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This note empirically validates forecasting management competence (FMC) as a higher-order construct based on four underlying sets of practices: internal integration, forecasting process quality, effective use of advanced systems, and evaluation of forecasting. The results from a partial least squares structural equation model support FMC as a significant driver for three outcomes: forecast accuracy, cost reduction, and delivery performance, thereby establishing predictive validity. The study provides insights to the relative effectiveness of the four sets of forecasting practices constituting FMC. A mediator-moderator analysis shows that forecast accuracy is not a mediator or a moderator between FMC and the other two outcome variables of cost reduction and delivery performance. This indicates that in addition to effective demand forecasting practices, other processes such as sales and operations planning (S&OP) are also important for translating the benefits of effective forecasting to realize favorable business outcomes. A multigroup analysis shows that the impact of the four practice elements on the three performance outcomes also differs based on specific business contexts.

Mobile Opportunistic Networks (MONs) use the store-carry-and-forward scheme to transmit packets, so as to deal with the intermittently connected links. This new communication paradigm makes them very different from the traditional multi-hop wireless networks. To improve the delivery performance, some smart forwarding schemes have been proposed by injecting multiple copies of packets into the temporal network. Unfortunately, these schemes allocate data copies following the aggregate contact information, i.e., information obtained by considering the samples from all pairs. They ignore the individual contact feature of nodes. We show that the aggregate contact can be very different from the contact of individual pairs, therefore, using the former to guide copy allocation is not correct in general, although it works well in some cases. In this paper, we propose OPPO, an optimal copy allocation scheme in MONs. OPPO exploits the transient contact ratio of nodes to spray data copies. Theoretical analysis proves that OPPO achieves the optimal delivery delay, and experimental results verify it simultaneously improves the packet delivery ratio compared to the SprayWait and HS, two state-of-the-art works.

We compare the predictive validity of single-item and multiple-item measures utilized in Just-in-Time (JIT) research. The study examines if single-item measures could be used for some of the JIT practices, especially if the object of inquiry is concrete singular and if the attribute to be researched is concrete. Arguments are developed for the concrete nature of the JIT practice of “set-up time reduction” and we examine the ability of a single-item measure of this variable to predict the criterion variable (delivery performance). In addition, the study also examines the efficacy of using multiple-item measures for variables that are abstract in nature, and thereby attempts to develop a continuum of JIT constructs ranging from concrete to abstract. The results obtained by analyzing two sets of survey data show that multiple-item measures are not necessarily more valid than single-item measures for all constructs. The findings provide evidence that multiple-item measures and single-item measures for scale development should be contingent upon the nature of constructs. For concrete constructs, single-item measures are as valid as multi-item measures. Meanwhile, for abstract constructs it is important to ensure that multiple items are considered to capture the multi-dimensional nature of these constructs. Results also reveal that JIT practices display significant differences in terms of abstract/concrete perceptions. The paper presents theoretical and practical implications of the findings, and offers directions for future research.

This research mainly focuses on the evaluation of the sustainability of maritime containers. To examine the relationship between maritime container and packaging, this study compares containers and general packaging in terms of delivery performance, operation risk, cost structure, and operations improvement. This analysis is also applicable to the containers' supply chain to examine the effect that packaging has on performance, such as the compatibility of packaging, goods, environment, and operations. The analysis allows the development of an evaluation framework for sustainable container management. In addition, this study provides a case study on rice business in the UK applying that evaluation framework.

Current sourcing paradigms are described by greater complexity in managing suppliers' performance in purchasing cycle execution, product quality and logistics competence. When we combine the stages of the order fulfillment cycle with the buyer's information sharing factors, a more complete view of the buyer-supplier exchange becomes useful for performance evaluation of both the suppliers and the buyers. Using operational data obtained from a large telecommunications firm, which placed strategic importance on measuring the performance in the purchase order fulfillment cycle stages, this study offers a new context for supplier evaluation. This context also conceptualizes several on-time delivery disruption scenarios as supplier delivery performance risk, and investigates the sensitivity of both the buyer's information sharing and the suppliers’ performance capabilities to on-time delivery disruptions. We evaluate supplier performance and segment suppliers through recourse to chance-constrained data envelopment analysis at high and low discriminatory power levels. Our results show that there are statistically significant relationships between the dimensions of information sharing by the buying firm and the classification of supplier firms at varying levels of on-time delivery performance risk. We also identify robust suppliers demonstrating the capability to remain efficient across disruption levels despite poor buyer performance on information sharing factors, and provide managerial insights on buyer-supplier exchange.

Evaluating suppliers and supporting their continuous improvement have become critical for supply chain (SC) performance management. Since the performance of an organization in a SC depends on the performance of its suppliers, it is desirable that the evaluation of a supplier can be integrated to the evaluation of the SC. Few studies propose decision making models to aid the supplier evaluation for development. However, these studies adopt criteria similar to ones used in supplier selection, which can lead to a mismatch between supplier and SC performance evaluations. Therefore, to overcome this lack of alignment, this article presents a new approach that uses the performance metrics of the SCOR® (Supply Chain Operations Reference) model to evaluate the suppliers in the dimensions cost and delivery performance. It combines two fuzzy TOPSIS models for evaluating and categorizing the suppliers in four groups depending on their performance evaluation. According to their categorization, directives for action plans are proposed. An illustrative application was developed based on a manufacturing context. The combination between the SCOR® and fuzzy TOPSIS brings several benefits when compared with other approaches, such as: it facilitates the integration of the processes of performance evaluation of the suppliers and the SC; it enables benchmarking against other SCs; the fuzzy TOPSIS requires few judgments to parameterization, which contributes to the agility of the decision process; it does not limit the number of alternatives simultaneously evaluated; it does not cause the ranking reversal problem when a new supplier is included in the evaluation process.

