MEASURES OF EXOGENOUS VARIBALBES 58

The model of this study has three exogenous variables: Information Quality, OSS EIS Quality, and Community Service Quality. The study developed the survey instrument for exogenous variables by adopting existing validated instruments wherever possible as well.

Information Quality is to measure the quality of OSS EIS outputs: namely, the quality of the information the system produces in reports and on-screen. Many recent studies indicated information quality as a success factor of IS (Rai et al., 2002; Shin, 2003; Gable et al., 2003; Wixom and Todd, 2005). Wixom and Todd (2005) defined completeness, accuracy, format, and currency as four information quality antecedents. Rai et al. (2002) measured information quality of IS by using seven items: accuracy, relevance, sufficiency, correctness, satisfaction, quality of output, and value of output. Shin (2003) investigated information quality dimension by measuring the utility (usefulness) of information acquired from a data warehouse. Some IS researchers have preferred to measure the quality of the information that the system produces, primarily in the form of reports.

Gable et al. (2003) used information quality as an IS success factor of enterprise systems. Bailey and Pearson (1983) identified 9 items to measure information quality: accuracy, precision, currency, timeliness, reliability, completeness, format, and relevance. King and Epstein (1983) also identified 9 similar items. Mahmood (1987) identified report accuracy and report timeliness as information quality measurements. Miller and Doyle (1987) found 4 items to measure information quality: completeness of information, accuracy of information, relevance of reports, and timeliness of report. Srinivasan (1985) identified report accuracy, report relevance, understandability, and report timeliness as measurements for information quality. Based on the literature, the present research adopts the three most frequently used items: timeliness, accuracy, and relevancy.

OSS EIS Quality is utilized to measure the performance of OSS EIS. This construct is equivalent to the system quality construct described in 2.5.1. Prior studies used system quality as a IS success factor (Rai et al., 2002; Shin, 2003; Gable et al., 2003; Sedera and Gable, 2004; Wixom and Todd, 2005; Sabherwal et al., 2006).

DeLone and McLean (2003) developed this construct to measure the quality of information system itself. It is based on Bailey and Pearson (1983)’s study that identified convenience of access (ease of use), flexibility of system, integration of systems, and response time. Wixom and Todd (2005) defined reliability, flexibility, integration, accessibility, and timeliness as the instruments to measure system quality. Rai et al. (2002) identified user friendliness and ease of use to measure system quality. Shin (2003) identified system throughput, ease of use, ability to locate data, access authorization, and data quality (currency, level of detail, accuracy, consistency) to measure system quality. Sabherwal et al. (2006) defined reliability, ease of use, and response time to measure

system quality. Their work separated user-related constructs and context-related constructs from the prior IS success model. They used system quality as a construct representing IS success.

Gable et al. (2003) found 10 items of system quality measurement from prior studies and used system quality as a construct in a study of EIS success. Sedera and Gable’s (2004) nine validated items to measure system quality for enterprise system success include: ease of use, ease of learning, user requirements, system fearues, system accuracy, flexibility, sophistication, integration, and customization. Belardo et al. (1982) identified reliability, response time, ease of use, and ease of learning; Srinivasan (1985) identified response time, reliability, and accessibility; Franz and Robey (1979) identified perceived usefulness of IS; Hiltz and Turoff (1981) and Goslar (1986) identified usefulness as measurements for system quality. Larcker and Lessig (1980) proved the validity and reliability of the perceived usefulness measure. The present research adopts the most frequently used items from the prior studies: response time, ease of use, and perceived usefulness.

Community Service Quality is to measure quality of community services that a user experiences. This construct is equivalent to service quality described in 2.5.3. OSS EIS communities include on-line communities or partners who provide OSS EIS and/or supports to organization. Shin (2003) defined user training to measure service quality. Yang et al. (2005) measured service quality by validating and using five validated instruments: usability, usefulness of content, adequacy of information, accessibility, and interaction.

The original model DeLone and McLean (1992) developed did not include service quality as an IS success factor. Pitt et al. (1995) argued that an IS success model should include a service component and they identified 5 items to measure service quality for IS effectiveness. Later, DeLone and McLean (2003) added service quality as a success measure in their IS success model. The present research adopts 5 measurement items from the studies done by Pitt et al. (1995) and DeLone and McLean (2003) based on SERVQUAL measurement instrument. Lee et al. (2009) adopted the same measurements for their study.

Since the present research concerns success factors of OSS EIS, it is necessary to incorporate OSS characteristics. OSS is developed in on-line communities by voluntary developers who may also provide maintenance and support, such as bug fixes. Because interactions between developers and users in on-line communities are observed, this study includes service quality as a construct for the OSS EIS success model. Questionnaire items suggested by DeLone and McLean (2003) are employed for Community Service Quality. The exogenous variables and the measurement methods are summarized in Table 3.3.