Research on growth of innovations introduced to the market has gradually shifted its focus from aggregate-level diffusion to exploring how growth is influenced by a given social network structure's ...characteristics. In this paper, we critically review this branch of literature. We argue that the growth of an innovation in a social network is shaped by the network's structure. Borrowing from the field of industrial organization in economics, which defines itself as the study of the effect of market structure on market performance, we describe this new wave of research on growth of innovations as the effect of social network structure on innovation performance. Hence, social network structural characteristics should be incorporated into research on new product growth as well as into managerial marketing decisions such as targeting and new product seeding.
We review how social network structure influences innovations' market performance. Specifically, we discuss (1) a networks' global characteristics, namely average degree, degree distribution, clustering, and degree assortativity; (2) dyadic characteristics, or the relationships between pairs of network members, namely tie strength and embeddedness; (3) intrinsic individual characteristics, namely opinion leadership and susceptibility; and (4) location-based individual characteristics, namely the degree centrality, closeness centrality, and betweenness centrality of an individual network member.
Overall, we find that growth is particularly effective in networks that demonstrate the “3 Cs”: cohesion (strong mutual influence among its members), connectedness (high number of ties), and conciseness (low redundancy). We identify gaps in current knowledge, discuss the implications on managerial decision making, and suggest topics for future research.
This paper studies the influence of network topology on the speed and reach of new product diffusion. While previous research has focused on comparing network types, this paper explores explicitly ...the relationship between topology and measurements of diffusion effectiveness. We study simultaneously the effect of three network metrics: the average degree, the relative degree of social hubs (i.e., the ratio of the average degree of highly-connected individuals to the average degree of the entire population), and the clustering coefficient. A novel network-generation procedure based on random graphs with a planted partition is used to generate 160 networks with a wide range of values for these topological metrics. Using an agent-based model, we simulate diffusion on these networks and check the dependence of the net present value (NPV) of the number of adopters over time on the network metrics. We find that the average degree and the relative degree of social hubs have a positive influence on diffusion. This result emphasizes the importance of high network connectivity and strong hubs. The clustering coefficient has a negative impact on diffusion, a finding that contributes to the ongoing controversy on the benefits and disadvantages of transitivity. These results hold for both monopolistic and duopolistic markets, and were also tested on a sample of 12 real networks.
•Directly studies the dependence of new product diffusion on network topology.•Uses agent-based models on 160 networks for monopoly and duopoly markets.•Generates networks using random graphs with a planted partition.•Average-degree and high-degree hubs enhance diffusion.•Clustering negatively affects diffusion.
Understanding consumers’ associations with brands is at the core of brand management. However, measuring associations is challenging because consumers can associate a brand with many objects, ...emotions, activities, sceneries, and concepts. This article presents an elicitation platform, analysis methodology, and results on consumer associations of U.S. national brands. The elicitation is direct, unaided, scalable, and quantitative and uses the power of visuals to depict a detailed representation of respondents’ relationships with a brand. The proposed brand visual elicitation platform allows firms to collect online brand collages created by respondents and analyze them quantitatively to elicit brand associations. The authors use the platform to collect 4,743 collages from 1,851 respondents for 303 large U.S. brands. Using unsupervised machine-learning and image-processing approaches, they analyze the collages and obtain a detailed set of associations for each brand, including objects (e.g., animals, food, people), constructs (e.g., abstract art, horror, delicious, famous, fantasy), occupations (e.g., musician, bodybuilder, baker), nature (e.g., beach, misty, snowscape, wildlife), and institutions (e.g., corporate, army, school). The authors demonstrate the following applications for brand management: obtaining prototypical brand visuals, relating associations to brand personality and equity, identifying favorable associations per category, exploring brand uniqueness through differentiating associations, and identifying commonalities between brands across categories for potential collaborations.
On Brands and Word of Mouth LOVETT, MITCHELL J.; PERES, RENANA; SHACHAR, RON
Journal of marketing research,
08/2013, Letnik:
50, Številka:
4
Journal Article
Recenzirano
Brands and word of mouth (WOM) are cornerstones of the marketing field, and yet their relationship has received relatively little attention. This study aims to enhance understanding of brand ...characteristics as antecedents of WOM by executing a comprehensive empirical analysis. For this purpose, the authors constructed a unique data set on online and offline WOM and characteristics for more than 600 of the most talked-about U.S. brands. To guide this empirical analysis, they present a theoretical framework arguing that consumers spread WOM on brands as a result of social, emotional, and functional drivers. Using these drivers, the authors identify a set of 13 brand characteristics that stimulate WOM, including three (level of differentiation, excitement, and complexity) that have not been studied to date as WOM antecedents. The authors find that whereas the social and functional drivers are the most important for online WOM, the emotional driver is the most important for offline WOM. These results provide an insightful perspective on WOM and have meaningful managerial implications for brand management and investment in WOM campaigns.
Diffusion processes of new products and services have become increasingly complex and multifaceted in recent years. Consumers today are exposed to a wide range of influences that include ...word-of-mouth communications, network externalities, and social signals. Diffusion modeling, the research field in marketing that seeks to understand the spread of innovations throughout their life cycle, has adapted to describe and model these influences.
