Organizational Research Methods最新文献

IF 9.5 2区管理学

Organizational Research Methods Pub Date : 2026-04-27 DOI: 10.1177/10944281261432629

Siyi Liu, Louis Hickman, Linus Dahlander, Henning Piezunka

{"title":"Textual Similarity in Organizational Research: Review of Applications, Consistency of Methods, and Best Practice Recommendations","authors":"Siyi Liu, Louis Hickman, Linus Dahlander, Henning Piezunka","doi":"10.1177/10944281261432629","DOIUrl":"https://doi.org/10.1177/10944281261432629","url":null,"abstract":"Organizational research increasingly uses natural language processing (NLP) to measure textual similarity. Despite common usage, the meaning and consistency of similarity measures (e.g., cosine similarity and Euclidean distance) across common NLP methods (e.g., n -grams and document embeddings) is unclear. This risks misalignment between theoretical constructs and textual measures, undermining the comparability of findings across studies. To address this gap, we review studies using textual similarity in organizational and psychological research, finding a jingle-jangle fallacy: identical labels are used for similarity estimates from different NLP methods, and different labels are used for the same method. Additionally, we examine the consistency of similarity measures across and within NLP methods. Different transformer-based embeddings’ similarity results are interchangeable. However, n -grams yield distinct, inconsistent results and are less appropriate for estimating similarity with distance measures. When applied to multi-word inputs, dictionaries and word embeddings return similar results reflecting linguistic style. We provide best practice recommendations and example code for operationalizing textual similarity, including clarifying which NLP methods correspond to content similarity, linguistic style similarity, and semantic similarity at the word, sentence, and document-levels of analysis.","PeriodicalId":19689,"journal":{"name":"Organizational Research Methods","volume":"151 1","pages":""},"PeriodicalIF":9.5,"publicationDate":"2026-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147751554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

“How Many Interviews Do I Need?” An Examination of Interview Numbers and Sampling Moves in Qualitative Research “我需要多少次面试？”定性研究中访谈数和抽样动作的检验

IF 9.5 2区管理学

Organizational Research Methods Pub Date : 2026-04-09 DOI: 10.1177/10944281261424516

Kasper Trolle Elmholdt, Michael Gill, Jeppe Agger Nielsen

{"title":"“How Many Interviews Do I Need?” An Examination of Interview Numbers and Sampling Moves in Qualitative Research","authors":"Kasper Trolle Elmholdt, Michael Gill, Jeppe Agger Nielsen","doi":"10.1177/10944281261424516","DOIUrl":"https://doi.org/10.1177/10944281261424516","url":null,"abstract":"Qualitative researchers face an enduring question: How many interviews do I need? While a variety of guidelines exist, there is limited consensus over which specific factors should determine the number of interviews required. We examined the determination of interview sample sizes in 562 qualitative studies across six high-impact management and organizational journals over a decade. Our findings reveal considerable variance in interview numbers, yet limited information is often provided on the criteria used to determine them. To promote clearer alignment between sample sizes and methodology, we examined studies with detailed descriptions of their interview sampling. We identified specific “sampling moves” used to determine the number of interviews, categorized into three types—opening, focusing, and closing sampling moves—that researchers use to establish confidence in the sample and support theoretical insights. By implication, our study refutes the notion of a “magic” interview number. Instead, sampling moves are heuristic tools that qualitative researchers can thoughtfully adapt to their analytical aims when determining appropriate sample sizes.","PeriodicalId":19689,"journal":{"name":"Organizational Research Methods","volume":"28 1","pages":""},"PeriodicalIF":9.5,"publicationDate":"2026-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147635728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling Unfolding Response Data Within the Structural Equation Modeling Framework 结构方程建模框架下展开响应数据的建模

IF 9.5 2区管理学

Organizational Research Methods Pub Date : 2026-04-08 DOI: 10.1177/10944281261421529

