Management Science and Operations Research, Statistics, Probability and Uncertainty
11
Scopus Publications
577
Scholar Citations
8
Scholar h-index
7
Scholar i10-index
Scopus Publications
AI-Enhanced Qualitative Analysis in Healthcare: Unlocking Insight from Interviews of Leadership at Top-Performing Academic Medical Centers Triss Ashton, Seth Chatfield Healthcare Switzerland, 2026 Background/Objectives: Vast amounts of textual data are generated by healthcare organizations every year. Traditional content analysis is time-intensive, error-prone, and potentially biased. This study demonstrates how freely available large language model (LLM) artificial intelligence (AI) tools can efficiently and effectively analyze qualitative healthcare data and uncover insights missed by traditional manual analysis. Interview data from chief nursing officers (CNOs) at top-performing academic medical centers were analyzed to identify factors contributing to their operational and patient quality success. Methods: Semi-structured interviews were conducted with CNOs from top-performing academic medical centers that achieved top-decile quality measures while using resources most efficiently. Interview transcripts were analyzed using a mix of traditional text mining in LSA and Gemini 2.5. The capability of four freely available AI platforms—Gemini 2.5, Scholar AI 5.1, Copilot’s Chat, and Claude’s Sonnet 4.5—was also reviewed. Results: LLM AI analysis identified ten primary factors, comprising twenty-four subtopics, that characterized successful hospital performance. Notably, AI analysis identified a theoretical connection that manual analysis had missed, revealing how the identified framework aligned with Donabedian’s seminal structure, process, outcomes quality model. The AI analysis reduced the required time from weeks to nearly instantaneous. Conclusions: LLM AI tools offer a transformative approach to unlocking insight from the analysis of qualitative textual data in healthcare settings. These tools can provide rapid insight that is accessible to personnel with minimal text-mining expertise and offer a practical solution for healthcare organizations to unlock insight hidden in the vast amounts of textual data they hold.
The temporal dynamics of attribute-based firm reputation: examining short-term and long-term reputation and regulation in the U.S. automobile industry David E. Cavazos, Matthew Rutherford, Triss Ashton International Journal of Organizational Analysis, 2023 Purpose This study aims to examine the implications of short-term and long-term reputation change because of government agency responses to firm product defects. Design/methodology/approach This study’s findings have important implications for both scholars and practitioners. From a scholarly perspective, the authors create a more fine-grained examination of reputation that may be used to assess various performance dimensions. From a practice perspective, managers must realize that reputation can be one of an organization’s most important resources as it meets each of the valuable, rare, inimitable and nonsubstitutable criteria associated with those resources capable of providing sustainable competitive advantage. Findings Analysis of 17,879 product recalls from 15 automobile manufacturers in the US suggests that firms with higher long-term reputations are more likely to face regulator sanctions when a reputation-damaging event happens. On the other hand, firms with higher short-term reputations are less likely to face sanctions in such circumstances. Finally, firms whose short-term reputation exceeds their long-term reputation are less likely to be sanctioned by regulators when reputation-damaging events occur. Research limitations/implications There are several limitations that should be addressed. First, as our reputation measure is based on government investigations of potential defects, vehicles that have never been inspected are not included in the sample. Although this number is likely extremely low, omitting vehicles that have never been inspected leaves out some high-reputation firms from the sample. In addition, the study relies on a single-firm stakeholder that is capable of punitive actions. Practical implications From a practical perspective, this study’s findings encourage managers to think about the temporal aspects associated with firm reputation, and to realize that stakeholders may react differently when their expectations are not met depending on an organization’s relative long- and short-term reputations. From a theoretic perspective, the primary contribution of this study is to illustrate how long-term and short-term changes in reputation can provide mixed signals to firm stakeholders regarding future performance. Originality/value This study explores the temporal aspects of firm reputation by examining how government sanctions vary depending on firms’ long-term (10 years) and short-term (1 year) reputation. The findings of this study contribute to current reputation research by illustrating the variation in government responses to product defects as a function of short-term and long-term reputation. In doing so, the important role of the timing of firm performance is considered.
Researching family firm heterogeneity: A guide to identifying firm-level categorical and variational differences Field Guide to Family Business Research, 2023
Family Firm Heterogeneity: A Definition, Common Themes, Scholarly Progress, and Directions Forward Joshua J. Daspit, James J. Chrisman, Triss Ashton, Nicholas Evangelopoulos Family Business Review, 2021 While progress has been made in recent years to understand the differences among family firms, insights remain fragmented due, in part, to an incomplete understanding of heterogeneity and the scope of differences that exist among family firms. Given this, we offer a definition of and review the literature on family firm heterogeneity. A latent semantic analysis of 781 articles from 33 journals identified nine common themes of family firm heterogeneity. For each theme, we review scholarly progress made and highlight differences among family firms. Additionally, we offer directions for advancing the study of family firm heterogeneity.
