The influence of external factorson routine ERP usage

Simona SternadFaculty of Economics and Business, University of Maribor, Maribor, Slovenia

Miro GradisarFaculty of Economics, University of Ljubljana, Ljubljana, Slovenia, and

Samo BobekFaculty of Economics and Business, University of Maribor, Maribor, Slovenia

Abstract

Purpose Enterprise resource planning (ERP) systems have been implemented in mostorganizations for a few years. ERP solutions go through three phases of lifecycle: selection,implementation and operation phase; the operation phase consists of the stabilization stage and theroutine stage. To improve the efficiency and effectiveness of ERP system use in the operation phase,organizations need to research the factors that have impact on users satisfaction. The literature showsthat few published studies have examined users adoption of ERP systems through a technologicalacceptance model (TAM) or examined external factors that have influence the intention to use an ERPsystem, or ERP use in the stabilization stage. The purpose of this paper is to expose and researchexternal factors which have influence on ERP users in the operation phase of ERP lifecycle and toinvestigate the impact of those factors on ERP system use.

Design/methodology/approach The TAM proposed by Davis has been the most widely-usedmodel for researching user acceptance and usage of information technology/information systems.Despite the existence of several additions to TAM connected with ERP use, the authors aim to makefurther contribution in the area of external factors. Within this context the present research is focusedon the mature use of ERP system (more than one year of ERP use in an organization). A limitednumber of external factors mentioned in already published papers connected with TAM regardingERP use has also been extended. The authors have researched the effect of external factors through thesecond-order factors on the original TAM. The model has been empirically tested using the datacollected from a survey of 161 ERP users from a national telecom company, which has been using anERP system since 1999. The model has been analysed using PLS approach.

Findings The study shows that extended external factors observed through the second-orderfactors have important influence on ERP usefulness and ERP ease of use; they also have a stronginfluence on the attitude toward using ERP system by ERP users in the routine (maturity) stage.

Originality/value The paper researches the factors which have an impact on ERP solution use inthe routine (mature) stage of ERP lifecycle. The paper adds to the literature, in that few previousstudies have examined the users adoption of ERP systems through the TAM or examined externalfactors that have influence on the intention to use an ERP system or ERP use in the stabilization stage.

Keywords Slovenia, Manufacturing resource planning, Resource management,Enterprise resource planning, ERP, Technological acceptance model, TAM, Partial least squares, PLS,Second-order factors

Paper type Research paper

1. IntroductionEnterprise resource planning (ERP) systems are integrated, all-encompassing, complexmega packages designed to support key functional areas of organizations (Adam andSammon, 2004). They integrate information from various sources inside and outside

The current issue and full text archive of this journal is available at

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Received 1 March 2011Revised 7 June 2011

Accepted 10 June 2011

Industrial Management & DataSystems

Vol. 111 No. 9, 2011pp. 1511-1530

q Emerald Group Publishing Limited0263-5577

DOI 10.1108/02635571111182818

the organization and can provide real-time data to employees and organizationalpartners (Motiwalla and Thompson, 2009). ERP solutions have been adopted by manylarge organizations (Momoh et al., 2010) and are a basic tool for enterprises seeking tomerge supply chain management systems and integrate inter-company andinternational collaborative operations across entire industry processes (Yu, 2005).ERP systems have been shown to reduce the time to complete business processes andhelp organizations share information (Olhager and Selldin, 2003; Lee et al., 2010),facilitating an integrated and coordinated work flow among supply chain stakeholders.

As with other information systems (IS), ERP system adoption typically follows threelifecycle phases: selection, implementation and operation, the latter of which can bedivided into a stabilization stage and a routine stage. Most literature on ERP solutions isfocused on either evaluating the appropriateness of the ERP system vis-a`-vis software,vendors, or consultants, or identifying critical successful factors (CSFs) affecting ERPselection and implementation (Yu, 2005), but less effort is given to identifyingpotential post-implementation impact (Gattiker and Goodhue, 2005). Several CSFs havebeen identified in the selection and implementation phases, including: top managementsupport and involvement; clear goals, objectives, scope and planning; project teamcompetence and organization; user training and education; business processreengineering; change management; effective communication; project management;user involvement; data analysis and conversion; consultants; project sponsor;architecture choice; and minimal customization (Welti, 1999; Al-Sehali, 2000; Parr andShanks, 2000; Skok and Legge, 2002; Zhang et al., 2002; Zhang et al., 2002; Akkermansand Helden, 2002; Stratman, 2002; Gattiker and CFPIM, 2002; Umble et al., 2002;Mabert et al., 2003; Al-Mashari et al., 2003; Bradford and Florin, 2003; Somers andNelson, 2003; Gargeya and Brady, 2005; Ngai et al., 2007; Finney and Corbett, 2007;Wang et al., 2007; Bobek and Sternad, 2010). CSFs are not equally important in all phasesof the ERP lifecycle, however (Bobek and Sternad, 2010); some influence operationaleffectiveness as well as implementation (Gattiker and Goodhue, 2005).

Much of the success of ERP implementation resides in the operationalphase (Bradford, 2008; Motiwalla and Thompson, 2009). In the stabilization stage,ERP systems go through a post-implementation breaking-in period in whichperformance may not be typical of the long-term effects an organization mightexperience (Gattiker and Goodhue, 2005). In the routine stage, ERP systems might beimplemented successfully from a technical perspective, but success depends on ERPusers attitudes toward and actual use of the system (Boudreau, 2002; Kwahk and Lee,2008). ERP systems benefit organizations only to the extent that users accept and utilizethem frequently and extensively. To improve the efficiency and effectiveness of ERPsystems in the operation phase, organizations need to research the factors that impactuser satisfaction. In this area, the technological acceptance model (TAM) is widely usedfor explaining behavioural intent and usage; it can enhance understanding influencesthat increase the efficiency and effectiveness of ERP system use (Shih and Huang, 2009).Several researchers have applied TAM to examine ERP system use (Calisir et al., 2009;Shih and Huang, 2009; Sun et al., 2009; Youngberg et al., 2009; Lee et al., 2010), butfew scholars have examined multiple external factors that influence intent to use an ERPsystem or ERP system usage in the stabilization stage. Although a small number ofexternal factors fail to illuminate user opinions about specific systems

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(Agarwal and Prasad, 1999; Lu et al., 2003; Sun et al., 2009), most studies address only asmall number of external factors.

