Operating performance of Chinese manufacturers in the wake of ERP implementation
Joseph Callaghan School of Business Administration Oakland University, 2200 N. Squirrel Road, Rochester, MI, 48309, USA E-mail: [email protected]
Li Dang Orfalea College of Business, California Polytechnic State University, San Luis Obispo, CA 93407, USA E-mail: [email protected]
Arline Savage UAB School of Business, University of Alabama at Birmingham, 1530 3rd Ave. S, Birmingham, AL 35294-4460, USA E-mail: [email protected]
Yuefan Sun* Business School, Beijing Technology and Business University, 517 Zonghelou, 33 Fucheng Road, Haidian District, Beijing, 100048, China E-mail: [email protected] *Corresponding author
Abstract: This paper develops a model of firm operational performance in the aftermath of an ERP implementation based upon subjects’ perceptions. We obtained a unique set of data for 198 public Chinese manufacturing companies involved in enterprise resource planning (ERP) implementations from 1993 to 2006. We collected fundamental data from a survey of these companies, and then analysed their ERP implementations and post-implementation operational performances. We use subjects’ perceptions to model firm operational performance as a function of effective business process improvement (BPI) that is related to effective ERP implementation and post-implementation systems integration. These intervening factors, in turn, are modelled as a function of both the level of CEO involvement and the extent of business process reengineering (BPR). We find that operational performance is positively associated with BPI, which is positively related to perceived ERP effectiveness
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and post-implementation systems integration, and that these are positively related to both the level of CEO involvement and the extent of BPR. Finally, competition and organisational change factors, along with ERP intensity variables are found to be effective controls in the underlying conceptual model.
Reference to this paper should be made as follows: Callaghan, J., Dang, L., Savage, A. and Sun, Y. (2013) ‘Operating performance of Chinese manufacturers in the wake of ERP implementation’, Int. J. Business Information Systems, Vol. 12, No. 3, pp.296–320.
Biographical notes: Joseph Callaghan is a Professor of Accounting at Oakland University in Rochester, Michigan, USA. He has a Doctorate in Accountancy from the University of Illinois at Urbana-Champaign. His expertise lies in the financial, managerial and accounting information systems areas. His primary research areas include evaluating risk and performance of organisations, and reengineering legacy AIS.
Li Dang is an Associate Professor at California Polytechnic State University San Luis Obispo, USA. Her research interests and publications focus on audit quality, international accounting, and accounting information systems. She teaches financial accounting and accounting information systems courses.
Arline Savage is a Professor of Accounting at the University of Alabama at Birmingham in the USA. She received her Doctorate from the University of Port Elizabeth (now Nelson Mandela Metropolitan University) in South Africa. Her research areas include information systems, financial accounting and forensic investigations.
Yuefan Sun is an Associate Professor at Beijing Technology and Business in China. Her research interests and publications focus on management information systems, corporate governance, and audit quality. She teaches financial accounting, auditing, and management information systems courses.
1 Introduction
Since economic reform in China was initiated by Premier Deng Xiaoping in 1978, the country’s economy has grown significantly at an annual rate of 9.0% or more for nearly three decades [Brown and He, (2007), p.132; World Bank, (2010), p.10]. China now plays an increasingly important role in the world economy. While the global economy remains in dire straits, China’s economic growth has been strong and its economic outlook remains favourable, with predictions of GDP of 9.5% for 2010 and 8.5% for 2011 (World Bank, 2010). This makes China the world’s second-biggest economy after the USA. It is from this perspective that we consider the effects of the growth in the implementation and integration of enterprise resource planning (ERP) in China. As Martinsons (2005, p.46) succinctly states: “More than any other country, China is being transformed by its application of IT, from a poor and isolated society to a major force in the global economy”. It is in this context that the operating effectiveness of systems implementation and integration in China can be envisaged.
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The increasing globalisation of the Chinese economy is leading to a growing need for modern software to replace traditional legacy systems, which inhibit economic sustainability and competitiveness. The Chinese Government supports ERP systems implementations. Prior to 2000, ERP implementations generally had a success rate of about 33%, while the success rate in China was much lower than the Western World at only 10%. However, since 2001, the Chinese Government’s policy of using IT to speed up industrialisation has been widely implemented [Ge and Voß, (2009), p.503]. According to a Gartner, Inc. (2010) press release, ERP is a priority area for software spending in China. China’s ERP software market is forecast to maintain strong performance, with an estimated compound annual growth rate (CAGR) of 14.6% from 2008 to 2013 and 14.8% in 2010 – the highest in the world. In comparison, the ERP market in the USA had a CAGR for 2005 to 2009 of 5.0% (IBISWorld, 2010). The top four industries, which account for approximately 60% of total software spending in China, are manufacturing, financial services, communications and government. In this study, we focus on Chinese manufacturing companies. New empirical studies are needed to validate any improvement in operating and financial performance after ERP implementation, especially in view of the enormous financial resources expended on ERP implementations and the paucity of research in the accounting literature. This study contributes in this regard.