This paper describes a project that used the co-creation of value model to collect and analyse data on storm drains for a city so that it could become smarter in managing the water drainage issues. The city worked with a University centre and ensured that the prerequisite conditions — mutual value-creation potential, commitment and trust, and demonstrated delivery performance — were met. The project was able to integrate science and technology through Information Systems, analyse, optimize, control, and monitor the conditions of the 27,000 storm drains in the city, and enhance the decision making process of the city. This case study provides an example of how a city and a university centre can co-create value thereby helping the city's management become “smarter” in managing its storm drains and the students obtain a rich field-based educational experience.

Purpose – The purpose of this paper is to develop a conceptual framework of integrated supply chain model that can be used to measure, evaluate and monitor operational performance under dynamic and uncertain conditions. Design/methodology/approach – The research methodology consists of two stages: configuration of a conceptual framework of integrated supply chain model linked with performance measures and illustration of the integrated supply chain model and delivery performance using a case of dairy industry. The integrated supply chain model is based on a unitary structuring technique and forms the basis for measuring and evaluating supply chain performance. Delivery performance with variation of demand (forecast and actual) is monitored using a fuzzy-based decision support system, based on three inputs: capacity utilization (influenced by production disruption), raw materials shortage and quality of dairy products. Findings – Integration of supply chain components (materials, resources, operations, activities, suppliers, etc.) of key processes using unitary structuring approach enables information integration in real time for performance evaluation and monitoring in complex supply chain situations. In addition, real-time performance monitoring is recognized as being of great importance for supply chain management in responding to uncertainties inherent in the operational environment. Research limitations/implications – Implementation of an integrated model requires maintenance of supply chain components with all necessary data and information in a system environment such as enterprise resource planning. Practical implications – The integrated model provides decision-makers with an overall view of supply chain components and direct links that need to be maintained for supply chain performance evaluation and monitoring. Wider adaptation and diffusion of the proposed model require further validation of the model and feasibility of implementation, using real-time data and information on selected performance measures. Originality/value – Integration of supply chain components across supply chain processes directly linked with performance measures is a novel approach for effective supply chain performance evaluation and monitoring in complex supply chains under dynamic and uncertain conditions.

The study was initiated to explore the difficulties that frequently appear to plague the relationship between the NHS and the Voluntary Sector as regards mental health service delivery. It was found that the performance of the mental healthcare delivery system is subject to a number of criticisms. The latter could be attributed to low levels of collaboration and communication between social actors involved. Based on interviews, focus group discussions and results from the literature a number of possible ways to improve the system were identified. The results of the study are expected to contribute to the improved designed of health care systems and of performance management concerning the mental health services. Various attempts to improve performance in the past were explored and criticised. One important obstacle to success was identified as a lack of understanding in the NHS and in the Voluntary Sector - of the implications of the use of externally generated performance criteria versus the use of internally generated self-organised criteria. A conceptual model was developed to help clarify these notions as management tool. It includes the idea of a spiral development and of ‘complete collective satisfaction'.

Purpose – The purpose of this paper is to explore and explain the circumstances in which a highly collaborative integrated project delivery form such an alliance is the most appropriate choice of delivering infrastructure projects. Design/methodology/approach – The paper draws upon two previously published studies on alliancing to enable gathering insights from a quantitative study with some qualitative data that indicates project alliance delivery performance is high and suggests why it may be adopted as a project delivery form. A second qualitative study recently completed and published on integrated collaborative forms of project delivery such as alliances is re-analysed to better understand how and why this form may be successful. Together these two studies allowed a focus on the motivation to form an alliance and specific conditions relating to the alliance party’s level of ability and willingness to deeply collaborate. Findings – The motivation to deeply collaborate may be triggered by specific internal and external trigger mechanisms. These are identified in the paper together with discussion about the requirement of parties to have sufficient knowledge, skills, attributes and experience to collaborate at a deeply engaged level. Research limitations/implications – The data used in the studies were from large scale infrastructure construction projects. The examples are mainly drawn from countries where collaboration is common and culturally acceptable; results may not apply to cultures, country or workplace, where high levels of competition are seen to be the optimal strategy for project delivery success. Also, the data were drawn from construction project management (PM). Other project-based areas such as professional services for example may present a different context and hence a different rationale. Practical implications – The study provides deep insights about the nature of collaboration. It may have wider applicability. Social implications – Project organising is a social activity with social implications for how they are delivered that affect internal as well as external stakeholders. Being mindful about the motivation to choose a particular delivery form is important. Originality/value – This is a new area of research in PM and the world faces a massive demand for large scale complex projects. This paper may provide a rational to drive policy in project delivery choices.

Nanomedicine has been growing exponentially due to its enhanced drug targeting and reduced drug toxicity. It uses the interactions where nanotechnological components and biological systems communicate with each other to facilitate the delivery performance. At this scale, the physiochemical properties of delivery systems strongly affect their capacities. Among current delivery systems, DNA nanotechnology shows many advantages because of its unprecedented engineering abilities. Through molecular recognition, DNA nanotechnology can be used to construct a variety of nanostructures with precisely controllable size, shape, and surface chemistry, which can be appreciated in the delivery process. In this review, different approaches that are currently used for the construction of DNA nanostructures are reported. Further, the utilization of these DNA nanostructures with the well-defined parameters for the precise control in drug delivery and gene therapy is discussed.

The order assignment in the food delivery industry is of high complexity due to the uneven distribution of order requirements and the large-scale optimization of workforce resources. The delivery performance of employees varies in different conditions, which further exacerbates the difficulty of order assignment optimization. In this research, a non-linear multi-objective optimization model is proposed with human factor considerations in terms of both deteriorating effect and learning effect, in order to acquire the optimal solutions in practice. The objectives comprised the minimization of the operational cost in multiple periods and the workload balancing among multiple employees. The proposed model is further transformed to a standardized mixed-integer linear model by the exploitation of linearization procedures and normalization operations. Numerical experiments show that the proposed model can be easily solved using commercial optimization softwares. The results indicate that the variance of employee performance can affect the entire delivery performance, and significant improvement of workload balancing can be achieved at the price of slight increase of the operational cost. The proposed model can facilitate the decision-making process of order assignment and workforce scheduling in the food delivery industry. Moreover, it can provide managerial insights for other labor-intensive service-oriented industries.