The goal of the present study is to explore a large number of external factors whichpotentially influence attitudes and behaviour regarding ERP use in the operationalphase of the ERP lifecycle. Because of the large sample size required to apply TAM tomultiple individual variables, we combine external factors into three groups: personalcharacteristics and information literacy (PCIL); system and technologicalcharacteristics (STC), and; organizational-process characteristics (OPC) (Figure 1).To test these factors, we collected survey data from a national telecom company wherean ERP system has been in operation for several years, and we employed partial leastsquares (PLS) to analyse the data.

2. TAM and ERP systemsSeveral theories have been used to explain the acceptance and use of informationtechnology (IT), including, reasoned action (TRA; Fishbein and Ajzen, 1975), plannedbehaviour (TPB; Ajzen, 1991), and the TAM (Davis et al., 1989). Compared to othertheories, TAM is believed to be highly parsimonious, predicative and robust (Venkateshand Davis, 2000; Lu et al., 2003; Liu and Ma, 2006), thus, it is commonly employed byIS/IT researchers (Davis, 1989; Davis et al., 1989; Amoako-Gyampah and Salam, 2004;Lee et al., 2010). TAM posits that two beliefs2 perceived usefulness (PU) and perceivedease of use (PEOU) 2 are of primary relevance for acceptance behaviour (Davis et al.,1989). PU is defined as the degree to which a person believes that using a particularsystem would enhance his or her job performance (Davis, 1989, p. 320). PEOU refers tothe degree to which a person believes that using a particular system would be free ofeffort (Davis, 1989, p. 320). The two central hypotheses in TAM state that PU and PEOUpositively influence an individuals attitude about a technology which in turn influenceshis or her intent and actual use of the technology. TAM also predicts that PEOUpositively influences PU, as Davis et al. (1989, p. 987) put it: effort saved due to theimproved PEOU may be redeployed, enabling a person to accomplish more work for thesame effort. The key purpose of TAM is to provide a basis for measuring the impact ofexternal factors on internal beliefs, attitudes and intentions (Davis et al., 1989). Theoriginal TAM is well established and tested and a variety of extensions regardingexternal factors have been developed.

Several studies (Umble et al., 2002; Nah et al., 2004) suggest that ERP failure is relatedto user attitudes toward ERP systems. Few studies, however, have investigated ERP

Figure 1.Research model

Attitude toERP system

ERP Usefulness

ERP Ease of Use

OrganizationalProcess

Characteristics

System andTechnologicalCharacteristics

PersonalCharacteristics andInformation Literacy TAM

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user acceptance and usage utilizing TAM, and most of these investigate a small numberof external factors in the operational phase of the ERP lifecycle (Table I). Because ERPsystems are complex and complex systems decrease usefulness and ease of use(Momoh et al., 2010), a better understanding of the factors influencing user acceptance ofERP systems is necessary to facilitate successful ERP system usage (Nah et al., 2004).

3. External factors of TAM related to ERP systemsSeveral researchers have examined the antecedents of PU and PEOU in IS and IT. Asnoted by Venkatesh and Davis (2000), a better understanding of these factors wouldenable more effective organizational interventions that lead to increased acceptance anduse of systems. Venkatesh and Davis (2000) proposed an extension of TAM TAM2 by identifying six determinants of PU: subjective norm, image, job relevance, outputquality, results demonstrability and PEOU. Venkatesh (2000) developed a model of thedeterminants of PEOU, which include: computer self-efficacy, computer anxiety,computer playfulness and perceptions of external control (or facilitating conditions).Venkatesh and Bala (2008) combined TAM2 (Venkatesh and Davis, 2000) and the modelof the determinants of PEOU (Venkatesh, 2000) and developed an integrated model oftechnology acceptance, which they labelled TAM3.

Even though TAM can be applied to a variety of technologies, the constructs of TAMneed to be extended by customizing factors for specific IS (Calisir et al., 2009). Schwarz(2003) grouped the antecedents of PEOU and PU into three sets: individual variables(e.g. computer experience, self-efficacy, prior experiences), organizational influences(e.g. management and external support, perceived resources) and technologycharacteristics (e.g. accessibility of the medium and interface type). Additionally, fourexternal factors appear to influence individual variables: computer experience,computer self-efficiency, technological innovativeness and computer anxiety (Table II).We name this group of individual factors PCIL.

Based on prior research regarding ERP systems we placed external factors into twogroups: one that represents STC and the one that represents OPC. External factors in theSTC group include: data quality, ERP system functionality, ERP system performance,and user manual helpfulness. Included in the OPT group are: social influence, fit withbusiness processes, training and education in the ERP system, ERP support and ERPcommunications. In these two groups, we are trying to capture a large number of CSFwhich influence ERP users during the operational phase. Groups of external factorsmentioned by authors which impact IS use are shown in Table II.

4. Theoretical foundation for hypotheses developmentTAM has been tested primarily on technologies that are relatively simple andvoluntary (e.g. e-mail, word processors). Several researchers (Nah et al., 2004) haverecommended that TAM be revised to address user attitude, intent and behaviourwhen applied to complex IT in organizational settings where usage is generallyconsidered mandatory (Nah et al., 2004). Because ERP users impact others, they do nothave the choice to avoid the system, regardless of their attitudes about ERP systems.A conceptual model extending TAM in these directions is shown in Figure 1.

