The impact of ERP systems on firm performance

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Global Business and Economics Review, Vol. 17, No. 1, 2015

The impact of ERP systems on firm performance: the case of Greek enterprises Fotini Voulgaris* School of Management and Economics, Technological Institute of Crete, Agios Nikolaos Branch, P.O. Box 128, 72100 Agios Nikolaos, Greece Fax: +30-28410-82879 and Department of Finance and Insurance, Technological Educational Institute of Crete, Agios Nikolaos, Crete, GR-72100, Greece Email: [email protected] *Corresponding author

Christos Lemonakis Department of Finance and Insurance, Technological Educational Institute of Crete, Agios Nikolaos, Crete, GR-72100, Greece Email: [email protected]

Manos Papoutsakis Department of Finance and Insurance, University οf Portsmouth, Agios Nikolaos, Crete, GR-72100, Greece Email: [email protected] Abstract: There are contradicting results on the effect of enterprise resource planning (ERP) adoption to the profitability of firms. International evidence suggests that ERP systems are one of the important drivers of a firm’s successful performance and competitiveness. The objective of this study is to empirically investigate the impact of ERP systems on firm performance of enterprises operating in Greece under economic crisis conditions. Our sample consists of 88 firms ERP adopters and non-adopters comparing their performance with the use of ROA, ROS and ATO metrics for a period of ten years (2001–2011). The findings suggest that the performance of ERP adopters is superior to that of the non-adopters and that there exists a significant relation between firm size and financial health of ERP adopters with respect to ROA, ROS and ATO. Keywords: enterprise resource planning; ERP; firm performance; productivity paradox; economic crisis; ERP systems; Greek enterprises; global business and economics; Greece.

Copyright © 2015 Inderscience Enterprises Ltd.

The impact of ERP systems on firm performance

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Reference to this paper should be made as follows: Voulgaris, F., Lemonakis, C. and Papoutsakis, M. (2015) ‘The impact of ERP systems on firm performance: the case of Greek enterprises’, Global Business and Economics Review, Vol. 17, No. 1, pp.112–129. Biographical notes: Fotini Voulgaris is a Professor in the Department of Finance and Insurance at the Technological Educational Institute of Crete. Christos Lemonakis is a Lecturer in the Department of Finance and Insurance at the Technological Educational Institute of Crete. Manos Papoutsakis is an MSc in Business Economics Finance and Banking at the University οf Portsmouth. This paper is a revised and expanded version of a paper entitled ‘The impact of ERP systems on firm performance: the case of Greek enterprises’ presented at EuroMed Academy of Business, 5th Annual EuroMed Conference on ‘Building New Business Models for Success Through Innovation, Entrepreneurship, Competitiveness and Responsibility’, Glion-Montreux, Switzerland, 4–5 October 2012.

1

Introduction

The academic community, triggered by the growing popularity of enterprise resource planning (ERP) systems, focused its research interest in the impact of these systems on business performance. Until today, the findings have shown a mixed relationship between ERP and business performance. Some researchers believe that ERP improves performance while others have evidence it does not. Without a doubt, ERP systems offer many advantages to a business organisation. Their benefits can be widely classified into: a

efficiency gains, as direct effects of an ERP, which are usually quantifiable

b

effectiveness gains, as indirect, intangible and mostly non-quantifiable outcomes of ERP usage (Fub et al., 2007).

Firms that have not adopted an ERP system, use independent software programs for each of their departments. Those software solutions do not interface each other; as a result, they do not synchronise the processes of the firm, damaging firms’ performance and productivity. ERP systems distribute the information that is scattered across different departments of the company, synchronise the work flow, give a clear overview of the business that should be carried out, optimise decision making and improve execution speed. Taking under consideration management of expenses and asset usage, we could say that ERPs provide managers with a more efficient way in expanding the availability of the firm equipment and, as a result, decrease the costs of the plants. An ERP has the ability to increase inventory turnover and brings the manufacturing production to an optimum level, leading to an increased cash flow. At this point, we should mention that, as substantial business investment in ERPs is continuing, it is increasingly important to understand which solution is most appropriate