This paper empirically studies the matching and delivery process in a major crowd-sourced delivery platform. The aim is to develop models to understand and predict crowd-shipping delivery performance and using the findings to design incentives to improve user experiences as well as system performance. We apply the random forest machine learning algorithm to predict the shipment status of 14,858 crowd-shipping requests recorded between January 2015 and December 2016 throughout the U.S. The models are used to predict three phases of the crowd-shipping performance, namely bidding, acceptance, and delivery, using shipping request, built-environment, and socioeconomic features as explanatory variables. The results demonstrate that the context of the shipment provides strong predictive performance even when shipping request and package information is unknown. Calculating the sensitivity of bid probability, we show that offering a higher reward and posting a shipping request in the morning has the largest effect on the probability to secure a bid. We also find that larger shipments, out-of-state destinations, and peer-to-peer shipments lead to higher sensitivity, likely reflecting the higher perceived risks of such transactions. In practice, the models presented in this study show promise in their ability to effectively predict shipment status in real time. We illustrate a valuable application of the sensitivity analysis derived from the random forest models to develop customer-tailored crowd-shipping smartphone applications. Based on the data mined from past deliveries, customers are given empirically based delivery forecasts for their specific package request and can modify delivery requests to increase their odds of delivery. We find that pricing is the variable with the highest potential to increase delivery probability followed by the timing of the request.

Delivery performance is one of the indications of enterprise’s success to provide products to customers. In this research, simulation is done to measure the delivery performance and all the processes included in delivery process. In fact, every process has their own risks could delay delivery process that the delivery performance is reduced. The methods used to identify the risks and the causes are Failure Mode and Effects Analysis (FMEA) and Fault Tree Analysis (FTA). Risks analysis is done with the help of Pareto diagrams and scatter plot to determine the risks need to be corrected immediately. The proposed improvements are integrating the systems in form of e-cargo ready and implementing bar-coding. After the proposed e-cargo ready applied and being simulated, the delivery performance in terms of average total time reduced by 29,398%.

© 2018 Elsevier B.V. Sourcing flexibility is an increasingly important building block of supply chain flexibility. Our study which is grounded in information processing theory argues that two mechanisms can support firms in building up sourcing flexibility. Based on a survey of 336 manufacturing firms from Europe and the U.S. and using partial least squares (PLS) modeling as well as hierarchical regression analysis, we show that supplier evaluation and selection, and the integration of information systems at the buyer-supplier interface are positively related to sourcing flexibility. Sourcing flexibility, in turn, is curvilinearly related to delivery performance. Finally, delivery performance positively influences the product's financial performance. The strong associations between sourcing flexibility, delivery performance, and product financial performance underscore that sourcing flexibility merits the attention of supply chain managers during supplier selection and purchasing decisions.

Procurement is a key stage affecting the successful delivery of a sustainable project. Previous project procurement practice employed either the Lowest Tender (LT) method for homogeneous projects or the Best Value (BV) method for heterogeneous projects. Recently, a new type of procurement method for moderately heterogeneous project, the Heterogeneous Lowest Tender (HLT), was introduced and it has proven to be more beneficial and sustainable to clients in terms of both cost-effectiveness and the delivery performance of project products/results. However, statistics also showed that only 0.33% of public works adopt HLT for project procurement in Taiwan due to the lack of a useful method selection model. To solve this problem, this paper proposes an enhanced graphical method that is based on a previously defined Price Elasticity of Performance (PEP) measure, namely the Graphical Analysis Method for Price Elasticity of Performance (GAM-PEP), to select a more appropriate method from among the three prevailing project procurement methods: LT, BV, and HLT, so that the sustainability objectives of a project can be better realized. Finally, a real-world case construction procurement project was selected to demonstrate the feasibility of the proposed model. It is concluded that the proposed GAM-PEP outperforms the previous models in determining the most sustainable project procurement method.

The mobile opportunistic networks (MONs) aim to realize the data delivery in challenged network environment that is characterized by intermittent connectivity and dynamic network topology. To address the routing problems in MONs, a connectivity probability based spray and wait routing algorithm (CPSWR) is presented. First of all, in view of the data sending and receiving status of nodes in MONs, a three-dimensional connectivity matrix for network nodes is constructed. Then, CPSWR calculates the connectivity probability between nodes for the next time slot based on connectivity matrix. Finally, the spray process is guided by the connectivity probability. In CPSWR, the packet replication only takes place between nodes with high connectivity probability to improve the effectiveness of data forwarding. The simulation results demonstrate that compared with traditional spray and wait routing algorithm (SWR), CPSWR can reduce inefficient data forwarding and improve packet delivery performance.

In this paper a system is proposed whereby a group of small and inexpensive LEGO robots cooperate autonomously to transport a relatively much larger object to a specific location. In achieving this objective, the robots were able to generate a formation, recognise and locate neighbouring robot positions, control their motion and coordinate as a team in order to move the object to a set target location. Cooperative transportation algorithms were implemented, tested and evaluated on a physical setup, including pushing, caging and grasping. Results demonstrate that any desired formation shape can be generated and maintained without distance or orientation constraints. Caging and grasping algorithms yielded an accurate delivery performance, exhibiting reliability across different scenarios.

The main goal of this paper is to demonstrate the impact of transformational leadership, participative management and empowerment in green organizations on the OTD (On Time Delivery) index. An OTD index is one of the basic indicators monitored continuously in all production companies today. The first part reviews the literature related to impact of managing green organizations on goals fulfilment, which includes delays of orders realization. In the research part an analysis was performed in three enterprises located in Poland. It includes results showing how transformational leadership, participative management and empowerment influence OTD index in green organizations.

