Overcoming consumer resistance to innovations – an analysis of adoption triggers

Traditionally, innovation adoption research has focused on the determinants of the states ‘adoption’ and ‘nonadoption’. Aiming at a more detailed understanding of innovation adoption and resistance behavior, this study takes a different perspective and analyzes the transition stage between the nonadoption state and the adoption state to investigate triggers that overcome initial consumer resistance. The study seeks to answer three questions within this novel perspective: (1) What are triggers that lead nonadopters to become adopters? (2) Do adopters and nonadopters differ in their assessment of adoption triggers? and (3) How do adoption triggers relate to innovation adoption barriers? We apply a qualitative exploratory approach that relies on 160 face‐to‐face interviews with both adopters and nonadopters about nine different innovations to generate a framework of adoption triggers. The results reveal that adoption triggers fall into three broad categories: ‘increasing innovation attraction’, ‘reducing barriers’ or ‘tilting the system’. In addition, we find that adopters and nonadopters differ significantly in their assessment of (potential) adoption triggers. Nonadopters mention performance improvements more frequently as crucial adoption triggers than adopters do. In contrast, adopters indicate knowledge acquisition and a social system push significantly more often than nonadopters do. However, adoption triggers and corresponding adoption barriers do not appear to be linked in a systematic way. Instead, adoption triggers such as a social system push exert influence independent of the existing adoption barriers. We suggest strategies for pre‐ and postlaunch strategies to facilitate adoption triggers. We also discuss the implications of our findings for theory and present further research opportunities.     

Understanding early diffusion of digital wireless phones

There is increasing empirical evidence from academic research and strong recognition among policymakers that wide diffusion and innovative uses of digital wireless phones are important sources of a country's economic growth and social development. Adopters do not necessarily adopt digital wireless phones at the same time though. Although the diffusion of innovation theory suggests five adopter categories according to their degree of innovativeness, this approach lacks theoretical justification and, more importantly, it makes a critical assumption of a normal distribution of adopters that needs empirical validation. This study investigates the basis for defining different adopter categories and factors that affect adoption decisions of digital wireless phones using the aggregate data on 46 developed and developing countries from 1992 to 2002. This paper utilizes a two-step analysis approach. The first step evaluates the distribution of adopters over time using various diffusion models. The second step uses iterative survival analysis to examine the patterns of influential factors on adoption behavior by evaluating the survival models using a 1% increment of cumulative penetration as the targeted events. The results of the best-fitting diffusion models indicate that digital wireless phone adoption patterns did not follow a normal distribution and did not map exactly into Rogers’ five adopter categories. The results from the iterative survival analysis suggest four adopter categories (innovators, early adopters, breakthrough adopters, and mainstream adopters) among the first 30% of adopters. Different factors are observed to influence various adopter categories’ adoption decisions. The results offer insights to support telecommunication operators to develop strategies to attract these adopters. It also supports policymakers’ efforts to design effective regulatory frameworks.     

The impact of emerging institutional norms on adoption timing decisions: evidence from C‐TPAT—A government antiterrorism initiative

Drawing upon an institutional theoretic perspective, this study explores the performance outcomes associated with adoption timing and level of investment in a government antiterrorism initiative—the Customs Trade Partnership Against Terrorism (C‐TPAT). Using a large‐scale sample of C‐TPAT certified importers, this study found that performance outcomes for high levels of investment in adoption processes differ depending upon the strength of institutional forces. Specifically, early adopters of C‐TPAT processes in a weak institutional context that reported high levels of investment performed no better than firms who invested nominally in the processes, while late adopters in a strong institutional context that reported high investment levels outperformed those that invested nominally. This finding can be explained by viewing C‐TPAT as an ‘emerging’ institution, where forces are coalescing. Copyright © 2011 John Wiley & Sons, Ltd.     

Follow the small? Information‐revealing adoption bandwagons when observers expect larger firms to benefit more from adoption

We extend understanding of information‐revealing bandwagons by considering a common condition under which adoption of a practice by small organizations, rather than large ones, has a disproportionate influence on future adoption propensities. We hypothesize that when the value of adoption increases with organizational size, smaller adopters have such disproportionate influence because they allow observers better to infer that adoption will be profitable for their own organization. We elaborate the theory by predicting that alternative information sources moderate the influence of smaller adopters. Empirically, we test our theory with longitudinal data on the adoption of the ISO 9000 quality management standard. Copyright © 2007 John Wiley & Sons, Ltd.     

