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This study aims to understand the market structure and explore the applicability of recognised generalisations to a European wine retail market. The study considers whether brands in European wine retailing follow the established double jeopardy and duplication of purchase laws, with the aim of investigating their limits so as to identify where market partitions are evident.

The researchers conducted a cross-purchasing analysis within the wine category over a 12-month period, using a customer panel of n = 25,000 across a chain of independent retail stores in an English-speaking European country. Analysis was conducted across purchases of the top 20 wine brands.

Consumer wine repurchase results confirmed a double jeopardy pattern. These consumers’ wine repurchasing behaviour from other top-20 wine brands could have generally been predicted in line with the duplication of purchase law. However, a small number of exceptions to these patterns were identified, suggesting the existence of market partitions.

In this study, market partitions were evident for selected brands, a wine region and a common grape variety, Sauvignon blanc. Such exceptions illustrate that consumer purchase patterns can deviate from predictions, for a small number of brands in a consumer goods category than would be expected given duplication of purchase law norms. Such anomalies to empirical generalisations help demonstrate boundary conditions and lead further research on the market conditions required for such anomalies to be evident. Implications suggest that further research should be conducted on the product features creating market partitions.

The findings suggest that regional wines can appeal to a more clearly partitioned customer group within the clientele, but that substitution is noted among brands within regions.

To the best of the authors’ knowledge, this is the first study to use a large sample consumer database to determine the generalisability of two well-established empirical generalisations: the double jeopardy and duplication of purchase laws, to the wine retail market. Knowing these are applicable to the wine retail markets allows wine producers and retailers to predict expected repurchase and cross-purchasing norms.

The purpose of this paper is to investigate, experimentally and numerically, the pressure pulse characteristics and unsteady flow behavior in a Francis turbine runner for moderate flow heads. The pressure pulses in the runner blade passage were predicted numerically for both moderate and high heads. The calculations were used to partition the turbine operating regions and to clarify the various for the unsteady flow behavior, especially the blade channel vortex in the runner.

Experimental and numerical analyses of pressure pulse characteristics at moderate flow heads in a Francis turbine runner were then extended to high heads through numerical modeling with 3D unsteady numerical simulations performed for a number of operating conditions. The unsteady Reynolds‐averaged Navier‐Stokes equations with the k‐ω‐based shear stress transport turbulence model were used to model the unsteady flow within the entire flow passage of a Francis turbine.

The dominate frequency of the predicted pressure pulses at runner inlet agree with the experimental results in the head cover at moderate flow heads. The influence of the blade passing frequency causes the simulated peak‐to‐peak amplitudes in the runner inlet to be larger than in the head cover. The measured and predicted pressure pulses at different positions along the runner are comparable. At the most unstable operating condition of 0.5a₀ guide vane opening, the pressure pulses in the runner blade passage are due to the blade channel vortex and the rotor‐stator interference. The predictions show that the frequency of the blade channel vortex is relatively low and it changes with the operating conditions.

The paper describes a study which experimentally and numerically investigated the pressure pulses characteristics in a Francis turbine runner at moderate flow heads. The pulse characteristics and unsteady flow behavior due to the blade channel vortex in the runner at high heads were investigated numerically, with the turbine operating regions then partitioned to identify safe operating regions.

The expected benefits of newly developed transportation infrastructures are the saving of travel time and further promoted transport economics. There is a need for a methodology of travel time estimation with acceptable robustness and practicability. Macroscopic fundamental diagram (MFD) represents the overall traffic performance at a network level by linking average flow, speed and density. MFD can be used to estimate network state and to describe various traffic management strategies. This study aims to describe the effect of new infrastructure development on the network performance using the MFD framework.

The scenarios of Islamabad Road network before and after the infrastructure construction were simulated, in which the floating car data set (FCD) for multiple modes was extracted. MFD has been formed for the whole region and partitioned region, which was divided on the basis of infrastructural changes. Moreover, this study has been extended to calculate travel time for multiple modes using the MFD results and the Bureau of Public Roads (BPR) function at a neighborhood level.

MFD results for the whole network showed that the speed of traffic improves after the construction of new infrastructure. The travel time estimates using MFD results were dependent on the speed estimates, whereas the estimates obtained using the BPR function were found to be dependent on the traffic volume variation during different intervals of the day. By using the FCD for multiple modes, travel time estimates for multiple modes were obtained. The BPR function method was found valid for estimating travel time of traffic stream only.

This paper innovatively investigates the change in network performance for pre-construction and post-construction scenarios using the MFD framework. In practice, the approach presented can be used by transportation agencies to evaluate the effect of different traffic management strategies and infrastructural changes.

The purpose of this paper is to measure the performance of a sampling method through the average number of samples drawn in control.

Matching the adjusted average time to signal (AATS) of sampling methods, using as a reference the AATS of one of them the paper obtains the design parameters of the others. Thus, it will be possible to obtain, in control, the average number of samples required, so that the AATS of the mentioned sampling methods may be equal to the AATS of the method that the paper uses as the reference.

A more robust performance measure to compare sampling methods because in many cases the period of time where the process is in control is greater than the out of control period. With this performance measure the paper compares different sampling methods through the average total cost per cycle, in systems with Weibull lifetime distributions: three systems with an increasing hazard rate (shape parameter β=2, 4 and 7) and one system with a decreasing failure rate (β=0, 8).

