Transportation Costs Research Articles

The multidimensional spectrum of eco-evolutionary relationships between sharks and remoras.

Remoras are a highly specialised group of fishes known to associate with a range of marine megafauna, including elasmobranchs, cetaceans and marine reptiles. Remoras appear to benefit from these interspecific interactions through consumption of host dermal parasites or reduced cost of transport. Shark-remora associations are widely documented, yet our understanding of the costs and benefits involved in these interactions is poor. Studies frequently make claims about mutualistic, commensalistic or parasitic relationships without providing the necessary quantitative information necessary to make these claims. Here I explain why this approach is problematic, and proceed to examine shark-remora interactions in a rigorous eco-evolutionary framework. These interactions cannot be properly classified without considering net evolutionary fitness and context dependence. In reality, shark-remora interactions are best defined by a multidimensional spectrum of fitness consequences, with net fitness outcomes shifting between mutualism and parasitism (and vice versa) through space and time.

Unveiling energy security in agriculture through vital indicators extraction and insights

Despite advancements in meeting various human needs, energy supply remains a top priority for all countries worldwide. The escalating energy consumption in the agricultural sector underscores the necessity to scrutinize its energy usage. Presently, there exists an absence of a precise tool for accurately measuring this consumption. Hence, this study aims to identify indicators for measuring energy security in agriculture, conducted in three phases: content analysis, indicator validation, and field investigation. In the content analysis phase, energy security indicators were extracted and grouped into four categories: accessibility, availability, utilization, and sustainability. Following this, a two-stage validation process led to the identification of 18 indicators for assessing energy security in agriculture. In the field phase, a tailored questionnaire was distributed to 160 randomly selected farmers. The findings revealed that the availability component held the highest rank in establishing energy security, with an average score of 3.31. However, the current status of the access component indicates a more unfavorable situation compared to other dimensions. Consequently, to achieve energy security in agriculture, particular emphasis should be placed on enhancing energy access. Key areas to address include reducing transportation costs and minimizing the use of chemical pesticides. This indicates a necessity for focused interventions aimed at improving both energy access and sustainability within the agricultural sector. These efforts would contribute to enhancing economic efficiency and promoting environmental conservation.

Chabahar Port: A Geopolitical Need Or, Economic Compulsion for India

In the year 2024, in the case of Chabahar port in Iran, two important events took place; first, the visit of Mr. S Jaishankar, India’s External Affairs Minister to Tehran in January 2024 and second, one is the terror attack on Chabahar port by Jaish-al-Ahad on 3 April 2024. Both these developments are pole apart as far as the development of Chabahar port and the realisation of The International North-South Transportation Corridor (INSTC) is concerned. The first one talks about development, hope, connectivity, and the future of trade through a new corridor and the second one is about the existing security challenges in the region which has put this project on a slow grind since the year 2002. As we are aware the International North-South Transportation Corridor (INSTC) is a multi-modal transportation network connecting India, Iran, Russia, Central Asia, and Europe. It aims to facilitate the movement of goods and reduce transportation costs by providing an alternative route to traditional sea routes. The Chabahar Port, located in southeastern Iran, plays a crucial role in the INSTC as a key maritime gateway.

Role of China-Pak Economic Corridor (CPEC) in Logistic System of Pakistan's and China's

This study will explain the impact of China-Pak Economic Corridor (CPEC) on logistic system of China and Pakistan. This project is estimated investment of US $90 billion, CPEC project is consists of various sub-projects including energy, road, railway and fiber optic cable but major portion will be spent on energy. This project will start from Kashgar port of china to Gwadar port of Pakistan. Transportation is sub-function of logistic that consists of 44% total cost of logistic system and 20% total cost of production of manufacturing and mainly shipping cost and transit/delivery time are critical for logistic system. According to OEC (The Observing Economic Complexity) currently, china is importing crude oil which 13.4% from Persian Gulf. CPEC will china for lead time that will be reduced from 45 days to 10 days and distance from 2500km to 1300km. This new route will help to china for less transit/deliver time and shipping cost in terms of logistic of china. Pakistan’s transportation will also improve through road, railway and fiber optic cabal projects from Karachi-Peshawar it will have speed 160km per hour and with help of pipeline between Gwadar to Nawabshah gas will be transported from Iran. According to (www.cpec.inf.com) Pakistan logistic industry will grow by US $30.77 billion in the end of 2020.

