SlideShare une entreprise Scribd logo
1  sur  43
Télécharger pour lire hors ligne
The Emerald Research Register for this journal is available at            The current issue and full text archive of this journal is available at
   www.emeraldinsight.com/researchregister                                   www.emeraldinsight.com/1741-0398.htm




JEIM
18,4                                      Factors affecting ERP system
                                                    adoption
                                        A comparative analysis between SMEs and
384                                                 large companies
                                                   G. Buonanno, P. Faverio, F. Pigni, A. Ravarini,
                                                           D. Sciuto and M. Tagliavini
                                                                   `
                                                    CETIC Universita Cattaneo – LIUC, Castellanza, Italy

                                     Abstract
                                     Purpose – Proposes providing an insight about enterprise resource planning (ERP) adoption,
                                     highlighting contact points and significant differences between the way small to medium-sized
                                     enterprises (SMEs) and large companies approach such a task.
                                     Design/methodology/approach – The research is based on a wide literature review, focused on the
                                     identification of a taxonomy of business and organizational factors influencing ERP adoption. The
                                     deriving research model was incorporated in a questionnaire that was preliminarily tested and finally
                                     provided to a sample of 366 companies of any size. Responses were collected through personal
                                     interviews made by a dedicated team to a top manager.
                                     Findings – The analysis of the empirical data shows that business complexity, as a composed factor,
                                     is a weak predictor of ERP adoption, whereas just company size turns out to be a very good one. In
                                     other words, companies seem to be disregarding ERP systems as an answer to their business
                                     complexity. Unexpectedly, SMEs disregard financial constraints as the main cause for ERP system
                                     non-adoption, suggesting structural and organizational reasons as major ones. This pattern is
                                     partially different from what was observed in large organizations where the first reason for not
                                     adopting an ERP system is organizational. Moreover, the decision process regarding the adoption of
                                     ERP systems within SMEs is still more affected by exogenous reasons or “opportunity of the moment”
                                     than business-related factors, contrary to large companies that are more interested in managing
                                     process integration and data redundancy/inconsistency through ERP implementation.
                                     Research limitations/implications – The research model is based on the assumption that
                                     business complexity and organizational change are the most relevant variables influencing ERP
                                     adoption, and such variables are explained through a set of factors inherently limited by the results of
                                     the literature review.
                                     Practical implications – The results of the empirical research provide indication to SMEs willing
                                     to take into consideration the adoption of an ERP system. The same outcomes could be incorporated
                                     into the development strategies of ERP software houses.
                                     Originality/value – This paper contributes to enhancing the understanding of the factors
                                     influencing the evolution of information systems within SMEs with respect to large companies.
                                     Keywords Manufacturing resource planning, Small to medium-sized enterprises, Organizational change
                                     Paper type Research paper



Journal of Enterprise Information    Introduction
Management                           The capability of enterprise resource planning (ERP) systems to manage a company’s
Vol. 18 No. 4, 2005
pp. 384-426                          resources efficiently and effectively by providing a total, integrated solution for its
q Emerald Group Publishing Limited
1741-0398
                                     information processing needs (Fui Hoon Nah et al., 2001) has persuaded both
DOI 10.1108/17410390510609572        practitioners and managers of the importance of integrated systems, not only for large
multinational organizations, but also for small and medium-sized firms (Van                     Factors affecting
Everdingen et al., 2000).                                                                          ERP system
    The evaluation of the contribution of ERP systems in terms of both value creation and
economic returns is a difficult task, because of the extent of the organizational changes               adoption
(Lozinsky, 1999; Shtub, 1999; Willcocks and Lacity, 1998) to which their implementation
leads, as well as the difficulties in predicting the return on investment (Mabert et al.,
2001). The competences required to manage properly the organizational change                               385
determined by an ERP system implementation is still a debated issue. The most qualified
literature has always stressed the importance of change and project management
competences as critical success factors for ERP implementation (Davenport, 2000;
Mandal and Gunasekaran, 2003; Motwani et al., 2002), hereby indirectly raising the issue
of small to medium-sized enterprises’s (SMEs’s) lack of organizational preparation. Such
a situation is mainly caused by the low extent of formalization of people’s roles and
responsibilities that is expressed by with their continuous re-shuffle (Dutta and Evrard,
1999). This structural condition makes the identification of ERP implementation’s main
figures, such as the process owner and the key user (Davenport, 2000), extremely difficult
to achieve. Beside this, SMEs generally suffer from a widespread lack of culture, as to the
concept of business process: it is not by chance that the reinforcement of the concept of
business process is often claimed among the critical success factors in ERP
implementation (Beretta, 2002). In particular, the business process concept helps
promoting co-operation and convergence of efforts among managers (i.e. managerial
integration), versus the internal competition induced by the functionally-oriented
organizational models which is typical of SMEs.
    One of the most misleading legacies of traditional software project management is
that the company expects to gain value from the use of the software application as soon
as it is installed (Al-Mashari et al., 2003). Since the adoption of an ERP system requires
extensive efforts, both for the technological and business aspects of the
implementation, neither information technology (IT) practitioners nor researchers
have developed a deterministic method to evaluate the related impacts (Al-Mashari,
2002). In spite of the benefits potentially offered by ERP systems (Banker et al., 1998;
Davenport, 1998; Gable, 1998; Hicks and Stecke, 1998; Minahan, 1998) the evaluation
issue plays an essential role regardless the company size; during the planning phase it
is critical for companies to figure out whether a specific ERP system fits their business
practices. When the features of the software application do not correctly fit the
business requirements two possible strategies can be identified:
    (1) Change the business processes to fit the software with minimal customization. On
         one hand, fewer modifications to the software application should reduce errors
         and help to take advantage of newer versions and releases (Fui Hoon Nah et al.,
         2001). On the other hand, this choice could mean changes in long-established
         ways of doing business (that often provide competitive advantage), and could
         shake up important people roles and responsibilities (Dewett and Jones, 2001;
         Koch et al., 1999).
    (2) Modify the software to fit the processes. This choice would slow down the
         project, could affect the stability and correctness of the software application and
         could increase the difficulty of managing future releases, because the
         customizations could need to be torn apart and rewritten to work with the
         newer version (Koch et al., 1999). Conversely, it implies less organizational
JEIM          changes, because it does not require dramatically changing the company best
              practices, and therefore the way people work.
18,4
       Although ERP vendors are concentrating on the customization process needed to match
       the ERP system modules with the actual features of existing processes in a number of
       different industries, several studies show that configuring and implementing ERP
386    systems is a complex and expensive task (Van Everdingen et al., 2000; Mabert et al., 2000).
          Several aspects related to this twofold approach towards ERP adoption and
       implementation become even more critical, for their known specificities, within SMEs
       (Ravarini et al., 2000; Van Everdingen et al., 2000). Although the effective use of
       business information is a strategic goal for companies of any size, nowadays most of
       the ERP systems available on the market are too expensive for the financial
       capabilities of smaller companies (Chau, 1995; Gartner Group and Dataquest, 1998,
       1999). SMEs differ from large companies in important ways affecting their
       information-seeking practices (Lang et al., 1997). These differences include the:
           .
              lack of (or substantially less sophisticated) information system management
              (Kagan et al., 1990);
           .
              frequent concentration of information-gathering responsibilities into one or two
              individuals, rather than the specialization of scanning activities among top
              executives (Hambrick, 1981);
           .
              lower levels of resource available for information-gathering; and
           .
              quantity and quality of available environmental information (Pearce et al., 1982).

       Chan (1999) asserts that many SMEs either do not have sufficient resources or are not
       willing to commit a huge fraction of their resources due to the long implementation
       times and high fees associated with ERP implementation. The resource scarcity, the
       lack of strategic planning of information systems (IS) (Cragg and Zinatelli, 1995; Levy
       and Powell, 2000; Zinatelli et al., 1996), the limited expertise in IT (Levy and Powell,
       2000) and also the opportunity to adopt a process-oriented view of the business are
       among the factors that strongly influence, either positively or negatively, ERP
       adoption by SMEs. Thus it is necessary to find out alternative solutions providing the
       ERP capabilities at an affordable price, including implementation costs (Rao, 2000).
       Some ERP vendors have taken up the gauntlet and have been moving their attention
       toward SMEs (Gable and Stewart, 1999) by offering simplified and cheaper solutions
       (Kirchmer, 1998) from both the organizational and technological points of view,
       pre-configured systems based on best-practices at a fraction of the cost originally
       required and promising implementation times of 60 days. In spite of such promises,
       there is not a general agreement on the effectiveness of such systems. As a result, the
       current ERP systems adoption rate in SMEs is still low. Furthermore, even if ERP
       implementation differences between large and small organizations are recognized in
       literature (Bernroider and Koch, 2001), their focus is on the decision-making process.
       Hence, other issues need to be further explored: To what extent SMEs informational
       needs are different with respect to large companies? Are SME peculiarities a real
       obstacle to ERP adoption? Is it possible to identify a relationship between
       organizational change and ERP adoption in companies of different size?
           This paper studies the factors influencing ERP systems adoption, and discusses to
       what extent the differences between SMEs and larger firms affect such factors,
contributing to the increasing literature on ERP adoption in small businesses. Through          Factors affecting
a detailed literature review, a set of indicators are identified as variables which could            ERP system
influence the ERP adoption process. These indicators have been tested on the field
through an empirical study carried out on a sample of 366 companies.                                    adoption

Conceptual framework
The literature provides different definitions of ERP systems: Rosemann (1999) defines an                      387
ERP system as a customizable, standard application software which includes integrated
business solutions for the core processes (e.g. production planning and control,
warehouse management) and the main administrative functions (e.g. accounting, human
resource management) of an enterprise. Gable (1998) defines it as a comprehensive
package software solution that seeks to integrate the complete range of business
processes and functions in order to present an holistic view of the business from a single
information and IT architecture. Watson and Schneider (1999) define ERP as an
integrated, customized, packaged software-based system that handles the majority of an
enterprise’s system requirements in all functional areas such as finance, human
resources, manufacturing, sales, and marketing. It has a software architecture that
facilitates the flow of information among all functions within an enterprise. It is built on a
common database and is supported by a single development environment. Previous
research works (Gibson et al., 1999; Ryan, 1999) suggested how ERP adoption and
implementation could be an highly complex task in which strong managerial and
strategic competences are required to achieve the best fit between the business
peculiarities and the system itself and to deal with the unavoidable organizational
impact induced by an ERP implementation. Other studies outlined different adoption
patterns depending on company size and also observed that smaller companies face only
subset of the needs and opportunities of larger organizations (Markus and Tanis, 2000).
Furthermore, for a long time ERP adoption reasons within SMEs were explained only by
contingency or exogenous factors (Tagliavini et al., 2002). To investigate these
differences further, the research model presented in this paper explores to what extent
the business complexity (measured from a set of business factors) and the awareness of
the organizational requirements (measured by the extent of organizational change) affect
the extent of ERP adoption. Such an effort seems, in fact, feasible for organizations
experiencing high business complexity and information needs, and expecting, or even
planning, significant organizational changes.
   The methodology contribution of this paper is experimentally proved by testing the
relationship between business complexity, organizational change and ERP adoption on
300 SMEs through direct, survey-based, interviews. Such an approach, based on a
statistical analysis on a high number of respondents, implies that its findings are not
easily comparable to other previous research works that are often based on case
studies on a very small set of companies.
   The following sections will detail the two main components of the conceptual
framework: the business factors and the organizational change.

Business factors
Although the organizational structure of larger firms could be very different from SMEs,
it is reasonable to assume that companies of any size, characterized by high
organizational complexity (or “business complexity”), also show a critical need for
JEIM   coordination and control of business activities which, in turn, is related to the complexity
18,4   of the information system (Grinyer et al., 1986; Lorange, 1980; Vancil and Lorange, 1975).
       Since ERP systems have been very often advocated by researchers and practitioners as
       “the answer” to manage the complexity of information flows more effectively, this last
       interpretation of business complexity, will be used in the research model to investigate if
       the “the condition” of being a complex organizations (which is measured by a set of
388    business factors) and a greater extent of ERP adoption are straight related factors. Hence,
       the model approaches ERP systems as a sort of “black box” and thus their undeniable
       inner complexity (expressed by implementation and technological issues for instance) is
       taken for granted, and are therefore considered only an exogenous factor embedded into
       the ERP concept itself. In particular, the several issues related to ERP system chartering,
       development and maintenance (i.e. project and change management issues or cultural
       and organizational un-readiness) are typical of the “critical success factors” stream of
       research (Davenport, 2000; Mandal and Gunasekaran, 2003; Motwani et al., 2002) and
       generally refer more to the success of the implementation than to the reasons that bring
       companies to evaluate the opportunity of implementing an ERP system. Therefore, is
       business complexity the possible explanation?
           The assessment of the complexity measures is partially based on previous works
       (Grinyer et al., 1986; Yasai-Ardekani and Haug, 1997) that have developed and
       proposed metrics essentially based on size, diversification, and divisionalization. This
       paper neither proposes any new measure nor tests their reliability; instead it studies
       their occurrence in ERP adoption. Since the consistency of these indicators is essential
       for the theoretical validity of the whole framework, a detailed analysis of the IS
       literature has been performed in order to identify a set of additional business factors:
           .
              Company size (micro, small, medium, large). Existing literature confirms the
              existence of a mutual dependence between size and organizational complexity.
              Kimberly (1976) stressed the necessity of applying a different approach
              depending on the industry the company belongs to: for the services industry the
              number of employees has a better fit, while for manufacturing companies the
              turnover seems to be a better match. In any case, literature emphasizes size as
              one of the issues increasing the need for co-ordination and control of
              organizational activities (Howard and Hine, 1997; Yasai-Ardekani and Haug,
              1997). Apart from any organizational or strategic remark, other research works
              (IDC, 1999) simply suggest a direct relationship between the size of organizations
              and the percentage of organizations where ERP has been implemented.
           .
              The market area (local, regional, national, international). Working on a wider
              market area requires the management of more differentiated legal and cultural
              issues, thus introducing a higher level of complexity (Davenport, 1998; Hamel
              and Prahalad, 1994; Prahalad, 1990; Sanders and Carpenter, 1998), as well as the
              facing of competitive pressures characterizing the international markets (Bartlett
              and Ghoshal, 1989; Roth and O’Donnell, 1996; Rumelt, 1974). In addition, as
              companies become more global and develop international supply chains, the
              limitations of MRPII have become apparent. Literature has identified the
              attempts being made by many organizations to expand their IS infrastructure
              beyond their organizational boundaries through the development of
              inter-organizational business systems. Consequently, this has resulted in the
              widespread adoption of ERP solutions (Irani, 2002).
.
       The membership an industrial group (either as the holding or as a controlled firm).     Factors affecting
       This variable seems to be strongly related to the co-ordination of dispersed               ERP system
       business units, in terms of alignment of processes and procedures both between
       the holding and the controlled companies and among controlled companies                        adoption
       themselves. However, if the imposition of common operating processes on all
       units could lead to a tight coordination between the controlled companies, in a
       multiregional context strict process uniformity could be counterproductive in                      389
       terms of flexibility (Davenport, 1998).
   .
       The presence of branch offices (localization and number of branches). The
       management of information flows is a crucial issue for companies with branch
       offices which need to be remotely controlled. In larger organizations the
       development of intranets is often characterized by a lack of coordination and
       supervision (Horgan, 1997). SMEs face different issues (i.e. the cultural and
       technological levels of the entrepreneur): this is one of the aspects that must be
       considered to comprehend fully the fall-outs in terms of management complexity,
       organizational impact and required competencies.
   .
       The level of diversification (in terms of products, markets, technologies).
       Operating in different product-market combinations introduces another level of
       complexity (Yasai-Ardekani and Haug, 1997). In related-diversified firms, an
       increase in the number of businesses adds information-processing demands by
       increasing business-unit interdependencies (Hill and Hoskisson, 1987; Kerr, 1985;
       Michel and Hambrick, 1992; Pitts and Hopkins, 1982). In unrelated-diversifiers,
       as the number of businesses increases, the information-processing requirements
       associated with maintaining efficient internal capital markets also increase
       (Jones and Hill, 1988). Moreover, because of the greater need for co-ordination
       and control of activities, complex organizations will tend to have specialized
       planning departments, employ a larger number of planners and consequently
       devote a substantially larger amount of financial resources to strategic planning
       (Grinyer et al., 1986; Kukalis, 1989).
   .
       The degree of functional extension (number of activities carried out internally).
       Many companies prefer to outsource those activities that are not directly related to
       the business strategies (non-core processes). The degree of functional extension
       refers to the number of strategic functions directly managed within the company,
       which should be related to the amount of information to be managed (Price, 1997).
In the light of the identified business factors, it is therefore necessary to verify the
association between these factors and the use of ERP systems by testing the following
six main hypotheses:
   H1. The company size affects the adoption of ERP systems.
   H2. The market area affects the adoption of ERP systems.
   H3. The membership of a group affects the adoption of ERP systems.
   H4. The presence of branch offices affects the adoption of ERP systems.
   H5. The level of diversification affects the adoption of ERP systems.
   H6. The degree of functional extension affects the adoption of ERP systems.
JEIM                        Organizational change factors
18,4                        Even though business factors play an important role in determining business complexity
                            they are not considered sufficient to assure the feasibility of ERP adoption. Another issue
                            that deserves consideration is the organizational impact of ERP systems as they tend to
                            impose their own logic on company strategy, organization and culture (Davenport, 1998).
                            Thus, the ERP adoption decision affects most of the company business functions and
390                         directly involves a significant number of people. The project team responsible for ERP
                            implementation will be challenged to either match the functionality of the application to
                            business practice or find ways to adapt or change current processes and procedures,
                            while the project team could face organizational resistance to changing the status quo
                            (Laughlin, 1999). By providing universal, real-time access to operating and financial
                            data, ERP systems allow companies to streamline their management structures, creating
                            flatter, more flexible, and more democratic organizations. On the other hand, they also
                            involve the centralization of control over information and the standardization of
                            processes, which are qualities more consistent with hierarchical, command-and-control
                            organizations with uniform cultures (Davenport, 1998). Are the organizations aware of
                            such a change and then ready to bear and manage it? Is the alignment between the
                            desired organizational change and the complexity of the IT solution verified? These
                            remarks highlight a possible relationship between the extent of organizational change
                            and the rate of ERP system adoption.
                               The extent of organizational change represents the degree of company
                            transformation that the entrepreneur plans as a consequence of a technological
                            innovation. This measure depends on the evaluation of the organizational and
                            economic impacts, such as the competence of the internal staff or their expected
                            resistance to change to the adoption of a new technology. In order to analyze the factors
                            influencing the adoption of ERP systems, we assume that ERP systems could generate
                            larger benefits if implemented when a high level of organizational change is planned.
                            Venkatraman (1994) classifies five main levels of transformation (Figure 1):
                               (1) Local automation of existing procedures. This strategy is pursued only for
                                    automation of local, independent procedures. It requires minimal efforts and the
                                    corresponding expected results are enhancements in business process
                                    performance. Benefits coming from this strategy are easily duplicable, as




