Teaching Information Quality in Information Systems Undergraduate Education
| Autor: | Omar E. M. Khalil, Diane M. Strong, Leo L. Pipino, Beverly K. Kahn |
|---|---|
| Rok vydání: | 1999 |
| Předmět: |
Service quality
Total quality management Knowledge management lcsh:T58.5-58.64 lcsh:Information technology business.industry Computer science media_common.quotation_subject Information quality Library and Information Sciences Competitive advantage Data quality Information system Quality (business) Relevance (information retrieval) business media_common |
| Zdroj: | Informing Science The International Journal of an Emerging Transdiscipline, Vol 2, Pp 053-059 (1999) Informing Science The International Journal of an Emerging Transdiscipline, Vol 2, Iss 3, Pp 53-59 (1999) |
| ISSN: | 1521-4672 1547-9684 |
| DOI: | 10.28945/601 |
| Popis: | Introduction Poor data and information quality can have a significant negative impact on organizations' success. Consequently, organizations are implementing programs to improve data quality to achieve competitive advantage (Redman 1995; 1996). Such improvement programs are critical for the development and maintenance of data warehouses, which are being built by organizations to improve customer service and managerial decision making. Without proper data quality processes, the data warehouse will begin to accumulate "dirty data" (Garcia 1997). The expectations of information consumers (people who use information) go beyond accurate and factually correct data. Information consumers expect the information custodians (IS professionals responsible for managing the organization's data and information resources) to provide systems (1) that are responsive, (2) that deliver relevant and easily interpreted information, (3) that provide flexible, easily aggregated, and easily manipulated data, and (4) that are secure and robust enough to prohibit accidental or intentional data corruption (Mathieu and Khalil 1997; Strong, Lee and Wang 1997a). As a consequence, IS professionals must seek not only to improve data accuracy, but also to ensure information accessibility and relevance as it relates to the context of the information consumers' tasks (Wang and Strong 1996; Strong, Lee and Wang 1997b). Few IS professionals, however, have received formal training in specific techniques to maintain and improve information quality. What techniques they are taught are often presented in an ad hoc way as part of technical IS courses. For example, they may learn about concepts such as entity integrity and referential integrity that contribute to information quality. The important issue of information quality (IQ) is not addressed directly in most IS curriculum models. IS curricula in most universities give it little attention and leave the teaching of IQ to individual faculty preferences and initiatives. At best, IS students are exposed to topics that impact IQ, but they are not equipped with a broad understanding of the principles behind measuring, analyzing and improving IQ in an organization. Further, IS students do not receive instruction on the overall role of IQ in the design and implementation of information systems, databases, and data warehouses (Mathieu and Khalil 1997). This comes at a time when IS professionals are increasingly becoming responsible for their organization's IQ. There appears to be a mismatch between the needs of organizations for delivering high-quality information to information consumers and the skills of new IS professionals graduating from universities in business and management programs. This paper examines this mismatch in detail and makes recommendations on closing the gap and improving IQ teaching and learning. A Model of Information Quality High quality information is information that is fit for use by information consumers (Strong, Lee and Wang 1997b). This definition follows directly from the standard fitness-for-use definition for products and services (Deming 1986; Juran and Gryna 1988; Figenbaum 1991). The Product and Service Performance Model for Information Quality (PSP/IQ Model), shown in Table 1, captures the key quality aspects that are relevant to delivering high-quality information (Kahn and Strong 1998; Kahn, Strong and Wang Forthcoming). It operationalizes the general fitness-for-use definition of IQ. The PSP/IQ Model is based on constructs from two traditional disciplines. The first is that of total quality management in which two views of quality performance goals are prevalent: quality as conformance to specifications and quality as meeting or exceeding consumer expectations (Reeves and Bednar 1994). The second discipline is that of marketing which distinguishes between product quality and service quality, e.g., (Zeithaml, Berry and Parasuraman 1990). … |
| Databáze: | OpenAIRE |
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