The organizational adoption of high-technology products “for use”: Effects of size, preferences, and radicalness of impact

This research reports the results of a study on organizational adoption of high-technology products “for use” in contrast to “for manufacture.” Additionally, the study examines high-technology adoptions which often have different issues that are important to the decision process relative when compared to the adoption of less-technical products. For example, the level of compatibility or the availability of complementary products (e.g., network externality considerations) are often important issues for high-technology adoptions. As such, this study provides additional information in the relatively underresearched organizational adoption literature, particularly as it relates to high-technology products. In order to maintain connectivity with past work, we look at the firm size versus adoption issue. At the same time, we add new information by also examining how organizational preferences for products, and the degree of radicalness of the products affect organizational adoption. We use a proportional-hazards model to test our hypotheses using panel data on 400 firms that are drawn from 14 industries. As part of the research effort we developed an improved scale for judging the radicalness of a product than has been used in prior research. Furthermore, we extended the Booz, Allen, & Hamilton New Product Categories (1982) approach to incorporate innovation impact. As expected, the results show that size “does matter,” but that it is modified by degree of product radicalness and organizational preference. Interestingly, we found that for high-technology products “for use,” organizations prefer radical impact products but adopt incremental impact products. Hence, preferences and purchase behaviors do not match.     

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.     

Biases in the selection stage of bottom‐up strategy formulation

We propose that the failure to adopt an idea or innovation can arise from an in‐group bias among employees within an organizational subunit that leads the subunit's members to undervalue systematically ideas associated with members of the organization outside their subunit. Such biases in internal selection processes can stymie organizational adaptation and therefore depress the performance of the firm. Analyzing data on innovation proposals inside a large, multinational consumer goods firm, we find that evaluators are biased in favor of ideas submitted by individuals that work in the same division and facility as they do, particularly when they belong to small or high‐status subunits. Copyright © 2013 John Wiley & Sons, Ltd     

Configurations of social media-enabled strategies for open innovation,firm performance,and their barriers to adoption

The use of social media offers tremendous innovation potential. Yet, while current research emphasizes success stories, little is known about how firms can leverage the full potential of their social media use for open innovation. In this paper, the authors address this gap by conducting a configurational analysis to develop an integrative taxonomy of social media-enabled strategies for open innovation. This analysis stems from the integration of internal and external variables such as social media communication activities, organizational innovation seekers, potential innovation providers, the stages of the open innovation process, and their relationship with different performance outcomes and barriers to social media adoption for open innovation. Through an empirical study of 337 firms based in eight countries, four clusters have been identified that are characterized as distinct strategies: “marketing semi-open innovators,” “cross-department semi-open innovators,” “cross-department full process semi-open innovators” and “broad adopters open innovators.” The findings reveal the trade-offs associated with different strategies for implementing social media for open innovation and provide insights of the use of these strategies. By doing so, they suggest a more nuanced approach that contrasts with the traditionally positive (or even rosy) depiction of the effects of social media on open innovation. Accordingly, managers are encouraged to contemplate their organizational competencies, capabilities, and their strategic intent when drafting social media strategies for open innovation. Selective approaches, along with greater adoption leading to greater benefits, are shown to be more rewarding than a middle way that spreads things too thin. Avenues for further research include qualitative explorations of the trajectories unfolding through implementing social media strategies for innovation activities and the use of objective performance measures rather than subjective perceptions from informants to understand the complex relationships between social media adoption and performance.     

Intermediating technologies and multi-group adoption: A comparison of consumer and merchant adoption intentions toward a new electronic payment system

