Recen Advances in Applied & Biomedical Informaics and Compuaional Engineering in Sysems Applicaions ERP and Assisance Sysems CARLOS J. COSTA Insiuo Universiario de Lisboa (ISCTE-IUL), Adei-IUL, Lisboa PORTUGAL carlos.cosa@isce.p MANUELA APARICIO Insiuo Universiario de Lisboa (ISCTE-IUL), Adei-IUL, Lisboa PORTUGAL manuela.aparicio@isce.p Absrac: - User assisance sysems are especially imporan in complex informaion sysems. ERP (Enerprise Resource Planning) is an example of a complex sysem. On he oher hand, users of hose sysems wan a quick and precise answer o heir problems in order o perform specific asks. In his paper, we analyze he adopion of user assisance sysems. In order o analyze, we use as heoreical framework he Technology Accepance Model (TAM). We also proposed some characerisics relaed o he percepion of ERP use ha may influence he accepance and adopion of user assisance sysems. Key-Words: ERP, TAM, Organizaional Sysems, Empirical Sudy, Assisance Sysems 1 Inroducion The use of user assisance sysems is especially imporan. Nowadays organizaional employees have o use ERP. Ofen, hey mus choose among several ypes of user assisance sysems. Invesigaing he facors associaed wih user accepance of new sofware sysems has been an imporan research sream in he field of informaion sysems for many years. The echnology accepance model has long been used o examine he accepance of informaion sysems. In his specific case, he assisance sysem is a suppor o oher informaion sysem. In our research we use TAM (Technology Accepance Model) wih he purpose of analyzing wha facors influence he use of user assisance sysem. In he following secion we presen broadly he TAM. Then, we presen he main user assisance sysems, used nowadays, ha suppor informaion sysems and specifically ERP. In he nex secion, we presen he research hypohesis, suppored in he TAM heoreical framework. Then, we repor main resuls from he empirical work. 2 Technology Accepance Model Technology Accepance Model (TAM) was inroduced by Davis [5]. I aims o undersand he process of user accepance of informaion sysems. TAM is one of he mos cied heoreical frameworks. Specifically, he TAM specifies he causal relaionships beween sysem design feaures, he perceived usefulness, he perceived ease of use, he aiude owards usage and acual he usage behavior. In general, he TAM provides an informaive represenaion of he mechanisms by which design choices influence user accepance. Consequenly i is helpful in applied conexs for forecasing and evaluaing user accepance of specific echnology. The model aims no only o explain key facors of user accepance of informaion sysems. In fac, is purpose is also predicing he relaive imporance of he facors in he diffusion of echnological sysems [6]. TAM proposes ha perceived ease of use and perceived usefulness of echnology are predicors of user aiude owards using he echnology, consequenly inenions of behavior and acual echnology usage. Perceived ease of use was also considered o influence perceived usefulness of echnology. Figure 1 presens original version of TAM [5]. exernal variables perceived usefulness perceived ease of use behavioural inenion acual sysem use Figure 1 TAM Technology Accepance Model [6] Venkaesh and Davis [16], proposed an exension of TAM, he TAM2. TAM2 includes ISBN: 978-1-61804-028-2 216
Recen Advances in Applied & Biomedical Informaics and Compuaional Engineering in Sysems Applicaions social influence process such subjecive norm, and cogniive insrumenal process such as job relevance, oupu qualiy and resuls. TAM has been applied in numerous sudies esing user accepance of informaion echnology. Jus for example, TAM was applied o sudy he following echnologies: word processors [6], spreadshee applicaions [12], e-mail [15], web browser [13], elemedicine [9], websies [10], e- collaboraion [4], elearning [11], ERP [2] and Lego Robo Mindsorms [3]. 