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.     

Commercializing Technological Innovation: Learning from Failures in High‐Tech Markets*

Commercialization is known to be a critical stage of the technological innovation process, mainly because of the high risks and costs that it entails. Despite this, many scholars consider it to be often the least well managed phase of the entire innovation process, and there is ample empirical evidence corroborating this belief. In high‐tech markets, the difficulties encountered by firms in commercializing technological innovation are exacerbated by the volatility, interconnectedness, and proliferation of new technologies that characterize such markets. This is clearly evinced by the abundance of new high‐tech products that fail on the market chiefly due to poor commercialization. Yet there is no clear understanding, in management theory and practice, of how commercialization decisions influence the market failure of new high‐tech products. Drawing on research in innovation management, diffusion of innovation, and marketing, this article shows how commercialization decisions can influence consumer acceptance of a new high‐tech product in two major ways: (i) by affecting the extent to which the players in the innovation's adoption network support the new product; (ii) by affecting the post‐purchase attitude early adopters develop toward the innovation, and hence the type of word‐of‐mouth (positive or negative) they disseminate among later adopters. Lack of support from the adoption network is found to be an especially critical cause of failure for systemic innovations, while a negative post‐purchase attitude of early adopters is a more significant determinant of market failure for radical innovations. There follows a historical analysis of eight innovations launched on consumer high‐tech markets (Apple Newton, IBM PC‐Junior, Tom Tom GO, Sony Walkman, 3DO Interactive Multiplayer, Sony MiniDisc, Palm Pilot, and Nintendo NES), which illustrates how commercialization decisions (i.e., timing, targeting and positioning, inter‐firm relationships, product configuration, distribution, advertising, and pricing) can determine lack of support from the innovation's adoption network and a negative post‐purchase attitude of early adopters. The results of this work provide useful insights for improving the commercialization decisions of product and marketing managers operating in high‐technology markets, helping them avoid errors that are precursors of market failure. It is also hoped the article will inform further research aimed at identifying, theoretically and empirically, other possible causes of poor customer acceptance in high‐tech markets.     

How Cloudy a Crystal Ball: A Psychometric Assessment of Concept Testing*

Although traditional and conjoint forms of concept testing play an important role in the new product development process, they largely ignore data quality issues, as evidenced by the traditional reliance on the percent Top‐2‐Box scores heuristic. The purpose of this research is to reconsider the design of concept testing from a measurement theory (generalizability theory) perspective and to use it to suggest some ways to improve the psychometric quality of concept testing. Generalizability theory is employed because it can account for the multiple facets of variation in concept testing, and it enables a concept test to be designed to provide a required level of accuracy for decision making in the most effective way, whether the purpose of measurement is to scale concepts or something else, such as to scale respondents. The paper identifies four types of sources—concept‐related factors, response task factors, situational factors, and respondent factors—that can contribute to the observed variation in concept testing and develops six research propositions that summarize what is known or assumed about their contribution to observed score variance. Four secondary data sets from different concept testing contexts are then used to test the propositions. The results provide new insights into the design of concept tests and the psychometric quality of the concept testing data: (1) the concepts facet is not a major contributor to response variation; (2) of the response task factors, concept formulations are a trivial source of variance, but items are not always a trivial source of variance; (3) the situational factors that are investigated are trivial sources of variance; (4) respondents are always a major contributor to the total variation; (5) concepts by respondents are not always a major contributor and the other interactions are often not trivial; and (6) residual error is always a major source of variance. Additionally, the analyses of the secondary data sets enable some useful managerial conclusions to be drawn about the design of concept testing. First, the sample size needed to reliably scale concepts depends on the types of concepts being tested. Second, averaging over items provides considerably more reliable information than relying on a single item. Third, which specific item performs best is inconsistent and very context specific. The popular purchase intention item is never the best single item to use. Fourth, not much is gained by sampling levels of the response task factors. Finally, concept testing should be designed to meet the needs of specific managerial tasks.     

