Order Life Cycle Research Articles

What are the root causes of material delivery schedule inaccuracy in supply chains?

PurposeThis study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?Design/methodology/approachA mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.FindingsThe effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.Practical implicationsThe findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.Originality/valueThe findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?

НЕЧЕТКАЯ ОЦЕНКА ПЕРСПЕКТИВНОСТИ ЗАКАЗА ДЛЯ ИННОВАЦИОННОГО ПРЕДПРИЯТИЯ

The authors of this article propose developing a methodology for assessing the potential of an order for an innovative industrial enterprise, taking into account uncertainty at the contracting stage and using international industry profitability and turnover standards. Such a proposal is positioned in the «modified marginal profitability – asset turnover» coordinates. Depending on the niche that the order falls into, the enterprise chooses one of three negotiation strategies for the order: a) determining the volume of concessions, b) fighting for basic contract terms, or c) refusing to execute the order. Accounting for uncertainty in the order based on a fuzzy model allows the enterprise to assess the risks that, during the order's life cycle, it will be depositioned (change its niche) and ultimately prove unprofitable for the enterprise. A calculation example is included. Order risk management based on a fuzzy model enables enterprises to take preemptive measures to counter risks (shortening production times, minimizing the cost of the order, hedging import operations, etc.). If the integrated risk during the negotiation stage exceeds 20%, the order priority should be reduced and the terms of its contract should be reevaluated during the negotiation or tender process. This article focuses on the starting risk background around the order. However, a model can be proposed in which the integrated risk of the order is assessed at all stages of its life cycle, including aftersales services. These proposals are aimed at enterprises with smallscale custom production and a high proportion of hightech products in circulation. For such enterprises, order risk management is the basis for survival and maintaining acceptable levels of profitability.