The Determinants of ERP, SCM and CRM Systems in European Firms Elsa Fontainha ISEG – Technical University of Lisbon, Rua Miguel Lupi, 20, 1200 Lisbon, Portugal
[email protected]
Abstract. The aim of this paper is to study of the determinants of the adoption in the European firms of Enterprise Resource Planning (ERP), Supply Chain Management (SCM) and Customer Relationship Management (CRM) systems. The empirical analysis is based on the European e-Business Market Watch microdata (14,065 firms, 29 countries, 10 sectors of activity) and models the probability of adopting those systems using probit models. The results show the importance of innovative (product and process) firm behavior and size as common determinants of the adoption of the three systems. Other factors are system specific. Keywords: Use of EIS subsystems; European firms; SME; probit models.
1 Introduction Most European firms have Internet access and use electronic email [1] [2]; however, the use of e-business through the different components is far from being a generalized behavior. The three main aspects of e-business - intra-organizational (internal to the firm), inter-organizational (between firms and supply chain) and e-commerce (customer to firm) [3; p.3] - are absent in most small enterprises. Enterprise Information Systems (EIS) allow the creation and development of links among the firm internally and with clients and suppliers. This has a strong impact on the way information is managed such as Intranet, KMS, EDM, Enterprise Resource Planning (ERP), Supply Chain Management (SCM), and accounting. It also affects efficiency, costs and profits and quality of goods and services provided. SCM develops the relationship between the buyer and supplier and facilitates information and financial flows as well as those of goods and services [4]. Empirical studies about EIS usually focus on specific sectors or countries. For a recent survey centered on Small and Medium Enterprises (SMEs) see [5]. My research takes advantage of a rich database and analyses a broad set of sectors and countries. The aim of this paper is to study of the determinants of the adoption in the European firms of Enterprise Resource Planning (ERP) Supply Chain Management (SCM) and Customer Relationship Management (CRM) systems. Special attention will be given to SME because they represent a large share of production and employment in Europe and face particular difficulties in the adoption of ICT [1; p. 53]. J.E. Quintela Varajão et al. (Eds.): CENTERIS 2010, Part I, CCIS 109, pp. 147–150, 2010. © Springer-Verlag Berlin Heidelberg 2010
148
E. Fontainha
2 Data and Methodology The empirical analysis is based on e-Business W@tch dataset (2006), which includes 14,065 firms from 29 countries and 10 sectors. The countries included are listed in [6]. The activity sector comprise: Food and beverages, Footwear, Pulp and paper, ICT Manufacturing, Consumer electronics, Shipbuilding and repair, Construction, Tourism, Telecommunications and Hospital activities. Table 1. Variables definitions and means by firm size Variable name Dependent Variables ERPYN SCMYN CRMYN Independent Variables SIZEMIC SIZES SIZEM SIZEL SIZESME EDU50 ICTEXP ICTINF FINR INOVPT INOVPC COMP NMK INTMK CPRIV CBUS CMIX
Mean All N=14,065
Mean Large 250+ N=682
Mean SME 10-249 N=6,201
=1 if firm uses ERP (0 otherwise) =1if firm uses SCM (0 otherwise) =1 if firm uses CRM (0 otherwise)
0.23 0.15 0.16
0.55 0.30 0.23
0.28 0.17 0.19
=1 if firm is 1-9 (0 otherwise) =1 if firm is 10-49 (0 otherwise) =1 if firm is 50-249 (0 otherwise) =1 if firm is 250+ (0 otherwise) =1 if firm is 10-219 (0 otherwise) =1 if firm has 50%+ Univ empl (0 otherwise) Future impact intensity (min=0; max=7) Positive influence of ICT (min=0; max=7) =1 if firm turnover decreased in 2005 (0 otherwise) =1 if new products in 2005 (0 otherwise) =1 if new internal processes in 2005 (0 otherwise) =1 if ICT increased in sector (0 otherwise) =1 if national market is the main (0 otherwise) =1 if international market is the main (0 otherwise) =1if primary customers private cons.(0 otherwise) =1 if primary customers other business(0 otherwise) =1 if primary customers mixed(0 otherwise)
0.43 0.30 0.20 0.06 0.51 0.26 4.12 5.00 0.11 0.40 0.33 0.54 0.83 0.16 0.30 0.34 0.20
0 0 0 1 0 0.24 4.98 5.57 0.07 0.52 0.51 0.64 0.72 0.27 0.15 0.31 0.12
0 0 0 0 1 0.16 4.24 5.07 0.10 0.40 0.36 0.53 0.80 0.19 0.26 0.38 0.19
Definition
The three independent variables (each corresponding to a EIS subsystem) were selected from the questions: (i) “Do you use for managing information in the company/(or hospital) an ERP system, that is Enterprise Resource Planning System?” (ii) “Do you use for managing information in the company/(or hospital) an SCM system, that is Supply Chain Management System?” (iii) “Does your company (or hospital) use a CRM system, that is specific software suite for customer relationship management?”. In accordance with relevant literature, different determinants were essayed. These were related to firm characteristics (size, country, sector, financial situation, and skilled personnel), and firm strategies, behavior and expectations (expected impact of ICT on several domains, innovative practice, competitive position, market geographical orientation, and market customer orientation). The independent and dependent variables are presented in Table 1 (global values and those for Large and SMEs; micro-enterprises not shown). The country and activity sector will be included as dummies in future research. Innovation of processes and
The Determinants of ERP, SCM and CRM Systems in European Firms
149
products took place in more than half the large enterprises. For SMEs these values were consistently lower (36% and 40% respectively). Market orientation also differed between large and SMEs with large firms being more internationally oriented. Compared with SMEs, the use of ERP and SCM in large firms is almost double (28% and 55% for ERP and 17% and 30% for SCM). The methodology to study determinants of ERP, SCM and CRM follows partially [7], who studied the adoption of e-commerce (firm as buyer and as seller) using the same database as this paper. The adoption of each of the three systems (ERP, SCM and CRM) is studied separately.