The grey area within the dotted line denotes the original TAM. Because ourresearch is focused on groups of external factors which influence routine ERP usage,there is no need to examine intent (Pijpers and Montfort, 2006; Simon and Paper, 2007).

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Reference Focus Lifecycle phase

Nah et al. (2004) The impact of four cognitive constructors (PU,PEOU, perceived compatibility, and perceived fit)on attitudes toward using ERP systems andsymbolic adoption

Post-implementation(stabilization stage)

Amoako-Gyampah andSalam (2004)

The impact of one belief construct (shared beliefsin the benefits of a technology) and twotechnology success factors (training andcommunications) on PU and PEOU in one globalorganization

Implementation

Shivers-Blackwell andCharles (2006)

Student readiness for change (through gender,computer self-efficacy, and perceived benefits ofERP) on behavioural intention regarding the ERPimplementation

Implementation

Bradley and Lee (2007) The relationship between training satisfactionand PEOU, PU, effectiveness and efficiency inimplementing an ERP system at a mid-sizeduniversity

Implementation

Hsieh and Wang (2007) The impact of PU and PEOU on extended use Post-implementation(routine stage)

Kwahk and Lee (2008) Readiness for change (enhanced by two factors:organizational commitment and perceivedpersonal competence) and its effect on theperceived technological value of an ERP systemleading to its use

Post-implementation(stabilization stage)

Bueno and Salmeron(2008)

A research model based on TAM for testing theinfluence of selected CSF (top managementsupport, communication, cooperation, training,and technological complexity) on ERPimplementation

Implementation

Uzoka et al. (2008) The application of TAM to the selection and use ofERP systems in organizations using: impact ofsystem quality, information quality, servicequality and support quality as key determinantsof cognitive response

Selection

Sun et al. (2009) Impacts on IT usage such as the role of ERPsperceived work compatibility with user intention,usage and performance in work settings

Post-implementation(routine stage)

Shih and Huang (2009) Behavioural intention and actual use as impactedby top management support, computer self-efficacy and computer anxiety

Post-implementation(routine stage)

Calisir et al. (2009) Factors (subjective norms, compatibility, gender,experience, and education level) that affectbehavioural intention to use an ERP system basedon potential ERP users at one manufacturingorganization

Implementation

Youngberg et al. (2009) The impact of PEOU, results demonstrability, andsubjective norms on PU and their impact on usagebehaviour

Post-implementation(stabilization stage)

Lee et al. (2010) Factor organizational support (formal andinformal) on original TAM factors

Post-implementation

Table I.ERP literature review

regarding TAM

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Externalfactors Authors Description

PCILComputerexperience

Davis et al. (1989), Venkatesh et al. (2003),Thompson et al. (2006), Venkatesh and Bala(2008), Calisir et al. (2009)

Experience with computer has been found tobe an important factor for the acceptance of atechnology (Calisir et al., 2009)

Computer self-efficiency

Venkatesh and Davis (2000), Venkatesh et al.(2003), Thompson et al. (2006), Shivers-Blackwell and Charles (2006), Venkatesh andBala (2008), Shih and Huang (2009)

Computer self-efficiency is the degree towhich an individual believes that he/she hasthe ability to perform a specific task/jobusing the computer (Venkatesh and Bala,2008; Shih and Huang, 2009)

Technologicalinnovativeness

Agarwal and Prasad (1999), Rogers (2003),Yi et al. (2006), Thompson et al. (2006)

Technological innovativeness represents thedegree to which an individual is willing to tryout a new IT (Agarwal and Prasad, 1999)

Computeranxiety

Venkatesh et al. (2003), Liu and Ma (2006),Venkatesh and Bala (2008), Shih and Huang(2009)

Computer anxiety represents the degree of anindividuals apprehension, or even fear, whenshe/he is faced with the possibility of usingcomputers (Venkatesh et al., 2003)

STCERP dataquality

Venkatesh (1998), Venkatesh and Davis(2000), Gattiker and Goodhue (2005),Kositanurit et al. (2006), Insiti (2007)

Without accurate and relevant data, anorganization is severely constrained in thecoordination and task efficiency benefits itcan achieve from its ERP system (Gattikerand Goodhue, 2005)

ERP systemfunctionality

Musaji (2002), Somers et al. (2003), Lu et al.(2003), Kositanurit et al. (2006), Insiti (2007)

System functions are used to measure therapid response, stability, easy usage andflexibility of the system (Lu et al., 2003)

ERP systemperformance

Boudreau (2002), Musaji (2002), Venkateshet al. (2003), Somers et al. (2003), Kositanuritet al. (2006), Liu and Ma (2006), Insiti (2007)

ERP system performance refers to the degreeto which person believes that a system isreliable and responsive during a normalcourse of operations (Liu and Ma, 2006)

User manualhelpfulness

Kelley (2001), Boudreau (2002), Musaji (2002),Kositanurit et al. (2006), Bradford (2008)

The degree to which an individual viewsinadequate user manuals as the reason forunsuccessful ERP performance (Kelley, 2001)

OPCSocialinfluence

Venkatesh (1998), Venkatesh et al. (2003),Thompson et al. (2006), Bradford (2008),Calisir et al. (2009)

Social influence joins two factors: subjectivenorms and social factors. Subjective normsare defined as a persons perception thatmost people who are important to him/herthink that he/she should or should notperform the behaviour in question(Venkatesh, 1998). Social factors are anindividuals internalization of the referencegroups subjective culture, and specificinterpersonal agreements that the individualhas made with others in specific socialsituations (Venkatesh et al., 2003)

Fit withbusinessprocesses

Amoako-Gyampah and Salam (2004), Nahet al. (2004), Bradley and Lee (2007), Bradford(2008), Bobek and Sternad (2010)