3 Problem Soluion Tradiionally, user assisance was suppored mainly in prined manuals. Then, oher forms of user assisance sysem were developed. As well as echniques used in he conex of auhoring and publishing (e.g. DITA form OASIS). Bu oher sysems sar o be employed like: Digial manual, Tuorials, Help files, help desk, icke sysems, Remoe Assisance, Forum and Wiki. A iny evoluion of he prined manual is he digial manual. Tuorials are also ineresing evoluions of he radiional prined manual. Nowadays, mulimedia uorials and small videos play an imporan role in user suppor, Help files are also an ineresing evoluion of he radiional manual. They were very popular in office applicaions. WikiWikiWeb was he firs wiki [8]. Remoe assisance is a form of assisance suppored in a nework infrasrucure. In he remoe assisance, he assisan may solve he problem wihou he inervenion of he user. FAQ is a very old form of presening informaion. For example, Summa Theologica was presened in a Q&A forma [1]. Forums were based in he bullein board sysems. Help desk sysems are a poin of conac where users may obain he answer o heir problems. They used o be suppored in a phone. Typically, he inerface is a human person, bu may also be an answer machine. A icke sysem is anoher way of implemening a help desk sysem. 4 Research Hypoheses Suppored in he TAM concepual framework we analyze he level of accepance of assisance sysems. We sared by analyzing perceived usefulness (PU), perceived ease of use (PEO) and Inenion o use he sysem (INT). H1 PU PEOU H2a H2b INT Figure 2 Hypoheses H1, H2a H2b Suppored in he previous dimension, he following hypoheses were derived: H1) Perceived ease of Use will have a posiive effec on he perceived usefulness. H2a) Perceived usefulness will have a posiive effec on he users behavioral inenion of using an H2b) Perceived ease of Use will have a posiive effec on he user behavioral inenion of using he PU H3a PEOU H3b AT H4a H4b Figure 3 Hypoheses H3a, H3b, H4a H4b INT Hypohesis H3a, H3b, H4a and H4b were also suppored in he TAM heoreical framework. H3a) Perceived usefulness will have a posiive effec on he users aiude owards using an H3b) Perceived ease of Use will have a posiive effec on he user aiude owards using he H4a) The user aiude owards using he assisance sysem will have a posiive effec on heir inenion o use he sysem. H4b) Perceived ease of Use will have a posiive effec on heir inenion o use he sysem. ISBN: 978-1-61804-028-2 217
Recen Advances in Applied & Biomedical Informaics and Compuaional Engineering in Sysems Applicaions The following hypoheses were suppored in he observaion. In fac, we observed ha one of he purposes of he users is o be efficien, effecive and have saisfacion in he use of he ERP sysem. So i was analyzed in wha exen produciviy and saisfacion have impac in he use of a specific suppor sysem. INT In order o evaluae hose research hypoheses, we esimaed a regression, where PEU (perceived ease of use) is independen variable and PU (perceived usefulness) is dependen variable. Regression 1 224.899 224.899 205.875 0.000 PROD SAT Residual 398 434.778 1.092 Toal 399 659.678 Dependen Variable: "PU" Figure 4 Hypohesis H5, H6 H5) If he assisance sysem improves produciviy of ERP use i increases he behavioral inenion of using his assisance sysem H6) If he assisance sysem improves saisfacion of ERP use i increases he behavioral inenion of using his assisance sysem 5 Empirical Sudy In order o evaluae research hypohesis, we used a group of sudens from managemen and indusrial engineering as subjecs. Those sudens had o performed several asks using an ERP Open Source. Those sudens had a previous raining and hen were asked o solve a case sudy composed wih a se of operaions. In order o solve he case hey also had o use several user suppor sysems (Wiki, Remoe assisance, FAQ, Forum, help desk, Manual, Tickes, Help Files). Then, hey had o answer o a quesionnaire wih TAM quesions o each suppor sysem. The number of users ha used ERP sysems and ERP help sysems were 50. The number of help sysems evaluaed by each user was 8. Consequenly, he number of oal observaions was 400. In order o evaluae he hypohesis, daa from he quesionnaire was subjec o saisical reamen. Regression analysis was used. 6 Empirical Resuls and Hypohesis Evaluaion H1) Perceived ease of Use will have a posiive effec on he perceived usefulness. 0.584 0.341 205.875 0.000 1 398 Adjused R Squared = 0.339 Sd. of Esimae = 1.045 Variable Bea B Sd. "PEU" 0.58 4 Consan = 2.015 0.61 3 0.043 14.34 8 Prob.> VIF 0.000 1.000 1.000 According o he resuls, he correlaion beween he wo variables is no high. Neverheless, values esimaed were significan. H2a) Perceived usefulness will have a posiive effec on he users behavioral inenion of using an H2b) Perceived ease of Use will have a posiive effec on he user behavioral inenion of using he In order o evaluae hose research hypoheses, we esimaed a regression, where PEU (perceived ease of use) and PU (perceived usefulness) are independen variables INT (inenion o use he sysem) is dependen variable. Regression 2 363.989 181.995 152.930 0.000 Residual 397 472.451 1.190 Toal 399 836.440 Dependen Variable: "INT" ISBN: 978-1-61804-028-2 218
