International Journal of Mechanical Engineering and Technology (IJMET) Volume 10, Issue 04, April 2019, pp. 199–211, Article ID: IJMET_10_04_022 Available online at http://www.iaeme.com/ijmet/issues.asp?JType=IJMET&VType=10&IType=4 ISSN Print: 0976-6340 and ISSN Online: 0976-6359 © IAEME Publication Scopus Indexed FACTORS OF INFORMATION SYSTEM SUCCESS: APPLIED DELONE AND MCLEAN MODEL WITH TECHNOLOGY ACCEPTANCE MODEL FOR SALES MANAGEMENT APPLICATION IN BANKING SECTOR OF INDONESIA Refa Nathanael Jusuf, Nilo Legowo, Taufik Samiaji, Deny Sundari Information Systems Management Department, Binus Graduate Program – Master of Information Systems Management, Bina Nusantara University, Jakarta Indonesia 11480 ABSTRACT The banking industry in Indonesia is developing using technology and one of the private bank in Indonesia uses technology to build Information Systems (IS). The purpose of this study is to evaluate information system success model for sales management application. The methodology used to this study is the Delone and McLean Model with the Technology Acceptance Model and added with the trust factor. The study hypothesis consists of 15 hypotheses, where system quality, information quality, service quality, and trust have an influence on perceived usefulness and perceived ease of use. Then, perceived usefulness and perceived ease of use through attitude toward using, behavioral intention to use, actual system usage, user satisfication have an influence on net benefit. Data obtained from employees that are distributed to the private bank employees. The number of employees in this study are 360 respondent. The results of this study are known to have three hypotheses rejected, namely: service quality has no effect on perceived usefulness, service quality has no effect on perceived ease of use, and trust has no effect on perceived usefulness. Keywords: Evaluation, Sales Mobile Application, Delone & McLean, Technology Acceptance Model, Bank. Cite this Article: Refa Nathanael Jusuf, Nilo Legowo, Taufik Samiaji and Deny Sundari, Factors of Information System Success: Applied Delone and Mclean Model with Technology Acceptance Model For Sales Management Application In Banking Sector of Indonesia, International Journal of Mechanical Engineering and Technology 10(4), 2019, pp. 199–211. http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=10&IType=4 http://www.iaeme.com/IJMET/index.asp 199 editor@iaeme.com Factors of Information System Success: Applied Delone and Mclean Model with Technology Acceptance Model For Sales Management Application In Banking Sector of Indonesia 1. INTRODUCTION The development of technology in Indonesia grows rapidly. The banking industry in Indonesia is transforming by utilizing technology. Investments in technology have a significant impact on the banking industry. There are several factors that are key to the transformation of banks in Indonesia. Technology and customer needs are the most influential key factors for banks to transform [1]. Table 1 Bank Transformation Factors in Indonesia Category Percentage (%) Technology Customer Needs Competition Operational Others 43 34 14 6 3 As the banking sector expanded, the number of banks continues to increase and along with the development of technology, bank services changed. Investment banks in large quantities for the decision support systems and banks need a competitive system on the market and make better decisions [2] and banks invest in large volumes to adjust all changes, but the return on investment is still a constant debate [3]. IS are the main drivers for starting business changes within the organization and are considered very important for running an efficient and effective modern business [4]. The private bank implements a mobile-based IS for their employees by utilizing technology. After the application is implemented, there are a lot of problem reported by the user. The application crashes when it is being accessed, slow response when retrieving data, and user failed to login into the application with an error message “Network Error”. The Figure 1 represent total incidents when the application crashes and The Figure 2 respresent total incidents when the application give an error message “Network Error”. Both of incidents taken from October 2017 until March 2018. Figure 1 Total Incidents When The Application Crashes Figure 2 Total Incidents When The Application Give An Error Message “Network Error” From the two figures above, it can be seen that many incidents occurred for these two problems. This problem can be annoying when users want to use the application to get data information or process data. It must be wise to evaluate the success of a system, given that investing in an information system project costs a lot and does not always guarantee success [5]. Considering