An investigation into the mixed reported adoption rates for ABC: Evidence from Australia, New Zealand and the UK

An accumulated body of the literature confirms that the adoption of activity-based costing (ABC) can lead to a substantial improvement in organisational performance, productivity and profitability, and therefore encourages further adoption of the technique. However, studies investigating the diffusion of ABC have reported inconsistent and mixed results. This could cause uncertainty for many potential adopters of ABC (especially for those who follow the fashion and fads approaches) and influence their tendencies towards the adoption of ABC in the future. Addressing the diffusion process as a contextual factor, this study simultaneously investigates the adoption of ABC from the perspectives of different diffusion processes. Using two commonly adopted diffusion processes (the stages of adoption and the levels of adoption), this study examines the relationship between the reported adoption rates for ABC and the diffusion process approaches chosen to measure its adoption rates in three western countries: Australia, New Zealand and the UK. A similar questionnaire was used and more than 2000 qualified CIMA members (via a survey study and follow-up interviews) were targeted. The findings suggest a significant association between the reported adoption rates for ABC and the diffusion process approaches chosen to measure the adoption rates. The findings further suggest that the lack of a common understanding of ABC systems may have also contributed to the mixed reported adoption rates for ABC, as many ABC adopters have considered themselves adopters of traditional accounting systems by mistake (especially when they are dealing with ‘facility costs’ as one of the main cost hierarchies under ABC systems).     

Lifestyles and the use of new media technology in urban China

Research in adoption of new mediatechnologies for social identity and its relationship to lifestyle has received little attention. The purpose of thisstudy is to link consumers’ lifestyle orientation and media use to the adoption behavior of new media technologies in urban China. Key findings indicate that (1) lifestyles significantly affect innovativeness; (2) the upscale socioecono-mic profile of earlier adopters was consistent with early research; and (3) adoption of certain new media technologies appeared to project certain social identities such as ‘life expansionists’, ‘sophisticated and fashionable’,and ‘pleasurable and enjoyable’. The results have important implications for marketing managers and media planners.     

Whose Crystal Ball to Choose? Individual Difference in the Generalizability of Concept Testing

The product development literature has identified several individual characteristics that could influence how subjects respond to new products in concept tests. Few of these characteristics have been thoroughly investigated. The purpose of this research is to examine whether a number of personality traits (1) do influence concept evaluation scores and (2) can be used to identify respondents who provide substantially higher‐quality data in concept testing and whether the answers to these questions change for major versus minor innovations. The data quality of the concept testing data is defined using the generalizability theory, which provides a decision‐specific G‐coefficient. Higher quality means a G‐coefficient closer to 1 for a particular managerial decision. A Web‐based study to concept test 10 appliance innovations on multiple occasions was conducted among 105 panelists from the Institute for Online Consumer Studies (IOCS). During the concept testing, respondents' innovativeness, change‐seeking tendency, and propensity to exert cognitive effort were also measured. The results showed that the respondent characteristics influence the mean evaluation of the concepts and the psychometric quality of the concept testing data: (1) there is a significant linear relationship between concept scores and all of the innovativeness scales and change‐seeking measures; (2) the effect of innovativeness on concept testing outcomes is even more substantial for major innovations than for minor innovations; (3) the study provides evidence that the quality of concept testing data provided by respondents varies substantially with their innovativeness, whereas the differences are more modest when scaling just minor innovations; (5) there are also strong effects on data quality for the Need to Evaluate scale used to capture cognitive effort characteristics; and (6) there is little effect of segmenting on social desirability on data quality. Managerially, the current results indicate that a product manager wanting to concept test a pool of appliance concepts can benefit from screening for the respondents who will provide higher‐quality concept testing data. For example, respondents who are high on domain‐specific innovativeness provide the highest‐quality concept testing data for both minor and major innovations. The effects of traits are stronger for major innovations, supporting the claim that subject selection is a more critical issue in concept testing of major innovations. Product managers can improve the quality of their concept testing data without an increase in cost by screening the subjects they use in concept testing.     

Lifestyle orientations and the adoption of Internet-related technologies in Taiwan

Using Rogers' diffusion of innovation model as the theoretical framework, this study examined the relationships between lifestyle orientations and the adoption of nine Internet-related technologies in Taiwan including IPTV, digital cable, emails, Internet instant messages, Facebook, scanners, notebooks, printers and personal computers. A telephone survey was conducted to collect data, and 506 valid questionnaires were obtained, representing a response rate of 58.6%. The results showed that lifestyle orientations were a powerful predictor for the adoption of information-oriented and entertainment-oriented technologies, but not for the adoption of interpersonally oriented technologies. Furthermore, this study found that while demographics were the most powerful variable that distinguished the adopters from the non-adopters, mass media use was not.     

