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Topic models are becoming a frequently employed tool in the empirical methods repertoire of information systems and management scholars. Given textual corpora, such as consumer reviews and online discussion forums, researchers and business practitioners often use topic modeling to either explore data in an unsupervised fashion or generate variables of interest for subsequent econometric analysis. However, one important concern stems from the fact that topic models can be notorious for their instability, i.e., the generated results could be inconsistent and irreproducible at different times, even on the same dataset. Therefore, researchers might arrive at potentially unreliable results regarding the theoretical relationships that they are testing or developing. In this paper, we attempt to highlight this problem and suggest a potential approach to addressing it. First, we empirically define and evaluate the stability problem of topic models using four textual datasets. Next, to alleviate the problem and with the goal of extracting actionable insights from textual data, we propose a new method, Stable LDA, which incorporates topical word clusters into the topic model to steer the model inference toward consistent results. We show that the proposed Stable LDA approach can significantly improve model stability while maintaining or even improving the topic model quality. Further, employing two case studies related to an online knowledge community and online consumer reviews, we demonstrate that the variables generated from Stable LDA can lead to more consistent estimations in econometric analyses. We believe that our work can further enhance management scholars' collective toolkit to analyze ever-growing textual data. [ABSTRACT FROM AUTHOR]

Questions pertaining to the locus of information systems (IS) governance have been extensively examined in existing research. However, questions pertaining to the decision rationale applied for IS portfolio prioritization (why are certain initiatives approved, and why are certain others rejected), noted to be a critical component of IS governance, need further investigation. We submit that the IS strategy of a firm is likely to explain the decision rationale it applies to IS portfolio prioritization and maintain that it is critical to ensure this decision rationale is in congruence with the firm's IS strategy. By extending prior theoretical work on IS strategy types, we develop theoretical profiles of the decision rationale applied to IS portfolio prioritization using three attributes: communicability of decision rationale, consistency in applying decision rationale, and risk appropriateness of decision rationale. Since the decision rationale applied for IS portfolio prioritization is often tacit, unknown even to the decision makers themselves, we employ the decision tree induction methodology to discover this tacit decision rationale. We analyze over 150 IS portfolio prioritization decisions on a multimillion dollar IS portfolio of a multibusiness, Fortune 50 firm and our findings, which support our propositions, indicate that firms that adopt different IS strategies rely on systematically different profiles of decision rationale for IS portfolio prioritization. Implications for IS governance practices are developed. [ABSTRACT FROM AUTHOR]