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To assess the introduction and performance of light electric freight vehicles (LEFVs), more specifically cargo cycles in major 3PL organizations in at least two Nordic countries.

Case studies. Interviews. Company data on performance before as well as after the introduction. Study of differing business models as well as operational setups.

The results from the studied cases show that LEFVs can compete with conventional vans in last mile delivery operations of e-commerce parcels. We account for when this might be the case, during which circumstances and why.

Inherent limitations of the case study approach, specifically on generalization. Future research to include more public–private partnership and multi-actor approach for scalability.

Adding to knowledge on the public sector facilitation necessary to succeed with implementation and identifying cases in which LEFVs might offer efficiency gains over more traditional delivery vehicles.

One novelty is the access to detailed data from before the implementation of new vehicles and the data after the implementation. A fair comparison is made possible by the operational structure, area of delivery, number of customers, customer density, type of packages, and to some extent, the number of packages being quite similar. Additionally, we provide data showing how city hubs can allow cargo cycles to work synergistically with delivery vans. This is valuable information for organizations thinking of trying LEFVs in operations as well as municipalities/local authorities that are interested.

The purpose of this study is to examine households’ behavior towards dirty cooking energy utilisation in an environment where relatively higher accessibility to clean energy is noted. Although the low utilisation rate of clean energy can partly be attributed to utility gains anticipated in dirty energy mixes (DEMs) arising out of accessibility constraints, affordances and enablers, it is still unclear on the extend at which each of these contributes towards DEMs manifestation among the seemingly well-to-do households with higher levels of clean energy mixes (CEM) access. This study, therefore, hinges on scrutinising on this lower utilisation patterns despite a seemingly higher accessibility of CEMs, specifically liquified petroleum gases (LPG).

The study is based on a household’s survey that was carried out in 2018, reaching a sample of 393 households using questionnaires in four wards of the Kigamboni district in Tanzania. Subsequent analyses were descriptive as well as inferential based on binary logistic regression analysis where utilisation of DEMs was predicted for both the high and low social economic status (SES) households by incorporating accessibility constraints, affordances and enablers.

The results show, first, if one assumes energy stacking is not an issue, as households become more constrained towards CEMs utilisation, they shift towards DEMs suggesting that the overall effect is a substitution, and second, the complementarity effect ultimately outweighs the substitution effect as households do not shift from DEMs to CEMs rather stack multiple energy. DEMs flourish in this case study area because those with high income are among those in the lowest SES, and some of those with the highest SES are from among the lowest income category, and all of them end up with more DEMs because shifting towards CEMs require income to complement SES.

Policy-wise, removing hurdles in accessing CEMs such as LPG subsidy programme, gas stove provision to the poor, and enhanced LPG awareness will most likely benefits only those who do not stack energy in cooking while strategies targeting those at the lowest SES such as higher education attainment, empower women as a family decision maker, encourage co-occupancy to enlarge the household size and contain urban growth within certain perimeter will have a significant impact only if they raise both incomes and SES.

Despite of the dominance of DEMs for cooking such as charcoal and firewood in Tanzania, CEMs such as LPG, have emerged as complements or alternatives in the household energy basket. The utilisation of such CEMs is, however, still very low despite the accessibility, cost, environmental and health advantages they offer. Accessibility is not the only factor fuelling CEMs; a complementarity must exist between SES and income for the positive transition towards CEMs to be realised.

The supply chain (SC) of the fast-moving consumer goods (FMCG) sector in India witnessed a significant change soon after introducing the Goods and Services Tax (GST). With the initiation of this tax, companies started moving from individual state-wise warehouses to consolidation warehouses model to save costs. This paper proposes a model that frames a mathematical formulation to optimize the distribution network in the downstream SC by considering the complexities of multi-product lines, multi-transport modes and consolidated warehouses.

The model is designed as mixed-integer linear programming (MILP), and an algorithm is developed that works on the feedback loop mechanism. It optimizes the transportation and warehouses rental costs simultaneously with impact analysis.

Total cost is primarily influenced by the critical factor transportation price rather than the warehouse rent. The choice of warehouses at prime locations was a trade-off between a lower distribution cost and higher rent tariffs.

