
Complex equipment refers to special equipment that differs from general equipment. The collaborative development work of complex equipment in the military-civilian integration context involves numerous suppliers. We consider a two-tier supply network composed of different suppliers that participate in the development work to assemble complex equipment that cooperate with a main-manufacturer regarding spare parts. However, in terms of spare parts, a substitution relationship exists in assembly work for complex equipment. Hence, selecting a suitable supplier from the matching process between suppliers and spare parts under a military-civilian integration background is essential. This study considers three main analyses to obtain a suitable supplier for the development work of complex equipment. First, we construct a two-stage model to acquire the necessary evaluation dimension for subsequent processes. Second, we examine the evaluated attributes for the matching process based on entropy-group-DEMATEL analysis. Third, we perform information aggregation for the uncertain preference information between spare parts and suppliers using a Bonferroni mean operator. Finally, an illustrative example is presented to demonstrate the whole efficiency. Through the aforementioned analysis, we can select a suitable supplier that could participate in complex equipment military-civilian collaborative development work.
Industrial engineering. Management engineering, Two-stage game, Entropy-group-DEMATEL analysis, Military-civilian integration, Complex equipment, T55.4-60.8, Bonferroni mean operator, Collaborative development
Industrial engineering. Management engineering, Two-stage game, Entropy-group-DEMATEL analysis, Military-civilian integration, Complex equipment, T55.4-60.8, Bonferroni mean operator, Collaborative development
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 2 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