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for each company. Due to the complexity and enormous size of ERP systems, there are many factors which determine the success or failure of such an IT implementation. Miscommunication between the internal business IT experts and the external ERP consultants (Hit et al., 2002) insufficient training of the future users of the ERP system (Gupta et al., 2004) and insufficient alignment between ERP implementation objectives and the strategic goals of the firm (Kang et al., 2008), are only a few of the factors that a company must have in mind in order to achieve the promising ERP benefits. A succession of academics and professionals worldwide consider this topic as a very important one, mainly for three significant reasons. The first important reason is the popularity of ERP systems. Y2K problem1 and replacement of the traditional IT applications were the main reasons for the adoption of first ERPs from large manufacturing companies. Next in the line, small- and medium-sized companies adopted ERPs which now had more to offer such as sales-force automation, customer service and demand planning software (Escalle and Cotteleer, 1999). After them, financial services become enthusiasts of ERPs, while higher education-specific ERP systems are used by universities and colleges (Savarese, 2003; Spathis and Ananiadis, 2004). Moreover, healthcare organisations and hospitals start to make use of ERP systems (Stefanou and Revanoglou, 2006). As a result, today there are industry-specific ERP solutions ready to satisfy every customer in every industry or industry segment (Beheshti and Beheshti, 2010). The second major reason, is the really long list of the benefits that ERP is claimed to provide. Gupta et al. (2004) argue that “The integrated solution, known as ERP, promises benefits from increased efficiency to improved quality, productivity, and profitability. Installation of an ERP by an organization has many benefits. Lowered lead times, leaner hierarchical structure, increased efficiency and better decision making are some of the direct benefits, while better customer satisfaction, good corporate image are some of the intangible benefits that accrue”. The third reason is the fact that there are many examples of negative ERP effects on businesses. Gupta et al. (2004) are referring to the cases of Volkswagen, Whirlpool, Hershey Foods and Fox Meyer. More specifically, in Volkswagen, the adoption of ERPs leaded to significant delays, in Whirlpool and Hershey Foods the result was massive distribution problems and Fox Meyer reached into bankruptcy. Based on the above, we could mention that the implementation of an ERP is a big challenge for many organisations up to today and sometimes, it might simply be a waste of money if installed before the company is really ready for it. Therefore, it is of great importance to review the relationship of ERP and firm performance. The principal objective of this study is to empirically investigate the impacts of ERP systems on firm performance of enterprises operating into the geographical area of Greece. In order to do so, accounting measures used in previous studies (Balakrishnan et al., 1996; Barber and Lyon, 1996; Stedman, 1999; Mabert et al., 2000) such as return on assets (ROA), return on investment (ROI), return on sales (ROS) and asset turnover (ATO), will be used for evaluating firm performance. During the time period of the research Greece is undergoing a severe depression, which has affected the performance of all firms, both ERP adopters and non-adopters. Over the past six years (2006–2012), while central government expenditures increased by 87%, revenues grew by only 31%, leading to budget deficits. Some of the main causes of the country’s deficit are a large and inefficient public administration, costly pension and healthcare systems and tax evasion. It is believed that high relative wages and low


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productivity as a primary factor of the Greek industry’s suffering. Wages in Greece has increased at a 5% annual rate since the adoption of the euro, and this is double the average rate in the Eurozone. Moreover, Greek exports to its major trading partners grew at 3.8% per year, which is half the rate of those countries’ imports from other countries.

2

Literature review and hypotheses testing

2.1 Interaction of ERP systems and firm performance The general term ‘IT’, information technology, can be used in order someone to refer to ERP systems. What is the exact relationship between IT and the performance of a firm is a major topic that concerned researchers for quite a long time. According to Pavlou et al. (2005) “previous literature has not conclusively shown that IT investments have a positive effect on either firm or process performance”. There is a number of researchers that believe in the positive relationship of IT and business performance, however there are others arguing that investments in IT (or ERP specifically) do not contribute to improved financial performance. We could hypothesise, as Elragal and Al-Serafi (2011) do, that “there is a mixed result when analyzing the effect of IT on business performance”. Although according to the theory, IT investments are supposed to enhance productivity, first empirical research on the field (between 1980 and 1990) showed that there were no additional productivity gains, for those companies that invested in IT. The phenomenon is called ‘productivity paradox’. However, recent research findings indicate that IT actually can lead to productivity improvements (Sudzina et al., 2011; Maroofi et al., 2011). Researchers tried to find the root of this problem and identify possible factors, which can lead to a positive relationship between IT and business performance. Such factors were found to be organisational change, innovation and increased employee skills (Pilat, 2004). False measurements of output to measure productivity, measurements done before the long payoff time until when returns on IT investments accrue, economy-wide measurements errors due to rearrangements of output, and mismanagement (Hamilton and Asundi, 2008) are possible factors for a negative relationship. A plausible also explanation to productivity paradox could be the fact that the prices drop right after an innovative technologies adoption and demand increases as a result of price sensitivity (Eliashberg and Chatterjee, 1985). Some other factors that can influence the financial performance of adopters are competitive intensity, industry heterogeneity, demand uncertainty, and adoption rate of competitor firms. On the other hand, the results of Hitt et al. (2002) were very promising since according to them, during an ERP implementation, the financial performance of a firm increases. According to Madapusi and D’Souza (2012), the more ERP modules implemented by a firm, the more strengthened its performance will be. Velcu (2005) empirically investigated if the successful ERP adopters have a higher financial performance comparing to the less successful ERP adopters. The idea was that a less successful adoption can prevent the efficiency of assets utilisation and business processes. In order to measure the financial performance, the following indicators were used: ROA, ROI, profit margin, assets turnover, capital turnover, and the