Figure 1.
Levels of business
transformation related to
technological innovation
most of standardized solutions. Therefore, it is unlikely to obtain competitive          Factors affecting
         advantage by simply automating existing procedures.                                          ERP system
   (2)   Internal integration of existing business processes. It aims at integrating the                  adoption
         business processes and the company IS in order to create competitive advantage.
         The required integration has to be pursued both at the technological and
         organizational level: whenever necessary, people belonging to different business
         functions have to cooperate to reach common objectives. Together with the                            391
         necessary automation effort, this strategy requires an integration effort; however,
         in both cases the business process structures remain unchanged.
   (3)   Business process reengineering. It involves the partial or complete redesign of
         business processes, affecting not only the company procedures, but also its
         organizational structure.
   (4)   Business network redesign. Changes overcome the boundaries of the company
         and could affect the entire network of its external relationships. For instance,
         electronic data interchange (EDI) can represent the technology chosen to pursue
         this strategy, but a great effort has to be put into business process integration,
         through a continuous information exchange and competence sharing. Under
         these conditions each partner can exploit the competencies of the business
         network instead of adopting expensive solutions of vertical integration.
   (5)   Redefinition of company boundaries through the creation of inter-organizational
         relationships. The information communication technologies (ICT) allow the
         redefinition of the competitive environment through the creation of strong
         inter-organizational relationships (joint ventures, long-term contracts, licensing
         agreements).

Therefore another hypothesis to be tested is focused on the matching between
organizational issues and ERP system adoption:
   H7. The extent of planned organizational change is directly related to the use of
       ERP systems (the greater is the planned organizational change, the greater is
       the rate of adoption of ERP systems).
To develop an effective framework it is necessary to include into the research model (as
control measures) both the endogenous and exogenous reasons that may affect ERP
adoption. According to the literature (Al-Mashari, 2002), among the reasons that may
affect ERP adoption, either positively or negatively, it is possible to distinguish operational
reasons (i.e. improving responsiveness to customers and simplifying ineffective or
complex business processes) and technological reasons (i.e. Y2K compliance requirements,
integration of business processes and systems, replacement of older, obsolete systems).
For those companies which have stated that they do not make use of an ERP system, we
classified each justification for ERP non-adoption into four main categories:
   (1) Structural motivations related to the need for coordination and control of business
        activities, thus to the complexity of information flows (which means that the
        company is not sufficiently complex to need an ERP system to manage the business).
   (2) Organizational motivations (the company is not prepared to face and manage
        the organizational changes related to the adoption and implementation of an
        ERP system).
JEIM                       (3) Economic motivations (ERP system adoption and implementation would be too
18,4                           costly for the company).
                           (4) Other reasons.

                        In the light of the control measures introduced the whole framework can be represented
                        as shown in Figure 2.
392
                        Methodology
                        Based on the literature review, focused on the identification of a taxonomy of business
                        and organisational factors, a questionnaire was designed. It comprised three parts: the
                        company demographics, the assessment of each business factor and the extent of the
                        organizational change. Before the complete deployment of the survey a first trial was
                        carried out on 122 companies suggesting the validity of the proposed approach
                        (Tagliavini et al., 2002). Responses were collected through personal interviews made by
                        a dedicated team to a top manager (possibly the entrepreneur him/herself or the CEO)
                        since the proposed questions required the knowledge of the main business objectives,
                        as well as of the features of the different business activities. The final questionnaire (an
                        abstract is shown in Figure 2) was then proposed to a random sample of about 2000
                        Italian companies of any size and industry, geographically located in northern Italy.
                        Data were finally analyzed with SPSS v11, in particular the hypotheses (from H1-H7)
                        have been tested by means of cross tabulations. Pearson chi-square was used to verify
                        whether the cross-tabulated groups were different, while p-values measure how the
                        previously mentioned difference is statistically significant. Finally, the value of
                        Spearman’s R is used to evaluate the reliability of correlations.
                            A preliminary validation of collected data has been performed by cross-tabulating
                        ERP adoption with each of the seven factors corresponding to the seven hypotheses
                        (from H1-H7). Chi-square and p-value tests have been used to verify whether the set of
                        companies using an ERP system is significantly different from the set of the not
                        adopters. Then, the connection existing between each factor and ERP adoption has
                        been assessed through Pearson’s R. A further analysis has been also performed




Figure 2.
Theoretical framework
separating SMEs from large companies to highlight possible differences between the         Factors affecting
two subsets.                                                                                   ERP system
                                                                                                   adoption
Variable measurement
According to the theoretical framework, the following sets of variables were measured:
  (1) The business complexity factors have been evaluated through six indicators                       393
      detailed in the Figure 3. Respondents were asked to qualitatively assess each
      variable of the set. More specifically:
      .
         Diversification has been measured as a synthetic index of business strategy
         by offering only two possible responses: diversification and other strategies
         (including cost-based and differentiation strategies).
      .
         Degree of functional extension, i.e. the number of activities carried out
         internally, has been assessed with respect to a set of typical business
         activities. The classical representation of the value chain (Porter and Millar,
         1985) has been integrated with a more recent measure used to assess the
         impact of BPR on manufacturing firms (Guimaraes and Bond, 1996). This
         measure has been already adopted in author’s previous research (Tagliavini
         et al., 2002).
  (2) The extent of organizational change which aims at evaluating the level of
      organizational change the company is prepared to face in order to achieve
      competitive advantage through the use of IT, has been assessed through a
      question suggesting Venkatraman five levels of organizational change. Due to
      the academic formulation which undoubtedly characterizes the question in the
      survey, all the organizational implications and characteristics related to each
      level of the Venkatraman’s model have been thoroughly explained by the
      interviewers to respondents, to clearly point out any organizational-related
      issue.
  (3) The technological and operational drivers have been assessed using the model
      proposed by Al-Mashari (2002) integrated with other drivers which have been
      identified in a previous research (Chau, 1995). Multiple responses were allowed.
  (4) The motivations for ERP non-adoption have been assessed by asking
      respondents to select items from a check-list (also in this case multiple
      responses were allowed).

Research findings
Of the 2,000 contacted companies only 370 accepted to be interviewed yielding a
response rate of 18.5 percent. Data from this sample were collected and filtered to
resolve inconsistencies and correct anomalies, resulting in 366 valid questionnaires.
The choice of the direct interviews to collect data is accountable for the low rate of
rejected questionnaires: only four questionnaires were discarded.

Demographic data
The first part of the questionnaire dealt with companies’ demographics. Firm size
(number of employees and turnover) was investigated according to the current
definition provided by the European Union (see Table I).
JEIM
18,4


394




Figure 3.
Measures adopted in the
questionnaire
Small sized companies represent 43 percent of respondents (18 percent micro, 25            Factors affecting
percent small) while 42 percent have a medium size. Large enterprises represent 15             ERP system
percent of the sample.
   With respect to the industry, the sample can be further categorized into three main             adoption
groups: manufacturing (66 percent), services (20 percent) and trade (14 percent). This
distribution is highly representative of the economical characteristics of this
geographic area, where large enterprises and services/wholesaling companies play a                           395
secondary role (see Figure 4).

Company size (H1)
The analysis of the correlation between company size (as a composite index between
turnover and number of employees) and ERP adoption shows a very good fit with data.
The two groups are significantly different (chi-square equal to 65,166 and p-value
lower than 0.001) while the Pearson’s R (0.401) shows that firms size and ERP adoption
are significantly correlated. In detail, while only 7 percent of companies not making use
of ERP systems are large-sized, the value corresponding to those large companies
adopting ERP systems seems even more significant. In fact, despite not constituting
the most relevant group in absolute terms (medium-sized companies are the 47 percent
of the whole sample adopting ERP), in relative terms as to the sample composition (in
which large companies are only 15 percent) large companies show an interesting result
(38 percent). The analysis clearly shows also that the rate of ERP system adoption is
quite low among both micro and small firms (3 percent and 12 percent respectively).
This reinforces the persuasion that the company size affects the ERP adoption process.
   H1: verified.

Membership of a group (H2)
The cross tabulation for H2 shows an inverse correlation between membership of a
group and ERP adoption (Pearson’s R ¼ 20:277). Moreover, the 55 percent of companies

                                             Micro         Small-sized     Medium-sized
Criteria                                   enterprises     enterprises      enterprises

Maximum number of employees                   ,10             ,50              ,250
Maximum turnover in e million                  –                7                40
Maximum balance-sheet total in e million       –                5                27
                                                                                                         Table I.
Source: European Commission (1996)                                                                  SMEs definition




                                                                                                         Figure 4.
                                                                                           Sample definition by size,
                                                                                             industry and enterprise
                                                                                                         application
JEIM                      belonging to a group prefer other management systems rather than ERP (Tables II-IV).
                          A correct interpretation of such result requires considering that distribution of the
18,4                      sample according to this factor as unbalanced (237 firms in a standalone configuration
                          compared to 53 belonging to an industrial group). Nonetheless, it is reasonable to
                          conclude that, despite what suggested in the existing literature, the membership of a
                          group seems not to be directly related to the use of ERP systems.
396                          The Pearson’s R index of correlation computed on SMEs (2 0.169, Tables V-VII) and
                          large enterprises (0.060, Tables VIII-X) did not show consistent results.
                             H2: rejected.

                          Market area (H3)
                          At a first glance, a wider market area of a company seems to be related to the use of
                          ERP systems. Only a small subset of companies with a limited market area make use of
                          ERP systems, while this value is higher for companies with a national market area (22
                          percent) and even more for those companies acting on international markets (74
                          percent, see cross-tabulation in Tables XI-XIII). Nevertheless, the high percentage of
                          companies with an international market area which do not use ERP systems (68
                          percent) clearly shows that the ERP system is far from being the only solution adopted
                          as stated in H3. The significant difference between the cross-tabulated groups,

                                                                        Company size and ERP adoption
                                                                               (whole sample)
                          Size                                      Other management system          ERP               Total

                          Micro             Count                              62                         3             65
                                            % within size                      95.4                       4.6          100.0
                                            % within ERP                       23.6                       3.3           18.4
                          Small             Count                              77                        11             88
                                            % within size                      87.5                      12.5          100.0
                                            % within ERP                       29.3                      12.2           24.9
                          Medium            Count                             105                        42            147
                                            % within size                      71.4                      28.6          100.0
                                            % within ERP                       39.9                      46.7           41.6
                          Large             Count                              19                        34             53
                                            % within size                      35.8                      64.2          100.0
                                            % within ERP                        7.2                      37.8           15.0
                          Total             Count                             263                        90            353
Table II.                                   % within size                      74.5                      25.5          100.0
Company size and ERP                        % within ERP                      100.0                     100.0          100.0
adoption (whole sample)                     % of total                         74.5                      25.5          100.0




                                                               Value          df         Asymptotic significance (two-sided)
                                                                       a
                          Pearson chi-square                  65.166           3                        0.000
                          Likelihood ratio                    65.121           3                        0.000
Table III.                Linear-by-linear association        56.552           1                        0.000
Company size and ERP      n of valid cases                   353
adoption (whole sample)
– Chi-square tests        Note: a 0 cells (0.0 percent) have expected count less than 5. The minimum expected count is 13.51
(chi-square ¼ 14:538, p-value ¼ 0:000, Tables XI-XIII), is contradicted by the                               Factors affecting
unsatisfactory value of the Pearson’s R index (0.190), which confirms the lack of a                               ERP system
correlation between market area and ERP adoption.
                                                                                                                     adoption
   H3 has also been tested on both SMEs and large companies, pointing out the same
trend (Tables XIV-XVI and Tables XVII-XIX).
   H3: rejected.
                                                                                                                              397

                                                         Asymptotic        Approximate     Approximate
                                               Value   standard errora         Tb          significance

Interval by interval Pearson’s R               0.401       0.042              8.197              0.000c
Ordinal by ordinal Spearman correlation        0.405       0.044              8.287              0.000c
n of valid cases                               0.353                                                                      Table IV.
                                                                                                              Company size and ERP
Notes: a Not assuming the null hypothesis; b Using the asymptotic standard error assuming the null           adoption (whole sample)
hypothesis; c Based on normal approximation                                                                    – symmetric measures




                                                        Membership of a group and ERP
                                                             adoption (whole sample)
                                                       Other management system       ERP             Total

Member of a group         Count                                     54                    44          98
                          % within membership                       55.1                  44.9       100.0
                          % within ERP                              20.4                  48.9        27.6
Standalone company        Count                                    211                    46         257
                          % within membership                       82.1                  17.9       100.0
                          % within ERP                              79.6                  51.1        72.4
Total                     Count                                    265                    90         355
                          % within membership                       74.6                  25.4       100.0                Table V.
                          % within ERP                             100.0                 100.0       100.0     Membership and ERP
                          % of total                                74.6                  25.4       100.0   adoption (whole sample)




                                                        Asymptotic            Exact             Exact
                                                        significance        significance      significance
                                 Value           df     (two-sided)        (two-sided)       (one-sided)

Pearson Chi-square               27.327b          1        0.000
Continuity correctiona           25.919           1        0.000
Likelihood ratio                 25.640           1        0.000
Fisher’s exact test                                                           0.000               0.000
Linear-by-linear association     27.250           1        0.000
n of valid cases                355                                                                                       Table VI.
        a                                  b
                                                                                                               Membership and ERP
Notes: Computed only for a 2 £ 2 table; 0 cells (0.0 percent) have expected count less than 5. The           adoption (whole sample)
expected count is 24.85                                                                                            – Chi-square tests
JEIM                      Presence of branch offices (H4)
18,4                      According to the literature, the presence of branch offices could be a factor that
                          positively influences the complexity of information flows and that, consequently, could
                          lead to a larger adoption of ERP systems. The empirical analysis shows a correlation
                          between the extent of geographical dispersion of the company and the use of ERP
                          systems. These systems have been adopted by only 15 percent of respondents with no
398                       branch offices and by 42 percent of companies with geographically dispersed offices


                                                                                    Asymptotic        Approximate     Approximate
                                                                         Value    standard errora         Tb          significance