Traditional technology adoption research has assumed a single adopting group. However, there are many settings in which multiple groups must jointly adopt an innovation in order for it to succeed. This is particularly true for new information technology innovations that mediate the relationship between two groups. For example, online exchanges (e.g., Freemarkets, GoFish) must attract both suppliers and buyers in order to be successful. The same is true for providers of hardware/software solutions for electronic data interchange and supply chain management. This article describes the phenomenon of multigroup adoption with a particular focus on applications within the financial services and retailing industries. Empirically, the article reports findings from a study that illustrates the importance of evaluating and managing multigroup technology adoption in the specific context of an in‐market trial of a new smart card‐based electronic payment system. Two distinct groups critical to the smart card's success are studied: consumers (who must decide to use the new card) and retailers (who must agree to adopt and use new technology needed to process smart card transactions). The study identifies which characteristics of the smart card innovation are most closely linked to intention to adopt for each group, and examines how these key characteristics differ by group. Perceptual data were collected via a mail survey from consumers and merchants living in the city where a one‐year market trial of the new card was taking place. Four separate sampling frames were established for both consumers and merchants who were participating in the trial as well as both consumers and merchants who were not participating in the trial. Random samples were then drawn from these frames. More than 350 consumers and over 250 merchants completed and returned the survey. Responses were analyzed separately for each of the four groups sampled. The most important characteristic leading to adoption identified by all four groups was relative advantage—the smart card had to demonstrate a clear competitive advantage over what they currently used. Compatibility (i.e., the degree to which the smart card fit with their current preferences) was also noted as important to all but the nonparticipating merchant group. Beyond this, the key drivers of adoption differed considerably by group. Participating consumers and participating merchants appeared to possess different perspectives when assessing their decision to adopt the smart card technology. Consumers seemed to value the notion that the adoption decision is under their control, whereas merchants seemed to place more value on the antecedents that had the potential to add to their bottom line. This suggests that it is necessary to institute different marketing tactics to attract the early adopting groups. In addition, significant differences in the importance of antecedents between participating and nonparticipating consumers and participating and nonparticipating merchants suggest that, over time, it may also be necessary to develop and use different marketing tactics for later adopters.     

Diffusing New Ideas In-House

New ideas trigger the innovation process and the development of new products. This article is concerned with new ideas generated in-house and ways to ensure that these ideas have the maximum chance of being captured and diffused. Sandra Vandermerwe reports results of an exploratory study involving an international group of senior executives concerning their attempts to introduce new ideas and gain support for them within their firms. In particular, she was alert to reports of organizational resistance, when it was reported. She asked why this resistance occurred and what might be done to improve the receptivity to new ideas. The article examines the executives' responses and highlights an interesting feature of the findings: that new technological ideas may, by their very nature, be slow-movers. Firms are encouraged to put more conscious effort into internal diffusion activity as they do externally in the marketplace. This would require new skills and a new role for originating individuals.     

The adoption of information technology in the sales force

The purpose of this article is to explain why salespeople adopt information technology. The results from a cross-sectional study of 229 salespeople indicate that putting sales technology to use strongly depends on salespeople's perceptions about the technology enhancing their performance, their personal innovativeness and organizational efforts in terms of user training. Throughout the adoption process companies also need to target sales line managers-next to end users-because salespeople clearly comply with the expectations of their supervisors. Finally, the threat from competing sales professionals or peers who use similar sales technology seems to be of secondary importance for individual sales technology adoption.     

Adoption of Technologically Based Innovations: The Neglected Role of Bounded Rationality

The purpose of this research is to examine the possibility of distinguishing between adopters and nonadopters when conceptualizing the drivers of the decision to adopt technologically based innovations. A second research objective is to examine factorial validity through the assessment of the explanatory power of the investigated conceptualization. In the pursuit of these objectives, the theory of bounded rationality represents the underlying theoretical framework, and Internet banking (IB) represents the nomological framework, in which two alternative conceptualizations, one for IB adopters and a second for nonadopters, are considered. “Intention to adopt” and “adoption” are the criterion variables, respectively. To meet the objectives of the study, two different populations are examined: adopters of IB and nonadopters. The former was used to examine the hypothesized framework for predictive validity against actual adoption; the latter was used to examine the predictive validity regarding intention to adopt. To collect data from IB adopters, the four leading banks, which account for approximately 73% of adopters, agreed to place a link to a Web‐based questionnaire at the log‐in page of their IB system inviting customers to participate in the study. Through this process, 858 useable questionnaires were produced. To reach the nonadopters population, a convenience sample of executive M.B.A. students from two leading Greek universities was employed. Respondents from this sample were screened to ensure that they had never used IB. This process yielded 418 useable questionnaires from the nonadopters population. A major finding from this investigation is that the decision to adopt improves the understanding of adopters regarding the benefits delivered by an innovation. Consequently, they hold a precise, less ambiguous perception of how specific innovation attributes translate into benefits. Hence, when recalling the decision process through which they adopted an innovation, adopters relate specific innovation attributes, including specific benefits received. This situation is displayed in the ability of a direct, first‐order model to capture the relationships between specific innovation attributes and the adoption decision. In contrast, nonadopters, having no direct experience with the innovation, lack this familiarity. They require a significantly greater amount of information in order to associate innovation attributes with potential benefits. The intangibility of technologically based service innovation further increases a nonadopter's need for information. However, this increased need for information renders nonadopters subject to cognitive strain, which causes them to aggregate innovation attributes into more abstract constructs. That aggregation was displayed in the ability of a second‐order model to capture the relationships between specific innovation attributes and the nonadopters' intention to adopt the innovation in the future. In both occasions though, the instrumental drivers of adoption represent the most powerful explicators of the adoption decision. From a practitioner's perspective, this study shows that managers can structure the content of their communication to facilitate the rise of societal drivers, but they should avoid relying on such elements to quicken the pace of the adoption rate. Rather, at the core of communication campaigns, practitioners should place brief and clear claims demonstrating the instrumental arguments in favor of the adoption decision.     

