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On the value of mobile business intelligence : An affordance approach

Tona, Olgerta LU and Schultze, Ulrike LU (2018) 26th European Conference on Information Systems, ECIS 2018
Abstract

Mobile BI (m-BI) is an extension of BI delivered on mobile devices such as smartphones and tablets. Even though proponents of m-BI are highlighting its capabilities and outcomes, still its value-generating potential in organizations is surrounded by ambiguity. Given this uncertainty, we use an affordance approach to explore the action possibilities and benefits arising from the interaction of m-BI and users. We conduct a case study in a retail organization where m-BI has been in use for more than four years. Three affordances - cursory scanning, aligning distributed intelligence in real time and real-time performance tracking - are explored in detail based on their constitutive elements, namely, technological capabilities, user... (More)

Mobile BI (m-BI) is an extension of BI delivered on mobile devices such as smartphones and tablets. Even though proponents of m-BI are highlighting its capabilities and outcomes, still its value-generating potential in organizations is surrounded by ambiguity. Given this uncertainty, we use an affordance approach to explore the action possibilities and benefits arising from the interaction of m-BI and users. We conduct a case study in a retail organization where m-BI has been in use for more than four years. Three affordances - cursory scanning, aligning distributed intelligence in real time and real-time performance tracking - are explored in detail based on their constitutive elements, namely, technological capabilities, user intention and key differences with its closest technological rival. Each affordance is further theorized in relation to the decision making process. The affordances primarily support the intelligence and the review phase of decision-making; the design phase is minimally supported, while the choice phase is not supported. Moreover, we note the performative nature of affordances, highlighting the behavioural expectations and practices they produced.

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Please use this url to cite or link to this publication:
author
and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Affordances, Benefits, Decision-making, Mobile business intelligence
host publication
ECIS 2018 Proceedings : Research Papers - Research Papers
publisher
AIS Electronic Library (AISeL)
conference name
26th European Conference on Information Systems, ECIS 2018
conference location
Portsmouth, United Kingdom
conference dates
2018-06-23 - 2018-06-28
external identifiers
  • scopus:85061307911
language
English
LU publication?
yes
id
40c52d07-1186-4621-bd8c-7514af71990e
alternative location
https://aisel.aisnet.org/ecis2018_rp/112/
date added to LUP
2019-02-19 14:46:12
date last changed
2024-01-11 09:19:08
@inproceedings{40c52d07-1186-4621-bd8c-7514af71990e,
  abstract     = {{<p>Mobile BI (m-BI) is an extension of BI delivered on mobile devices such as smartphones and tablets. Even though proponents of m-BI are highlighting its capabilities and outcomes, still its value-generating potential in organizations is surrounded by ambiguity. Given this uncertainty, we use an affordance approach to explore the action possibilities and benefits arising from the interaction of m-BI and users. We conduct a case study in a retail organization where m-BI has been in use for more than four years. Three affordances - cursory scanning, aligning distributed intelligence in real time and real-time performance tracking - are explored in detail based on their constitutive elements, namely, technological capabilities, user intention and key differences with its closest technological rival. Each affordance is further theorized in relation to the decision making process. The affordances primarily support the intelligence and the review phase of decision-making; the design phase is minimally supported, while the choice phase is not supported. Moreover, we note the performative nature of affordances, highlighting the behavioural expectations and practices they produced.</p>}},
  author       = {{Tona, Olgerta and Schultze, Ulrike}},
  booktitle    = {{ECIS 2018 Proceedings : Research Papers}},
  keywords     = {{Affordances; Benefits; Decision-making; Mobile business intelligence}},
  language     = {{eng}},
  month        = {{01}},
  publisher    = {{AIS Electronic Library (AISeL)}},
  title        = {{On the value of mobile business intelligence : An affordance approach}},
  url          = {{https://aisel.aisnet.org/ecis2018_rp/112/}},
  year         = {{2018}},
}