Measuring supply chain knowledge management (SCKM) performance based on double/triple loop learning principle

被引:18
作者
Ramish, Asher [1 ]
Aslam, Haris [1 ]
机构
[1] Univ Management & Technol, Dept Operat & Supply Chain, Lahore, Pakistan
关键词
Performance measurement; Supply chain; Key indicators; KPI; Inter-organizational learning; Knowledge management; Learning; Performance measures; Supply chain knowledge management; Double loop learning; Triple loop learning;
D O I
10.1108/IJPPM-01-2015-0003
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Purpose - The purpose of this paper is to propose performance measures for supply chain knowledge management (SCKM) performance. Design/methodology/approach - This is a conceptual study. State of performance measurement has been analyzed on the basis of a comprehensive review of literature in field of SCKM. Based on principles of double and triple loop learning, performance measures have been identified for measuring the success of KM practices in SCs. Findings - Principles of double identity and knowledge supply chain stratum. The relevance and justification of these KPI's is also discussed. Research limitations/implications - This study is limited to conceptualized measures for SCKM only. Further research is required to test the benefits of these performance measures based on industry applications. Practical implications - These proposed KPI's will facilitate the development of the new processes through re-engineering, i.e. problem identification and then rectification. Further, these KPI's will provide some essential insights as to how supply chains can develop their performance evaluation systems to become more effective and learning oriented. Originality/value - This study aims to not only identify the gaps present in the SCKM performance measurement literature but also aims to fill the knowledge gap by suggesting suitable performance metrics.
引用
收藏
页码:704 / 722
页数:19
相关论文
共 72 条
[41]   Strategic supply chain management: Improving performance through a culture of competitiveness and knowledge development [J].
Hult, G. Tomas M. ;
Ketchen, David J., Jr. ;
Arrfelt, Mathias .
STRATEGIC MANAGEMENT JOURNAL, 2007, 28 (10) :1035-1052
[42]   A bottom-up approach for productivity measurement and improvement [J].
Jagoda, Kalinga ;
Lonseth, Robert ;
Lonseth, Adam .
INTERNATIONAL JOURNAL OF PRODUCTIVITY AND PERFORMANCE MANAGEMENT, 2013, 62 (04) :387-406
[43]  
Johnson H.T., 1987, RELEVANCE LOST RISE
[44]  
KAPLAN RS, 1992, HARVARD BUS REV, V70, P71
[45]   Development of performance-based service strategies for the oil and gas industry: a case study [J].
Kumar, Rajesh ;
Markeset, Tore .
JOURNAL OF BUSINESS & INDUSTRIAL MARKETING, 2007, 22 (4-5) :272-280
[46]  
Lambert D.M., 2001, INT J LOGIST MANAG, V12, P1
[47]   Collaborative knowledge management practices Theoretical development and empirical analysis [J].
Li, Yulong ;
Tarafdar, Monideepa ;
Rao, S. Subba .
INTERNATIONAL JOURNAL OF OPERATIONS & PRODUCTION MANAGEMENT, 2012, 32 (3-4) :398-422
[48]   The implementation gaps for the knowledge management system [J].
Lin, C ;
Tseng, SM .
INDUSTRIAL MANAGEMENT & DATA SYSTEMS, 2005, 105 (1-2) :208-222
[49]   Managing knowledge contributed by ISO 9001: 2000 [J].
Lin, Chinho ;
Wu, Chuni .
INTERNATIONAL JOURNAL OF QUALITY & RELIABILITY MANAGEMENT, 2005, 22 (09) :968-+
[50]   Metrics and performance measurement in operations management: dealing with the metrics maze [J].
Melnyk, SA ;
Stewart, DM ;
Swink, M .
JOURNAL OF OPERATIONS MANAGEMENT, 2004, 22 (03) :209-217