Analysis of the socio-economic determinants of mobile money adoption and use in Cameroon

This study analyses the adoption and use of mobile money (MM) services based on data collected on 1000 households from the Global Findex Survey conducted in 2017 in Cameroon, by the World Bank. More specifically, this study attempts to first profile MM adopters, and then identify the explanatory factors of the different uses of these services. A Probit model is used to highlight the explanatory factors of MM adoption combined with multivariate regressions to identify the determinants of MM service use. Then, estimates of three independent Probits, under the assumption of non-simultaneity of the different uses of MM services are done to test the reliability and robustness of the results. The results reveal that socio-economic factors such as age, level of education, the standard of living and mobile phone ownership differentially affect both the adoption and use of MM services in Cameroon.     

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.     

Is direct seeded rice a boon for economic performance? Empirical evidence from India

The direct-seeded rice (DSR) establishment method can improve productivity and labor efficiency while taking into account the soil and hydrologic conditions of the field, the availability of appropriate land equipment, and irrigation-drainage systems. Using plot- and household-level data, we analyze the impacts of DSR adoption in two rice-growing states of India. We account for observed and unobserved heterogeneity using endogenous switching regression. We analyze the yield and costs effects of DSR adoption. Our study shows a small but significant effect of DSR adoption on yield and costs. We find increase in rice yields (by 3.74%) for DSR adopters; an increase in rice yields (by 6.79%) if the DSR method were adopted on puddled transplant rice (PTR) parcels. We find a 7.51% reduction in total costs for DSR adopters; a decrease in total costs (by 3.71%) if the DSR method was adopted on PTR parcels. DSR farmers can significantly reduce their fertilizer and land preparation costs. Hence, the decision to adopt DSR may help households with limited resources to reduce their cost of production without compromising the yield.     

Incorporating Network Externalities into the Technology Acceptance Model*

Research on network externalities has identified a number of product categories in which the market performance of an innovation (e.g., unit sales and revenues) is an increasing function of that innovation's installed base and the availability of complementary products. Innovation scholars have attributed these findings to the positive impact of network externality variables on consumer perceptions of innovation attributes. This paper provides the first empirical examination of these perceptual linkages by extending the Technology Acceptance Model to include consumer perceptions of network externality variables. The authors hypothesize that, when direct and indirect network externalities exist, consumer purchase intentions and consumer perceptions of an innovation's usefulness and ease of use will positively reflect perceptions of installed base size and the availability of complementary products. To test this reasoning, the authors developed new measures of consumer perceptions of network externality variables. These measures were incorporated into a survey that explored the attitudes in Japan of potential adopters toward digital music (DM) players at an early stage in the product life cycle. Findings reveal a direct positive relationship between ease of use and the perceived availability of digital music. The authors also find positive and significant relationships between both purchase intention and perceived usefulness and (1) the perceived size of the DM player installed base and (2) the perceived availability of digital music. An application of the Baron‐Kenny test for mediating variables reveals that (1) ease of use partially mediates the relationship between the perceived availability of digital music and perceived usefulness and (2) perceived usefulness partially mediates the relationship between the perceived availability of digital music and purchase intention. The research has important implications for future research on new product adoption and for the management of innovations that involve network externalities. The conceptual model provides a framework for testing alternative explanations of observed variations in the impact of network externalities within and across product categories. The empirical analysis provides guidance for managers who wish to manage the impact of network externalities on adoption. In addition to stimulating the size of the installed base and the variety of complementary products, executives must also manage consumer awareness of network externality variables and consumer understanding of the relationship between those variables and innovation attributes. Finally, traditional adoption models link consumer adoption decisions to perceptions of innovation attributes. The findings provided here imply that predictive accuracy of these models can be improved by including consumer perceptions of network externality variables.     

