Making more of less: using divestitures to unlock pharmaceutical innovation.

Pharmaceutical managers have been encouraged to look to acquisitions and alliances for innovation. However, the literature warns that the capacity of a company to 'absorb' new knowledge is limited. Here, we introduce corporate divestitures as a tool for freeing up managerial attention. We build a sample of 349 companies, which announced 1784 divestitures and filed 63523 patents, over a 15-year period. We show that innovating companies that divest more produce more and improved patents, and those that divest to create corporate focus also produce more breakthroughs. In doing so, we introduce divestitures as an innovation tool, highlight the importance of the absorptive capacity of a company when discussing innovation, and add nuance to the discussion on external tools for innovation.

Mining and analysing online social networks: Studying the dynamics of digital peer support.

In recent years, the rapid growth of user-generated content has led to much research evaluating the patterns of online information exchange. These studies demonstrate that online communities are valuable data sources which provide rich, longitudinal data that would otherwise be difficult, if not impossible to access. Given the increased research interest, mining and analysing online social networks has become an important research domain, encompassing a variety of approaches. To analyse the large number of observations commonly found in online communities, we propose to first mine the data using a so-called Webscraper and then combine Social Network Analysis (SNA) with Sentiment Analysis to explore both content and relationships. The hands-on approach described in this article is targeted at researchers without a background in technical disciplines. Instead of focusing on some of the specific algorithms that facilitate the mining and analysis of online data, we describe how to use and combine out-of-the-box solutions to collect and analyse the online network data. Moreover, we document the steps taken and present important lessons learnt throughout the process of collecting and analysing data from an online health community with 108,569 registered users who contributed to 197,980 discussions with a total of 484,250 replies. In sum, our method proposes to:•Extract all relevant data from an openly accessible online community using a Webscraper.•Determine and visualise the relationships between users and the properties of the social network as a whole using Social Network Analysis.•Conduct Sentiment Analysis to detect the emotional tone of the online contributions, and to possibly infer further variables from the text such as the personality characteristics of users.

Moving motives: How past and present strategy influence the market.

We investigate the market's reactions to serial acquirers that switch strategy. We collect data on 204 serial acquirers in four high tech industries, and use March's explore-exploit framework, to classify these firms' 1,415 acquisitions. We then distinguish, for example, exploration-based acquisitions, conducted after a series of exploitation-based acquisitions. Our results suggest that the market takes a portfolio perspective when reacting to an acquisition. In support of the ambidexterity literature, we show that the market responds positively to a switch from one type of strategy to another. Zooming in on the direction of the shift, we find that the market responds more positively to a switch towards exploration after exploitation, compared with the alternative. In so doing, we contribute to the literature on acquisition motives, by showing that prior announcements matter in explaining market reactions, and we contribute to the literature on ambidexterity, by showing that the market favours firms that oscillate between exploration and exploitation.

Perception of peer advice in online health communities: Access to lay expertise.

When seeking advice online about health concerns, forums dedicated to medical themes are increasingly becoming an appreciated source of information for many individuals. In online health communities, patients can ask questions or otherwise seek advice that is particularly relevant to them. While they may find some of the advice useful, other advice may be perceived as less valuable. By studying the advice-seeking, advice-giving, and advice-evaluation behaviours in one of the largest online health communities in Europe, this paper looks at what determines which advice is perceived as helpful, and why. Drawing on network theory, we analysed the interaction data of 108,569 users over twelve consecutive years based on all publicly available information of an established Q&A online health community. Utilising zero-inflated negative binominal modelling, our results show that advice received from others, who have similar predominant interests, is valued more when reaching out for lay expertise. If this advice is given by peers, who can also draw on expertise from other health areas, allowing for a combination of diverse "lay" expertise, the advice is valued even more. Advice provided by those who are quick to obtain the latest knowledge available in the larger community further reinforces these effects. Our findings offer an original view to understand the influence of lay expertise exchanged via online health communities and hold implications for both policy-makers and medical practitioners regarding their approach to patient-initiated use of social media for health-related reasons.