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A fundamental tension exists in creativity between novelty and similarity. This research exploits this tension to help creators craft successful projects in crowdfunding. To do so, the authors apply the concept of combinatorial creativity, analyzing each new project in connection to prior similar projects. By using machine learning techniques (Word2vec and Word Mover’s Distance), they measure the degrees of similarity between crowdfunding projects on Kickstarter. They analyze how this similarity pattern relates to a project’s funding performance and find that (1) the prior level of success of similar projects strongly predicts a new project’s funding performance, (2) the funding performance increases with a balance between being novel and imitative, (3) the optimal funding goal is close to the funds raised by prior similar projects, and (4) the funding performance increases with a balance between atypical and conventional imitation. The authors use these findings to generate actionable recommendations for project creators and crowdfunding platforms.

When faced with new technologies, the incumbents’ dilemma is whether to embrace the new technology, stick with their old technology, or invest in both. The entrants’ dilemma is whether to target a niche and avoid incumbent reaction or target the mass market and incur the incumbent’s wrath. The solution is knowing to what extent the new technology cannibalizes the old one or whether both technologies may exist in tandem. The authors develop a generalized model of the diffusion of successive technologies, which allows for the rate of disengagement from the old technology to differ from the rate of adoption of the new. A low rate of disengagement indicates people hold both technologies (coexistence), whereas a high rate of disengagement indicates they let go of the old technology in favor of the new (cannibalization). The authors test the validity of the model using a simulation of individual-level data. They apply the model to 660 technology pairs and triplets–country combinations from 108 countries spanning 70 years. Data include both penetration and sales plus important case studies. The model helps managers estimate evolving proportions of segments that play different roles in the competition between technologies and predict technological leapfrogging, cannibalization, and coexistence.

The authors test five theoretically derived hypotheses about what drives video ad sharing across multiple social media platforms. Two independent field studies test these hypotheses using 11 emotio...

Radical innovation is an important driver of the growth, success, and wealth of firms and nations. Because of its importance, authors across various disciplines have proposed many theories about the drivers of such innovation, including government policy and labor, capital, and culture at the national level. The authors contrast these theories with one based on the corporate culture of the firm. They test their theory using survey and archival data from 759 firms across 17 major economies of the world. The results suggest the following: First, among the factors studied, corporate culture is the strongest driver of radical innovation across nations; culture consists of three attitudes and three practices. Second, the commercialization of radical innovations translates into a firm's financial performance; it is a stronger predictor of financial performance than other popular measures, such as patents. The authors discuss the implications of these findings for research and practice.

Radical innovation is an important driver of the growth, success, and wealth of firms and nations. Because of its importance, authors across various disciplines have proposed many theories about the drivers of such innovation, including government policy and labor, capital, and culture at the national level. The authors contrast these theories with one based on the corporate culture of the firm. They test their theory using survey and archival data from 759 firms across 17 major economies of the world. The results suggest the following: First, among the factors studied, corporate culture is the strongest driver of radical innovation across nations; culture consists of three attitudes and three practices. Second, the commercialization of radical innovations translates into a firm's financial performance; it is a stronger predictor of financial performance than other popular measures, such as patents. The authors discuss the implications of these findings for research and practice.

China and India are the fastest-growing major markets in the world and the most popular markets for foreign entrants. However, no study has examined the success or failure of these entries. Using a new definition of success and a uniquely compiled archival database, the authors analyze whether and why firms that entered China and India succeeded or failed. The most important findings are rather counterintuitive: Smaller firms are more successful than larger firms, and firms entering more open emerging markets have less success. Other findings are that success is greater with earlier entry, greater control of entry mode, and shorter cultural and economic distances between the home and the host countries. Importantly, with or without control for these drivers, firms have less success in India than in China. The authors discuss the reasons for and implications of these findings.

