探索性因素分析
克朗巴赫阿尔法
普通合伙企业
知识管理
可靠性(半导体)
业务
差异(会计)
质量(理念)
营销
产品(数学)
供应链
心理学
服务(商务)
计算机科学
功率(物理)
哲学
物理
几何学
数学
会计
财务
认识论
量子力学
作者
Basu Govindaraju,John Jeyasingam,Md. Mamun Habib,Uvarani Letchmana
出处
期刊:International Journal of Supply Chain Management
日期:2019-08-24
卷期号:8 (4): 152-161
被引量:1
摘要
Abstract: Supply chain management practices (SCMP) have progressively emerged as a contingent factor in improving sustainable performance in universities. More and more organisations including the manufacturing and service sectors are making use of SCM to improve their performance. This study aims to develop an effective instrument to measure SCM practices with reliable predictors to enhance product quality and business performance in education industries in Malaysia. The study measures administrative staff’s response and perceptions regarding SCM practices and its impact on performance in their universities. One hundred and thirty responses were received and the data was analysed using SPSS. The validity and reliability of the instruments used in determining SCM practices were tested using exploratory factor analysis (EFA) and Cronbach’s alpha. Twenty seven items from five competencies comprising: supplier partnership, customer partnership, information sharing, information technology and innovation competencies were designated for the initial instrument. Exploratory factor analysis (EFA) revealed that five factor-structures of the instrument of education SCM practices explained 68.76% of the variance in the pattern of relationships among the items. All five factors had high reliabilities at or above of Cronbach’s > .80. Twenty two items remained in the final questionnaire after deleting five items which cross-loaded on multiple factors. The fiver-factor structure of the education SC practice instrument was confirmed through this study. Thus, practitioners may use such instruments in order to gain a better understanding of the level of contribution of the stated factors towards SCM practices to determine overall university performance and key competencies.
科研通智能强力驱动
Strongly Powered by AbleSci AI