                          Interval by interval Pearson’s R               20.277       0.056             2 5.426             0.000c
                          Ordinal by ordinal Spearman correlation        20.277       0.056             2 5.426             0.000c
Table VII.                n of valid cases                               355
Membership and ERP
adoption (whole sample)   Notes: a Not assuming the null hypothesis; b Using the asymptotic standard error assuming the null
– symmetric measures      hypothesis; c Based on normal approximation




                                                                                   Membership of a group and ERP
                                                                                           adoption (SMEs)
                                                                                  Other management system     ERP               Total

                          Member of a group         Count                                      36                    17          53
                                                    % within membership                        67.9                  32.1       100.0
                                                    % within ERP                               15.2                  32.1        18.3
                          Stand-alone company       Count                                     201                    36         237
                                                    % within membership                        84.8                  15.2       100.0
                                                    % within ERP                               84.8                  67.9        81.7
                          Total                     Count                                     237                    53         290
Table VIII.                                         % within membership                        81.7                  18.3       100.0
Membership and ERP                                  % within ERP                              100.0                 100.0       100.0
adoption (SMEs)                                     % of total                                 81.7                  18.3       100.0




                                                                                  Asymptotic             Exact             Exact
                                                                                  significance         significance      significance
                                                            Value          df     (two-sided)         (two-sided)       (one-sided)
                                                                     b
                          Pearson chi-square                 8.269          1         0.004
                          Continuity correctiona             7.177          1         0.007
                          Likelihood ratio                   7.393          1         0.007
                          Fisher’s exact test                                                            0.009               0.005
                          Linear-by-linear association       8.240          1         0.004
Table IX.                 n of valid cases                 290
Membership and ERP
adoption (SMEs) –         Notes: a Computed only for a 2 £ 2 table; b 0 cells (0.0 percent) have expected count less than 5. The
Chi-square tests          expected count is 9.69
(Tables XX-XXII). The evaluation of the behavior of companies making use of ERP                             Factors affecting
systems confirms this relationship: 62 percent of them have geographically dispersed                             ERP system
offices, while only 38 percent of ERP users have no branch offices to manage. Although
                                                                                                                    adoption
this interesting trend, a correlation between the two variables cannot be fully claimed:
the empirical verification shows a Pearson’s R value equal to 0.297 that is not
statistically reliable to state that the presence of branch offices directly affects a higher
rate of ERP system adoption (Tables XX-XXII).
                                                                                                                             399

                                                       Asymptotic         Approximate     Approximate
                                            Value    standard errora          Tb          significance

Interval by interval Pearson’s R           20.169         0.067             2 2.907             0.004c
Ordinal by ordinal Spearman correlation    20.169         0.067             2 2.097             0.004c
n of valid cases                           290                                                                          Table X.
                                                                                                              Membership and ERP
Notes: a Not assuming the null hypothesis; b Using the asymptotic standard error assuming the null              adoption (SMEs) –
hypothesis; c Based on normal approximation                                                                    symmetric measures




                                                     Membership and ERP adoption (large
                                                                companies)
                                                     Other management system      ERP               Total

Member of group           Count                                    15                    25          40
                          % within membership                      37.5                  62.5       100.0
                          % within ERP                             78.9                  73.5        75.5
Standalone company        Count                                     4                     9          13
                          % within membership                      30.8                  69.2       100.0
                          % within ERP                             21.1                  26.5        24.5
Total                     Count                                    19                    34          53                Table XI.
                          % within membership                      35.8                  64.2       100.0     Membership and ERP
                          % within ERP                            100.0                 100.0       100.0          adoption (large
                          % of total                               35.8                  64.2       100.0              companies)




                                                      Asymptotic             Exact             Exact
                                                      significance         significance      significance
                                  Value       df      (two-sided)         (two-sided)       (one-sided)

Pearson Chi-square                0.193b      1          0.660
Continuity correctiona            0.011       1          0.915
Likelihood ratio                  0.196       1          0.658
Fisher’s exact test                                                          0.749               0.464
Linear-by-linear association      0.190       1          0.663                                                          Table XII.
n of valid cases                 53                                                                           Membership and ERP
                                                                                                                    adoption (large
Notes: a Computed only for a 2 £ 2 table; b 1 cell (25.0 percent) has expected count less than 5. The       companies) – Chi-square
expected count is 4.66                                                                                                         tests
JEIM                      The empirical verification of H4 on the subsets obtained by separating the companies
18,4                      by size does not show any interesting result (Tables XXIII-XXV and
                          Tables XXVI-XXVIII). In particular, the statistical analysis on large companies
                          (Tables XXVI-XXVIII) does not show any meaningful difference between the two
                          groups (chi-square ¼ 0:348 and p-value ¼ 0:409).
                             H4: rejected (weak significance on the whole sample).
400

                                                                                  Asymptotic       Approximate     Approximate
                                                                       Value    standard errora        Tb          significance

                          Interval by interval Pearson’s R              0.060        0.134            0.432           0.668c
Table XIII.               Ordinal by ordinal Spearman correlation       0.060        0.134            0.432           0.668c
Membership and ERP        n of valid cases                             53
adoption (large
companies) – symmetric    Notes: a Not assuming the null hypothesis; b Using the asymptotic standard error assuming the null
measures                  hypothesis; c Based on normal approximation




                                                                               Market area and ERP adoption
                                                                                      (whole sample)
                          Market area                                       Other management system       ERP             Total

                          Local              Count                                      19                      2          21
                                             % within market area                       90.5                    9.5       100.0
                                             % within ERP                                7.0                    2.2         5.8
                          Regional           Count                                      25                      2          27
                                             % within market area                       92.6                    7.4       100.0
                                             % within ERP                                9.2                    2.2         7.4
                          National           Count                                      83                     20         103
                                             % within membership                        80.6                   19.4       100.0
                                             % within ERP                               30.6                   21.7        28.4
                          International      Count                                     144                     68         212
                                             % within market area                       67.9                   32.1       100.0
                                             % within ERP                               53.1                   73.9        58.4
                          Total              Count                                     271                     92         363
Table XIV.                                   % within market area                       74.7                   25.3       100.0
Market area and ERP                          % within ERP                              100.0                  100.0       100.0
adoption (whole sample)                      % of total                                 74.7                   25.3       100.0




                                                               Value            df           Asymptotic significance (two-sided)

                          Pearson Chi-square                   14.358a           3                         0.002
                          Likelihood ratio                     16.081            3                         0.001
Table XV.                 Linear-by-linear association         13.113            1                         0.000
Market area and ERP       n of valid cases                    363
adoption (whole sample)
– Chi-square tests        Note: a 0 cells (0.0 percent) have expected count less than 5. The minimum expected cost is 5.32
Diversification (H5)                                                                                       Factors affecting
Despite the support provided by the literature for diversification as a factor affecting                       ERP system
the complexity of information flows, the empirical verification does not show
meaningful correlations with the adoption of ERP systems (Tables XXIX-XXXI). Only                                 adoption
27 percent of diversified companies make use of an ERP system. Moreover, 55 percent
of companies adopting an ERP system pursue another kind of strategy. The low
significance of diversification as a factor affecting ERP adoption is also confirmed by                                      401
the results of the statistical analysis: the two groups are not significantly different


                                                         Asymptotic       Approximate     Approximate
                                              Value    standard errora        Tb          significance

Interval by interval Pearson’s R               0.190        0.042             3.684           0.000c
Ordinal by ordinal Spearman correlation        0.196        0.046             3.796           0.000c
n of valid cases                             363                                                                     Table XVI.
                                                                                                             Market area and ERP
Notes: a Not assuming the null hypothesis; b Using the asymptotic standard error assuming the null        adoption (whole sample)
hypothesis; c Based on normal approximation                                                                 – symmetric measures




                                                  Market area and ERP adoption (SMEs)
Market area                                       Other management system        ERP              Total

Local               Count                                     19                                   19
                    % within market   area                   100.0                                100.0
                    % within ERP                               7.9                                  6.4
Regional            Count                                     21                        2          23
                    % within market   area                    91.3                      8.7       100.0
                    % within ERP                               8.7                      3.6         7.7
National            Count                                     74                       13          87
                    % within market   area                    85.1                     14.9       100.0
                    % within ERP                              30.6                     23.6        29.3
International       Count                                    128                       40         168
                    % within market   area                    76.2                     23.8       100.0
                    % within ERP                              52.9                     72.7        56.6
Total               Count                                    242                       55         297
                    % within market   area                    81.5                     18.5       100.0            Table XVII.
                    % within ERP                             100.0                    100.0       100.0     Market area and ERP
                    % of total                                81.5                     18.5       100.0         adoption (SMEs)




                                      Value            df           Asymptotic significance (two-sided)
                                              a
Pearson Chi-square                    9.643            3                          0.022
Likelihood ratio                     13.235            3                          0.004
Linear-by-linear association          9.561            1                          0.002                           Table XVIII.
n of valid cases                    297                                                                     Market area and ERP
                                                                                                              adoption (SMEs) –
Note: a Two cells (25.0 percent) have expected count less than 5. The minimum expected count is 3.52             Chi-square tests
JEIM                      (Chi-square equal to 0.261, with a p-value of 0.610) and the very low value of Pearson’s
18,4                      R correlation index (0.027) bears out that no correlation occurs. Accordingly to the
                          methodology, the analysis has been carried out on both SMEs and large companies to
                          verify possible different behaviors in the sub-groups (Tables XXXII-XXXIV and
                          Tables XXXV-XXXVII), but no statistical evidence has been found.
                             H5: rejected.
402

                                                                                      Asymptotic       Approximate     Approximate
                                                                            Value   standard errora        Tb          significance

                          Interval by interval Pearson’s R                0.180          0.039             3.138           0.002c
                          Ordinal by ordinal Spearman correlation         0.173          0.049             3.019           0.003c
Table XIX.                n of valid cases                              297
Market area and ERP
adoption (SMEs) –         Notes: a Not assuming the null hypothesis; b Using the asymptotic standard error assuming the null
symmetric measures        hypothesis; c Based on normal approximation



                                                                                   Market area and ERP adoption
                                                                                         (large companies)
                          Market area                                           Other management system       ERP              Total

                          Local               Count                                                                  1           1
                                              % within market   area                                               100.0       100.0
                                              % within ERP                                                           2.9         1.9
                          Regional            Count                                         3                                    3
                                              % within market   area                      100.0                                100.0
                                              % within ERP                                 15.8                                  5.7
                          National            Count                                         4                        7          11
                                              % within market   area                       36.4                     63.6       100.0
                                              % within ERP                                 21.1                     20.6        20.8
                          International       Count                                        12                       26          38
                                              % within market   area                       31.6                     68.4       100.0
                                              % within ERP                                 63.2                     76.5        71.7
Table XX.                 Total               Count                                        19                       34          53
Market area and ERP                           % within market   area                       35.8                     64.2       100.0
adoption (large                               % within ERP                                100.0                    100.0       100.0
companies)                                    % of total                                   35.8                     64.2       100.0




                                                                Value               df           Asymptotic significance (two-sided)
                                                                        a
                          Pearson Chi-square                    6.230               3                          0.101
Table XXI.                Likelihood ratio                      7.351               3                          0.062
Market area and ERP       Linear-by-linear association          1.397               1                          0.237
adoption (large           n of valid cases                     53
companies) – Chi-square
tests                     Note: a Five cells (62.5 percent) have expected count less than 5. The minimum expected count is 0.36
Functional extension (H6)                                                                                      Factors affecting
Even though most of respondents (88 percent) manage all the business activities                                    ERP system
internally, the functional extension does not seem to affect the rate of ERP system
adoption. For each meaningful value of functional extension (cross-tabulation cells                                    adoption
with more than five companies, Tables XXXVIII-XL), the percentage of companies
making use of ERP systems is at most equal to the 26.1 percent. In particular, only 25.9
percent of the 321 companies characterized by the maximum level of functional                                                   403

                                                             Asymptotic      Approximate      Approximate
                                                  Value    standard errora       Tb           significance

Interval by interval Pearson’s R               0.164            0.145           1.187              0.241c
Ordinal by ordinal Spearman correlation        0.163            0.141           1.180              0.244c                Table XXII.
n of valid cases                              53                                                                 Market area and ERP
                                                                                                                       adoption (large
Notes: a Not assuming the null hypothesis; b Using the asymptotic standard error assuming the null             companies) – symmetric
hypothesis; c Based on normal approximation                                                                                  measures




                                                            Branch offices and ERP adoption
                                                                    (whole sample)
Branch offices                                             Other management system       ERP            Total

No                  Count                                          193                      35         228
                    % within branch offices                          84.6                    15.4       100.0
                    % within ERP                                    70.7                    37.6        62.3
Yes                 Count                                           80                      58         138
                    % within branch offices                          58.0                    42.0       100.0
                    % within ERP                                    29.3                    62.4        37.7
Total               Count                                          273                      93         366
                    % within branch offices                          74.6                    25.4       100.0            Table XXIII.
                    % within ERP                                   100.0                   100.0       100.0   Branch offices and ERP
                    % of total                                      74.6                    25.4       100.0   adoption (whole sample)




                                                             Asymptotic         Exact              Exact
                                                             significance     significance       significance
                                 Value              df       (two-sided)     (two-sided)        (one-sided)
                                          b
Pearson Chi-square               32.282             1           0.000
Continuity correctiona           30.890             1           0.000
Likelihood ratio                 31.597             1           0.000
Fisher’s exact test                                                             0.000               0.000
Linear-by-linear association     32.194             1           0.000
n of valid cases                366                                                                                      Table XXIV.
        a                                     b
                                                                                                                Branch offices and ERP
Notes: Computed only for a 2 £ 2 table; 0 cells (0.0 percent) have expected count less than 5. the             adoption (whole sample)
maximum expected count is 35.07                                                                                      – Chi-square tests
JEIM                      extension claim to make use of an ERP system. The unbalanced distribution of the
18,4                      sample undoubtedly challenges the reliability of the analysis; nevertheless SMEs do
                          not consider ERP systems as the solution needed to improve their organizational
                          performance yet. The analysis of both correlation and statistical significance with
                          respect to SMEs and large companies does not show any meaningful change in of the
                          main indexes (Tables XLI-XLI and Tables XLIV-XLVI).
404                          H6: rejected.


                                                                                  Asymptotic      Approximate      Approximate
                                                                      Value     standard errora       Tb           significance

                          Interval by interval Pearson’s R              0.297        0.052            5.934             0.000c
                          Ordinal by ordinal Spearman correlation       0.297        0.052            5.934             0.000c
Table XXV.                n of valid cases                            366
Branch offices and ERP
adoption (whole sample)   Notes: a Not assuming the null hypothesis; b Using the asymptotic standard error assuming the null
– symmetric measures      hypothesis; c Based on normal approximation




                                                                                    Branch offices and ERP
                                                                                       adoption (SMEs)
                          Branch offices                                       Other management system     ERP               Total

                          No                  Count                                     181                      29         210
                                              % within branch offices                     86.2                    13.8       100.0
                                              % within ERP                               74.2                    51.8        70.0
                          Yes                 Count                                      63                      27          90
                                              % within branch offices                     70.0                    30.0       100.0
                                              % within ERP                               25.8                    48.2        30.0
                          Total               Count                                     244                      56         300
Table XXVI.                                   % within branch offices                     81.3                    18.7       100.0
Branch offices and ERP                         % within ERP                              100.0                   100.0       100.0
adoption (SMEs)                               % of total                                 81.3                    18.7       100.0



                                                                                 Asymptotic          Exact              Exact
                                                                                 significance      significance       significance
                                                            Value        df      (two-sided)      (two-sided)        (one-sided)

                          Pearson Chi-square                10.877b       1         0.001
                          Continuity correctiona             9.837        1         0.002
                          Likelihood ratio                  10.230        1         0.001
                          Fisher’s exact test                                                        0.002               0.001
                          Linear-by-linear association      10.841        1         0.001
Table XXVII.              n of valid cases                 300
Branch offices and ERP
adoption (SMEs) –         Notes: a Computed only for a 2 £ 2 table; b 0 cells (0.0 percent) have expected count less than 5. the
Chi-square tests          maximum expected count is 16.80
Extent of organizational change (H7)                                                                        Factors affecting
Unlike previous factors (from H2-H6), the results of the data analysis on H7                                    ERP system
(Table XLVII-XLIX) highlights that the extent of organizational change the company
wishes to achieve is likely to affect the decision of whether adopting an ERP system or not.                        adoption
Even though the Pearson’s R value (0.306) shown by the whole sample is just acceptable,
other considerations support this statement. In particular (Tables L-LII), companies
adopting other management systems reveal a lower mean for the organizational change                                           405
factor (1.2) in comparison with those companies which have adopted an ERP system (2.3).