the high investment in IT, the success of investment and the quality of the system developed are the most important for research and practitioners [6]. http://www.iaeme.com/IJMET/index.asp 200 editor@iaeme.com Refa Nathanael Jusuf, Nilo Legowo, Taufik Samiaji and Deny Sundari Evaluation is the process of providing information designed to help make decisions about the object being evaluated [7]. Evaluation is a series of techniques that facilitate decision making with the aim of achieving the best results for the organization [8]. Measurement of effectiveness against the success of information systems is an important problem for practitioners and researchers. Measurement of success is very important to understand the value of information systems and investments of information systems [9]. Researcher will conduct a case study to evaluate information system success model for sales management application. 2. METHODS Researcher focus to evaluating IS success and searching the best model for the bank. Researcher adopted the integrated IS success model and added trust variable to the model. The integrated IS success model is generated by encompassing the fundamental theories of both the Technology Acceptance Model and the Delone & McLean Update IS Success Model is proposed [10]. The discussion starts with an introduction of Technology Acceptance Model, Delone & McLean IS Success Model, Integreted IS Success Model, Trust Factor, The Research Model, Hypothesis, Measurement of The Variables, Population and Sample, and Data Collection. 2.1. Technology Acceptance Model (TAM) Technology Acceptance Model consists of six dimensions: External Variables, Perceived Usefulness, Perceived Ease of Use, Attitude Toward Using, Behavioral Intention to Use, and Actual System Use [11]. TAM is a model for predicting rather than describing, which is used to predict the acceptance of the system by the user. This model proposes that when users are offered to use a new system, a number of factors influence their decisions about how and when to use the system, especially in terms of usefulness and ease of use [12]. TAM starts by proposing external variables as the basis for tracing the impact of external factors on two main internal beliefs, which are perceived usefulness and perceived ease of use, while perceived ease of use also affects perceived usefulness over and above external variables [13]. 2.2. Delone & McLean Information System Success Model The original model of Delone & McLean was founded in 1992. The main purpose of this model was to “identify those factors that contribute to information systems success” [14]. They identified six dimensions of information systems success: Information Quality, System Quality, Use, User Satisfaction, Individual Impact and Organizational Impact. “System quality” refers to the performance of an IS system itself, while “Information quality” refers to how good is the output from a particular IS system. “Use” is used to measure how well the output of the IS system, such as information or physical reports, are used. “User satisfaction” represents users’ overall comments on the IS system. “Individual impact” that Delone and McLean address here refers to the influence of the outputs of IS systems on individual users’ behaviors, while “Organizational impact” refers to the effects of the usage of IS systems on the organizational performance. It is proposed that Information quality and System quality have influence on both Use and User satisfaction. Use and User satisfaction affects Individual impact, and Individual impact in terms influences Organizational impact. One thing needs to be addressed is that the model was built based on a process nature, and the focus while utilizing this model should be to examine how these six categories of factors are http://www.iaeme.com/IJMET/index.asp 201 editor@iaeme.com Factors of Information System Success: Applied Delone and Mclean Model with Technology Acceptance Model For Sales Management Application In Banking Sector of Indonesia interrelated and interdependent with one another instead of concerning the causal relationships among them [10]. In 2003, Delone & McLean refined the original IS success model in response to feedback received from other scholars working in the area [15]. Delone and McLean slightly modify their original model by including some factors that are newly considered important for evaluating IS success. In Delone and McLean’s update model, they do not separately consider about individual impact, organizational impact, and some other kinds of emerging impact measures, such as work group impact and consumer impact. On the contrary, Delone and McLean use the term “net benefits” to represent all the impact measures for the sake of simplifying the model. In addition, Delone and McLean think