3 Results and Discussion The results from the probit estimations are shown in Table 2. Four determinants were found to be common to the three systems. The opinion about the positive influence of ICT (ICTINF) and the expected future impact of ICT (ICTEXP) on several domains of firm activity contribute to the likelihood of adoption. Similarly, the innovation activity measured by the introduction of new or significantly improved internal processes (INOVPC) and new or substantially improved products or services (INOVPT ) contributes to EIS adoption, the first being stronger than the second (varying the probability of adoption between 6 % and 9%) . The size of the firm, as expected, influences the use of EIS. Being a micro enterprise (between 1 and 9 employees) contributes negatively to the adoption of SCM and CRM. By contrast, the probability of adopting an ERP system for large enterprises (250 or more employees), increases by 37%. Table 2. Use of ERP, SCM and CRM; Marginal Effects after Probit Variable SIZEMIC(a) SIZEL(a) SIZESME(a) EDU50(a) ICTEXP ICTINF FINR(a) INOVPT(a) INOVPC(a) COMP(a) INTMK(a) CBUS(a) CPRIV(a)
ERP .37*** .12*** .00 .02*** .02*** -.02 .04*** .09*** .01 .03* .06*** -.02
SCM CRM -.11*** -.05** -.07*** -.01 .02*** .01*** -.00 .04*** .06*** .00 .01 .02* .01
.02 .05*** .01*** .01*** -.04*** .06*** .08*** .04*** .04*** .02** .02*
N 10,891 10,919 10,832 Pseudo R2 0.1192 0.0706 0.1146 Log likelihood -5024.1 -4150.5 -4100.1 Significance levels are: *** (1%), **(5%), * (10%). (a)Marginal effects are for discrete change of the dummy variable from 0 to 1.
150
E. Fontainha
The results for SMEs are contradictory: being a SME increases the probability of adopting ERP by 12% but decreases the probability of adopting SCM by 7%. Some authors, as [8] have highlighted the heterogeneous universe of SMEs, which could explain these results. For CRM system adoption two factors are statistically significant: the educational level of employees (EDU50) has a positive influence and the financial restrictions (FINR) have a negative effect. These results suggest that CRM requires more human capital and investment. Surprisingly, these two factors did not statistically show any influence on the adoption of ERP or SCM. The market composition and orientation affects ERP use and CRM adoption. While producing for other business influences the three EIS use, it is stronger for ERP. Having an international market orientation and being engaged in e-business as a result of competition stimulus, increase the probability of adopting CRM by 4%. The global results for competition influence converge with the hypothesis formulated by [9] that threat of entry should influence e-business positively, but too much competition should influence it negatively.
4 Conclusions and Future Avenues of Research Using a public dataset with a wealth of information on European firms, the determinants of the adoption of some EIS subsystems were studied. The results show the importance of firm size, innovative behavior and ICT positive expectations as key determinants to the likelihood of a firm adopting any of the three subsystems studied (ERP, SCM and CRM). Future research includes the analysis by sectors and countries, combining ebusiness W@tch data with data from Eurostat sources and improving and exploring new methodologies and models.
References 1. European Commission: The European e-Business Report 2008. The impact of ICT and e-business on firms, sectors and economy, European Commission (2008) 2. European Commission and Sectoral e-Business Watch : E-Business Survey (2006) 3. Levy, M., Powell, P.: Strategic Intent and E-Business in SMEs: Enablers and Inhibitors. Information Resources Management Journal 18(4), 1–20 (2005) 4. Kauremaa, J., Nurmilaakso, J.-M., Tanskanen, K.: E-Business enable operational linkages: the role of RosettaNet in integration the telecommunications supply chain. Int. J. Production Economics (2009) (article in press) doi:10.1016/j.ijpe.2009.08.024 5. Parker, C.M., Castleman, T.: New directions for research on SME e-Business: insights from an analysis of journal articles from 2003 to 2006. Journal of Information Systems and Small Business 1(2-2), 21–40 (2007) 6. E-Business W@tch Survey Methodology, http://www.ebusiness-watch.org 7. Vicente, M.R., López, A.J.: Patterns of E-Commerce Adoption and Intensity Evidence for the European Union-27. Documento de Trabajo, n.47/2009 (2009) 8. Matlay, H.: E-entrepreneurship and small e-business development. Towards a comparative research agenda Journal of Small Business and Enterprise Development 11(3), 408–414 9. Martin, L.: Understanding the implementation of e-business strategies: Evidence from Luxemburg, MPRA n.13645 (2009)