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ratio wages / total costs. The findings showed no significant difference in the financial performance change after implementation between the two groups of firms as far as ROA and ROI are concerned. However, successful ERP adopters seem to have better efficiency benefits than the less successful ERP adopters, in terms of Assets turnover and Capital turnover, during the first two years of the ERPs implementation. Another study that examines the effect of ERP implementation on firm performance is that of Hunton et al. (2002). The researchers proved that firm which had implemented ERP systems had better performance than those which had not. What should be highlighted is that, the difference in firm performance between adopters and non-adopters is due to the fact that the performance of the former remained fixed and the performance of the latter reduced. It seems that the adoption of IT can or cannot enhance performance but in each case “the performance of non-adopters would be expected to deteriorate by comparison in a competitive marketplace” (Hunton et al., 2003). As a result, as Hunton et al. (2003) concluded with, we should not necessarily expect to prove pre- to post-adoption financial gains for firms that have implemented ERP systems. However, we strongly believe that firms that have not adopted such a system are going to perform worse than the adopters. And that brings our first hypothesis (alternate form): H1

Long-term performance of ERP adopters will be higher than non-adopters.

2.2 Correlation of ERP systems with size and financial health of a firm It could be claimed that large firms spend much more money in order to buy and implement an ERP system than small firms do. The truth is that since big firms have access to high levels of resources can pay out large amounts of money in order to buy an expensive, highly integrated ERP system. A smaller firm is more likely to choose a more affordable ERP system. However, it seems that the adoption of such a system is a heavy burden for small enterprises. According to Mabert et al. (2000) the implementation cost for a very small company is 13.65% of its revenue while the same proportion for a very large firm is only 0.82%. We could conclude that the more resources a company possesses the better it can handle the problems that may occur from an ERP implementation. As far as financial health is concerned, we could say that an unhealthy firm needs an ERP adoption in order to become a healthy one. Such a firm needs improvements in many areas and these improvements are what an ERP system has to offer. That was the conclusion of Khurana and Lippincott (2000). A company that is already efficient has little room for improvement. However, this is not the case for the relatively small firms. A small firm that is not healthy will take advantage of the ERP-benefits and will become healthy. On the other hand, a small firm which is already healthy will use an ERP system and will become bigger. As Hayes et al. (2001) showed markets have a more positive reaction to ERP announcements made by small and healthy companies than by small and unhealthy ones. In a later piece of work, Huang et al. (2009), unlike with earlier studies of Hitt et al. (2002), were focused on the benefits of an ERP adoption that occur in the long term. They used a sample of 25 companies operating in Taiwan, which had implemented ERP packages. Because of the implication of the ERP systems, their benefits can be seen four or five years after their implementation. Based on their empirical evidence, the


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researchers claimed that business process, process efficiency, and profitability increased. In more detail, their main results are: 1

big firms enhance their business process since they enhance their process efficiency and financial performance

2

medium-sized firms raise their operating income only in the first five years

3

small ones do not show any improvement.

Their views are consistent with a previous research work of Liu et al. (2008). As a result, we conclude with one more hypothesis, which was made also by Hunton et al. (2003): H2

Positive relationship between firm performance and financial health exists in small firms which have implemented an ERP system.

For Greece, there are very few studies on the effect of ERP systems on firm performance. An interesting study conducted for Greece is one by Stefanou (2001), who argues that ERP systems have a wide range of benefits. According to the author, financial measures such as net present value (NPV), internal rate of return (IRR), ROI, and payback in time ‘are not alone sufficient to support ERP justification’. There are three reasons for this phenomenon: 1

there is benefits that are not easily identifiable

2

there are others that although are identifiable, they are not quantifiable and finally

3

there are benefits that emerge not from the use of ERP system but from the organisational changes proposed by ERP.

Hence, the evaluation of ERPs has to be both quantitative and qualitative. The paper also suggests a framework for the selection process of ERP software and the associated costs and benefits. Stefanou and Revanoglou (2006) described and evaluated an ERP implementation in Papageorgiou Regional General Hospital and found that there are many benefits in better decision making, channelling of information, etc. Kanellou and Spathis (2011) tried to discover the accounting benefits for business firms which resulted from ERP adoption. They resulted that there were many accounting benefits but no reduction in personnel. Galani et al. (2010) tried to find differences between technical and business led firms based on questionnaires. They found that there are benefits from ERP implementation which lead to cost reduction and improvement in tactical decision making. Argyropoulou et al. analyses the frameworks, methodology and preliminary findings from 40 SMEs in Greece of various industries. The study found that there are differences on how an SME and a large enterprise perceive an ERP system adoption and proceeds to its implementation. The results indicate that factors such as unawareness, unskilled personnel, resistance to change, balk ERP implementation in SMEs. Small and medium Enterprises use ERPs mainly for their finance and accounting functions. The CEO’s role is significant in ERP implementation for SMEs. The above mentioned empirical research focused on costs and benefits of the ERP implementation in Greek firms-based mainly on questionnaires and qualitative characteristics. Moreover, they were mainly case studies or based on a small sample size.