the variable “use” in their original model is defined without considering the actual complexity of the usage behaviors. They realize that perspective system users, especially the e-commerce system users, are not always required to use the system. The usage of the systems performed by these users may not be able to totally represent the complex conception of “use” for the purpose of evaluating net benefits under certain circumstances. They suggest “intention to use” as an alternative of “use” for some particular circumstances in their update model [10]. The Delone and McLean model is implemented to provide a general and comprehensive definition of IS success that includes different perspectives in evaluating IS. This model review the definitions of the success of existing IS and appropriate actions, and classify them into six main categories [3]. 2.3. Integration of TAM and Delone & McLean Information System Success Model Researcher adopted the integrated IS success model by Wang & Liu because it is comprehensive and solid model for evaluating IS success model. The model is combination both of TAM and Delone & McLean. TAM focus how users to accept and use a technology and Delone & McLean focus in net benefits received by the users. TAM and Delone & McLean have their own strenghts and weakness in evaluating IS success. The new model is built by taking three variables, system quality, information quality, and service quality from Delone & McLean IS success model. In the new model, Wang & Liu include variables perceived usefulness and perceived ease of use because both of them have direct influence on system usage. They replace intention to use / use with the three factors that are proposed in TAM for evaluating system usage, which are attitude toward using, behavioral intention to use, and actual system usage. Wang & Liu keep the variable user satisfaction because that actual system usage has direct impact on both user satisfaction and the overall benefits that are generated by the implementation of the information system, and user satisfaction also directly affects the overall benefits.They suggest that user satisfaction has direct influence on perceived ease of use and perceived usefulness, and in turn affects actual system usage indirectly. 2.4. Trust Factor Researcher feels the model that proposed by Wang & Liu is not suitable enough for the banking sector. In the banking sector, trust is really important and can give a big impact to the IS success. Building trust is based on a feeling of security and system security, resulting in a positive attitude towards the system [16]. Trust is the desire to be vulnerable to the actions of others and the desire to depend on others [17]. http://www.iaeme.com/IJMET/index.asp 202 editor@iaeme.com Refa Nathanael Jusuf, Nilo Legowo, Taufik Samiaji and Deny Sundari Trust factors have a positive and significant impact on perceived ease of use and perceived usefulness. Trust factors can potentially influence user interest in using information systems [18]. Trust factors have a positive and significant impact on customer satisfaction and customer loyalty. User or customer satisfaction can be assumed to determine net benefits or individual impacts [19]. 2.5. The Research Model This study adopted The Integrated IS Success Model which combination of TAM and Delone & McLean. The researcher also added trust factor into the model and modify the relationship between variables which suitable for the bank for assessing IS success. The researcher added trust factor into the model because the employees will store and process very sensitive data related to their customer from the application. The trust factor becomes very important because the employees does not know whether the information entered is stored correctly and can only be accessed by people who have the right to access the information. If the employees have a small trust, then the information entered will be less information while the information is needed to analyze and help the bank to determine the strategy. The research model to evaluate IS success shown below in Figure 3. Figure 3 The Research Model 2.6. Hypothesis Researcher have developed hypothesis to test the research model. The following 15 hypothesis will be tested: H1 There is a significant positive relationship between System Quality and Perceived Usefulness. H2 There is a significant positive relationship between System Quality and Perceived Ease of Use. H3 There is a significant positive relationship between Information Quality and Perceived Usefulness. H4 There is a significant positive relationship between Information Quality and Perceived Ease of Use. H5 There is a significant positive relationship between Service Quality and Perceived Usefulness. H6 There is a significant positive relationship