e-BUSINESS MATURITY AND INFORMATION TECHNOLOGY

Elisabete Morais, José Adriano Pires

Instituto Politécnico de Bragança, Bragança, Portugal

Ramiro Gonçalves

Universidade de Trás-os-Montes, Vila Real, Portugal

Keywords: E-Business, Maturity, Stages of growth, Information Technology.

Abstract: Maturity models describe the maturing of the use of information systems in organizations. They are a useful

framework to describe an organization’s current position as well as a range of possible position in the future

in terms of their e-business maturity. The relationship between Information Technology (IT) and e-business

maturity is examined. We used a model of e-business maturity, Stages Of Growth for e-business (SOGe)

model, to put an organization in a maturity stage. In our survey we presented a set of technologies and we

asked to enterprises which of them are implemented, in development, planned or inexistent. We concluded

that there is a strongly correlation between IT implementation and the e-business maturity.

1 INTRODUCTION

Whether IT is considered in strategic terms or not, it

is generally accepted that the management efforts

surrounding the technology play a pivotal role in

ensuring its successful use (Booth and Philip, 2005).

The primary issue with any strategic tool is the

degree that its usage benefits the user. Yet, strategic

tools are often employed with little concrete

understanding of the advantages they engender

(Stone et al., 2007). It is popular to consider that the

usage of technology provides high returns, some

authors suggests this is not always true (Macmillan,

1997), (Grover et al., 1998). Technologies can, in

fact, have uncertain, little or no impact on

profitability (O’Sullivan, 1998), calling into question

how such strategic decisions are assessed

(Torkzadeh and Doll, 1999) and the reassessment IT

value (Tallon et al., 2000).

While IT is credited with enhancing productivity

(Anandarajan et al., 2000), it remains less clear to

what degree productivity from using IT is rewarding

in a competitive environment since a variety of

components must be used effectively to ensure

quality usage. As a result, since some time that

theme in IT research focuses on understanding

linkages between IT and its impact on performance

(Griswold, 1998). E-business IT investments have

many potential uses, such as enhancing customer

marketing and sales relationships or facilitating the

acquisition of the input goods to production (Kleist,

2003).

Providing a linkage between some IT use and

impacts on e-business maturity is the focus for the

study presented in this paper.

Our purpose in this paper is to know the e-

business maturity of the Portuguese enterprises and

identifying what is the IT used by these enterprises

and which is the correlation between the technology

and e-business maturity.

2 e-BUSINESS AND MATURITY

2.1 Definition of e-Business

The terminology involved within the field of

Information Communication Technology (ICT)

usage on the Internet is vast and contradictory. Two

frequently used terms are e-commerce and e-

business. Kalakota and Whinston (1996) define e-

commerce as the “… buying and selling of

information, products and services via computer

networks”. Laudon and Travel (2006) define e-

commerce as the “use of the Internet and the Web to

transact business”. Others argue that e-business

555

Morais E., Pires J. and GonÃ

galves R.

e-BUSINESS MATURITY AND INFORMATION TECHNOLOGY.

DOI: 10.5220/0001817005550558

In Proceedings of the Fifth International Conference on Web Information Systems and Technologies (WEBIST 2009), page

ISBN: 978-989-8111-81-4

encompasses the entire word of internal and external

electronically based activities, including e-

commerce (Kalakota and Robinson, 2003). In the

scope of this paper we used the definition of e-

business given by Kalakota and Robinson (2003).

2.2 The Stages Concept Maturity

in e-Business

The stages theory provides an insight into the way

IT evolves in organizations, and offers IT

management the possibility of managing this

complex phenomenon (Khandelwal and Ferguson,

1999).

Nolan’s stages hypothesis first appeared in the

70’s, bringing with a series of debates and

arguments on the validity and viability of the stages

concept in Information Systems (IS). After the first

model (Nolan, 1973), various models appeared.

More recently, with the emergence of the

Internet and e-commerce, several stages of growth

models were formulated to describe the various

phases involved in moving towards greater

sophistication with the respect to the use and

management of Information Systems/Information

Technology in the new e-commerce environment.

Amongst these are the electronic commerce maturity

model (KPMG, 1997); Grant’s Model (Grant, 1999);

the maturity model of McKay et al., (2000); the

model of Earl (2000); the SOG-e Model (Prananto et

al., 2001); the model of Rayport and Jaworski

(2002); the model of Rao et al. (2003) and the model

of Chan and Swatman (2004).

After comparing the models, we chose the SOGe

Model, in order to explain the e-business maturity in

the context of the Portuguese enterprises.

To compare the models we used the comparative

framework to evaluate e-business stages of growth

models (Morais et al., 2007).

As with all other stages of growth models, the

SOGe model assumes that a normal progression is

from a less mature stage to an increasing

sophistication over time (Prananto et al., 2003).

3 THE RESERCH DESIGN

3.1 Data Collection

A survey technique was used to collect data.

Prior to distribution, a series of pilot tests were

conducted with a group of 10 information system

director enterprises from a range of businesses and a

group of 5 PhD students. After the questionnaire had

been finalized, it was administered to 1000

managing directors of the biggest (according to

amount of business) Portuguese enterprises. A total

of 1000 presentation letters of the questionnaire

were sent by post. This presentation letter and e-mail

referred the website, the login and password for the

survey. The presentation letters of the questionnaire

were distributed in November 2007.

