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Enhancing Decision-Making Efficiency Through M-BI Use

Tona, Olgerta LU and Carlsson, Sven LU (2017) In Proceedings of the 25th European Conference on Information Systems (ECIS)
Abstract
Mobile business intelligence (m-BI) denotes the delivery of business information on mobile devices, such as tablets and smartphones. m-BI promises to support the mobile workforce in making decisions just in time. Yet, a lack of knowledge exists on how m-BI use can actually lead to improved decisionmaking performance at the individual level. This void of understanding has implications for both practitioners and academics, with the former feeling insecure about the benefits of investing in yet another technology, and the latter lacking empirical studies on technologies that challenge traditional decision support system (DSS) platforms. To this end, drawing inspiration from the information system (IS) success models and information search... (More)
Mobile business intelligence (m-BI) denotes the delivery of business information on mobile devices, such as tablets and smartphones. m-BI promises to support the mobile workforce in making decisions just in time. Yet, a lack of knowledge exists on how m-BI use can actually lead to improved decisionmaking performance at the individual level. This void of understanding has implications for both practitioners and academics, with the former feeling insecure about the benefits of investing in yet another technology, and the latter lacking empirical studies on technologies that challenge traditional decision support system (DSS) platforms. To this end, drawing inspiration from the information system (IS) success models and information search literature, a research model is designed and tested through a survey-based study. Data are collected from 357 m-BI users employed in different organisations. The study findings support our research model. Reactive search and proactive search, both of which use modes of m-BI, significantly influence decision-making efficiency, albeit with different prediction-size effects. Furthermore, mobility and time criticality (i.e. mobile work characteristics) influence proactive search, and time criticality is a predictor of reactive search. (Less)
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author
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Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
Proceedings of the 25th European Conference on Information Systems (ECIS)
publisher
European Conference on Information Systems (ECIS) at AIS Electronic Library (AISeL)
ISBN
978-989-20-7655-3
language
English
LU publication?
yes
id
02e2ce4a-d8f8-4307-a6c1-af3b0f89ce6b
alternative location
http://aisel.aisnet.org/ecis2017_rp/30/
date added to LUP
2017-12-18 14:28:02
date last changed
2017-12-20 14:11:10
@inproceedings{02e2ce4a-d8f8-4307-a6c1-af3b0f89ce6b,
  abstract     = {Mobile business intelligence (m-BI) denotes the delivery of business information on mobile devices, such as tablets and smartphones. m-BI promises to support the mobile workforce in making decisions just in time. Yet, a lack of knowledge exists on how m-BI use can actually lead to improved decisionmaking performance at the individual level. This void of understanding has implications for both practitioners and academics, with the former feeling insecure about the benefits of investing in yet another technology, and the latter lacking empirical studies on technologies that challenge traditional decision support system (DSS) platforms. To this end, drawing inspiration from the information system (IS) success models and information search literature, a research model is designed and tested through a survey-based study. Data are collected from 357 m-BI users employed in different organisations. The study findings support our research model. Reactive search and proactive search, both of which use modes of m-BI, significantly influence decision-making efficiency, albeit with different prediction-size effects. Furthermore, mobility and time criticality (i.e. mobile work characteristics) influence proactive search, and time criticality is a predictor of reactive search.},
  author       = {Tona, Olgerta and Carlsson, Sven},
  booktitle    = {Proceedings of the 25th European Conference on Information Systems (ECIS)},
  isbn         = {978-989-20-7655-3 },
  language     = {eng},
  publisher    = {European Conference on Information Systems (ECIS) at AIS Electronic Library (AISeL)},
  title        = {Enhancing Decision-Making Efficiency Through M-BI Use},
  year         = {2017},
}