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The purpose of this paper is to examine the relevance of retailer country-of-origin (COO) on consumers’ actual choice between foreign and domestic retailers. It explores two basic issues regarding the relevance of COO, first to assess consumer perceptions regarding the importance of retailer COO (PIO) and the importance of supporting domestic retailers (PISD) in store choice decisions. The second is to analyse the influence of these factors on store choice decisions. Relative influence of PIO and PISD (compared to the retail mix factors) was also evaluated.

Data were collected through a consumer survey targeting grocery consumers in a second-tier city in China. Factor analysis and binary probit models were used to analyse the data.

The authors found that a considerable proportion of respondents perceive retailer COO and being supportive of domestic retailers as important factors when choosing between foreign and domestic retailers. Interestingly, results of probit analysis showed that consumers’ perceived importance of retailer COO (PIO) did not have a significant impact on consumer store choice behaviour. In contrast, consumers’ perceived importance of supporting domestic retailers has a negative effect on consumers’ choice of foreign retailers. Results of the relative contribution of retail mix factors and COO variables showed that generally, COO variables are as important as retail mix factors.

This study is one of the few empirical studies on the relevance of retailer COO and it focused on two basic issues concerning the consumer perceptions regarding the importance of retailer COO, seldom studied previously. This study makes a significant contribution to the COO literature not only because it focuses on the retailing context but also by providing a fresh perspective.

The purpose of this paper is to review the food supply chain management (FSCM) in terms of systems and implementations so that observations and lessons from this research could be useful for academia and industrial practitioners in the future.

A systematical and hierarchical framework is proposed in this paper to review the literature. Categorizations and classifications are identified to organize this paper.

This paper reviews total 192 articles related to the data-driven systems for FSCM. Currently, there is a dramatic increase of research papers related to this topic. Looking at the general interests on FSCM, research on this topic can be expected to increase in the future.

This paper only selected limited number of papers which are published in leading journals or with high citations. For simplicity without generality, key findings and observations are significant from this research.

Some ideas from this paper could be expanded into other possible domains so that involved parties are able to be inspired for enriching the FSCM. Future implementations are useful for practitioners to conduct IT-based solutions for FSCM.

As the increasing of digital devices in FSCM, large number of data will be used for decision-makings. Data-driven systems for FSCM will be the future for a more sustainable food supply chain.

This is the first attempt to provide a comprehensive review on FSCM from the view of data-driven IT systems.

Accurately, positioning is a fundamental requirement for vision measurement systems. The calculation of the harvesting width can not only help farmers adjust the direction of the intelligent harvesting robot in time but also provide data support for future unmanned vehicles.

To make the length of each pixel equal, the image is restored to the aerial view in the world coordinate system. To solve the problem of too much calculation caused by too many particles, a certain number of particles are scattered near the crop boundary and the distribution regularities of particles’ weight are analyzed. Based on the analysis, a novel boundary positioning method is presented. In the meantime, to improve the robustness of the algorithm, the back-projection algorithm is also used for boundary positioning.

Experiments demonstrate that the proposed method could well meet the precision and real-time requirements with the measurement error within 55 mm.

In visual target tracking, using particle filtering, a rectangular is used to track the target and cannot obtain the boundary information. This paper studied the distribution of the particle set near the crop boundary and proposed an improved particle filtering algorithm. In the algorithm, a small amount of particles is used to determine the crop boundary and accurate positioning of the crop boundary is realized.

To reduce the effect of parameter uncertainties and input saturation on path tracking control for autonomous combine harvester, a path tracking controller is proposed, which integrates an adaptive neural network estimator and a saturation-aided system.

First, to analyze and compensate the influence of external factors, the vehicle model is established combining a dynamic model and a kinematic model. Meanwhile, to make the model simple, a comprehensive error is used, weighting heading error and position error simultaneously. Second, an adaptive neural network estimator is presented to calculate uncertain parameters which eventually improve the dynamic model. Then, the path tracking controller based on the improved dynamic model is designed by using the backstepping method, and its stability is proved by the Lyapunov theorem. Third, to mitigate round-trip operation of the actuator due to input saturation, a saturation-aided variable is presented during the control design process.

To verify the tracking accuracy and environmental adaptability of the proposed controller, numerical simulations are carried out under three different cases, and field experiments are performed in harvesting wheat and paddy. The experimental results demonstrate the tracking errors of the proposed controller that are reduced by more than 28% with contrast to the conventional controllers.

An adaptive neural network-based path tracking control is proposed, which considers both parameter uncertainties and input saturation. As far as we know, this is the first time a path tracking controller is specifically designed for the combine harvester with full consideration of working characteristics.

Despite the widespread expectation that additive manufacturing (AM) will become a disruptive technology to transform the spare parts supply chain, very limited research has been devoted to the quantitative modeling and analysis on how AM could fulfill the on-demand spare parts supply. On the other hand, the choice of using AM as a spare parts supply strategy over traditional inventory is a rising decision faced by manufacturers and requires quantitative analysis for their AM-or-stock decisions. The purpose of this paper is to develop a quantitative performance model for a generic powder bed fusion AM system in a spare parts supply chain, thus providing insights into this less-explored area in the literature.

In this study, analysis based on a discrete event simulation was carried out for the use of AM in replacement of traditional warehouse inventory for an on-demand spare parts supply system. Generic powder bed fusion AM system was used in the model, and the same modeling approach could be applied to other types of AM processes. Using this model, the impact of both spare parts demand characteristics (e.g. part size attributes, demand rates) and the AM operations characteristics (e.g. machine size and postpone strategy) on the performance of using AM to supply spare parts was studied.