In a usual production cycle where the in control period is much larger than the out of control period, particularly if the sampling costs and false alarms costs are high in relation to malfunction costs, the paper thinks that this methodology allows us a more careful choice of the appropriate sampling method.

To compare the statistical performance between different sampling methods using the average number of samples need to be inspected when the process is in control. Particularly, the paper compares the statistical and economic performance between different sampling methods in contexts not previously considered in literature. The paper presents an approximation for the average time between the instant that failure occurs and the first sample with the process out of control, as well.

The purpose of this review is to comprehensively consider the material properties and processing of additive titanium alloy and provide a new perspective for the robotic grinding and polishing of additive titanium alloy blades to ensure the surface integrity and machining accuracy of the blades.

At present, robot grinding and polishing are mainstream processing methods in blade automatic processing. This review systematically summarizes the processing characteristics and processing methods of additive manufacturing (AM) titanium alloy blades. On the one hand, the unique manufacturing process and thermal effect of AM have created the unique processing characteristics of additive titanium alloy blades. On the other hand, the robot grinding and polishing process needs to incorporate the material removal model into the traditional processing flow according to the processing characteristics of the additive titanium alloy.

Robot belt grinding can solve the processing problem of additive titanium alloy blades. The complex surface of the blade generates a robot grinding trajectory through trajectory planning. The trajectory planning of the robot profoundly affects the machining accuracy and surface quality of the blade. Subsequent research is needed to solve the problems of high machining accuracy of blade profiles, complex surface material removal models and uneven distribution of blade machining allowance. In the process parameters of the robot, the grinding parameters, trajectory planning and error compensation affect the surface quality of the blade through the material removal method, grinding force and grinding temperature. The machining accuracy of the blade surface is affected by robot vibration and stiffness.

This review systematically summarizes the processing characteristics and processing methods of aviation titanium alloy blades manufactured by AM. Combined with the material properties of additive titanium alloy, it provides a new idea for robot grinding and polishing of aviation titanium alloy blades manufactured by AM.

The purpose of this paper is to determine if services brands such as banks share their customers with competing brands in line with the market share of those competitors, and whether services brands with similar images form market partitions with heightened competitive intensity.

The study uses brand usage, forced-choice and brand perceptions data obtained from a survey of consumers. The study uses a log-linear modelling framework to identify market structure and to test if partitions correspond to similarities in brand image.

Analysis of in-market data shows customers share their requirements between competing brands in line with market share, and that brands with similar images do not form partitions. However, when consumers are asked to choose brands for a specific product, there is some tentative evidence of brand partitions among brands with similar brand image.

The results here can help managers in service markets such as banking and insurance understand market structure. As a result, they can better plan customer acquisition and retention strategies.

The study addresses a lack of research into customer sharing and switching in services markets. No previous study has successfully employed brand-sharing, forced-choice and brand image data to identify market structure in a services context.

This study aims to understand the degree of predictability and value in analyzing consumer purchase patterns in the US wine retail market. The study considers whether brands in US wine retailing follow the well-established Duplication of Purchase Law and Double Jeopardy Law.

Over 20,000 customer panel wine purchases were analyzed from a number of locations within a supermarket chain based on the West Coast of the USA. Cross-purchasing behavior for the top 20 wine brands by market penetration was analyzed to assess whether the well-established Duplication of Purchase Law and Double Jeopardy Law hold up in this wine retail setting in the USA. The degree of predictability and the existence of anomalies in expected cross-purchasing behavior were identified in the analysis.

Results confirmed a Double Jeopardy pattern and that wine cross-purchasing patterns for the most part followed the Duplication of Purchase Law. However, exceptions to these patterns were found, which indicated areas in need of managerial attention due to the potential to remedy, develop or monitor the most prominent variations between predicted and realized cross-purchasing behavior. Repeated identification of variations has been identified in other product categories, known as market partitions.

Although it is commonly believed that wine is a unique product category, the results of this study demonstrate that consumer behavior toward wine is similar to other fast-moving consumer goods. The exceptions suggest that while similar consumer purchase patterns are evident, consumers are more likely to cross purchase wine brands and grape types more than would be expected given Duplication of Purchase Law benchmarks.

An algorithm for Delaunay partitioning in three dimensions is given, and its use in numerical semiconductor models is examined. In particular, tetrahedral elements are found to be compatible with the Scharfetter‐Gummel discretization of the stationary continuity equations associated with such models, using the Voronoi cross‐sections for each edge in the obtained network. For tetrahedral elements, however, the Voronoi cross‐sections do not coincide with those previously shown to be compatible with the Scharfetter‐Gummel method.

This paper addresses the issues involved in the design of high‐density boards for high‐density chip scale packages. An analytical model is developed to calculate the number of I/Os accommodated by the printed wiring board. The model is placed under constraints of package area, package I/O pitch, number of lanes per channel, PWB device feature sizes (I/O, via pad, signal traces), number of routing layers on board and the partition of routing regions on each level. The model is utilized to study the precise impact of number of routing layers and device feature size on the I/O density of PCB. The scheme for optimally partitioning each layer to achieve maximum I/O density is discussed. Specific guidelines are provided pertaining to the usage of higher board layers and/or reduced device feature sizes to design high‐density boards for future electronic products.