Fit with business processes from an end-users perspective is the degree to which theERP system perceived by a user meets his/her organizations needs (Nah et al., 2004)

ERP trainingand education

Amonko-Gyampah and Salam (2004),Bradley and Lee (2007), Bueno and Salmeron(2008), Bobek and Sternad (2010)

ERP training and education is defined as thedegree to which a user thinks that he/she hashad enough formal and informal trainingafter ERP implementation

(continued )

Table II.External factorsmentioned by authors

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Researchers have found support for TAM in ERP settings in the routine stage (Hsiehand Wang, 2007; Shih and Huang, 2009; Sun et al., 2009; Lee et al., 2010) but they do notall support the hypothesis that PEOU influences PU. According to Davis (1989) andDavis et al. (1989), PEOU influences PU, and PU and PEOU influence attitudes aboutusing IS. TAM research suggests strong empirical support of PEOU influencing PU(Davis, 1989; Heijden, 2001). Specifically, with ERP systems, some research supportsthis relationship (Amoako-Gyampah and Salam, 2004; Hsieh and Wang, 2007; Buenoand Salmeron, 2008; Calisir et al., 2009; Lee et al., 2010) while other studies do not(Shivers-Blackwell and Charles, 2006; Shih and Huang, 2009). Because we surveyedroutine ERP users, we cannot measure PU and PEOU, but only ERP usefulness andERP ease of use. Based on this literature, our hypotheses are:

H1. ERP ease of use positively and directly affects ERP usefulness.

H2. ERP ease of use positively and directly affects attitude toward the ERPsystem.

H3. ERP usefulness positively and directly affects attitude toward the ERPsystem.

One problem with TAM research is that most researchers investigate a smallnumber of external factors assumed to influence user acceptance and usage. In the caseof ERP systems, several external factors may influence user acceptance. Thus, theconceptualisation of multiple, higher-order factors (in our case, second-order factors)must be investigated to understand user behaviour. Ease of use has been theorized to beclosely associated with individual self-efficacy and procedural knowledge, requiringhands-on experience and skills (Davis et al., 1989; Venkatesh, 2000; Venkatesh and Bala,2008). On this basis, we can propose that a generic factor named PCIL be constituted byfour components experience with computer, computer self-efficiency, technologicalinnovativeness and computer anxiety and be related to ERP ease of use. Venkatesh(2000) adds that the determinants of ease of use are primarily individual differencevariables and general beliefs about computers and computer use. Venkatesh and Bala(2008) suggest that system-related characteristics also will influence PEOU. Combiningthese perspectives, we believe that the external factors of data quality, ERP systemfunctionality, ERP system performance and user manual helpfulness influence ERP easeof use via a composite variable named STC. Stated as hypotheses:

Externalfactors Authors Description

ERP support Boudreau (2002), Lee et al. (2010) We define ERP support as the degree towhich an individual views adequate ERPsupport as the reason for ones successfulERP usage

ERPcommunication

Kelley (2001), Musaji (2002), Boudreau (2002),Amoako-Gyampah and Salam (2004), Buenoand Salmeron (2008), Bobek and Sternad(2010)

ERP communication problems refer to thelack of communication regarding the ERPapplications and their modifications (Kelley,2001) Table II.

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H4. ERP ease of use is affected by PCIL.

H5. ERP ease of use is affected by STC.

PU is impacted by social influence processes (Venkatesh and Davis, 2000). Usefulness isan instrumental belief that is conceptually similar to extrinsic motivation and consists ofbeliefs about the benefits of using IS or IT. Venkatesh and Bala (2008) suggest thatinformation-related system characteristics influence PU. OPC capture external factorssuch as social influence, fit with business processes, training and education on ERPsystems, ERP support and ERP communication, which impact user beliefs regarding thebenefits of using a system. The sixth hypothesis, therefore, is:

H6. ERP usefulness is affected by OPC.

5. Method5.1 Questionnaire designThe components of the proposed model are ERP usefulness, ERP ease of use, and attitudetoward ERP use, each influenced by various external factors. The external factors aredistributed among three second-order constructs which are: information literacy andpersonal characteristics (ILPC), STC and OPC. Second-order factors are composed byspecifying a latent variable which represents all the manifest variables of the underlyinglower-order factors. ILPC includes: computer experience, computer self-efficiency,technological innovativeness and computer anxiety. STC is composed of: ERP dataquality, ERP system functionality, ERP system performance and user manual helpfulness.OPC includes: social influence, fit with business processes, ERP training and education,ERP support and ERP communication. Our model includes 16 first-order factors and threesecond-order factors. All factor items were measured on a seven-point Likert scale, rangingfrom strongly disagree to strongly agree, taken from relevant prior research andadapted to ERP usage (Table IV). Demographic information was collected as well.

Following Straub (1989), the questionnaire was developed in multiple stages. Basedon an extensive literature review, an initial instrument was developed. The draftedinstrument was evaluated by ERP system experts and modified according to theirsuggestions. The original questionnaire was designed in English and translated into thelocal language and then reverse translated to insure wording accuracy. A high degree ofcorrespondence existed between the original English questionnaire and itsreverse-translated version. Although survey items had been validated by pastresearch, the adopted instrument was examined for content, construct validity andreliability within the ERP context. As Amoako-Gyampah and Salam (2004) point out,instrument validation or re-validation is necessary because the validity of theinstrument may not be persistent across different technologies and user groups.The instrument was pilot tested with a group of 30 ERP users in a manufacturingorganization. The instruments reliability was evaluated, the Cronbachs a valuesranged from 0.58 to 0.91, indicating a satisfactory level of reliability exceeding a 0.5 value(Hinton et al., 2004). Item wording feedback from the pilot was used to make finalmodifications. The final survey items are reproduced in Table IV.