Disparate information systems impede an organisation’s long-term growth (Xue et al., 2005). Change is driven by economics and competition and made possible by technology [Bancroft et al., (1998), p.216]. ERP systems were developed to provide the solution by automating and integrating all or many of an organisation’s business processes and functions into a single software system, using one application, a single database to share data across the enterprise, a unified interface, and real-time access to information (e.g., Bingi et al., 1999; Nah et al., 2001), resulting in integrated information flows (Davenport, 1998). Adopting firms expect ERP systems to improve operating performance and ultimately financial performance (Kallunki et al., 2011). The top-tier ERP vendors are SAP, Baan, Oracle and Peoplesoft. ERP was developed to manage and automate all aspects of an organisation’s business operations, including sales and distribution, materials, human resources, production planning, purchasing, sales, customer relationships, supply chain, product life-cycle, business intelligence and accounting. Each ERP module is business-process specific [Benco and Prather, (2008), p.145]. EDI, internet EDI, and extranets are used to connect an ERP system to the IT systems of vendors and customers. This allows different functional areas within the organisation to communicate with one another and with customers and vendors more effectively.
The successful implementation of an ERP system should lead to significant benefits such as reduced labour, better cash flow management, increased accounts receivable turnover, fewer bad debts, more timely reporting, reduced inventory, tightened supply chain links, improved production scheduling, reduced manufacturing costs, reduced order processing time, improved customer service, and consequently, an increase in competitiveness, profitability and stock prices. However, history shows that the successful implementation and integration rate remains fairly low and many enterprises that have gained some benefits from ERP implementation have not exploited the software’s full potential [Ge and Voß, (2009), p.501; Zabjek et al., 2009]. Research into ERP effectiveness and performance is important from an accounting perspective. By its nature, accounting should provide the answer of whether ERP systems are worth the money that firms invest in them.
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The focus of this paper is on ERP implementation and integration in the manufacturing industry in China, specifically post-implementation ERP effectiveness and post-implementation operational performance. The next section of this paper reviews the relevant literature. The third section proposes a theoretical model, while the fourth section discusses the research methodology. The fifth section discusses the results, while the final section summarises the paper and lays the foundation for further research.
2 Literature review
2.1 ERP implementation and integration critical success factors
The most extensive category of ERP implementation research is the critical success factor (CSF) stream [Brown and He, (2007), p.134], based on the concept of CSFs popularised by MIT’s Rockhart (1979). This research appears to be based mainly on survey research of perceptions of successfulness and case studies of ERP implementations. Dezdar and Sulaiman (2009) provide the most recent extensive investigation into ERP implementation CSFs in the literature from 1999 to 2008 and then formulate a taxonomy and rankings of 17 CSFs identified from 95 articles by doing frequency and comparative analyses. The highest ranking CSFs (with frequency out of 95 articles in parenthesis) were:
1 top management support (72%)
2 effective project management and evaluation (70%)
3 business process reengineering (BPR) and minimum customisation (62%)
4 ERP team composition and competence (56%).
Motwani et al. (2008, p.162) identified almost identical CSFs from the 1999 to 2004 literature as Dezdar and Sulaiman (2009).
We have decided to focus on only two top-cited CSFs, CEO sponsorship/involvement and BPR, for our model for the following reasons:
1 our methodology’s focus on operating performance
2 the abundance of research into ERP CSFs
3 our need to limit the length of the questionnaire
4 enterprise systems are essential IT enablers of BPR (Hammer and Champy, 1993)
5 findings that the top management sponsorship and involvement variable is a prerequisite for the other CSFs [Akkermans and van Helden, (2002), p.42; Bancroft et al., (1998), p.136].
2.1.1 CEO sponsorship and involvement
The literature contends that top management support is key to securing the necessary conditions (i.e., the other CSFs) to successful implement an ERP system [e.g., Aladwani, (2001), p.272; Bingi et al., 1999; Cheng et al., 2006; Dong, 2001; Kamhawi and
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Gunasekaran, (2009), p.699; Reimers, 2003; Umble and Umble, 2002; Yusuf et al., 2006]. Partially overlapping with Desai and Sulaiman’s (2009) 1999 to 2008 synthesis of 95 articles, Ngai et al. (2008) present a review of 48 studies in the CSF literature up to and including 2005 of 12 groups of countries and regions, including South America, the USA, Europe, the UK, Denmark, Australia, China, the Middle East, and the Arab Gulf States. Six of the studies they identify include China, with four solely focused on China. These 48 studies identify 18 CSFs and all of them list top management support as a one of the most CSFs, with many investigations finding this CSF to be the single most important factor internationally to secure the necessary conditions for introducing the organisational changes that will result from a successful ERP implementation [e.g., Akkermans and van Helden, (2002), p.36; Aladwani, 2001; Brown and He, 2007; He, 2004; Jafari et al., 2009; Yusuf et al., 2006, Zabjek et al., 2009]. Law and Ngai (2007) and Reimers (2003, p.347) also find that top management support of business process improvement (BPI), a consequence of successful ERP, is positively associated with the extent of BPI. CEO sponsorship and commitment provides a symbolic indication of priority for an ERP project, which should in turn promote organisation-wide commitment, user involvement and a successful ERP system [Jafari et al., (2009), p.399; Zhang et al., (2005), p.78].