Ringo Moon-ho Ho, Jie Xin Lim, Olexander Chernyshenko

{"title":"Modeling Unfolding Response Data Within the Structural Equation Modeling Framework","authors":"Ringo Moon-ho Ho, Jie Xin Lim, Olexander Chernyshenko","doi":"10.1177/10944281261421529","DOIUrl":"https://doi.org/10.1177/10944281261421529","url":null,"abstract":"Dominance and unfolding response processes describe two ways in which individuals may respond to rating scale items. The dominance process assumes a monotonic relationship between a latent trait and the probability of endorsement and is typically modeled using a linear factor model within structural equation modeling (SEM). In contrast, the unfolding process assumes single-peaked response functions, with endorsement most likely when item and person locations are close on the latent continuum. Fitting unfolding models usually requires specialized software, which limits their integration with SEM. In this article, we proposed the ordered categorical response unfolding model (OCRUM), which can be estimated in Mplus. We illustrated its use with two empirical datasets and found that item and person locations were comparable to those obtained from the generalized graded unfolding model (GGUM). We also conducted Monte Carlo simulations to examine parameter recovery under varying sample sizes, test lengths, and response formats. Finally, we demonstrated that OCRUM can serve as the measurement component of a general structural equation model, enabling dominance and unfolding response processes to be represented within a single SEM framework.","PeriodicalId":19689,"journal":{"name":"Organizational Research Methods","volume":"64 1","pages":""},"PeriodicalIF":9.5,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147635727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Applying Machine Learning and Natural Language Processing Methods to Support Taxonomy Development and Maintenance 应用机器学习和自然语言处理方法支持分类法的开发和维护

IF 9.5 2区管理学

Organizational Research Methods Pub Date : 2026-03-27 DOI: 10.1177/10944281261434975

Nathaniel M. Voss, Jiayi Liu, Saron Demeke, Martin C. Yu, Harrison J. Kell, Brian Prost, Dan J. Putka

{"title":"Applying Machine Learning and Natural Language Processing Methods to Support Taxonomy Development and Maintenance","authors":"Nathaniel M. Voss, Jiayi Liu, Saron Demeke, Martin C. Yu, Harrison J. Kell, Brian Prost, Dan J. Putka","doi":"10.1177/10944281261434975","DOIUrl":"https://doi.org/10.1177/10944281261434975","url":null,"abstract":"Taxonomies provide a systematic way to organize phenomena and have various practical and theoretical benefits for organizational researchers and practitioners. While taxonomy development and maintenance is often a burdensome process (e.g., time-consuming, costly, and prone to judgmental error), advances in natural language processing (NLP) have the potential to streamline this process. In this study, we employed various evaluation metrics (e.g., cosine similarity) to investigate how machine learning (ML) methods and large language models (LLMs) can automate taxonomy development and maintenance. We examined two embedding models, six clustering algorithms, and three generative LLMs (for creating cluster labels) to construct taxonomies and compared their alignment with four established taxonomies (CABIN, IPIP-NEO-120, ATAF, and O*NET). The confirmatory taxonomic method we examined resulted in effective clustering (i.e., similar text statements were consistently grouped), frequently yielded structures similar to the original taxonomies for ATAF, IPIP-NEO-120, and CABIN (with O*NET being more variable), and resulted in extremely efficient taxonomy title generation. These findings can provide researchers with a foundation for how to approach NLP-based taxonomy development and maintenance activities for their own contexts.","PeriodicalId":19689,"journal":{"name":"Organizational Research Methods","volume":"15 1","pages":""},"PeriodicalIF":9.5,"publicationDate":"2026-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147518883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unpacking the Validity of Open-Ended Personality Assessments Using Fine-Tuned Large Language Models 利用微调的大型语言模型揭示开放式人格评估的有效性

IF 9.5 2区管理学

Organizational Research Methods Pub Date : 2026-03-11 DOI: 10.1177/10944281251413746

Andrew B. Speer, Angie Y. Delacruz, Takudzwa A. Chawota, James Perrotta, Cort W. Rudolph

{"title":"Unpacking the Validity of Open-Ended Personality Assessments Using Fine-Tuned Large Language Models","authors":"Andrew B. Speer, Angie Y. Delacruz, Takudzwa A. Chawota, James Perrotta, Cort W. Rudolph","doi":"10.1177/10944281251413746","DOIUrl":"https://doi.org/10.1177/10944281251413746","url":null,"abstract":"Alternative approaches to personality measurement, such as open-ended narrative-based assessments, have potential advantages for organizational research and practice. In this research, we investigate factors that affect valid application of natural language processing (NLP) for scoring open-ended personality assessments and when, how, and why such assessments capture personality-related variance. Using a large sample of responses to open-ended assessments, convergence between NLP scores and self-report target scores increased as the degree of customization and the sophistication of the underlying model increased, with the worst psychometric performance occurring for zero-shot large language model (LLM) scores and the best for fine-tuned LLM scores. However, all scoring methods exhibited evidence of validity. Additionally, when trained to predict direct evaluations of the narrative responses, correlations with target scores were large ( M = .83). NLP scores also exhibited discriminant and criterion-related validity evidence. However, validity was contingent upon the methodological rigor employed in developing writing prompts. Prompts designed to elicit trait-relevant information outperformed generic prompts, and this occurred because trait-specific prompts increased the amount of trait-relevant information (i.e., narrative units), which was associated with enhanced convergence with target scores.","PeriodicalId":19689,"journal":{"name":"Organizational Research Methods","volume":"15 1","pages":""},"PeriodicalIF":9.5,"publicationDate":"2026-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147393412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