between Service Quality and Perceived Ease of Use. H7 There is a significant positive relationship between Trust and Perceived Usefulness. H8 There is a significant positive relationship between Trust and Perceived Ease of Use. H9 There is a significant positive relationship between Trust and User Satisfication. http://www.iaeme.com/IJMET/index.asp 203 editor@iaeme.com Factors of Information System Success: Applied Delone and Mclean Model with Technology Acceptance Model For Sales Management Application In Banking Sector of Indonesia H10 There is a significant positive relationship between Perceived Usefulness and Attitude Toward Using. H11 There is a significant positive relationship between Perceived Ease of Use and Attitude Toward Using. H12 There is a significant positive relationship between Attitude Toward Using and Behavioral Intention to Use. H13 There is a significant positive relationship between Behavioral Intention to Use and Actual System Usage. H14 There is a significant positive relationship between Actual System Usage and User Satisfication. H15 There is a significant positive relationship between User Satisfication and Net Benefit. 2.7. Measurement of The Variables This study is measures with data on IS success and technological factors. A selection of indicators is that they have been used frequently in IS research as a measure of IS success. The following indicators will be used: System Quality is measured by Access, Reliability, System Features, and Response Time [6][20]. Information Quality is measured by Accuracy, Understandability, Consistency, and Completeness [6] [20]. Service Quality is measured by IS Training, and Responsiveness [21]. Trust was measured by Privacy, and Security [18]. Perceived Usefulness is measured by Effectiveness, Increase Productivity, Work More Quickly, Makes Job Easier, Job Performance, and Useful [11]. Perceived Ease of Use is measured by Clear & Understandable, Easy to Use, Controllable, Easy to Learn, Flexible, and Easy to Become Skillful [11]. Attitude Toward Using is measured by Fun, and Enjoy [22]. Behavioral Intention to Use is measured by Use, and Plan [23]. Actual System Usage is measured by Duration, and Frequency [24]. User Satisfication is measured by Effectiveness, Efficiency, and Overall Satisfaction [25]. Net Benefit is measured by Job Effectiveness, Job Simplification, Productivity, and Decision Effectiveness [6][20]. 2.8. Population and Sample The population of this study consisted of employees who used sales management application in the bank. The total employees from all regions in Indonesia are 360 employees. 2.9. Data Collection This study used a survey to collect data to test the relationships shown in the research model. The survey was conducted from August to October 2018. The survey method is required to be the most suitable method for this study to test the relationships. This study used five point Likert scale to represent the responses, whereas scale from 5 (highly agree or satisfied) to 1 (highly disagree or satisfied). A total of 360 questionnaires was distributed, but only 205 questionnaires used for analysis at 57% from total questionnaires. http://www.iaeme.com/IJMET/index.asp 204 editor@iaeme.com Refa Nathanael Jusuf, Nilo Legowo, Taufik Samiaji and Deny Sundari 3. RESULT AND DISCUSSION The analysis of the retrieved survey data is based on SmartPLS 3. The result below in Figure 4. Researcher will use a lot of techniques to validate the IS success model. For example, the validity will be measured by using factor loading and average variance extracted, the reability will be measured by using composite reability and cronbach’s alpha. Finally, the multiple regression analysis was used to further explain the significance of the independent and dependent variables of hypothesis. Figure 4 The Research Result 3.1. Demographic Analysis A summary of the demographic characteristics from the employees is shown in below Table 2. Table 2 The Demographic Characteristics Age Gender Educational Level Working Experience Using Application Experience <= 20 21 – 30 31 – 40 >= 41 Male Female Bachelor’s Master’s <= 1 Year 1 Year – <= 3 Years 3 Years – <= 7 Years > 7 Years <= 1 Month 2 – 6 Months 7 – 12 Months > 12 Months http://www.iaeme.com/IJMET/index.asp Frequency (N = 205) 1 81 113 10 132 73 197 8 24 Percentage (%) 0.5 39.5 55.1 4.9 64.2 35.8 96.3 3.7 11.5 79 38.7 101 49.4 1 13 11 147 34 0.4 6.2 5.2 71.6 16.5 205 editor@iaeme.com Factors of Information System Success: Applied Delone and Mclean Model with Technology Acceptance Model For Sales Management Application In Banking Sector of Indonesia Respondents to age ranged from 20 to more than 41 years of age, approximately 60% above 31 years and 40% between 20 to 30 years. According to gender Men is more respondents than Women (Men 64.2% and Women 35.8%) and from educational level, bachelor’s is the highest degree with 96.3%. Respondents working experience approximately 49.8% above of 3 years and 50.2% less than 3 years. Respondents experience when using application approximately 88,1% above of 6 months and 11,9% less than 7 months. 