=Paper=
{{Paper
|id=Vol-1898/paper3
|storemode=property
|title=Task Characteristics that Fit Use of Business Intelligence
|pdfUrl=https://ceur-ws.org/Vol-1898/paper3.pdf
|volume=Vol-1898
|authors=Rikke Gaardboe,Tanja Svarre,Tom Nyvang
|dblpUrl=https://dblp.org/rec/conf/bir/GaardboeSN17
}}
==Task Characteristics that Fit Use of Business Intelligence==
https://ceur-ws.org/Vol-1898/paper3.pdf
Task characteristics that fit use of Business Intelligence
Rikke Gaardboe, Tanja Svarre, and Tom Nyvang
Aalborg University, Department of Communication and Psychology, Aalborg, Denmark
{gaardboe,tanjasj,nyvang}@hum.aau.dk
Abstract. We present a literature review that identifies a gap in business
intelligence knowledge regarding the fit between technology and the tasks
solved using the technology. We propose a model that frames the fit between
task characteristics and the use of business intelligence. The model represents
task, system, and information quality as independent constructs with task
compatibility as the dependent construct. A future quantitative study will test
the model by looking at business intelligence users and how they use
technology to perform tasks for solving problems.
Keywords: Task difficulty, task variability, Business Intelligence, Digital
transformation
1 Introduction
In many organisations, the IT manager's top priority is to handle the increasing
volume of data produced internally and externally in structured and unstructured
formats. The data must be available to analysts and decision makers throughout all
levels of the organisation because it is the foundation for future digital transformation
[1]. Some of the 25 highest-ranked transformation factors include work, coordination
and digital uses[1]. In the future, we should not regard hierarchy and horizontality as
opposites, but instead, as different and complementary ways to coordinate. The next
generation's behaviour is also reflected in new digital use as it is a generation raised
with IT. It regards the relationship between employee and company as "something-
for-something," tied in with memories of past managerial practices experienced [2].
According to Teague [1], high-quality IT systems are essential because when the
users are satisfied, then they will do their job effectively independent of their
characteristics. Therefore, in the context of the digital transformation, it is highly
relevant to research how business intelligence (BI) quality fits certain tasks
characteristics.
BI supports decision making at all levels in an organisation [3]. The top
management often uses BI to follow up on the realisation of the established
objectives. On the tactical level, BI provides a basis for decision-making about
optimisation and modifying organisational, financial, and technical aspects of the
organisation. At the operational level, BI is used for ad hoc analysis and reports
related to daily operations [4].
Task structure is one of the most interesting variables in information systems (IS)
research. First, task structure has been used to define the tasks that must be supported
by IS. Second, task structure has been used to explain IS successes [5]. Achieving the
net benefit of implementing BI, technology must be utilised and have a good fit with
the supported tasks [6]. In the field of IS, several work activity determinants
supported by IS have been identified [7]. In BI research publications, we have
identified four papers focusing on task compatibility [4, 8–10] related to IS success.
Unlike general IS research, BI research only focused on the fit between technology
and jobs and not on the dimension of examining tasks characteristics’ fit with the
technology. In this paper, we provide a research model for how task characteristics
and quality of a BI system is related to task compatibility.
2 Literature review
We conducted a systematic literature review to reveal state-of-the-art to identify the
critical success factors (CSF) for BI [11].We focused on peer-reviewed papers in the
period from 2006-2015. We used Papaioannou et. al.’s [12] search strategy covering
databases, reference lists, and citations. The queries applied consisted of two
components: one containing synonyms for the CSF and one for BI. Papers were
selected first by abstract reading. In the remaining part we read the full paper content.
Out of 336 papers and 1184 references, 29 papers were relevant to the scope of the
review. We used the Petter, DeLone & McLean [7] framework of IS success to
identify the CSFs and to analyse and map how researchers identify success in BI
systems. CSFs were considered distinct if they occurred in more than 20% of the
reviewed papers.
The findings motivating our model introduced below include: (i) the research in
CSFs has a small focus on the task compatibility as an independent factor to BI
success, which will be elaborated further in Section 3.1; (ii) as users often have access
to the source system and BI, no previous research investigated the characteristics of
the tasks supported by BI; and (iii) the most dominant factor describing BI success is
the quality dimension, either in the understanding of system quality or information
quality.
3 A Model for BI Tasks
3.1 Task
Tasks are the activities that support an organisation. A job consists of several tasks
[13]. Thus, the purpose of the use of IS is to complete tasks [14]. Also, the purpose of
implementing IS is either to automate tasks or to obtain information for the task [15].
Since there is a relation between tasks and IS, there are various antecedents of IS
success related to the task structure and characteristics [16]. In the contingency theory
literature, there is a close relation between task/fit and performance [17]. An example
of misfit is when the user wants to use information from the BI to follow-up on Key
Performance Indicators (KPI), and the data is not available [18].
