بررسی اثر رضایت کاربر بر روی استفاده از سیستم و عملکرد فردی با سیستم های هوش کسب و کار (هوش تجاری) : مطالعه تجربی از صنعت الکترونیک در تایوان

The advent of new information technology has radically changed the end-user computing environment over the past decade. To enhance their management decision-making capability, many organizations have made significant investments in business intelligence (BI) systems. The realization of business benefits from BI investments depends on supporting effective use of BI systems and satisfying their end user requirements. Even though a lot of attention has been paid to the decision-making benefits of BI systems in practice, there is still a limited amount of empirical research that explores the nature of end-user satisfaction with BI systems. End-user satisfaction and system usage have been recognized by many researchers as critical determinants of the success of information systems (IS). As an increasing number of companies have adopted BI systems, there is a need to understand their impact on an individual end-user's performance. In recent years, researchers have considered assessing individual performance effects from IS use as a key area of concern. Therefore, this study aims to empirically test a framework identifying the relationships between end-user computing satisfaction (EUCS), system usage, and individual performance. Data gathered from 330 end users of BI systems in the Taiwanese electronics industry were used to test the relationships proposed in the framework using the structural equation modeling approach. The results provide strong support for our model. Our results indicate that higher levels of EUCS can lead to increased BI system usage and improved individual performance, and that higher levels of BI system usage will lead to higher levels of individual performance. In addition, this study's findings, consistent with DeLone and McLean's IS success model, confirm that there exists a significant positive relationship between EUCS and system usage. Theoretical and practical implications of the findings are discussed.

Today, many organizations continue to increase their investment in implementing various types of information systems (IS), such as enterprise resource planning (ERP) and customer relationship management (CRM), primarily because of the belief that these investments will lead to increased productivity for employees (Jain & Kanungo, 2005). Evaluating individual employee performance from IS use has been an ongoing concern in IS research (Goodhue & Thompson, 1995). However, previous studies that examined the relationship between IS usage and individual performance effects have reported contradictory results that range from positive to non-significant, to even a negative relationship. For instance, Goodhue and Thompson (1995) explored the role of task-technology fit on individual performance effects and indicated a positive relationship between IS use and individual performance. Conversely, Pentland (1989) found a negative relationship between IS use and individual performance. Lucas and Spitler (1999) found that IS use has no impact on individual performance. Many researchers have recognized user satisfaction as a critical determinant of the success of IS (Bailey and Pearson, 1983, DeLone and McLean, 1992, Doll and Torkzadeh, 1988 and Igbaria and Tan, 1997). When data computing in organizations has transformed from transactional data processing into end-user computing (EUC), Doll and Torkzadeh (1988) have developed a 12-item and five-factor instrument for measuring end-user computing satisfaction (EUCS) in the EUC environment. Even though EUCS instrument has already been widely applied and validated for various IS applications (e.g., decision support systems (McHaney et al., 1999 and Wang et al., 2007), ERP systems (Somers, Nelson, & Karimi, 2003), and online banking systems (Pikkarainen, Pikkarainen, Karjaluoto, & Pahnila, 2006), it has not been validated with users of business intelligence (BI) systems. BI systems were designed to provide decision-makers with actionable information delivered at the right time, at the right place, and in the correct form to make the right decisions (Negash & Gray, 2004). Given these goals, attributes measured by EUCS such as timeliness, accuracy, content, etc., are relevant to an evaluation of BI systems. Since an increasing number of companies have adopted BI systems, there is a need to understand the impact of EUCS on individual job performance. DeLone and McLean (2003) propose that higher levels of individual satisfaction with using an IS will lead to higher levels of intention to use, which will subsequently affect the use of the system. Most studies investigating system usage at the individual level terminate at the user acceptance of the computer technology rather than at the performance outcome (Dasgupta, Granger, & McGarry, 2002). The main reason could be attributed to the conventional wisdom that more use leads to better performance. However, empirical studies that examined the relationship between IS usage and individual performance effects have reported contradictory results ranging from positive to non-significant, to even a negative relationship. Therefore, the purpose of this study is to investigate whether it is appropriate to adopt the EUCS instrument to measure user satisfaction with BI systems. Furthermore, this study also examines the following research question: How does EUCS influence system usage and individual job performance? In this paper, we present a model that identifies the relationships between EUCS, system usage, and individual performance. Drawing on Igbaria and Tan's (1997) nomological net model, we propose that EUCS has a positive impact on individual performance both directly and indirectly through system use. Operational measures for the constructs are developed and tested empirically, using data collected from 330 respondents in the Taiwanese electronics industry to a survey questionnaire. Structural equation modeling is used to test the hypothesized relationships. The structure of this paper is organized as follows. In Section 2, we review the related literature on BI systems, EUCS, and performance measures to provide the necessary background information for the study. Section 3 presents the research framework and develops the hypothesized relationships, while Section 4 describes the research methodology. Section 5 presents the data analysis and results, which are discussed in Section 6. Section 7 presents implications for practice and research, and the final section describes the limitations of the study.

Empirical studies that investigated the relationship between IS usage and individual performance effects have reported contradictory results. The primary purpose of this study was to empirically examine the research framework, identifying the relationships between EUCS, system usage, and individual performance in the context of a BI system. We examine three research questions: (1) does there exist a significant positive relationship between EUCS and BI system usage; (2) does an individual with higher levels of BI system usage have higher levels of individual performance; and (3) does an individual with higher levels of EUCS have higher levels of individual performance? Based on survey data from 330 respondents in the Taiwanese electronics industry, the research framework was examined using structural equation modeling. Overall, these results provide strong empirical evidence that higher levels of EUCS lead to increased BI system usage and improved individual performance. This finding also confirms the argument of DeLone and McLean (2003), who suggest a significant bidirectional positive relationship between system use and user satisfaction so that the greater the use of the BI system, the more satisfied the user and the more satisfied the user, the greater the use of the BI system. Consistent with prior studies (Gelderman, 1998 and Igbaria and Tan, 1997), our research results indicate that higher levels of EUCS lead to improved individual performance by using BI systems. The strong and statistically significant impact of EUCS on individual performance supports the suggestion that user satisfaction may serve as a valid surrogate for individual performance (Iivari, 2005 and Ives et al., 1983). BI adoption in organizations helped individuals accomplish their tasks more effectively, increased their productivity, and improved their decision-making quality. Therefore, organizations can improve employee performance if the user has a higher level of user satisfaction with BI systems. In particular, the results demonstrate the importance of examining end-user computing satisfaction in explaining user performance.