2.1.2 Business process reengineering
‘BPR followed by ERP’ [Koch, (2001), p.261] is necessary for a successful and integrated ERP system (e.g., Ip and Chen, 2004; Koch, 2001; Panayiotou et al., 2011; Yusuf et al., (2006), p.1332; Zabjek et al., 2009). A business process is a set of logically related tasks or activities performed to achieve a particular business outcome. For example, the business outcome of the cash receipts process is cash deposited in the bank. BPR is the analysis and redesign of an organisation’s workflows and processes. According to Hammer and Champy (1993) “…to benefit from BPR, ERP is the essential [IT] enabler” because the objective is that all processes in an organisation conform to the ERP model, which consists of generic ‘best practices’ embedded in templates in the software in areas like management, human resources, accounting, production, etc. [Gattiker and Goodhue, (2005), p.560]. Both the costs and benefits of realigning business processes with an ERP model can be substantial. However, some of an organisation’s business processes may be unique and to redesign them to conform to the ERP model would result in a loss of competitive advantage. Therefore, the ERP software would have to be customised for those processes to better suit the needs of the organisation. But more customisation results in higher implementation costs [Bingi et al., (1999), p.10]. Consequently, the goal of BPR would be problem identification to conform to the ERP model, with minimum ERP customisation [Dezdar and Sulaiman, 2009; Ip and Chen, (2004), p.81]. Research shows that organisations with better BPR abilities usually experience smoother ERP implementations [Kamhawi and Gunasekaran, (2009), p.691; Zabjek et al., 2009].
Because extensive process redesign results in significant organisational changes, top management support for BPR would logically to be needed. Consequently, one would expect a significant relationship between CEO sponsorship and involvement and the successful operationalisation of BPR by the ERP system, resulting in BPI.
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2.1.3 Other factors
The other CSFs identified by Dezdar and Sulaiman (2009) in their synthesis of the literature (ranked in order of importance) are
1 project management and evaluation
2 ERP team composition, competence and compensation
3 change management programme
4 user training and education
5 business plan and vision
6 enterprise-wide communication and cooperation
7 organisational culture
8 ERP vendor support
9 software analysis, testing and troubleshooting
10 project champion
11 careful selection of ERP software
12 use of consultants
13 appropriate business and IT legacy systems
14 system quality
15 user involvement.
2.2 Performance in the wake of ERP implementation
An implicit assumption often appears to be that successful ERP implementations will somehow lead to business change and improved operational performance. However, this is not always supported by the extant research [e.g., Law and Ngai, (2007), p.419]. For example, Martin’s (1998) title is: ‘An Electronics Firm Will Save Big Money by Replacing Six People with One and Lose All This Paperwork Using ERP Software’. As previously stated, the success rate of ERP implementations has been low, with researchers reporting up to a 90% failure rate (see Zabjek et al., 2009, for an in-depth discussion). We organise this literature stream into two categories:
1 post-implementation ERP and integration effectiveness and BPI
2 post-implementation operational performance.
Theoretically, ERP implementation affords an opportunity for BPR, hopefully resulting in systems integration and BPI.
2.2.1 Post-implementation ERP integration effectiveness and BPI
Using an analytic hierarchy process, Tsai et al. (2006) assess the relative importance weights of ERP measures and identify the even most important measures of success as:
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1 accuracy of output
2 precision of input
3 data accuracy
4 frequency of report requests
5 timeliness of output
6 user’s confidence in the system
7 system accuracy.
Gattiker and Goodhue (2002) found that the adoption of ERP software was positively associated with business process change. Delone and McClean (1992) identified the variable ‘Information Systems Success’, which has since been generally accepted as a suitable foundation for further research [Zhang et al., (2005), p.59]. Delone and McClean identify the following dimensions which Tsai et al. (2007) use to measure perceived ERP success: system quality, information quality, system use, user satisfaction, individual impact on information recipient’s behaviour, and organisational impact. Tsai et al. (2007) further propose the balanced scorecard (BSC) method to measure the performance improvements in ‘organisational impact’ from four traditional BSC perspectives, namely financial, customer, internal business process, and learning and growth. Logically, the BSC internal business process and learning and growth dimensions relate to this category, while the other two relate to the following category.
2.2.2 Post-implementation operational performance
The purpose of investments in ERP systems is to improve firm organisational efficiency and effectiveness, resulting in improved operational performance (non-financial) and ultimately, improved financial performance (profitability and stock prices). While Gattiker and Goodhue (2002) found a positive association between ERP adoption and business process change, they did not find support for a relationship between business process change and organisational impact – a counter-intuitive finding. For 96 companies internationally and from diverse industries, Law and Ngai (2007) later found that the perceived extent of BPI, as measured by five items used for perceptual ratings, i.e., errors/defects prevention, process improvement standards, ease of use of new processes, intra- and extra-organisation and coordination, was positively associated with ERP success as measured by user satisfaction [an average computed of the 12 items of the Doll and Torkzadeh (1988) user satisfaction instrument on five dimensions: information content, accuracy of information, output format, ease of use, and timeliness of information]. Law and Ngai (2007) also found that both ERP success and the perceived extent of BPI were positively related to perceived organisational performance, as measured by an average of five items obtained from respondents’ perceptions: customer satisfaction, customer retention rate, sales growth rate, firm profitability, and overall competitive advantage.