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Emphasis was placed on the difficulties of ERP implementation. Our study is the only one so far that investigates the impact of ERP implementation on the profit performance and efficiency of Greek firms, for a long time period (ten years), covering also the severe depressionary economic conditions in Greece, with the use of panel data econometric techniques and financial metrics. The study is the only one that uses financial performance accounting metrics as control variables to the ERP adoption, investigating their effect on firm profitability and efficiency.

3

Research methodology

3.1 Sample selection According to Madapusi and D’Souza (2005), it seems that, regarding the manufacturing industry, large firms are the first ERP adopters and smaller enterprises use small scale ERP systems only when and if they become available. Moreover, large enterprises are more likely to bear the weight of the capital and time investment needed for an ERP implementation (Akkermans and van Helden, 2002). Therefore, we conducted a study on the largest companies of Greece, which are most likely to be ERP adopters. According to the EU definition of the small and medium-sized enterprises, large companies are considered those with more than 250 employees and turnover more than €50 m or total assets of more than €43 m. We included ERP adopters and non-adopters in our sample, to control also for macroeconomic factors that influence the business performance of the sample firms (Anderson et al., 2011; Hunton et al., 2003). The firms in the sample belonged to the service sectors (food and beverages, transportation, clothing, computers, supermarkets and department stores, oil, gas and pharmaceuticals), manufacturing sectors (Food and beverages, pharmaceuticals, tobacco, electrical appliances, metallic products, printing and publishing, chemicals, agricultural, etc.) and construction. The period covered is from 2001–2011 separated into two sub periods, 2001–2009 and 2009–2011. Most of the firms (64) employed from 150 to 250 employees and 47 firms with more than 250 employees. For our financial data we used the database of ICAP Hellas S.A., a private database and research company in Greece. Financial ratios are used as variables accounting for the financial performance of the sample firms. Since it can take several years for a company to enjoy the benefits of an ERP implementation, we included in our sample only firms for which financial data for at least three years before ERP implementation were available in the database of ICAP. Due to our goal to examine the long-run affect of ERPs on firm performance, we chose also firms for which financial data for six years after ERP implementation were available in the database of ICAP. Since there is no database with information about ERP adoptions in Greece we conducted a telephone survey to the IT managers of the sample firms, in order to find out if the firms had adopted an ERP system or not. Due to the low response of the telephone survey and the lack of data for some of our respondents, we finally managed to have a sample of 48 large firms (over 250 employees) that had adopted an ERP system and 40 firms non-adopters, a total of 88 firms. The non-adopters were chosen from the same industry sectors as those of the ERP-adopters.


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3.2 Regression model As we have mentioned before, the main goal of our research is to examine the impact of ERP adoption on firm performance. In order to do so, we divided performance, according to Hunton et al. (2003), into two time periods: 1

firm performance before the ERP adoption – pre-adoption

2

firm performance after the ERP adoption by – post-adoption. The year of ERP adoption for each firm, was identified as year t0.

The pre-adoption period covered three years (t–3 to t–1) while the post-adoption period covers three years (t+1 to t+3). Additionally, we run the model using a second post-adoption period which covered the fourth, fifth and sixth year following the year of the ERP implementation (t+4 to t+6). The regression model used in order to test our first hypothesis is an extension of the one used by Hunton et al., (2003): Post_Ratio = a0 + a1 Pre_Ratio + a2 ERP_Adoption + a3 Age + a4 Size + a5 Z -score + e

where Post_Ratio is the firm performance after the ERP implementation and Pre_Ratio is the firm performance before the ERP implementation. ERP_Adoption is a dummy variable that takes the value 1 if the firm has adopted an ERP system and the value 0 if the firm has not. Age is the difference between the year 2011 and the foundation year each firm, Size is measured in terms of the number of firm’s employees, Z-score is an index that represents the financial health of the firm and e is the error term. The model was used as dependent variable each of the three ratios, ROA, ROS and ATO measuring firm profit performance according to literature. The average of these ratios was used over a period of three years, to calculate Post_Ratio and Pre_Ratio for each firm. With the above regression model we examined the differences between firm performance of the pre-adoption and the post-adoption period. Moreover, this model allows us to control for the pre-adoption performance of each firm. For the Z-score index we used the Altman’s (1968) model. According to this model Z = 1.2 X1 + 1.4 X2 + 3.3 X3 + 0.6 X4 + 1.0 X5, where coefficients X1, …, X5 represent variables of financial performance of the firm, as explained in Table 1. Table 1

