This paper introduces a research exploring the important strategic elements and their prioritisation for e-retailers' home delivery supply's efficacy improvement. The research was completed through literature review, focus group, survey and importanceperformance analysis (IPA). It identified, confirmed and prioritised a set of explicitly important strategic elements currently deemed important by e-retailers for ensuring the efficacy of their home delivery logistics processes in Chinese marketplace. The findings contribute to the enrichment of the theoretical knowledge pool of e-retailers' logistics performance improvement, and guide/inform the strategy development and implementation for e-retailers entering and/or operating in Chinese and other similar emerging marketplaces.
With supply chains becoming increasingly extended, the uncertainties in the upstream production process can greatly affect the material flows that aim toward meeting the uncertain demands at the downstream. We analyze a two‐location system in which the upstream production facility experiences random capacities and the downstream store faces random demands. Different from the widely used approach that seeks the decomposition of the profit function based on the echelon inventories, our approach builds on the notions of stochastic functions, in particular, the stochastic linearity in midpoint and the directionally concave order. With these notions, we establish the concavity and submodularity of the profit functions in the transformed decision variables. In general, it is optimal to follow a two‐level state‐dependent threshold policy such that an order is issued at a location if and only if the inventory position of that location is below the corresponding threshold. In the special case where the salvage values are linear in the ending inventories, the profit function becomes separable in the inventory positions, and the optimal policy reduces to the echelon base‐stock policy. The effect of the uncertain capacity and demand depends critically on whether the production capacity is limited or ample in relation to the demand. Only when the capacity and the demand do not differ much, the upstream facility carries positive inventory; otherwise, all units produced are shipped immediately toward the downstream. We further extend our analysis to systems with general stochastic production functions and with multiple locations.
As a fundamental element of knowledge management (KM), knowledge identification is a crucial issue in contemporary business organisations. As evidenced by research, medium sized enterprises (MEs) contribute constructively and significantly to economic development, society stabilisation and employment increase. Their healthy survival and growth are of critical importance to a nation. Among the approaches ensuring the successful development of MEs, quality improvement (QI) is a crucial one. However, what is and how to identify the knowledge most relevant to the MEs' QI, the drives and sources for identifying the QI knowledge (QIK) as well as the underpinning rationales, are currently lacking of sufficient exploration. A research focusing on these issues has been strongly emphasised by literature and attested by this research itself of its meaningfulness. Through analysing empirical data collected and attested by a combination of firstly semi-structured interview, focus group following a case study strategy and then a structured interview, this exploratory research has obtained and prioritised the up-to-date answers to these questions, leading to the enrichment of the theoretical understanding of KM approaches in operations with a consideration of quality management. Real world MEs can rely on these findings as a guidance to obtain, select and apply appropriate QIK for their operations performance improvement. The findings can also be referential for knowledge identification and application in view of QI in other type business organisations.
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