O’Leary (2004) confirms the Deloitte Consulting (1998) study of key ERP benefits realised, which are inventory reduction, personnel reduction, productivity improvements, order management improvements, financial close cycle reduction, IT cost
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Results from a study by Wieder et al. (2006) are contradictory. Using perception-based measures to capture both business process and financial performance measures, they found no support for their prediction that ERP adopters will have ‘significantly higher performance scores at both the core business process level and at firm level’. However, they did find that longer experience with ERP has a positive impact on firm performance. The financial performance measures used were return on investment, operating profits, sales growth rate, cost reduction programmes, and cash flow. The 22 business process measures include relative levels of various logistics, manufacturing and inventory costs, speed at filling orders, percentage of on-time deliveries, backorder level, production time, shipping errors, and customer complaints [Wieder et al., (2006), pp.28–29].
2.2.3 Financial and stock market performance
Velcu (2007) finds that, while ERP adopters report a number of post-implementation operational benefits, these adopters are unable to quantify the impact of ERP on financial performance (Kallunki et al., 2011).
Poston and Grabski (2001) examined the financial performance for a group of firms for three years before and after ERP implementation and find no general financial improvement. Despite this finding, the employees-to-revenue ratio significantly decreased in all three years and the sales-to-cost ratio improved in the third year. The measures they used were residual income, selling, general and administration expenses/revenues, cost of goods sold/revenues and number of employees/revenues. Hunton et al. (2003) investigates longitudinal financial performance effects of ERP implementation by matching adopters to non-adopters. They find that financial performance, measured by return on assets, return on investments and asset turnover, was not significantly different for adopters when examining pre-to-post ERP implementation effects over a three-year period. However, non-adopters significantly underperformed adopters by the third year, suggesting that ERP helps adopters gain a competitive advantage over non-adopters. Similarly, Nicolaou et al. (2003) compare financial data of ERP system adopters with a control group. They used return on assets, return on sales and asset turnover measures. Their results show that firms with ERP systems had significantly higher performance in the second year after implementation than the control group. Matolcsy et al. (2005) track financial ratios (net profit margin, current ratio, fixed asset turnover, sales days outstanding, accounts payable days, inventory turnover, sales change) for two years for companies that adopted ERP systems versus companies that did not adopt ERP. The result was that the adoption of ERP systems led to sustained operational efficiencies and improved overall liquidity. In addition, they found some support for increased profitability two years after the adoption of ERP and for improvements in accounts receivable management.
Research studies on ERP systems in the accounting literature also tend to focus on stock price or financial analyst reaction to announcements of plans to invest in ERP systems (Benco and Prather, 2008; Hayes et al., 2001; Hunton et al., 2002). These studies show that investors and financial analysts believed that the ERP implementations would
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enhance firm value. Wier et al. (2007) also use return on assets and stock returns to measure corporate performance.
A study that considers the long-term stock price and profitability effects of 186 ERP investment announcements appears in the operations management literature (Hendricks et al., 2007). The authors examine performance effects for both the implementation and post-implementation phases and find some evidence of improvements in profitability, but not in stock returns. A possible explanation for this apparent anomaly could be that the market had previously incorporated the anticipated benefits. Despite high ERP implementation costs, they find no consistent evidence of negative performance associated with enterprise system investments. Generally, empirical results of performance improvement are mixed.
3 Theoretical model and hypotheses
Our research focus for this paper is on post-implementation operational performance of ERP systems for public Chinese manufacturing companies. The literature (e.g., O’Leary, 2004) suggests that this dependent performance construct and its related measures are a positive function of BPI. Further BPI is posited to be positively affected by both effective ERP implementation and post-implementation systems integration factors (e.g., Law and Ngai, 2007). These intervening factors are, in turn, posited to be a positive function of the CSFs, CEO sponsorship and involvement (e.g., Aladwani, 2001; Bingi et al., 1999; Cheng et al., 2006; Dong, 2001; Kamhawi and Gunasekaran, 2009; Reimers, 2003; Umble and Umble, 2002; Yusuf et al., 2006) and BPR (e.g., Ip and Chen, 2004; Koch, 2001; Yusuf et al., 2006; Zabjek et al., 2009). Post-implementation operational performance measures, as well as measures related to other factors, are based on respondents’ scaled responses to questions deemed related to operational performance. The scale used was a five-point Likert-type scale, ranging from Strongly Disagree (1) to Strongly Agree (5). All factor categories and their related questionnaire items used in this study are shown in the Appendix. Intervening factors, ERP effectiveness and post-implementation systems integration, are also based on respondents’ perceptions, as are the two CSFs, CEO sponsorship and involvement and BPR.
Figure 1 reflects our framework. It depicts our hypothesised relations in three stages. Working right to left, the underlying CSFs for ERP effectiveness and post-implementations systems integration are CEO sponsorship and involvement, and the extent to which BPR is undertaken. If an ERP implementation is viewed strategically, as more than merely a software installation, albeit a big one, and as an opportunity to reengineer underlying business processes, conforming to the implied business process of the ERP system that are perhaps reflective of best business practices, then ERP effectiveness should be positively affected by BPR. In addition, BPR independent of the ERP implementation will likely affect how the ERP is configured and customised, and how post-implementation systems integration is effectively accomplished. Thus CEO sponsorship and involvement affects intervening factors, ERP effectiveness and post-implementation systems integration. But ERP effectiveness and post-implementation systems integration are not business ends in themselves. Rather, they are intervening factors to BPI and ultimately to the payoffs in terms of improved operational performance.
