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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 study aims to examine reciprocal exchange in teams using a psychological contract (PC) framework. Adopting Rousseau’s conceptualization of the contract, the authors explore the extent to which the team members reciprocate perceived team obligations and fulfilment by adjusting their own obligations and fulfilment. A new scale for the measurement of obligations and fulfilment was developed. Team commitment was hypothesized as a mediating variable.

The new PC scale was tested in a longitudinal study design. A survey of a representative sample of 230 Dutch first-year college students nested in 73 teams was conducted.

The authors found that in student teams, perceived team obligations at Time 1 are positively associated with perceived member obligations at Time 2. Furthermore, they found higher commitment to the team as the team fulfilled the obligations as perceived by its members. Contrary to the exchange theory, in student teams, perceived fulfilment of obligations at Time 1 is not reciprocated by more obligations of its members at Time 2. No significant mediating effects are found of team commitment.

To date, this study provides the first measurement of contract fulfilment in non-hierarchical team relationships. The instrument can act as a tool to assess future team effectiveness and performance and adjust team composition accordingly.

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.

Optimization of resources related to man, money, manpower and those related to organization is critical in context of after-sales supply chains. Many times, organizational objectives in terms of resource optimization and providing superior customer experience might be conflicting, however.

One such instance is when customers expect near 100% service level in which case the organizational costs to meet such high service level goes up significantly. To this end, in this research a novel bi-objective optimization model has been evolved for a typical after-sales service supply chain network constituted of the manufacturer, the retailer and the customer. The first objective function pertains to maximization of the manufacturer's and the retailer's profit. The second objective function is related to the minimization of tardiness of order fulfilment (by the retailer) for the customer.

Employing a small problem instance, the authors generate a number of findings related to service level and information asymmetry. In particular, the authors observe that achieving best possible manufacturer-retailer profit and at the same time 100% service level is a mathematical impossibility. Furthermore, reducing information asymmetry between the customer and the retailer (as opposed to reducing information asymmetry between the retailer and the manufacturer) actually yields higher profits for the manufacturer-retailer pair.

This research describes the mathematical structure of a three-tier after-sales supply chain wherein information quality and service level requirements are key constraints. Furthermore, the study evolves the bi-objective optimization model as a formulation that can drive the operational decisions of manufacturers and retailers who are part of such after-sales service supply chains.

Grocery sellers that have entered the online business must now carry out order fulfilment activities previously done by the customer. Consequently, in a context of online sales growth, the purpose of this study is to identify and implement best practices in order to redesign the order picking process in a retailer with a store-based model.

To identify different work alternatives, an approach is developed to analyse the methods used in distinct stores of one large Spanish grocer. The methodology employed is a three-step statistical analysis that combines ANOVA and MANOVA techniques to settle on the best alternatives in each case.

Substantial improvements can be achieved by analysing the different working methods. The three-step statistical analysis identified best practices in terms of their impact on preparation time, allowing a faster working method.

To manage business processes efficiently, online grocers that operate store-based fulfilment strategies can redesign their working method using a criterion based on their own performance.

This is one of the few contributions focusing on the improvement of e-grocery fulfilment operations by disseminating best practices through decision-making criteria. This study contributes by addressing the lack of approaches studying the order picking process by considering its various features and applying best practices.

The purpose of this paper is to derive monetary benchmarks and managerial implications for omni-channel retailers’ B2C e-fulfillment strategies by investigating the trade-offs between lead time, delivery convenience and total price including shipment in the context of online electronics retailing.

Based on a choice-based conjoint analysis among 550 US online shoppers, the monetary values of lead time and convenience were calculated in a log-log regression model. In addition, latent class segmentation was applied to identify consumer segments according to their differing e-fulfillment preferences.

From a consumer perspective, the analysis suggests that price is the most important criteria in omni-channel retailer selection, followed by lead time and convenience. The value of time is, on average, $3.61 per day. Regarding convenience, the results indicate that delivery to the home is highly preferred over pick-up options. The value of the consumer’s travel time was estimated at $10.62 per hour. The latent class segmentation identified four segment groups with different preferences.

To validate the findings, future research could analyze real data from omni-channel retailers’ customers’ buying behavior. It should also be interesting to extend the research to other price ranges, market segments and e-fulfillment factors, such as return options, shop ratings and membership programs aiming for further generalization.

The findings guide omni-channel retailers to focus on efficient B2C e-fulfillment strategies. Considerable competitive advantages may be gained by reducing lead times and offering convenient delivery in line with the lead time valuation of the identified customer segment.

This study fills gaps in the academic research of consumer behavior in retailer selection, which has primarily concentrated on the choice between “brick-and-mortar” and online sales channels. It paves the way for a more service-oriented perspective in omni-channel retailing research.

This paper aims to explore methods of defining ejecting zones (EZs) used in automatic picking systems (APSs), particularly in A-frame APSs. An A-frame APS automatically ejects products onto a conveyor, which then brings the products to their destination. EZs are moving zones on a conveyor, and each EZ corresponds to one picking order. Products are ejected as a zone passes channels in which the products are stored.

