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Intermittent demand appears sporadically, with some time periods not even displaying any demand at all. Even so, such patterns constitute considerable proportions of the total stock in many industrial settings. Forecasting intermittent demand is a rather difficult task but of critical importance for corresponding cost savings. The current study aims to examine the empirical outcomes of three heuristics towards the modification of established intermittent demand forecasting approaches.

First, optimization of the smoothing parameter used in Croston's approach is empirically explored, in contrast to the use of an a priori fixed value as in earlier studies. Furthermore, the effect of integer rounding of the resulting forecasts is considered. Lastly, the authors evaluate the performance of Theta model as an alternative of SES estimator for extrapolating demand sizes and/or intervals. The proposed heuristics are implemented into the forecasting support system.

The experiment is performed on 3,000 real intermittent demand series from the automotive industry, while evaluation is made both in terms of bias and accuracy. Results indicate increased forecasting performance.

The current research explores some very simple heuristics which have a positive impact on the accuracy of intermittent demand forecasting approaches. While some of these issues have been partially explored in the past, the current research focuses on a complete in‐depth analysis of easy‐to‐employ modifications to well‐established intermittent demand approaches. By this, the authors enable the application of such heuristics in an industrial environment, which may lead to significant inventory and production cost reductions and other benefits.

The implementation of sustainable supply chain management (SCM) calls for an acknowledgement of uncertainty inherent in complex environment. Confucianist society forms social networks in Confucianist society, called guanxi networks, influence economic behaviours and business practices in the workplace. The purpose of this study is to explore how these social networks influence the implementation of sustainable SCM. In doing so, this study aims to critically investigate the constructs of guanxi networks, their impact on flow of supply chain capital and how this leverages the implementation of sustainable SCM.

Two systematic literature reviews are conducted to understand the constructs of social networks in Confucianist culture and their impacts on the flow of supply chain capitals. The reviews also analyse evidence related to the economic, social and environmental practices to reveal the current state of the literature and research gaps. Propositions and a framework are developed to support future research in this area.

The constructs of ganqing, renqing, xinren and mianzi in guanxi networks have expanded the contexts of social networks in Western literature. Guanxi networks increase the flow of supply chain capital and generate trust between players, thus enhancing capabilities to implement sustainable SCM. Guanxi networks also create the mechanism of network governance with which to increase sustainable SCM implementation under the institutional logics of sustainability.

The conceptual framework and justification are based on the reviews of current studies in the field. Future empirical study is encouraged to test the propositions, both in Confucianist culture and other countries with culture of social networks.

Social networks are socially constructed concepts. The constructs of guanxi networks revealed in this study have developed the knowledge of Western-based social network theory. Besides, arguments from a social network perspective provide an alternative answer to explain increased behavioural commitment and companies’ investment in sustainable SCM. This study helps practitioners understand the logic of this social norm and to use it to maximise their operation outputs, including sustainable SCM implementation.