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Figure 1 Conceptual model (see online version for colours)
Thus, the hypotheses for this study, expressed in the alternative form, one-tail, are:
H1(a) ERP effectiveness is positively related to Chief Executive Officer (CEO) sponsorship and involvement.
H2(a) ERP effectiveness is positively related to BPR measures.
H3(a) Post-implementation systems integration is positively related to CEO sponsorship and involvement.
H4(a) Post-implementation systems integration is positively related to BPR measures.
H5(a) ERP effectiveness is positively related to post-implementation systems integration.
H6(a) BPI is positively related to ERP effectiveness.
H7(a) BPI is positively related to post-implementation systems integration.
H8(a) Operational performance is positively related to BPI.
Additionally, operational performance is deemed to be affected by the degree of existing industry competition faced by the implementing organisation and the nature ERP implementation in terms of intensity (number of modules installed) and the degree of ERP customisation. Further, BPI effectiveness is impacted by facilitating organisational structural changes (ORGs). These factors and variables are used to control the model’s dependent factors.
4 Research methodology
We used a self-administered, five-point Likert scale multi-item survey instrument (see Appendix for categories and items) because the complexity inherent in an investigation into ERP implementation and performance cannot be adequately measured with a single item. Multi-item scales can reduce measurement error of complex, latent variables by
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combining several individual items (Yang and Su, 2009). The questionnaire was designed after a cross-disciplinary literature review (e.g., accounting, operations management, information technology, information systems and management) to identify ERP implementation factors and performance constructs for post-implementation operational performance. From this review, we determined questionnaire categories and items. Then practitioner experts, namely ERP consultants, CIOs and ERP project managers, who were qualified to assess the content validity of the proposed items and constructs, were interviewed to refine the questionnaire. This was followed by a pilot test with ten subjects. The feedback was that some of the questions were too complicated. Therefore, we simplified the language to make those questions more understandable. The response rate was 70%, with 198 usable responses.
We use confirmatory factor analysis (CFA) and Cronbach’s alpha to measure the reliability of the Likert scales of the individual questions that comprise the factors (latent variables) of our models. We propose hypothesised relationships in three stages: CSFs versus intervening factors in stage 1, intervening factors versus BPI in stage 2, and BPI versus operating performance in stage 3. The research methodology that we adopt parallels the hypothesised relationships. Specifically, we perform an ordinary least squares (OLS) regression analysis in three stages (e.g., Biddle et al., 2011; Cherkes et al., 2009) to provide preliminary evidence that the underlying constructs predicted by the literature, theory and logic would prevail. The regression analyses parallel our research framework demonstrated in Figure 1. The results of this regression analysis confirm our underlying conceptual model and factor associations.
5 Discussion of results
5.1 Descriptive statistics
5.1.1 Subjects’ background information
We received 198 usable questionnaires from nearly 300 Chinese publicly-traded manufacturing companies we surveyed at the end of 2006, all of which invested in the ERP software of one of the major players in the ERP market. The respondents’ positions in their firms were CIOs (50%), other IT or systems-related employees (18%), the ERP project managers (5%), other (10%), and unclear (17%).The average ERP experience of respondents was 6.23 years. Sixty-six respondents were the ERP project team leaders, while 83 were team members. Seven respondents were not project team members, while 11 companies did not have ERP project teams.
5.1.2 ERP implementation
Of the 198 surveyed companies, 138 had completed ERP implementations and 60 had not. Of the 138 companies that had completed ERP implementations, the average time taken to complete the implementations (the gap between the time when ERP was initiated and the time when it was completed) was 21.65 months (six companies did not respond to this question). Of the 60 companies that had not completed implementations, the average completion rate was 63.21% (13 companies did not respond to this question).
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The average time taken to do pre-implementation research was 9.49 months. The average time taken to implement the ERP system was 8.86 months. The average time taken to test the system was 3.79 months. One hundred and fifty companies purchased ERP modules from only one provider; the remainder purchased modules from more than one provider. Seventy-two companies hired a consulting company for module integration, while 125 companies did not.
The total implementation cost, on average, was 25,417,719.3 RMB1 (there were 27 missing values). The average total cost for those companies that had completed implementations was 27,942,177.4 RMB (there were 14 missing values). The average total cost for companies that had not completed implementations was 18,757,446.8 RMB (there were 13 missing values).
The choice of an ERP vendor was decided on the following factors: reasonable price (41 responses); brand name (65 responses); leading technology (53 responses); perfect functions (39 responses); wide/flexible applications (7 responses); good customer support (37 responses); fits business needs (77 responses); perfect solutions (37 responses); good training (6 responses); user friendly (20 responses); easy for customisation (34); good communications (26 responses); prior successful implementations (60 responses); required by a supervising company (1 response); government recommendations (0 response); headquarter decision (10 responses); other (60 responses). Table 1 Descriptive statistics
N Minimum Maximum Mean Std. deviation Kurtosis Std. error
Notes: Variable definitions: OPER: the average of ‘operating performance’ item scores BPI: the average of ‘BPI’ item scores ERPE: the average of ‘ERP effectiveness’ item scores ERPP: the average of ‘Post-ERP implementation’ item scores CEO: the average of ‘CEO involvement/sponsorship’ item scores BPR: the average of ‘BPR’ item scores ORG: the average of ‘organisation structural changes’ item scores COMP: the average of ‘competition’ item scores Module: ERP implementation intensiveness based on a five-point scale Custom: a dichotomous variable with a value 1 indicating customisation, 0 otherwise.
