Vai trò của cảm nhận tính hữu dụng trong mối quan hệ giữa sự phù hợp giữa nhiệm vụ và công nghệ với kết quả công việc cá nhân trong môi trường ứng dụng erp – bằng chứng từ các doanh nghiệp Việt Nam

Science & Technology Development Journal – Economics - Law and Management, 3(4):451-461 Open Access Full Text Article Research Article University of Economics, Ho Chi Minh City Correspondence Pham Tra Lam, University of Economics, Ho Chi Minh City Email: phamtralamais@ueh.edu.vn History  Received: 04/3/2019  Accepted: 13/5/2019  Published: 31/12/2019 DOI :10.32508/stdjelm.v3i4.587 Copyright © VNU-HCM Press. This is an open- access article distributed under the terms of the Creative Commons Attribution 4.0 International license. The role of perceived usefulness in the relationship between task — technology fit and individual job performance in ERP implementation— evidence from Vietnam’s enterprises Vo Van Nhi, Pham Tra Lam* Use your smartphone to scan this QR code and download this article ABSTRACT In this context, the aim of the study was to examine the role of perceived usefulness in the relation- ship between individual job performance and task – technology fit in ERP environment. The study was done by 225 individuals. The results of the PLS_SEM analysis reveal ed that task— technology fit was significantly and positively related to perceived usefulness and individual job performance in ERP environment. Furthermore, perceived usefulness was significantly to individual job perfor- mance in ERP context. The results of this study added to the empirical evidence in the application of background theories including TTF, TAM and TTF models combined, DeLone and McLean IS Success Model, and ECM. Besides, they also added to the theoretical background of ERP's success. Furthermore, they support for companies who are planning to use ERP systems and the ERP ven- dors and implementers become more knowledgeable about ERP's success and forecast success when using ERP systems. Based on these results, the enterprise can plan the application to im- prove the efficiency of ERP systems. At the same time, the ERP vendors and developers can better advise and support their customers when delivering and deploying ERP systems. Key words: Enterprise resource planning (ERP), job performance, perceived usefulness, task - technology fit, Vietnam INTRODUCTION Companies all over the world have adopted enter- prise resource planning (ERP) systems to integrate their business processes and stay competitive 1. Be- cause ERP is information system (IS), user percep- tions about an ERP system play an important role in both usage and success of ERP2. Some organiza- tions have applied the ERP system but users are non- adoption of the system3. In this case, job performance and job satisfaction are lower and turnover rates are higher4. In addition, if the job performance of indi- vidual is low, it will adversely affect the performance of organization5. As a critical indicator of ERP imple- mentation success, it is important to examine possible factors that affect employee job performance 4. Bradford and Florin 6 developed and tested a model of ERP implementation success which is measured by perceived organizational performance and user sat- isfaction. While the study of Bradford and Florin 6 examined perceived organizational performance, the others explored the factors that can impact individual performance when using ERP systems such as Kosi- tanurit et al. (2006), Park et al. (2007), Sykes et al. (2014), Sykes (2015) 4,5,7,8. Kositanurit et al. provides evidence that system quality, utilization, and ease of use are the three important factors bearing on individ- ual performance in ERP environment5. The study of Park et al. found that the users’ ability to understand ERP knowledge influenced its performance and or- ganizational support moderated the relationship be- tween their absorptive capacity and performance7. Sykes et al. show workflow advice and software ad- vice are associated with job performance4. Besides, that study found that the interactions of workflow and software get-advice, workflow and software give- advice, and software get- and give-advice impacted job performance. Similarly, Sykes disclosures both