5.2 SamplingWe distributed our electronic questionnaire within a large national telecom companywhich has utilized SAP solutions since 1999. The company has approximately 1,100 SAP

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licences but only about 500 ERP users use SAP on a daily basis. We distributed oursurvey to these users. A total of 176 surveys were returned and 161 were valid foranalysis (valid return rate 32.2 per cent). Of the respondents, 57.1 per cent were maleand 42.9 per cent were female; most (79.5 per cent) had at least a high school education;56.9 per cent identified themselves as non-management employees (professional andtechnical workers), 35.8 per cent were lower-level managers (e.g. manager of a group ororganization unit) and 7.3 per cent identified as mid-level managers (e.g. CIO). Theaverage total working years was 19.9 years (min. 1, max. 43), and the averagenumber of working years in each workplace was 7.5 years. The average respondent hadused SAP for 6.5 years (min. 1, max. 18).

Respondents estimated their intensity of ERP usage via the following statement:I would rate the intensity of my job-related ERP system use to be [. . .] on a seven-pointLikert scale, ranging from not important to very important. Most respondentsselected 4, or average intensity. Further, respondents estimated their frequency ofERP use via three statements proposed by Schwarz (2003), also on seven-point Likertscale. Responses to these questions are presented in Table III. For all three statements,an average value is around 3.4, which represents a moderate degree of use.

6. Analysis and resultsCovariance-based structural equation modelling (SEM), component-based SEM or a PLSapproach can be employed to estimate the parameters of a hierarchical model. Accordingto Chin (1998), PLS offers several strengths: it is suitable for situations with little theorydevelopment; it places minimal demands on measurement scales; it avoids factorindeterminacy problems and inadmissible solutions; it avoids identification problems ofrecursive models; it makes no assumptions about the data; it requires no specificdistributions for measured variables; it assumes the errors are uncorrelated; it workswell with small samples; and it is better suited for analysing complex relationships andmodels. Models, which include the second-order factors, consist of higher-order factorsthat are modelled as causally impacting a number of the first-order factors (i.e. standardfactors with measured indicators; Chin, 1998). Therefore, these second-order factors arenot directly connected to any measurement items. PLS allows the conceptualisation ofhigher-order factors through the repeated use of manifest variables (Tenenhaus et al.,2005). A higher-order factor can thus be created by specifying a latent variable whichrepresents all the manifest variables of the underlying lower-order factors. We employeda PLS approach because of the relatively small number of samples of valid data and ourdesire to analyse second-order factors. Data were analysed in two stages involving a PLStechnique using SmartPLS 2.0 M3 (Ringle and Will, 2005). All measurement scaleswere examined for their psychometric properties prior to testing hypotheses.

In a typical one-month period, what is the likelihood of you [. . .] Average Mediana

[. . .] using most of features of the ERP solution? 3.45 4[. . .] using more features than other users of the ERP solutions? 3.44 4[. . .] using more obscure aspects of the ERP solutions? 3.34 3

Note: aScale 1-7, not important to very importantTable III.

Degree of use

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6.1 Measurement modelAlthough all scale items were derived from previously developed and validatedmeasures and the instruments reliability was evaluated through pilot testing, each scalewas assessed for reliability, convergent validity, and discriminant validity. For externalfactors, a second-order factor procedure was employed. The method of repeatedindicators known as the hierarchical component model suggested by Wold (1982) wasthe easiest to implement. The second-order factor is directly measured by observedvariables for all the first-order factors that are measured with reflective indicators. Whilethis approach repeats the number of manifest variables used, the model can be estimatedby the standard PLS algorithm (Henseler et al., 2009). We excluded external factors fromfurther analysis if they did not contribute significantly to the measurement model. Thefactors which were excluded were: computer self-efficacy and computer experience(PCIL group), ERP functionality (STC group), and ERP support, ERP communicationand ERP training and education (OPC group).

We examined two measures of reliability: Cronbachs a and composite reliability(CR). As shown in Table IV each of our ten sub-scales had Cronbachsas exceeding 0.70,and CR exceeding 0.8, indicating adequate reliability. Fornell and Larckers (1981)assessment criteria were used to test for convergent validity: specifically, all item factorloadings should be significant and exceed 0.7 and the average variance extracted (AVE)for each construct should exceed 0.5. Table IV lists item factor loadings, all of which weresignificant at p , 0.01 and exceeded the recommended minimum level of 0.70. All valuesof AVE exceeded 0.5. Thus, the measurement scales demonstrate convergent validity.Table VI shows the factor loadings and CR and AVE of the second-order modelmeasures.

Discriminant validity between constructs were assessed following Fornell andLarckers (1981) recommendation that the square root of AVE for each construct shouldexceed the bivariate correlations between that construct and all other constructs.The inter-construct correlation matrix (Table V) shows that the principal diagonalelements (square root AVE) exceed non-diagonal elements in the same row or columns(bivariate correlations), demonstrating that the discriminant validity of all scales isadequate. Overall, the measurement results are satisfactory and suggest that it isappropriate to proceed with the evaluation of the structural model.

6.2 Structural model and hypotheses testingThe next step in the analysis is to examine the path significance and magnitude of eachof our hypothesized effects and the overall explanatory power of the proposed model.The hypothesis testing results utilize bootstrapping (with 500 subsamples) to test thestatistical significance of each path coefficient using t-tests, as recommended by Chin(1998). Results of this analysis are shown in Figure 2.

As given in Table VI, the loadings of the first-order factors on the second-orderfactors exceed 0.7 and the second-order factors have a significant positive impact onERP usefulness and on ERP ease of use (Figure 2).