3.2 Sample

Within the cut-off date, set at 3 weeks after the

survey was distributed, there were 208 returned

questionnaires. Of the 208 questionnaires, 40 were

eliminated from the sample, because they were

incompletes. Effectively, 168 usable responses were

included in the sample for further analysis,

representing a good response rate at 16,8%. This is

well above the normal low response rate of 5-10%

for a postal survey (Alreck and Settle, 1985),

(Barnett, 1991).

4 RESULTS

4.1 Demographics

The sample is characterized by values on several

variables that are displayed in table 1. The

respondents self-reported all the demographic values

that are reported.

Table 1: The demographics for the sample.

Function

Director

(%)

General

Director

(%)

Administrator

(%)

Executive

(%)

Other

(%)

50,0%

7,3% 5,5% 14,6% 22,6%

Education Level

Higher education (%)

Post Graduation

(%)

Secondary School (%)

57,6% 29,7% 12,7%

Number of employees

1-50 (%)

51-250 (%) 251-500 (%) 501-1000

(%)

1000+

(%)

11,9%

28,1% 18,8% 23,1% 18,1%

Website

Yes (%)

No (%)

83%

17%

Within the sample, 50% are directors, 7,3%

general directors, 5,5% administrators, 14,6%

executives and 22,6% have other function in

enterprise. The majority of the cases are responsible

for Information Systems (IS) department. In the

sample we have 40% with less than 250 employees,

condition in Portugal to be SME. But this only

happens when the amount of business is minor than

WEBIST 2009 - 5th International Conference on Web Information Systems and Technologies

556

50 000 000 Euros and the active also minor than 43

000 000 Euros. Within the sample, none of them is

SME. 83% indicated the website and 17% do not

indicated.

4.2 Relationship between IT and

e-Business Maturity

In figure 1 we can see that almost half of the sample

is between stage 5 and 6 and only 26% are in the

two first maturity stages.

e-business maturity

Stag e 1

13%

Stage 2

13%

Stage 3

12%

Stage 4

18%

Stage 5

27%

Stage 6

17%

Figure 1: E-business maturity of the biggest Portuguese

enterprises.

The respondents were questioned about a set of

technologies: Enterprise Resource Planning (ERP),

Customer Relationship Management (CRM), Supply

Chain Management (SCM), Data warehouse,

Business Intelligence (BI), Electronic Data

Interchange (EDI), Business-to-Business (B2B),

Business-to-Consumer (B2C), Business-to-

Government (B2G), Workflow, Groupware and

Knowledge Management (KM). The respondents

could choose one of the following options:

implemented, in development, planned or inexistent.

Besides these options the respondents could also add

other technologies used by the companies.

In order to explore the relationship between each

technology and the maturity, we used the Spearman

Correlation test. Both the variables are ordinal, the

maturity is an ordinal variable with values from one

to six (corresponding to the stage one to six) and the

IT is an ordinal variable with values from one to

four (corresponding to implemented, in

development, planned and inexistent, respectively).

The results of the test they are shown in table 2.

Table 2: Spearman Correlation test between IT and

Maturity.

Maturity

ERP

Correlation coefficient -,259(**)

Sig ,001

N 164

CRM

Correlation coefficient -,479(**)

Sig ,000

N 158

SCM

Correlation coefficient -,458(**)

Sig ,000

N 157

Correlation coefficient -,423(**)

Sig ,000

N 160

Correlation coefficient -,438(**)

Sig ,000

N 155

EDI

Correlation coefficient -,381(**)

Sig ,000

N 158

B2B

Correlation coefficient -,667(**)

Sig ,000

N 155

B2C

Correlation coefficient -,559(**)

Sig ,000

N 148

B2G

Correlation coefficient -,491(**)

Sig ,000

N 146

Workflow

Correlation coefficient -,424(**)

Sig ,000

N 157

Groupware

Correlation coefficient -,420(**)

Sig ,000

N 147

Correlation coefficient -,428(**)

Sig ,000

N 147

** Correlation is significant at the 0.01 level

The test results lead us to conclude that in all

technologies the correlation with the maturity is

significant at 1%. That is, the higher the maturity

stage is, the bigger is the probability of the

technology being implemented, and the less the

maturity stage is, the higher is the probability of the

non-existence of the technology.

The strongest correlation is with B2B and the

weakest is with ERP, however, all of them are

significant at the 0,01 level. The maturity and the IT

above referred are not independent.

We also made the correlation between all the

technologies and the enterprise dimension (number

of employees), and through the results of the test we

concluded that the variable number of employees is

not independent from the IT.

5 CONCLUSIONS

Understanding to what degree a strategic tool

benefits the organization is a critical issue (Stone et

e-BUSINESS MATURITY AND INFORMATION TECHNOLOGY

557

al., 2007). Moreover, understanding to what degree a

strategic tool benefits the e-business maturity is also

a crucial matter. We cannot conclude which is the

degree, but with our survey we can conclude that

there is a correlation between some technologies and

the maturity of the e-business, being that some have

an almost perfect correlation.