traditional support structures and peer advice ties were found to influence the various outcomes in- cluding system satisfaction, job stress, job satisfac- tion and job performance8. On the individual level, the factors that are proven to have an impact on the job performance in ERP environment include sys- tem quality, utilization, ease of use, users’ ability to understand ERP knowledge, workflow advice, soft- ware advice, traditional support structures and peer advice ties. Similar to the above studies, this work seeks to examine post — implementation employee job performance. However, we look for the impact of other factors including perceived usefulness and Cite this article : Nhi V V, Lam P T. The role of perceived usefulness in the relationship between task — technology fit and individual job performance in ERP implementation — evidence from Vietnam’s enterprises. Sci. Tech. Dev. J. - Eco. Law Manag.; 3(4):449-459. 451 Science & Technology Development Journal – Economics - Law and Management, 3(4):451-461 task — technology fit on job performance of users in ERP context. Based on Task- Technology Fit the- ory (TTF)9–11, TAM and TTF models combined 12, DeLone and McLean IS Success Model2,13and ECM (Expectation–Confirmation Model)14, this study ex- amined the role of perceived usefulness in the rela- tionship between individual job performance and task — technology fit in ERP environment. This article is structured as follows. First, we describe the theoretical background on individual job perfor- mance, perceived usefulness and task — technology fit. Next, we present the research methodology used. Then, we present the findings. Finally, we present some conclusions and further work. LITERATURE REVIEW Individual Job Performance According to TTF theory, performance benefits im- prove a range of performance outcomes15. The spe- cific outcomes that have been examined in prior TTF research include system use/intention to use, job per- formance, satisfaction with technology, opinions re- garding a technology, appropriation changes made, decision efficiency, decision quality, decision strategy employed, joint profit attained, number of ideas gen- erated, quality of solution, task completion time, task accuracy, ability to perform tasks, perceived ease of use, perceived usefulness, perceived playfulness, per- ceived risk15. High performance implies that there is a mix between improved efficiency, improved effective and/ or im- proved quality 10. It was often confused with produc- tivity 16. However, it is actually measured by more global variables such as the quality of outputs, job knowledge, leadership, or judgment16. In the tradi- tional office, job performance is largely established by scanning for employees’ presence and through direct and indirect observations16. There exists a wide range of employee outcomes in ERP implementation, such as systems satisfaction, job stress, job satisfaction, and individual job perfor- mance8. Job performance is a way to measure em- ployee outcomes. Job performance is a good way of performing an employee’s work 8. This study defined individual job performance in ERP environment was that the employee feels that with the help of ERP systems he/she can improve a range of performance outcomes. Task— Technology Fit Task — technology fit concept derives from the Task- Technology Fit theory (TTF) 9–11. According to TTF, the task — technology fit represents the degree of matching or alignment between the capabilities of an information system and the demands of the tasks that must be performed 15. Base on TTF, this study de- fined t ask — technology fit is the degree of relevance between the ability of ERP system and the tasks which an employee must perform. Based on three theories including TTF, TAMandTTF models combined, and the DeLone and McLean IS Success Model (2013) 13, this study develops the hy- pothesis H1. Firstly, according TTF, task — technol- ogy fit impact on performance benefit10 while indi- vidual job performance is used as an indicator of per- formance benefit15. Secondly, TAM and TTF models combined show that task — technology fit have sig- nificant effect on actual tool use 12. At the same time, the user behavior has an impact on