The study enables FMCG firms to plan their downstream SC efficiently and to be in line with the recent trend of consolidation of warehouses. The study will help SC managers solve complexities such as multi-product categories, truck selection and consolidation warehouse selection problems and find the optimum value for each.

The issues addressed in the proposed work are transporting products with different sizes and weights, selecting consolidated warehouses, selecting suitable vehicles for transportation and optimizing distance in the distribution network by considering consolidated warehouses.

The purpose of this paper is to study the aerodynamic characteristics of Ahmed body in longitudinal and lateral platoons under crosswind by computational fluid dynamics simulation. It helps to improve the aerodynamic characteristics of vehicles by providing theoretical basis and engineering direction for the development and progress of intelligent transportation.

A two-car platoon model is used to compare with the experiment to prove the accuracy of the simulation method. The simplified Ahmed body model and the Reynolds Averaged N-S equation method are used to study the aerodynamic characteristics of vehicles at different distances under cross-winds.

When the longitudinal distance x/L = 0.25, the drag coefficients of the middle and trailing cars at β = 30° are improved by about 272% and 160% compared with β = 10°. The side force coefficients of the middle and trailing cars are increased by 50% and 62%. When the lateral distance y/W = 0.25, the side force coefficients of left and middle cars at β = 30° are reduced by 38% and 37.5% compared with β = 10°. However, the side force coefficient of the right car are increased by about 84.3%.

Most of the researches focus on the overtaking process, and there are few researches on the neat lateral platoon. The innovation of this paper is that in addition to studying the aerodynamic characteristics of longitudinal driving, the aerodynamic characteristics of neat lateral driving are also studied, and crosswind conditions are added. The authors hope to contribute to the development of intelligent transportation.

This study reduces carbon emission in logistics distribution to realize the low-carbon site optimization for a cold chain logistics distribution center problem.

This study involves cooling, commodity damage and carbon emissions and establishes the site selection model of low-carbon cold chain logistics distribution center aiming at minimizing total cost, and grey wolf optimization algorithm is used to improve the artificial fish swarm algorithm to solve a cold chain logistics distribution center problem.

The optimization results and stability of the improved algorithm are significantly improved and compared with other intelligent algorithms. The result is confirmed to use the Beijing-Tianjin-Hebei region site selection. This study reduces composite cost of cold chain logistics and reduces damage to environment to provide a new idea for developing cold chain logistics.

This study contributes to propose an optimization model of low-carbon cold chain logistics site by considering various factors affecting cold chain products and converting carbon emissions into costs. Prior studies are lacking to take carbon emissions into account in the logistics process. The main trend of current economic development is low-carbon and the logistics distribution is an energy consumption and high carbon emissions.

A model for calculating the global overpressure time history of a single cloud detonation from overpressure time history of discrete positions in the range of single cloud detonation is to be proposed and verified. The overpressure distribution produced by multiple cloud detonation and the influence of cloud spacing and fuel mass of every cloud on the overpressure distribution are to be studied.

A calculation method is used to obtain the global overpressure field distribution after single cloud detonation from the overpressure time history of discrete distance to detonation center after single cloud detonation. On this basis, the overpressure distribution produced by multi-cloud under different cloud spacing and different fuel mass conditions is obtained.

The results show that for 150 kg fuel, when the spacing of three clouds is 40 m, 50 m, respectively, the overpressure range of larger than 0.1 MPa is 5496.48 mˆ2 and 6235.2 mˆ2, which is 2.89 times and 3.28 times of that of single cloud detonation. The superposition effect can be ignored when the spacing between the three clouds is greater than 60 m. In the case of fixed cloud spacing, once the overpressure forms continuous effective superposition, the marginal utility of fuel decreases.

A model for calculating the global overpressure time history of a single cloud detonation from overpressure time history of discrete positions in the range of single cloud detonation is proposed and verified. Based on this method, the global overpressure field of single cloud detonation is reconstructed, and the superimposed overpressure distribution characteristics of three cloud detonation are calculated and analyzed.

Recently, electric vehicles have been widely used in the cold chain logistics sector to reduce the effects of excessive energy consumption and to support environmental friendliness. Considering the limited battery capacity of electric vehicles, it is vital to optimize battery charging during the distribution process.