In the review, we found that BI literature has not thoroughly investigated tasks as a
CSF [11]. Many researchers have investigated task characteristics and their impact on
use, and there have been various suggestions for how the concept can be
operationalized [6]. Petter, et al. [7] identified six determinants of the category task
determining IS success: task compatibility, task difficulty, task interdependence, task
significance, task variability, and task specificity. In the literature review, task
compatibility was not considered a distinct CSF, having only been investigated in four
papers[2]. Task compatibility differs from the other determinants in that the variable
examines the fit between technology and task, whereas the remainder of the
determinants describes the task itself independently of the technology. No examples
of papers investigating the remaining five determinants as BI CSF’s were found in the
review.
The task characteristics construct is divided into several variables. Task
interdependence is specifying the extent to which the task supported by BI depends on
other tasks to be completed. Task difficulty is to what extent the task underwritten by
BI is challenging for users of the system. Task significance is the task supported by
BI and is necessary for the user’s job or other employees in the organisation. Task
variability is the degree of coherence between tasks that a person performs in
interaction with that work process. Task specificity is the level of detail of the task
[7].
3.2 BI Quality
In the literature, system quality was found to be an important parameter for BI
success [11]. According to Lee, Strong, Kahn and Wang [19], quality can be divided
into four different dimensions: intrinsic IQ, contextual IQ, representational IQ, and
accessibility IQ. Intrinsic IQ is equal to DeLone and McLeans [20] dimensions
information quality. Contextual IQ is equal to Goodhue’s [6] concept of task/fit. The
last two dimensions are equal to DeLone and McLean's system quality. Lee, Strong,
Kahn and Wang [19] do not include service quality as a quality dimension as DeLone
and McLean[21] in their Updated IS Success Model, as it is equal to the finding the
literature review.
The quality of information the system produces is referred to as information
quality [22]. It is considered an important factor when the system is being evaluated
because the process involves the production of information to be used in decision-
making processes [23]. In the review, 16 papers investigated information quality as a
factor in BI success (Gaardboe & Svarre, 2017). Thus, it can be considered a distinct
element in the BI literature. System quality is concerned with issues such as user
interface system errors, ease of use, and quality and maintenance of program code
[23]. Twenty-eight out of 29 papers in the review included system quality as a CSF
(Gaardboe & Svarre, 2017). Thus, the review finds system quality as the most well
investigated of all BI system success determinants of Petter, DeLone & McLean’s [7]
framework.
3.3 Task Compatibility
Task compatibility highlights the requirement that the information quality must be
evaluated in the context of the task. BI must have the qualities needed to complete the
user's task [6]. When these requirements are met, the system and task would add
value. The information must be relevant, timely, complete, and of an appropriate
amount [19]. This all leads to obtaining task compatibility. When BI has the proper
amount of information, then this amount of information fit the user’s needs. The
completeness is different from a suitable amount because it measures the information
including all the necessary values. The timeliness variable focusing on the
information is up-to-date for the user’s requirement. The last variable is the relevancy,
which is the information relevant to the user’s need to fulfil the task as is supported
by BI [19].
3.4 Task/BI Compatibility Model
The model presented here consists of four constructs. We divided BI quality into
system quality and information quality because system quality is an evaluation of the
BI system itself, and information quality is an evaluation of the information from BI.
The third construct is task. All construct affect task compatibility.
Fig. 1. Task/BI Compatibility Model.
Task:
- Task interdependence
- Task difficulty
- Task significance
- Task variability
- Task specificy
System quality
- Accessability
- Ease of Operation
Task compatibility:
-Understandability
- Appropriate amount
- Interpretability
- Completleness
- Concise representation
- Timeliness
-Consistent representation
- Relevancy
- Ease of Operation
-Security
- Objectivity
Information Quality
- Belivability
- Free of Error
- Reputation
4 Conclusion and Outlook
It is essential for many companies to effectively handle and utilise large amounts
of data to survive in the global competitive environment. Based on a literature review,
we developed a Task/BI compatibility model consisting of three independent
constructs: task, system quality, and information quality with a dependent construct of
task compatibility. The assumption in the model is that if tasks and technology fit
together, users will (or are more likely to) use the technology. However, at present,
we do not know how tasks fit BI.
To test the model, we will use the guidelines by Dillman [24] to construct a survey.
The purpose will be to create a questionnaire where serval variables measure each
construct. Based on existing research, we will find studies where the questions have
been used, tested and validated. The questions must be quality-assured by other
researchers before conducting a pilot study. The questionnaire must be prepared and
distributed to respondents in a web survey. We will find organisations with very
different characteristics and a major use of BI within each organisation. We will then
test the model using the PLS-SEM, which is useful for the development of theory.
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