                                                          Asymptotic      Approximate      Approximate
                                             Value      standard errora       Tb           significance

Interval by interval Pearson’s R              0.190         0.062            3.348              0.001c
Ordinal by ordinal Spearman correlation       0.190         0.062            3.348              0.001c
n of valid cases                            300                                                                    Table XXVIII.
        a                                    b
                                                                                                             Branch offices and ERP
Notes: Not assuming the null hypothesis; Using the asymptotic standard error assuming the null                   adoption (SMEs) –
hypothesis; c Based on normal approximation                                                                     symmetric measures



                                                         Presence of branch offices and
                                                        ERP adoption (large companies)
Branch offices                                         Other management system        ERP            Total

No                  Count                                         4                       5           9
                    % within branch offices                       44.4                    55.6       100.0
                    % within ERP                                 21.1                    14.7        17.0
Yes                 Count                                        15                      29          44
                    % within branch offices                       34.1                    65.9       100.0
                    % within ERP                                 78.9                    85.3        83.0
Total               Count                                        19                      34          53              Table XXIX.
                    % within branch offices                       35.8                    64.2       100.0    Branch offices and ERP
                    % within ERP                                100.0                   100.0       100.0            adoption (large
                    % of total                                   35.8                    64.2       100.0                companies)



                                                        Asymptotic           Exact              Exact
                                                        significance       significance       significance
                                  Value          df     (two-sided)       (two-sided)        (one-sided)

Pearson Chi-square                 0.348b        1         0.555
Continuity correctiona             0.044         1         0.835
Likelihood ratio                   0.340         1         0.560
Fisher’s exact test                                                          0.706               0.409
Linear-by-linear association       0.342         1         0.559                                                      Table XXX.
n of valid cases                  53                                                                         Branch offices and ERP
                                                                                                                     adoption (large
Notes: a Computed only for a 2 £ 2 table; b One cell (25.0 percent) has expected count less than 5. The     companies) – Chi-square
maximum expected count is 3.23                                                                                                  tests
JEIM                      A detailed analysis of the cross-tabulation between organizational change and ERP
                          adoption has pointed out some interesting remarks (see Figure 5):
18,4
                             .  Companies seem to privilege the ERP solution when their need to integrate,
                                reengineer or redesign business processes becomes a priority (respectively the
                                17.4 percent, 25 percent and the 16.3 percent). Only 11 percent of companies
                                which make use of ERP systems exploit this solution just for local automation
406                             purposes, while the number of companies considering a more advanced solution
                                (business network redesign levels) is quite negligible (8.7 percent).



                                                                                  Asymptotic        Approximate      Approximate
                                                                      Value     standard errora         Tb           significance

                          Interval by interval Pearson’s R             0.081         0.141             0.581              0.564c
Table XXXI.               Ordinal by ordinal Spearman correlation      0.081         0.141             0.581              0.564c
Branch offices and ERP     n of valid cases                            53
adoption (large
companies) – symmetric    Notes: a Not assuming the null hypothesis; b Using the asymptotic standard error assuming the null
measures                  hypothesis; c Based on normal approximation




                                                                                 Diversification and ERP adoption
                                                                               Other management system        ERP             Total

                          Other strategy      Count                                         158                    51         209
                                              % within diversification                        75.6                  24.4       100.0
                                              % within ERP                                   57.9                  54.8        57.1
                          Diversification      Count                                         115                    42         157
                                              % within diversification                        73.2                  26.8       100.0
                                              % within ERP                                   42.1                  45.2        42.9
                          Total               Count                                         273                    93         366
Table XXXII.                                  % within diversification                        74.6                  25.4       100.0
Diversification and ERP                        % within ERP                                  100.0                 100.0       100.0
adoption (whole sample)                       % of total                                     74.6                  25.4       100.0




                                                                                 Asymptotic            Exact              Exact
                                                                                 significance        significance       significance
                                                            Value       df       (two-sided)        (two-sided)        (one-sided)

                          Pearson chi-square                0.261b      1           0.609
                          Continuity correctiona            0.152       1           0.697
                          Likelihood ratio                  0.260       1           0.610
                          Fisher’s exact test                                                          0.629               0.348
                          Linear-by-linear association      0.260       1           0.610
Table XXXIII.             n of valid cases                  0.366
Diversification and ERP
adoption (whole sample)   Notes: a Computed only for a 2 £ 2 table; b 0 cells (0.0 percent) have expected count less than 5. The
– Chi-square tests        maximum expected count is 39.89
.
        A quite unexpected outcome of the analysis is the relevant percentage of                               Factors affecting
        companies (21.7 percent) declaring that no organizational change occurred, or                              ERP system
        has been foreseen, as a consequence of ERP adoption. This result is even more
        surprising in the light of the support given by IS literature to the thesis that ERP                           adoption
        adoption both requires and provokes an unavoidable organizational reshuffling
        of roles and tasks (Dewett and Jones, 2001).
   .
        The comparative analysis of means and distribution for the organizational                                                407
        change factor (Table XLVII-XLIX) also shows that the underestimation of the


                                                             Asymptotic      Approximate      Approximate
                                               Value       standard errora       Tb           significance

Interval by interval Pearson’s R                 0.027         0.052            0.510              0.610c
Ordinal by ordinal Spearman correlation          0.027         0.052            0.510              0.610c
n of valid cases                               366                                                                    Table XXXIV.
        a                                      b                                                               Diversification and ERP
Notes: Not assuming the null hypothesis; Using the asymtopic standard error assuming the null                  adoption (whole sample)
hypothesis; c Based on normal approximation                                                                      – symmetric measures




                                                           Diversification and ERP adoption
                                                                        (SMEs)
                                                         Other management system        ERP            Total

Other strategy      Count                                          142                      32         174
                    % within diversification                         81.6                    18.4       100.0
                    % within ERP                                    58.2                    57.1        58.0
Diversification      Count                                          102                      24         126
                    % within diversification                         81.0                    19.0       100.0
                    % within ERP                                    41.8                    42.9        42.0
Total               Count                                          244                      56         300              Table XXXV.
                    % within diversification                         81.3                    18.7       100.0    Diversification and ERP
                    % within ERP                                   100.0                   100.0       100.0           adoption (SMEs)
                    % of total                                      81.3                    18.7       100.0



                                                           Asymptotic           Exact              Exact
                                                           significance       significance       significance
                                  Value            df      (two-sided)       (two-sided)        (one-sided)
                                           b
Pearson Chi-square                 0.021           1           0.885
Continuity correctiona             0.000           1           1.000
Likelihood ratio                   0.021           1           0.885
Fisher’s exact test                                                             0.882               0.500
Linear-by-linear association       0.021           1           0.886
n of valid cases                 300                                                                                   Table XXXVI.
                                                                                                                Diversification and ERP
Notes: a Computed only for a 2 £ 2 table; b 0 cells (0.0 percent) have expected count less than 5. The               adoption (SMEs) –
maximum expected count is 23.52                                                                                         Chi-square tests
JEIM                              organizational change factor becomes even more relevant among those
18,4                              companies that make use of another management system (50.4 percent).
                          The previous analysis has been performed also separating SMEs and large companies
                          in order to highlight possible differences in the behavior of the two sub-groups.
                          Organizational change shows a stronger correlation with ERP adoption in the case of
408                       large companies (Pearson’s R ¼ 0:386, Tables LIII-LV) with respect to SMEs
                          (Pearson’s R ¼ 0:218, Table LVI-LVIII). To explore the reasons underlying the
                          different correlation shown by the two sub-groups, the previous outcome has been

                                                                                    Asymptotic      Approximate      Approximate
                                                                      Value       standard errora       Tb           significance

                          Interval by interval Pearson’s R              0.008         0.058            0.144              0.886c
                          Ordinal by ordinal Spearman correlation       0.008         0.058            0.144              0.886c
Table XXXVII.             n of valid cases                            300
Diversification and ERP
adoption (SMEs) –         Notes: a Not assuming the null hypothesis; b Using the asymptotic standard error assuming the null
symmetric measures        hypothesis; c Based on normal approximation




                                                                                  Diversification and ERP adoption
                                                                                          (large companies)
                                                                                Other management system        ERP            Total

                          Other strategy      Count                                        12                      17          29
                                              % within diversification                      41.4                    58.6       100.0
                                              % within ERP                                 63.2                    50.0        54.7
                          Diversification      Count                                         7                      17          24
                                              % within diversification                      29.2                    70.8       100.0
                                              % within ERP                                 36.8                    50.0        45.3
Table XXXVIII.            Total               Count                                        19                      34          53
Diversification and ERP                        % within diversification                      35.8                    64.2       100.0
adoption (large                               % within ERP                                100.0                   100.0       100.0
companies)                                    % of total                                   35.8                    64.2       100.0




                                                                                  Asymptotic           Exact              Exact
                                                                                  significance       significance       significance
                                                            Value       df        (two-sided)       (two-sided)        (one-sided)

                          Pearson Chi-square                0.852b       1           0.356
                          Continuity correctiona            0.403        1           0.525
                          Likelihood ratio                  0.859        1           0.354
                          Fisher’s exact test                                                          0.401               0.264
Table XXXIX.              Linear-by-linear association      0.836        1           0.361
Diversification and ERP    n of valid cases                 53
adoption (large
companies) – Chi-square   Notes: a Computed only for a 2 £ 2 table; b 0 cells (0.0 percent) have expected count less than 5. The
tests                     maximum expected count is 8.60
9. Factors Affecting Erp System Adoption
9. Factors Affecting Erp System Adoption
9. Factors Affecting Erp System Adoption
9. Factors Affecting Erp System Adoption
9. Factors Affecting Erp System Adoption
9. Factors Affecting Erp System Adoption
9. Factors Affecting Erp System Adoption
9. Factors Affecting Erp System Adoption
9. Factors Affecting Erp System Adoption
9. Factors Affecting Erp System Adoption
9. Factors Affecting Erp System Adoption
9. Factors Affecting Erp System Adoption
9. Factors Affecting Erp System Adoption
9. Factors Affecting Erp System Adoption
9. Factors Affecting Erp System Adoption
9. Factors Affecting Erp System Adoption
9. Factors Affecting Erp System Adoption
9. Factors Affecting Erp System Adoption

Contenu connexe

Tendances

What Is Enterprise Resource Planning System
What Is Enterprise Resource Planning SystemWhat Is Enterprise Resource Planning System
What Is Enterprise Resource Planning SystemKhawaja Naveed
 
ERP (ENTERPRISE RESOURCE PLANNING)
ERP (ENTERPRISE RESOURCE PLANNING)ERP (ENTERPRISE RESOURCE PLANNING)
ERP (ENTERPRISE RESOURCE PLANNING)Sujeet TAMBE
 
Phases of ERP Implementation Lifecycle By ControlERP
Phases of ERP Implementation Lifecycle By ControlERPPhases of ERP Implementation Lifecycle By ControlERP
Phases of ERP Implementation Lifecycle By ControlERPCalvin Hewitt
 
A STUDY ON THE EFFECTIVENESS OF ERP SYSTEM
A STUDY ON THE EFFECTIVENESS OF ERP SYSTEM A STUDY ON THE EFFECTIVENESS OF ERP SYSTEM
A STUDY ON THE EFFECTIVENESS OF ERP SYSTEM DAVIS THOMAS
 
Hadoop Presentation - PPT
Hadoop Presentation - PPTHadoop Presentation - PPT
Hadoop Presentation - PPTAnand Pandey
 
Benefits of an ERP system for your business.
Benefits of an ERP system for your business.Benefits of an ERP system for your business.
Benefits of an ERP system for your business.SYSPRO
 
Enterprise Resource Planning
Enterprise Resource PlanningEnterprise Resource Planning
Enterprise Resource PlanningAnkesh Gorkhali
 
Exploring Levels of Data Literacy
Exploring Levels of Data LiteracyExploring Levels of Data Literacy
Exploring Levels of Data LiteracyDATAVERSITY
 
White Paper - Data Warehouse Governance
White Paper -  Data Warehouse GovernanceWhite Paper -  Data Warehouse Governance
White Paper - Data Warehouse GovernanceDavid Walker
 
Objectives of erp implementation
Objectives of erp implementationObjectives of erp implementation
Objectives of erp implementationBabasab Patil
 
ERP implementation Failure at Hershey Food Corperation
ERP implementation Failure at Hershey Food CorperationERP implementation Failure at Hershey Food Corperation
ERP implementation Failure at Hershey Food CorperationOlivier Tisun
 

Tendances (20)

Introduction to ERP
Introduction to ERPIntroduction to ERP
Introduction to ERP
 
What Is Enterprise Resource Planning System
What Is Enterprise Resource Planning SystemWhat Is Enterprise Resource Planning System
What Is Enterprise Resource Planning System
 
ERP (ENTERPRISE RESOURCE PLANNING)
ERP (ENTERPRISE RESOURCE PLANNING)ERP (ENTERPRISE RESOURCE PLANNING)
ERP (ENTERPRISE RESOURCE PLANNING)
 
ERP PROJECT
ERP PROJECTERP PROJECT
ERP PROJECT
 
Phases of ERP Implementation Lifecycle By ControlERP
Phases of ERP Implementation Lifecycle By ControlERPPhases of ERP Implementation Lifecycle By ControlERP
Phases of ERP Implementation Lifecycle By ControlERP
 
A STUDY ON THE EFFECTIVENESS OF ERP SYSTEM
A STUDY ON THE EFFECTIVENESS OF ERP SYSTEM A STUDY ON THE EFFECTIVENESS OF ERP SYSTEM
A STUDY ON THE EFFECTIVENESS OF ERP SYSTEM
 
Hadoop Presentation - PPT
Hadoop Presentation - PPTHadoop Presentation - PPT
Hadoop Presentation - PPT
 
Benefits of an ERP system for your business.
Benefits of an ERP system for your business.Benefits of an ERP system for your business.
Benefits of an ERP system for your business.
 
SAP Power Designer
SAP Power DesignerSAP Power Designer
SAP Power Designer
 
Comparison between erp software
Comparison between erp softwareComparison between erp software
Comparison between erp software
 
Erp
ErpErp
Erp
 
EA Report.pdf
EA Report.pdfEA Report.pdf
EA Report.pdf
 
Executive information system
Executive information systemExecutive information system
Executive information system
 
Enterprise Resource Planning
Enterprise Resource PlanningEnterprise Resource Planning
Enterprise Resource Planning
 
Exploring Levels of Data Literacy
Exploring Levels of Data LiteracyExploring Levels of Data Literacy
Exploring Levels of Data Literacy
 
White Paper - Data Warehouse Governance
White Paper -  Data Warehouse GovernanceWhite Paper -  Data Warehouse Governance
White Paper - Data Warehouse Governance
 
Objectives of erp implementation
Objectives of erp implementationObjectives of erp implementation
Objectives of erp implementation
 
ERP in Small Business
ERP in Small BusinessERP in Small Business
ERP in Small Business
 
ERP implementation Failure at Hershey Food Corperation
ERP implementation Failure at Hershey Food CorperationERP implementation Failure at Hershey Food Corperation
ERP implementation Failure at Hershey Food Corperation
 
Electronic data interchange (edi)
Electronic data interchange (edi)Electronic data interchange (edi)
Electronic data interchange (edi)
 

Similaire à 9. Factors Affecting Erp System Adoption

The Hidden Financial Costs Of Erp Software
The Hidden Financial Costs Of Erp SoftwareThe Hidden Financial Costs Of Erp Software
The Hidden Financial Costs Of Erp SoftwareDonovan Mulder
 
Implementing Erp Systems In Small And Midsize Manufacturing Firms
Implementing Erp Systems In Small And Midsize Manufacturing FirmsImplementing Erp Systems In Small And Midsize Manufacturing Firms
Implementing Erp Systems In Small And Midsize Manufacturing FirmsDonovan Mulder
 
4. Expectation And Reality In Erp Implementation Consultant And Solution Prov...
4. Expectation And Reality In Erp Implementation Consultant And Solution Prov...4. Expectation And Reality In Erp Implementation Consultant And Solution Prov...
4. Expectation And Reality In Erp Implementation Consultant And Solution Prov...Donovan Mulder
 
Information management example
Information management exampleInformation management example
Information management exampleIkram KASSOU
 
Evaluating E R P Implementation Luo Strong
Evaluating  E R P Implementation  Luo StrongEvaluating  E R P Implementation  Luo Strong
Evaluating E R P Implementation Luo StrongMark
 
An Empirical Investigation Of Factors Affecting ERP Impact
An Empirical Investigation Of Factors Affecting ERP ImpactAn Empirical Investigation Of Factors Affecting ERP Impact
An Empirical Investigation Of Factors Affecting ERP ImpactLisa Muthukumar
 