the job perfor- mance17. Finally, Peter et al.18 suggested that task compatibility impact on the IS success. Task compat- ibility is the fit or consistency between the task and the IS that supports that task13. In this study, task — technology fit was defined similarly to task compati- bility. Petter et al.18 measured the IS success based on the update DeLone and McLean2 IS success model, including information quality, system quality, service quality, intention to use/ use, user satisfaction, and net benefits. In this study, individual job performance was considered an indicator of net benefits. Based on the above arguments, this study developed hypothesis H1. This hypothesis is also supported by several stud- ies, such as Norzaidi et al. (2009), Bhattacherjee (2001), Teo and Bing (2008), Kositanurit et al. (2006), D’Ambra and Wilson (2004a), D’Ambra and Wilson (2004b), Wongpinunwatana et al. (2000), Goodhue et al. (1997), Goodhue andThompson (1995), Good- hue (1995), Henseler (2015) 5,9,10,14,19–25. In particu- lar, Staples and Seddon18 show that task — technol- ogy fit had an impact on individual job performance in both kinds of IT use, voluntary and mandatory. In this study, if an enterprise is using an ERP system, employees are required to use it. So Staples and Sed- don18 strongly support the hypothesis H1. H1: The task – technology f it has a positive effect on the job performance of employee in ERP envi- ronment. Perceived Usefulness In TAM, perceived usefulness is “the degree to which a person believes that using particular system would enhance his or her job performance”26 (p.320). Per- ceived usefulness is a dimension of performance ex- pectancy in UTAUT27. In this study, perceived use- fulness of ERP systems was understood as the level at 452 Science & Technology Development Journal – Economics - Law and Management, 3(4):451-461 which the user believes ERP systems delivers good re- sults for their work. According TTF, task – technology fit impact on per- formance benefit10 and perceived usefulness can be used as an indicator of performance benefit15,28. Be- sides, Dishaw et al.12 suggested TAM and TTF mod- els combined that demonstrated task— technology fit to have a significant impact on perceived usefulness. Based on TTF, TAM and TTF models combined and some studies such as Norzaidi et al. (2009), Tjahjono (2009), Chang (2008), Wu et al. (2007), Klopping and McKinney (2004), Dishaw and S trong (1999), Good- hue (1995) 9,10,19,29–33 hypothesis H2 is stated as fol- lows: H2: The task— technology fit has a positive effect o n the perceived usefulness in ERP environment. Based on three theories, namely TAM and TTF models combined, ECM (Expectation–Confirmation Model)14 and DeLone and McLean IS Success Model (2013)2, this study developed the hypothesis H3. The first, according TAMandTTFmodels combined, per- ceived usefulness has effect on attitude toward use, then attitude toward use impact on intention to use, after that intention to use effect on actual tool use 12. Next, ECMshows that perceived usefulness impact on IS continuance intention14. Last, user expectations was proven to have an impact on the IS success2. User expectations is the degree to which the user’s percep- tions about the IS are consistent with the actual IS 10. In this study, perceived usefulness was close to the user expectations used in Petter et al. (2013)13. In general, TAM and TTF models combined, ECM and DeLone and McLean IS Success Model (2013) 2 have shown that the perceived usefulness of the informa- tion system had a positive impact on user behavior. At the same time, the user behavior had an impact on the job performance17. Furthermore, some studies include Rajan and Baral (2015), Furneaux (2012), Sternad and Bobek (2013), Soto-Acosta et al. (2013), Elkhani et al. (2014), Zhang et al. (2013), Keong et al. (2012), Norzaidi et al. (2009), Youngberg et al. (2009), Calisir et al. (2009), Lee et al. (2010), Chang (2008), Wu et al. (2007), Ramayah and May- Chiun Lo (2007), Sey- mour et al. (2007) andAmoako- Gyampah and Salam (2004) have also shown that the perceived useful- ness of IS/ ERP had a positive impact on user behav- ior15,17,19,30,31,34–44. In addition, Goodhue demon- strated that