The structural model demonstrates predictive power via the variance explained(R 2) of endogenous constructs. Specifically, the model resulted in 0.46 for ERPusefulness, 0.31 for ERP ease of use, and 0.60 for attitude toward the ERP system. AllR 2 results can be described as moderate according to Chin (1998). The findings showthat our model explains a large portion of the variance in the endogenous variables,

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Construct (source)ItemMean

ItemSD Load. a CR AVE

Technological innovativeness (Yi et al., 2006; Thompson et al., 2006)If I hear about a new IT, I will look for ways to experimentwith it

5.43 1.44 0.88 0.88 0.93 0.81

Among my peers I am usually the first to try out new IT 4.42 1.75 0.88I like to experiment with new IT 5.09 1.64 0.93Computer anxiety (Venkatesh, 1998; Venkatesh et al., 2003)Working with a computer makes me nervousa 1.63 1.10 0.91 0.81 0.89 0.74I get a sinking feeling when I think of trying to use acomputera

1.53 1.08 0.92

I feel comfortable working with a computer 6.33 1.17 0.73Data quality (Gattiker and Goodhue, 2005; Venkatesh, 1998; Kositanurit et al., 2006)The ERP system provides the precise information I need 5.36 1.08 0.78 0.88 0.92 0.69The information contents provided by the ERP system meetmy needs

5.39 1.24 0.87

The ERP system provides reports that seem to be exactlywhat I need

5.08 1.40 0.81

The ERP system provides sufficient information to my needs 5.33 1.35 0.89The ERP system provides complete features I need 4.94 1.57 0.78System performance (Venkatesh et al., 2003; Kositanurit et al., 2006; Liu and Ma, 2006)It is fast to search data in the ERP system 4.90 1.61 0.81 0.86 0.92 0.79I was able to retrieve data quickly 5.26 1.41 0.92It is fast to use this ERP system 5.09 1.35 0.92User manual helpfulness (Kelley, 2001)The content and index of the user manuals are useful 5.23 1.66 0.86 0.85 0.91 0.77The user manuals are current (up-to-date) 5.35 1.72 0.88The user manuals are complete 4.97 1.94 0.90Business processes fit (Amoako-Gyampah and Salam, 2004; Nah et al., 2004)The ERP solution fits well with the business needs of me 5.47 1.35 0.95 0.89 0.93 0.82The ERP solution fits well with the business need of mydepartment

5.36 1.46 0.86

All in the ERP system is satisfactoryin meeting my needs

5.33 1.32 0.90

Social influence (Venkatesh et al., 2003; Venkatesh, 1998)My supervisor is very supportive of the use of the ERPsystem for my job

5.99 1.44 0.77 0.75 0.84 0.57

In general, the organization has supported the use of the ERPsystem

5.94 1.30 0.70

People who influence my behaviour think that I should usethe ERP system

5.84 1.45 0.82

People who are important to me think that I should use theERP system

6.14 1.58 0.73

ERP usefulness (Davis, 1989)Using ERP solution in my job enables me to accomplishtasks more quickly

5.45 1.38 0.93 0.96 0.97 0.90

Using ERP solution improves my job performance 5.36 1.42 0.96Using ERP solution enhances my effectiveness on the job 5.43 1.40 0.96Using ERP solution makes it easier to do my job 5.35 1.43 0.93ERP ease of use (Davis, 1989)My interaction with the ERP solution is clear andunderstandable

5.07 1.41 0.93 0.81 0.91 0.84

(continued )

Table IV.Psychometric properties

of the instrument

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with an average R 2 of 0.45. Communality and redundancy coefficients are alsopresented in Table VII. They can be used essentially in the same way as the R 2 sincethey reflect the relative amount of explained variance for latent and manifest variables.

An important part of model evaluation is the examination of the fit indexesreflecting the predictive power of estimated inner and outer model relationshipsmeasured by evaluating the goodness-of-fit (GoF) coefficient (Tenenhaus et al., 2005).According to the results in Table VII, GoF is 0.52, which is considered satisfactory.

7. DiscussionThe aim of our research was to identify factors which influence ERP usage in theoperational phase of the ERP lifecycle. In doing so, we observed multiple, externalinfluences through second-order factors. Based on the results of our PLS analysis(Figure 2), ERP ease of use is positively related to ERP usefulness and attitudes aboutusing ERP systems (H1 and H2 are supported). Additionally, ERP usefulness directlyinfluences ERP attitude (H3 is supported). The results also show that the indirect effect ofERP ease of use on ERP attitude (through ERP usefulness,H1 andH3) is greater than thedirect effect of the ERP ease of use on ERP attitude (H2). The results of the current studysupport prior research finding a relationship between the PEOU and PU of ERP systems(Amoako-Gyampah and Salam, 2004; Hsieh and Wang, 2007; Bueno and Salmeron, 2008;Sun et al., 2009; Youngberg et al., 2009; Calisir et al., 2009; Lee et al., 2010), PEOU andattitude toward ERP systems (Nah et al., 2004; Bueno and Salmeron, 2008) and the linkbetween PU and attitudes about ERP systems (Amoako-Gyampah and Salam, 2004;Nah et al., 2004; Shivers-Blackwell and Charles, 2006, Bueno and Salmeron, 2008;

1 2 3 4 5 6 7 8 9 10

1. Technological innovativeness 0.902. Computer anxiety 0.42 0.863. ERP data quality 0.15 0.22 0.834. ERP system performance 0.03 0.13 0.53 0.895. User manual helpfulness 0.20 0.12 0.55 0.44 0.886. Business processes fit 0.22 0.26 0.68 0.60 0.58 0.917. Social influence 20.01 0.02 0.31 0.27 0.24 0.52 0.768. ERP usefulness 0.11 0.25 0.49 0.54 0.37 0.66 0.35 0.959. ERP ease of use 0.19 0.21 0.41 0.54 0.41 0.40 0.01 0.46 0.92

10. ERP attitude 0.03 0.21 0.37 0.52 0.29 0.52 0.19 0.74 0.55 0.89

Table V.Intercorrelations of thelatent variables

Construct (source)ItemMean

ItemSD Load. a CR AVE

I find the ERP solution is easy to use 4.79 1.43 0.91Attitude toward ERP system (Venkatesh et al., 2003;Nah et al., 2004)Using the ERP system is a good idea 5.94 1.31 0.86 0.75 0.89 0.80I like the idea of using the ERP system to perform my job 5.47 1.48 0.92

Notes: n 161; aItems have been inverted for processing statistical data in SmartPLSTable IV.