3.2. Validity Test Validity test is conducted in this study using the all questions in the questionnaire, this test will divided by two test which are Convergent Validity and Discriminant Validity. 3.2.1 Convergent validity Researcher used factor loading value to determine the convergent validity. The factor loading value must be greater than 0.5 and ideally it is 0.7 or greater [26]. If the factor loading value is greater than 0.7, then the variable is valid and if the factor loading value is smaller than 0.7, then the variable is invalid. The result is shown in below Table 3. Table 3 The Convergent Validity Variables System Quality Information Quality Service Quality Trust Perceived Usefulness Perceived Ease of Use Attitude Toward Using Behavioral Intention to Use Actual System Usage User Satisfication Net Benefit SQ1 SQ2 SQ3 SQ4 IQ1 IQ2 IQ4 RQ1 RQ2 TR1 TR2 PU1 PU2 PU3 PU4 PU5 PU6 PE3 PE4 PE6 AU1 Factor Loadings 0.730 0.729 0.770 0.825 0.876 0.872 0.861 0.897 0.884 0.935 0.941 0.766 0.833 0.881 0.920 0.857 0.733 0.930 0.945 0.860 0.962 AU2 0.962 0.700 Valid IU1 0.944 0.700 Valid IU2 0.938 0.700 Valid SU1 1.000 0.700 Valid US1 US2 US3 NB1 NB2 NB3 NB4 0.894 0.947 0.924 0.899 0.917 0.857 0.868 0.700 0.700 0.700 0.700 0.700 0.700 0.700 Valid Valid Valid Valid Valid Valid Valid Code http://www.iaeme.com/IJMET/index.asp 206 Coefficient Result 0.700 0.700 0.700 0.700 0.700 0.700 0.700 0.700 0.700 0.700 0.700 0.700 0.700 0.700 0.700 0.700 0.700 0.700 0.700 0.700 0.700 Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid editor@iaeme.com Refa Nathanael Jusuf, Nilo Legowo, Taufik Samiaji and Deny Sundari The result indicate that the convergent validity for the dimensions of IS success ranged between (0.729 – 1.000) and the average is (0.879). These values are considered acceptable for the purposes of this study. 3.2.2. Discriminant validity Researcher used average variance extracted (AVE) value to determine the discriminant validity. The AVE value must must be greater than 0.5 but can still be accepted if it is greater than 0.4 [27]. If AVE value is greater than 0.5, then the variable is valid and if the factor loading value is smaller than 0.5, then the variable is invalid. The result is shown in below Table 4. Table 4 The Discriminant Validity Variables System Quality Information Quality Service Quality Trust Perceived Usefulness Perceived Ease of Use Attitude Toward Using Behavioral Intention to Use Actual System Usage User Satisfication Net Benefit AVE 0.585 0.757 0.793 0.880 0.696 0.833 0.925 0.886 1.000 0.850 0.785 Coefficient 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.500 Result Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid The result indicate that the discriminant validity for the dimensions of IS success ranged between (0.585 – 1.000) and the average is (0.817). These values are considered acceptable for the purposes of this study. 3.3. Reability Test Researcher used composite reability value and cronbach’s alpha for assessing reliability. The composite reability value must be greater than 0.7 [28] and the recommendation for the cronbach's alpha value is 0.7 or it can be more [29]. If the composite reability or cronbach’s alpha value is greater than 0.7, then the variable is reliable and if the composite reability or cronbach’s alpha value is smaller than 0.7, then the variable is not reliable. The result is shown in below Table 5. Table 5 The Reability Test Variables System Quality Information Quality Service Quality Trust Perceived Usefulness Perceived Ease of Use Attitude Toward Using Behavioral Intention to Use Actual System Usage User Satisfication Net Benefit Composite Reablility 0.849 0.903 0.885 0.936 0.932 Cronbach’s Alpha Coefficient Result 0.767 0.842 0.740 0.864 0.911 0.700 0.700 0.700 0.700 0.700 Reliable Reliable Reliable Reliable Reliable 0.937 0.899 0.700 Reliable 0.961 0.919 0.700 Reliable 0.939 0.871 0.700 Reliable 1.000 0.936 0.785 1.000 0.911 0.909 0.700 0.700 0.700 Reliable Reliable Reliable http://www.iaeme.com/IJMET/index.asp 207 editor@iaeme.com Factors of Information System Success: Applied Delone and Mclean Model with Technology Acceptance Model For Sales Management Application In Banking Sector of Indonesia The result indicate that the composite reability for the dimensions of IS success ranged between (0.785 – 1.000) and the average is (0.915) and the result for the cronbach’s alpha for the dimensions of IS success ranged between (0.740 – 1.000) and the average is (0.872). These values are considered acceptable for the purposes of this study. 