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Sixty-four companies had some ERP modules before ERP implementations. For these companies there were, on average, two pre-ERP modules. On average, about 7.59 modules had been or were in the process of being implemented for all surveyed companies. Of all the 189 survey companies, 103 companies had gone through or were going through ERP customisation, which is not surprising given that they are manufacturing companies. The average customisation cost was 4,238,860.76 RMB. Of the 138 companies that completed ERP implementations, 90 had gone through customisation and the average cost was 4,820,892.86 RMB (there were 35 missing values).
During ERP implementations, 184 companies had formed an ERP project team. On average, there were 68 (16) members (technical members) in the project team. In 124 companies, the CEO was one of the leading project team members.
After combining questionnaire items into factor categories, we calculated the descriptive statistics. Descriptive statistics for each of the factors are reported in Table 1.
The eight (A-H) factors map to our conceptual model, while the two control variables, Module and Custom reflect two dimensions of ERP intensity.
5.2 Reliability and CFA results
Table 2 summarises the results related to the reliability of the model factors and their underlying questions. In each case the selected set of questions provided a reasonable measure of reliability associating them to their related factor based on a Cronbach’s alpha cut-off of .65 to .70 (Cheng et al., 2006; Nunnally, 1978). The only exception is the CEO involvement factor whose raw alpha measure was only 0.53. Improvements could possibly be made by dropping questions, but since there were only four questions and the factor was found impactful under OLS, we judged that all questions be included for this factor. Further, CFA found the factor to be a good fit in the proposed model. In general, the CFA results confirmed that the underlying factors should be included in the model. Table 2 Questionnaire item analysis
Confirmatory factor analysis of questionnaire items
Factor Measured variables selected
Cronbach's alpha
(standardised) reliability
Operational performance (OPER) A1-A5 0.828 (0.823) Business process improvement (BPI) B1-B5 0.777 (0.789) ERP effectiveness (ERPE) C1-C6 0.750 (0.750) Post-implementation systems integration (ERPP) D1-D7 0.766 (0.770) CEO sponsorship and involvement (CEO) E1-E4 0.530 (0.532a) BPR measures (BPR) F1-F6 0.720 (0.726)
Note: aThis score is low against the traditional standard of 0.7 or higher.
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5.3 Correlation analysis
Pairwise correlations of the factors and variables are provided in Table 3. The correlation matrix suggests that operating performance was significantly linearly related to BPI, ERPE, ERPP, CEO, module and custom. BPI was significantly related to ERPE, ERPP, CEO, BPR, ORG, COMP, module and custom. Further, ERPE was significantly related to ERPP, CEO, BPR, ORG, COMP and module. Moreover, ERPP was significantly associated with CEO, BPR, ORG, COMP and module. The CSF, CEO, was linearly related to BPR, ORG and COMP, while BPR was related to ORG and Comp. Many of these correlations are consistent with the associations implied by our conceptual model. All significant correlations indicate positive associations. Table 3 Correlation matrix
Notes: aWe also calculated the non-parameter Spearman rank correlations for these factors and variables and found very similar correlations. Variable definitions: OPER: the average of ‘operating performance’ item scores BPI: the average of ‘BPI’ item scores. ERPE: the average of ‘ERP effectiveness’ item scores. ERPP: the average of ‘Post-ERP implementation’ item scores. CEO: the average of ‘CEO involvement/sponsorship’ item scores. BPR: the average of ‘BPR’ item scores ORG: the average of ‘organisation structural changes’ item scores COMP: the average of ‘competition’ item scores Module: ERP implementation intensiveness based on a five-point scale Custom: a dichotomous variable with a value 1 indicating customisation, 0 otherwise.
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5.4 Staged regression analyses
We run OLS regressions for the 138 companies that had completed ERP implementations2. The measurement for each variable is achieved by taking a simple average of those responses to related questionnaire items. The items, in turn, were selected based first on their questionnaire category and then on their reliability and CFA measures. The OLS regressions proceeded in three stages:
1 intervening factors on CSFs and ERP effectiveness on post-implementation systems integration
2 BPI factor on intervening factors with controls for organisation structural changes
3 operating performance regressed on BPI controlled by degree of competition factor and module and customisation control variables. OLS regression results for stages 1, 2, and 3 are presented in Tables 4, 5, and 6 respectively.
5.4.1 Stage 1 OLS regressions
In stage 1, we examine the linear relationships between intervening factors and CSFs as well as the relationship between the two intervening factors. Therefore, the following three OLS regression models are analysed in stage 1.
0 1 2 1.1: Model ERPE CEO BPRα α α= + +
0 1 2 1.2: Model ERPP CEO BPRβ β β= + +
0 2 1.3: Model ERPE ERPPχ χ= +
where
ERPE ERP effectiveness
BPR business reengineering
ERPP post-implementation system integration.
