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Fast fulfilment is a key performance measure in online retail, and some retailers have achieved faster times by adopting new designs in their order fulfilment infrastructure. This research empirically confirms and quantifies the fulfilment time advantage that Amazon has achieved, relative to other online retailers. The purpose of this paper is to investigate three research questions: what is the overall mean fulfilment time difference between the new logistics designs of Amazon and the alternative designs of other retailers? For each order what is the distribution of the fulfilment time difference? What is the difference in fulfilment time by product category, price and size?

This research uses an empirical method to evaluate the fulfilment time performance of consumer orders made through the Amazon website and one or more competing online retailers. For 1,000 different products two fulfilment times, one at Amazon and another at a competing omnichannel retailer, are recorded. The analysis is then focused on the comparison between this paired data.

The research confirms that the new logistics methods, including physical facilities, distribution networks and intelligent order processing methods, have resulted in faster order fulfilment times. The performance, though, is not universally dominant and for 33 per cent of orders, the difference is 1 day or less. The fulfilment time difference varied by product, category, price or size.

The ongoing transformation of fulfilment and logistics operations at online retailers has generated several new research questions. This includes the need to confirm the fulfilment efficiency of the new designs and specify time targets. This paper identifies the fulfilment time gap between new and traditional operations. The results suggest that store-based or distribution centre-based fulfilment strategies may not match the new designs.

The study provides a quantitative analysis of the fulfilment time differentials in online retailing. The critical role of fulfilment logistics in the rapidly growing online retail industry can now be better modelled and studied. The survey method representing a single buyer allows for order pair equivalency and eliminates order bias. The results suggest that new warehousing and logistics designs can lead to significantly faster fulfilment times.

This paper discusses evidence from field studies undertaken to investigate the responsiveness of the order fulfilment process in a number of companies. The evidence is analysed in the context of the literature on responsiveness and related areas such as time‐based competition. Similarities and differences are analysed across a number of industrial sectors with respect to order fulfilment processes and the interpretation and significance of responsiveness. Generic factors that influence different types of companies are identified. Four components of responsiveness – stimuli, awareness, capabilities and goals – emerge from an analysis of the literature. The field and case study evidence allows the development of more precise definitions and descriptions of each of these components. The study also allows a generic responsiveness framework to be developed that incorporates both strategic and operational viewpoints. The need for more field studies on responsiveness is noted. More work is advocated on the assessment and measurement of responsiveness and on developing appropriate responsiveness interventions, particularly with respect to the order fulfilment process.

Demand forecast methodologies have been studied extensively to improve operations in e-commerce. However, every forecast inevitably contains errors, and this may result in a disproportionate impact on operations, particularly in the dynamic nature of fulfilling orders in e-commerce. This paper aims to quantify the impact that forecast error in order demand has on order picking, the most costly and complex operations in e-order fulfilment, in order to enhance the application of the demand forecast in an e-fulfilment centre.

The paper presents a Gaussian regression based mathematical method that translates the error of forecast accuracy in order demand to the performance fluctuations in e-order fulfilment. In addition, the impact under distinct order picking methodologies, namely order batching and wave picking. As described.

A structured model is developed to evaluate the impact of demand forecast error in order picking performance. The findings in terms of global results and local distribution have important implications for organizational decision-making in both long-term strategic planning and short-term daily workforce planning.

Earlier research examined demand forecasting methodologies in warehouse operations. And order picking and examining the impact of error in demand forecasting on order picking operations has been identified as a research gap. This paper contributes to closing this research gap by presenting a mathematical model that quantifies impact of demand forecast error into fluctuations in order picking performance.

This article aims to quantify and analyse empirically how the geographic dispersion of a firm's supply chain impacts on intra‐firm supply chain performance.

Generalised linear modelling is utilised to analyse a sample of 95 large manufacturing companies operating in Finland.

Results indicate that the increased geographic dispersion of the upstream supply chain results in higher costs of warehousing and logistics administration. On the downstream side, inventory costs, inventory days of supply, and cash‐to‐cash cycle time tend to increase due to geographically dispersed sales network. Increased geographic dispersion in the upstream and downstream supply chain results in the decline of perfect orders, and increases order fulfilment cycle time. However, the increased dispersion of the production network reduces order fulfilment cycle time. The results also indicate that the larger the firm, the better it can alleviate the negative implications of dispersion on perfect order fulfilment. Make‐to‐stock companies suffer less from the supply chain dispersion related delays in comparison to companies that utilise more pull‐type production and inventory strategies.

Research limitations include the cross‐sectional nature of the data, the concentrated geographic origin of the respondents, and the small sample size.

Building on the multidisciplinary body of prior literature on geographic dispersion, the research provides quantified insights into the general principles of international supply chain design in the presence of a performance related trade‐off between the dispersion and centralisation of operations across the tiers of the supply chain. Contributions are made to the discussions on supply chain complexity, international sales portfolio diversification and international purchasing.

A deeper understanding of what needs to be considered to improve the targeted incorporation of employees’ knowledge into continuous improvement (CI) programmes in industrialised housebuilding (IHB) is required. This paper aims to address the current lack of involvement and connect it to structural and corporate culture factors. To avoid misjudgements in improvement activities as well as to use the full potential of performance improvement ideas, CI tools and measures need to be adapted to facilitate this integration. Relevant factors are analysed and their influences on CI measures are assessed.

The research approach is built upon an explorative case study supported by a comprehensive literature review. Empirical data were collected through participant observation, guided interviews and company documents.

The influences on employee involvement within CI programmes and the corresponding suitability of important CI measures were evaluated on a set of relevant factors. These factors include unique building projects, project-based focus on order fulfilment, fragmented order fulfilment process, separation of order fulfilment activities in terms of space and time, procedural rules for dealing with on-site failures, short-term contracts with subcontractors and the practice of evaluating and monitoring performance on site.

