8. Infraestructura de respaldo
8.6. Asistencia administrativa mutua
This study explained 33% variance in supply chain configuration complexity through product demand volatility, product life cycle and product innovativeness. Supply chain configuration was conceptualised through a number of value adding tiers, number of logistics channels in supply chain and partnerships. Table 8.2 below summarises the influences of product demand and design characteristics on supply chain configuration complexity.
Table 8.2: Standardised Effects of Impacts on Supply Chain Configuration Complexity
Supply Chain Configuration Complexity
Direct
S.E. p value
Product Demand Volatility 0.375 0.005
Product Life Cycle 0.259 0.004
Product Innovativeness 0.313 0.004
Product Modularity 0.016 0.886
Product demand volatility has a significant impact on supply chain configuration complexity
with a standardised effect of 0.375. Hence, hypothesis 3 – H3: Product demand volatility
positively impacts on supply chain configuration complexity – is supported. Thus, under high
demand volatility conditions, supply chain configuration is deemed to be more complex. A closed loop supply chain configuration proposed by Amin and Zhang (2013) considered demand uncertainty as the main factor in supply chain design. El Maraghy and Mahmoudi (2009) also claim that supply chain configuration in certain geographical locations should match demand requirements. The volatility of demand can further impact on the supply chain
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strategies, in terms of responding to this demand through strategic location or number of facilities, i.e. production plants, distribution centres and warehouses. Results strongly support Amin and Zhang (2013) and El Maraghy and Mahmoudi (2009) in that they confirm the impact of product demand on supply chain configuration and design. This relationship emphasises the necessity to align supply chain configuration with product demand volatility.
Product life cycle has a significant relationship with supply chain configuration complexity.
The standardised effect of product life cycle on supply chain configuration is 0.259. Therefore, hypothesis 7 – H7: Product life cycle positively impacts on supply chain
configuration complexity – is supported. Supply chains of products with longer life cycles are
more complex while products with shorter life cycles have less complex supply chain configuration to respond to tense lead times. Short product life cycles impose time pressures on firms and new product development operations. The product design, procurement, production, distribution and delivery operations have to be executed in a more agile and time efficient way. Shorter product life cycles require faster production and delivery lead time (Olhager, 2010), enabling manufacturing plants to be closer to their final consumers. As new products are being introduced to global distribution networks with increasing frequency, plus the added complication of withdrawing obsolete products at the end of their now very short life cycles, the frequency of new product development will increase. This outcome will in turn create greater supply chain complexity (Fisher, 1997). Findings of this research support the arguments made by others (i.e. Mason Jones et al., 2000a; Fisher, 1997; Olhager, 2010) and suggest product life cycle is one of the main determinants of supply chain configuration complexity.
Product innovativeness’s impact on supply chain configuration complexity is significant with
a standardised effect of 0.31. Based on this finding, hypothesis 10 – H10: Product
innovativeness positively impacts on supply chain configuration complexity – is supported.
Therefore higher product innovativeness is a source of higher supply chain configuration complexity. Increasing product innovativeness will increase the number of new product development projects, which will consequently increase the supply chain complexity. This product innovativeness requires supply chains to be more global and fragmented in multiple locations so that new innovative technologies can be harnessed. Innovativeness with respect to different degrees of mass customisation necessitates different approaches to supply chain configuration, primarily depending on variations in customer specifications (Salvador et al.,
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2014). Pero et al. (2010) also suggest that highly innovative products call for deep changes in product architectures so that various suppliers can be engaged. Furthermore, case studies by Caridi et al. (2009) also indicated that more innovation in NPD projects results in higher supply chain configuration complexity. Results of this study support previous research and reiterate the importance of aligning supply chain configuration with product innovativeness.
Product modularity has no significant relationship with supply chain configuration
complexity. Therefore, hypothesis 13 - H13: Product modularity positively impacts on supply
chain configuration complexity, is not supported. This is in contrast with previous research.
Product modularity is a key enabler of outsourcing, co-development and therefore competitive advantage (Howard & Squire, 2007; Jacobs et al., 2007; Swink et al., 2007; Lau et al., 2010b). Furthermore, product modularity can increase outsourcing and offshore manufacturing. It wields an important influence on integration strategies. Build-to-order strategies enabled by product modularity will complement such outsourcing decisions. Chiu and Okudan (2014) observed that increased modularity is critical for design and integration of supply chain and therefore the configuration. According to Kumar and Chatterjee (2013) modularity at different levels to satisfy customer needs in different markets increases supply chain configuration complexity. Product modularity combined with the relocation of value adding activities and a reduced supplier base will decrease the level of vertical integration (Pero et al., 2010). It will also increase the number of supply chain partners and therefore increase the supply chain configuration complexity. However, the findings of this thesis do not support previous research and their propositions. One explanation for these contradictory results is the methodological differences or the sample characteristics. Previous studies in the majority of cases chose a case study approach while this study is performed across several manufacturing industries. Nevertheless this outcome suggests further investigation is needed to assess the impact of product modularity on supply chain configuration.