Gaining insight from professional online social networks to support business decisions
Melendez Esquivel, A.I.
MetadataShow full item record
Online social networks are a technological phenomenon that has affected the communication dynamics of modern society. From the way people interact with friends and colleagues, to how companies use them to market products or recruit new personnel. Exploiting the datasets generated by online social networks has captured the attention of companies as they provide new means to understand and communicate with society. Current developments for exploiting these datasets focus on accessing people to support marketing, advertisement and recruitment practices, but little is known on how to support core organizational functions, e.g. in employee development, project sales and delivery, and other core processes. Research and business applications that make use of these datasets to improve business decision making affecting these processes are scarce, and understanding the challenges and value proposition of integrating these datasets into enterprise information systems is unclear. By designing, developing and implementing a prototype system, an understanding of this value proposition was created. The system integrates LinkedIn profile data to extend the data at hand and improve employee development and organizational planning processes. In addition, an expert finding capability based on the data set generated by the system enabled support for activities in project sales, delivery and technical support. The prototype was validated by means of a single case study performed with a software services business unit at an IT services company. The biggest challenge concerned the reliability of the dataset, which was solved by mapping the user generated data to a company validated context. This enabled an expert finding capability that provided support for activities pertaining to the core operational processes of the case study business unit, e.g. team conformation, human resource allocation problems, tender requirements checks and other related activities. The implications of this work provide future researchers with a better understanding of the challenges and value proposition presented by the approach. An alignment model exhibits how the prototype provoked an understanding of the integration of online social networks in processes and activities that extend the current state of scientific knowledge and business applicability.