Regression results for models 1.1, 1.2, and 1.3 are presented in Table 4 Panel A, B, and C respectively. The results show that significant positive associations between ERPE and both CEO and BPR are confirmed, with the overall model adjusted R-squared of around 25% (see Panel A). Similar to model 1.1, significant positive associations between ERPP and both CEO and BPR are confirmed, with the overall model adjusted R-squared of around 9% (see Panel B). Finally for stage 1, a significant positive association between ERPE and ERPP is confirmed, with the overall model adjusted R-squared of around 31% (see Panel C). In summary, both CEO involvements and BPR significantly and positively impact ERP effectiveness. These results are consistent with prior research (e.g., Aladwani, 2001; Bingi et al., 1999; Cheng et al., 2006; Dong, 2001; Ip and Chen, 2004; Kamhawi and Gunasekaran, 2009; Koch, 2001; Reimers, 2003; Umble and Umble, 2002; Yusuf et al., 2006; Zabjek et al., 2009). Also, ERP effectiveness is found to be positively associated with the post-implementation systems integration factor. Thus, these OLS regression results provide some evidence that underlying constructs predicted by the literature, theory and our conceptual model prevail between the intervening factors themselves and their underlying CSFs.
Operating performance of Chinese manufacturers 311
Notes: Variable definitions: ERPE: the average of ‘ERP effectiveness’ item scores ERPP: the average of ‘Post-ERP implementation’ item scores CEO: the average of ‘CEO involvement/sponsorship’ item scores BPR: the average of ‘BPR’ item scores.
5.4.2 Stage 2 OLS regression
The stage 2 regression examines the linear association between the BPI factor and the intervening factors of ERP effectiveness and post-implementation systems integration and the ORG control factor. Specifically, we examine the following model:
0 1 2 3 2: Model BPI ERPE ERPP ORGλ λ λ λ= + + +
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where
BPI business process improvement
ERPE ERP effectiveness
ERPP post-implementation system integration
ORG organisational structural changes.
According to the regression result presented in Table 5, significant positive associations between BPI and both ERPE and ERPP are established, with the overall model adjusted R-squared of around 56%. Also, BPI is found to be positively associated with the ORG control factor. Thus, this OLS regression result provided some evidence that BPI is positively affected by ERP effectiveness and post-implementation systems integration factor, controlling for the organisational change factor. Table 5 OLS regression results (stage 2)
Notes: Variable definitions: BPI: the average of ‘BPI’ item scores ERPE: the average of ‘ERP effectiveness’ item scores ERPP: the average of ‘post-ERP implementation’ item scores ORG: the average of ‘organisation structural changes’ item scores.
5.4.3 Stage 3 OLS regression
The stage 3 regression examines the linear association between the post-implementation operating performance factor, our ultimate factor of interest, and the BPI factor, controlling for the COMP factor and the module and customisation variables. Specifically, we examine the following model:
0 1 2 3 4 3: Model OPER BPI Module Custom COMPη η η η η= + + + +
where
OPER operating performance
BPI business process improvement
Module number of models implemented
Operating performance of Chinese manufacturers 313
Note: Variable definitions: OPER: the average of ‘operating performance’ item scores BPI: the average of ‘BPI’ item scores Module: ERP implementation intensiveness based on a five-point scale COMP: The average of ‘competition’ item scores.
As shown in Table 6, a significant positive association between perceived operational performance and BPI and both module and customisation is established, with the overall model adjusted R-squared of around 24%. Also, operational performance is found to be negatively associated with the COMP control factor. Thus, this OLS regression result provided some evidence that post-implementation operating performance is positively affected by BPI, controlling for the COMP factor and module and customisation variables. This result confirms prior research, which suggests that ERP implementations improve operational performance (e.g., O’Leary, 2004).
5.5 Findings
A summary of the staged regression results is shown in Table 7 (p-values are based on a one-tail test).
In summary, our main findings are:
1 BPI significantly and positively affects a company’s operational performance and therefore supports H8(a). Moreover, the control variables: COMP, module and customise are significantly associated with post-implementation operating performance, and in the directions predicted.
2 ‘ERP effectiveness’ and ‘Post-implementation systems integration’ are factors which are positively and significantly associated with BPI. Accordingly, we accept H6(a) and H7(a), respectively. Further, the ORG control factor is significant in the positively predicted direction.
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3 The ‘Post-implementation systems integration’ factor is positively and significantly related to the ‘ERP effectiveness’ factor, resulting in the acceptance of H5(a).
4 CEO involvement and BPR factors each positively and significantly affect both ‘ERP effectiveness’ and ‘post-implementation systems integration’ factors. Thus we accept both H1(a) and H2(a) and H3(a) and H4(a).
Collectively, these results confirm the staged conceptual model proposed in this study to explore and explain operating performance results for Chinese manufacturers in the aftermath of an ERP implementation. Table 7 Summary of the staged regression results
Notes: Where: OPER: the average of ‘operating performance’ item scores BPI: the average of ‘BPI’ item scores ERPE: the average of ‘ERP effectiveness’ item scores ERPP: the average of ‘post-ERP implementation’ item scores CEO: the average of ‘CEO involvement/sponsorship’ item scores BPR: the average of ‘BPR’ item scores ORG: the average of ‘organisation structural changes’ item scores COMP: the average of ‘competition’ item scores Module: ERP implementation intensiveness based on a five-point scale Custom: a dichotomous variable with a value 1 indicating customisation, 0 otherwise.
