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  • 标题:Modeling Critical Success Factors Influencing Energy Management Performance towards Sustainability in Malaysian Public Universities Using PLS-SEM Approach
  • 本地全文:下载
  • 作者:Alia Abdullah Saleh ; Abdul Hakim Mohammed
  • 期刊名称:International Journal of Academic Research in Business and Social Sciences
  • 电子版ISSN:2222-6990
  • 出版年度:2017
  • 卷号:7
  • 期号:12
  • 页码:165-173
  • DOI:10.6007/IJARBSS/v7-i12/3602
  • 语种:English
  • 出版社:Human Resource Management Academic Research Society
  • 摘要:Energy usage in Malaysian universities has increased constantly. Frequent commentaries in the literature have stated by identifying critical success factors (CSFs) and continually measured using Key Performance Indicators (KPIs) will ensure successful effective performance for the organization. However, no one has yet tried to define in a formal way these relationships. Thus, this study is carried out to identify the CSFs and determine the relationship of identified CSFs with the KPIs, indirectly developing the CSFs structural model. The conceptual model is composed by exogenous latent variables (LVs) namely Top Management Support, Comprehensive Energy Management Team, Awareness, Strategic Maintenance Management and Good Relationship of Stakeholders and one endogenous LVs which is KPIs to achieve the goals of energy management performance improvement. The study presents empirical evidence from a survey of five research universities in Malaysia, where 280 sets of questionnaire were analyzed using PLS-SEM to test the conceptual model. The indicators for these enablers and result criteria were extracted from the past literature and by a pilot study. The findings show that the comprehensive EM team has the highest path coefficient (? value) which has the most significant relationship on KPIs (?=0.195; t-value=2.701) followed by strategic maintenance management (?=0.187; t-value= 2.661); awareness (?=0.149; t-value=2.336); top management support (?=0.106; t-value=1.963); and the least is good relationship of stakeholders (?=0.104; t-value=1.443). From the findings, this study provide insight to management team in universities to focus on the implications from these four constructs to improve the energy management performance within an organization.
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