Altman’s Z-score model

X1 = Working capital / Total assets X2 = Retained earnings / Total assets X3 = Earnings before interest and taxes / Total assets X4 = Market value of equity / Book value of total liabilities X5 = Sales / Total assets Z = Overall index or score Source: Altman (1968)

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Since two different post-adoption periods were used, two different Z-score indexes were calculated, one for each period. The Z-score indexes represent the average of the three years of each period. Furthermore, a t-test of means among ERP adopters and non-adopters was used in order to evaluate the financial performance of ERP adopters vs. the non-adopters, during the first and the second post ERP adoption period. For the Post_ROS model, basically 2009–2011 periods, 384 total panel (unbalanced) observations were used. For the Post_ATO model, 2009–2011 period, 412 total panel (unbalanced) observations were used and for the post ROA model, 2009–2011 periods, 420 balanced observations were used.

4

Research results

4.1 Results for the first hypothesis In order to test our first hypothesis we used t-tests of means to find if the performance of ERP adopters was better than ERP non-adopters. The period of the study is from 2001 to 2011. Since we wanted the firms in the sample to have three years before ERP adoption, plus three years after ERP adoption, for post 1 and 3 additional years after the post1 period for post 2 period, the periods after ERP adoption were separated to 2004–2008 for post1 and 2009–2011 for post 2. However, it should be noted that in the post 2 period, Greece was under severe depression and all firms performed very badly. The macroeconomic environment should therefore be taken into consideration in explaining the results of the study. Table 2

Firm performance of ERP adopters and ERP non-adopters Panel A: pre- and post-adoption means for ERP adopters (n = 48)

Variables

Pre

Post 1

Post 2

Pre vs. post 1

Pre vs. post 2

ROA

19.86201

9.568819

9.316111

P = 0.013**

P = 0.005***

ROS

3.631076

1.201458

0.022431

P = 0.081*

P = 0.029**

ATO

4.297569

4.688194

3.352465

P = 0.353

P = 0.111

Panel B: pre- and post-adoption means for non-ERP adopters (n = 40) Variables ROA

Pre

Post 1

Post 2

Pre vs. post

Pre vs. post 2

20.97537

13.84943

–13.4922

P = 0.067

P = 0.006*

ROS

–1.4376

–0.78557

–9.13354

P = 0.440

P = 0.098

ATO

6.830447

4.440366

4.24874

P = 0.081

P = 0.075

Notes: ***, **, *statistically significant at 1% 5% and 10% respectively (two-tailed). For all the variables in the table means are provided. Pre refers to the time periods –3 through –1. Post refers to the time periods +1 through +3. Post 2 refers to the time periods +4 through +6.

The results of the t-tests are shown in Table 2. Table 2 shows the means of each financial performance ratio: 1

ROA

2

ROS

The impact of ERP systems on firm performance 3

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ATO for: a three years before ERP adoption (pre) b three years after ERP adoption (post 1) c the 4th, 5th and 6th years period after ERP adoption (post 2).

Table 3

t-test for equality of means of ERP adopters and ERP non-adopters t

p

Pre_ROA

1.156

0.25100

Pre_ROS

–0.90861

0.36609

Pre_ATO

1.337543

0.18457

Post_ROA1

–2.42755

0.01729*

Post_ROS1

–3.07351

0.00283**

Post_ATO1

–0.11287

0.91039

Post_ROA2

–2.60548

0.01001**

Post_ROS2

–2.21718

0.02925*

Post_ATO2

0.774256

0.44090

Note: ***, **, *statistically significant at 1% 5% and 10% respectively (two-tailed).

From Table 2, we can conclude that both ERP adopters and non-adopters faced a statistically significant decline in ROA and ROS in the first post adoption period (post 1) i.e., the first three years after ERP adoption, due to the increased fixed implementation costs of the ERP adoption and the second post adoption period (4th, 5th and 6th year after ERP adoption) due to the severe recessionary conditions in Greece at that time. As far as ATO is concerned, the decline is not significant at conventional levels. However, looking at Table 2, firms that have not adopted an ERP system faced a much sharper drop in ROA and ROS over the same post adoption periods, both period 1 and period 2, especially over the second post adoption period, suggesting that financial gains from cost reduction may be passed to customers through lower prices. However, in our case, the sharp decline in the post 2 period was mainly due to the severe recessionary conditions in Greece. The findings suggest that the performance of both ERP adopters and ERP non-adopters declined over the years but the decline for ERP non-adopters was much sharper. The only unexpected value in the table above is the increase in ROS for ERP non-adopters over the first post adoption period, but this increase is not significant at conventional levels (p-value = 0.440) and could be explained by other factors and the general good economic conditions in Greece. Our results are in line with the results of Hunton et al. (2003). They used data from 126 firms (63 ERP-adopters and 63 non-ERP adopters) and the adoption years of those firms were between 1992 and 1996, good years for the US economy. According to their research, the performance of ERP-firms had significantly changed three years after the ERP implementation while the performance of non-ERP-firms declined over the same period. In case Greece’s economic conditions remained steady, we would have seen more obvious differences in the change of the performance of the ERP adopters vs. the non-adopters. As a result, we could say that our first hypothesis is partially supported. Results of our research indicate that long-term firm performance (first and second post adoption

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period) of ERP adopters, declined less than the performance of non-adopters over the same period.

