The case of EAI facilitating knowledge management integration in local government domain

被引:11
|
作者
Kamal, Muhammad Mustafa [1 ]
机构
[1] Brunel Univ, Brunel Business Sch, Uxbridge UB8 3PH, Middx, England
关键词
Knowledge integration; EAI; LGAs; Information Systems; IT infrastructure; Integration layers; ENTERPRISE APPLICATION INTEGRATION;
D O I
10.1016/j.ijinfomgt.2011.02.002
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
Information Technology (IT) infrastructure integration and knowledge management (KM) share communal objectives e.g. to transform organisations into more effective and efficient, agile and innovative, and more responsive to market changes. Such an association when assimilates bona fide knowledge management philosophy, it offers the IT departments a headship opportunity for organisational transformation in correlation with the rest of the organisation. Despite more than a decade of active research and practice in this complex problem area, advocates still perceive that Local Government Authorities (LGAs) lack integrated IT infrastructures that have resulted in the generation of data inconsistencies and redundancies, inefficient knowledge exchange and reduction in service quality and delivery. In the recent years, several LGAs have implemented Enterprise Application Integration (EAI) solutions to integrate their IT infrastructure. However, on analysing the relevant research studies, it is noticeable that application of EAI has been practiced at a larger scale in the private domain but to limited scale in the public domain. The shortage of such research studies presents a knowledge gap that needs to be endorsed. This research adapts a Revised Model for Integration Layers (REAL). By adapting to this model, it is exemplified that EAI achieves integration at five layers namely: connectivity, transportation, transformation, process integration and knowledge integration. The methodology for validating this model included a qualitative analysis of data gathered from formal interviews, observations and archive documents guided by initial conceptual observations from the literature. The findings indicate that cases leading to data inconsistencies and replication can be prevented by integrating knowledge through EAI. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:294 / 300
页数:7
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