the perceived usefulness of IS has a pos- itive impact on the individual job performance in IT context9. Based on the above arguments, this study hypothesized the following: H3: The perceived usefulness of the ERP has a pos- itive effect on the job performance of employee in ERP environment. Figure 1 represents the proposed research model that was used for this research. Figure 1: Proposed researchmodel. METHODOLOGY Measures All research constructs included in this study had multi-item scales derived from the relevant literature. Each item in the survey employed a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree), and a not applicable (NA) option was available for the re- spondents to choose. We now elaborate our mea- sures for the constructs. This study accepted scale of the individual job performance in ERP environ- ment (PER) from Goodhue and Thompson10. PER is a first – order construct and reflective measures with 2 items. We measured task – technology fit (TTF) using a11- item scale adapted fromKositanurit et al.5 that captures the eight dimensions including currency (CURR), right data (RDAT), right level of detail (RDET), meaning (MEAN), ease of use (EOU), training (TRAI), authorization (AUT) and system re- liability (REL). TTF is a high – order construct and reflective – reflective measures. The perceived useful- ness (PU) was measured with 6 items adapted from Calisir and Calisir45 (from the TAM model). PU is a first – order construct and reflective measures. Data collection This study was conducted using quantitative means as it aimed to validate the proposed relationships be- tween factors affecting individual job performance in ERP context. The research instrument was used a questionnaire distributed to the end-users (employ- ees). The data were collected from June 2017 to Au- gust 2017. The questionnaires were sent by email or postal mail to an initial sample of 5 00 employees who 453 Science & Technology Development Journal – Economics - Law and Management, 3(4):451-461 are using ERP system. We collected 265 responses (re- sponse rate was 53 %). Baruch46 points out that for surveys addressed to individual, the average response rate is 52.7%. Thus, the response rate of our study seems to be above average. Of the 265 employees, 225 employees from 49 companies gave usable responses at all points of measurement. Table 1 presents the sample characteristics age, gen- der, education and average computer experience. The sample consisted of 161 (71.6 %) female and 64 (28.4 %) male. The Table 1 shows that 75.5% of the sam- pled individuals were fewer than 35. In addition, 72% of the sampled individuals had bachelor degree. Av- erage experience using an ERP system was 2.56 years. The Issue of CommonMethod Bias Because there was only one respondent for each indi- vidual, common method bias (CMB) was a potential problem. In this study, we took a number of steps sug- gested by Podsakoff et al.47 to reduce the possibility of commonmethod bias. Firstly, we used multiple items for each construct and ensured the neutral wording of the items. Secondly, we assured respondents of the anonymity of their responses and emphasized that there were no right or wrong answers; each of these actions enabled them to answer questions as honestly as possible. Thirdly, we separated the measurement of predictors and criterion variables in the question- naire to diminish the respondent’s ability andmotiva- tion to use his/her prior responses to answer subse- quent questions. Finally, we also used the Harman’s single-factor test and the marker variable approach to control for commonmethod variance (CMV). Results are discussed in data analysis and results section. DATA ANALYSIS AND RESULTS Measurementmodel We estimated the internal consistency reliability, con- vergent validity, and discriminant validity of each measurement scale to assess the measurement model. We used two criterions for internal consistency were composite reliability (CR) and Cronbach’s alpha. All the reflective constructs in our model show in Table 2 have a Cronbach’s alpha over the cut off of 0.70, as suggested by Hair et al.48. Similarly, a composite re- liability (CR) of all the constructs is also higher than 0.7, as