4.2 Results for the second hypothesis Based on the OLS model: Post_Ratio = a0 + a1 Pre_Ratio + a2 ERP_Adoption + a3 Age + a4 Size + a5 Z -score + e

We regressed post ERP adoption performance over the second post adoption period on the whole sample, i.e., adopters and non-adopters. The second post adoption period here, as explained above, accounts for the last three years of the six-year period following the ERP adoption. The variables were checked for correlation, as shown in the correlation table in the Appendix. We used a fixed effects model which gave better results than the simple regression model. The results are presented in Table 4. E-views 5.0 econometric software was used for all regressions. Table 4

Regression results of ERP adopters and ERP non-adopters Post-ROA

Post-ROS

Post-ATO

20.47 (0.3636)

–0.166 (0.2397)

8.081 (0.0000)***

Variables C Pre Adoption_Ratio Age Size

Coefficients 0.008 (0.6180)

0.148 (0.0007)***

0.001 (0.9798)

–0.228 (0.0076)**

–0.000 (0.0056)**

–0.014 (0.0000)***

–2.107 (0.4080)

0.023 (0.1211)

–0.915 (0.0000)***

ERP_Adoption

16.523 (0.0000)***

0.057 (0.2211)

–1.822 (0.0000)***

WC / Sales

–3.529 (0.0000)***

Z-score R-square

–65.051 (0.0000)***

4.56(0.0089)**

0.011 (0.6664)

0.144 (0.0000)***

0.6733

0.5382

0.7605

Breusch-Pagan test (LM) 4.53 (X20.001,6 = 22.46) 5.23 (X20.001,6 = 22.46) 17.25 (X20.001,6 = 22.46) Degrees of freedom (df)

6

Model used

6

6

Fixed effects model

Cross section heteroscedasticity test

White cross section transformation

F-statistic

3.8900

2.0900

5.8800

Prob (F-statistic)

0.0000

0.0000

0.0000

Notes: ***, **, *statistically significant at 1% 5% and 10% respectively (two-tailed). For all the independent variables the coefficient value and (p-value) are provided. Pre-ratio is the average of the financial ratio from the time periods –3 through –1. The post 2 ratio is the average of the ratio from time periods +4 through +6. ERP_Adoption is a dummy variable that takes the value 1 if the firm has adopted an ERP system and the value 0 if the firm has not, Age is the difference between the year 2011 and the year each firm was founded, Size is the number of firm’s employees and Z-score is an index that represents the financial health of the firm.


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The Breusch-Pagan test (LM) is used to test for heteroscedasticity in indicating that the most appropriate model to use is the fixed effects model in order to control the effects of time invariant variables with time-invariant effects. We also use White cross section transformation to control for cross section heteroscedasticity (CSH). The findings of the three regression models indicate that ERP adoption is a significant and positive determinant at 1% level of both profitability (ROA model) and efficiency (ATO model), which agrees with H1. However, for the profitability measure of net profit margin ROS), it did not come out as significant, possibly due to the fact that the ERP adoption could not affect the deterioration caused by the financial depression of Greece over the last four years of the study period (2008–2011). Our results show stronger effect of ERP adoption to ROA and ATO than Hunton et al. (2003). Other variables found to affect significantly at 1% level ROA and ATO for all sample firms are age, liquidity (measured by WC/Sales) and financial performance (Z-score). More specifically, age was found to affect all performance ratios in a negative way, suggesting that young firms are more profitable and efficient due to higher use of new technologies, modern organisation and promotion schemes, efficient use of resources and competitive products. Older firms possibly stick to the old fashioned mode of operation. Z-score denotes the importance of strong financial condition for profitability and efficiency. Liquidity measured in terms of WC / Sales is negatively correlated to profitability and efficiency, as expected, based on theory and literature, given that high levels of working capital indicate inefficient use of valuable resources, earning a much lower rate of return than invested in long term assets. Size came out as significant but with a negative sign, only for the efficiency model (ATO), as was also expected, implying that smaller firms manage their resources better (i.e., lower fixed assets, inventories, etc.), as indicated by theory and literature. Table 6 implies that size should be combined with good financial performance in order to be benefited from ERP systems. It is interesting also to note that pre-adoption profit performance was an indicator of post adoption performance only in the ROS model. A possible explanation for this is that firms with good net profit margins, able to effectively manage their expenses, continue to be profitable after the ERP adoption, because of other fundamental capabilities of the management the firm. The overall inference from the ROS model is that young competitive firms with a proven ability of effective management of operational and financial expenses will be able to sustain a good profit margin even in periods of severe economic crisis, supported by the implication of an ERP system. As an additional test for the hypotheses H1 and H3 we regressed performance measures after separating firms that had adopted an ERP system into two groups: 1

large ERP-adopters

2

small ERP-adopters, following Hunton et al. (2003).

