Location
Grand Wailea, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
7-1-2020 12:00 AM
End Date
10-1-2020 12:00 AM
Description
There is a growing body of empirical studies on business ecosystems. Driven by different questions these studies typically employ a wide variety of data sources – ranging from open to proprietary, structured to unstructured – that contain a broad range of entities, relationships, activities, and issues of interest. Individually, these data sources offer the ability to investigate very targeted business ecosystem questions. However, when linked and combined these data sources can potentially open up many new lines of inquiry. The purpose of this study is to provide an overview of the scope and complexity of the business ecosystem data landscape, discuss what type(s) of information is captured in them, identify how data sources overlap and differ, discuss strengths and weaknesses, and suggest new types of analyses that could be generated when combined. In doing so this study aims to help researchers and practitioners with the data identification and selection process and stimulate novel data-driven ecosystem intelligence. The study concludes with theoretical and managerial implications.
Understanding Ecosystem Data
Grand Wailea, Hawaii
There is a growing body of empirical studies on business ecosystems. Driven by different questions these studies typically employ a wide variety of data sources – ranging from open to proprietary, structured to unstructured – that contain a broad range of entities, relationships, activities, and issues of interest. Individually, these data sources offer the ability to investigate very targeted business ecosystem questions. However, when linked and combined these data sources can potentially open up many new lines of inquiry. The purpose of this study is to provide an overview of the scope and complexity of the business ecosystem data landscape, discuss what type(s) of information is captured in them, identify how data sources overlap and differ, discuss strengths and weaknesses, and suggest new types of analyses that could be generated when combined. In doing so this study aims to help researchers and practitioners with the data identification and selection process and stimulate novel data-driven ecosystem intelligence. The study concludes with theoretical and managerial implications.
https://aisel.aisnet.org/hicss-53/os/managing_ecosystems/2