Engineering-To-Order (ETO) is a production approach where manufacturers design, engineer, and assemble a unique product based on specific customer requirements. In this type of operation, manufacturers are faced with many uncertainties in the supply chain and design process, which often lead to unreliable delivery time and high total cost. This paper proposes a project management approach to cope with the uncertainties in the ETO supply chain by allocating some buffer times within the supply chain network. Particle Swarm Optimization (PSO) is used to find the optimal configuration of the buffer time within the supply chain. The result shows that the buffer time optimization method can help manufacturers to keep a high level of on-time delivery performance (95%) while keeping the total cost minimum.

The growing threats are to states and the challenge is to strengthen them to withstand these mainly political forces and still be effective deliverers of services and programs. Consistent with the objective of effective government, the frequent call is for governments that can plan and deliver policies, programs, and projects efficiently and effectively, that is, delivery performance which is least cost and to maximum effectiveness in serving client needs. Because governments consist of horizontal and vertical structures of organizations and institutional processes, the tendency is to divide up this problem functionally. The actual quality of government and institutions is revealed partly by allocation of resources, usually through planning, approval, and execution of public budgets for current services and capital works. For improving governmental effectiveness, the relation between law and public management is all important. Law should facilitate management discretion in making necessary financial and personnel choices to deliver services, programs and projects as planned.

Large corporates and government institutions tend to have multi-year service engagements with IT-vendors who provide various kinds of infrastructure and management services including software, servers, IT - security, facility management etc. The engagements are formalized as legal contracts. Given the legal binding and the natural expectation to renew, there is a need to constantly monitor the performance against the stated objectives. Typically, a principle investigator or an account executive hold the responsibilities of deliverables and perform corrective actions as and when required. Given the complexity of the language and various variables involved, it is extremely difficult to proactively detect performance degradation. In this paper, we introduce the notion of contract health and describe Fitcon - a contract mining system that detects service level agreements from contracts, tracks the delivery performance against them and predicts the health of long term contracts. Fitcon is intelligent as it reads these natural language legal contract documents to set its monitoring goals. Fitcon tracks key parameters of the contract and predicts their performance. Comprehensive experiments on real contracts and corresponding past performance data are conducted to test the effectiveness of the system. We test our system across 11 large engagements and the analysis shows promising results. To the best of our knowledge, Fitcon is first such system that has been deployed into production for large scale contract health determination and prediction.

The topic of blockchain has been inundated with the fanaticism of cryptocurrencies' enthusiasts in recent years. In fact, the theory of blockchain and technologies behind are more worthy to be discussed to bring revolution to nowadays business operation. In this paper, we conduct an interdisciplinary study on business logistics as well as the cutting edge information technologies. We discuss the ongoing projects of blockchain in business industry, and then we propose our assessment model and blockchain framework to seek an enhanced metric for delivery performance with real-time feature and higher accuracy. Based on the our analysis, we identify the shortcomings of traditional assessment on delivery performance in contemporary global supply chain management and we discuss the potential benefits brought by adoption of our proposed framework.

Vehicular ad-hoc networking (VANET) is an effective and green approach to supporting the communication requirements of networked electric vehicles (EVs). This paper studies trajectory-based infrastructure-to-vehicle (I2V) message delivery over VANETs, whose operations can be summarized as follows: 1) the server first selects an appropriate roadside unit on the destination vehicle's subsequent trajectory as the rendezvous point (RP); 2) the server then transmits the message to the RP and expects that when the vehicle passes through the RP later, the message can be delivered from the RP to the vehicle. Such existing protocols commonly assume that vehicles move strictly following the suggested routes, without detours. Consequently, the delivery performance can be overestimated. This paper proposes an analytic model to investigate the impacts of vehicle detours on trajectory-based VANET I2V message delivery. The model derives the probability that a destination vehicle will pass through its RP, and thus receive the message successfully, considering the fact that the vehicle may detour during the movement. We validate the analytic model against simulation. Finally, several numerical examples are presented to quantitatively show how the message reception performance is affected by vehicle detours.

In recent content delivery mechanisms, popular contents tend to be placed closer to the users for better delivery performance and lower network resource occupation. Caching mechanisms in Content Delivery Networks (CDN), Mobile Edge Clouds (MECs) and fog computing have implemented edge caching paradigm for different application scenarios. However, state-of-the-art caching mechanisms in literature are mostly bounded by application scenarios. With the rapid development of heterogeneous networks, the lack of uniform caching management has become an issue. Therefore, a novel caching mechanism, Semi-Edge caching (SE), is proposed in this paper. SE caching mechanism is based on in-network caching technique and it could be generically applied into various types of network fog. Furthermore, two content allocation strategies, SE-U (unicast) and SE-B (broadcast), are proposed within SE mechanism. The performance of SE-U and SE-B are evaluated in three typical topologies with various scenario contexts. Compared to edge caching, SE can reduce latency by 7% and increase cache hit ratio by 45%.

The article presents the results of experimental study, conducted to determine UAV ad hoc network parameters providing the probability of link connectivity guaranteeing PDR (Packet Delivery Ratio) not less than 90% in the given area. For the research purpose the network structure imitation model was built in ns-2. OLSR is used as a routing protocol to discover paths between the nodes. The dependence of the nodes connectivity on such network parameters as the nodes number and transmission range is determined.

This paper proposes, describes and analyses two innovative approaches which make use of the Multipath Transmission Control Protocol (MPTCP) and its multiple flows for prioritised AR/VR content delivery. The first approach involves delivery of prioritised data using a fixed subflow and therefore establishment of a virtual private channel (VPC) for sending data. The second approach introduces a novel QoS on-the-fly (QoSF) algorithm that evaluates all subflows' delivery performance and dynamically selects one of them to deliver the prioritised content with the lowest latency. Both algorithms are assessed in single-homed and multi-homed configurations and present different performance improvements in comparison to the classic MPTCP. While QoSF algorithm demonstrates the best performance in scenarios where the delivery latency variation between sub flows is high, the VPC algorithm has the best results in scenarios where this variation is smaller.