6 Conclusions and further research
This investigation makes a contribution by providing empirical evidence to support theories on ERP implementations, post-implementation ERP success, integration, process change, and operational performance of these systems for public manufacturing companies in China. Specifically, the results of our study confirm prior research on top ERP implementation CSFs and post-ERP operational performance. In addition, our study contributes to the existing research by investigating intervening factors, i.e., ERP effectiveness, post-ERP integration, and BPI. Finally, our study advances and provides positive evidence for a staged conceptual model that integrates findings of the extant literature using a unique data set for Chinese manufacturers implementing ERP systems.
One limitation of this study is that it relies on perceptual inputs from survey respondents. Another is that, by not limiting the survey to a single ERP vendor’s
Operating performance of Chinese manufacturers 315
implementations in China, we do not limit any variation in the ERP systems themselves [Reimers, (2003), p.339].
We currently have a system of interdependent equations that we have to solve for. The next stage in this research project is to simultaneously solve for all the implied equations. Our future research will also examine both accounting and market performance measures as possible validating measures of perceived operating performance. Consequently, measures from three levels will be examined: managerial perception, firm performance and market response to these ERP implementations. This three-prong approach enables us to triangulate results regarding the perceived and actual factors affecting the efficacy of the ERP implementations.
Acknowledgements
The authors would like to thank the reviewers for their constructive and helpful comments, which have substantially improved the manuscript.
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Notes 1 The exchanges rates between US dollar and Chinese yuan (RMB) were 1USD = 6.60231,
6.82702, 6.8225, 7.2946, and 7.8041 RMB at the end of year 2010, 2009, 2008, 2007, and 2006, respectively.
2 Due to missing values, our list-wise sample size is 93.
Appendix
Questionnaire items for variables and related factors (strongly disagree 1, 2, 3, 4 and 5 strongly agree) Code Category Items
B1 Business process improvement Improved cash collection and cash flow management B2 Business process improvement Improved inventory and supply chain management B3 Business process improvement Improved production management B4 Business process improvement Improved sales management B5 Business process improvement Reduced the financing reporting and closing period C1 ERP effectiveness ERP interface is well designed for dealing with the
firm’s daily operations C2 ERP effectiveness Employees can easily retrieve data from the database C3 ERP effectiveness Your business can effectively use the standard data
platform after ERP implementation C4 ERP effectiveness All business units can effectively process data
without relying on manual work
Operating performance of Chinese manufacturers 319
Questionnaire items for variables and related factors (strongly disagree 1, 2, 3, 4 and 5 strongly agree (continued) Code Category Items
C5 ERP effectiveness Information is better transferred and shared across business units
C6 ERP effectiveness Employees from different business units can better exchange and share opinions
D1 Post-implementation systems integration
Information integration on sales and distributions is effective and is completely done by the ERP system
D2 Post-implementation systems integration
Information integration on material management is effective and is completely done by the ERP system
D3 Post-implementation systems integration
Information integration on production planning is effective and is completely done by the ERP system
D4 Post-implementation systems integration
Information integration on purchasing management is effective and is completely done by the ERP system
D5 Post-implementation systems integration
Information integration on order-form management is effective and is completely done by the ERP system
D6 Post-implementation systems integration
Information integration on inventory management is effective and is completely done by the ERP system
D7 Post-implementation systems integration
Information integration on financial management is effective and is completely done by the ERP system
E1 CEO sponsorship and involvement
The CEO is clear about the goals set by the ERP project team
E2 CEO sponsorship and involvement
The CEO is the leader in making decisions related to ERP implementations
E3 CEO sponsorship and involvement
The CEO provided great financial support for ERP implementation
E4 CEO sponsorship and involvement
The CEO has given enough attention to the application of the ERP system after the implementation
F1 Business process reengineering (BPR)
BPR was implemented according to solutions provided by a standard ERP application software
F2 Business process reengineering Your company had done thorough planning before the BPR implementation
F3 Business process reengineering BPR was implemented as planned F4 Business process reengineering BPR was implemented primarily through
configurations of ERP software and also with some internal software development
F5 Business process reengineering Your IT department coordinated with the leading project team on BPR implementation
F6 Business process reengineering BPR was implemented and maintained primarily by related business units
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Questionnaire items for variables and related factors (strongly disagree 1, 2, 3, 4 and 5 strongly agree (continued) Code Category Items
G1 Organisation structural changes The ERP training programme not only include ERP but also emphasise the overall business goals of your company
G2 Organisation structural changes The ERP training outcome was evaluated G3 Organisation structural changes More cooperation has been achieved among basic-
level, mid-level, and high-level business units after ERP went live
G4 Organisation structural changes The CEO has given great attention to BPR and organisation structural changes
G5 Organisation structural changes The IT department has become more important among all departments
G6 Organisation structural changes The phenomenon of ‘information isolated island’ associated with the IT department was eliminated
H1 Degree of competition The substitutability of the products is high H2 Degree of competition The price competition in the industry is fierce H3 Degree of competition Your company is facing high competition pressure in
the domestic market H4 Degree of competition Your company is facing high competition pressure in
the global market H5 Degree of competition In the domestic market, the top five companies in the
industry all implemented ERP systems H6 Degree of competition In the global market, the top five companies in the
