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26-29 May 2015
Europe/Berlin timezone
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04-01 - Business Analytics and Knowledge Management


Location: Fürstenberghaus
Address: Domplatz 20-22 48143 Münster Germany
Room: F3
Date: 28 May 13:30 - 15:30


Many research contributions have emphasized the importance of taking care of (big) data, information and knowledge assets for efficient and effective decision support, management, or leadership. Consequently, business analytics (BA) & knowledge management (KM) are essential for organizations’ daily business, directly influencing competitive advantage and business development in a networked society or culture. In addition to a kind of traditional organizational focus, BA & KM are more and more happening in social environments (networks). Thus, BA and KM increasingly develop the networked society by providing technologies and methods that allow for gathering, preparing, and analyzing data generated in social environments. Improved communication, optimized networks, and new business models are examples for the innovative usage of these new and various data sources (such as mobile data, sensor data, web data, social media data, and network data). This changes the way of interaction in society and the way corresponding information and communication technology (ICT) is used on the individual’s level, in or across teams as well as the organizational level and beyond. Extant BA research explores primarily organizational and technological advances to improve business performance in a continuous and iterative way. It includes exploratory data analysis techniques to develop new insights as well as descriptive data analysis techniques – often also termed business intelligence – which cover ETL, OLAP as well as related technologies to provide historical, current, and predictive views of the business. However, limited attention has been paid to individuals’ perspective focusing on personal objectives and characteristics as enabling or preventing factors to BA utilization. ‘Big data’ as a new hot topic and an enabler for innovative applications for analytics addresses many challenges which come along with increasing variety, volume, and velocity of data. Extending existing analytics beyond the organizations’ borders bares large potential for research and practice. New phenomena emerge same way as new business models do. Furthermore, the availability of practically infinite computing and storage capacity through cloud computing enables new opportunities in servitizing our networked society. There is some agreement today that knowledge in organizations is an abstract concept that is represented in manifestations such as people and knowledge networks, organizational procedures as well as digital artifacts. As organizations or knowledge workers are more and more distributed, the need for efficient management of knowledge-intensive processes becomes still higher leading to changing practices in organizations or communities. Particularly, collaboration takes place in different forms of communities (social environments) within and across organizations. Several types of IS and social software have appeared to facilitate such collaboration by providing adequate virtual rooms, bridging time and space, etc. Basically, due to the usage of social software, organizational boundaries become more blurred and knowledge could be diffused much easier. But openness and inter-organizational collaboration demand new mental models and corresponding organizational change. Organizations in particular are challenged how to best prevent knowledge loss during knowledge sharing activities. Even though, collaborative KM systems like social software support the traceability of rich and contextualized knowledge sharing activities among networked persons within and beyond organizational boundaries, it is not yet deemed ready to cover the various needs in the intra- and inter-organizational KM. Eventually, in an increasingly networked society, organizations are required to exploit relationships with other organizations and to gain benefits out of such relationships. The BA & KM track aims to promote multi-disciplinary contributions dealing with a managerial, an economic, a methodological, a cultural, or a technical perspective on BA and KM. Submissions based on theoretical research, design research, action research, or behavioral research are encouraged. We welcome both full research papers and research in progress papers.


  • Session 1
    • Popovič, Aleš (University of Ljubljana)

Timetable | Contribution List

Displaying 4 contributions out of 4
Type: Complete Research Paper Session: 04-01 - Business Analytics and Knowledge Management
Track: 04 - Business Analytics and Knowledge Management
Leveraging the benefits of business intelligence and analytics (BI&A) and improving decision quality does not only depend on establishing BI&A technology, but also on the organization and characteristics of decision processes. This research investigates new perspectives on these decision processes and establishes a link between characteristics of BI&A support and decision makers’ modes of inform ... More
Presented by Martin KOWALCZYK, Jin P. GERLACH on 28/5/2015 at 11:30
Type: Complete Research Paper Session: 04-01 - Business Analytics and Knowledge Management
Track: 04 - Business Analytics and Knowledge Management
Charities are often complex and networked, and face an increasingly demanding environment. Providing stakeholders with timely and adequate information on activities and impact is therefore challenging. Based on case studies of six UK charities, this paper finds that small/medium charities can use Enterprise Performance (EPM) systems to support providing such information, despite some challenges to ... More
Presented by Diana LIMBURG on 28/5/2015 at 12:30
Type: Complete Research Paper Session: 04-01 - Business Analytics and Knowledge Management
Track: 04 - Business Analytics and Knowledge Management
The Internet has become a critical part of the infrastructure supporting modern life. The high degree of openness and autonomy of information providers determines the access to a vast amount of information on the Internet. However, this makes the web vulnerable to inaccurate, misleading, or outdated information. The unnecessary and unusable content, which is referred to as “information waste,” ... More
Presented by Chintan AMRIT, Fons WIJNHOVEN on 28/5/2015 at 12:00
Type: Complete Research Paper Session: 04-01 - Business Analytics and Knowledge Management
Track: 04 - Business Analytics and Knowledge Management
Big Data analytics has recently fostered significant research on the influence of news sentiment in finance. This paper thus examines the effect of news sentiment on crude oil prices for different investor types according to the noise trader approach. The noise trader approach assumes the presence of informed and uninformed investors. Informed investors possess a perfect information horizon, where ... More
Presented by Stefan FEUERRIEGEL on 28/5/2015 at 13:00
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