Vehicular Ad-hoc Networks (VANETs) have emerged as a promising approach to support communications between autonomous cars and the accompanying intelligent transportation systems. Research in this area, namely vehicle-to-everything (V2X) communication, is focusing on two types of technologies: dedicated-short-range communication (DSRC) and advances in cellular networks. However, both technologies have limitations in performance, especially in high-density vehicular scenarios. In this paper, we propose a cognitive protocol translator capable of translating between LTE Sidelink device-to-device (D2D) and IEEE 802.11p DSRC packets, allowing interoperability of the two technologies. We propose this hybrid architecture as a potential solution to address the challenge of interoperability. We demonstrate through simulations the feasibility of our solution and show how the protocol converter has no adverse affect on packet delivery performance of the component DSRC and LTE ProSe technologies.

Irrigation performance assessment is an important step in ensuring sustainable agricultural development and improving the capacity of irrigation water management. In this paper, we examined irrigation water management in the Jiamakou Irrigation Scheme in the province of Shanxi (China) using four typical indicators, namely adequacy, efficiency, dependability, and equity. These indicators were calculated both globally and by grouping the data according to different irrigation processes (water allocation and water delivery). Results show that water was poorly allocated, and crop water requirements calculated through the FAO56 Penman-Monteith method was not met timely by scheduled water. They indicate that the overall performance of the scheme was relatively poor, owing to dismal water allocation. Nevertheless, water delivery performance was good, indicating that the scheme was able to deliver adequate and dependable water in an equitable and efficient manner. Our findings suggest that farmers should be trained in allocating irrigation water. The study provides insights into the current behavior of the irrigation scheme and may be used as a base for improvement of irrigation performance.

Globally, the adoption of Industrialised building system (IBS) has been acknowledged as a panacea for housing delivery performance. However, in most developing nations, especially Nigeria, its successful adoption is confronted with myriad of factors that are differently perceived by stakeholders resulting in poor performance and low uptake. The focus of this study is, therefore, to identify and evaluate those inhibiting factors as perceived by key construction stakeholders in the Nigerian construction industry. Initially, sixty-four (64) factors were identified through literature and structured interview. After which, a panel of experts, through Delphi method, considered forty-seven (47) of the factors contextual to IBS performance in Nigeria. 210 (70%) multidisciplinary construction professionals responded to the 300 administered questionnaires anchored on a Likert scale of I-5, (1-least significant to 5-Most Significant). Mean score approach was employed for data analysis. All the success factors were perceived to be critical. However, while forty (40) factors were perceived to excise high influence, seven (7) factors were found to moderately influence IBS performance. The five (5) critical success factors (CSFs) based on mean score (MS) are; Clear and precise goals (3.986), knowledge & skills (3.976), planning & control (3.948), top management support (3.938), and transportation (3.924). Having the knowledge of factors critical to IBS performance will assist key stakeholders' in their decision-making towards achieving effective project delivery.

Opportunistic mobile social networks (OMSNs) exploit human mobility to physically carry messages to the destinations. Routing algorithms in these networks typically favour the most popular individuals (nodes) as optimal carriers for message transfers to achieve high delivery performance. The state-of-the-art routing protocol BubbleRap uses a cumulative moving average technique (called C-Window) to identify a node's popularity level, measured in node degree, in a time window. However, our study found that node degree in real-life OMSNs varies quickly and significantly in time, and C-Window moreover slowly adapts to this node degree changes. To tackle this problem, we propose a new method of node degree computation based on the Kalman-filter theory. Using simulation, driven by real human contact traces, we showed that our approach can increase BubbleRap's performance, in terms of delivery ratio and traffic (load) distribution fairness.

CV Menoreh Politan is one of sugar coconut compan ies in Kalibuko, Kokap, Kulon Progo Regency Yogyakarta. Some of its coconut sugar products are sent to various regions in Indonesia, and some others are occasionally exported. The company, however, had encountered some constraints both in supply and product fulfillment. T his research was, t herefore , aimed at studying the efficiency of performance at CV Menoreh Politan. The input variables used wer e order fulfillment cycle, supply chain flexibility, total supply chain cost, cash to cash cycle time, and daily inventory, while input variables for output of supply chain performance were delivery performance, order fulfillment, and conformity with standard. The efficiency of coconut sugar supply chain performance is analyzed by Data Envelopment Analysis (DEA) method with constant return to scale (CRS) assumption. Analysis of farmer efficiency by using Data Envelopment Analysis (DEA) resulted in farmer efficiency level. CV Menoreh Politan has operated efficiently with its 14 partners (24.14 percent), while the remaining 44 farmers of CV Menoreh Politan (75.86 percent) have not reached the maximum efficiency level. The inefficiency of farmers was largely due to the cost of supply chains and long-term enterprise turnover. O veral l, t he collectors have been fully operational. Similarly, the company has been technically efficient, meaning that in terms of input and output , it ha s been good.