We discuss efforts to model these influences between and across markets and brands. In the context of a single market, we focus on social networks, network externalities, takeoffs and saddles, and technology generations. In the context of cross-markets and brands, we discuss cross-country influences, differences in growth across countries, and effects of competition on growth.
On the basis of our review, we suggest that the diffusion framework, if it is to remain a state-of-the-art paradigm for market evolution, must broaden in scope from focusing on interpersonal communications to encompass the following definition:
Innovation diffusion is the process of the market penetration of new products and services that is driven by social influences, which include all interdependencies among consumers that affect various market players with or without their explicit knowledge.
Although diffusion modeling has been researched extensively for the past 40
years, we believe that this field of study has much more to offer in terms of describing and incorporating current market trends, which include the opening up of markets in emerging economies, web-based services, online social networks, and complex product–service structures.
In word-of-mouth seeding programs, customer word of mouth can generate value through market expansion; in other words, it can gain customers who would not otherwise have bought the product. ...Alternatively, word of mouth can generate value by accelerating the purchases of customers who would have purchased anyway. This article presents the first investigation exploring how acceleration and expansion combine to generate value in a word-of-mouth seeding program for a new product. The authors define a program's "social value" as the global change, over the entire social system, in customer equity that can be attributed to the word-of-mouth program participants. They compute programs' social value in various scenarios using an agent-based simulation model and empirical connectivity data on 12 social networks in various markets as input to the simulation. The authors show how expansion and acceleration integrate to create programs' social value and illustrate how the role of each is affected by factors such as competition, program targeting, profit decline, and retention. These results have substantial implications for the design and evaluation of word-of-mouth marketing programs and of the profit impact of word of mouth in general.
Environments such as shopping malls, airports, or hospital emergency-departments often experience crowding, with many people simultaneously requesting service. Crowding highly fluctuates, with sudden ...overcrowding "spikes". Past research has either focused on average behavior, used context-specific models with a large number of parameters, or machine-learning models that are hard to interpret. Here we show that a stochastic population model, previously applied to a broad range of natural phenomena, can aptly describe hospital emergency-department crowding. We test the model using data from five-year minute-by-minute emergency-department records. The model provides reliable forecasting of the crowding distribution. Overcrowding is highly sensitive to the patient arrival-flux and length-of-stay: a 10% increase in arrivals triples the probability of overcrowding events. Expediting patient exit-rate to shorten the typical length-of-stay by just 20 minutes (8.5%) cuts the probability of severe overcrowding events by 50%. Such forecasting is critical in prevention and mitigation of breakdown events. Our results demonstrate that despite its high volatility, crowding follows a dynamic behavior common to many systems in nature.
The Diffusion of Services Libai, Barak; Muller, Eitan; Peres, Renana
Journal of marketing research,
04/2009, Letnik:
46, Številka:
2
Journal Article
Recenzirano
Many of the products introduced during the past two decades have been services rather than goods. An important influence on the growth and long-term profits of these services is customer attrition, ...which can occur at the category level (disadoption) or between firms (churn). However, the literature has rarely modeled how services penetrate a market and has not evaluated the effect of attrition on growth. The authors combine diffusion modeling with a customer relationship approach to investigate the influence of attrition on growth in service markets. In particular, the authors model the effects of disadoption and churn on evolution of a category and on growth of individual firms in a competitive environment. The authors show how neglecting disadoption can bias parameter estimation and, especially, market potential. They also derive an expression for the customer equity of a growing service firm and apply it to valuation of firms operating in competitive industries. The results for six of seven firms in four service categories are remarkably close to stock market valuations, an indicator for the role of customer equity in valuations of growing service firms.
Narrowband Influencers and Global Icons Peres, Renana; Talwar, Sunali; Alter, Liav ...
Journal of international marketing (East Lansing, Mich.),
03/2020, Letnik:
28, Številka:
1
Journal Article
Recenzirano
This article analyzes how political leaders communicate with their target audiences and examines whether they adopt a country-specific communication persona, or react to the global media-intensive ...environment by offering more universal communication. Politicians communicate through presentational (e.g., social media) and representational (e.g., press) outlets, and the compatibility between these outlets represents the leader’s effectiveness in transmitting the desired messages to the audience. The authors of this study suggest a theoretical framework that classifies public figures’ communication along two dimensions: universality (particular–universal) and media compatibility (low–high). The authors used language processing tools to study the sentiment, topic mixture, and use of pronouns by 61 global world leaders in more than 300,000 messages from the leaders’ Twitter accounts and press articles. The results show a high level of universality across political leaders in sentiment, topic mixture, and pronoun usage. The media compatibility is high, with Twitter being slightly more positive. Most leaders fall within the categories of Cosmopolitan Antagonist (high universality, low media compatibility) and Global Icon (high universality, high media compatibility). Overall, the sentiment of their communications is positive. Popular topics include diplomacy, economy, corruption, and the Arab world. No significant relationship was found between the sentiment or communication topics and country characteristics.
How does ChatGPT, and other forms of Generative Artificial Intelligence (GenAI) affect the way we have been conducting—and evaluating—academic research, teaching, and business practice? What are the ...implications for the theory and practice of marketing? What are the opportunities and threats, and what are some interesting avenues for future research? This editorial aims to kick off an initial discussion and stimulate research that will help us better understand how the marketing field can fully exploit the potential of GenAI and effectively cope with its challenges.
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