CALL FOR PAPERS Special Issue of Decision Support Systems: Perspectives on Numerical Data Quality in IS Research
• 大类 : 工程技术 - 2区
• 小类 : 计算机：人工智能 - 2区
• 小类 : 计算机：信息系统 - 2区
• 小类 : 运筹学与管理科学 - 2区
In their recent Decision Support Systems paper, Marsden and Pingry argued the following: “... there are major, persistent numerical data quality issues in IS academic research. These issues undermine the ability to replicate our research – a critical element of scientific investigation and analysis. In IS empirical and analytics research articles, the amount of space devoted to the details of data collection, validation, and/or quality pales in comparison to the space devoted to the evaluation and selection of relatively sophisticated model form(s) and estimation technique(s). Yet erudite modeling and estimation can yield no immediate value or be meaningfully replicated without high quality data inputs.”
Marsden and Pingry stated their purposes as: “1) to detail potential quality issues with data types currently used in IS research, and 2) to start a wider and deeper discussion of data quality in IS research.”
This Call for Papers is for an upcoming special issue of Decision Support Systems focused on providing a platform for researchers to argue for/against data quality thresholds. to detail possible quality thresholds for any or all of the various numerical data types listed by Marsden and Pingry, and/or to discuss possible journal policies that emphasize data quality and reproducibility. Finally, we welcome submissions that respond to the arguments of Marsden and Pingry.
Submissions should be no more than fourteen double-spaced pages including all material. Arguments should be clear and concise. Working with guest reviewers and additional guest editors, we will select the clearest, most erudite submissions with a goal of balancing out the
discussions of each data type.