suggested by Fornell and Larcker49, implying high internal consistency. Convergent validity is verified through the t-statistic for each factor loading. In PLS_SEM, we can use an indicator’s outer loading. An outer loading should be above 0.7 and the t-statistic for each outer loading significant48. Results of measurement models show that the items including AUT1, AUT2, REL1, REL2 and TRAI have outer loading was above 0.7 but the t- statistic for each outer loading was not significant. As such, the AUT1, AUT2, REL1, REL2 and TRAI were excluded from the TTF scales. Table 2 shows that re- sults of final measurement models. A ll factor load- ings are greater than the typical cut off value of 0.7 48 and significant at the p <0.001 level. In this study, we also used the average variance extracted (AVE) to assess convergent validity. An AVE value of 0.50 or higher indicates that, on average, the construct ex- plains more than half of the variance of its indicators. To establish discriminant validity, we used the HTMT criterion, Fornell – Larcker criterion and cross load- ings. The results of discriminant validity are show in Table 3. Cross-factor loadings are reported in Ap- pendix A. The square root of the AVE of each construct should be higher than its highest correlation with any other construct49. Table 3 shows that the square root of AVE exceeds the correlation between other con- structs. In addition, all HTMT of constructs are sig- nificantly smaller than 125. These results imply satis- factory discriminant validity. Structural model The structural model was examined to test the hy- potheses. The R2, which is generated for each re- gression equation, indicates the explanatory power or variance explained of the latent endogenous variable. Figure 2 shows the structural model result. Figure 2: Result of proposed researchmodel. ThePLS path analysis results show that task – technol- ogy fit was significantly related to individual job per- formance (b = 0.434, p < 0.001) and perceived useful- ness (b = 0.607, p < 0.001) supporting hypotheses H1 andH2. Perceived usefulness was significantly related to individual job performance (b = 0.504, p < 0.001) supporting hypotheses H3. 454 Science & Technology Development Journal – Economics - Law and Management, 3(4):451-461 Table 1: Sample characteristics (n = 225) Category Frequency Percentages (%) Category Frequency Percentages (%) Age Education < 35 170 75.5 Master 7 3.1 35 – 45 47 20.9 Bachelor 162 72 > 45 8 3.6 Colleges 43 19.1 Gender Others 13 5.8 Male 64 28.4 Average computer experience (years) 2.56 56 Female 161 71.6 The external variables including task – technology fit and perceived usefulness could explain 70.7 percent variance in individual job performance (R2 = 0.707). Task – technology fit explained 36.8 percent of vari- ance of perceived usefulness (R2 = 0.368). Next, we assessed the predictive relevance of the path model by Q2 values. All Q2 values are considerably above zero (Q2 of individual job performance is 0.631 and Q2 of perceived usefulness is 0.261), thus provid- ing support for the model’s predictive relevance re- garding the endogenous latent variables. Thefinal assessments address the f2 and q2 effect sizes. Table 4 summarizes the results of the f2 and q2 effect sizes with respect to all the relationships in themodel. Target constructs appear in the first row, whereas the predecessor constructs are in the first column. Table 4 shows TTF has a large effect size of 0.405 (0.290) on PER and of 0.583 (0.404) on PU. Similarly, PU has a large effect size of 0.546 (0.345) on PER. Additionally, the variance inflation factor (VIF) was assessed to check multicollinearity. The collinearity diagnostics given inTable 5 shows that VIF for the in- dependent variables higher than 0.20 (lower than 5) which further suggests that multicollinearity does not exist among the independent variables. MEDIATION ANALYSIS In this study, we examined a mediator variable, inter- venes between two other related constructs. Specifi- cally, we examined the role of perceived usefulness in the relationship from task – technology fit to individ- ual job performance in ERP context. Table 6 shows result of mediator variable. We find that both direct