Strategic Behavior of Competitive Local Citizen Energy Communities in Liberalized Electricity Markets

The liberalization of energy retail markets empowered consumers with the ability to be part of new emerging entities, such as Citizen Energy Communities. With the increasing penetration of decentralized variable generation, communities have the advantage of incentive local carbon neutrality and sustainability. Local generation reduces transport grid usage and costs to consumers. Furthermore, worldwide legislation incentives energy communities by providing them discounts to other fee parts of the tariff apart from wholesale prices. This paper presents a model of strategic behavior, investment, and trading of energy communities. The model comprises the investment in local renewable generation, the design of competitive tariffs, and strategic bidding on wholesale markets. Consumers have an optimization model that selects the retail tariff that minimizes their costs with energy. These models are tested using data from Portuguese consumers and the Iberian electricity market. Results from the study indicate that inflexible consumers may reduce their costs by 29% by being part of the community. Furthermore, they have the potential to reduce their costs above 50% when using demand–response, adapting themselves to local production and wholesale prices.

Constraints Faced by the Farmers in Production and Marketing of Cauliflower in Haryana, India

Cauliflower (Brassica oleracea var. Botrytis) is one of the most important remunerative vegetable crops grown on commercial scale in India. It is widely grown across India and is a popular vegetable among the people. It is known for its white, tender head or curd, which is used in curries, soups, and for pickling. Cauliflower is a crucial winter vegetable grown in India. A survey was conducted among a group of cauliflower growers to understand the challenges they encounter during cauliflower production and marketing. The objective of the study was to identify the production and marketing constraints faced by the cauliflower growers. Panipat and Sonipat districts were purposively selected due to their significant cauliflower cultivation areas in the state. A total of 200 cauliflower growers were conveniently chosen to gather the necessary data. In Panipat and Sonipat district, the study revealed that the major constraints in cauliflower production included the high cost of cauliflower seeds, expensive fertilizers, labour scarcity during peak periods, and other similar challenges. In terms of cauliflower marketing, respondents reported multiple constraints such as high transportation costs, numerous intermediaries in the marketing process, price fluctuations, lack of awareness about the Bhavantar Bharpayee Yojana (BBY) and its complex procedures, and the higher margins of middlemen. To address these constraints, it is recommended to establish sufficient storage facilities that enable producers to distribute their sales throughout the year. Efforts should be made to ensure the availability of quality seeds and protect producers from experiencing low prices during peak seasons.

Kamchatka Berry (Lonicera caerulea L.) Pomace Bioferment as an Innovative Cosmetic Raw Material

Kamchatka berries (Lonicera caerulea L.) are known for their high content of phenolic compounds or vitamins, which is reflected in their antibacterial, detoxifying and anti-inflammatory properties. They are used in the production of jams, juices, wines and as natural dye. A bioferment was prepared from the pomace of the Kamchatka berry varieties Aurora and Indigo Gem and the strains Saccharomyces cerevisiae and Lacticaseibacillus paracasei, which was used to prepare a cosmetic preparation with a concentration of 5% in accordance with the guidelines of the COSMOS certification body. We conducted physico-chemical and organoleptic analyses and bioactive profile characterisation (UHPLC-DAD and UHPLC-ESI-MS/MS). The results showed that the presence of caffeic acid (4.47 ± 0.07 mg/100 g) was detected after fermentation of Kamchatka berry pomace. In addition, vitamin C content increased by 141% after fermentation. The results of stability tests showed that in the process of physico-chemical analysis of the cosmetic preparation with bioferment of Kamchatka berry pomace, the pH should oscillate in the range of 4.38–4.76 ± 0.01. Stability tests showed that the cosmetic should be protected from high temperatures and UV radiation and proved that the product is stable under changing conditions, resulting in lower transport and storage costs.

An empirical study of the impact of COVID‐19 on container freight rates: Evidence from the panel data of China

AbstractThe container shipping industry has undergone significant changes in the post‐COVID‐19 era. This study examines the impact of the pandemic on container freight rates (CFR) through a demand analysis approach, using 11 major international container trade lanes from Shanghai, China as a case study. We analyze the CFR data on both weekly and monthly bases, with a focus on retaining more individual and time information using long panel data. To better reveal the pandemic's impact on CFR, we introduce interactive terms and simultaneous equations in our model. Our empirical analysis shows that the pandemic has not only directly and positively affected CFR, but, more importantly, has also indirectly promoted the growth of container shipping cost by stimulating the demand for containerized goods exported from China. Additionally, the connectivity or capacity of a given trade lane has inhibited the pandemic's effects on CFR to a certain extent. These findings provide insights into the remarkable growth of CFR from the demand side in 2020.