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Calisir et al., 2009). The findings suggest that ERP usefulness serves a mediating roleenhancing the positive effect of PEOU and attitudes about ERP systems.

Research shows that PCIL is not positively related to ERP ease of use (b 0.11,p . 0.05); consistent with previous research, hypothesisH4was not supported. STC has

Figure 2.Results of structural

model analysis

Businessprocesses fit

Social influence

ERP support

ERPcommunication

ERP training

Data quality

Systemperformance

User manuals

ERP functionality

Technologicalinnovativeness

Note: Path significance at: *p < 0.05, **p < 0.01 and n.s. not significant(shapes are marked dotted)

Computer anxiety

Computerself-efficacy

Computerexperience

OPC

STC

PCIL

ERP usefulnessR2 = 0.46

ERP ease of useR2 = 0.31

AttitudeR2 = 0.60

0.84(21.44**)

0.90(38.12**)

0.90(29.33**)

0.51(8.57**)

0.78(15.33**)

0.78(14.41**)

0.86(39.19**)

0.52(6.45**)

0.13(1.38n.s.)

0.33(3.34**)

0.61(7.55**)

0.27(3.39**)

0.82(19.83**)

First-order externalfactors

PCIL(a 0.83; CR 0.88;

AVE 0.55)STC

(a 0.90; CR 0.92;AVE 0.50)

OPC(a 0.84; CR 0.88;

AVE 0.51)Technologicalinnovativeness 0.86 (t 39.19)Computer anxiety 0.82 (t 19.83)Business process fit 0.90 (t 38.12)Social influence 0.84 (t 21.44)ERP data quality 0.90 (t 29.33)ERP systemperformance 0.78 (t 15.33)ERP user manualhelpfulness 0.78 (t 14.41)Note: All t-values are significant at p , 0.01

Table VI.Path coefficients

external variables insecond-order model

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a strong positive effect on ease of use (b 0.61, p , 0.01) and OPC has a strong positiveeffect on PU (b 0.45, p , 0.01). These findings provide empirical support forH5 and H6. No other relationships among PCIL, STC and OPC on PEOU and PU weresignificant. Among the four components of PCIL (computer experience, computerself-efficiency, technological innovativeness and computer anxiety), only technologicalinnovativeness and computer anxiety appear to be important to ERP users. Althoughthese factors are important during the implementation phase (Davis et al., 1989;Venkatesh et al., 2003; Thompson et al., 2006; Shivers-Blackwell and Charles, 2006;Venkatesh and Bala, 2008; Calisir et al., 2009; Shih and Huang, 2009), our findingssuggest they become less so during routine ERP operations. This is consistent with thearguments of Venkatesh and Davis (2000) and Thompson et al. (2006) who suggest thatthrough experience, PEOU becomes more connected with specific features of thesoftware and is less influenced by general factors.

Our findings also suggest that STC (b 0.54, p , 0.01) factors (data quality, systemperformance and user manual helpfulness) are significant in determining ease of use(explaining 31 per cent variance), while ERP functionality has not been found to be astatistically significant component of STC. Data quality has been cited as an importantfactor in successful ERP implementations (Gattiker and CFPIM, 2002; Ngai et al., 2007).Our research supports this finding suggesting that for ERP users, data quality is themost important external factor of STC (b 0.90, p , 0.01). Our findings are consistentwith previously literature which suggests that ERP users value timely access to helpfuland accurate data (Venkatesh, 1998; Venkatesh and Davis, 2000; Gattiker and Goodhue,2005; Kositanurit et al., 2006). System performance is concerned with ERP systemreliability, flexibility and response time, and is an important critical success factor in theoperational phase of an ERP solution (Bobek and Sternad, 2010). System performancewas found to be an important factor (b 0.78, p , 0.01) of STC in the routine stage inour study as well. Our study also identified that complete and up-to-date user manualhelpfulness is an important contributor to STC (b 0.78, p , 0.01) during the routinestage.

The third group of external factors researched was OPC. The results of the currentstudy support that notion that business process fit and social influence (b 0.5,p , 0.01) significantly influence perceived ERP usefulness, a finding consistent withprior studies (Venkatesh and Davis, 2000; Venkatesh and Bala, 2008). Business process

R 2 Communality Redundancy

OPC 0.51STC 0.50PCIL 0.55ERP usefulness 0.46 0.90 0.31ERP ease of use 0.31 0.84 0.25ERP attitude 0.60 0.80 0.41Average 0.45 0.60a 0.32

Note: aComputed as a weighted average of the different communalities with the weights being thenumber of manifest variables per constructSource: Tenenhaus et al. (2005)

Table VII.Explained variance (R 2),communality andredundancy

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fit (b 0.90; p , 0.01) is the largest contributing element to OPC. Bancroft et al. (2001)and Somers and Nelson (2003), pointed out that business process reengineering plays aparticularly crucial role in the early stages of implementation. It is moderately importantin the acceptance stage and tends to be less important once the technology reaches theroutine stage. Our study confirms the argument that business process fit andreengineering is a continuous process, extending into the post-implementation phase ofthe ERP lifecycle (Welti, 1999; Bradford, 2008). Social influence is affected by topmanagement support and sponsorship, suggesting that these are critical in all phases ofthe ERP lifecycle a finding widely recognized in ERP research literature (Umble et al.,2002; Gattiker and CFPIM, 2002; Stratman, 2002; Somers and Nelson, 2003). Sponsorshipplays a critical role in the acceptance of technology. Management sponsors are usually atthe senior management level so they have the authority to implement substantialorganizational changes (Akkermans and Helden, 2002; Ngai et al., 2007; Finney andCorbett, 2007). Despite the fact that support (Boudreau, 2002; Lee et al., 2010),communication (Al-Sehali, 2000; Al-Mashari et al., 2003; Somers and Nelson, 2003) andtraining and education (Bancroft et al., 2001; Boudreau, 2002; Akkermans and Helden,2002; Umble et al., 2002; Al-Mashari et al., 2003; Bradford and Florin, 2003; Gargeya andBrady, 2005; Motiwalla and Thompson, 2009) are often mentioned as CSF, none werestatistically significant in our study.