10. What Managers Should Know About Erp Erpii
10. What Managers Should Know About Erp Erpii10. What Managers Should Know About Erp Erpii
10. What Managers Should Know About Erp ErpiiDonovan Mulder
 
Erp research agenda(imds)
Erp research agenda(imds)Erp research agenda(imds)
Erp research agenda(imds)012roger
 
A Critical Success Factors Model For Enterprise Resource Planning Implementation
A Critical Success Factors Model For Enterprise Resource Planning ImplementationA Critical Success Factors Model For Enterprise Resource Planning Implementation
A Critical Success Factors Model For Enterprise Resource Planning ImplementationJoko Sriyanto
 
Analysis of Enterprise Resource Planning Systems (ERPs) with Technical aspects
Analysis of Enterprise Resource Planning Systems (ERPs) with Technical aspectsAnalysis of Enterprise Resource Planning Systems (ERPs) with Technical aspects
Analysis of Enterprise Resource Planning Systems (ERPs) with Technical aspectszillesubhan
 
Introduction to ERP Systems
Introduction to ERP SystemsIntroduction to ERP Systems
Introduction to ERP SystemsBilal Shaikh
 
Iadispaper erpevolutionandsmeconstraints-120215113510-phpapp02
Iadispaper erpevolutionandsmeconstraints-120215113510-phpapp02Iadispaper erpevolutionandsmeconstraints-120215113510-phpapp02
Iadispaper erpevolutionandsmeconstraints-120215113510-phpapp02sliang
 
Investigation and Study of Vital Factors in Selection, Implementation and Sat...
Investigation and Study of Vital Factors in Selection, Implementation and Sat...Investigation and Study of Vital Factors in Selection, Implementation and Sat...
Investigation and Study of Vital Factors in Selection, Implementation and Sat...IJECEIAES
 
The Critical Success Factors For Erp Implementation An Organisational Fit Per...
The Critical Success Factors For Erp Implementation An Organisational Fit Per...The Critical Success Factors For Erp Implementation An Organisational Fit Per...
The Critical Success Factors For Erp Implementation An Organisational Fit Per...Donovan Mulder
 
Pre assessment model for erp implementation
Pre assessment model for erp implementationPre assessment model for erp implementation
Pre assessment model for erp implementationIAEME Publication
 
Pre assessment model for erp implementation
Pre assessment model for erp implementationPre assessment model for erp implementation
Pre assessment model for erp implementationIAEME Publication
 
8. Erp Managing The Implementation Process
8. Erp   Managing The Implementation Process8. Erp   Managing The Implementation Process
8. Erp Managing The Implementation ProcessDonovan Mulder
 
Business intelligence implementation case study
Business intelligence implementation case studyBusiness intelligence implementation case study
Business intelligence implementation case studyJennie Chen, CTP
 

Similaire à 9. Factors Affecting Erp System Adoption (20)

The Hidden Financial Costs Of Erp Software
The Hidden Financial Costs Of Erp SoftwareThe Hidden Financial Costs Of Erp Software
The Hidden Financial Costs Of Erp Software
 
Implementing Erp Systems In Small And Midsize Manufacturing Firms
Implementing Erp Systems In Small And Midsize Manufacturing FirmsImplementing Erp Systems In Small And Midsize Manufacturing Firms
Implementing Erp Systems In Small And Midsize Manufacturing Firms
 
4. Expectation And Reality In Erp Implementation Consultant And Solution Prov...
4. Expectation And Reality In Erp Implementation Consultant And Solution Prov...4. Expectation And Reality In Erp Implementation Consultant And Solution Prov...
4. Expectation And Reality In Erp Implementation Consultant And Solution Prov...
 
Information management example
Information management exampleInformation management example
Information management example
 
Evaluating E R P Implementation Luo Strong
Evaluating  E R P Implementation  Luo StrongEvaluating  E R P Implementation  Luo Strong
Evaluating E R P Implementation Luo Strong
 
An Empirical Investigation Of Factors Affecting ERP Impact
An Empirical Investigation Of Factors Affecting ERP ImpactAn Empirical Investigation Of Factors Affecting ERP Impact
An Empirical Investigation Of Factors Affecting ERP Impact
 
10. What Managers Should Know About Erp Erpii
10. What Managers Should Know About Erp Erpii10. What Managers Should Know About Erp Erpii
10. What Managers Should Know About Erp Erpii
 
Erp research agenda(imds)
Erp research agenda(imds)Erp research agenda(imds)
Erp research agenda(imds)
 
Jom 06 02_013
Jom 06 02_013Jom 06 02_013
Jom 06 02_013
 
A Critical Success Factors Model For Enterprise Resource Planning Implementation
A Critical Success Factors Model For Enterprise Resource Planning ImplementationA Critical Success Factors Model For Enterprise Resource Planning Implementation
A Critical Success Factors Model For Enterprise Resource Planning Implementation
 
Analysis of Enterprise Resource Planning Systems (ERPs) with Technical aspects
Analysis of Enterprise Resource Planning Systems (ERPs) with Technical aspectsAnalysis of Enterprise Resource Planning Systems (ERPs) with Technical aspects
Analysis of Enterprise Resource Planning Systems (ERPs) with Technical aspects
 
C044031823
C044031823C044031823
C044031823
 
Introduction to ERP Systems
Introduction to ERP SystemsIntroduction to ERP Systems
Introduction to ERP Systems
 
Iadispaper erpevolutionandsmeconstraints-120215113510-phpapp02
Iadispaper erpevolutionandsmeconstraints-120215113510-phpapp02Iadispaper erpevolutionandsmeconstraints-120215113510-phpapp02
Iadispaper erpevolutionandsmeconstraints-120215113510-phpapp02
 
Investigation and Study of Vital Factors in Selection, Implementation and Sat...
Investigation and Study of Vital Factors in Selection, Implementation and Sat...Investigation and Study of Vital Factors in Selection, Implementation and Sat...
Investigation and Study of Vital Factors in Selection, Implementation and Sat...
 
The Critical Success Factors For Erp Implementation An Organisational Fit Per...
The Critical Success Factors For Erp Implementation An Organisational Fit Per...The Critical Success Factors For Erp Implementation An Organisational Fit Per...
The Critical Success Factors For Erp Implementation An Organisational Fit Per...
 
Pre assessment model for erp implementation
Pre assessment model for erp implementationPre assessment model for erp implementation
Pre assessment model for erp implementation
 
Pre assessment model for erp implementation
Pre assessment model for erp implementationPre assessment model for erp implementation
Pre assessment model for erp implementation
 
8. Erp Managing The Implementation Process
8. Erp   Managing The Implementation Process8. Erp   Managing The Implementation Process
8. Erp Managing The Implementation Process
 
Business intelligence implementation case study
Business intelligence implementation case studyBusiness intelligence implementation case study
Business intelligence implementation case study
 

Plus de Donovan Mulder

Towards A Model Of Organisational Prerequistes For Enterprise Wide Sys Integ
Towards A Model Of Organisational Prerequistes For Enterprise Wide Sys IntegTowards A Model Of Organisational Prerequistes For Enterprise Wide Sys Integ
Towards A Model Of Organisational Prerequistes For Enterprise Wide Sys IntegDonovan Mulder
 
The Royalty Of Loyalty Crm, Quality And Retention
The Royalty Of Loyalty Crm, Quality And RetentionThe Royalty Of Loyalty Crm, Quality And Retention
The Royalty Of Loyalty Crm, Quality And RetentionDonovan Mulder
 
Realising Enhanced Value Due To Business Network Redesign Through Extended Er...
Realising Enhanced Value Due To Business Network Redesign Through Extended Er...Realising Enhanced Value Due To Business Network Redesign Through Extended Er...
Realising Enhanced Value Due To Business Network Redesign Through Extended Er...Donovan Mulder
 
Managing Dirty Data In Organization Using Erp
Managing Dirty Data In Organization Using ErpManaging Dirty Data In Organization Using Erp
Managing Dirty Data In Organization Using ErpDonovan Mulder
 
16. Erp Ii A Conceptual Framework For Next Generation Enterprise Systems
16. Erp Ii A Conceptual Framework For Next Generation Enterprise Systems16. Erp Ii A Conceptual Framework For Next Generation Enterprise Systems
16. Erp Ii A Conceptual Framework For Next Generation Enterprise SystemsDonovan Mulder
 
15. Assessing Risk In Erp Projects Identify And Prioritize The Factors
15. Assessing Risk In Erp Projects Identify And Prioritize The Factors15. Assessing Risk In Erp Projects Identify And Prioritize The Factors
15. Assessing Risk In Erp Projects Identify And Prioritize The FactorsDonovan Mulder
 
14. Business Process Approach Towards An Inter Organizational Enterprise System
14. Business Process Approach Towards An Inter Organizational Enterprise System14. Business Process Approach Towards An Inter Organizational Enterprise System
14. Business Process Approach Towards An Inter Organizational Enterprise SystemDonovan Mulder
 
13. Effectiveness Of Erp Systems
13. Effectiveness Of Erp Systems13. Effectiveness Of Erp Systems
13. Effectiveness Of Erp SystemsDonovan Mulder
 
12. Managing Risk Factors In Erp Implementation And Design
12. Managing Risk Factors In Erp Implementation And Design12. Managing Risk Factors In Erp Implementation And Design
12. Managing Risk Factors In Erp Implementation And DesignDonovan Mulder
 
11. Requirements Of An Erp Enterprise Erp Modeller
11. Requirements Of An Erp Enterprise Erp Modeller11. Requirements Of An Erp Enterprise Erp Modeller
11. Requirements Of An Erp Enterprise Erp ModellerDonovan Mulder
 
6. The Usefulness Of Erp Systems For Effective Management
6. The Usefulness Of Erp Systems For Effective Management6. The Usefulness Of Erp Systems For Effective Management
6. The Usefulness Of Erp Systems For Effective ManagementDonovan Mulder
 
5. Change Management Strategies For Successful Erp Implementation
5. Change Management Strategies For Successful Erp Implementation5. Change Management Strategies For Successful Erp Implementation
5. Change Management Strategies For Successful Erp ImplementationDonovan Mulder
 
3. Project Management A Case Study Of A Successful Erp Implementation
3. Project Management A Case Study Of A Successful Erp Implementation3. Project Management A Case Study Of A Successful Erp Implementation
3. Project Management A Case Study Of A Successful Erp ImplementationDonovan Mulder
 
2. Erp Innovation Implementation Model Incorporating Change Management
2. Erp Innovation Implementation Model Incorporating Change Management2. Erp Innovation Implementation Model Incorporating Change Management
2. Erp Innovation Implementation Model Incorporating Change ManagementDonovan Mulder
 
1. An Erp Performance Measurement Framework Using A Fuzzy Integral Approach
1. An Erp Performance Measurement Framework Using A Fuzzy Integral Approach1. An Erp Performance Measurement Framework Using A Fuzzy Integral Approach
1. An Erp Performance Measurement Framework Using A Fuzzy Integral ApproachDonovan Mulder
 
Using A Km Framework To Evaluate An Erp System Implementation
Using A Km Framework To Evaluate An Erp System ImplementationUsing A Km Framework To Evaluate An Erp System Implementation
Using A Km Framework To Evaluate An Erp System ImplementationDonovan Mulder
 

Plus de Donovan Mulder (17)

Towards A Model Of Organisational Prerequistes For Enterprise Wide Sys Integ
Towards A Model Of Organisational Prerequistes For Enterprise Wide Sys IntegTowards A Model Of Organisational Prerequistes For Enterprise Wide Sys Integ
Towards A Model Of Organisational Prerequistes For Enterprise Wide Sys Integ
 
The Royalty Of Loyalty Crm, Quality And Retention
The Royalty Of Loyalty Crm, Quality And RetentionThe Royalty Of Loyalty Crm, Quality And Retention
The Royalty Of Loyalty Crm, Quality And Retention
 
Realising Enhanced Value Due To Business Network Redesign Through Extended Er...
Realising Enhanced Value Due To Business Network Redesign Through Extended Er...Realising Enhanced Value Due To Business Network Redesign Through Extended Er...
Realising Enhanced Value Due To Business Network Redesign Through Extended Er...
 
Managing Dirty Data In Organization Using Erp
Managing Dirty Data In Organization Using ErpManaging Dirty Data In Organization Using Erp
Managing Dirty Data In Organization Using Erp
 
Higher Order Testing
Higher Order TestingHigher Order Testing
Higher Order Testing
 
16. Erp Ii A Conceptual Framework For Next Generation Enterprise Systems
16. Erp Ii A Conceptual Framework For Next Generation Enterprise Systems16. Erp Ii A Conceptual Framework For Next Generation Enterprise Systems
16. Erp Ii A Conceptual Framework For Next Generation Enterprise Systems
 
15. Assessing Risk In Erp Projects Identify And Prioritize The Factors
15. Assessing Risk In Erp Projects Identify And Prioritize The Factors15. Assessing Risk In Erp Projects Identify And Prioritize The Factors
15. Assessing Risk In Erp Projects Identify And Prioritize The Factors
 
14. Business Process Approach Towards An Inter Organizational Enterprise System
14. Business Process Approach Towards An Inter Organizational Enterprise System14. Business Process Approach Towards An Inter Organizational Enterprise System
14. Business Process Approach Towards An Inter Organizational Enterprise System
 
13. Effectiveness Of Erp Systems
13. Effectiveness Of Erp Systems13. Effectiveness Of Erp Systems
13. Effectiveness Of Erp Systems
 
12. Managing Risk Factors In Erp Implementation And Design
12. Managing Risk Factors In Erp Implementation And Design12. Managing Risk Factors In Erp Implementation And Design
12. Managing Risk Factors In Erp Implementation And Design
 
11. Requirements Of An Erp Enterprise Erp Modeller
11. Requirements Of An Erp Enterprise Erp Modeller11. Requirements Of An Erp Enterprise Erp Modeller
11. Requirements Of An Erp Enterprise Erp Modeller
 
6. The Usefulness Of Erp Systems For Effective Management
6. The Usefulness Of Erp Systems For Effective Management6. The Usefulness Of Erp Systems For Effective Management
6. The Usefulness Of Erp Systems For Effective Management
 
5. Change Management Strategies For Successful Erp Implementation
5. Change Management Strategies For Successful Erp Implementation5. Change Management Strategies For Successful Erp Implementation
5. Change Management Strategies For Successful Erp Implementation
 
3. Project Management A Case Study Of A Successful Erp Implementation
3. Project Management A Case Study Of A Successful Erp Implementation3. Project Management A Case Study Of A Successful Erp Implementation
3. Project Management A Case Study Of A Successful Erp Implementation
 
2. Erp Innovation Implementation Model Incorporating Change Management
2. Erp Innovation Implementation Model Incorporating Change Management2. Erp Innovation Implementation Model Incorporating Change Management
2. Erp Innovation Implementation Model Incorporating Change Management
 
1. An Erp Performance Measurement Framework Using A Fuzzy Integral Approach
1. An Erp Performance Measurement Framework Using A Fuzzy Integral Approach1. An Erp Performance Measurement Framework Using A Fuzzy Integral Approach
1. An Erp Performance Measurement Framework Using A Fuzzy Integral Approach
 
Using A Km Framework To Evaluate An Erp System Implementation
Using A Km Framework To Evaluate An Erp System ImplementationUsing A Km Framework To Evaluate An Erp System Implementation
Using A Km Framework To Evaluate An Erp System Implementation
 

