Information and Knowledge Management using ArcGIS ModelBuilder

Sharina Tajul Urus, Alemayehu Molla and Say Yen Teoh
positive or negative manner. The remaining part of this paper is organised as follow. Next, a brief
literature provided in the next section. Then, we outline and discuss the methodology. Following that,
we describe the cases and feral systems in the finding section. The final section concludes the paper
with discussion and summary.
2. Background
To conceptualise feral system, we should first define it. Startlingly, there is imprecise definition of feral
system used in the general IS field and specific context of ERP research. The review from previous
literature have identified three basic concepts used to define the Post-ERP feral systems – “Feral
systems”, “Workaround systems” and “Shadow system”. The definition of the three basic concepts is
illustrated in the above table (Table 1).
Table 1: Summary of feral system conceptualisation
Reference Terminology Definition
Houghton and Feral System “An information system (computerized) that is developed by individuals
Kerr (2006)
or group of employees to help them with their work, but is not condoned
by management nor its part of the corporation‘s accepted information
technology infrastructure. Its development is designed to circumvent
existing organizational information system”.
Poelmans Workaround “A coping strategy that deviates from strategies that have been defined
(1999)
System in the work flow system (WFS). End users work around the system to
save the time or efforts or to avoid the limitations of the WFS.”
Behrens and
Sedera (2004)
Shadow
System
“Systems which replicate in full or in part data and/or functionality of the
legitimate system in the organization”.
While feral, shadow and workaround systems are sometimes used interchangeably, Houghton and
Kerr (2006) argue that the feral systems are not similar to workaround. This is because workaround is
created with the intention to bypass a recognized problem and to fix the problem temporarily
(Koopman & Hoffman 2003; Poelmans 1999). On the contrary, feral systems are the deliberate
attempts to permanently circumvent a fully functional and operationally sound system. Nevertheless,
while all feral systems can be classified as workaround systems, the reverse is not true. As such,
workaround systems become feral systems only when they are user created and their usage is
outside the formal information systems. For example, Koopman and Hoffman (2003) reported how
end users created a workaround system by modifying input data and operations to compensate the
deficiency of a formal system.
One notable observation from the literature is that, the concept of “system” in feral system has not
always been clear. Some authors proposed feral system as ‘system’ or ‘information system’(Behrens
& Sedera 2004; Houghton & Kerr 2006) , while other define it as strategy (Poelmans 1999). The
‘system’ also sometimes refers to a fully functional information system which has been created
outside accepted ERP systems (Behrens 2009; Houghton & Kerr 2006) or the use of personal
software like Microsoft Excel and Microsoft Access (Houghton & Kerr 2006; Kerr, Houghton &
Burgess 2007). One thing obvious about the previous studies on feral systems is that there is hardly a
clear framework to identify and classify feral systems. In order to conceptualise feral system definition,
there are few relevant questions to illustrate its concept. These questions surround issues such as:
Who sanctions them? What it is? Why it is exists? Answers from these questions will chart a direction
to the development of feral system taxonomy. Thus, this study is the first to use both previous studies
and case evidence to define feral system classification taxonomy.
3. Research method
This research utilised qualitative research approach using exploratory multiple case studies.
Exploratory case study is useful for studying complex phenomenon in their natural setting and
appropriate for new topic areas (Eisenhardt 1989). Four large organisations from Malaysia that have
implemented ERP systems were approached. Three agreed to participate, which we will refer here as
Case A, B and C. Data were collected through face-to-face interviews with 30 interviewees over the
period of 3 months from 15 th March 2010 until 15 th June 2010. Each interview lasted between 1 hour
to 1 ½ hours. The interview questions were open ended in nature with additional questions expanding
on emerging themes. Table 2 below provides a summary of interviewees’ profile.
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