MITS5502 Assignment 1: ERP Systems and Firm Performance Analysis

This report critically evaluates the research by Kallunki, Laitinen, and Silvola (2011) on the impact of enterprise resource planning (ERP) systems on management control systems and firm performance. The report highlights the limitations of the study, particularly the small sample size of 70 Finnish firms, which reduces statistical power and limits the generalizability of the findings. The analysis discusses the impact of the sample size on research validity and reliability, emphasizing the need for a more diverse and larger sample to accurately represent the broader population of businesses using ERP systems. The report also touches upon the influence of cultural and economic contexts on the implementation and effectiveness of ERP systems, concluding that the original research's findings may not be universally applicable without further investigation using a larger, more representative sample. The report also underscores the importance of robust research methodology and the potential biases introduced by a single-country focus.

Paper Title: Impact of enterprise resource planning
systems on management control systems and firm
performance

1st Given Name Surname
dept. name of organization
(of Affiliation)
name of institution
(of Affiliation)
City, Country
email address or ORCID

I. INTRODUCTION
To become more competitive, improve operational
performance or to attain higher efficiencies and cut
operational costs, many firms have implemented enterprise
systems; enterprise systems refer to software that offer some
solution to integrate business organizations [1]. In the article
‘Impact of enterprise resource planning systems on
management control systems and firm performance’ ,
Kallunki, Laitinen and Silvola (2011) extend research on
effects on enterprise systems implementation in
organizations on both the financial and non financial
performance of organizations [2]. More specifically, the
authors investigate the mediating mechanisms that both
formal and non formal management control systems on how
enterprise systems adoption have on the performance of
firms using data on Finnish firms. The research findings are
detailed and offer new interesting insights into the effects of
implementing enterprise systems on firm performance; both
formal and informal- however there are limitations into the
generalization of the findings to firms and the sample used,
both size and the population represented. .
II. DISCUSSION
The determination of a sample size refers to the act of
selecting the numbers of replicates or observations to be
included in a statistical sample. The sample size is a very
important aspect and feature in any empirical study where
the objective of to generate inferences covering an entire
population represented by the sample size. In practice, the
size of a sample used in research is determined by a number
of factors that include time, cost, and convenience in data
collection and the need for the sample size to have statistical
power that is sufficient for the purposes of the research [3].
The choosing of a sample size is done using various ways;
the use of experience, using the target variance for estimates
to be derived form the sample eventually used, using target
statistical test power or through the use of a given confidence
level as a guide: if a large confidence level is required, then
an equally large sample size is required. Increased precision
during the estimation of unknown parameters require larger
sample sizes and this is governed by the central limit
theorem and the law of numbers. However, in some cases,
due to strong dependence in data and the presence of
systematic errors, the increase in precision when larger
sample sizes are used is minimal [4].
In the research, the authors use a sample size of seventy
firms in Finland to represent the population of businesses
that implement enterprise systems ad how this affects their
performance. Yet the sample size has a significant effect on
the accuracy and veracity of research outcomes [5].
Computing or determining the sample size to use in research
forms part of the initial research preparation stages and is
determined by methodological and ethical indications. For
instance, if two investigations are conducted using the same
research methodology and which give equivalent results can
point to problems and give different directions when making
decisions. As such, samples should not be small and neither
should they be too large / excessive. In conducting the
research, the authors use firms from Finland alone to
represent a global population of firms implementing
enterprise systems. This already causes problems and
systematic bias in the research findings; the business
environment and other local factors affect the firms in unique
ways that are not necessarily the same case in different
jurisdictions or countries [6]. How enterprise systems affect
management control systems, financial and non financial
parameters of firm performance in the Finland is not the
same for say, forms in the USA or China. There are cultural
and social factors that are unique in different locations and
these will influence how enterprise systems impact
organizational performance for both financial and non
financial metrics.
The issue of sample size and its calculation has become
an important and overwhelming topic in scientific research;
samples should neither be too small or too large, and must be
reasonably representative of the population it represents [7].
This is because both (too small or too large) because both
result in significant limitations in research and can result in
compromises in the findings and inferences made from the
research. In their research, Kallunki, Laitinen and Silvola
(2011) use a sample size of seventy firms from Finland;
while there is effort to use firms of different sizes and age,
the sample size, based on the population it represents is small
and insufficient to represent the entire population of
businesses implementing enterprise systems [8]. For an
empirical research as the one undertaken, this sample size
has the impact of decreasing the statistical power and so
adversely impacting the findings from the research. The need
to have the right and representative sample size when
conducting research is important and this is understandable
the findings from research are usually used in decision
making and in making generalizations about the topic of
research with regard to the entire research population [9]. For
instance, how would the findings of the research be suitable
for use in the Australian context?
The researchers use a general topic Impact of enterprise
resource planning systems on management control systems
and firm performance; however, the sample is composed
entirely of firms from Finland. Either the research topic
should have been limited to Finnish firms or the researchers
should have used a large sample size [10]. The empirical
findings cover important aspects of firm performance with
respect to the implementation of enterprise systems; financial
and non financial performance as well as how these are
affected by both formal and informal management systems.
Yet the cultural, social, and economic conditions in Finland
would impact the use of non formal and formal management
systems in a manner that is different in Australia or the USA.
As such, the research findings still remain open to questions;
is the sample size large enough to represent the general
population? [11]. The answer is that the sample size used in
light of the representative population is small. Further, the
use of firms from a single country means there is no
randomization to reduce internal research bias. Conducting
the same research using a larger sample size of say 200 firms
selected random;y from different countries or regions would
likely give different empirical findings and change the
inferences made from the findings. As such, the sampling
and sample size used by Kallunki, Laitinen and Silvola
(2011) may not give the same results when the research is
replicated. Among the cornerstones of rigorous research is
research reliability and validity and using a small sample size
does little to achieve these objectives in scientific research
[12].

CONCLUSION
This paper evaluated the veracity of the research
conducted by Kallunki, Laitinen and Silvola (2011) in ‘
Impact of enterprise resource planning systems on
management control systems and firm performance’. The
empirical findings from the research have limitations given
that the sample size used is small (70 firms) from Finland-
the implication of this is that the statistical power of the
empirical research is significantly reduced and using only
Finnish firms means there is inherent bias in the sample size.
As such, the inferences made form the empirical findings
cannot be applied in a global audience without inaccuracies.
The use of a small sample size, despite the authors using
excellent approaches and hypothesis formulation, mean that
the research fails to meet the requirements for research
validity and reliability. Using the research findings in a
different region such as USA or Australia is impractical due
to the limited size of the samples used and the source of the
population sample.
REFERENCES
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support in enterprise systems success: a contingency perspective of fit
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