No abstract

The extended warranty is an important strategy for the manufacturers to expand their market share. In this work, we studied the optimal extended warranty length considering preventive maintenance behaviour, which mainly avoids the producers and consumers' moral hazard. Based on the profit function maximization, the optimal extended warranty length under different situations can be achieved. We conducted a simulation analysis to see the influence on preventive maintenance behaviour during the warranty period to the optimal extended warranty length.

PurposeIn this study, the focus was shifted from repairing durable goods to achieving healthier ecology, making durable goods more secure in turn. This study introduced preventive maintenance behavior to trace the ex-post control of “curling” back to the ex-post control of “self-healing.” This study tries to close the gap between the human repair of machines and their “self-curing.” Finally, the author makes the machines healthier.Design/methodology/approachThe paper constructed a mathematical model of preventive maintenance behavior during a specific period for durable consumer goods. The author builds a simulation function of the two-stage preventative maintenance behavior relations. The study used simulations to analyze the influencing relationship and differences between three preventive maintenance behavior elements to basic warranty preventive maintenance (BWPM) behavior and extended warranty preventive maintenance (EWPM) behavior.FindingsBoth BWPM behavior and EWPM behavior were affected by the preventive maintenance (PM) behavioral components in different ways. The influence paths of the two warranty periods affected by PM behavior were also different.Research limitations/implicationsThis study introduced PM behavior to trace the ex-post control of “curling” back to the ex-post control of “self-healing.” This study adopted the human–machine interaction mode to improve durable goods' self-healing ability during operation and enable a more effective and sustainable development.Practical implicationsThis study’s conclusions may help manufacturers guide PM behavior in a way that achieves “self-healing” of the durable goods.Originality/valueThe author opened a “black box” of PM behaviors and analyzed their components. The internal structure relation of PM behavior is built and the closed-loop system of spatial structure is formed.

How to promote deep knowledge transfer and knowledge application during the process of R&D achievements delivery? This paper takes knowledge transfer as the research object. First of all, the path of knowledge transfer during the process of R&D achievements delivery is drawn. Next, the status of knowledge transfer is assessed by constructing users’ tolerance zone model by selecting key factors in the path of knowledge transfer. Empirical research finds the following conclusions: knowledge transfer experience[Formula: see text], knowledge transfer distance and knowledge transfer carrier have a positive influence on the actual service level of knowledge transfer. Knowledge transfer experience[Formula: see text], continuous strengthening behavior and knowledge service commitment have a positive impact on the ideal service level of knowledge transfer. Then, based on knowledge transfer path and users’ tolerance zone model, this paper explores the knowledge navigation model from the environment, main structure and transmission mode. Finally, from the perspective of knowledge transfer environment, knowledge transfer subject, knowledge transfer object and knowledge transfer mode, the relevant strategies were put forward to reduce knowledge retention, and promote the deep knowledge absorption and transformation during the process of R&D achievements delivery.

In the situation of indirect network effect, this paper mainly studies the optimal extended warranty price. First, the characteristics of the extended warranty price are discussed. Next, the optimal extended warranty price model is advanced. From the model, the authors can draw that the influence factors mainly include the producer and consumers’ risk preferences, the incompatible degree of the producer’s maintenance technology, the extended warranty period, the producer and consumers’ per-occasion maintenance cost. Finally, the authors carry the simulation method to indicate their influence relation. The results have theoretical significance for the automobile producer to ensure the optimal extended warranty price.