TY  - CONF
A1  - Müller, Jonas
A1  - Schuh, Günther
A1  - Meichsner, Dustin
A1  - Gudergan, Gerhard
T1  - Success factors for implementing Business Analytics in small and medium enterprises in the food industry
T2  - [Proceedings] 2020 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)
N2  - In an increasingly changing market environment, the long-term survival of companies depends on their ability to reduce latencies in adapting to new market conditions. One strategy to meet this challenge is the anchoring of data-driven decision making, which leads to an increasing use of advanced information technologies and, subsequently, to an increase in the amount of data stored. The complexity of processing these data spurred the demand for advanced statistical methods and functions called Business Analytics. Companies are, despite all promised benefits, overwhelmed with the implementation of Business Analytics as indicated by a failure rate of 65 to 80 %. This paper provides an empirically validated, multi-dimensional model that takes an integrative look at critical success factors for the implementation
of Business Analytics and based on which management recommendations can be generated. For this purpose, constructs of the model are conceptualized, before a structural equation model is developed. This model is then validated with data from 69 industrial partners in the food industry. It is shown amongst others, that the three success factors top management support, IT infrastructure and system quality are pivotal to increase the company performance.
KW  - Business Analytics
KW  - small and medium enterprises
KW  - food industry
KW  - critical success factors
KW  - structural equation modeling
Y1  - 2022
UR  - https://epub.fir.de/frontdoor/index/index/docId/1532
UR  - https://ieeexplore.ieee.org/document/9380609
SN  - 978-1-7281-5950-8
SN  - 2159-5119
PB  - IEEE
CY  - Piscataway (NJ)
ER  -