9. Factors Affecting Erp System Adoption

  • 1. The Emerald Research Register for this journal is available at The current issue and full text archive of this journal is available at www.emeraldinsight.com/researchregister www.emeraldinsight.com/1741-0398.htm JEIM 18,4 Factors affecting ERP system adoption A comparative analysis between SMEs and 384 large companies G. Buonanno, P. Faverio, F. Pigni, A. Ravarini, D. Sciuto and M. Tagliavini ` CETIC Universita Cattaneo – LIUC, Castellanza, Italy Abstract Purpose – Proposes providing an insight about enterprise resource planning (ERP) adoption, highlighting contact points and significant differences between the way small to medium-sized enterprises (SMEs) and large companies approach such a task. Design/methodology/approach – The research is based on a wide literature review, focused on the identification of a taxonomy of business and organizational factors influencing ERP adoption. The deriving research model was incorporated in a questionnaire that was preliminarily tested and finally provided to a sample of 366 companies of any size. Responses were collected through personal interviews made by a dedicated team to a top manager. Findings – The analysis of the empirical data shows that business complexity, as a composed factor, is a weak predictor of ERP adoption, whereas just company size turns out to be a very good one. In other words, companies seem to be disregarding ERP systems as an answer to their business complexity. Unexpectedly, SMEs disregard financial constraints as the main cause for ERP system non-adoption, suggesting structural and organizational reasons as major ones. This pattern is partially different from what was observed in large organizations where the first reason for not adopting an ERP system is organizational. Moreover, the decision process regarding the adoption of ERP systems within SMEs is still more affected by exogenous reasons or “opportunity of the moment” than business-related factors, contrary to large companies that are more interested in managing process integration and data redundancy/inconsistency through ERP implementation. Research limitations/implications – The research model is based on the assumption that business complexity and organizational change are the most relevant variables influencing ERP adoption, and such variables are explained through a set of factors inherently limited by the results of the literature review. Practical implications – The results of the empirical research provide indication to SMEs willing to take into consideration the adoption of an ERP system. The same outcomes could be incorporated into the development strategies of ERP software houses. Originality/value – This paper contributes to enhancing the understanding of the factors influencing the evolution of information systems within SMEs with respect to large companies. Keywords Manufacturing resource planning, Small to medium-sized enterprises, Organizational change Paper type Research paper Journal of Enterprise Information Introduction Management The capability of enterprise resource planning (ERP) systems to manage a company’s Vol. 18 No. 4, 2005 pp. 384-426 resources efficiently and effectively by providing a total, integrated solution for its q Emerald Group Publishing Limited 1741-0398 information processing needs (Fui Hoon Nah et al., 2001) has persuaded both DOI 10.1108/17410390510609572 practitioners and managers of the importance of integrated systems, not only for large
  • 2. multinational organizations, but also for small and medium-sized firms (Van Factors affecting Everdingen et al., 2000). ERP system The evaluation of the contribution of ERP systems in terms of both value creation and economic returns is a difficult task, because of the extent of the organizational changes adoption (Lozinsky, 1999; Shtub, 1999; Willcocks and Lacity, 1998) to which their implementation leads, as well as the difficulties in predicting the return on investment (Mabert et al., 2001). The competences required to manage properly the organizational change 385 determined by an ERP system implementation is still a debated issue. The most qualified literature has always stressed the importance of change and project management competences as critical success factors for ERP implementation (Davenport, 2000; Mandal and Gunasekaran, 2003; Motwani et al., 2002), hereby indirectly raising the issue of small to medium-sized enterprises’s (SMEs’s) lack of organizational preparation. Such a situation is mainly caused by the low extent of formalization of people’s roles and responsibilities that is expressed by with their continuous re-shuffle (Dutta and Evrard, 1999). This structural condition makes the identification of ERP implementation’s main figures, such as the process owner and the key user (Davenport, 2000), extremely difficult to achieve. Beside this, SMEs generally suffer from a widespread lack of culture, as to the concept of business process: it is not by chance that the reinforcement of the concept of business process is often claimed among the critical success factors in ERP implementation (Beretta, 2002). In particular, the business process concept helps promoting co-operation and convergence of efforts among managers (i.e. managerial integration), versus the internal competition induced by the functionally-oriented organizational models which is typical of SMEs. One of the most misleading legacies of traditional software project management is that the company expects to gain value from the use of the software application as soon as it is installed (Al-Mashari et al., 2003). Since the adoption of an ERP system requires extensive efforts, both for the technological and business aspects of the implementation, neither information technology (IT) practitioners nor researchers have developed a deterministic method to evaluate the related impacts (Al-Mashari, 2002). In spite of the benefits potentially offered by ERP systems (Banker et al., 1998; Davenport, 1998; Gable, 1998; Hicks and Stecke, 1998; Minahan, 1998) the evaluation issue plays an essential role regardless the company size; during the planning phase it is critical for companies to figure out whether a specific ERP system fits their business practices. When the features of the software application do not correctly fit the business requirements two possible strategies can be identified: (1) Change the business processes to fit the software with minimal customization. On one hand, fewer modifications to the software application should reduce errors and help to take advantage of newer versions and releases (Fui Hoon Nah et al., 2001). On the other hand, this choice could mean changes in long-established ways of doing business (that often provide competitive advantage), and could shake up important people roles and responsibilities (Dewett and Jones, 2001; Koch et al., 1999). (2) Modify the software to fit the processes. This choice would slow down the project, could affect the stability and correctness of the software application and could increase the difficulty of managing future releases, because the customizations could need to be torn apart and rewritten to work with the newer version (Koch et al., 1999). Conversely, it implies less organizational
  • 3. JEIM changes, because it does not require dramatically changing the company best practices, and therefore the way people work. 18,4 Although ERP vendors are concentrating on the customization process needed to match the ERP system modules with the actual features of existing processes in a number of different industries, several studies show that configuring and implementing ERP 386 systems is a complex and expensive task (Van Everdingen et al., 2000; Mabert et al., 2000). Several aspects related to this twofold approach towards ERP adoption and implementation become even more critical, for their known specificities, within SMEs (Ravarini et al., 2000; Van Everdingen et al., 2000). Although the effective use of business information is a strategic goal for companies of any size, nowadays most of the ERP systems available on the market are too expensive for the financial capabilities of smaller companies (Chau, 1995; Gartner Group and Dataquest, 1998, 1999). SMEs differ from large companies in important ways affecting their information-seeking practices (Lang et al., 1997). These differences include the: . lack of (or substantially less sophisticated) information system management (Kagan et al., 1990); . frequent concentration of information-gathering responsibilities into one or two individuals, rather than the specialization of scanning activities among top executives (Hambrick, 1981); . lower levels of resource available for information-gathering; and . quantity and quality of available environmental information (Pearce et al., 1982). Chan (1999) asserts that many SMEs either do not have sufficient resources or are not willing to commit a huge fraction of their resources due to the long implementation times and high fees associated with ERP implementation. The resource scarcity, the lack of strategic planning of information systems (IS) (Cragg and Zinatelli, 1995; Levy and Powell, 2000; Zinatelli et al., 1996), the limited expertise in IT (Levy and Powell, 2000) and also the opportunity to adopt a process-oriented view of the business are among the factors that strongly influence, either positively or negatively, ERP adoption by SMEs. Thus it is necessary to find out alternative solutions providing the ERP capabilities at an affordable price, including implementation costs (Rao, 2000). Some ERP vendors have taken up the gauntlet and have been moving their attention toward SMEs (Gable and Stewart, 1999) by offering simplified and cheaper solutions (Kirchmer, 1998) from both the organizational and technological points of view, pre-configured systems based on best-practices at a fraction of the cost originally required and promising implementation times of 60 days. In spite of such promises, there is not a general agreement on the effectiveness of such systems. As a result, the current ERP systems adoption rate in SMEs is still low. Furthermore, even if ERP implementation differences between large and small organizations are recognized in literature (Bernroider and Koch, 2001), their focus is on the decision-making process. Hence, other issues need to be further explored: To what extent SMEs informational needs are different with respect to large companies? Are SME peculiarities a real obstacle to ERP adoption? Is it possible to identify a relationship between organizational change and ERP adoption in companies of different size? This paper studies the factors influencing ERP systems adoption, and discusses to what extent the differences between SMEs and larger firms affect such factors,
  • 4. contributing to the increasing literature on ERP adoption in small businesses. Through Factors affecting a detailed literature review, a set of indicators are identified as variables which could ERP system influence the ERP adoption process. These indicators have been tested on the field through an empirical study carried out on a sample of 366 companies. adoption Conceptual framework The literature provides different definitions of ERP systems: Rosemann (1999) defines an 387 ERP system as a customizable, standard application software which includes integrated business solutions for the core processes (e.g. production planning and control, warehouse management) and the main administrative functions (e.g. accounting, human resource management) of an enterprise. Gable (1998) defines it as a comprehensive package software solution that seeks to integrate the complete range of business processes and functions in order to present an holistic view of the business from a single information and IT architecture. Watson and Schneider (1999) define ERP as an integrated, customized, packaged software-based system that handles the majority of an enterprise’s system requirements in all functional areas such as finance, human resources, manufacturing, sales, and marketing. It has a software architecture that facilitates the flow of information among all functions within an enterprise. It is built on a common database and is supported by a single development environment. Previous research works (Gibson et al., 1999; Ryan, 1999) suggested how ERP adoption and implementation could be an highly complex task in which strong managerial and strategic competences are required to achieve the best fit between the business peculiarities and the system itself and to deal with the unavoidable organizational impact induced by an ERP implementation. Other studies outlined different adoption patterns depending on company size and also observed that smaller companies face only subset of the needs and opportunities of larger organizations (Markus and Tanis, 2000). Furthermore, for a long time ERP adoption reasons within SMEs were explained only by contingency or exogenous factors (Tagliavini et al., 2002). To investigate these differences further, the research model presented in this paper explores to what extent the business complexity (measured from a set of business factors) and the awareness of the organizational requirements (measured by the extent of organizational change) affect the extent of ERP adoption. Such an effort seems, in fact, feasible for organizations experiencing high business complexity and information needs, and expecting, or even planning, significant organizational changes. The methodology contribution of this paper is experimentally proved by testing the relationship between business complexity, organizational change and ERP adoption on 300 SMEs through direct, survey-based, interviews. Such an approach, based on a statistical analysis on a high number of respondents, implies that its findings are not easily comparable to other previous research works that are often based on case studies on a very small set of companies. The following sections will detail the two main components of the conceptual framework: the business factors and the organizational change. Business factors Although the organizational structure of larger firms could be very different from SMEs, it is reasonable to assume that companies of any size, characterized by high organizational complexity (or “business complexity”), also show a critical need for
  • 5. JEIM coordination and control of business activities which, in turn, is related to the complexity 18,4 of the information system (Grinyer et al., 1986; Lorange, 1980; Vancil and Lorange, 1975). Since ERP systems have been very often advocated by researchers and practitioners as “the answer” to manage the complexity of information flows more effectively, this last interpretation of business complexity, will be used in the research model to investigate if the “the condition” of being a complex organizations (which is measured by a set of 388 business factors) and a greater extent of ERP adoption are straight related factors. Hence, the model approaches ERP systems as a sort of “black box” and thus their undeniable inner complexity (expressed by implementation and technological issues for instance) is taken for granted, and are therefore considered only an exogenous factor embedded into the ERP concept itself. In particular, the several issues related to ERP system chartering, development and maintenance (i.e. project and change management issues or cultural and organizational un-readiness) are typical of the “critical success factors” stream of research (Davenport, 2000; Mandal and Gunasekaran, 2003; Motwani et al., 2002) and generally refer more to the success of the implementation than to the reasons that bring companies to evaluate the opportunity of implementing an ERP system. Therefore, is business complexity the possible explanation? The assessment of the complexity measures is partially based on previous works (Grinyer et al., 1986; Yasai-Ardekani and Haug, 1997) that have developed and proposed metrics essentially based on size, diversification, and divisionalization. This paper neither proposes any new measure nor tests their reliability; instead it studies their occurrence in ERP adoption. Since the consistency of these indicators is essential for the theoretical validity of the whole framework, a detailed analysis of the IS literature has been performed in order to identify a set of additional business factors: . Company size (micro, small, medium, large). Existing literature confirms the existence of a mutual dependence between size and organizational complexity. Kimberly (1976) stressed the necessity of applying a different approach depending on the industry the company belongs to: for the services industry the number of employees has a better fit, while for manufacturing companies the turnover seems to be a better match. In any case, literature emphasizes size as one of the issues increasing the need for co-ordination and control of organizational activities (Howard and Hine, 1997; Yasai-Ardekani and Haug, 1997). Apart from any organizational or strategic remark, other research works (IDC, 1999) simply suggest a direct relationship between the size of organizations and the percentage of organizations where ERP has been implemented. . The market area (local, regional, national, international). Working on a wider market area requires the management of more differentiated legal and cultural issues, thus introducing a higher level of complexity (Davenport, 1998; Hamel and Prahalad, 1994; Prahalad, 1990; Sanders and Carpenter, 1998), as well as the facing of competitive pressures characterizing the international markets (Bartlett and Ghoshal, 1989; Roth and O’Donnell, 1996; Rumelt, 1974). In addition, as companies become more global and develop international supply chains, the limitations of MRPII have become apparent. Literature has identified the attempts being made by many organizations to expand their IS infrastructure beyond their organizational boundaries through the development of inter-organizational business systems. Consequently, this has resulted in the widespread adoption of ERP solutions (Irani, 2002).
  • 6. . The membership an industrial group (either as the holding or as a controlled firm). Factors affecting This variable seems to be strongly related to the co-ordination of dispersed ERP system business units, in terms of alignment of processes and procedures both between the holding and the controlled companies and among controlled companies adoption themselves. However, if the imposition of common operating processes on all units could lead to a tight coordination between the controlled companies, in a multiregional context strict process uniformity could be counterproductive in 389 terms of flexibility (Davenport, 1998). . The presence of branch offices (localization and number of branches). The management of information flows is a crucial issue for companies with branch offices which need to be remotely controlled. In larger organizations the development of intranets is often characterized by a lack of coordination and supervision (Horgan, 1997). SMEs face different issues (i.e. the cultural and technological levels of the entrepreneur): this is one of the aspects that must be considered to comprehend fully the fall-outs in terms of management complexity, organizational impact and required competencies. . The level of diversification (in terms of products, markets, technologies). Operating in different product-market combinations introduces another level of complexity (Yasai-Ardekani and Haug, 1997). In related-diversified firms, an increase in the number of businesses adds information-processing demands by increasing business-unit interdependencies (Hill and Hoskisson, 1987; Kerr, 1985; Michel and Hambrick, 1992; Pitts and Hopkins, 1982). In unrelated-diversifiers, as the number of businesses increases, the information-processing requirements associated with maintaining efficient internal capital markets also increase (Jones and Hill, 1988). Moreover, because of the greater need for co-ordination and control of activities, complex organizations will tend to have specialized planning departments, employ a larger number of planners and consequently devote a substantially larger amount of financial resources to strategic planning (Grinyer et al., 1986; Kukalis, 1989). . The degree of functional extension (number of activities carried out internally). Many companies prefer to outsource those activities that are not directly related to the business strategies (non-core processes). The degree of functional extension refers to the number of strategic functions directly managed within the company, which should be related to the amount of information to be managed (Price, 1997). In the light of the identified business factors, it is therefore necessary to verify the association between these factors and the use of ERP systems by testing the following six main hypotheses: H1. The company size affects the adoption of ERP systems. H2. The market area affects the adoption of ERP systems. H3. The membership of a group affects the adoption of ERP systems. H4. The presence of branch offices affects the adoption of ERP systems. H5. The level of diversification affects the adoption of ERP systems. H6. The degree of functional extension affects the adoption of ERP systems.
