Is Query Reuse Potentially Harmful? Anchoring and Adjustment in Adapting Existing Database Queries

• 成果类型: Article
• 署名作者: Allen, Gove; Parsons, Jeffrey
• 署名单位: Brigham Young University; Memorial University Newfoundland
• 刊物名称: INFORMATION SYSTEMS RESEARCH
• ISSN/ISSBN: 1047-7047
• DOI: 10.1287/isre.1080.0189
• 发表日期: 2010
• 页码: 56-77
• 关键词: software reuse; REPRESENTATION; heuristics; interface; accuracy; QUALITY; LESSONS; DESIGN; BIAS

摘要

Reusing database queries by adapting them to satisfy new information requests is an attractive strategy for extracting information from databases without involving database specialists. However, the reuse of information systems artifacts has been shown to be susceptible to the phenomenon of anchoring and adjustment. Anchoring often leads to a systematic adjustment bias in which people fail to make sufficient changes to an anchor in response to the needs of a new task. In a study involving 157 novice query writers from six universities, we examined the effect of this phenomenon on the reuse of Structured Query Language (SQL) queries under varying levels of domain familiarity and for different types of anchors. Participants developed SQL queries to respond to four information requests in a familiar domain and four information requests in an unfamiliar domain. For two information requests in each domain, participants were also provided with sample queries (anchors) that answered similar information requests. We found evidence that the opportunity to reuse sample queries resulted in an adjustment bias leading to poorer quality query results and greater overconfidence in the correctness of results. The results also indicate that the strength of the adjustment bias depends on a combination of domain familiarity and type of anchor. This study demonstrates that anchoring and adjustment during query reuse can lead to queries that are less accurate than those written from scratch. We also extend the concept of anchoring and adjustment by distinguishing between surface-structure and deep-structure anchors and by considering the impact of domain familiarity on the adjustment bias.