How to Overcome Pro‐Change Bias: Incorporating Passive and Active Innovation Resistance in Innovation Decision Models

Adoption literature is largely subject to a pro‐change bias; researchers mainly assume that consumers are open to change and thus interested in evaluating new products. However, consumers often reject innovations without considering their potential, such that the adoption process ends before it really has begun. The present study instead argues that innovation resistance, prior to product evaluation, is a regular consumer response that must be recognized and managed to facilitate new product adoption. The authors suggest differentiating passive from active innovation resistance. While passive innovation resistance results from a consumer's generic predisposition to resist innovations prior to new product evaluation, active innovation resistance is an attitudinal outcome that follows an unfavorable new product evaluation. This study also extends extant innovation decision models by describing how passive and active innovation resistance emerge and how they affect decision‐making in later stages of the process.     

Social services and telecommunications: Innovation in human services delivery

This article presents an analysis of the current state of adoption of telecommunications technologies by organizations and individuals who work in human services. It examines the barriers to use of innovations and suggests the future course of acceptance for the different technologies. Radio and telephone appear to have the fewest barriers to adoption, and it is likely that as consumers become more accustomed to advanced technologies in their homes, they will be more likely to accept them in the workplace.     

Antecedents of Innovation Strategies in New Technology‐based Firms: Interactions between the Environment and Founder Team Composition

This research contributes to the ongoing stream of research on the integration of technical and business knowledge for successful innovation, but does so with a unique focus—that of new firm founder teams. This is in contrast to much of the existing literature, which focuses on organizational units in large firms. As part of their strategy for success, new technology‐based firms need to find an optimal balance between exploration and exploitation in their innovation activities. However, the resource constraints they typically face make it difficult for them to pursue both at the same time, which means that at any given point in time they are likely to opt for either exploration or exploitation rather than both. The purpose of this research is to investigate what influences new technology‐based firms to select one innovation strategy over another. Data collected in 145 new technology‐based firms are used to test hypotheses about how environmental conditions and founder team composition interact in their contributions to choice of innovation strategy. Based on hierarchical regression analysis of the data, the research findings suggest that teams consisting of individuals who have dissimilar backgrounds are more likely to adapt their innovation strategy to the characteristics of the environment than teams of individuals with similar backgrounds. Conversely, teams consisting of individuals with similar backgrounds are more likely to continue to follow their preferred strategy. However, as competitive intensity or environmental dynamism increases, such teams are likely to deviate from their preferred strategy.     

