The Role of Enterprise Resource Planning Systems (ERP) in Organizational Productivity Case Study: Tabriz Tractor Manufacturing Company

Subject Areas : Biannual Journal of Value Chain Management

batool zareie ¹

1 - باشگاه پژوهشگران جوان و نخبگان، واحد تبریز، دانشگاه آزاد اسلامی، تبریز، ایران.

Received: 2016-04-02 Accepted : 2016-06-13 Published : 2016-05-21

Keywords: productivity, Flexibility, Enterprise Resource Planning, Resource optimization,

Abstract :

Abstract Enterprise resource planning (ERP) systems integrate all business recording and reporting processes into one single management information system. ERP systems require a great degree of coordination and complex technological infrastructure within a firm. ERP systems are described as computer-based information systems designed to facilitate an organization’s transactions, integrate and planning real-time, production and response to the customer. Organizations implement ERP to improve operational efficiency and effectiveness of their business. Though, some of them faile to apply it properly and acheive desirable productivity level. In this paper, the literature and ERP features reviewed using existing theoretical studies. A model and framework provided for assessing the impact of ERP systems on productivity of organization. The Cronbach’s coefficient of each variable and compiste reliability (CR) were greater than 0.8.  Aslo the average variance extracted (AVE) values were greater than 0.5. The three conditions of this study were coincident with good convergent validity. Findings from the study confirmed the validity of the proposed model and acceptance of all the hypothesis.

References:

• Amid, A., Moalagh, M., & Zare Ravasan, A. (2012). Identification and classification of ERP critical failure factors in Iranian industries. Information Systems, 37(3), 227-237.


• Bernard Grabot , A. M., Fabien Lauroua , Raymond Houe (2013). ERP 2.0, what for and how? Computers in Industry, 976-1000.


• Bi, R., Wei, J., & Chen, R. (2007). ERP Sandtable simulation evaluation based on ANP. Paper presented at the IEEE International Conference on Industrial Engineering and Engineering Management.


• Chang, J. Y., Wang, E. T., Jiang, J. J., & Klein, G. (2013). Controlling ERP consultants: Client and provider practices. Journal of Systems and Software, 86(5), 1453-1461.


• Chen, H.-R., & Tseng, H.-F. (2012). Factors that influence acceptance of web-based e-learning systems for the in-service education of junior high school teachers in Taiwan. Evaluation and program planning, 35(3), 398-406.


• Cheng, H.-H., & Yang, H.-L. (2014). The antecedents of collective creative efficacy for information system development teams. Journal of Engineering and Technology Management, 33, 1-17.


• Chou, H.-W., Chang, H.-H., Lin, Y.-H., & Chou, S.-B. (2014). Drivers and effects of post-implementation learning on ERP usage. Computers in Human Behavior, 35, 267-277.


• Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334.


• Dalveren, Y. (2014). Using e-learning in enterprise resource planning (ERP) training: a case study to assist curriculum designers in Turkey. Procedia-Social and Behavioral Sciences, 116, 1353-1357.


• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 39-50.


• Galy, E., & Sauceda, M. J. (2014). Post-implementation practices of ERP systems and their relationship to financial performance. Information & Management, 51(3), 310-319.


• Gumussoy, C., Calisir, F., & Bayram, A. (2007). Understanding the behavioral intention to use ERP systems: An extended technology acceptance model. Paper presented at the Industrial Engineering and Engineering Management, 2007 IEEE International Conference on.


• Huang, Y.-M., Huang, Y.-M., Huang, S.-H., & Lin, Y.-T. (2012). A ubiquitous English vocabulary learning system: Evidence of active/passive attitudes vs. usefulness/ease-of-use. Computers & Education, 58(1), 273-282.


• Kumar, A., & Gupta, P. (2012). Identification and Analysis of Failure Attributes for an ERP System. Procedia-Social and Behavioral Sciences, 65, 986-991.


• Moon, Y. B. (2007). Enterprise Resource Planning (ERP): a review of the literature. International Journal of Management and Enterprise Development, 4(3), 235-264.


• Navimipour, N. J., & Zareie, B. (2015). A model for assessing the impact of e-learning systems on employees’ satisfaction. Computers in Human Behavior, 53, 475-485.


• Nunnally, J. (1978). Psychometric methods. New York: McGraw.


• Parthasarathy, S., & Sharma, S. (2014). Determining ERP customization choices using nominal group technique and analytical hierarchy process. Computers in Industry, 65(6), 1009-1017.


• Rouhani, S., & Zare Ravasan, A. (2013). ERP success prediction: An artificial neural network approach. Scientia Iranica, 20(3), 992-1001.


• Ruivo, P., Oliveira, T., & Neto, M. (2014). Examine ERP post-implementation stages of use and value: Empirical evidence from Portuguese SMEs. International Journal of Accounting Information Systems, 15(2), 166-184.


• Sadrzadehrafiei, S., Chofreh, A. G., Hosseini, N. K., & Sulaiman, R. (2013). The Benefits of Enterprise Resource Planning (ERP) System Implementation in Dry Food Packaging Industry. Procedia Technology, 11, 220-226.


• Teittinen, H., Pellinen, J., & Järvenpää, M. (2013). ERP in action—Challenges and benefits for management control in SME context. International Journal of Accounting Information Systems, 14(4), 278-296.


• Tenhiälä, A., & Helkiö, P. (2014). Performance Effects of Using an ERP System for Manufacturing Planning and Control under Dynamic Market Requirements. Journal of Operations Management.


• Wetzels, M., Odekerken-Schröder, G., & Van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS quarterly, 177-195.