Nonresponse bias in survey‐based entrepreneurship research: A review, investigation, and recommendations

无响应偏差 创业 检查表 数据收集 心理学 测量数据收集 调查研究 响应偏差 选择偏差 报告偏差 调查方法 营销 计量经济学 应用心理学 业务 统计 政治学 社会心理学 社会学 经济 梅德林 社会科学 数学 财务 认知心理学 法学
作者
David J. Scheaf,Andrew C. Loignon,Justin W. Webb,Eric D. Heggestad
出处
期刊:Strategic Entrepreneurship Journal [Wiley]
卷期号:17 (2): 291-321 被引量:24
标识
DOI:10.1002/sej.1453
摘要

Abstract Research Summary Entrepreneurship researchers commonly use survey‐based research designs. However, surveying entrepreneurs poses unique challenges. A principal concern for survey‐based research is nonresponse bias, which occurs when survey respondents systematically differ from those who were sampled but did not participate in the study. To address this concern, we conducted a systematic review of the literature to determine what practices are currently being used to address nonresponse bias (142 articles, 180 surveying efforts) and conducted multiple studies to determine the extent to which nonresponse bias can affect statistical results. Based on these efforts, we present a series of techniques and a checklist that entrepreneurship scholars and reviewers and editors can consider to mitigate the risk of nonresponse bias prior to, and following, their data collection efforts. Managerial Summary In an average survey of entrepreneurs, approximately 40% of the people contacted will respond. This raises an important question: Can we make conclusions about the entrepreneurs who did not respond? Answering this question requires one to consider nonresponse bias (i.e., if respondents differ from nonrespondents). We conducted a systematic review of survey‐based studies in entrepreneurship and conducted three field studies. Our results show that nonresponse bias can manifest in different ways across studies, but it is rarely discussed in the literature. We also show that response rates are poor proxies of nonresponse bias. Based on these efforts, we present several techniques for scholars, reviewers, and editors to consider in the hopes of mitigating the risk of nonresponse bias in their studies.
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