effect and indirect effect are significant. Our finding provided empirical support for the mediating role of perceived usefulness in the relationship from task – technology fit to individual job performance in ERP context. Because path coefficient of the relationship from task – technology fit to individual job performance was 0.434 and significant, path coefficient of the relation- ship from task – technology fit to perceived useful- ness was 0.607 and significant, and path coefficient of the relationship from perceived usefulness to individ- ual job performance was 0.504 and significant, per- ceived usefulness represents complementary media- tion of the relationship from task – technology fit to individual job performance in ERP context. The Issue of CommonMethod Bias We used the Harman’s single-factor test and the marker variable approach to control for CMV in PLS analysis. Result of Harman’s single-factor test by EFA shows that one factor only account for 40.537% of the total variance. In this case, CMV is not a serious prob- lem50. The marker variable approach was conducted by us- ing marker variable. The first stage, we involved sur- vey questionnaire that had a question was “Do you re- ally like black coffee?” – this question was a marker variable24. The next stage, we used PLS to test path coefficient of the relationship frommarker variable to other variable in proposal model including perceived usefulness, task – technology fit and individual job performance. Analysis results showed that all path coefficients of the relationships from marker variable to perceived usefulness, task – technology fit and in- dividual job performance were less than 0.3 (-0.102, 0.094 and -0.060). This finding suggests that CMV was not a serious problem in this study. Besides, we also based on VIF to test CMB. Table 5 show that all VIFs resulting from a full collinearity test were lower than 3.3, the model can be considered free of CMB. 455 Science & Technology Development Journal – Economics - Law and Management, 3(4):451-461 Table 2: Results summary of measurementmodels Latent variable Indicators Convergent validity Internal consistency reliability Discriminant validityLoadings Indicator reliability AVE Composite reliability Cronbach’s Alpha > 0.7 >0.5 > 0.5 0.6–0.95 0.6–0.95 PER PER1: ERP systems system has a positive impact on my productivity in my job 0.966*** 0.933 0.937 0.932 0.967 Yes PER2 : ERP systems is an important aid to me in the performance of my job 0.970*** 0.941 PU PU1 : Using ERP systems in my job increased my productivity 0.884*** 0.781 0.768 0.939 0.952 Yes PU2: I found ERP systems useful in my job 0.855*** 0.731 PU3: Using ERP systems improved my job performance 0.854*** 0.729 PU4: Using ERP systems enhanced my effectiveness on the job 0.913*** 0.834 PU5: Using ERP systems in my job enabled to accomplish tasks more quickly 0.900*** 0.810 PU6: Using ERP systems made it easier to do my job 0.849*** 0.721 CURR CURR: The data provide by ERP systems is up-to-date enough formy purposes 1.000 1.000 1.000 1.000 1.000 Yes RDAT RDAT: ERP systems available to me is missing critical data that are very useful to me in my job 1.000 1.000 1.000 1.000 1.000 Yes RDET RDET : ERP systemsmaintains data at an appropriate level of detail for my group’s tasks 1.000 1.000 1.000 1.000 1.000 Yes MEAN MEAN:The exact definition of data fields relating to my tasks is easy to find out 1.000 1.000 1.000 1.000 1.000 Yes EOU EOU1: It is easy to learn how to use ERP systems 0.953*** 0.908 0.912 0.904 0.954 Yes EOU2: ERP systems I use is conve- nient and easy to use 0.957*** 0.916 ***p <0.001. 