Organizational Culture and Innovation: A Meta‐Analytic Review

The relationship of organizational culture and innovation has been subject to extensive research over the last decades. The multitude of cultural variables under investigation has led to a fragmented concept of culture for innovation, and an inclusion into management theory is still missing. Further, managerial practice requires an underlying structure in order to decide what culture should be implemented in order to foster innovation, and to assess if a specific culture is an effective and efficient coordination instrument. Hence, a framework is needed which allows classification of cultural values without residuals, to draw expedient comparisons with reference to the criteria by which they are grouped, and to assess their relationship with organizational innovation. This meta‐analysis, which comprises 43 studies with a combined sample size of 6341 organizations, reveals that Quinn and Rohrbaugh's Competing Values Framework provides a meaningful structure for the ideational aspects of organizational culture. The Competing Values Framework describes value systems based on two main dimensions. Those two pairs of opposing values are flexibility versus control and internal versus external orientation. The analysis shows that the congruence of different cultures with organizational goals of innovation can be described based on that framework. Control theory is used to explain the relationship of organizational culture and innovation. While culture describes the ideational aspects of organizational values, clan control describes their coordinative effect. Managers may choose different clan control strategies according to the Competing Values Framework. They will most likely follow the strategy that provides a high level of congruence between the goals of management and the goals of their organization's social system. Individuals that have internalized the organizational values apply them as a form of self‐control. Those values will also be applied in groups, such as product development teams. While development teams may be formed and disbanded with certain projects and individuals may leave the company, the organization forms the steady frame of those activities. The cumulative data confirms the hypothesis that managers of innovative organizations most likely implement a developmental culture, which emphasizes an external and a flexibility orientation. Yet also group and rational cultures are to a certain extent consistent with the goals of an innovative organization and may thus be appropriate social control strategies. Hierarchical cultures emphasize control and an internal orientation and are less likely to be found in innovative organizations. A moderator analysis of the culture–innovation relationship revealed that it is not influenced by the differentiation between radical and incremental innovation, and only weak evidence exists for an influence of innovation adoption versus innovation generation. A potential reason is that those organizations that are geared toward innovation will pursue it consequently, without differentiating between different kinds of innovation. Therefore, managers that follow a (radical) innovation strategy should establish a developmental culture in their organization. If innovation rather represents a minor aspect of the firm's long‐term objectives, the efficiency‐oriented rational culture or a group culture may also be the right choice.     

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.     

Network board continuity and effectiveness of open innovation in Swedish strategic small-firm networks

Increasing adoption of open innovation as an alternative route to research and development necessitates the development of new ways to organize innovation, as well as reassessment of existing ways. Much like traditional corporations that subscribe to the closed innovation paradigm, novel organizational arrangements targeting open innovation, such as small-firm networks, employ boards to effectively manage joint research-and-development activities. These boards are similar yet different from traditional corporate boards; as such, they may have different requirements for proper functioning. We use 5-year longitudinal data on 53 Swedish strategic small-firm networks to investigate how the boards should be organized to help improve the innovative status of network participants. We expand the set of tools available for effective organization of the boards' operations and emphasize the effects of network board continuity (rates of renewal) on network members' innovative performance. We argue that the relationship is curvilinear (U-shaped) and demonstrate that it is more pronounced in larger networks.     

Factors Influencing the Adoption of Mass Customization: The Impact of Base Category Consumption Frequency and Need Satisfaction

Mass customization has received considerable interest among researchers. However, although many authors have analyzed this concept from different angles, the question of which factors can be used to spot customers most likely to adopt a mass‐customized product has not been answered to a satisfactory extent until now. This article explicitly deals with this question by focusing on factors related to the base category, which is defined as the group of all standardized products within the same product category as the mass‐customized product under investigation. Specifically, this article investigates the influence of a customer's base category consumption frequency and need satisfaction on the decision to adopt a mass‐customized product within this base category. A set of competing hypotheses regarding these influences is developed and subsequently evaluated by a combination of partial least squares and latent class analysis. This is done by using a sample of 2,114 customers surveyed regarding their adoption of an individualized printed newspaper. The results generated are threefold: First, it is shown that there is a significant direct influence of base category consumption frequency and need satisfaction on the behavioral intention to adopt. The more frequently a subject consumes products out of the base category or the more satisfied his or her needs are due to this consumption, the higher the behavioral intention to adopt a mass‐customized product within this base category. Second, the article provides an indication that base category consumption frequency has a significant moderating effect when investigating the behavioral intention to adopt in the context of the theory of reasoned action and the technology acceptance model. The more frequently a subject consumes products out of the base category, the more important will be the impact of perceived ease of use mediated by perceived usefulness. Finally, this article shows that different latent classes with respect to unobserved heterogeneity regarding the latent variables base category need satisfaction or dissatisfaction have significantly different adoption behaviors. Individuals who show a high level of need dissatisfaction are less interested in the ease of use of a mass‐customized product than its usefulness (i.e., increase in need satisfaction). On the other hand, subjects who have a high degree of base category need satisfaction base their adoption decision mainly on the ease of use of the mass‐customized product. These results are of managerial relevance regarding the prediction of market reactions and the understanding of the strategic use of product‐line extensions based on mass‐customized products. This work provides an indication that base category consumption frequency and need satisfaction positively influence the behavioral intention to adopt a mass‐customized product. Hence, mass customization can be seen as one way to deepen the relationship with existing clients.     