Developing and validating e-retailing satisfaction scales with text-mining Triss Ashton, Victor R. Prybutok Journal of Modelling in Management, 2020 Purpose The purpose of this study includes two parts. First, it introduces a machine-based method for model and instrument development and updating that integrates large sample qualitative data. Second, a new model and instrument for e-commerce customer satisfaction are developed. Design/methodology/approach The research occurs in two phases. In Phase 1, data collection occurs with a literature-based quantitative model and instrument that includes at least one qualitative scale item per construct. Data analysis of the resulting data includes factor analysis (FA) and latent semantic analysis text mining to generate an updated model and instrument. In Phase 2, data collection uses the new model and instrument. Data analysis in Phase 2 includes exploratory data analysis with FA, exploratory structural equation modeling and partial least square modeling. Findings As a result of the information gained by the integration of qualitative scales in the literature-based survey, the final model departs substantially from the initial research-based research model. It integrates many of the constructs known to impact a website and software usability from information systems research into a new e-retail satisfaction model. Originality/value The research method, as presented here, offers a strategy for integrating large scale qualitative data for refinement of models and the development of instruments. It is essentially a method of gaining the wisdom of crowds economically while simultaneously reducing the biases and laborious effort commonly associated with qualitative research.
Assessing text mining algorithm outcomes Triss Ashton, Nicholas Evangelopoulos, Audhesh Paswan, Victor R. Prybutok, Robert Pavur Journal of Business Analytics, 2020 There is a surge in the development of decision-oriented analysis tools intended to extract actionable information from text. These tools integrate various text-mining methods that were performance tested in a manner that was often biased toward the new system. Those tests primarily utilised descriptive measurement criteria and test datasets that are inconsistent with most business corpora. We propose and test a user-oriented judgment approach that allows testing under controlled customer-oriented corpora and generates effect size measures. To illustrate the approach, customer relations data was analysed by latent semantic analysis and latent Dirichlet analysis with results evaluated by prospective business analysts. Reporting includes comparisons of results with published literature. While the research centres on the context-region text-mining systems, literature comparisons include word-embedding methods. The analysis concludes that none of the systems reviewed possess a repeatable statistical advantage over the others. Instead, distribution attributes, algorithm configuration, and the evaluation task drive results.
AI-Enhanced Qualitative Analysis in Healthcare: Unlocking Insight from Interviews of Leadership at Top-Performing Academic Medical Centers T Ashton, S Chatfield Healthcare 14 (2), 248 , 2026 2026 Citations: 1
Researching family firm heterogeneity: A guide to identifying firm-level categorical and variational differences JJ Daspit, JJ Chrisman, V Skorodziyevskiy, S Davis, T Ashton Field guide to family business research, 46-60 , 2023 2023 Citations: 16
Predicting eBook Purchases of Heterogeneous Social Groups in a Social Network Site Using Network Metrics J Yu, D Oh, T Ashton, Y Wang International Journal of Mobile Communications 22 (1), 92-110 , 2023 2023 Citations: 2
The temporal dynamics of attribute-based firm reputation: examining short-term and long-term reputation and regulation in the US automobile industry DE Cavazos, M Rutherford, T Ashton International Journal of Organizational Analysis 31 (7), 3519-3531 , 2022 2022 Citations: 5
Family firm heterogeneity: A definition, common themes, scholarly progress, and directions forward JJ Daspit, JJ Chrisman, T Ashton, N Evangelopoulos Family Business Review 34 (3), 296-322 , 2021 2021 Citations: 418
Developing and validating e-retailing satisfaction scales with text-mining T Ashton, VR Prybutok Journal of Modelling in Management 15 (4), 1655-1677 , 2020 2020 Citations: 14
Assessing text mining algorithm outcomes T Ashton, N Evangelopoulos, A Paswan, VR Prybutok, R Pavur Journal of Business Analytics 3 (2), 107-121 , 2020 2020 Citations: 9