The results of these regressions are presented in Tables 5 and 6. E-views 5.0 econometric software was used for all regressions.

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Table 5

Regression results of large ERP adopters Regression results of large ERP-adopters (n = 20)

Variables C Pre-ratio Age Size Z-score R-square

ROA

ROS

ATO

–25.45408 (0.0566) 1.004085 (0.0002)*** 0.111894 (0.5398) 0.023200 (0.2329) 4.038096 (0.3016) 0.844138

–12.68365 (0.0088)*** 0.922449 (0.0001)*** 0.039811 (0.5333) 0.010716 (0.1250) 2.691501 (0.1019) 0.909431

–3.007967 (0.1184) 1.689080 (0.0000)*** 0.012349 (0.6471) 0.002170 (0.4288) –0.216346 (0.6405) 0.906583

Notes: ***statistical significant at 1%. For all the independent variables the coefficient value and (p-value) are provided. Pre-ratio is the average of the financial ratio from the time periods –3 through –1. The post 2 ratio is the average of the ratio from time periods +4 through +6. ERP_Adoption is a dummy variable that takes the value 1 if the firm has adopted an ERP system and the value 0 if the firm has not, Age is the difference between the year 2011 and the year each firm was founded, Size is the number of firm’s employees and Z-score is an index that represents the financial health of the firm. Table 6

Regression results of small ERP adopters Regression results of small ERP-adopters (n = 28)

Variables C

ROA

ROS

ATO

–10.37852

–26.82871

1.676132

(0.3276)

(0.0005) ***

(0.3907)

0.094965

0.013325

0.229527

(0.3420)

(0.9371)

(0.0031)***

Age

–0.231680

–0.099699

–0.042042

(0.2049)

(0.3216)

(0.1695)

Size

0.044790

0.102380

–0.002677

(0.4113)

(0.0044) ***

(0.7694)

Pre-ratio

Z-score R-square

9.267829

5.381218

1.330731

(0.0015) ***

(0.0030)* ***

(0.0055) ***

0.521541

0.600966

0.517903

Notes: ***statistical significant at 1%. For all the independent variables the coefficient value and (p-value) are provided. Pre-ratio is the average of the financial ratio from the time periods –3 through –1. The post 2 ratio is the average of the ratio from time periods +4 through +6. ERP_Adoption is a dummy variable that takes the value 1 if the firm has adopted an ERP system and the value 0 if the firm has not, Age is the difference between the year 2011 and the year each firm was founded, Size is the number of firm’s employees and Z-score is an index that represents the financial health of the firm.


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Tables 5 and 6 give us a better insight into the significant determinants of a steady strong financial performance following ERP adoption, under conditions of severe economic crisis. The findings suggest that for large firms the significant determinants of profit generating capability and efficiency, is the ability of management to control expenses and invest funds profitably, before the ERP implementation (the pre adoption period profit performance is what matters). It seems that ERP adoption is the result of good management practices. Furthermore, large healthy firms can expect greater performance gains than their large size unhealthy counterparts. This finding contradicts the findings of Hunton et al. (2003). For small firms Table 6 totally supports our last hypothesis. According to that hypothesis, a positive relationship is expected between firm performance and financial health for small firms which have implemented an ERP system. Z-score, which is the variable for financial performance, shows to affect positively and significantly ROA, ROS and ATO at 1% level of significance. According to the findings, for small ERPadopters, the greater the financial health, the greater is the firm’s performance. Because of their healthy financial condition small-healthy firms show better access to financial resources and a full ERP implementation, while small-unhealthy firms most of the times choose to adopt an ERP system not in systematic way. Economic crisis affects small unhealthy firms more, as well as their interaction with banks and their financial position, causing cash flow shortages (Ioannou and Mihai-Yiannaki, 2010). A healthy small firm can have access to important resources which are very important for the right use of an ERP system. As a result, small-healthy firms take advantage of all the benefits of such an implementation. In that way, the good use of the system leads to the whole packet of the anticipated benefits giving the firm a competitive advantage. Small unhealthy firms unfortunately will not be able to take advantage of ERP systems and business process innovation which could improve their financial condition. Our findings are once more in line with the findings of Hunton et al. (2003) and Hitt et al. (2002). They concluded that “for smaller ERP firms, as financial heath improved, so did financial performance”.