The delivery of green building projects is often more difficult than non-green building projects thereby resulting in low project performance. In order to overcome the difficulties and improve the delivery performance of green building projects, there is need to explore the perceived relationship between motivation and owner commitment (OC) based on the self-determination theory (SDT) of motivation. However no previous research has empirically tested this relationship in the context of green building delivery performance. Therefore this study evaluated this relationship using survey data from 150 project owners of green building projects in the Australian building sector. Data obtained was analyzed using both confirmatory factor analysis (CFA), and structural equation modelling (SEM) analysis of eight hypotheses (H1-H8). The SEM results reveal that OC has direct positive relationship with traditional delivery performance (TDP). Additionally, only the internal motivation (INT) of project owners has direct positive relationship with sustainability delivery performance (SDP), and this relationship is partially mediated by OC. The external motivation (EXT) has no direct positive relationship with OC, and neither TDP nor SDP. The study concludes that OC helps to improve the TDP of green building projects, while the INT of project owners is required to increase their commitment (OC) towards improving the SDP of green building projects. In addition, the EXT of project owners is not effective to increase their commitment (OC), as well as not contributing to improve TDP and SDP of green building projects. Theoretically, the application of SDT of motivation helps to contribute to the knowledge of how to improve the delivery performance of green building projects in the field of construction management and engineering. Practically, this study will help project owners to contribute to improve the delivery performance of green building projects. This study also provides the direction in which policies for encouraging the development of green building projects and associated practices should take in both Australia and the US henceforth.

Just-in-time delivery has become a key aspect of pharmaceutical industry when loyalizing customers and competing internationally. Additionally, prolonged lead times may lead to increased work-in-process inventory, penalties for non-compliance and cost overrun. The problem is more complex upon considering a wide variety of products as often noted in pharmaceutical companies. It is then relevant to design strategies focusing on improving the delivery performance. Therefore, this paper proposes the use of Discrete-event simulation (DES) to identify inefficiencies and define solutions for the delivery problem. First, input data were gathered and analyzed. Then, a DES model was developed and validated. Finally, potential improvement scenarios were simulated and analyzed regarding productivity rate and proportion of tardy jobs. A case study in a pharmaceutical laboratory is presented to validate the proposed methodology. The results evidenced that, by implementing the best scenario, the productivity may be augmented by 44.83% which would generate zero tardy jobs.

This paper addresses Information Centric Networks, and considers in-network caching for Named Data Networking (NDN) architectures. We depart from forwarding algorithms which primarily use links that have been selected by the routing protocol for probing and forwarding, and propose an adaptive forwarding strategy using reinforcement learning with the random neural network (NDNFS-RLRNN), to leverage the routing information and actively seek possible deliveries outside these paths in a controlled way. Our simulations show that NDNFS-RLRNN achieves more efficient delivery performance than a strategy that strictly follows the routing layer or a strategy that retrieves contents from the nearest caches by flooding requests.

The blood–brain barrier (BBB) hinders drug delivery to the brain. Despite various efforts to develop preprogramed actuation schemes for magnetic drug delivery, the unmodeled aggregation phenomenon limits drug delivery performance. This paper proposes a novel scheme with an aggregation model for a feed-forward magnetic actuation design. A simulation platform for aggregated particle delivery is developed and an actuation scheme is proposed to deliver aggregated magnetic nanoparticles (MNPs) using a discontinuous asymmetrical magnetic actuation. The experimental results with a Y-shaped channel indicated the success of the proposed scheme in steering and disaggregation. The delivery performance of the developed scheme was examined using a realistic, three-dimensional (3D) vessel simulation. Furthermore, the proposed scheme enhanced the transport and uptake of MNPs across the BBB in mice. The scheme presented here facilitates the passage of particles across the BBB to the brain using an electromagnetic actuation scheme.

In this paper we study the problem of minimizing total weighted tardiness, a proxy for maximizing on-time delivery performance, on parallel nonidentical batch processing machines. We first formulate the (primal) problem as a nonlinear integer programming model. We then show that the primal problem can be solved exactly by solving a corresponding dual problem with a nonlinear relaxation. Since both the primal and the dual problems are NP-hard, we use genetic algorithms, based on random keys and multiple choice encodings, to heuristically solve them. We find that the genetic algorithms consistently outperform a standard mathematical programming package in terms of solution quality and computation time. We also compare the smaller problem instances to a breadth-first tree search algorithm that gives evidence of the quality of the solutions.

We model a 3 echelon SC with uncertain and biased customers demand and RHF contract.Case study: Over 200 SC contracts were reviewed and customer order behavior analyzed.Changes in performance for different order behavior and RHF contracts were observed.RHF contracts need to be altered acc. to order behavior to increased performance.Asymmetrical RHF contracts perform better than symmetrical for biased demand data. The evidence base for the configuration of rolling horizon flexibility (RHF) contracts (a type of quantity flexibility contract) used in the semiconductor industry to coordinate production and demand remains meagre, more art than science. Informed by the characteristics of actual clauses and demand behaviors drawn from a companys experience, a discrete-event simulation model is developed to represent the companys supply chain. It comprises of three parties: a customer, a supplier (semiconductor manufacturer), and a capacity provider. Through analysis of customer forecasted demand the paper characterizes forecast demand as being under, over or unbiased. Models of these forecasted demands drives both long and short term planning. In long term planning, which is given twelve months before an order is delivered, capacity at the capacity provider is booked. Short term planning is also driven by this forecast which, within a binding period, is governed by an RHF contract. Results from the model report inventory levels, and delivery compliance, namely Delivery Performance (DP) and Delivery Reliability (DR), measures widely used in this sector. It is concluded from this work that on the balance of performance measures RHF contracts with asymmetrical flexibility bounds are substantially better than those with symmetrical boundaries, and that this conclusion is robust with regard to both over-planning and under-planning behaviors. This robustness is a critical attribute with respect to the endemic medium-term vacillation between both states experienced in practice in this sector.