In the last few years several initiatives have been

taken in Portugal and, at the end of 2005, the

Technological Plan was launched. This plan,

included in a broader plan - the National Action

Program for Growth and Jobs, 2005-2008 - is based

on three main axes: knowledge, technology and

innovation.

Summing up, considering all the technologies we

can conclude that they are not independent from the

maturity variable, nor of the dimension of the

enterprise. The more employees the enterprise has

and the bigger maturity stage is, the greater is the

probability to have the technologies implemented.

Our survey was implemented in the 1000 biggest

Portuguese enterprises. It would also be interesting

to apply it to SME and for activity sectors.

REFERENCES

Alreck, L., Settle, B., 1985. The survey research

handbook. Irwin.

Anandarajan, M., Igbaria, M., Anakwe, U. P., 2000.

Technology acceptance in the banking industry: a

perspective from a less developed country.

Information Technology & People, 13 (4), 298-312.

Barnett, V., 1991. Sample survey: Principles and methods.

Edward Arnold.

Booth M. E., Philip G., 2005. Information systems

management: role of planning, alignment and

leadership. Behaviour & Information Technology,

24(5), 391-404.

Chan C., Swatman, P., 2004. B2B E-commerce stages of

growth: the strategic imperatives. In Proceedings of

the 37th Hawaii International Conference on Systems

Science .Hawaii, USA, pp. 80230a.

Earl, M. J., 2000. Evolving the E-Business. Business

Strategy Review, 11 (2), 33-38.

Grant S., 1999. E-Commerce for Small Businesses,

Innovation Through Electronic Commerce. In

Proceedings of the 2

International Conference.

Manchester, England.

Griswold, C., 1998. Evaluating IT investments. Health

Management Technology, 19, 24-26.

Grover, V., Teng, J., Fiedler, K., 1998. IS investment

priorities in contemporary organizations.

Communications of the ACM, 41, 40-48.

Kalakota, R., Whinston. A., 1996. Frontiers of Electronic

Commerce. Addison-Wesley.

Kalakota, R., Robinson M., 2003. E-business 2.0:

Roadmap for Success. 2

edition, Addison-Wesley.

Khandelwal, V., Ferguson, J., 1999. Critical Success

Factors (CSFs) and the Growth of IT in Selected

Geographic Regions. In Proceedings of 32nd Hawaii

International Conference on Systems Sciences

(HICSS-32), USA.

Kleist V., 2003. An Approach to Evaluating E-Business

Information Systems Projects. Information Systems

Frontiers, 5 (3), 249-263.

KPMJ, 1997. Electronic Commerce Research Report.

London, UK.

Laudon, K., Traver C., 2006. E-commerce Business,

Technology, Society. Prentice Hall.

Macmillan, H., 1997. Managing information systems:

three key principles for general managers. Journal of

General Management, 22, 12-23.

McKay, J., Prananto, A., Marshall, P., 2000. E-business

Maturity: The SOG-e Model. In Proceedings of the

Australasian Conference on Information Systems

(ACIS), Australia.

Morais, E., Gonçalves, R., Pires J., 2007. Electronic

Commerce Maturity: A Review of the Principal

Models. In Proceedings of IADIS International

Conference - E-Society 2007, Lisbon, Portugal, 3-6

July.

Nolan, R. L., 1973. Managing the Computer Resource: A

Stage Hypothesis. Communications of ACM, 16 (7),

339-406.

O’Sullivan, O., 1998. Technology spending’s uncertain

payback. USBANKER, 108, 32-44.

Prananto, A., McKay, J., Marshall, P., 2001. Frameworks

to Support E-Business Strategy. In Global

CoOperation in the New Millennium, The 9

European Conference on Information Systems. Bled,

Slovenia.

Prananto, A., Marshall, P., McKay, J., 2003. Spectrum of

eBusiness Maturity in Australian SMEs: A Multiple

Case Studies Approach to the Applicability of the

Stages Of Growth for eBusiness Model. In

Proceedings of the Eleventh European Conference on

Information Systems, Napoli, Italy, 16-21 June.

Rao, S., Metts, G., Monge, C., 2003. Electronic

Commerce Development in Small and Medium Sized

Enterprises: A Stage Model and its Implications.

Business Process Management Journal, 9(1); 11-32.

Rayport, J. F., Jaworski B. J., 2002. Introduction to E-

Commerce. New York, McGraw-Hill.

Stone, R. W., Good, D. J., Baker-Eveleth L., 2007. The

impact of information technology on individual and

firm marketing performance. Behaviour and

Information Technology, 26 (6), 465-482.

Tallon, P., Kraemer, K. L., Gurbaxani, V., 2000.

Executives’ perceptions of the business value of

information technology: a process oriented approach.

Journal of Management Information Systems, 16(4),

145-173.

Torkzadeh, G., Doll, W.J., 1999. The development of a

tool for measuring the perceived impact of information

technology on work. Omega. 27, 297-300.

WEBIST 2009 - 5th International Conference on Web Information Systems and Technologies

558