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Understanding continued smartwatch usage: the role of emotional as well as health and fitness factors
Electronic Markets ( IF 7.1 ) Pub Date : 2021-02-18 , DOI: 10.1007/s12525-021-00458-3
Carolin Siepmann , Pascal Kowalczuk

Smartwatches are the most popular wearable device and increasingly subject to empirical research. In recent years, the focus has shifted from revealing determinants of smartwatch adoption to understanding factors that cause long-term usage. Despite their importance for personal fitness, health monitoring, and for achieving health and fitness goals, extant research on the continuous use intention of smartwatches mostly disregards health and fitness factors. Grounding on self-determination theory, this study addresses this gap and investigates the impact of health and fitness as well as positive and negative emotional factors encouraging or impeding consumers to continuously use smartwatches. We build upon the expectation-confirmation model (ECM) and extend it with emotional (device annoyance and enjoyment) as well as health and fitness factors (goal pursuit motivation and self-quantification behavior). We use structural equation modeling to validate our model based on 335 responses from actual smartwatch users. Results prove the applicability of the ECM to the smartwatch context and highlight the importance of self-quantification as a focal construct for explaining goal pursuit motivation, perceived usefulness, confirmation and device annoyance. Further, we identify device annoyance as an important barrier to continuous smartwatch use. Based on our results, we finally derive implications for researchers and practitioners alike.



中文翻译:

了解智能手表的持续使用:情感以及健康和健身因素的作用

智能手表是最流行的可穿戴设备,并且越来越受到实证研究的影响。近年来,重点已经从揭示智能手表采用的决定因素转移到了理解导致长期使用的因素。尽管它们对于个人健康,健康监测以及实现健康和健身目标非常重要,但有关智能手表持续使用意图的现有研究大多忽略了健康和健身因素。这项研究基于自我决定理论,解决了这一差距,并研究了健康和健身以及鼓励或阻止消费者继续使用智能手表的正面和负面情绪因素的影响。我们以期望确认模型(ECM)为基础,并在情感(设备烦恼和娱乐)以及健康和健身因素(目标追求动机和自我量化行为)方面进行扩展。我们使用结构方程建模,基于来自实际智能手表用户的335个响应来验证我们的模型。结果证明了ECM在智能手表环境中的适用性,并强调了自我量化作为解释目标追求动机,感知的有用性,确认和设备烦恼的重点结构的重要性。此外,我们将设备烦恼识别为持续使用智能手表的重要障碍。根据我们的结果,我们最终对研究人员和从业人员都产生了启示。我们使用结构方程建模,基于来自实际智能手表用户的335个响应来验证我们的模型。结果证明了ECM在智能手表环境中的适用性,并强调了自我量化作为解释目标追求动机,感知的有用性,确认和设备烦恼的重点结构的重要性。此外,我们将设备烦恼识别为持续使用智能手表的重要障碍。根据我们的结果,我们最终对研究人员和从业人员都产生了启示。我们使用结构方程建模,基于来自实际智能手表用户的335个响应来验证我们的模型。结果证明了ECM在智能手表环境中的适用性,并强调了自我量化作为解释目标追求动机,感知的有用性,确认和设备烦恼的重点结构的重要性。此外,我们将设备烦恼识别为持续使用智能手表的重要障碍。根据我们的结果,我们最终对研究人员和从业人员都产生了启示。我们认为设备烦恼是持续使用智能手表的重要障碍。根据我们的结果,我们最终对研究人员和从业人员都产生了启示。我们认为设备烦恼是持续使用智能手表的重要障碍。根据我们的结果,我们最终对研究人员和从业人员都产生了启示。

更新日期:2021-02-19
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