Recen Advances in Applied & Biomedical Informaics and Compuaional Engineering in Sysems Applicaions Variable Bea B Sd. Prob.> VIF 0.660 0.435 152.930 0.000 2 397 Adjused R Squared = 0.432 Sd. of Esimae = 1.091 "PEU" 0.40 9 "PU" 0.34 3 0.497 0.056 8.909 0.000 1.517 0.659 0.397 0.053 7.475 0.000 1.517 0.659 Variable Bea B Sd. "PEU" 0.420 0.49 6 "PU" 0.320 0.36 0 Consan = 0.386 Prob.> VIF 0.055 9.033 0.000 1.517 0.659 0.052 6.883 0.000 1.517 0.659 Like in he previous regression he explanaory power of he regression is no very high, wih an R squared of 0.435 and an adjused R squared of 0.432. On he oher hand, PEU had a bea (and b) slighly superior han PU. I means ha he Inenion of use is more influenced by he perceived ease of use han he perceived usefulness. H3a) Perceived usefulness will have a posiive effec on he users aiude owards using an H3b) Perceived ease of Use will have a posiive effec on he user aiude owards using he In order o evaluae hose research hypoheses, we esimaed a regression, where PEU (perceived ease of use) and PU (perceived usefulness) are independen variables and AT (Aiude oward he sysem) is dependen variable. Consan = 0.181 Like in he previous regression he explanaory power of he regression is no very high, wih an R squared of 0.449 and an adjused R squared of 0.446. Also like in he previous siuaion, PEU had a bea (and b) slighly superior han PU. I means ha he Aiude oward he sysem is more influenced by he perceived ease of use han he perceived usefulness. H4a) The user aiude owards using he assisance sysem will have a posiive effec on heir inenion o use he sysem. H4b) Perceived ease of Use will have a posiive effec on heir inenion o use he sysem. In order o evaluae hose research hypoheses, we esimaed a regression, where AT (Aiude oward he sysem) and PU (perceived usefulness) are independen variables and INT (inenion o use he sysem) is dependen variable. Regression 2 492.224 246.112 283.853 0.000 Residual 397 344.216 0.867 Toal 399 836.440 Regressio n 2 396.100 198.050 161.583 0.000 Residual 397 486.598 1.226 Toal 399 882.697 Dependen Variable: "AT" Dependen Variable: "INT" 0.767 0.588 283.853 0.000 2 397 Adjused R Squared = 0.586 Sd. of Esimae = 0.931 0.670 0.449 161.583 0.000 2 397 Adjused R Squared = 0.446 Sd. of Esimae = 1.107 ISBN: 978-1-61804-028-2 219
Recen Advances in Applied & Biomedical Informaics and Compuaional Engineering in Sysems Applicaions Variab le Bea B Sd. Prob.> VIF of using as resul of he percepion of produciviy improvemen. "AT" 0.638 0.621 0.039 16.12 1 0.000 1.512 0.661 "PU" 0.194 0.218 0.045 4.889 0.000 1.512 0.661 Consan = 0.677 The explanaory power of he regression may be considered good in he conex of social behavior, wih an R squared of 0.588 and an adjused R squared of 0.586. AT had a bea (and b) superior han PU. I means ha he aiude owards he sysem influences more Inenion of use he sysem han usefulness. H5) If he assisance sysem improves produciviy of ERP use i increases he behavioral inenion of using his assisance sysem In order o evaluae hose research hypoheses, we esimaed a regression, where PROD (assisance sysem improves produciviy of ERP) is independen variable and INT (inenion of using he sysem) is dependen variable. H6) If he assisance sysem improves saisfacion of ERP use i increases he behavioral of using his assisance sysem In order o evaluae hose research hypohesis, we esimaed a regression, where SAT (assisance sysem improves saisfacion in he use of ERP) is independen variable and INT (inenion of using he sysem) is dependen variable. Regression 1 297.196 297.196 219.352 0.000 Residual 398 539.244 1.355 Toal 399 836.440 Dependen Variable: "INT" 0.596 0.355 219.352 0.000 1 398 Regression 1 198.852 198.852 171.742 0.000 Residual 398 460.825 1.158 Adjused R Squared = 0.354 Sd. of Esimae = 1.164 Toal 399 659.678 Dependen Variable: "INT" 0.549 0.301 171.742 0.000 1 398 Adjused R Squared = 0.300 Sd. of Esimae = 1.076 Variable Bea B Sd. Prob.