This study establishes an electric vehicle routing model for cold chain logistics with charging stations, which will integrate multiple distribution centers to achieve sustainable logistics. The suggested optimization model aimed at minimizing the overall cost of cold chain logistics, which incorporates fixed, damage, refrigeration, penalty, queuing, energy and carbon emission costs. In addition, the proposed model takes into accounts factors such as time-varying speed, time-varying electricity price, energy consumption and queuing at the charging station. In the proposed model, a hybrid crow search algorithm (CSA), which combines opposition-based learning (OBL) and taboo search (TS), is developed for optimization purposes. To evaluate the model, algorithms and model experiments are conducted based on a real case in Chongqing, China.

The result of algorithm experiments illustrate that hybrid CSA is effective in terms of both solution quality and speed compared to genetic algorithm (GA) and particle swarm optimization (PSO). In addition, the model experiments highlight the benefits of joint distribution over individual distribution in reducing costs and carbon emissions.

The optimization model of cold chain logistics routes based on electric vehicles provides a reference for managers to develop distribution plans, which contributes to the development of sustainable logistics.

In prior studies, many scholars have conducted related research on the subject of cold chain logistics vehicle routing problems and electric vehicle routing problems separately, but few have merged the above two subjects. In response, this study innovatively designs an electric vehicle routing model for cold chain logistics with consideration of time-varying speeds, time-varying electricity prices, energy consumption and queues at charging stations to make it consistent with the real world.

The Uppsala internationalization model is one of the widely accepted models for the development of exports. This model suggests that the explanation of relations between psychic distance, its antecedents and marketing mix adaptation would lead to successful export practices. Consequently, this study aims to determine the determinants of export performance, antecedents of psychic distance and marketing mix adaptation.

This study uses a mixed-methods research design in which qualitative and quantitative research methods were used together. The face-to-face interview method was used to identify the psychic distance antecedents. The face-to-face interview was with eight Turkish exporting firms. Based on the data obtained from face-to-face interviews, a scale for measuring the antecedents of psychic distance has been developed and used in the quantitative study. The scales used for measuring marketing mix adaptation, export performance and psychic distance perception, which has both individual and country dimensions, were adapted from the literature. Data were collected from 221 Turkish exporting companies for quantitative research. Structural equation modeling was used to test relationships between the variables.

As a result of the data analysis of face-to-face interviews, six antecedents of psychic distance were determined. According to the subsequent quantitative research results, it has been determined that employee expertise, which is one of the antecedents of psychic distance, only affects the country dimension of psychic distance perception; the cooperation, institutionalization and international market experience affect both the country and individual dimensions of psychic distance perception. The country and individual dimensions of psychic distance were found to have an impact on the product, price, promotion and distribution dimensions of marketing mix adaptation. Only the product dimension of marketing mix adaption was found to affect export performance.

This study offers a comprehensive perspective for both theoretical and practical studies by discussing various aspects that would help improve the exporting activities of firms within the scope of antecedents of perceived psychic distance.

In this research, a scale was developed for measuring the antecedents of psychic distance, and the variables affecting export performance were analyzed holistically.

Wafer bonding is a key process for 3 D advanced packaging of integrated circuits. It requires very high accuracy for the wafer alignment. To solve the problems of large movement stroke, position calibration error and low production efficiency in optical alignment, this paper aims to propose a new wafer magnetic alignment technology (MAT) which is based on tunnel magneto resistance effect. MAT can realize micro distance alignment and reduces the design and manufacturing difficulty of wafer bonding equipment.

The current methods and existing problems of wafer optical alignment are introduced, and the mechanism and realization process of wafer magnetic alignment are proposed. Micro magnetic column (MMC) marks are designed on the wafer by the semiconductor manufacturing process. The mathematical model of the space magnetic field of the MMC is established, and the magnetic field distribution of the MMC alignment is numerically simulated and visualized. The relationship between the alignment accuracy and the MMC diameter, MMC remanence, MMC thickness and sensor measurement height was studied.

The simulation analysis shows that the overlapping double MMCs can align the wafer with accuracy within 1 µm and can control the bonding distance within the micrometer range to improve the alignment efficiency.

Magnetic alignment technology provides a new idea for wafer bonding alignment, which is expected to improve the accuracy and efficiency of wafer bonding.