ASSESSING SUPPLY NETWORK COMPLEXITY IN MARITIME INDUSTRY IN MALAYSIA: INTER-FIRMS€™ RELATIONS DRIVES PATTERN OF SUPPLY NETWORK STRUCTURE

Background: Complexity has been an interesting research area for academics and businesses practices due to its relevance in determining the best practices and impacts to the supply network.  The contribution of this research extend to the literature and put forward solutions for the industry since previous studies are neglecting whole network relations, which is highlighted as source of supply network complexity (SNC).  Specifically, this research extends to enriching the literature and recommending solutions to the industry players since previous studies are neglecting important Inter Firm Relation (IFR) elements, formal inter-firm relation (FIFR) and informal inter-firm relations (IIFR), which are highlighted as a pertinent factor in this research.  In this study, the Social Network Analysis (SNA) method was adopted to develop valid attribute for the measurement process and the embeddedness theory was used to evaluate the interrelationships among the proposed attributes.  This study found that FIFR and IIFR have different effects towards the formation of SNS and consequently towards SNC.  Finally, theoretical and industrial implications are also discussed.

Methods: Traditional statistical tools focus on attributes of phenomenon as determinants for occurrence of economic payoff.  Thus, traditional statistical analysis is not suitable to measure the impact of relations or connections among member of network contributing to network complexity.  For the purpose of this research, the Social Network Analysis methodology was adopted to collect, analyse and interpret network data.  Network survey was conducted to collect relational data among members of maritime industry supply network.  Network data was analysed and interpreted using specialized social network program i.e. UCINET and NETDRAW.  Statistical network measures such as centralization and density was applied to determine the relations between network complexity and network relations.

Results: The findings of this study indicate that Inter Firm Relation (IFR), formal inter-firm relation (FIFR) and informal inter-firm relations (IIFR), which are highlighted as a pertinent factor in this research,  have different effects towards the formation of SNS and consequently towards SNC.

Conclusion: The results of the statistical network analysis indicate that, network complexity exist in different forms and structure, depending on the type of relations that formed the network in the first place.  Consequently, what these mean are, managing network requires different types of resource and strategy as the level of the network complexity are different at different states of connectivity.