  • 7. JEIM Organizational change factors 18,4 Even though business factors play an important role in determining business complexity they are not considered sufficient to assure the feasibility of ERP adoption. Another issue that deserves consideration is the organizational impact of ERP systems as they tend to impose their own logic on company strategy, organization and culture (Davenport, 1998). Thus, the ERP adoption decision affects most of the company business functions and 390 directly involves a significant number of people. The project team responsible for ERP implementation will be challenged to either match the functionality of the application to business practice or find ways to adapt or change current processes and procedures, while the project team could face organizational resistance to changing the status quo (Laughlin, 1999). By providing universal, real-time access to operating and financial data, ERP systems allow companies to streamline their management structures, creating flatter, more flexible, and more democratic organizations. On the other hand, they also involve the centralization of control over information and the standardization of processes, which are qualities more consistent with hierarchical, command-and-control organizations with uniform cultures (Davenport, 1998). Are the organizations aware of such a change and then ready to bear and manage it? Is the alignment between the desired organizational change and the complexity of the IT solution verified? These remarks highlight a possible relationship between the extent of organizational change and the rate of ERP system adoption. The extent of organizational change represents the degree of company transformation that the entrepreneur plans as a consequence of a technological innovation. This measure depends on the evaluation of the organizational and economic impacts, such as the competence of the internal staff or their expected resistance to change to the adoption of a new technology. In order to analyze the factors influencing the adoption of ERP systems, we assume that ERP systems could generate larger benefits if implemented when a high level of organizational change is planned. Venkatraman (1994) classifies five main levels of transformation (Figure 1): (1) Local automation of existing procedures. This strategy is pursued only for automation of local, independent procedures. It requires minimal efforts and the corresponding expected results are enhancements in business process performance. Benefits coming from this strategy are easily duplicable, as Figure 1. Levels of business transformation related to technological innovation
  • 8. most of standardized solutions. Therefore, it is unlikely to obtain competitive Factors affecting advantage by simply automating existing procedures. ERP system (2) Internal integration of existing business processes. It aims at integrating the adoption business processes and the company IS in order to create competitive advantage. The required integration has to be pursued both at the technological and organizational level: whenever necessary, people belonging to different business functions have to cooperate to reach common objectives. Together with the 391 necessary automation effort, this strategy requires an integration effort; however, in both cases the business process structures remain unchanged. (3) Business process reengineering. It involves the partial or complete redesign of business processes, affecting not only the company procedures, but also its organizational structure. (4) Business network redesign. Changes overcome the boundaries of the company and could affect the entire network of its external relationships. For instance, electronic data interchange (EDI) can represent the technology chosen to pursue this strategy, but a great effort has to be put into business process integration, through a continuous information exchange and competence sharing. Under these conditions each partner can exploit the competencies of the business network instead of adopting expensive solutions of vertical integration. (5) Redefinition of company boundaries through the creation of inter-organizational relationships. The information communication technologies (ICT) allow the redefinition of the competitive environment through the creation of strong inter-organizational relationships (joint ventures, long-term contracts, licensing agreements). Therefore another hypothesis to be tested is focused on the matching between organizational issues and ERP system adoption: H7. The extent of planned organizational change is directly related to the use of ERP systems (the greater is the planned organizational change, the greater is the rate of adoption of ERP systems). To develop an effective framework it is necessary to include into the research model (as control measures) both the endogenous and exogenous reasons that may affect ERP adoption. According to the literature (Al-Mashari, 2002), among the reasons that may affect ERP adoption, either positively or negatively, it is possible to distinguish operational reasons (i.e. improving responsiveness to customers and simplifying ineffective or complex business processes) and technological reasons (i.e. Y2K compliance requirements, integration of business processes and systems, replacement of older, obsolete systems). For those companies which have stated that they do not make use of an ERP system, we classified each justification for ERP non-adoption into four main categories: (1) Structural motivations related to the need for coordination and control of business activities, thus to the complexity of information flows (which means that the company is not sufficiently complex to need an ERP system to manage the business). (2) Organizational motivations (the company is not prepared to face and manage the organizational changes related to the adoption and implementation of an ERP system).
  • 9. JEIM (3) Economic motivations (ERP system adoption and implementation would be too 18,4 costly for the company). (4) Other reasons. In the light of the control measures introduced the whole framework can be represented as shown in Figure 2. 392 Methodology Based on the literature review, focused on the identification of a taxonomy of business and organisational factors, a questionnaire was designed. It comprised three parts: the company demographics, the assessment of each business factor and the extent of the organizational change. Before the complete deployment of the survey a first trial was carried out on 122 companies suggesting the validity of the proposed approach (Tagliavini et al., 2002). Responses were collected through personal interviews made by a dedicated team to a top manager (possibly the entrepreneur him/herself or the CEO) since the proposed questions required the knowledge of the main business objectives, as well as of the features of the different business activities. The final questionnaire (an abstract is shown in Figure 2) was then proposed to a random sample of about 2000 Italian companies of any size and industry, geographically located in northern Italy. Data were finally analyzed with SPSS v11, in particular the hypotheses (from H1-H7) have been tested by means of cross tabulations. Pearson chi-square was used to verify whether the cross-tabulated groups were different, while p-values measure how the previously mentioned difference is statistically significant. Finally, the value of Spearman’s R is used to evaluate the reliability of correlations. A preliminary validation of collected data has been performed by cross-tabulating ERP adoption with each of the seven factors corresponding to the seven hypotheses (from H1-H7). Chi-square and p-value tests have been used to verify whether the set of companies using an ERP system is significantly different from the set of the not adopters. Then, the connection existing between each factor and ERP adoption has been assessed through Pearson’s R. A further analysis has been also performed Figure 2. Theoretical framework
  • 10. separating SMEs from large companies to highlight possible differences between the Factors affecting two subsets. ERP system adoption Variable measurement According to the theoretical framework, the following sets of variables were measured: (1) The business complexity factors have been evaluated through six indicators 393 detailed in the Figure 3. Respondents were asked to qualitatively assess each variable of the set. More specifically: . Diversification has been measured as a synthetic index of business strategy by offering only two possible responses: diversification and other strategies (including cost-based and differentiation strategies). . Degree of functional extension, i.e. the number of activities carried out internally, has been assessed with respect to a set of typical business activities. The classical representation of the value chain (Porter and Millar, 1985) has been integrated with a more recent measure used to assess the impact of BPR on manufacturing firms (Guimaraes and Bond, 1996). This measure has been already adopted in author’s previous research (Tagliavini et al., 2002). (2) The extent of organizational change which aims at evaluating the level of organizational change the company is prepared to face in order to achieve competitive advantage through the use of IT, has been assessed through a question suggesting Venkatraman five levels of organizational change. Due to the academic formulation which undoubtedly characterizes the question in the survey, all the organizational implications and characteristics related to each level of the Venkatraman’s model have been thoroughly explained by the interviewers to respondents, to clearly point out any organizational-related issue. (3) The technological and operational drivers have been assessed using the model proposed by Al-Mashari (2002) integrated with other drivers which have been identified in a previous research (Chau, 1995). Multiple responses were allowed. (4) The motivations for ERP non-adoption have been assessed by asking respondents to select items from a check-list (also in this case multiple responses were allowed). Research findings Of the 2,000 contacted companies only 370 accepted to be interviewed yielding a response rate of 18.5 percent. Data from this sample were collected and filtered to resolve inconsistencies and correct anomalies, resulting in 366 valid questionnaires. The choice of the direct interviews to collect data is accountable for the low rate of rejected questionnaires: only four questionnaires were discarded. Demographic data The first part of the questionnaire dealt with companies’ demographics. Firm size (number of employees and turnover) was investigated according to the current definition provided by the European Union (see Table I).
  • 12. Small sized companies represent 43 percent of respondents (18 percent micro, 25 Factors affecting percent small) while 42 percent have a medium size. Large enterprises represent 15 ERP system percent of the sample. With respect to the industry, the sample can be further categorized into three main adoption groups: manufacturing (66 percent), services (20 percent) and trade (14 percent). This distribution is highly representative of the economical characteristics of this geographic area, where large enterprises and services/wholesaling companies play a 395 secondary role (see Figure 4). Company size (H1) The analysis of the correlation between company size (as a composite index between turnover and number of employees) and ERP adoption shows a very good fit with data. The two groups are significantly different (chi-square equal to 65,166 and p-value lower than 0.001) while the Pearson’s R (0.401) shows that firms size and ERP adoption are significantly correlated. In detail, while only 7 percent of companies not making use of ERP systems are large-sized, the value corresponding to those large companies adopting ERP systems seems even more significant. In fact, despite not constituting the most relevant group in absolute terms (medium-sized companies are the 47 percent of the whole sample adopting ERP), in relative terms as to the sample composition (in which large companies are only 15 percent) large companies show an interesting result (38 percent). The analysis clearly shows also that the rate of ERP system adoption is quite low among both micro and small firms (3 percent and 12 percent respectively). This reinforces the persuasion that the company size affects the ERP adoption process. H1: verified. Membership of a group (H2) The cross tabulation for H2 shows an inverse correlation between membership of a group and ERP adoption (Pearson’s R ¼ 20:277). Moreover, the 55 percent of companies Micro Small-sized Medium-sized Criteria enterprises enterprises enterprises Maximum number of employees ,10 ,50 ,250 Maximum turnover in e million – 7 40 Maximum balance-sheet total in e million – 5 27 Table I. Source: European Commission (1996) SMEs definition Figure 4. Sample definition by size, industry and enterprise application
  • 13. JEIM belonging to a group prefer other management systems rather than ERP (Tables II-IV). A correct interpretation of such result requires considering that distribution of the 18,4 sample according to this factor as unbalanced (237 firms in a standalone configuration compared to 53 belonging to an industrial group). Nonetheless, it is reasonable to conclude that, despite what suggested in the existing literature, the membership of a group seems not to be directly related to the use of ERP systems. 396 The Pearson’s R index of correlation computed on SMEs (2 0.169, Tables V-VII) and large enterprises (0.060, Tables VIII-X) did not show consistent results. H2: rejected. Market area (H3) At a first glance, a wider market area of a company seems to be related to the use of ERP systems. Only a small subset of companies with a limited market area make use of ERP systems, while this value is higher for companies with a national market area (22 percent) and even more for those companies acting on international markets (74 percent, see cross-tabulation in Tables XI-XIII). Nevertheless, the high percentage of companies with an international market area which do not use ERP systems (68 percent) clearly shows that the ERP system is far from being the only solution adopted as stated in H3. The significant difference between the cross-tabulated groups, Company size and ERP adoption (whole sample) Size Other management system ERP Total Micro Count 62 3 65 % within size 95.4 4.6 100.0 % within ERP 23.6 3.3 18.4 Small Count 77 11 88 % within size 87.5 12.5 100.0 % within ERP 29.3 12.2 24.9 Medium Count 105 42 147 % within size 71.4 28.6 100.0 % within ERP 39.9 46.7 41.6 Large Count 19 34 53 % within size 35.8 64.2 100.0 % within ERP 7.2 37.8 15.0 Total Count 263 90 353 Table II. % within size 74.5 25.5 100.0 Company size and ERP % within ERP 100.0 100.0 100.0 adoption (whole sample) % of total 74.5 25.5 100.0 Value df Asymptotic significance (two-sided) a Pearson chi-square 65.166 3 0.000 Likelihood ratio 65.121 3 0.000 Table III. Linear-by-linear association 56.552 1 0.000 Company size and ERP n of valid cases 353 adoption (whole sample) – Chi-square tests Note: a 0 cells (0.0 percent) have expected count less than 5. The minimum expected count is 13.51
  • 14. (chi-square ¼ 14:538, p-value ¼ 0:000, Tables XI-XIII), is contradicted by the Factors affecting unsatisfactory value of the Pearson’s R index (0.190), which confirms the lack of a ERP system correlation between market area and ERP adoption. adoption H3 has also been tested on both SMEs and large companies, pointing out the same trend (Tables XIV-XVI and Tables XVII-XIX). H3: rejected. 397 Asymptotic Approximate Approximate Value standard errora Tb significance Interval by interval Pearson’s R 0.401 0.042 8.197 0.000c Ordinal by ordinal Spearman correlation 0.405 0.044 8.287 0.000c n of valid cases 0.353 Table IV. Company size and ERP Notes: a Not assuming the null hypothesis; b Using the asymptotic standard error assuming the null adoption (whole sample) hypothesis; c Based on normal approximation – symmetric measures Membership of a group and ERP adoption (whole sample) Other management system ERP Total Member of a group Count 54 44 98 % within membership 55.1 44.9 100.0 % within ERP 20.4 48.9 27.6 Standalone company Count 211 46 257 % within membership 82.1 17.9 100.0 % within ERP 79.6 51.1 72.4 Total Count 265 90 355 % within membership 74.6 25.4 100.0 Table V. % within ERP 100.0 100.0 100.0 Membership and ERP % of total 74.6 25.4 100.0 adoption (whole sample) Asymptotic Exact Exact significance significance significance Value df (two-sided) (two-sided) (one-sided) Pearson Chi-square 27.327b 1 0.000 Continuity correctiona 25.919 1 0.000 Likelihood ratio 25.640 1 0.000 Fisher’s exact test 0.000 0.000 Linear-by-linear association 27.250 1 0.000 n of valid cases 355 Table VI. a b Membership and ERP Notes: Computed only for a 2 £ 2 table; 0 cells (0.0 percent) have expected count less than 5. The adoption (whole sample) expected count is 24.85 – Chi-square tests
  • 15. JEIM Presence of branch offices (H4) 18,4 According to the literature, the presence of branch offices could be a factor that positively influences the complexity of information flows and that, consequently, could lead to a larger adoption of ERP systems. The empirical analysis shows a correlation between the extent of geographical dispersion of the company and the use of ERP systems. These systems have been adopted by only 15 percent of respondents with no 398 branch offices and by 42 percent of companies with geographically dispersed offices Asymptotic Approximate Approximate Value standard errora Tb significance Interval by interval Pearson’s R 20.277 0.056 2 5.426 0.000c Ordinal by ordinal Spearman correlation 20.277 0.056 2 5.426 0.000c Table VII. n of valid cases 355 Membership and ERP adoption (whole sample) Notes: a Not assuming the null hypothesis; b Using the asymptotic standard error assuming the null – symmetric measures hypothesis; c Based on normal approximation Membership of a group and ERP adoption (SMEs) Other management system ERP Total Member of a group Count 36 17 53 % within membership 67.9 32.1 100.0 % within ERP 15.2 32.1 18.3 Stand-alone company Count 201 36 237 % within membership 84.8 15.2 100.0 % within ERP 84.8 67.9 81.7 Total Count 237 53 290 Table VIII. % within membership 81.7 18.3 100.0 Membership and ERP % within ERP 100.0 100.0 100.0 adoption (SMEs) % of total 81.7 18.3 100.0 Asymptotic Exact Exact significance significance significance Value df (two-sided) (two-sided) (one-sided) b Pearson chi-square 8.269 1 0.004 Continuity correctiona 7.177 1 0.007 Likelihood ratio 7.393 1 0.007 Fisher’s exact test 0.009 0.005 Linear-by-linear association 8.240 1 0.004 Table IX. n of valid cases 290 Membership and ERP adoption (SMEs) – Notes: a Computed only for a 2 £ 2 table; b 0 cells (0.0 percent) have expected count less than 5. The Chi-square tests expected count is 9.69