I Gotta Feeling: Advancing Sentiment Analysis in Organizational Science 我有感觉：组织科学中先进的情感分析

IF 9.5 2区管理学

Organizational Research Methods Pub Date : 2026-03-02 DOI: 10.1177/10944281251408073

Imran Kadolkar, Divya V Doshi, Scott Tonidandel, Jose M Cortina

{"title":"I Gotta Feeling: Advancing Sentiment Analysis in Organizational Science","authors":"Imran Kadolkar, Divya V Doshi, Scott Tonidandel, Jose M Cortina","doi":"10.1177/10944281251408073","DOIUrl":"https://doi.org/10.1177/10944281251408073","url":null,"abstract":"Sentiment analysis (SA) has grown considerably in organizational science research over the past two decades, particularly in the last few years. While enthusiasm for integrating advanced natural language processing algorithms is encouraging, authors are not reaping the benefits of such tools fully. Our systematic review of SA application in the organizational sciences suggests that authors struggle to appreciate all of the decisions that are inherent to SA, the choices that are available at each decision point, and the consequences of each choice. To address this gap, we use a working example to illustrate four critical decision points authors confront when conducting SA, and the subsequent impact different choices can have on one's conclusion. Decision points include selecting the SA method, computing a sentiment score, preprocessing the data, and using an appropriate level of analysis. We conclude with a framework outlining five dimensions (e.g., accuracy, interpretability, computational cost) to guide the selection of an SA approach based on study goals and needs, along with seven recommendations to authors wishing to apply SA.","PeriodicalId":19689,"journal":{"name":"Organizational Research Methods","volume":"250 1","pages":""},"PeriodicalIF":9.5,"publicationDate":"2026-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147358803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Application of Prototype Analysis to Organizational Research: A Critical Methodological Review 原型分析在组织研究中的应用：批判性方法论回顾

IF 9.5 2区管理学

Organizational Research Methods Pub Date : 2025-12-23 DOI: 10.1177/10944281251399210

Sandra Kiffin-Petersen, Sharon Purchase, Doina Olaru

{"title":"Application of Prototype Analysis to Organizational Research: A Critical Methodological Review","authors":"Sandra Kiffin-Petersen, Sharon Purchase, Doina Olaru","doi":"10.1177/10944281251399210","DOIUrl":"https://doi.org/10.1177/10944281251399210","url":null,"abstract":"Prototypes—internalized knowledge structures of the most typical or characteristic features of a concept—are important because they influence cognitive processing. Yet prototype analysis, the method used to examine prototypes, appears relatively underutilized in organizational research. To introduce prototype analysis to a wider audience of organizational scholars, we conducted a critical methodological literature review following a six-step procedure. Seventy-three prototype analyses published in 35 journals were categorized and their content analyzed. A prototype analysis typically includes a sequence of independent studies conducted over two stages, recently referred to as the standard procedure. Our review makes several contributions, including development of a taxonomy of prototype analysis applications, clarification of the standard procedure of a prototype analysis and possible variations, and suggestions for organizational research. Benefits of undertaking a prototype analysis include improved understanding of abstract workplace concepts that are difficult to measure directly, the ability to compare cross-cultural prototypes, and an approach for investigating the issue of construct redundancy. We conclude with best-practice recommendations, implications for organizational scholarship, methodological limitations, and future research suggestions.","PeriodicalId":19689,"journal":{"name":"Organizational Research Methods","volume":"22 1","pages":""},"PeriodicalIF":9.5,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145812772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Understanding Relative Differences with Magnitude-Based Hypotheses: A Methodological Conceptualization and Data Illustration 理解以震级为基础的假设的相对差异：方法概念化和数据说明

IF 9.5 2区管理学

Organizational Research Methods Pub Date : 2025-10-07 DOI: 10.1177/10944281251377139

Dane P. Blevins, David J. Skandera, Roberto Ragozzino

引用次数: 0

Generative Artificial Intelligence in Qualitative Data Analysis: Analyzing—Or Just Chatting? 定性数据分析中的生成式人工智能：分析还是聊天？

IF 9.5 2区管理学

Organizational Research Methods Pub Date : 2025-09-30 DOI: 10.1177/10944281251377154

Duc Cuong Nguyen, Catherine Welch

引用次数: 0

Unleashing the Creative Potential of Research Tensions: Toward a Paradox Approach to Methods 释放研究紧张的创造潜力：走向方法的悖论方法