> VIF "PRD" 0.549 0.517 0.039 13.105 0.000 1.000 1.000 Consan = 2.599 The correlaion beween he variables shows a modes explanaory power of he model esimaed. Bu i was idenified a posiive effec in he inenion Variab le Bea B Sd. Prob.> VIF "SAT" 0.596 0.628 0.042 14.811 0.000 1.00 0 Consan = 1.810 1.000 Like in he previous model, he correlaion beween he variables shows a modes explanaory power of he model esimaed. Bu i was also idenified a posiive effec in he inenion of using as resul of he percepion of saisfacion improvemen. Noe: Tolerance () is a measure of mulicollineariy. The Variance inflaion facor VIF = 1/ is used insead, as i could be inerpreed more easily. I shows direcly how much he sandard error of he esimaion is inflaed by he mulicollineariy. ISBN: 978-1-61804-028-2 220
Recen Advances in Applied & Biomedical Informaics and Compuaional Engineering in Sysems Applicaions VIF>10 (equivalenly <0.1) would indicae a mulicollineariy problem. 4 Conclusion In his paper we analyzed he accepance of assisance sysems. In fac, success of ERP depends on capaciy of using he sysem. As complex sysem, i depends heavily from user assisance. In his paper, we analyzed he accepance of user assisance sysems. In order o analyze, we used as heoreical framework he Technology Accepance Model (TAM). This heoreical framework proved o be adequae o explain he level of accepance end poenial adopion of assisance sysems by users. On he oher hand, i showed ha he ease of use is an imporan issue in he adopion of a specific a user Acknowledgemens: This work was parially suppored by FCT Fundação para a Ciência e Tecnologia Porugal. References: [1] Aquino, T. (1265-1274); Summa Theologica; Copyrigh Chrisian Classics Ehereal Library hp://www.ccel.org/ccel/aquinas/summa.pdf [2] Bueno, S., & Salmeron, J. L. (2008). TAMbased success modeling in ERP. Ineracing wih Compuers, 20(6), 515-523. doi:10.1016/j.incom.2008.08.003 [3] Chesney, T. (2006). An accepance model for useful and fun informaion sysems. Human Technology, 2(2), 225-235. [4] Dasgupa, S., Granger, M. & Mcgarry, N. (2002). User accepance of e-collaboraion echnology: an exension of he echnology accepance model, Group Decision and Negoiaion, 11, 87-100. [5] Davis, F. D. (1986). A Technology Accepance Model for Empirically Tesing New End-User Informaion Sysems: Theory and Resuls. Unpublished docoral disseraion, Massachuses Insiue of Technology.. [6] Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User accepance of compuer echnology: A comparison of wo heoreical models. Managemen Science, 35 (8), 982-1003. [7] Davis, F.D. (1989). Perceived usefulness, perceived ease of use and user accepance of informaion echnology. MIS Quarerly, 13(3), 319-339. [8] Ebersbach, A. (2008), Wiki: Web Collaboraion, Springer Science & Business Media [9] Hu, P.J., Chau, P.Y.K., Sheng, O.R.L., & Tam, K.Y. (1999). Examining he echnology accepance model using physical accepance of elemedicine echnology. Journal of Managemen Informaion Sysems, 16(2), 91-112. [10] Koufaris, M. (2002). Applying he echnology accepance model and flow heory o online consumer behavior. Informaion Sysems Research, 13 (2), 205-223. [11] Landry, B.J.L., Griffih, R., & Harman, S. (2006). Measuring suden percepions of blackboard using he echnology accepance model. Decision Sciences, 4(1), 87-99. [12] Mahieson, K. (1991). Predicing user inenions:comparing he echnology accepance model wih heory of planned behavior. Infromaion Sysems Research, 2(3), 173-191. [13] Morris, M.G., & Dillon, A. (1997). The influence of user percepions on sofware uilizaion: applicaion and evaluaion of a heoreical model of echnology accepance, IEEE Sofware, 14(4), 56-75. [14] Roca J.C. Chiu C.-M. & Marínez F. J. (2006) Undersanding e-learning coninuance inenion: An exension of he Technology Accepance Model Inernaional Journal of human-compuer sudies 64(8), 683-696. [15] Szajna, B. (1996). Empirical evaluaion of he revised echnology accepance model. Managemen Science, 42(1), 85-92. [16] Venkaesh, V. and Davis, F.D. (2000). A Theoreical Exension of he Technology Accepance Model: Four Longiudinal Field Sudies. Managemen Science, 46 (2), pp. 186-204. [17] hp://dia.xml.org/ ISBN: 978-1-61804-028-2 221