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Abstract

Hospitality and tourism (H&T) researchers employ structural equation modeling (SEM) and other multivariate techniques to test their models with survey data. These approaches assess relationships among constructs and model fit, but they do not highlight the most influential survey items or links among them. Other challenges include method-specific requirements for appropriate data, the best indices to identify optimal models, minimum sample sizes, missing data, and interpreting the results from complex models. Co-occurrence network analysis (CNA) can mitigate these limitations. This study validates CNA in the H&T field with a survey dataset that assesses market strategy, nonmarket strategy (NMS), organizational values, and firm performance. CNA is proposed as a complement to existing multivariate approaches for assessing survey data. The assessment includes nine steps: (1) identify the research purpose and hypothesis, (2) determine the hypothesis-related items to measure, (3) determine the sample, (4) administer the survey, (5) determine the analysis method, (6) test the hypotheses, (7) prepare survey inputs for CNA, (8) employ CNA, and (9) visualize and interpret results. This pathway demonstrates how future research can apply and address CNA’s advantages and limitations.

Keywords

co-occurrence network, multivariate analysis, methodology, sample size

Chinese Abstract

共现网络分析(CNA):评估在酒店和旅游研究中基于调查研究模式的替代工具

酒店和旅游(H&T)研究人员使用结构方程模型(SEM)和其他多变量技术来测试他们的模型与调查数据。这些方法评估构建变量之间的关系和模型拟合度,但它们并没有突出显示最具影响力的调查项目或它们之间的联系。其他挑战还包括对适当数据的具体要求、确定最佳模型的最佳指数、最小样本量、缺失数据以及解释复杂模型的结果。共现网络分析(CNA)可以缓解这些限制。本研究通过评估市场战略、非市场战略(NMS)、组织价值和公司绩效的调查数据集,在酒店和旅游领域中验证了CNA的应用。CNA被认为是对现有评估调查数据的多变量方法的一种补充。评估包括九个步骤:(1)确定研究目的和假设,(2)确定与假设相关的测量项目,(3)确定样本,(4)实施调查,(5)确定分析方法,(6)检验假设,(7)为CNA准备调查输入,(8)使用CNA,(9)可视化和解释结果。这条路径演示了未来研究如何应用CNA的优势和和解决其局限性。

关键词:共现网络,多变量分析,方法,样本量

ORCID Identifiers

Mehmet Ali Koseoglu: https://orcid.org/0000-0001-9369-1995

John A. Parnell: https://orcid.org/0000-0001-6158-7018

Hasan Evrim Arici: https://orcid.org/0000-0003-3429-4513

DOI

10.5038/2640-6489.7.1.1179

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

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