Heuristics-in-use in industrial interfirm-collaborating clusters - Lai, W.; Woodside, Arch (Emerald Group Publishing Ltd., 2015)
Purpose – The purpose of this paper is to help interfirm-collaborating cluster (ICC) executives examine the relevance of alternative decision rules in practical business contexts. Multi-party-implemented strategies and establishing multi-lateral collaborations are necessary actions for achieving success in new product development by small and medium enterprises (SMEs). This study explores interfirm decision-making heuristics relating to industrial ICCs. Design/methodology/approach – The study examines the relevancy to decision making in ICCs of heurstics such as “fast-and-frugal decision trees” (FFDTs) and “take-the-best” (TTB) to processing possibly influential decision-making cues. The study also examines simple heuristics versus the value of a “fully rational” approach to making decisions – calculating cue values, importance weights, multiplying values by weights, summing and selecting the option having the highest summed score. This study included interviewing executives of the pivotal firm in an ICC. Findings – This study reveals a decision-making solution for shortening the time and processes required in seeking new business collaboration partners in an ICC. This study not only develops a FFDT for six decision-making modules to quickly identify potential collaboration partners, but it also constructs a decision systems analysis (DSA) flowchart to effectively shorten the decision-making process. Research limitations/implications – This study is in accordance with the general type of industrial interfirm collaboration in Taiwan. The industrial interfirm collaboration could be further divided into the types of formal, semi-formal and informal industrial interfirm collaborations. Practical implications – This study argues that firms usually find it difficult to develop their own technology because of the high costs of research and development for SMEs. Therefore, firms need to collaborate with partners to maintain their competitive advantage. However, to collaborate, firms must learn to trust their collaboration partners, and the degree of collaboration also strongly depends on the degree to which they trust their collaboration partners. Originality/value – This study provides the efficient models of FFDT and DSA to quickly identify potential collaboration partners and to effectively shorten decision-making processes.