The simulation results show that in many cases the AM operation is not as cost competitive compared to the traditional warehouse-based spare parts supply operation, and that the spare parts size characteristics could significantly affect the overall performance of the AM operations. For some scenarios of the arrival process of spare parts demand, the use of the batched AM production could potentially result in significant delay in parts delivery, which necessitates further investigations of production optimization strategies.

The findings demonstrate that the proposed simulation tool can not only provide insights on the performance characteristics of using AM in the spare parts supply chain, especially in comparison to the traditional warehousing system, but also can be used toward decision making for both the AM manufacturers and the spare parts service providers.

The main purpose of this paper is to explore the influence mechanism of corporate social responsibility (CSR) for smart cities on consumers' purchase intention. The authors aim to identify the key components of CSR for smart cities based on the perspective of consumers, namely responsibility toward consumers, environment and community and validate their relationship.

The authors exploit data collected by questionnaire surveys to estimate the effects of CSR for smart cities on consumers' purchase intentions and to investigate the statistical causality between them. The multilinear regression model is used to figure out the different impact levels of the three dimensions of CSR for smart cities on consumers' purchase intention.

The results illustrate that CSR for smart cities and its three dimensions all have significant positive impacts on consumers' purchase intentions. Besides, consumer–corporate identity (CCI) exerts a partial mediation effect on this influence mechanism.

This research is based on a rather small sample size. Besides, due to the time limitation and other factors, some other control variables are neglected in the regression model. Therefore, the impact level could be distorted.

The authors put forward management implications according to research conclusions. Corporates should actively fulfill the CSR in the field of consumer responsibility to boost consumers' purchase intention. Corporate should strengthen the interaction with consumers to improve their corporate identity.

The main contribution of this paper is to provide convincing evidence of the impacts of CSR for smart cities on consumer purchase intention (CPI), thus proposing effective measures for corporates to win more consumers by taking on social responsibility for smart cities. This paper takes CCI as mediating variable to deepen the understanding of the impacts of CSR for smart cities on CPI, which is innovative and beneficial to enriching literature in related fields.

The purpose of this paper is to investigate the post-treatment processes on lattice structures of selective laser melting. Moreover, the effect of pressure during hot isostatic pressing (HIP) is determined.

Three post-treatment processes, annealing at 650°C, 920°C and HIP were adopted. The microstructure evolution and mechanical properties of selective lasering melted Ti6Al4V lattice structures after post-treatment were systematically investigated by optical microscope, scanning electron microscope, electron backscattered diffraction, differential scanning calorimetry and quasi-static mechanics tests.

The main findings in this paper are as below: first, the pores existing in the samples as-fabricated, annealed at 650°C and 920°C are disappeared after HIP. Second, the microstructure and compressive properties after HIP are similar to that after pure annealing at the same temperature. However, the HIPed sample had the highest number of cycles to failure. Third, the fracture mechanism of as-fabricated samples changes from mixed fracture to the micro-voids accumulation fracture after post-treatment processes.

HIP post-treatment can be replaced by annealing at the same temperature when the requirement for porosity and fatigue life is not very high.

This study developed two presentation modes of scientific articles and evaluated their usability with user experiments.

Two presentation modes of scientific articles, simply referred to as “genre presentation mode” and “argument presentation mode”, were constructed based on their genre structure and argument structure respectively. Their usability was evaluated by being compared against the existing RichHTML presentation mode in the experiments using eye-tracking and questionnaire methods.

The participants who were going to find the specific information of scientific articles rated the genre presentation mode higher than they did with either the argument or the RichHTML presentation mode for effectiveness. In contrast, those who were going to understand the general idea of scientific articles rated both the genre and argument presentation mode higher than they did with the RichHTML mode. In terms of efficiency, the participants took less reading time when the articles of non-native language were presented with the genre mode than they did when the articles were presented with the argument mode. When reading the articles in native language to understand the general idea, the participants took less reading time for the articles presented with the argument mode than they did for the articles presented with the genre mode. In comparison, they took less reading time when the articles were presented with the argument mode if they were going to find specific information. For satisfaction, the genre presentation mode was more popular than the argument mode and the RichHTML mode. However, the participants were less satisfied with the argument presentation mode than the other two when reading in native language and intending to find specific information.

The two presentation modes of scientific articles are found to improve the accuracy of information acquisition, shorten the total reading time and be more acceptable by readers.

The purpose of this paper is to investigate the effect of strut size on the compressive response for selective laser-melted lattice structure with a body-centered cubic (BCC) unit cell.

Theoretical analysis and numerical simulation were used to predict the compressive stiffness and strength of the lattice structures with different struts, and compression testing was conducted to validate the predicted results. The effect of strut size on actual porosity was determined with the dry weighting method. Scanning electron microscopy was used to observe the fracture morphologies.

The actual porosities in all the specimens turned out to be a little lower than the values expected from design. The maximum deviation appears at the strut size of 1.25 mm. The theoretical analysis reveals that the junctions of BCC unit cells are the most loaded points, and the maximum compression resistance load is proportional to the strut size. The stress–strain curves and collapse modes predicted by numerical simulation are in good agreement with the theoretical calculation and experimental results. The compression stress increases monotonously in strut size of 0.50–2.00 mm. The fracture morphologies reflect a transition from a mixed to ductile fracture mechanism. The lattice structure shows a stable plastic deformation without a destructive fracture for the strut size of 2.00 mm.

The findings of this study can provide theoretical and experimental support for the choice of strut size under different stress conditions. In addition, they are conductive to in-depth study of the compressive properties for lattice structures with different geometrical dimensions fabricated by selective laser melting.