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Extending the Diffusion of Innovation Theory to Predict Smartphone Adoption Behaviour Among Higher Education Institutions’ Lecturers in Nigeria

机译:延长创新理论的扩散,以预测高校尼日利亚高等教育机构讲师的智能手机采用行为

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With the rise in the number of ICT-enabled devices in Nigeria and considering the relevance and importance of these devices in effective teaching, it becomes legitimate and inevitable to understand the key predictors of smartphone adoption among lecturers in the higher education institutions (HEIs). While extant literatures are gorged with such investigations, the majority of Sub-Saharan African contexts are grossly under-researched. Using this as a point of departure, this paper seeks to answer these questions: what are the predictors of smartphone adoption among the university lecturers? And how do these identified predictors influence smartphone adoption among university lecturers? Since smartphone is a new technological device and its adoption as a teaching-enabled device is different from its traditional adoption for communication, the main objective of this paper is to empirically investigate the predictors of smartphone adoption among Nigerian university lecturers. The study was based on the lecturers of Nnamdi Azikiwe University, Awka, Anambra State, Nigeria. Data were collected using questionnaire based on multistage sampling technique of 284 respondents. Factor analysis and multiple regressions were used for data reduction and hypotheses testing respectively. Analyses of data reveal that personal experience, relative advantage, job relevance, triability, complexity and price were the predicators of smartphone adoption. The findings have serious implications for smartphone retail management among others.
机译:随着尼日利亚的能力的设备数量的增加,并考虑这些设备在有效教学中的相关性和重要性,了解高等教育机构(HEIS)讲师中智能手机采用的关键预测因子成为合法和不可避免的。虽然现存文献具有此类调查,但大多数亚撒哈拉非洲语境都有严重的研究。用这是一个出发的点,本文寻求回答这些问题:大学讲师中智能手机采用的预测因素是什么?这些识别的预测器如何影响大学讲师之间的智能手机?由于智能手机是一种新的技术设备,并且通过其作为一种教学的设备采用与传统的通信采用不同,因此本文的主要目标是经验研究尼日利亚大学讲师中智能手机采用的预测因素。该研究基于Nnamdi Azikiwe大学的讲师,Awka,Anambra State,尼日利亚。基于284名受访者的多级抽样技术使用调查问卷收集数据。因子分析和多元回归分别用于数据减少和假设测试。数据分析表明,个人经验,相对优势,工作相关性,可生力,复杂性和价格是智能手机采用的备件。调查结果对智能手机零售管理有严重影响。

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