The purpose of this study is to analyze the logistics delivery performance of rental tools delivery for temporary import in XYZ Power Plant Project at the Energy Service Division. This research is a mixture of quantitative and qualitative research and using both primary and secondary data, which collected from the company data including interview with the logistics manager and monitoring delivery data of XYZ Power Plant Project in the Logistics Department Energy Service Division. After the data was gathered, AMOS software is used to provide Structural Equation Modeling (SEM) and Path Diagram in order to identify influential factors to logistics delivery performance. Furthermore, to measure the KPI in terms of delivery reliability of logistics delivery performance levels of rental tools in XYZ power plant project in 2013 by the logistics department in the energy service fossil division. This study uses time series data from September 2013 - December 2013. Based on the results of research, it can be seen that customs clearance has positive moderate correlation to the logistics delivery performance, while number of items factor has a positive weak correlation to the logistics delivery performance. This research also found that the KPI in terms of delivery reliability of delivery performance level of rental tools in XYZ power plant project 2013 by the logistics department in the energy service division is 56.67%” which is Insufficient in logistics benchmark level. Thus, in purpose of increasing the logistics delivery performance in the XYZ Power Plant Project, the company should improve the delivery reliability. In addition the company should pay more attention to customs clearance process, since customs clearance is the most influential factor to the logistics delivery performance. Keywords: Logistics, Delivery Reliability, KPI, Temporary Import, On-Time Delivery.

Background : While both patients and physicians identify communication of bad news as an area of great challenge, the factors underlying this often complex task remain largely unknown. Emotional intelligence (EI) has been positively correlated with good general communication skills and successful leadership, but there is no literature relating EI to the delivery of bad news. Purpose : Our objectives were to determine: 1) performance of first-year pediatric residents in the delivery of bad news in a standardized patient (SP) setting; and 2) the role of EI in these assessments. Our hypothesis was that pediatric trainees with higher EI would demonstrate more advanced skills in this communication task. Methods : Forty first- year residents participated. Skill in bad news delivery was assessed via SP encounters using a previously published assessment tool (GRIEV_ING Death Notification Protocol). Residents completed the Emotional and Social Competency Inventory (ESCI) as a measure of EI. Results : Residents scored poorly on bad news delivery skills but scored well on EI. Intraclass correlation coefficients indicated moderate to substantial inter-rater reliability among raters using the delivering bad news assessment tool. However, no correlation was found between bad news delivery performance and EI. Conclusions : We concluded that first-year pediatric residents have inadequate skills in the delivery of bad news. In addition, our data suggest that higher EI alone is not sufficient to effectively deliver death news and more robust skill training is necessary for residents to gain competence and acquire mastery in this important communication domain. Keywords: breaking bad news; emotional intelligence; pediatrics (Published: 17 August 2015) Citation: Med Educ Online 2015, 20: 24245 - http://dx.doi.org/10.3402/meo.v20.24245

For any nation-state, multiple agencies are drawn in to guard their maritime interests, and technology plays a crucial role towards guarding such interests. This paper debates the significance of space technologies for the maritime domain in general and navies in particular. It identifies specific space technologies of relevance for improving ship movement and weapons delivery performance. Lastly, the paper also takes a macro view about investments made by India in space technologies for the purposes of their maritime requirements.

Given the growing importance of supplier delivery performance in buyer–supplier alignment and end-to-end fulfillment of supply chains, we investigate the managerial implications of a buyer who financially invests to improve a supplier’s delivery performance by demonstrating an optimization model for the buyer’s investment decision to reduce untimely delivery. We illustrate how improving supplier delivery performance leads to better supplier management. Our analysis utilizes the ingenious zeta transforms widely used in engineering to showcase its applicability in today’s complex supply landscapes that use multiple suppliers to create efficient frontiers for diverse sourcing initiatives.

Models for evaluating supply chain delivery performance commonly assume a Gaussian delivery time distribution when the true underlying delivery time probability density function (PDF) cannot be analytically determined. Recent research has identified limitations to using the Gaussian PDF and has demonstrated the advantages of using the asymmetric Laplace PDF to model a supply chain delivery time distribution. Current models which use the asymmetric Laplace to model a supply chain delivery time distribution are limited in their scope of application for modeling continuous improvement of delivery performance. In this paper we present a more robust asymmetrical Laplace delivery performance model which overcomes limitations found in the current set of models. A set of propositions for modeling delivery improvement in terms of both the mean and variance of the delivery time distribution are presented. The results of a set of 48 numerical examples conducted across a range of key input parameters are used to illustrate the delivery improvement capabilities of the model.

The alliance contract is a flexible form of partnering between organisations, and, to date, alliances for the delivery of infrastructure projects in the construction industry have typically been a partnership between one owner participant and one or more non-owner participants, including a design consultancy. The Christchurch infrastructure rebuild team in New Zealand, set up to deliver the reconstruction of the earthquake-damaged infrastructure, is a multi-client, multi-contractor programme alliance with professional services procured from consultancies amalgamated into four teams that are not participants in the alliance model. This multi-client, multi-contractor alliance is different from more commonly used ‘classes’ of alliances in the procurement of design services. In particular, the introduction of a delivery performance score provides price tension between the non-owner participants and ensures value for money for the client organisations, while the gain/pain incentive ensures both collaboration across the delivery teams and independent target outturn cost development with no direct price influence from the delivery teams.

The concept of delayed product differentiation has received considerable attention in the research literature in recent years. However, few analytical models explain and quantify the benefits of delayed product differentiation strategy with additional consideration of supplier delivery performance. This paper proposes a delayed product differentiation model in which a supply of raw materials is integrated at the beginning of the production process to match uncertain demand in a cost-effective way given the constraint of lead time delivery window. It develops insights regarding a delayed product differentiation strategy and shows that with respect to delivery windows, supplier delivery performance plays an important role in the determination of the optimal point of differentiation. This study also shows that when the “ on-time ” and the “ late ” portions of the delivery window are constant, the proposed cost function coincides with similar models found in the literature. An extension of this work also reveals that when the customer service level varies across various production stages, its choice affects the decision to delay or postpone the customization point. A mini industrial case involving the customization of a personal desktop computer is used to illustrate the applicability of the resulting framework.