In the routine stage, organizations should emphasize people andprocess improvements (Bradford, 2008). Many people who work with the system onlymaster their particular path and do not attempt to understand the entire system(Boudreau, 2002). In this stage, ERP users should accept the system and the usageshould become a regular activity. It often takes many months or even years forexperienced users to get comfortable with an ERP system, however. Eventually, usersbegin to see the advantages of the ERP system and they begin to explore its functions,gradually reaching success. This shows that ERP users have accepted the ERP systemand are putting it into extended use. In the national telecom company, SAP has been inplace for over ten years, but according to the results about the intensity of use and thedegree of use, ERP use is moderate. Boudreau (2002) defines limited use as existing whenindividuals used ERP systems because they had to but had not assimilated much of itsfunctionality. The aim of each organization implementing an ERP system (including thenational telecom firm) should be that ERP users fully utilize systems. Our findingssuggest that organizations should attend to external factors which impact ERPacceptance and usage indirectly. In our case the national telecom company should putmore effort into the adjustment of business processes of ERP solutions to ERP usersbusiness needs and into a more positive organization thinking regarding ERP systemuse if it wants to increase ERP usefulness. On the other hand, the company should putmore effort into right and up-to-date data, put more emphasis on ERP system reliability,flexibility and response time (system performance) and on a complete and up-to-dateuser manual helpfulness if it wants to increase ERP ease of use. For more detailedinterventions, further research (e.g. interviews of key ERP users) is needed.

8. ConclusionThe most important contributions of ERP systems are that they significantly reduce thetime to complete business processes and they facilitate information sharing (Olhagerand Selldin, 2003; Lee et al., 2010). Organizations offer a better work environment for

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their employees as they provide more efficient systems. In the routine phase of the ERPlifecycle, ERP systems may be implemented successfully from a technical perspective,but full success depends on ERP users being willing to use the delivered system(Boudreau, 2002; Kwahk and Lee, 2008).

Most studies employing TAM on ERP systems focus on the selection andimplementation phases. Studies focused in the post-implementation phase are scarceand only recently published (Sun et al., 2009; Shih and Huang, 2009; Lee et al., 2010).Most of these studies consider a limited number of factors which influence theacceptance and use of ERP systems. The aim of our paper was to extend the number ofobserved factors which influence user acceptance and use in the routine or maturestage of the lifecycle. Because we observed a large number of external factors, weemployed the concept of second-order factors. The use of second-order factors, togetherwith the use of a PLS approach to test our model, allowed us to test multiple influenceswith a relatively small dataset. TAM was used because it is the most widely used andempirically tested model for explaining actual IS use (Davis, 1989; Davis et al., 1989;Amoako-Gyampah and Salam, 2004; Lee et al., 2010). We focused on external factorsand their influence on the actual use of ERP systems based on published researchabout this issue (Table II).

The present study enhances our understanding of how multiple externalfactors can impact attitudes about ERP systems in the routine stage by incorporatingthree groups of external factors: PCIL, STC and OPC. The PCIL group includes:technological innovativeness, computer anxiety, computer self-efficacy and computerexperience. Data quality, system performance, user manual helpfulness and ERPfunctionality were included in STC. Business processes fit, social influence, ERP support,ERP communication and ERP training were included in OPC. PCIL, STC and OPC havebeen addressed in several studies of external factors impacting IS acceptance (someauthors related their research to TAM, but not all). The present research, however, showsthat PCIL does not impact ERP system usage significantly in the routine operation stagedespite its being mentioned in other studies unrelated to ERP systems (Venkatesh et al.,2003; Venkatesh and Bala, 2008). STC and OPC are similarly important but they impactdifferent variables of TAM in ERP usage. STC components of data quality, systemperformance and user manual helpfulness are significant in determining ERP ease of use,while business process fit and social influence (OPC) influence the PU of ERP systems.

One important contribution of the paper is the identification of the external factors forthe improvement of the efficiency and effectiveness of ERP use and the presentationof the impact of OPL and STC on attitude towards using ERP system in the organization.The implications for researchers and practitioners are that external factors of TAMthrough second-order factors appear to improve ERP usage. The managerialimplications of this study are that if the organization wants to improve businessperformance and increase ERP user satisfaction, it should take into account the externalfactors confirmed in this study.

The limitations of the present study present opportunities for further research. Manystudies have discovered that language, culture, nation and politics influence ERPimplementation (Yu, 2005). Since the respondents to the survey were limited to oneorganization, this study could be replicated in organizations varying by industry(manufacturing, retail, etc.), size (small, medium, large), market (local, regional, nationalor international) or across other potentially important differences. Further research

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is needed to explore the importance of external factors in different phases of the ERPlifecycle. Because ERP solutions are implemented by different methodologies andapproaches, the importance of external factors on ERP solutions could also be explored.Researching the impact of external factors on work compatibility (Nah et al., 2004;Sun et al., 2009) and the impact of work compatibility on TAM likewise could bepromising.

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Corresponding authorSimona Sternad can be contacted at: simona.sternad@uni-mb.si

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