肯尼亚上市公司商业智能能力、资源互补与绩效

IF 0.6 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE International Journal of Biometrics Pub Date : 2020-08-16 DOI:10.5539/ijbm.v15n9p66
Edward Buhasho, A. Wausi, J. Njihia
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引用次数: 0

摘要

尽管商业智能计划多年来一直是全球许多组织的主要关注点,并且占数十亿美元的资本支出,但关于这项投资所产生的实际影响的实证研究仍然很少。即使确立了利益,其对业务结果的间接和延迟影响也使评估其价值变得困难。关于如何将商业智能引发的洞察力转化为可盈利的业务学习的现有文献是模糊和分散的。因此,本研究的主要目的是建立互补资源对商业智能能力与企业绩效之间关系的影响。本研究运用跨学科的理论,即信息系统能力理论和组织学习来实现研究目标。本研究采用混合研究方法和横断面研究方法。数据收集自肯尼亚的64家上市公司。研究发现,互补资源对企业商业智能能力与绩效之间的关系具有显著的正向影响。该研究通过构建商业智能评估框架,包括显著提高绩效的因素,为理论做出了贡献。研究结果还为现有文献提供了新的见解,并为未来的研究方向提出了建议,对学术界、政策制定者和管理层具有重要意义。
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Business Intelligence Capability, Complementary Resources and Performance among Public Listed Firms in Kenya
Whereas Business Intelligence initiative has been a primary focus many organisations globally for several years and accounting for billions of dollars in capital expenditure, empirical research remains sparse on the actual impact derived from this investment. Even when the benefits are established, its indirect and delayed impact on business results make it difficult to assess its value. Available literature on how insights triggered by Business Intelligence are transformed into profitable business learning is vague and fragmented. Hence, the main objective of this study was to establish the influence of complementary resources on the relationship between Business Intelligence capability and firm performance. The study used interdisciplinary theories to achieve the research objective, namely, Information systems capability theory and organisational learning. The study was performed using a mixed methods research methodology and cross-sectional approach. Data was collected from 64 public listed companies in Kenya. Findings indicated that complementary resources have a positive and significant impact on the relationship between Business Intelligence capability and performance. The study contributed to theory by building a framework for business intelligence assessment, including factors that significantly lead to improved performance. The results also provide new insights into the existing literature and suggest directions for future research with implications for academia, policymakers and management.
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来源期刊
International Journal of Biometrics
International Journal of Biometrics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
1.50
自引率
0.00%
发文量
46
期刊介绍: Biometrics and human biometric characteristics form the basis of research in biological measuring techniques for the purpose of people identification and recognition. IJBM addresses the fundamental areas in computer science that deal with biological measurements. It covers both the theoretical and practical aspects of human identification and verification.
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