This study empirically investigated how small and medium-sized Chinese apparel enterprises (SME) formed their strategy as a response to the characteristics of business environment in order to achieve competitive business performance. An environment-strategy-performance model was proposed and tested. Using primary data gathered by a questionnaire survey of the Chinese apparel industry, factor analysis and structural equation modeling (SEM) were conducted for measurement and structural model analysis and hypothesis testing. Results show the proposed model met parsimonious statistical criteria. The differences in strategy responses to environment between high- and low-performing firms were striking. Confronting an increasingly turbulent business environment, high performers emphasized differentiation strategy through higher quality, better delivery performance, and greater flexibility than cost reduction. In contrast, low performers prioritized low cost while quality and flexibility were given certain weights. The lack of clear focus on strategies could result in a relatively lower performance. While the process of government-led industrial upgrading continues, forward-looking firms have proactively shifted their strategic focus from solely or mainly cost reduction to a variety of differentiating factors which bring in added value and are less imitable by competitors.

In the recent years, more and more researchers believe measurement‐based quality assurance (QA) method for intensity‐modulated radiotherapy (IMRT) is insensitive in detecting various types of failures. 1 , 2 , 3 Machine delivery log‐file analysis has been proposed to be a more effective and efficient approach in verifying IMRT delivery accuracy in terms of gantry, collimator, jaws, and MLCs. 1 , 4 , 5 , 6 , 7 , 8 , 9 However, whether log file measurements can replace conventional QA methods remains a major debate in current medical physics society. This is addressed as our first parallel/opposed topic. Nathan Childress is parallel to the argument. Dr. Childress received his Ph.D. in Medical Physics in 2004 from University of Texas‐M.D. Anderson Cancer Center, his M.S. in Nuclear Engineering, and his B.S. in Chemical Engineering from the University of Missouri‐Columbia, both in 2001. His dissertation focused on bulk IMRT QA analysis and film dosimetry. He worked as a clinical physicist for six years at The Methodist Hospital before founding Mobius Medical Systems, LP in 2010. Mobius has designed and developed software packages that perform linear accelerator QA, treatment plan QA, and IMRT QA. He created and maintains www.medphysfiles.com, a site for the free sharing of files related to clinical medical physics. Dr. Childress is a Section Editor for the JACMP and is certified by the American Board of Radiology in Therapeutic Radiological Physics. Quan Chen is opposing the argument. Dr. Chen obtained his Ph.D in medical physics from University of Wisconsin‐Madison, Madison, WI in 2004. He joined TomoTherapy Inc. the same year as a medical physicist, focusing on research and innovations. He joined University of Virginia in 2011 as an assistant professor in the radiation oncology department. His main research interests include tomotherapy, high‐performance computing, optimization and dose calculation, Monte Carlo, and innovative QA methods. He has authored and co‐authored over 50 papers in peer‐reviewed journals and holds seven granted patents. Dr. Nathan Childress (Mobius Medical Systems, LP) The goal of IMRT QA is to ensure each patient receives safe and effective treatment. Linear accelerator log files, when used intelligently, are the optimal means of performing IMRT QA. Not only can log file‐based IMRT QA verify information transfer integrity and delivery performance, it can do so more accurately and efficiently than conventional methods. Conventional IMRT QA methods of measuring the dose distribution in a plastic phantom are laborious, insensitive to some error types, and devoid of specificity. This leads some physicists to view IMRT QA as a tool to detect large machine calibration errors, whereas the true goal of IMRT QA is detecting errors specific to an individual patient's plan. Conventional IMRT QA produces a single, integrated result with limited pathway to identify and remedy error sources. Instead of fixing root causes, physicists end up either aimlessly repeating IMRT QA measurements until they pass, or they spend copious amounts of time investigating individual components. The lack of sophisticated methods may be one reason why approximately 20% of institutions fail RPC heterogeneous phantom irradiations at 7%/4 mm criteria (10) despite having acceptable conventional IMRT QA outcomes. Performing IMRT QA using log files offers several advantages. First, the delivered 3D dose can be calculated from log files in the patient CT and compared directly with the prescribed treatment plan. Not only does this comparison validate information transfer from the planning system, but it also allows for a comprehensive and quantitative assessment of the impact of delivery performance on the three‐dimensional dose in a patient. Second, log files are produced each time the plan is delivered, meaning the method can be utilized during patient deliveries, in addition to a single pretreatment measurement. This extends the current IMRT QA paradigm to include the entire course of delivery. Third, the entire process can be completely automated, yielding a detailed analysis of dose in patient's anatomy available within minutes of delivery. This reduces the workload required for IMRT QA on the medical physics team, and enables them to more efficiently focus their effort on evaluating the QA outcome rather than producing it. Finally, a system that employs an accurate, independent dose calculation algorithm to recalculate the dose in the patient CT using both the planned values and the data contained in the log files allows for a clear separation of errors (treatment plan versus treatment delivery), thus allowing physicists to fix root causes of problems. It is important to note that log file‐based IMRT QA must be augmented with independent commissioning measurements and a robust routine QA program (such as AAPM TG 142) to verify machine calibration. Once external systems are used to validate machine calibrations, the high temporal and spatial resolution of log files can identify patient‐specific errors and their sources almost automatically. Detection of certain errors in IMRT QA may then trigger additional machine‐specific tests. The use of log files for IMRT QA, when intelligently utilized as part of a robust QA program, can give physicists more time and information to analyze the clinical impact of detected errors and effectively mitigate them.

This article aims to integrate capability-based theory into purchasing management. The research model presented in the article focuses on the effect of supplier evaluation capability and risk management capability on delivery performance. Further, the article explores the moderating effect of demand and technological uncertainty. The methodology relies on a multiple informant survey design with responses from purchasing and production managers in Danish manufacturing companies. Hypotheses are tested using regression analysis based on data collected from 197 firms. Risk management capability is found to increase delivery performance. Unexpectedly, supplier evaluation capability was found to decrease delivery performance. Demand uncertainty has a negative effect on delivery performance. Technological uncertainty had no effect on delivery performance. The results are discussed in detail in the final section of the article.