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Delivery punctuality is essential in supply chain management, yet the cost of untimely delivery is usually assumed to be given or based on intuition and not quantified by facts.

The authors used a data set containing detailed transaction data for a nine-year period on orders and deliveries of sport goods. The methodology is based on applying a polynomial distributed lag model to longitudinal data on supply chain transactions.

The results indicate that small delivery delays up to two weeks decrease the sales by maximum 10% during a period of 3–4 weeks. Longer delays, up to 45 days, have a larger negative effect on sales, which can also last longer. For this case company, the estimated lost sales due to late deliveries (=5 days) were 5.1% of the delivery value. The longer delays got, the large the cost was: delays at least 45 days long were the most costly causing almost 40% of the estimated lost sales.

This study offers a methodology for quantifying lost sales due to delivery delays and estimating how long the poor delivery performance affects retailers' order behaviour.

The results give a quantitative decision-making tool for supply chain managers to estimate the profitability of investments in the supply chain performance, especially on improving punctuality.

The criticality of late deliveries in transportation lies in the threat of considerable multi-level supply chain costs. This study aims to reveal the dynamic capabilities playing a facilitating role in preventing delay, thus providing timely delivery, as well as developing an understanding of how and when those capabilities are activated within the supply chain network.

An exploratory study was conducted involving 16 semi-structured expert interviews with the representatives of logistics service providers and shippers. Following an interpretive phenomenology framework, the prevention phenomenon was explained.

Findings revealed two preventive capability categories in delay prevention: (1) proactive capabilities, referring to the enabling actions planned before departure, and (2) reactive capabilities, referring to actions planned after departure. Findings pinpoint that, in addition to the proactive capabilities, reactive capabilities enabled by innovative problem-solving actions are crucial for adapting to a dynamically changing environment in prevention. Moreover, this study shows that prevention capabilities are characterized by tangible and intangible resources and integration of resources with external links which constitute a delay prevention network within a wider service ecosystem.

This study stands out with its specific focus on delay prevention capabilities and enabling actions from the perspectives of logistics service providers and shippers. The premises of the resource-based view are combined with dynamic capabilities theory, leading to a proposed time-based taxonomy of proactive and reactive capabilities in supply chains, aimed at creating value and strengthening resilience.

Most collaborative SCM research has focused on the ideal situation of a manufacturer engaging with all its downstream partners. In view of extensive entry costs, lack of trust or simply non‐suitability of electronic data processing systems this, however, provides only limited support to actual problems of many companies. The paper seeks to investigate various common supply chain performance measures to show what impact increasing adoption of collaborative replenishment between manufacturer and several major customers has on each market participant.

The study uses discrete event simulation to evaluate various adjustments within the distribution frameworks of two food‐manufacturers and their major customers.

The analysis suggests that manufacturer and customers can substantially benefit from even a partial increase in demand visibility. This nevertheless can be costly since favouring some customers due to sharing a collaborative replenishment system, while others often seem to experience heavier delivery delays and declining service‐level.

The research focused on the delivery framework of the two involved manufacturers and the chosen products. Hence, research findings may differ and need to be modified before drawing conclusions for different products, companies or industries.

The analysis aims to help practitioners to identify possible opportunities and threats within an expanding collaborative SC replenishment system.

Investigating heterogeneous delivery frameworks within an emerging collaboration system has not been addressed much within prior SCM research. It aims to help mainly small‐ or medium‐sized enterprises to reveal possible advantages and drawbacks within the process of emerging with a varying number of customers from a traditional predetermined reorder‐point into a collaborative VMI/CPFR system.

This conceptual paper focuses on a common observation in the implementation stage of reward-based crowdfunding (RBC) – entrepreneurs' failures and delays in delivery of rewards to investors, which, in turn, may be perceived as violations of reward delivery obligations.

Drawing on entrepreneurial personality theory and psychological contract theory, this paper develops propositions and identifies factors related to both entrepreneurs (overconfidence and narcissism) and factors related to investors (types of motivators and psychological contracts) that may explain the perceived violations of reward delivery obligations. Implications for theory and practice are also discussed.

The theoretical analysis, by wielding two independently developed literatures, has demonstrated that it is important to investigate factors that are related to both investors and entrepreneurs in understanding issues and challenges at different stages of the RBC model. The authors believe that the current analysis provides an integrated understanding and a solid foundation for researchers to further examine these issues by empirically testing these propositions.

The authors examined two previously understudied psychological factors in the context of RBC – entrepreneurial traits, mainly overconfidence and narcissism, and the type of psychological contracts formed between investors and entrepreneurs, both of which, according to McKenny et al. (2017), need greater attention from researchers studying crowdfunding.

Peer‐to‐peer (P2P) streaming quickly emerges as an important application over the internet. A lot of systems have been implemented to support peer‐to‐peer media streaming. However, some problems still exist. These problems include non‐guaranteed communication efficiency, limited upload capacity and dynamics of suppliers which are all related to the overlay topology design. The purpose of this paper is to propose a novel overlay construction framework for peer‐to‐peer streaming.

To exploit the bandwidth resource of neighboring peers with low communication delay, application of the grouping method was proposed to construct a flexible two‐layered locality‐aware overlay network. In the proposed overlay, peers are clustered into locality groups according to the communication delays of peers. These locality groups are interconnected with each other to form the top layer of the overlay. In each locality group, peers form an overlay mesh for transmitting stream to other peers of the same group. These overlay meshes form the bottom layer of the overlay.

Through simulations, the performance was compared in terms of communication efficiency, source‐to‐end delivery efficiency and reliability of the delivery paths of the proposed solution currently. Simulation results show that the proposed method can achieve the construction of a scalable, efficient and stable peer‐to‐peer streaming environment.