  • 16. (Tables XX-XXII). The evaluation of the behavior of companies making use of ERP Factors affecting systems confirms this relationship: 62 percent of them have geographically dispersed ERP system offices, while only 38 percent of ERP users have no branch offices to manage. Although adoption this interesting trend, a correlation between the two variables cannot be fully claimed: the empirical verification shows a Pearson’s R value equal to 0.297 that is not statistically reliable to state that the presence of branch offices directly affects a higher rate of ERP system adoption (Tables XX-XXII). 399 Asymptotic Approximate Approximate Value standard errora Tb significance Interval by interval Pearson’s R 20.169 0.067 2 2.907 0.004c Ordinal by ordinal Spearman correlation 20.169 0.067 2 2.097 0.004c n of valid cases 290 Table X. Membership and ERP Notes: a Not assuming the null hypothesis; b Using the asymptotic standard error assuming the null adoption (SMEs) – hypothesis; c Based on normal approximation symmetric measures Membership and ERP adoption (large companies) Other management system ERP Total Member of group Count 15 25 40 % within membership 37.5 62.5 100.0 % within ERP 78.9 73.5 75.5 Standalone company Count 4 9 13 % within membership 30.8 69.2 100.0 % within ERP 21.1 26.5 24.5 Total Count 19 34 53 Table XI. % within membership 35.8 64.2 100.0 Membership and ERP % within ERP 100.0 100.0 100.0 adoption (large % of total 35.8 64.2 100.0 companies) Asymptotic Exact Exact significance significance significance Value df (two-sided) (two-sided) (one-sided) Pearson Chi-square 0.193b 1 0.660 Continuity correctiona 0.011 1 0.915 Likelihood ratio 0.196 1 0.658 Fisher’s exact test 0.749 0.464 Linear-by-linear association 0.190 1 0.663 Table XII. n of valid cases 53 Membership and ERP adoption (large Notes: a Computed only for a 2 £ 2 table; b 1 cell (25.0 percent) has expected count less than 5. The companies) – Chi-square expected count is 4.66 tests
  • 17. JEIM The empirical verification of H4 on the subsets obtained by separating the companies 18,4 by size does not show any interesting result (Tables XXIII-XXV and Tables XXVI-XXVIII). In particular, the statistical analysis on large companies (Tables XXVI-XXVIII) does not show any meaningful difference between the two groups (chi-square ¼ 0:348 and p-value ¼ 0:409). H4: rejected (weak significance on the whole sample). 400 Asymptotic Approximate Approximate Value standard errora Tb significance Interval by interval Pearson’s R 0.060 0.134 0.432 0.668c Table XIII. Ordinal by ordinal Spearman correlation 0.060 0.134 0.432 0.668c Membership and ERP n of valid cases 53 adoption (large companies) – symmetric Notes: a Not assuming the null hypothesis; b Using the asymptotic standard error assuming the null measures hypothesis; c Based on normal approximation Market area and ERP adoption (whole sample) Market area Other management system ERP Total Local Count 19 2 21 % within market area 90.5 9.5 100.0 % within ERP 7.0 2.2 5.8 Regional Count 25 2 27 % within market area 92.6 7.4 100.0 % within ERP 9.2 2.2 7.4 National Count 83 20 103 % within membership 80.6 19.4 100.0 % within ERP 30.6 21.7 28.4 International Count 144 68 212 % within market area 67.9 32.1 100.0 % within ERP 53.1 73.9 58.4 Total Count 271 92 363 Table XIV. % within market area 74.7 25.3 100.0 Market area and ERP % within ERP 100.0 100.0 100.0 adoption (whole sample) % of total 74.7 25.3 100.0 Value df Asymptotic significance (two-sided) Pearson Chi-square 14.358a 3 0.002 Likelihood ratio 16.081 3 0.001 Table XV. Linear-by-linear association 13.113 1 0.000 Market area and ERP n of valid cases 363 adoption (whole sample) – Chi-square tests Note: a 0 cells (0.0 percent) have expected count less than 5. The minimum expected cost is 5.32
  • 18. Diversification (H5) Factors affecting Despite the support provided by the literature for diversification as a factor affecting ERP system the complexity of information flows, the empirical verification does not show meaningful correlations with the adoption of ERP systems (Tables XXIX-XXXI). Only adoption 27 percent of diversified companies make use of an ERP system. Moreover, 55 percent of companies adopting an ERP system pursue another kind of strategy. The low significance of diversification as a factor affecting ERP adoption is also confirmed by 401 the results of the statistical analysis: the two groups are not significantly different Asymptotic Approximate Approximate Value standard errora Tb significance Interval by interval Pearson’s R 0.190 0.042 3.684 0.000c Ordinal by ordinal Spearman correlation 0.196 0.046 3.796 0.000c n of valid cases 363 Table XVI. Market area and ERP Notes: a Not assuming the null hypothesis; b Using the asymptotic standard error assuming the null adoption (whole sample) hypothesis; c Based on normal approximation – symmetric measures Market area and ERP adoption (SMEs) Market area Other management system ERP Total Local Count 19 19 % within market area 100.0 100.0 % within ERP 7.9 6.4 Regional Count 21 2 23 % within market area 91.3 8.7 100.0 % within ERP 8.7 3.6 7.7 National Count 74 13 87 % within market area 85.1 14.9 100.0 % within ERP 30.6 23.6 29.3 International Count 128 40 168 % within market area 76.2 23.8 100.0 % within ERP 52.9 72.7 56.6 Total Count 242 55 297 % within market area 81.5 18.5 100.0 Table XVII. % within ERP 100.0 100.0 100.0 Market area and ERP % of total 81.5 18.5 100.0 adoption (SMEs) Value df Asymptotic significance (two-sided) a Pearson Chi-square 9.643 3 0.022 Likelihood ratio 13.235 3 0.004 Linear-by-linear association 9.561 1 0.002 Table XVIII. n of valid cases 297 Market area and ERP adoption (SMEs) – Note: a Two cells (25.0 percent) have expected count less than 5. The minimum expected count is 3.52 Chi-square tests
  • 19. JEIM (Chi-square equal to 0.261, with a p-value of 0.610) and the very low value of Pearson’s 18,4 R correlation index (0.027) bears out that no correlation occurs. Accordingly to the methodology, the analysis has been carried out on both SMEs and large companies to verify possible different behaviors in the sub-groups (Tables XXXII-XXXIV and Tables XXXV-XXXVII), but no statistical evidence has been found. H5: rejected. 402 Asymptotic Approximate Approximate Value standard errora Tb significance Interval by interval Pearson’s R 0.180 0.039 3.138 0.002c Ordinal by ordinal Spearman correlation 0.173 0.049 3.019 0.003c Table XIX. n of valid cases 297 Market area and ERP adoption (SMEs) – Notes: a Not assuming the null hypothesis; b Using the asymptotic standard error assuming the null symmetric measures hypothesis; c Based on normal approximation Market area and ERP adoption (large companies) Market area Other management system ERP Total Local Count 1 1 % within market area 100.0 100.0 % within ERP 2.9 1.9 Regional Count 3 3 % within market area 100.0 100.0 % within ERP 15.8 5.7 National Count 4 7 11 % within market area 36.4 63.6 100.0 % within ERP 21.1 20.6 20.8 International Count 12 26 38 % within market area 31.6 68.4 100.0 % within ERP 63.2 76.5 71.7 Table XX. Total Count 19 34 53 Market area and ERP % within market area 35.8 64.2 100.0 adoption (large % within ERP 100.0 100.0 100.0 companies) % of total 35.8 64.2 100.0 Value df Asymptotic significance (two-sided) a Pearson Chi-square 6.230 3 0.101 Table XXI. Likelihood ratio 7.351 3 0.062 Market area and ERP Linear-by-linear association 1.397 1 0.237 adoption (large n of valid cases 53 companies) – Chi-square tests Note: a Five cells (62.5 percent) have expected count less than 5. The minimum expected count is 0.36
  • 20. Functional extension (H6) Factors affecting Even though most of respondents (88 percent) manage all the business activities ERP system internally, the functional extension does not seem to affect the rate of ERP system adoption. For each meaningful value of functional extension (cross-tabulation cells adoption with more than five companies, Tables XXXVIII-XL), the percentage of companies making use of ERP systems is at most equal to the 26.1 percent. In particular, only 25.9 percent of the 321 companies characterized by the maximum level of functional 403 Asymptotic Approximate Approximate Value standard errora Tb significance Interval by interval Pearson’s R 0.164 0.145 1.187 0.241c Ordinal by ordinal Spearman correlation 0.163 0.141 1.180 0.244c Table XXII. n of valid cases 53 Market area and ERP adoption (large Notes: a Not assuming the null hypothesis; b Using the asymptotic standard error assuming the null companies) – symmetric hypothesis; c Based on normal approximation measures Branch offices and ERP adoption (whole sample) Branch offices Other management system ERP Total No Count 193 35 228 % within branch offices 84.6 15.4 100.0 % within ERP 70.7 37.6 62.3 Yes Count 80 58 138 % within branch offices 58.0 42.0 100.0 % within ERP 29.3 62.4 37.7 Total Count 273 93 366 % within branch offices 74.6 25.4 100.0 Table XXIII. % within ERP 100.0 100.0 100.0 Branch offices and ERP % of total 74.6 25.4 100.0 adoption (whole sample) Asymptotic Exact Exact significance significance significance Value df (two-sided) (two-sided) (one-sided) b Pearson Chi-square 32.282 1 0.000 Continuity correctiona 30.890 1 0.000 Likelihood ratio 31.597 1 0.000 Fisher’s exact test 0.000 0.000 Linear-by-linear association 32.194 1 0.000 n of valid cases 366 Table XXIV. a b Branch offices and ERP Notes: Computed only for a 2 £ 2 table; 0 cells (0.0 percent) have expected count less than 5. the adoption (whole sample) maximum expected count is 35.07 – Chi-square tests
  • 21. JEIM extension claim to make use of an ERP system. The unbalanced distribution of the 18,4 sample undoubtedly challenges the reliability of the analysis; nevertheless SMEs do not consider ERP systems as the solution needed to improve their organizational performance yet. The analysis of both correlation and statistical significance with respect to SMEs and large companies does not show any meaningful change in of the main indexes (Tables XLI-XLI and Tables XLIV-XLVI). 404 H6: rejected. Asymptotic Approximate Approximate Value standard errora Tb significance Interval by interval Pearson’s R 0.297 0.052 5.934 0.000c Ordinal by ordinal Spearman correlation 0.297 0.052 5.934 0.000c Table XXV. n of valid cases 366 Branch offices and ERP adoption (whole sample) Notes: a Not assuming the null hypothesis; b Using the asymptotic standard error assuming the null – symmetric measures hypothesis; c Based on normal approximation Branch offices and ERP adoption (SMEs) Branch offices Other management system ERP Total No Count 181 29 210 % within branch offices 86.2 13.8 100.0 % within ERP 74.2 51.8 70.0 Yes Count 63 27 90 % within branch offices 70.0 30.0 100.0 % within ERP 25.8 48.2 30.0 Total Count 244 56 300 Table XXVI. % within branch offices 81.3 18.7 100.0 Branch offices and ERP % within ERP 100.0 100.0 100.0 adoption (SMEs) % of total 81.3 18.7 100.0 Asymptotic Exact Exact significance significance significance Value df (two-sided) (two-sided) (one-sided) Pearson Chi-square 10.877b 1 0.001 Continuity correctiona 9.837 1 0.002 Likelihood ratio 10.230 1 0.001 Fisher’s exact test 0.002 0.001 Linear-by-linear association 10.841 1 0.001 Table XXVII. n of valid cases 300 Branch offices and ERP adoption (SMEs) – Notes: a Computed only for a 2 £ 2 table; b 0 cells (0.0 percent) have expected count less than 5. the Chi-square tests maximum expected count is 16.80
  • 22. Extent of organizational change (H7) Factors affecting Unlike previous factors (from H2-H6), the results of the data analysis on H7 ERP system (Table XLVII-XLIX) highlights that the extent of organizational change the company wishes to achieve is likely to affect the decision of whether adopting an ERP system or not. adoption Even though the Pearson’s R value (0.306) shown by the whole sample is just acceptable, other considerations support this statement. In particular (Tables L-LII), companies adopting other management systems reveal a lower mean for the organizational change 405 factor (1.2) in comparison with those companies which have adopted an ERP system (2.3). Asymptotic Approximate Approximate Value standard errora Tb significance Interval by interval Pearson’s R 0.190 0.062 3.348 0.001c Ordinal by ordinal Spearman correlation 0.190 0.062 3.348 0.001c n of valid cases 300 Table XXVIII. a b Branch offices and ERP Notes: Not assuming the null hypothesis; Using the asymptotic standard error assuming the null adoption (SMEs) – hypothesis; c Based on normal approximation symmetric measures Presence of branch offices and ERP adoption (large companies) Branch offices Other management system ERP Total No Count 4 5 9 % within branch offices 44.4 55.6 100.0 % within ERP 21.1 14.7 17.0 Yes Count 15 29 44 % within branch offices 34.1 65.9 100.0 % within ERP 78.9 85.3 83.0 Total Count 19 34 53 Table XXIX. % within branch offices 35.8 64.2 100.0 Branch offices and ERP % within ERP 100.0 100.0 100.0 adoption (large % of total 35.8 64.2 100.0 companies) Asymptotic Exact Exact significance significance significance Value df (two-sided) (two-sided) (one-sided) Pearson Chi-square 0.348b 1 0.555 Continuity correctiona 0.044 1 0.835 Likelihood ratio 0.340 1 0.560 Fisher’s exact test 0.706 0.409 Linear-by-linear association 0.342 1 0.559 Table XXX. n of valid cases 53 Branch offices and ERP adoption (large Notes: a Computed only for a 2 £ 2 table; b One cell (25.0 percent) has expected count less than 5. The companies) – Chi-square maximum expected count is 3.23 tests
  • 23. JEIM A detailed analysis of the cross-tabulation between organizational change and ERP adoption has pointed out some interesting remarks (see Figure 5): 18,4 . Companies seem to privilege the ERP solution when their need to integrate, reengineer or redesign business processes becomes a priority (respectively the 17.4 percent, 25 percent and the 16.3 percent). Only 11 percent of companies which make use of ERP systems exploit this solution just for local automation 406 purposes, while the number of companies considering a more advanced solution (business network redesign levels) is quite negligible (8.7 percent). Asymptotic Approximate Approximate Value standard errora Tb significance Interval by interval Pearson’s R 0.081 0.141 0.581 0.564c Table XXXI. Ordinal by ordinal Spearman correlation 0.081 0.141 0.581 0.564c Branch offices and ERP n of valid cases 53 adoption (large companies) – symmetric Notes: a Not assuming the null hypothesis; b Using the asymptotic standard error assuming the null measures hypothesis; c Based on normal approximation Diversification and ERP adoption Other management system ERP Total Other strategy Count 158 51 209 % within diversification 75.6 24.4 100.0 % within ERP 57.9 54.8 57.1 Diversification Count 115 42 157 % within diversification 73.2 26.8 100.0 % within ERP 42.1 45.2 42.9 Total Count 273 93 366 Table XXXII. % within diversification 74.6 25.4 100.0 Diversification and ERP % within ERP 100.0 100.0 100.0 adoption (whole sample) % of total 74.6 25.4 100.0 Asymptotic Exact Exact significance significance significance Value df (two-sided) (two-sided) (one-sided) Pearson chi-square 0.261b 1 0.609 Continuity correctiona 0.152 1 0.697 Likelihood ratio 0.260 1 0.610 Fisher’s exact test 0.629 0.348 Linear-by-linear association 0.260 1 0.610 Table XXXIII. n of valid cases 0.366 Diversification and ERP adoption (whole sample) Notes: a Computed only for a 2 £ 2 table; b 0 cells (0.0 percent) have expected count less than 5. The – Chi-square tests maximum expected count is 39.89
  • 24. . A quite unexpected outcome of the analysis is the relevant percentage of Factors affecting companies (21.7 percent) declaring that no organizational change occurred, or ERP system has been foreseen, as a consequence of ERP adoption. This result is even more surprising in the light of the support given by IS literature to the thesis that ERP adoption adoption both requires and provokes an unavoidable organizational reshuffling of roles and tasks (Dewett and Jones, 2001). . The comparative analysis of means and distribution for the organizational 407 change factor (Table XLVII-XLIX) also shows that the underestimation of the Asymptotic Approximate Approximate Value standard errora Tb significance Interval by interval Pearson’s R 0.027 0.052 0.510 0.610c Ordinal by ordinal Spearman correlation 0.027 0.052 0.510 0.610c n of valid cases 366 Table XXXIV. a b Diversification and ERP Notes: Not assuming the null hypothesis; Using the asymtopic standard error assuming the null adoption (whole sample) hypothesis; c Based on normal approximation – symmetric measures Diversification and ERP adoption (SMEs) Other management system ERP Total Other strategy Count 142 32 174 % within diversification 81.6 18.4 100.0 % within ERP 58.2 57.1 58.0 Diversification Count 102 24 126 % within diversification 81.0 19.0 100.0 % within ERP 41.8 42.9 42.0 Total Count 244 56 300 Table XXXV. % within diversification 81.3 18.7 100.0 Diversification and ERP % within ERP 100.0 100.0 100.0 adoption (SMEs) % of total 81.3 18.7 100.0 Asymptotic Exact Exact significance significance significance Value df (two-sided) (two-sided) (one-sided) b Pearson Chi-square 0.021 1 0.885 Continuity correctiona 0.000 1 1.000 Likelihood ratio 0.021 1 0.885 Fisher’s exact test 0.882 0.500 Linear-by-linear association 0.021 1 0.886 n of valid cases 300 Table XXXVI. Diversification and ERP Notes: a Computed only for a 2 £ 2 table; b 0 cells (0.0 percent) have expected count less than 5. The adoption (SMEs) – maximum expected count is 23.52 Chi-square tests
  • 25. JEIM organizational change factor becomes even more relevant among those 18,4 companies that make use of another management system (50.4 percent). The previous analysis has been performed also separating SMEs and large companies in order to highlight possible differences in the behavior of the two sub-groups. Organizational change shows a stronger correlation with ERP adoption in the case of 408 large companies (Pearson’s R ¼ 0:386, Tables LIII-LV) with respect to SMEs (Pearson’s R ¼ 0:218, Table LVI-LVIII). To explore the reasons underlying the different correlation shown by the two sub-groups, the previous outcome has been Asymptotic Approximate Approximate Value standard errora Tb significance Interval by interval Pearson’s R 0.008 0.058 0.144 0.886c Ordinal by ordinal Spearman correlation 0.008 0.058 0.144 0.886c Table XXXVII. n of valid cases 300 Diversification and ERP adoption (SMEs) – Notes: a Not assuming the null hypothesis; b Using the asymptotic standard error assuming the null symmetric measures hypothesis; c Based on normal approximation Diversification and ERP adoption (large companies) Other management system ERP Total Other strategy Count 12 17 29 % within diversification 41.4 58.6 100.0 % within ERP 63.2 50.0 54.7 Diversification Count 7 17 24 % within diversification 29.2 70.8 100.0 % within ERP 36.8 50.0 45.3 Table XXXVIII. Total Count 19 34 53 Diversification and ERP % within diversification 35.8 64.2 100.0 adoption (large % within ERP 100.0 100.0 100.0 companies) % of total 35.8 64.2 100.0 Asymptotic Exact Exact significance significance significance Value df (two-sided) (two-sided) (one-sided) Pearson Chi-square 0.852b 1 0.356 Continuity correctiona 0.403 1 0.525 Likelihood ratio 0.859 1 0.354 Fisher’s exact test 0.401 0.264 Table XXXIX. Linear-by-linear association 0.836 1 0.361 Diversification and ERP n of valid cases 53 adoption (large companies) – Chi-square Notes: a Computed only for a 2 £ 2 table; b 0 cells (0.0 percent) have expected count less than 5. The tests maximum expected count is 8.60