马来西亚研发机构中以创新促进高效工作的做法:神话还是现实?

Mohd Shafiq Mohd Hanafi, A. Asmawi, K. Chew, Chia Yen Yang
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引用次数: 0

摘要

马来西亚的许多政策都强调需要建立卓越的研发能力,将其作为关键的经济驱动力。本研究承认高绩效工作实践(HPWP)对研发创新能力的影响。在社会交换理论的支持下,本研究调查了马来西亚研发机构实施创新增强型 HPWP 的情况及其与项目绩效的关系。研究收集了 210 名项目负责人和成员关于研发项目绩效和创新增强型 HPWP 六个维度的调查数据。结果表明,由于 HPWP 在研发部门可能是一种相对陌生的做法,因此创新增强型 HPWP 的实施率仍然较低。然而,HPWP 的四个维度对研发项目绩效有显著的预测作用:员工招聘、绩效评估、奖励与报酬以及员工参与。这些发现将指导管理人员制定相关的 HPWP,以促进创新。这包括对现有研发人员、流程和产品进行全面审核,以及如何将这三个 "P "简化为促进创新的 HPWP。
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INNOVATION-ENHANCING HIGH-PERFORMANCE WORK PRACTICES IN MALAYSIAN R&D ORGANIZATIONS: MYTH OR REALITY?
Numerous Malaysia policies underscore the need to build exceptional R&D capabilities as the key economic driver. This study acknowledges the influence of high-performance work practices (HPWP) on R&D innovativeness. Underpinned by social exchange theory, this study investigates the implementation of innovation-enhancing HPWP in Malaysian R&D organisations and their relationship with project performance. Survey data on R&D project performance and six dimensions of innovation-enhancing HPWP were collected from 210 project leaders and members. Results suggested that innovation-enhancing HPWP implementation is still low as HPWP might be a relatively unknown practice in the R&D sector. Nevertheless, four HPWP dimensions were significant predictors of R&D project performance: employee recruitment, performance appraisal, reward and compensation, and employee participation. These findings will guide managers in developing relevant HPWPs to foster innovativeness. This includes a comprehensive audit of existing R&D people, processes, and products, and how these three `Ps’ can be streamlined into an innovation-enhancing HPWP.
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INNOVATION-ENHANCING HIGH-PERFORMANCE WORK PRACTICES IN MALAYSIAN R&D ORGANIZATIONS: MYTH OR REALITY? THE RELATIONSHIP AMONG U-CONSTRUCTS, TRUST AND SATISFACTION: EVIDENCE FROM MOBILE BANKING USERS CONSUMERS’ PERCEPTIONS TOWARDS CELL PHONE BRAND PREFERENCE: THE CASE OF BANGLADESH IMPACT OF PRODUCTIVITY, CORRUPTION, AND GROWTH ON DEBT: EVIDENCE FROM PANEL DATA ANALYSIS ANALYSING THE ROLE OF DRIVER BEHAVIORS IN ROAD TRAFFIC ACCIDENTS: AN APPLICATION OF MACHINE LEARNING
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