The new contributions in this paper are a novel framework which includes the adaptability, maintenance and optimization schemes to adjust the size of overlay dynamically according to the dynamics of peers; and considering the importance of locality of peers in the system.

For parts of the time on a typical construction site concrete pour, the site placing crew is idle waiting for the arrival of the next truckmixer delivery, whereas for other periods, truckmixers are idle on site waiting to be unloaded. Ideally, the work of the crew should be continuous, with successive truckmixers arriving on site just as the preceding truckmixer has been emptied, to provide perfect matching between site and concrete plant resources. However, in reality, sample benchmark data, representing 118 concrete pours of 69 m³ average volume, illustrate that significant wastage occurs of both crew and truckmixer time. The purpose of this paper is to present and explain the characteristics of the wastage pattern observed and provide further understanding of the effects of the factors affecting the productivity of this everyday routine site concreting system.

Analytical algebraic models have been developed applicable to both serial and circulating truckmixer dispatch policies. The models connect crew idle time, truckmixer waiting time, truckmixer round trip time, truckmixer unloading time and truckmixer numbers. The truckmixer dispatch interval is another parameter included in the serial dispatch model. The models illustrate that perfect resource matching cannot be expected in general, such is the sensitivity of the system to the values applying to those parameters. The models are directly derived from theoretical truckmixer and crew placing time-based flow charts, which graphically depict crew and truckmixer idle times as affected by truckmixer emptying times and other relevant parameters.

The models successfully represent the magnitudes of the resource wastage seen in real life but fail to mirror the wastage distribution of crew and truckmixer time for the 118 pour benchmark. When augmented to include the simulation of stochastic activity durations, however, the models produce pour combinations of crew and truckmixer wastage that do mirror those of the benchmark.

The basic contribution of the paper consists of the proposed analytical models themselves, and their augmented versions, which describe the site and truckmixer resource wastage characteristics actually observed in practice. A further contribution is the step this makes towards understanding why such an everyday construction process is so apparently wasteful of resources.

Compared to the manufacturing industry, Lean Six Sigma (LSS) lacks a clear methodology for its application in the tertiary service. One reason is the difficulties to assess information flow compared to physical flow. Indeed, the use of information flow as a process entry in the LSS method is not well investigated, mainly due to the difficulties in collecting adequate and sufficient data. The purpose of this research study is to investigate the application of LSS in the tertiary service, in particular, real estate development.

The paper is based on an action research methodology where LSS methodology is applied to solve client-dissatisfaction issue. One of its main causes is found to be the late delivery time. The work describes how the method was applied.

LSS is an adequate approach for making well-thought-out improvement in real estate development.

The work provides an implementation of LSS in real estate development. It also gives new insights into the LSS application in the tertiary service. The work also suggests practical recommendations and solutions to address the main challenges faced by real estate development.

Construction is governed by many processes that are difficult to identify and, even more, to assess. LSS helps identifying those which create real value for the client.

The purpose of this paper is to study how variations in weather affect demand and supply chain performance in sport goods. The study includes several brands differing in supply chain structure, product variety and seasonality.

Longitudinal data on supply chain transactions and customer weather conditions are analysed. The underlying hypothesis is that changes in weather affect demand, which in turn impacts supply chain performance.

In general, an increase in temperature in winter and spring decreases order volumes in resorts, while for larger customers in urban locations order volumes increase. Further, an increase in volumes of non-seasonal products reduces delays in deliveries, but for seasonal products the effect is opposite. In all, weather affects demand, lower volumes do not generally improve supply chain performance, but larger volumes can make it worse. The analysis shows that the dependence structure between demand and delay is time varying and is affected by weather conditions.

The study concerns one country and leisure goods, which can limit its generalizability.

Well-managed supply chains should prepare for demand fluctuations caused by weather changes. Weekly weather forecasts could be used when planning operations for product families to improve supply chain performance.

The study focuses on supply chain vulnerability in normal weather conditions while most of the existing research studies major events or catastrophes. The results open new opportunities for supply chain managers to reduce weather dependence and improve profitability.

The Just‐In‐Time (JIT) philosophy holds tremendous potentials for improving the movement of precast concrete components from the prefabrication yard to, and within, the construction site. The space constraints for storage and the traffic congestion at the worksite can then be alleviated. Savings from the efficient management of precast concrete components can be used to offset the higher costs of procurement. By means of a survey, this paper examines if main contractors are ready to adopt the JIT philosophy to receiving and installing precast concrete components on site. Observations from the survey, however, suggest that JIT/lean operations need to work hand in hand with agile operations in the supply chain to cope with schedule fluctuations.

The service industry is a major component of the economy. Raw material, components, assemblies, and finished products are shipped between suppliers, manufacturers, distributors, and retailers. Accordingly, timely receipt of shipped goods is crucial in maintaining the efficiency and effectiveness of such service processes. A service provider offers an incentive to the customer by specifying a competitive target time for delivery of goods. Further, if the delivery time is deviant from the target value, the provider offers to reimburse the customer for an amount that is proportional to the value of the goods and the degree of deviation from the target value. The service provider may set the price to be charged as a function of product value. This price is in addition to the operational costs of logistics that are not considered in the formulated model. For protection against deviation from target due dates, the service provider agrees to reimburse the customer. The reimbursement could be based on an asymmetric loss function influenced by the degree of deviation from the target due date as well as product value. The penalties could be different for early and late deliveries since the customer may experience different impact and consequences accordingly. The chapter develops a model to determine the amount (price) that the provider should add to the cost estimate of the delivery contract for protection against delivery deviations. Such a cost estimate will include the operational costs (fixed and variable) of the shipment, to which an amount is added to cover the expected payout to customers when the delivery time deviates from the target value. The optimal price should be such that the expected revenue will at least exceed the expected payout.