Indirect network effects are of prime interest to marketers because they affect the growth and takeoff of software availability for and hardware sales of a new product. Although prior work on indirect network effects in the economics and marketing literature is valuable, there are two main shortcomings. First, empirical analysis of indirect network effects is rare. Second, in contrast to the importance prior literature credits to the “chicken-and-egg” paradox in these markets, the temporal pattern (i.e., Which leads to which?) of indirect network effects remains unstudied. Based on empirical evidence of nine markets, this study shows that (1) indirect network effects, as commonly operationalized by prior literature, are weaker than expected from prior literature and (2) in most markets examined, hardware sales “lead” software availability, whereas the reverse almost never happens, contrary to existing beliefs. These findings are supported by multiple methods, such as takeoff and time-series analyses, and fit with the histories of the markets studied herein. For academia, the study identifies a need for new and more relevant conceptualizations of indirect network effects. For public policy, it questions the need for intervention in network markets. For management practice, it downplays the importance of the availability of a large library of software for hardware technology to be successful.

The Internet has enabled consumers to make more informed decisions more conveniently with apparently more efficient price-clearing mechanisms than was available before its advent. One such mechanism is the name-your-own-price auction. The authors study the extent to which decisions made in such an auction are rational in relation to an economic model. The results from two independent markets show that a large number of consumers do not exhibit rational decision making.

Technological change is perhaps the most powerful engine of growth in markets today. To harness this source of growth, firms need answers to key questions about the dynamics of technological change: (1) How do new technologies evolve? (2) How do rival technologies compete? and (3) How do firms deal with technological evolution? Currently, the literature suggests that a new technology seems to evolve along an S-shaped path, which starts below that of an old technology, intersects it once, and ends above the old technology. This belief is based on scattered empirical evidence and some circular definitions. Using new definitions and data on 14 technologies from four markets, the authors examine the shape and competitive dynamics of technological evolution. The results contradict the prediction of a single S-curve. Instead, technological evolution seems to follow a step function, with sharp improvements in performance following long periods of no improvement. Moreover, paths of rival technologies may cross more than once or not at all.

A common perception in the field of innovation is that large, incumbent firms rarely introduce radical product innovations. Such firms tend to solidify their market positions with relatively incremental innovations. They may even turn away entrepreneurs who come up with radical innovations, though they themselves had such entrepreneurial roots. As a result, radical innovations tend to come from small firms, the outsiders. This thesis, which we term the “incumbent's curse,” is commonly accepted in academic and popular accounts of radical innovation. This topic is important, because radical product innovation is an engine of economic growth that has created entire industries and brought down giants while catapulting small firms to market leadership. Yet a review of the literature suggests that the evidence for the incumbent's curse is based on anecdotes and scattered case studies of highly specialized innovations. It is not clear if it applies widely across several product categories. The authors reexamine the incumbent's curse using a historical analysis of a relatively large number of radical innovations in the consumer durables and office products categories. In particular, the authors seek to answer the following questions: (1) How prevalent is this phenomenon? What percentage of radical innovations do incumbents versus nonincumbents introduce? What percentage of radical innovations do small firms versus large firms introduce? (2) Is the phenomenon a curse that invariably afflicts large incumbents in current industries? Is it driven by incumbency or size? and (3) How consistent is the phenomenon? Has the increasing size and complexity of firms over time accentuated it? Does it vary across national boundaries? Results from the study suggest that conventional wisdom about the incumbent's curse may not always be valid.

An emerging consensus in marketing is that consumers respond to price relative to some standard or reference price. Most researchers modeling brand choice have reasoned that this standard is based on past prices of the brand. The authors argue that consumers do use reference prices, but one that is also based on context—other prices in the store—rather than on past prices alone. An analysis of households’ brand choices in two subcategories and over three cities supports this premise. Within context, the lowest price seems to be an important cue for reference price, whereas within time, a brand's own past prices seem to be the most important cue. Households’ use of a contextual reference price also varies predictably across some consumer characteristics. Though their model can be applied to other categories, the findings have important managerial implications: Managerial focus on temporal reference prices could lead to an everyday high price, whereas focus on contextual reference prices could lead to an everyday low price. Only the inclusion of both contextual and temporal reference prices justifies variable pricing.