Leaders that bind: the role of network position and network density in opinion leaders' responsiveness to social influence

PurposeThe purpose of this present study is to investigate how opinion leaders' responsiveness to social influence varies with network positions (i.e. degree centrality and brokerage) and network density in new product diffusion networks.Design/methodology/approachThis study collected data based on a sociometric network survey. Hierarchical moderated regression and hierarchical linear modeling analyses were used to test the moderating effects of degree centrality, brokerage and density on the relationship between opinion leadership and susceptibility to social influence.FindingsThis study documents the significant moderating roles of network positions and network density in the relationship between individual influence (i.e. opinion leadership) and susceptibility to social influence. Interestingly, this study shows that the significant moderating effects of degree centrality and brokerage hold for opinion leaders' responsiveness to informational social influence, whereas that of network density holds for opinion leaders' responsiveness to normative social influence.Research limitations/implicationsThis research sheds light on the network structural characteristics under which opinion leaders would be differentially responsive to social influence (i.e. informational and normative influence) from others.Practical implicationsThis research provides marketing managers with insights into leveraging social influence by activating opinion leaders through existing network ties in new product diffusion networks.Originality/valueAlthough opinion leaders are generally less susceptible to social influence from others than nonleaders, this research finds that, under certain network conditions, opinion leaders would be equally responsive to social influence from their peers.

Consumer susceptibility to social influence in new product diffusion networks: how does network location matter?

Purpose This study aims to empirically investigate how susceptibility to social influence in new product adoption varies with one’s structural location in a social network. Design/methodology/approach The social network data were collected based on a sociometric network survey with 589 undergraduate students. Social network analysis and ordinary least squares regression analyses were used to test the hypotheses. Findings This study finds that consumers with high degree centrality (i.e. hubs) who have a large number of connections to others and consumers with high betweenness centrality (i.e. bridges) who connect otherwise distant groups in social networks are both less sensitive to informational influence from others. More importantly, the authors find evidence that consumers with moderate levels of degree/betweenness centrality are more susceptible to normative influence and status competition than those with low or high degree/betweenness centrality. The inverse-U patterns in the above relations are consistent with middle-status conformity and anxiety. Research limitations/implications This research complements social influence and new product diffusion research by documenting important contingencies (i.e. network locations) in consumer susceptibility to different types of social influence from a social network perspective. Practical implications The findings will assist marketers to leverage social influence by activating relevant social ties with effective messages in their network marketing strategies. Originality/value This research provides a better understanding of the mechanisms driving susceptibility to social influence in new product diffusion.

Nonlinear Dynamic Analysis of New Product Diffusion considering Consumer Heterogeneity

When a new product enters the market, individual consumers’ decision-making behavior and purchase time are uncertain. Based on the dynamics of epidemic transmission theory and agent modeling technology, this study proposes a new coupling model through the combination of the improved SEIR epidemic model and the heterogeneous agent model. This model considers consumer heterogeneity resulting from three aspects in consumers’ sensitivity, network topology, and considerations of information flow received. It aims to analyze how consumer heterogeneity affects the scale and speed of new product diffusion. The proposed model showed that consumers’ characteristics and behavior combination at the microlevel lead to the diversity of nonlinear diffusion curves at the macrolevel for new products. Moreover, a pilot study is conducted to simulate this model and examine how to estimate the model’s parameters using aggregated data about film products. The pilot study results suggested that different consumer characteristics and behavior combinations affect the scale and speed of new product diffusion to varying degrees. In different scenarios, there were significant differences in the influence of the degree of consumer heterogeneity on diffusion, accompanied by the occurrence of threshold. The results of the empirical analysis in this study are in line with reality.

PSO Based Grey Bass Model for Simulating New Product Diffusion

The Bass model is one of the basic models for new product diffusion analysis. But the Bass model requires a large quantity of raw data to determine parameters of Bass model and this model also uses the potential capacity of market based on the subjective experience. To solve the problem of necessity of large raw data of Bass model, Wang put forward the Grey Bass model. Wang used non-linear least square (NLS) method to find the parameters of Grey Bass model and to assess the potential capacity of market. In the present paper a more appropriate method for Grey Bass equation is offered which estimates potential capacity of market even if the sample size is small. The proposed model is based on the minimization of sum of square of error between actual and predicted data using Particle Swarm Optimization (PSO) technique. Using the case study data, as used by Wang, the accuracy of the improved method is investigated. The results show that the mean absolute percentage error (MAPE) in the present case is 6.52 % compared to 7.93% reported by Wang.

