25,248 research outputs found
Linking business analytics to decision making effectiveness: a path model analysis
While business analytics is being increasingly used to gain data-driven insights to support decision making, little research exists regarding the mechanism through which business analytics can be used to improve decision-making effectiveness (DME) at the organizational level. Drawing on the information processing view and contingency theory, this paper develops a research model linking business analytics to organizational DME. The research model is tested using structural equation modeling based on 740 responses collected from U.K. businesses. The key findings demonstrate that business analytics, through the mediation of a data-driven environment, positively influences information processing capability, which in turn has a positive effect on DME. The findings also demonstrate that the paths from business analytics to DME have no statistical differences between large and medium companies, but some differences between manufacturing and professional service industries. Our findings contribute to the business analytics literature by providing useful insights into business analytics applications and the facilitation of data-driven decision making. They also contribute to manager's knowledge and understanding by demonstrating how business analytics should be implemented to improve DM
How do top- and bottom-performing companies differ in using business analytics?
Purpose
Business analytics (BA) has attracted growing attention mainly due to the phenomena of big data. While studies suggest that BA positively affects organizational performance, there is a lack of academic research. The purpose of this paper, therefore, is to examine the extent to which top- and bottom-performing companies differ regarding their use and organizational facilitation of BA.
Design/methodology/approach
Hypotheses are developed drawing on the information processing view and contingency theory, and tested using multivariate analysis of variance to analyze data collected from 117 UK manufacture companies.
Findings
Top- and bottom-performing companies differ significantly in their use of BA, data-driven environment, and level of fit between BA and data-drain environment.
Practical implications
Extensive use of BA and data-driven decisions will lead to superior firm performance. Companies wishing to use BA to improve decision making and performance need to develop relevant analytical strategy to guide BA activities and design its structure and business processes to embed BA activities.
Originality/value
This study provides useful management insights into the effective use of BA for improving organizational performance
A gap analysis of Internet-of-Things platforms
We are experiencing an abundance of Internet-of-Things (IoT) middleware
solutions that provide connectivity for sensors and actuators to the Internet.
To gain a widespread adoption, these middleware solutions, referred to as
platforms, have to meet the expectations of different players in the IoT
ecosystem, including device providers, application developers, and end-users,
among others. In this article, we evaluate a representative sample of these
platforms, both proprietary and open-source, on the basis of their ability to
meet the expectations of different IoT users. The evaluation is thus more
focused on how ready and usable these platforms are for IoT ecosystem players,
rather than on the peculiarities of the underlying technological layers. The
evaluation is carried out as a gap analysis of the current IoT landscape with
respect to (i) the support for heterogeneous sensing and actuating
technologies, (ii) the data ownership and its implications for security and
privacy, (iii) data processing and data sharing capabilities, (iv) the support
offered to application developers, (v) the completeness of an IoT ecosystem,
and (vi) the availability of dedicated IoT marketplaces. The gap analysis aims
to highlight the deficiencies of today's solutions to improve their integration
to tomorrow's ecosystems. In order to strengthen the finding of our analysis,
we conducted a survey among the partners of the Finnish IoT program, counting
over 350 experts, to evaluate the most critical issues for the development of
future IoT platforms. Based on the results of our analysis and our survey, we
conclude this article with a list of recommendations for extending these IoT
platforms in order to fill in the gaps.Comment: 15 pages, 4 figures, 3 tables, Accepted for publication in Computer
Communications, special issue on the Internet of Things: Research challenges
and solution
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