Ex ante evaluations of alternate data structures for end user queries: Theory and experimental test

The data structure of an information system can significantly impact the ability of end users to efficiently and effectively retrieve the information they need. This research develops a methodology for evaluating, ex ante, the relative desirability of alternative data structures for end user queries. This research theorizes that the data structure that yields the lowest weighted average complexity for a representative sample of information requests is the most desirable data structure for end user queries. The theory was tested in an experiment that compared queries from two different relational database schemas. As theorized, end users querying the data structure associated with the less complex queries performed better Complexity was measured using three different Halstead metrics. Each of the three metrics provided excellent predictions of end user performance. This research supplies strong evidence that organizations can use complexity metrics to evaluate, ex ante, the desirability of alternate data structures. Organizations can use these evaluations to enhance the efficient and effective retrieval of information by creating data structures that minimize end user query complexity.

The effects of normalisation on the ability of business end-users to detect data anomalies: An experimental evaluation

With the proliferation of relational database programs for PC's and other platforms, many business end-users are creating, maintaining, and querying their own databases. More importantly, business end-users use the output of these queries as the basis for operational, tactical, and strategic decisions. Inaccurate data reduce the expected quality of these decisions. Implementing various input validation controls, including higher levels of normalisation, can reduce the number of data anomalies entering the databases. Even in well-maintained databases, however, data anomalies will still accumulate. To improve the quality of data, databases can be queried periodically to locate and correct anomalies. This paper reports the results of two experiments that investigated the effects of different data structures on business end-users' abilities to detect data anomalies in a relational database. The results demonstrate that both unnormalised and higher levels of normalisation lower the effectiveness and efficiency of queries relative to the first normal form. First normal form databases appear to provide the most effective and efficient data structure for business end-users formulating queries to detect data anomalies.

Reliability factors in business software: volatility, requirements and end-users

Many business-oriented software applications are subject to frequent changes in requirements. This paper shows that, ceteris paribus, increases in the volatility of system requirements decrease the reliability of software. Further, systems that exhibit high volatility during the development phase are likely to have lower reliability during their operational phase. In addition to the typically higher volatility of requirements, end-users who specify the requirements of business-oriented systems are usually less technically oriented than people who specify the requirements of compilers, radar tracking systems or medical equipment. Hence, the characteristics of software reliability problems for business-oriented systems are likely to differ significantly from those of more technically oriented systems.

The effects of information request ambiguity and construct incongruence on query development

This paper examines the effects of information request ambiguity and construct incongruence on end user's ability to develop SQL queries with an interactive relational database query language. In this experiment, ambiguity in information requests adversely affected accuracy and efficiency. Incongruities among the information request, the query syntax, and the data representation adversely affected accuracy, efficiency, and confidence. The results for ambiguity suggest that organizations might elicit better query development if end users were sensitized to the nature of ambiguities that could arise in their business contexts. End users could translate natural language queries into pseudo-SQL that could be examined for precision before the queries were developed. The results for incongruence suggest that better query development might ensue if semantic distances could be reduced by giving users data representations and database views that maximize construct congruence for the kinds of queries in typical domains. (C) 2001 Elsevier Science B.V. All rights reserved.

Cognitive style factors affecting database query performance

As end-user computing becomes more pervasive, an organization's success increasingly depends on the ability of end-users, usually in managerial positions, to extract appropriate data from both internal and external sources. Many of these data sources include or are derived from the organization's accounting information systems. Managerial end-users with different personal characteristics and approaches are likely to compose queries of differing levels of accuracy when searching the data contained within these accounting information systems. This research investigates how cognitive style elements of personality influence managerial end-user performance in database querying tasks. A laboratory experiment was conducted in which participants generated queries to retrieve information from an accounting information system to satisfy typical information requirements. The experiment investigated the influence of personality on the accuracy of queries of varying degrees of complexity. Relying on the Myers–Briggs personality instrument, results show that perceiving individuals (as opposed to judging individuals) who rely on intuition (as opposed to sensing) composed queries more accurately. As expected, query complexity and academic performance also explain the success of data extraction tasks.