The business model of Chinese movies

Purpose The motion picture industry is a cultural and creative industry. Unlike its US counterpart, the Chinese motion picture industry is still developing. Therefore, learning from the US market, the purpose of this paper is to analyze the business model of Chinese movies from the perspective of new product diffusion. Design/methodology/approach Based on 66 movies released in the US and 21 movies released in China, this paper first compares the diffusion curves of Chinese and US movies through the movie life cycle and box office trends. Next, it analyzes the moviegoing behaviors of Chinese and US audiences based on the innovation and imitation coefficients in the Bass model. Finally, it compares the attention to information of Chinese and US audiences from the perspective of interpersonal word-of-mouth (WOM). Findings In the USA, a movie’s highest weekly box office is usually in its opening week, followed by a weekly decline in revenue; in China, there is no difference in box office performance between the first two weeks, but a weekly decline in revenue similarly follows. US audiences pay more attention to advertisements for movies than WOM recommendations, while Chinese people pay more attention to WOM recommendations. Neither the Chinese nor the US market differs in the volume of WOM between the first week before release and the opening week, and these two weeks are the most active period of WOM in both markets. Practical implications During the production phase for Chinese movies, we should satisfy opinion leaders’ needs. During the distribution phase, we should not only focus on market spending before the movie’s release, but also increase market spending in the opening week. During the theater release phase, we should stimulate WOM communication between moviegoers and thereby attract many more opinion seekers. Originality/value Few studies have investigated the Chinese motion picture industry from the perspective of new products. This paper compares and analyzes the diffusion of Chinese and US movies using the Bass model of new product diffusion, providing systematic theoretical guidelines for the commercial operation of the Chinese motion picture industry.

Can search engine data improve accuracy of demand forecasting for new products? Evidence from automotive market

Purpose The purpose of this paper is to analyze the relationship between new product diffusion and consumer internet search patterns using big data and to investigate whether such data can be used in forecasting new product diffusion. Design/methodology/approach This research proposes a new product diffusion model based on the Bass diffusion model by incorporating consumer internet search behavior. Actual data from search engine queries and new vehicle sales for each vehicle class and region are used to estimate the proposed model. Statistical analyses are used to interpret the estimated results, and the prediction performance of the proposed method is compared with other methods to validate the usefulness of data for internet search engine queries in forecasting new product diffusion. Findings The estimated coefficients of the proposed model provide a clear interpretation of the relationship between new product diffusion and internet search volume. In 83.62 percent of 218 cases, analyzing the internet search pattern data are significant to explain new product diffusion and that internet search volume helps to predict new product diffusion. Therefore, marketing that seeks to increase internet search volume could positively affect vehicle sales. In addition, the demand forecasting performance of the proposed diffusion model is superior to those of other models for both long-term and short-term predictions. Research limitations/implications As search queries have only been available since 2004, comparisons with data from earlier years are not possible. The proposed model can be extended using other big data from additional sources. Originality/value This research directly demonstrates the relationship between new product diffusion and consumer internet search pattern and investigates whether internet search queries can be used to forecast new product diffusion by product type and region. Based on the estimated results, increasing internet search volume could positively affect vehicle sales across product types and regions. Because the proposed model had the best prediction power compared with the other considered models for all cases with large margins, it can be successfully utilized in forecasting demand for new products.

The Deterministic Model With Time Delay for a New Product Diffusion in a Market

The aim of this paper is to present and analyze a market through a nonlinear deterministic model. A firm launches a new product and devotes a fixed proportion of sales to advertising, while customers go through a three stage adoption process with some delay on the effect of advertisement. The mathematical model is described by three nonlinear differential equations with time delay, where the word-of-mouth and advertising effectiveness are taken into account. The variables consist of the number of non-adopters (unaware of the existence of the product or the number of people who have not repurchased it), the number of thinkers (the number of people who know about the product, but they have not yet purchased it) and the number of adopters (the number of people who have purchased the product). The time delays are introduced in both purchase decisions of the thinkers and repurchase decisions of the adopters as well. The positive equilibrium point is determined and the conditions for the asymptotic stability are provided, when there is no delay. When the delay is taken as bifurcation parameter the conditions for the existence of a Hopf bifurcation are given. The critical value of the delay is found where the asymptotic stability is lost. Numerical simulations and conclusions can be found in the last part of the paper.