[AISWorld] CORRECTION (too much eggnog!): Contents of Volume 17, Issue 12 (December) Journal of the Association for Information Systems (JAIS)

[JAIS]

Contents of Volume 17, Issue 12 (December) Journal of the Association for Information Systems (JAIS), Official Publication of the Association for Information Systems
Published: Monthly Electronically
ISSN: 1536-9323
Published by the Association for Information Systems, Atlanta, USA (http://aisel.aisnet.org/jais/)

Editor-in-Chief:  Professor Suprateek Sarker, University of Virginia, USA

Paper
Understanding the Role of IS and Application Domain Knowledge on Conceptual Schema Problem Solving: A Verbal Protocol Study

Vijay Khatri, Indiana University
Iris Vessey, The University of Queensland

Abstract
One of the most neglected areas of information systems research is the role of the domain to which researchers apply IS methods, tools, and techniques; that is, the application domain. For example, little prior information systems (IS) or related research has examined how IS and application domain knowledge (ISDK and ADK, respectively) influence how individuals solve conceptual schema problem-solving tasks. In this research, we investigate the effects of both ISDK and ADK on two types of conceptual schema problem-solving tasks: schema based and inferential. We used verbal protocol analysis to explore the roles that ISDK and ADK play in the problem-solving processes participants use when addressing these tasks. We found that, for the two types of conceptual schema problem-solving tasks, ADK and ISDK have similar effects on problem-solving processes. That is, we found that, for schema-based problem-solving tasks, participants used focused (depth-first) processes when the application domain was familiar as did participants with greater IS domain knowledge. We also found that, for inferential problem-solving tasks, participants used exploratory (breadth-first) processes when the application domain was familiar as did participants with greater IS domain knowledge. We then show how cognitive psychology literature on problem solving can help explain the effects of ISDK and ADK and, thus, provide the theoretical foundation for analyzing the roles of each type of knowledge in the process of IS problem solving.

To obtain a copy of the entire article, click on the link below:
http://aisel.aisnet.org/jais/vol17/iss12/2/


Paper
Enhancing Analysts’ Mental Models for Improving Requirements Elicitation: A Two-stage Theoretical Framework and Empirical Results

Padmal Vitharana, Syracuse University
Mariam Fatemeh Zahedi, University of Wisconsin - Milwaukee
Hemant K. Jain, University of Tennessee at Chattanooga

Abstract
Research has extensively documented the importance of accurate system requirements in avoiding project delays, cost overruns, and system malfunctions. Requirement elicitation (RE) is a critical step in determining system requirements. While much research on RE has emerged, a deeper understanding of three aspects could help significantly improve RE: 1) insights about the role and impacts of support tools in the RE process, 2) the impact of using support tools in multiple stages of the RE process, and 3) a clear focus on the multiplicity of perspectives in assessing RE outcomes. To understand how using support tools could improve RE, we rely on the theoretical lens of mental models (MM) to develop a dynamic conceptual model and argue that analysts form mental models (MMs) of the system during RE and these MMs impact their outcome performance. We posit that one can enhance analysts’ MMs by using a knowledge-based repository (KBR) of components and services embodying domain knowledge specific to the target application during two key stages of RE, which results in improved RE outcomes. We measured the RE outcomes from user and analyst perspectives. The knowledge-based component repository we used in this research (which we developed in collaboration with a multi-national company) focused on insurance claim processing. The repository served as the support tool in RE in a multi-period lab experiment with multiple teams of analysts. The results supported the conceptualized model and showed the significant impacts of such tools in supporting analysts and their performance outcomes at two stages of RE. This work makes multiple contributions: it offers a theoretical framework for understanding and enhancing the RE process, develops measures for analysts’ mental models and RE performance outcomes, and shows the process by which one can improve analysts’ RE performance through access to a KBR of components at two key stages of the RE process.

To obtain a copy of the entire article, click on the link below:
http://aisel.aisnet.org/jais/vol17/iss12/1/<http://aisel.aisnet.org/jais/vol17/iss11/1/>


On behalf of the Editorial Team at JAIS, we would like to wish the entire community a very happy New Year!  We look forward to your best submissions in 2017!

Elizabeth White Baker, PhD
Production Managing Editor, Journal of the AIS
jais at comm.virginia.edu