5

Conclusions

It is undeniable that ERP systems are part of the everyday life of the majority of the enterprises all over the world. They have significantly penetrated the global market and influence firms’ operational procedures. Moreover, they offer a great number of anticipated benefits but at the same time their implementation is a big challenge for many organisations and sometimes, it might simply be a waste of money if is installed before the company is really ready for it. The goal of this paper was to investigate the longitudinal impact of ERP adoption on firms’ financial performance, furthermore, analysing it under conditions of economic depression (2009–2011). In order to do so we used a sample which consisted of 88 Greek firms from different sectors, 48 of them ERP adopters and 40 non-adopters, for a period of ten years (2001–2011). We attempted to compare the performance of ERP adopters with ERP non-adopters, based on ROA, ROS and ATO metrics of performance before and during crisis period for Greece. Our scope was to investigate whether long-term firm performance of enterprises that have adopted ERP systems is better than that of non-adopters. As Hunton et al. (2003)

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proved in their research, our findings also suggest that firms that adopted ERP performed relatively better than non-adopters, showing a lower decline in their profit performance over the whole post adoption period which coincided with the country’s depression. More specifically, research findings suggest that ROA, ROS and ATO were significantly lower for non-ERP users mainly after the third year of ERP implementation. Results suggest that if the Greek economy was steady, ERP adopters would have performed better than non-adopters. Analysis revealed that non-adopters performed significantly worse than non-adopters and through an econometric analysis it was found that ERP implementation affects positively and significantly the profit performance and asset efficiency of Greek firms, controlling for size, liquidity, pre adoption profit performance and healthy financial condition. More so, young firms applying ERP systems were found to perform better than older ones. The findings also imply that small and financially strong ERP users tend to have better performance with respect to ROA, ROS and ATO than their financially weak counterparts, since they can have better access to financial resources required for the full implementation of ERP. In addition, the findings indicate that in the large sized firms ERP implementation helps good performers to continue their good financial performance even during depressionary economic conditions. Unfortunately, the results suggest that small unhealthy firms will not be able to take advantage of ERP implementation, unless other types of ERP financing is pursued, such as ERP vendors, application service providers, etc. The findings of this paper are important to both researchers and practitioners as they bring a clear message to managers and ERP adopting enterprises, on the impact of ERP systems on firm performance suggesting that ERP adoption helps firm gain a competitive advantage over non-adopters. Further, the results of our study confirm previous empirical research findings abroad. This study supports also the view that firms can improve their competitiveness and viability only if they rely on information technology, education and investments in new technology. The decrease of salaries of workers is not enough by itself to help firms and the economy to be in a competitive edge and grow.

6

Limitations of research and policy implications

Despite the novelty of the study, limitations do exist as of the time span of the research, given the severe economic crisis and the size of the sample. Future research could correct those limitations allowing for more time for ERP implementation effects to show and also focus on ERP effects on manufacturing firms, trade or service firms, separately. Managers should be aware that full ERP implementation could help Greek firms to become more competitive in terms of cost and quality of products and services offered, as shown by empirical research (Galani et al., 2010; Stefanou and Revanoglou, 2006; Hunton et al., 2003). The state should support full ERP adoption by providing low cost financing as well as subsidies and by encouraging cooperation of firms with higher education institutions and universities in the implementation of ERP systems. The use of other types of financing, such as ERP vendors, application service providers, etc., could also help in the extended implementation of ERP systems in Greece.


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Notes 1

The Y2K problem (year 2000 problem) was a problem for documentation and data storage situations which resulted from the practice of code programmers indicating a four-digit year using only two digits.


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Appendix Correlation table Pre_ROA

Pre_ATO

Pre_ROS

Pre_ROA

1.000000

0.297695

0.487789 –0.015537 0.068034

Age

Log_Size ERP_Adopt

WC_TS

Z_Score

0.066846

0.007318

0.236925

Pre_ATO

0.297695

1.000000

Pre_ROS

0.487789

0.087327

0.087327 –0.042052 –0.004720

0.004166

–0.147180 0.192445

1.000000

0.013723 0.072699

0.049140

Age

0.016133

0.321587

–0.015537 –0.042052 0.013723

1.000000 0.390076

0.243404

0.045479

0.040116 0.047877

Log_Size

0.068034 –0.004720 0.072699

0.390076 1.000000

0.529583

0.110493

ERP_Adopt

0.066846

0.049140

0.243404 0.529583

1.000000

–0.091229 –0.050561

WC_TS

0.007318 –0.147180 0.016133

0.045479 0.110493

–0.091229

1.000000

0.064195

Z_Score

0.236925

0.040116 0.047877

–0.050561

0.064195

1.000000

0.004166 0.192445

0.321587