A Multi-Analytical Examination of the Self-Control Concept TD Nguyen, A Paswan, T Ashton Pacific Business Review International 10 (4) , 2017 2017
Latent semantic analysis and real estate research: Methods and applications N Evangelopoulos, T Ashton, K Winson-Geideman, S Roulac Journal of Real Estate Literature 23 (2), 353-380 , 2015 2015 Citations: 20
Quantitative quality control from qualitative data: control charts with latent semantic analysis T Ashton, N Evangelopoulos, VR Prybutok Quality & Quantity , 2014 2014 Citations: 42
Extending monitoring methods to textual data: a research agenda T Ashton, N Evangelopoulos, V Prybutok Quality & Quantity 48 (4), 2277-2294 , 2014 2014 Citations: 35
Accuracy and Interpretability Testing of Text Mining Methods TA Ashton, N Evangelopoulos, A Paswan, VR Prybutok, R Pavur University of North Texas , 2013 2013
Exponentially weighted moving average control charts for monitoring customer service quality comments T Ashton, N Evangelopoulos, VR Prybutok International Journal of Services and Standards 8 (3), 230-246 , 2013 2013 Citations: 10
Detection of Multiple Dimensionalities in Textual Data N Evangelopoulos, T Ashton In Proceedings of 43rd annual Decision Sciences Institute Annual Meeting … , 2012 2012
CONTROL CHARTS FOR CUSTOMER COMMENTS: A CASE STUDY AND A RESEARCH AGENDA T Ashton, N Evangelopoulos In Proceedings of the forty-third Annual Meeting of the SouthWest DSI, 661-669 , 2012 2012 Citations: 5
MOST CITED SCHOLAR PUBLICATIONS
Family firm heterogeneity: A definition, common themes, scholarly progress, and directions forward JJ Daspit, JJ Chrisman, T Ashton, N Evangelopoulos Family Business Review 34 (3), 296-322 , 2021 2021 Citations: 418
Quantitative quality control from qualitative data: control charts with latent semantic analysis T Ashton, N Evangelopoulos, VR Prybutok Quality & Quantity , 2014 2014 Citations: 42
Extending monitoring methods to textual data: a research agenda T Ashton, N Evangelopoulos, V Prybutok Quality & Quantity 48 (4), 2277-2294 , 2014 2014 Citations: 35
Latent semantic analysis and real estate research: Methods and applications N Evangelopoulos, T Ashton, K Winson-Geideman, S Roulac Journal of Real Estate Literature 23 (2), 353-380 , 2015 2015 Citations: 20
Researching family firm heterogeneity: A guide to identifying firm-level categorical and variational differences JJ Daspit, JJ Chrisman, V Skorodziyevskiy, S Davis, T Ashton Field guide to family business research, 46-60 , 2023 2023 Citations: 16
Developing and validating e-retailing satisfaction scales with text-mining T Ashton, VR Prybutok Journal of Modelling in Management 15 (4), 1655-1677 , 2020 2020 Citations: 14
Exponentially weighted moving average control charts for monitoring customer service quality comments T Ashton, N Evangelopoulos, VR Prybutok International Journal of Services and Standards 8 (3), 230-246 , 2013 2013 Citations: 10
Assessing text mining algorithm outcomes T Ashton, N Evangelopoulos, A Paswan, VR Prybutok, R Pavur Journal of Business Analytics 3 (2), 107-121 , 2020 2020 Citations: 9
The temporal dynamics of attribute-based firm reputation: examining short-term and long-term reputation and regulation in the US automobile industry DE Cavazos, M Rutherford, T Ashton International Journal of Organizational Analysis 31 (7), 3519-3531 , 2022 2022 Citations: 5
CONTROL CHARTS FOR CUSTOMER COMMENTS: A CASE STUDY AND A RESEARCH AGENDA T Ashton, N Evangelopoulos In Proceedings of the forty-third Annual Meeting of the SouthWest DSI, 661-669 , 2012 2012 Citations: 5
Predicting eBook Purchases of Heterogeneous Social Groups in a Social Network Site Using Network Metrics J Yu, D Oh, T Ashton, Y Wang International Journal of Mobile Communications 22 (1), 92-110 , 2023 2023 Citations: 2
AI-Enhanced Qualitative Analysis in Healthcare: Unlocking Insight from Interviews of Leadership at Top-Performing Academic Medical Centers T Ashton, S Chatfield Healthcare 14 (2), 248 , 2026 2026 Citations: 1
A Multi-Analytical Examination of the Self-Control Concept TD Nguyen, A Paswan, T Ashton Pacific Business Review International 10 (4) , 2017 2017
Accuracy and Interpretability Testing of Text Mining Methods TA Ashton, N Evangelopoulos, A Paswan, VR Prybutok, R Pavur University of North Texas , 2013 2013
Detection of Multiple Dimensionalities in Textual Data N Evangelopoulos, T Ashton In Proceedings of 43rd annual Decision Sciences Institute Annual Meeting … , 2012 2012