First, three EZ types are defined, and their operations are explained. Second, picking orders are analyzed and categorized by considering the structure and the picking mechanism of an A-frame APS. In addition, picking-order instances reflecting actual data are randomly generated according to each category. Finally, the performance of the EZs is evaluated using the picking-order instances and computer simulations.

The results from the computer simulations suggest the EZ types suitable for use with various picking order types considering order fulfilment speed and energy usage.

In this paper, the authors only adopt a triangular distribution which is considered most practical distribution in the industry.

It is believed that these results can provide managers and operators with useful guides to facilitate the effective operation of an A-frame APS. The provided ideas have been implemented at the pharmaceutical warehouse of the largest logistics company in Korea.

The result shows that the proposed idea could save energy consumption and the APS have potential to save labor involvement in picking.

It is essential to define the EZs when operating an A-frame APS efficiently, but there is almost no research in this area. This paper focuses on defining EZs, as well as methods to utilize these zones.

Managing the production and operations of a contemporary electronics manufacturing is challenging. Companies need to be proactive for uncertainties of the market in a productive way. This paper analyses the electronics manufacturing context and proposes the data system implementations based on context requirements. The general trends in electronics manufacturing are time‐based competition, increasing product variety and new technologies. Cost structure changes are driving productivity. Price erosion is forcing flexible operations and fast inventory turn rates. The uncertainties in electronics manufacturing that need especial management are: volume – the change in demand and its effect on lead‐time of order‐fulfilment; product mix – managing product variety and lot sizing issues and product life cycles – changing products and production technologies. Managing and measuring these dimensions require wide implementation of ERP packages. In some cases, more advance planning tools such as product configurators and advanced planning systems are required.

The purpose of this paper is threefold: first, review the literature on the topic of behavioural antecedents of collaboration and their impact on supply chain integration and performance; second, lay the theoretical foundations and develop a conceptual model linking behavioural antecedents of collaboration, information integration, coordination of operational decisions and supply chain performance; and third, set out operationalisation considerations.

A conceptual model with theoretical basis on Relational Exchange Theory (RET) and extant supply chain theory is developed as a causal model that can be operationalised using structural equations modelling (partial least squares) and a “single key informant” approach.

Positive relationships between behavioural antecedents of collaboration (trust, commitment, mutuality/reciprocity), information integration, coordination of operational decisions and supply chain performance (efficiency, effectiveness) are hypothesised. RET provides adequate theoretical background that leads to the theoretical establishment of hypotheses between behavioural antecedents, supply chain integration and performance, which are worth testing empirically.

The ideas presented in this paper enrich the study of behavioural factors in supply chain management and their impact on supply chain performance, and may benefit researchers in the field. The paper also sets the scene (experimental design, measurement items) for the upcoming field research. The empirical part of the work will provide the necessary evidence for the validation of the established hypotheses.

The proposed linkages may stimulate the interest of supply chain strategists towards more collaborative relationship management and affect their decisions on the behavioural antecedents of relationship formation and management. Moreover, the proposed model may help clarify how the integration of critical operational contingencies – information, operational decisions – can help achieve superior supply chain performance.

The paper establishes a causal relationship between constructs which have not been researched (mutuality/reciprocity, coordination of operational decisions) or have been researched individually or in combination (impact of integration on performance, impact of collaboration on performance) but not in the proposed integrated way. It also addresses the challenge of lack of theoretical justification on the development of knowledge that will assist decision making in SCM/logistics and its integration into models, processes and tasks. Finally, by using RET in selecting of behavioural factors and establishing hypotheses, it adds to the body of knowledge concerning the use of interorganisational theories in supply chain relationships.

The main purpose of this paper is to investigate the current manufacturing strategies and practices of bus manufacturers in China, and to propose a framework of manufacturing strategies for time‐based competitive advantages.

The conceptual research framework is devised from a review of the literature, and case studies are used to investigate the manufacturing strategies and practices in place in the case companies. Data are collected through semi‐structured interviews and secondary documentation.

The results show that, with over‐capacity in the Chinese bus manufacturing industry, success is no longer determined by high productivity or low price; a quick response to the customers' tailored demands is essential in a climate of fierce competition. The suggested best practices for time‐based competitive advantages comprise building technical centers and post‐doctoral research stations, applying modularity logic, adopting radio frequency identification (RFID), and optimizing processes by, for example, involving customers and integrating inbound and outbound logistics.

The research results are limited within the context of the bus manufacturing industry in China.

The research results help both the practitioners and the researchers gain a better understanding of the practices of Chinese bus manufacturers from the perspective of time‐based competitive advantage. The proposed strategies and best practices have the potential to improve the manufacturing performance of this type of manufacturer.

This paper shows the big picture of manufacturing strategy and practice of bus manufacturers in the Chinese automobile industry. Furthermore, it presents a manufacturing strategy framework with best practice guidance to gain a time‐based competitive advantage.