Innovations—Doomed to Fail? Investigating Strategies to Overcome Passive Innovation Resistance

The constant and successful market introduction of new products is of major concern to companies throughout all industries. However, empirical research points to high failure rates of innovations, indicating that most new products fail as they are rejected by consumers due to their resistance to innovation. Several studies have confirmed the importance of passive innovation resistance as a dominant barrier, which has to be overcome before new product adoption can start. However, empirical evidence on how to overcome passive innovation resistance is still lacking. This study intends to address this gap by evaluating the effectiveness of marketing instruments (i.e., mental simulation and benefit comparison) to reduce negative effects of passive innovation resistance on new product adoption. The results of a scenario‐based experiment (n = 679) confirm high effectiveness for both instruments. However, the effectiveness varied with the type of passive innovation resistance present. More specifically, mental simulation was found to be the most effective instrument in the case of cognitive passive resistance, whereas benefit comparison was found to be most effective in the case of situational passive resistance. Thereby, the effect of both marketing instruments was stronger the more radical the new product was perceived. Hence, companies should assess the type of passive innovation resistance that is predominant in their target market, and align their choice of marketing instruments that accompany a new product launch to most effectively overcome passive innovation resistance. Employing such new product launch tactics should decrease initial market resistance and thus help companies in reducing innovation failure rates.     

Organizational intention to adopt big data in the B2B context: An integrated view

Grounded in the diffusion of innovation theory (DOI), institutional theory, configuration theory, and technology-organization-environment (TOE) framework, the study proposes a model incorporating factors in technological, organizational and environmental contexts that may influence an organization's decision to adopt big data strategies. Using survey data collected from Chinese companies, eight factors in three categories are tested utilizing a structural equation modeling (SEM) and Fuzzy-set Qualitative Comparative Analysis (fsQCA). The empirical results show that the factors relative advantage, technological competence, technology resources, support from top management, competitive pressure, and the regulatory environment all have a significant impact on the organizational adoption of big data. These findings contribute to the development of a better understanding of precisely how the big data diffusion process across industries functions in B2B practice.     

Methodology for increasing the adoption of R & D project selection models

Although some studies and experiences have shown that R & D project selection models can be potentially useful decision aids, their adoption and routine use is not widespread. This lack of usage may be a consequence of the lack of attention which model builders have traditionally given to the prevailing adoption attitudes of R & D managers. A design methodology centering around the measurement of adoption attitudes has been developed and used by the authors. The methodology consists of procedures for analyzing the organizational climate relative to project selection model usage, developing an acceptable model form relative to the organizational climate, and inducing the adoption of this model form within the climate. Three case applications of the methodology are described in which negative-to-positive shifts in adoption attitudes occurred and project selection models were adopted for long-term use. These results indicate that the use of this general methodology may lead to increased formal adoption and widespread usage of project selection model forms in R & D.     

Methodology for increasing the adoption of R & D project selection models

Although some studies and experiences have shown that R & D project selection models can be potentially useful decision aids, their adoption and routine use is not widespread. This lack of usage may be a consequence of the lack of attention which model builders have traditionally given to the prevailing adoption attitudes of R & D managers. A design methodology centering around the measurement of adoption attitudes has been developed and used by the authors. The methodology consists of procedures for analyzing the organizational climate relative to project selection model usage, developing an acceptable model form relative to the organizational climate, and inducing the adoption of this model form within the climate. Three case applications of the methodology are described in which negative-to-positive shifts in adoption attitudes occurred and project selection models were adopted for long-term use. These results indicate that the use of this general methodology may lead to increased formal adoption and widespread usage of project selection model forms in R & D.     

Fast and expensive: the diffusion of a disappointing innovation

Firms seek to imitate innovations that yield competitive advantage, but imitation can presage disappointment when the innovation value is below expectations. Empirical research has only rarely examined the diffusion of such disappointing innovations, and it is not known whether negative information from past adopters will halt the diffusion process. Likewise, the effect of heterogeneity in the innovation value on its spread has not been systematically investigated. Here, a unique dataset on a disappointing innovation is used to examine how adoption decisions are imitated, but actual use and subsequent abandonment can yield information that reduces the likelihood that others will adopt. The findings show imitation of the adoptions of other firms, but avoidance of the innovation once these firms start using the innovation or abandon it. Copyright © 2011 John Wiley & Sons, Ltd.