches by addressing issues challenged by Goodwin and Meeran, especially regarding the use of short time series and the consideration of replacement purchases. Then, the quasi‐endogenous estimation method for m favored by Goodwin and Meeran for the Gompertz curve is examined in terms of sensitivity to better understand its influence on sales forecasts, and the adequacy of the suggested range for m in the case of the approach by Decker and Gnibba‐Yukawa is investigated. In addition, the results presented in Goodwin and Meeran are considered from a more distant perspective, and possible causes of the variations in forecasting accuracy are discussed, which finally reveals that the forecasting performance of the utility‐based approach is not that “disappointing” as claimed. It provides more accurate (or at least equivalent) forecasts than the Gompertz curve approach in 64% of the cases considered. Furthermore, if product 14 (portable MP3 players) is excluded from the analysis because of the nonconsideration of probably existing product improvement effects, then the utility‐based approach, on average, outperforms the benchmark in all forecasting years. Altogether, this suggests that the approach by Decker and Gnibba‐Yukawa could achieve more accurate forecasts when applying a more reasonable range for m, rather than varying it between 2 and 15 times the cumulative sales by the end of year 7 as proposed by Goodwin and Meeran. It turns out that the Gompertz curve approach can perform on a par with the utility‐based approach in high‐technology product sales forecasting based on short time series if the market potential m is estimated exogenously. A combination of the outcomes of both approaches can even lead to more accurate forecasts as when being used individually insofar as composite forecasting seems to be a practicable approach to the problem of shorter time series compelled by the accelerated diffusion speed in high‐technology markets, rather than relying on one presumably “best” model.     

Brand Community Members as a Source of Innovation

Brand community members have a strong interest in the product and in the brand. They usually have extensive product knowledge and engage in product‐related discussions; they support each other in solving problems and generating new product ideas. Therefore, brand communities can be a valuable source of innovation. So far, little is known about the member's ability and willingness to participate in a company's innovation process. How does passion for the brand, affiliation to the brand community, and trust in the brand affect the willingness to engage in a company's innovation process? What is the effect of brand passion on brand knowledge and on domain‐specific skills, which are considered important prerequisites for qualified and creative contributions to new product development? What is the effect of personality traits on the willingness and ability to engage in new product development? This research addresses these questions, which are interesting for managers who are thinking about opening up their innovation process and collaborating with brand communities and for academics exploring the opportunities of online communities for new product development and trying to develop promising new forms of open innovation networks. Drawing on brand community literature, relationship theory, creativity theory, and personality traits research, this paper introduces a comprehensive set of antecedents affecting brand community members' willingness to engage in new product development. It is argued that consumer creativity, identification with the brand community, and brand‐specific emotions and attitudes (passion and trust) as well as brand knowledge are important determinants of consumers' willingness to share their knowledge with producers. The paper also identifies two personality traits (i.e., extraversion and openness) that have significant influence on brand passion, creativity, and identification with the community. The hypotheses are tested on a sample of 550 members of the Volkswagen Golf GTI car community. Structural equation modeling was used to test the relationship among the constructs. Though a positive disposition toward a brand may be advantageous for consumers that are willing to interact with producers during new product development, our results show that it is consumer interest in innovations and the innovative process that drives them to get involved. Further, brand community members with more knowledge and more innovative skills seem to be more willing to contribute than less qualified community members.     

The Effects of Supplier Involvement and Knowledge Protection on Product Innovation in Customer–Supplier Relationships: A Study of Global Automotive Suppliers in China

Globalization drives firms to develop product innovation through their global supply chains. While innovations generated by supply channel members, as opposed to individual partners, are playing an increasingly important role in the success of all supply chain partners, there has been limited research on how supply chain relationships cultivate the process of such innovation generation, particularly in emerging markets. Correspondingly, this study explores how multinational suppliers can develop adaptive product innovation to create competitive advantage in emerging markets. Drawing on the knowledge‐based view and transaction cost economics, this study investigates the influence of supplier involvement and other factors on supplier innovation and performance. The results of a survey of 170 multinational automobile suppliers in China provide support for most of the hypotheses. Specifically, supplier involvement in codesign has an inverted U‐shaped relationship with product innovation. Furthermore, knowledge protection, trust, and technological uncertainty are all found to drive greater product innovation. In addition, the institutional environment moderates the effect of product innovation on performance. Overall, this study enhances our understanding of how MNEs can acquire local knowledge and develop adaptive products in emerging markets.     

Firm Patenting,Innovations, and Government Institutional Support as a Double‐Edged Sword

In 2012, China was ranked fourth in patent filing by region of origin. However, firm innovation quality is not comparable to such quantity. Evidence of this is that no Chinese organization was named as a Thomson Reuters 2011 or 2012 Top 100 Global Innovators. This paradox of firm patenting and innovations in China challenges the traditional understanding of the role of government in industrial innovation. This paper provides a theoretical lens through which to examine traditional protective and strategic patenting motives. Based on institutional theory and the ultimate goals of patenting motives, the paper posits that protective patenting motives are directly law‐based while strategic patenting motives are largely law‐derived. The paper also aims to empirically examine three questions: (1) What is the relative importance of various patenting motives to firm patenting behaviors? (2) What effects do patenting behaviors have on firm product and process innovations? (3) How, if at all, does governmental institutional support affect firm patenting and innovations? This paper uses dominant analysis, structural equation modeling, and regression analysis to analyze the survey data collected from a sample of 270 firms in China. The empirical results provide new evidence about firm patenting, innovations, and government institutional support. First, the order of relative importance of patenting motives to patenting behaviors was found to be (in the descending order of importance) reputation, exchange, blocking, and protection. Second, patenting behaviors were more relevant to product innovations than to process innovations. Third, more importantly, while government institutional support can enhance the effects of protective patenting motives on patenting behaviors, it can mitigate the effects of strategic patenting motives on patenting behaviors. Moreover, government institutional support reduces the positive effect of patenting behaviors on product innovations. These findings suggest that firm patenting and innovations are distinct activities, and that government institutional support acts as a double‐edged sword in firm patenting and innovations: On the one hand government institutional support—an extralegal formal institution—may work alongside the patent system—a law‐based formal institution—to advance science and technology, but on the other hand government institutional support may distract firms from commercializing patented knowledge into new products. This paper primarily contributes to institutional theory, new product development literature, and innovation management practice by revealing the dynamics between two different types of formal institutions—patent system and government institutional support—by establishing an institution‐based view of patenting motives, by empirically distinguishing firm patenting and innovations, and more interestingly by uncovering a double‐edged role of government institutional support in firm patenting and innovations.