The research paves the way for the development of suitable tools, measures and methods to effectively involve employees from all profession within a CI programme in IHB. The empirical part of this research is based on a single case study.

This work extends the body of knowledge of CI application in the construction industry with an analysis of factors influencing its implementation and management.

The paper aims to clarify the effects of brand differentiation on the platform's formulation of channel strategy and help the online platform formulate the optimal channel strategy, which involves selecting a proper selling mode for each brand.

The paper develops a multistage game model consisting of one online platform and two competing manufacturers with differentiated brands and examines the effects of brand differentiation on these three channel members' profits under each candidate channel strategy.

The results show that the platform prefers to offer the reselling mode for both brands when the brand differentiation is low, and this preference will be enhanced by the decrease in order fulfilment cost. By contrast, when the brand differentiation is high, it will offer the reselling mode for the premium brand but the marketplace service for the economy brand if the order fulfilment cost is not high; or the marketplace mode will be offered to both brands if this cost is high.

This study assumes that the order fulfilment costs of platform and manufacturer are fixed and symmetric. Therefore, researchers are encouraged to consider asymmetric costs of order fulfilment.

The paper guides the online platform to formulate the optimal channel strategy for differentiated brands and provides managerial insights for differentiated brands entering online markets.

This paper explores platforms' optimal channel strategy by jointly considering the effects of brand differentiation and investigates the impacts of brand differentiation on the optimal decision making under four candidate options. Moreover, this paper has been extended to examine the case when the manufacturers' production costs cannot be neglected.

The purpose of this paper is to develop a scale for measuring information quality in the order fulfilment process.

Measurement scales are developed out of the practical information needs and a theory review. A state‐of‐the‐art description and further scale development are based on a survey of the most important suppliers of 136 Swedish companies.

The paper finds that information quality can be measured with variables as in time, accurate, convenient to access and reliable. The scales were found to possess unidimensionality, validity and reliability.

The implications of this paper are mainly theoretical, providing a foundation for further empirical research.

Even though established customer‐supplier relations were studied, information quality deficiencies were found on all variables. This is an indication of improvement possibilities.

There is a lack of research on measuring the information quality construct, which might be the reason for little empirical research on the impact of information quality on logistics performance.

When approaching a stock‐out situation, a company should be able to actively manage the allocation of available products on the basis of customer requirements and priorities as well as contractual relationships. The purpose of this paper is to describe different order promising mechanisms and analyze how well they can contribute to the effective management of stock‐out situations.

The paper provides a formal description and analysis of alternative order promising mechanism applicable in make to stock systems. Numerical analysis is conducted based on the data of a pharmaceutical company.

The paper clearly points out the potential of alternative order promising mechanisms to alleviate the negative consequences associated with a temporary stock‐out situation.

The paper does not consider implications of inventory pre‐allocation to customer classes. Further research should address the interplay between pre‐allocation and different order allocation mechanisms.

The results obtained from this analysis provide guidelines for manufacturers, retailers, and vendors of supply chain software on how to design and utilize order promising systems.

The paper provides a consistent formal approach to modelling order promising mechanisms, introduce new and innovative order promising mechanisms and provide valuable insight into their performance through numerical analysis.

The purpose is to explore how the configurations resulting from the interplay of last mile logistics practices and firm characteristics are associated with firm performance in an omni-channel context.

Drawing on configuration theory (CT), the authors use fuzzy-set qualitative comparative analysis (fsQCA) to analyze data on 72 Swedish omni-channel retailers.

Four configurations are identified—store-oriented small and medium-sized enterprises (SME's), online-oriented SME's, large store-oriented retailers and large online-oriented retailers. The results show that while offering a wide range of delivery options is necessary to achieve high performance, it is not sufficient, and that returns and fulfilment should be simultaneously considered. For instance, large high-performers leverage their stores and warehouses for fulfilment and returns in an integrated way irrespective of sales channel-mix. However, SME's appear to focus on fulfilment simplicity with less-costly delivery alternatives, where store-oriented SME's leverage stores and the online-oriented counterparts leverage warehouses. Consequently, the authors develop a configurational taxonomy and discuss a set of recipes which provide insights for researchers and practitioners.

The study provides a more comprehensive understanding of the pathways to success, and potential pitfalls, in the last mile logistics context.

This study applies a novel methodology in the field, namely fsQCA, to explore the paths to competitive advantage. It covers a wide range of stages in the LM including back-end fulfilment, delivery and returns. It also provides insight into the logistics practices of both SME's and large omni-channel retailers.

The purpose of this paper is to empirically test the validity of a two‐factor theory for seller service quality in the online auction context.

A sample of 2,000 buyer feedbacks about seller performance (1,000 positive and 1,000 negative) was collected from eBay. Content analysis of positive and negative feedback was conducted and the frequencies of mention of specific service quality attributes were compared.

Analysis of total mentions and exclusive mentions of service quality attributes showed significantly different content for positive and negative feedback, supporting the validity of two‐factor theory in this context and adding to the understanding of customer expectations in this environment.

The paper's findings can guide sellers' allocation of efforts in service design, so they can establish and maintain the reputation necessary to attract bidders and successfully compete in high‐risk online environments like eBay.

The paper extends the understanding of quality determinants in a service environment substantially different to traditional environments because of the risks to which buyers are exposed, information asymmetry, and the lack of previous experience with buyers. In addition, the finding of support for two‐factor theory is in a direct contrast with the conventional, one‐factor model subscribed by most quality researchers in the operations management field, and highlights the importance of investigating customer satisfaction and dissatisfaction separately in the online auction environment.