As discussed in the last lecture, social influence can have an impact on the behaviour of consumers in the online music community. But, social influence can also have an effect in other contexts. Therefore, Risselada et al. (2014) analyse the effects of social influence and direct marketing on the adoption of new, high-technology products.
Based on previous literature, the researchers expect that social influence will play a role since the decision to adopt a high-involvement product requires information gathering from different sources (Godes, 2011). They study this assumption on the basis of two research questions: (1) ‘What are the effects of social influence variables – in particular, recent and cumulative adoptions – on the adoption of a new product when accounting for the effect of direct marketing?’ and (2) ‘How do these effects and the effect of direct marketing change from the product introduction onward?’ (Risselada et al., 2014)
Figure 1 shows an overview of the conceptual framework. As mentioned, the dependent variable is the product adoption of an individual. In addition to the hypotheses, they control for sociodemographics and relationship characteristics. To study the hypotheses and aforementioned research questions, they used data from a large sample of customers from a Dutch mobile telecommunications operator. This sample was based on random selection.
This study presents a few main findings: First of all, they proved that social influence indeed affects adoption, which is what they expected. Furthermore, they found that the social influence effect from recent adoptions is positive and remains constant from the introduction of the product onward. The same accounts for cumulative adoptions. However, this positive effect decreases from the product introduction onward. Lastly, the effect of direct marketing is positive and decreases from the product introduction onward.
Although many studies have already been done about social influence and its effect, several issues remain unexplored. One example is that most studies assume that the effects of social influence remain constant from the product introduction onward (Bell and Song, 2007). This study dives deeper in these unexplored issues by providing new insights into the adoption of high-technology products by analysing dynamic effects of social influence and direct marketing simultaneously. Furthermore, this study discusses and assesses how the social influence effect varies from the introduction of the product onward. Therefore, this study fills a gap in the current literature.
Secondly, this study accounts for homophily and tie strength (the intensity and tightness of a social relationship). This is a strength since these variables could have an influence on the outcomes. They use both homophily and tie strength as weights to construct two social influence variables in addition to the unweighted ones. At the end, this research shows that homophily is an important dimension when it comes to social influence. However, this also creates a weakness, which will be elaborated more on later.
Lastly, they used random sampling for gathering the data. In this way, the sample represents the target population and sampling bias has been eliminated. This makes it more generalizable.
This study also has few limitations and weaknesses. First, in this paper, they focus on the marketing literature and do not adopt a social psychological view on social influence. As a result, the researchers do not study the mechanisms and processes that cause the influence, such as compliance and identification. They are simply not able to examine this because they do not have access to the required data. However, this could have been interesting to research since it has managerial importance. They could have somehow explained the mechanisms by providing theoretical explanations or by gaining access to more data.
Secondly, as mentioned before, the researchers used one homophily measure. The results showed that homophily has a great impact on social influence. Therefore, this research is too limited in providing a more in-depth analysis about the underlying dimensions. Since the researchers did not expect this, future research could focus more on this aspect.
Bell, D. R., Song, S. (2007), Neighbourhood effects and trial on the internet: Evidence from online grocery retailing, Quantitative Marketing and Economics, 5(4), 361-400.
Godes, D. (2011), Opinion leadership and social contagion in new product diffusions, Marketing Science, 30(2), 224-229
Risselada, H., Verhoef, P. C., Bijmolt, T. H. A (2014), Dynamic Effects of Social Influence and direct marketing on the adoption of high technology products, Journal of Marketing, 78(2), 52-68