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The use of analyst-user cognitive style differentials to predict aspects of user satisfaction with information systems

机译:使用分析师 - 用户认知风格差异来预测用户对信息系统满意度的方面

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摘要

This study was primarily an empirical investigation in the field of Information Systems (IS) and the related fields of occupational psychology and management. It focussed specifically on the concept of user satisfaction, the construct of cognitive style as applied to users and systems analysts, and their interrelationships. Prior studies were found rarely to investigate the changes in user satisfaction during system usage. Further, any reference to cognitive style in the IS literature proved to be sparse, open to question and discouraging in terms of its value. By developing and using a new instrument, the System Satisfaction Schedule, or SSS, the present study was able empirically to demonstrate clear patterns of changing user satisfaction during system usage. These were demonstrated, both as a general trend and in terms of its relationship to the cognitive styles of the key players (analyst and user) involved in system development and maintenance. Cognitive style was measured using Kirton's Adaption-innovation Inventory, or KAI. This study was thus able to suggest new rules for system development based on the assessments of the cognitive styles of both users and systems analysts. These rules focussed primarily on simple team choice: which analyst to put with which user. However, inferences for larger system development teams were drawn and suggestions for further research duly made. The present study thus also contributes to the successful practice of system development. To give effect to the above, this study set out to investigate empirically the way user satisfaction changes over 1½ to 2 years of system usage and, as mentioned above, the way user satisfaction is impacted by the cognitive styles of the user and the systems analyst. Most significantly, relationships were studied between user satisfaction and the difference in cognitive style between the analyst and user. It was found that user satisfaction generally rises linearly with usage, and that while the size of the analyst user cognitive differential does negatively impact user satisfaction over most of the time of system use, this effect is only particularly strong for two short periods; one within the first four months of usage and the other in the last three. From these results the new rules for system development mentioned above, followed. In terms of the decline of users' mean perceived severities of individual problems, the exponential decay and reciprocal models were found to fit the data the best. This study developed a new model for the motivation to use, develop or maintain a system (the Mechanical Model), based on its own results and Herzberg's two-factor theory of motivation. In this, Herzberg's hygiene factors have been replaced with the concept of dissatisfiers. These are measured as expressions of dissatisfaction as and when they occur. Their use removes the researcher's need, when designing user satisfaction instruments, to speculate on complete lists of factors which may satisfy users, and which may date as technology and other contextual factors change.
机译:这项研究主要是在信息系统(IS)领域以及相关的职业心理学和管理领域进行的实证研究。它特别关注用户满意度的概念,应用于用户和系统分析人员的认知风格的构建以及它们之间的相互关系。以前的研究很少发现要调查系统使用期间用户满意度的变化。此外,事实证明,在IS文献中对认知风格的任何提及都是稀疏的,值得商question的,并且就其价值而言是令人沮丧的。通过开发和使用一种新的工具,即“系统满意度计划”,即SSS,本研究能够凭经验证明在使用系统期间改变用户满意度的清晰模式。无论是作为一般趋势,还是与与系统开发和维护相关的关键参与者(分析师和用户)的认知风格的关系,都证明了这些。认知风格是使用Kirton的适应创新量表(KAI)进行衡量的。因此,这项研究能够根据对用户和系统分析师的认知风格的评估,为系统开发提出新的规则。这些规则主要集中在简单的团队选择上:将哪个分析师与哪个用户放在一起。但是,得出了较大的系统开发团队的推断,并提出了进一步研究的建议。因此,本研究也有助于系统开发的成功实践。为了实现上述效果,本研究着手对用户满意度在系统使用1½至2年内变化的方式进行调查,并且如上所述,用户满意度受用户和系统分析师的认知方式影响的方式。最重要的是,研究了用户满意度与分析师和用户之间的认知风格差异之间的关系。发现用户满意度通常随使用情况呈线性增长,并且尽管分析师用户认知差异的大小在系统使用的大部分时间内确实对用户满意度产生负面影响,但这种影响仅在两个短时间内特别明显。一个在使用的头四个月内,另一个在最后三个月内。从这些结果中,可以遵循上述新的系统开发规则。根据用户对各个问题的平均感知程度的下降,发现指数衰减和倒数模型最适合数据。这项研究基于其自身的结果和Herzberg的两因素动机理论,开发了使用,开发或维护系统的动机的新模型(机械模型)。在这方面,赫兹伯格的卫生因素已被不满意的概念所取代。这些衡量标准是不满发生时和不满发生时的表达。他们的使用消除了研究人员在设计用户满意度工具时对可能满足用户以及随着技术和其他背景因素的变化而确定的因素的完整清单进行推测的需要。

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    Mullany Michael John;

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  • 年度 2006
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