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Don't Mind the Gap:A Conceptual and Psychometric Analysis of the Individual Evaluation of Discrepancies in the Context of IS User Service Satisfaction

机译:不要忽略差距:在IS用户服务满意度的背景下对差异的个体评估的概念和心理分析

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摘要

When researchers are interested in capturing perceived discrepancies-for example, the perceived alignment between organizational and business-unit strategies, or the perceived gap between expected and received service delivery-many different measurement approaches are available. This paper presents a psychometric analysis of the various measures available to capture perceived discrepancies or gaps. More specifically, a set of comparative survey-based measures, drawn from published research across various disciplines, including marketing, information systems, and organizational behavior, are examined for their applicability.We first consider the conceptual assumptions of a set of comparative measurements previously employed by researchers to capture perceived discrepancies. In the context of predicting user satisfaction with a service, we test the relative psychometric performance of those measures along with some novel (modified) versions of those measures. Performance of the measures varies widely, with those that include an evaluative component offering stronger predictive validity than measures that focus exclusively on the size of the discrepancy. This paper contributes to the work on perceived discrepancies by empirically assessing both the current approaches, as well as multiple new measurement approaches. Our findings suggest that neglecting to attend to the conceptual underpinnings of a discrepancy measure can lead to model misspecifications and misinterpretations.
机译:当研究人员对捕获感知到的差异感兴趣时,例如,组织策略和业务部门策略之间的感知一致性,或者预期和接收的服务交付之间的感知差距,可以使用许多不同的度量方法。本文对可用来捕获感知到的差异或差距的各种措施进行了心理分析。更具体地讲,从市场,信息系统和组织行为等各个学科的已发表研究中得出的一组基于比较调查的措施的适用性进行了研究。我们首先考虑先前采用的一组比较措施的概念假设由研究人员捕获感知到的差异。在预测用户对某项服务的满意度的背景下,我们测试了这些措施的相对心理计量性能以及这些措施的某些新颖(修改)版本。措施的执行情况差异很大,与那些仅着眼于差异大小的措施相比,包含评估成分的措施提供了更强的预测有效性。本文通过经验评估当前方法以及多种新的测量方法,为感知差异的研究做出了贡献。我们的研究结果表明,忽视参加差异度量的概念基础可能会导致模型错误指定和错误解释。

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