Proceedings of the 8th International Conference on Intellectual ...

Value Creation Through Collaborative Supply Chain:
Holistic Performance Enhancement Road Map
Ridha Derrouiche 1 , Pongsak Holimchayachotikul 2 and Komgrit Leksakul 2
1
ESC – LSTI, Saint Etienne, France
2
Department <strong>of</strong> Industrial Engineering, Faculty <strong>of</strong> Engineering, Chiang Mai
University, Thailand
ridha_derrouiche@esc-saint-etienne.fr
holimchayachotikul@hotmail.com
komgrit@eng.cmu.ac.th
Abstract: This paper proposes an integrated novel framework between B2B-SCM using data mining techniques
such as K-Means based on particle swarm intelligence (PSO) and association rule. It constructs relationship rules
<strong>of</strong> holistic performance enhancement road map. The data set <strong>of</strong> relationships between enterprise and its direct
customers <strong>of</strong> <strong>the</strong> case study organizations in France was used for demonstration. The experiment results show
how domain managers powerfully utilize <strong>the</strong> graphical analysis results to provide <strong>the</strong> holistic performance
improvement and weakness resolution relationship rules. In <strong>the</strong> long run, organizations are able to use this
framework to design and adjust <strong>the</strong>ir units to conform <strong>the</strong> exact customer needs. This paper introduces and
explains a new idea <strong>of</strong> measuring value added along <strong>the</strong> supply chain from a collaborative perspective. The
extended model is adapted from our previous model and from Balanced Score Card (BSC) model. It provides a
tool to measure tangible and intangible value between partners.
Keywords: supply chain collaboration, value creation, holistic performance enhancement road map k-means,
particle swarm intelligence, association rules
1. Introduction
In recent decade, many global organizations have extensively integrated performance measurement
and management system (PMM) to SCM which is time completive weapon. On <strong>the</strong> o<strong>the</strong>r hands, <strong>the</strong>y
have also accumulated a ton <strong>of</strong> data from PMM reports which came from each unit in SCM. These
result from <strong>the</strong> lack <strong>of</strong> holistic performance improvement (PM) which takes advantage from <strong>the</strong> right
direction <strong>of</strong> collaborative PM. They still independently and individually build <strong>the</strong>ir performance up;
some <strong>of</strong> <strong>the</strong>ir linkages <strong>of</strong> performance attributes between supply chain (SC) units still lack vital
information extraction to improve <strong>the</strong>irs. Consequently, each SC unit does not have <strong>the</strong> applicable
holistic PM roadmap development toge<strong>the</strong>r. This leads to <strong>the</strong> primary question <strong>of</strong> this article which is
“How can we extract <strong>the</strong> vital information from a ton <strong>of</strong> PMM database using DM <strong>the</strong>ory and concept”
However, <strong>the</strong> DM concept and <strong>the</strong>ory are applicable directly to marketing and business problems, but
<strong>the</strong> PMM in SCM problem structure and database does not differ from <strong>the</strong> former. Clustering and
association rules have been becoming <strong>the</strong> popular techniques in business research field. The PMM in
SCM researches are still not certain <strong>of</strong> tangible and intangible benefits. These may achieve. To
promote <strong>the</strong> use <strong>of</strong> <strong>the</strong> integration between K-Means base on PSO and association rules with PMM in
SCM context is <strong>the</strong> challenge. All said before is why DM concept and <strong>the</strong>ory should consider as <strong>the</strong>
potential approach to <strong>the</strong> PMM in SCM.
Therefore, this article proposes <strong>the</strong> implementation and deployment <strong>of</strong> holistic performance
enhancement road map using K-Means base on PSO and association rules for B2B-SCM context.
The rest <strong>of</strong> this paper is organized as follows. In <strong>the</strong> second section illustrates <strong>the</strong> fundamental <strong>of</strong> this
research and reviews related literatures. The methodology <strong>of</strong> <strong>the</strong> proposed means is described in <strong>the</strong>
third section. Results and discussion are provided in <strong>the</strong> fourth section. The fifth section introduces
and explains a new idea <strong>of</strong> measuring value added along <strong>the</strong> supply chain from a collaborative
perspective. The extended model is adapted from our previous model and from Balanced Score Card
(BSC) model. It provides a tool to measure tangible and intangible value between partners. Finally,
<strong>the</strong> conclusions and fur<strong>the</strong>r research direction are warped up in <strong>the</strong> fifth section..
2. Context and literature review
Supply chain collaboration is <strong>of</strong>ten defined as two or more enterprises working toge<strong>the</strong>r to create a
competitive advantage and higher pr<strong>of</strong>its that cannot be achieved by acting alone (Simatupang and
Sridharan 2005). In this paper <strong>the</strong> term collaboration is chosen to describe <strong>the</strong> close cooperation
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