3.4. Hypothesis Test After all data are declared valid and reliable (based on the validity test and the reliability test), it can be said that the data is feasible to be processed in the next stage to test the hypothesis. P Value can also be interpreted as the amount of opportunity to make a mistake if we decide to reject H0. In general, P Value is compared to a certain level, usually 0.05 or 5%. If P Value is smaller than 0.05 then reject H0 (The hypothesis has a significant effect) and P Value is greater than 0.05 then accept H0 (The hypothesis does not have a significant effect) [30]. For t table with as many as 205 respondents and a significance level of 0.05, then the t table is 1.971, meaning that if t table> t result then H0 is accepted and H1 is rejected. Based on the hypothesis test, it can be concluded that there are 3 rejected hypothesis and 12 acceptable hypothesis. The result is shown in below Table 6. Table 6 The Hyphotesis Test H1 H2 H3 H4 H5 H6 H7 H8 H9 H10 H11 H12 H13 H14 H15 Original Sample 0.200 0.156 0.357 0.337 0.070 0.034 0.150 0.246 0.265 0.489 0.383 0.790 0.565 0.451 0.858 Sample Mean 0.207 0.160 0.350 0.338 0.073 0.035 0.147 0.245 0.266 0.484 0.387 0.789 0.565 0.450 0.858 Standard Deviation 0.086 0.066 0.070 0.075 0.082 0.072 0.091 0.084 0.066 0.065 0.066 0.032 0.065 0.076 0.022 T Statistics P Values 2.324 2.383 5.095 4.522 0.857 0.465 1.639 2.946 4.029 7.548 5.788 24.888 8.695 5.953 39.802 0.020 0.017 0.000 0.000 0.392 0.642 0.101 0.003 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Result Accepted Accepted Accepted Accepted Rejected Rejected Rejected Accepted Accepted Accepted Accepted Accepted Accepted Accepted Accepted Most of the hypotheses proposed are positive and significant, and the results confirm the main goals of this study. But not all of these results are consistent with the prior literature due to special condition at the private bank. Twelve hypothesis are accepted due to the p values are lower than 0.05 and the t values are higher than 1.971. The result are consistent with the references. Three hypothesis (H5, H6, H7) are rejected due to the p values are higher than 0.05 and the t values are lower than 1.971. In this case, when the employees have a problem with their application, the problem is not responded quickly and it takes a long time to resolve the problem and the bank does not provide training on how to use sales management applications to the employees. Other than that, the bank is not transparent to the employees regarding the policies that have been made for the application. http://www.iaeme.com/IJMET/index.asp 208 editor@iaeme.com Refa Nathanael Jusuf, Nilo Legowo, Taufik Samiaji and Deny Sundari 4. CONCLUSION This study explores the relationship between IS quality (system quality, information quality, service quality), and trust with a net benefit. Our results indicate that most variables provided a sufficient contribution for prediction of the dependent variable. IS quality dimensions (system quality and information quality) have a significant positive influence on perceived usefulness and perceived ease of use. But, service quality does not has a significant positive influence on perceived usefulness and perceived ease of use. Trust has a significant positive influence on perceived ease of use and user satisfaction but does not has a significant positive influence on perceived usefulness. Perceived usefulness and perceived ease of use have a significant positive influence on attitude toward using. Attitude toward using has a significant positive influence on behavioral intention to use. Behavioral intention to use has a significant positive influence on actual system usage. Actual system usage has a significant positive influence on user satisfication. Finally, user satisfication has a significant positive influence on net benefit. The result of the study also can be used by another researcher to develop high quality of information system success model. This study contributes the new model of IS success. The model presents IS quality dimensions (system quality, information quality, and service quality) with trust factor, which the trust factor is very imporant in the banking sector. These contributions are expected to give benefits to all of researchers and practitioners. Researchers can benefit by applying the new integrated information system success model in the similar sector and also modify the model with another adjustment based on needs from the research sector. Risk factor and customer / user needs factor can be added to the research model so that the research model becomes more comprehensive for evaluating information system success. REFERENCES [1] [2] [3] [4] [5] [6] [7] [8] PwC. (2018). 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