Intelligent model design of complex system becomes a key issue for organization responsiveness to uncertainties. In the real business world, the rule of competition between one firm verse another is replaced by a chain verse another chain, the cooperation is the same, where does it occur? At industrial cluster, there are a multiple of rivals or potential competitors for each member of value chain, industrial cluster location not only contains a couple of focal firms locating at the same tier, but includes the corresponding upstream and downstream firms as well, all of which concentrate on a close geographical site. For adopting to ever-changing market and sever competition, it is most likely to form multiple paralleled single supply chains for each focal firm of industrial cluster, these paralleled single supply chains compete and cooperate with each other. Recent researches regarding supply chain design mainly focus on a limited tier in single supply chain, which only take into account vertical cooperation and ignore the across-chain horizontal one. This paper, based on cluster supply chain, provides a novel framework and approach to design cluster supply chain without across-chain horizontal cooperation, then by introducing item allocation proportion of vertical and horizontal cooperation (α: 1 − α), the cluster supply chain design with acrosschain horizontal cooperation is developed, then presents a hybrid method to find solution, at last, computational study is presented to investigate values of decision variables and their influence on cluster supply chain design.
Due to inadequate designers in fast fashion industry and the development of the Internet, small-and-medium-sized garment makers have gradually turned to external talents to enhance their new product design efficiency via crowdsourcing initiative. This paper presents a new framework of crowdsourcing supply chain for fast fashion industry. First, a basic multiperiod order model is established in a crowdsourcing supply chain system, where a garment maker chooses the best one among available solutions submitted by online designers (i.e., crowdsources) in each period, then transforms it into finished product, and sells to consumers through a retailer. Second, we extend this model by integrating the factors of capital turnover, the retailer’s risk-aversion, and the garment maker’s minimum production quantity. Moreover, utilizing wholesale price, buyback, and profit-sharing scheme designs a mixed contract for coordinating crowdsourcees, retailer, and garment maker of crowdsourcing supply chain for achieving Pareto optimality. The models help the garment maker determining the optimal production quantities of crowdsourcing designed products and enable the retailer placing the optimum orders and setting the reasonable risk level. In addition, we also find that the incentive policy for crowdsourcing designers can be fulfilled by using a profit-sharing scheme with a piecewise function of order quantity instead of a linear function.
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