456 Science & Technology Development Journal – Economics - Law and Management, 3(4):451-461 Table 3: Results of discriminant validity Mean SD CURR EOU MEAN PER PU RDAT RDET CURR 4.50 1.530 1.000 EOU 4.428 1.383 0.390 0.955 0.410 MEAN 4.62 1.346 0.387 0.535 1.000 0.387 0.562 PER 5.029 1.327 0.351 0.716 0.634 0.968 0.362 0.779 0.657 PU 5.231 1.157 0.314 0.576 0.532 0.767 0.876 0.324 0.621 0.547 0.817 RDAT 3.96 1.565 0.143 0.301 0.147 0.110 0.026 1.000 0.143 0.317 0.147 0.114 0.049 RDET 4.69 1.338 0.618 0.375 0.519 0.492 0.418 0.125 1.000 0.618 0.394 0.519 0.508 0.433 0.125 Number of the top rows: Fornell – Larcker criterion Number of the below rows: HTMT criterion Table 4: f2 and q2 effect sizes f2 effect sizes q2 effect sizes PER PU PER PU TTF 0.405 0.583 0.290 0.345 PU 0.546 0.404 Table 5: Collinearity statistic Construct VIF Task – technology fit (TTF) 1.583 Perceived usefulness (PU) 1.583 Table 6: Significance analysis of the direct and indirect effects Direct effect 95% confidence interval of the direct effect t value Signifi- cance (p<0.05)? Indirect effect 95% confidence interval of the indirect effect t value Significance (p < 0.05)? TTF -> PER 0.434 [0.314; 0.541] 7.326 Yes 0.306 [0.230; 0.394] 7.143 Yes 457 Science & Technology Development Journal – Economics - Law and Management, 3(4):451-461 DISCUSSION The results of this research supportedmost of the pro- posed relationships in the structural model. Most were consistent with the previous study results. Task – technology fit was significantly and positively re- lated to perceived usefulness and individual job per- formance in ERP environment (H1 and H2 are sup- ported). Perceived usefulness was significantly and positively related to individual job performance in ERP context (H3 is supported). In ERP context, Kositanurit et al.5 found that task – technology fit was the important factor bearing on in- dividual performance. The result of this study is simi- lar to the result ofKositanurit et al.5. Thenewfindings of this study are that we provided empirical evidence on the impact of task – technology fit to perceived use- fulness and of perceived usefulness to individual job performance in ERP environment. CONCLUSIONS This study added to the empirical evidence in the application of background theories including TTF, TAM and TTF models combined, DeLone and McLean IS Success Model, and ECM. Besides, the re- sults of this study also added to the theoretical back- ground of ERP’s success, namely, the individual job performance of employee in ERP context. Specifi- cally, factors including perceived usefulness and tasks and technology fit have a significant impact on the in- dividual job performance employee in ERP context. Furthermore, the results of this study help companies who are planning to use ERP systems and the ERP vendors and implementers become more knowledge- able about ERP’s success and forecast success when using ERP systems. In this study, the ERP success was measured by job performance of employee. The fac- tors that have been tested are the impact on the in- dividual job performance of employee in ERP context including perceived usefulness and tasks and technol- ogy fit. Based on these results, the enterprise can plan the application to improve the efficiency of ERP sys- tems. At the same time, the ERP vendors and devel- opers can better advise and support their customers when delivering and deploying ERP systems. This study has a few limitations. ERP implemen- tations are complex and take time to complete51,52. However, this study was restricted to the shakedown phase of the implementation, which is widely ac- knowledged to be the most critical in terms of con- tinuation or abandonment of ERP 53. It could be that these findings might change over time, with some support structures gaining or losing influence on the outcomes of interest. Work that gives greater consid- eration to time would enrich our understanding of this phenomenon. Thus, an area for possible future work would be to examine ERP implementations and support structures over a significantly longer period of time—that is, across all phases of an implementa- tion. Besides, this study collected data from ERP user in many kinds of enterprises; therefore, there is a re- striction related to applicability of this study for each specific enterprise group. This study chose an approach for the employee to as- sess his or her job performance in ERP context that is not evaluated by the supervisor of the employee. Fu- ture research should collect data through supervisors to measure the job performance of the employee in ERP context. ABBREVIATIONS AVE: Average variance extracted CMB: Common method bias CMV: Common method variance CR: Composite reliability ECM: Expectation–Confirmation Model EFA: Exploratory factor analysis ERP: Enterprise Resource Planning IS: Information system HTMT:Heterotrait-monotrait ratio of correlations PLS_SEM: Partial Least Squares Based Structural Equation Modeling TAM: Technology Acceptance model TTF: Task-Technology Fit theory UTAUT: Unified theory of acceptance and use of technology VIF: Variance inflation factor COMPETING INTERESTS The authors declare that they have no conflicts of in- terest. AUTHORS’ CONTRIBUTIONS Vo Van Nhi and Pham Tra Lam have contributed in conducting experiments, getting hold of data and writing the manuscript. Pham Tra Lam has contributed explanation of data and revising the manuscript. A. APPENDIX Cross loading 458 Science & Technology Development Journal – Economics - Law and Management, 3(4):451-461 CURR EOU MEAN PER PU RDAT RDET CURR 1.000 0.390 0.387 0.351 0.314 0.143 0.618 EOU1 0.358 0.953 0.480 0.633 0.503 0.311 0.328 EOU2 0.386 0.957 0.542 0.732 0.595 0.264 0.387 MEAN 0.387 0.535 1.000 0.634 0.532 0.147 0.519 PER1 0.290 0.694 0.626 0.966 0.721 0.110 0.418 PER2 0.386 0.692 0.601 0.970 0.762 0.103 0.531 PU1 0.251 0.513 0.467 0.723 0.884 0.044 0.379 PU2 0.239 0.420 0.442 0.633 0.855 -0.060 0.422 PU3 0.318 0.469 0.358 0.633 0.854 0.039 0.356 PU4 0.292 0.485 0.469 0.679 0.913 0.013 0.382 PU5 0.250 0.535 0.543 0.687 0.900 0.030 0.342 PU6 0.302 0.593 0.506 0.669 0.849 0.064 0.323 RDAT 0.143 0.301 0.147 0.110 0.026 1.000 0.125 RDET 0.618 0.375 0.519 0.492 0.418 0.125 1.000 REFERENCES 1. Wei CC, Wang MJJ. A comprehensive framework for selecting an ERP system. International journal of project management. 2004;22(2):161–169. 2. DeloneWH, Mclean ER. 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Mis Quarterly. 2010;34(1):134–161. 460 Tạp chí Phát triển Khoa học và Công nghệ – Kinh tế-Luật và Quản lý, 3(4):451-461 Open Access Full Text Article Bài nghiên cứu Trường Đại học Kinh tế TP.HCM Liên hệ Phạm Trà Lam, Trường Đại học Kinh tế TP.HCM Email: phamtralamais@ueh.edu.vn Lịch sử  Ngày nhận: 04/3/2019  Ngày chấp nhận: 13/5/2019  Ngày đăng: 31/12/2019 DOI : 10.32508/stdjelm.v3i4.587 Bản quyền © ĐHQG Tp.HCM. Đây là bài báo công bố mở được phát hành theo các điều khoản của the Creative Commons Attribution 4.0 International license. Vai trò của cảm nhận tính hữu dụng trongmối quan hệ giữa sự phù hợp giữa nhiệm vụ và công nghệ với kết quả công việc cá nhân trongmôi trường ứng dụng erp – bằng chứng từ các doanh nghiệp Việt Nam Võ Văn Nhị, Phạm Trà Lam* Use your smartphone to scan this QR code and download this article TÓM TẮT Mục tiêu của nghiên cứu này là xem xét vai trò của sự hữu ích trong mối quan hệ giữa kết quả công việc cá nhân và sự phù hợp giữa nhiệm vụ và công nghệ trong môi trường ứng dụng ERP. Nghiên cứu được thực hiện bằng các bảng khảo sát được trả lời bởi 225 cá nhân. Kết quả phân tích PLS_SEM cho thấy sự phù hợp giữa nhiệm vụ và công nghệ có tác động tích cực đáng kể đến cảm nhận tính hữu dụng và kết quả công việc cá nhân trong môi trường ERP. Ngoài ra, cảm nhận tính hữu dụng cũng có tác động đáng kể đến kết quả công việc cá nhân trongmôi trường ERP. Kết quả của nghiên cứu này đã bổ sung bằng chứng thực nghiệm trong việc áp dụng các lý thuyết nền tảng bao gồm các mô hình TTF, TAM và TTF kết hợp, mô hình thành công của hệ thống thông tin của DeLone và McLean và mô hình ECM. Bên cạnh đó, các kết quả này cũng bổ sung vào nền tảng lý thuyết về sự thành công trong ứng dụng ERP. Từ các kết quả nghiên cứu này, các công ty đang có kế hoạch sử dụng hệ thống ERP và các nhà cung cấp và triển khai ERP có các cơ sở lý thuyết vững chắc về sự thành công của ERP và dự báo sự thành công khi quyết định ứng dụng hệ thống ERP. Dựa trên những kết quả này, doanh nghiệp có thể lập kế hoạch ứng dụng để cải thiện hiệu quả của hệ thống ERP. Đồng thời, các nhà cung cấp và triển khai ERP có thể tư vấn và hỗ trợ khách hàng tốt hơn khi cung cấp và triển khai hệ thống. Từ khoá: Hoạch định nguồn lực doanh nghiệp (ERP), kết quả công việc, nhận thức tính hữu dụng, sự phù hợp giữa nhiệm vụ và công nghệ, Việt Nam Trích dẫn bài báo này: Nhị V V, Lam P T. Vai trò của cảm nhận tính hữu dụng trong mối quan hệ giữa sự phù hợp giữa nhiệm vụ và công nghệ với kết quả công việc cá nhân trong môi trường ứng dụng erp – bằng chứng từ các doanh nghiệp Việt Nam. Sci. Tech. Dev. J. - Eco. Law Manag.; 3(4):451-461. 461