Will firms go green if it pays? The impact of disruption,cost, and external factors on the adoption of environmental initiatives

Research summary : Research on the link between financial and environmental performance implicitly assumes that firms will pursue profitable environmental actions. Yet, clearly, factors beyond profitability influence firms' environmental choices. We treat these choices as organizational change decisions and hypothesize that adoption of environmental initiatives is influenced by a combination of profit, level of disruption caused, and external influences. We test our hypotheses by examining firms' choices regarding implementation of energy‐savings initiatives. We find that degree of disruption, number of prior local adopters, and strength of environmental norms affect the adoption decisions. In addition, the effect of disruption is amplified by the implementation costs, but is mitigated by the number of prior local adopters. Managerial summary : Often, in trying to improve firms' environmental performance, academics and stakeholders have focused on actions that simultaneously improve environmental and financial performance. This assumes that firms will undertake projects that offer such dual benefits. We consider what might prevent firms from pursuing such ‘win‐win’ initiatives. We focus on how the degree of disruption of an energy‐saving initiative affects its probability of adoption. We find that firms are significantly more likely to adopt moderately profitable, but easy initiatives than more profitable but disruptive ones. We also examine internal and external factors that moderate the effect of disruption. Our findings suggest that in order to incentivize firms to improve environmental performance, it might be more beneficial make these activities less disruptive than to make them more profitable. Copyright © 2016 John Wiley & Sons, Ltd.     

The Effect of Personal and Virtual Word‐of‐Mouth on Technology Acceptance

This paper extends the Technology Acceptance Model (TAM) to incorporate the impact of personal and virtual word‐of‐mouth (pWOM and vWOM). The authors hypothesize that both types of word‐of‐mouth will be positively related with consumer perceptions of innovation usefulness and perceived ease of use. In addition, the authors examine two competing hypotheses regarding the relative impact of pWOM and vWOM on perceptions of innovation attributes. One hypothesis argues that potential adopters place more weight on pWOM sources because they perceive relatively more similarity between themselves and pWOM sources. The alternative hypothesis argues that potential adopters place more weight on vWOM sources because those sources (relative to pWOM sources) expose potential adopters to a wider variety of information and a larger number of experts. Finally, the authors argue that symbolic product usage will enhance the relationship between word‐of‐mouth and consumer perceptions of innovation attributes. These hypotheses are tested using data collected in Japan from over 600 potential adopters of Blu‐ray DVD recorders and smart phones. Findings indicate that, in both product categories, pWOM and vWOM are positively and significantly related with perceived ease of use. Moreover, in both samples pWOM is positively and significantly related with perceived usefulness, while vWOM is significantly related with perceived usefulness only in the smart phone sample. With regard to the relative impact of pWOM and vWOM on perceptions of innovation attributes, results indicate that vWOM has a larger impact on potential adopter perceptions of ease of use. Finally, the estimated model provides support for the hypothesis that symbolic consumption increases the impact of word‐of‐mouth on perceptions of innovation attributes. In particular, findings indicate that the impact of pWOM on perceptions of innovation usefulness is higher among potential adopters of smart phones than among potential adopters of Blu‐ray DVD recorders. Similarly, the impact of vWOM on perceptions of ease of use is higher among potential smart phone adopters than among potential adopters of Blu‐ray DVD recorders.     

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.     

SPLINTERING AND INERTIA IN NETWORK INDUSTRIES*

We analyse a stylised game of technology adoption with network effects and two new technologies. Potential adopters can adopt early, late or not at all. We show that one of the reasons for the failure of new technologies can be the presence of multiple incompatible variants of that technology. An adopter's individual incentives to adopt are lower with two technologies than with one. Turning to aggregate expected welfare, we find that two active technologies may be welfare‐improving.     

Speeding Up the Pace of New Product Development

This study empirically investigates a wide array of factors that have been argued to differentiate fast from slow innovation processes from the perspective of the research and development organization. We test the effects of strategic orientation (criteria- and scope-related variables) and organizational capability (staffing- and structuring-related variables) on the speed of 75 new product development projects from ten large firms in several industries. Backward-elimination regression analysis revealed that (a) clear time-goals, longer tenure among team members, and parallel development increased speed, whereas (b) design for manufacturability, frequent product testing, and computer-aided design systems decreased speed. However, when projects were sorted by magnitude of change, different factors were found to influence the speed of radical and incremental projects. Moreover, some factors that sped up radical innovation (e.g., concept clarity, champion presence, co-location) were found to slow down incremental innovation. Together, the radical and incremental models explain differences in speed better than the general model. This suggests a contingency approach to speeding up innovation. Implications for researchers and managers are discussed.