Assessing Maternal Management of Childhood Illnesses in Anaocha Local Government Area, Anambra State: A Study of Home-Based Practices and Strategies

Background: Children under 5 years are especially vulnerable to infectious diseases like malaria, pneumonia, diarrhea, HIV, and tuberculosis which are also the major causes of death among this age group. In this study, the three most common under 5 illnesses will be studied which are malaria, pneumonia, and diarrhea. Objectives: To ascertain the home management of childhood illness among mothers in Anaocha local government area of Anambra state. Methodology: This cross-sectional study was conducted among women and data collected using pretested interviewer administered questionnaire among 320 respondents. Results were analyzed using SPSS 25.0. Results: A total of 320 women were interviewed. Their mean age was 28.40±6.07 years, more than half of the respondents were within the age range of 20-29 years. Respondents who had heard about these illnesses before the study were 99.4%, 62.5% and 80.9% for malaria, pneumonia, and diarrhoea respectively. Majority of the respondents had good knowledge of symptoms of childhood illness, 222(69.4%) with an average knowledge score of about 56.4±21.0%. The relationship between educational level of mothers and preventive measure was statistically significant but there was no association between age and preventive measures. The prevalence of home management of the different childhood illnesses was 0.90, 0.81 and 0.36 for malaria, diarrhoea and pneumonia respectively. More than two-third of the respondents visited the hospital to seek for external assistance. The factors identified to cause delays in seeking medical care include cost of health care, 178(55.6%); and transportation, 159(49.7%). With respect to age, highest educational level attained, occupation of mothers and their relationship to visiting the hospital within 24hours of onset of illness, there was significant association with a p-value <0.05. Conclusion: It was found that mothers were able to recognise symptoms of childhood illnesses. Misconceptions about .............

Turkish cashier problem with time windows and its solution by matheuristic algorithms

Turkish Cashier Problem (TCP) is a new application area of the traveling salesman problem that was introduced to the literature recently. In this problem, the cashier can use public transportation or take a taxi where the cashier must visit multiple customer locations while minimizing the total transportation cost. In this study, we introduce a more realistic version of this problem where time has been integrated. This aspect is achieved by imposing time intervals within which the cashier must visit the customers. We name this problem as the TCP with time windows (TCPwTW). We develop several matheuristic algorithms to solve the TCPwTW: a modified version of the Simplify and Conquer (SAC) algorithm that was suggested for the TCP, simulated annealing (SA), original and modified versions of the migrating birds optimization (MBO) algorithm coupled with mathematical programming. We also tried to find the exact optimum using a Solver where for complex problems, only lower bounds were found. Numerical experimentation reveals that while for problems with loose time intervals, an exact solver can be considered. Once the time intervals tighten up, the best solutions can be obtained using matheuristics involving SA and MBO.

Optimal ordering quantity by retailer from supplier with transportation cost in a supply chain

Successful retailer-supplier collaborative relationship enhance profitability in the delivery of products or services to customers in a supply and can help alleviate pressures along all key points in the supply system. A strong alliance can bring products to market faster; reduce production and logistics costs, drive market shares, and increase sales, while maximizing profit for both partners. The success of fast-moving consumer goods from the suppliers has a direct relationship with the performance of the leading retailers, which are their main channel of distribution. The objective of this study was to establish a profit model between a single supplier and multiple supply chain collaboration that will enhance response to customer requirements. We considered the costs for various parties and use a referenced simplified framework model to obtain joint optimal pair for the outcome of coordination between the retailer and supplier. Our results showed that the value of the annual cost, with the same optimal ordering quantity, is higher when the retailer incurs transportation cost than when the supplier incurs transportation cost. This study revealed that the supplier will minimize cost when incurring transportation charges and maximize profit.

Wireless Electric Vehicle Charging with Solar Panels

This paper presents an innovative design of a solar-powered electric vehicle (EV) charging station and addresses critical issues of fuel consumption and environmental pollution. With the global spread of electric cars, their environmental benefits and cost-effectiveness are increasingly recognized. The proposed electric car charging system offers a unique solution that enables wireless charging of vehicles without stopping and even while driving. The system runs entirely on solar power, so no external power source is needed. The report describes the design and engineering of a solar-powered electric car charger for built-in roads that provides a novel and efficient solution to two challenges. fuel consumption and emissions. The number of countries where electric cars are on the road is constantly growing. In addition to helping the environment, electric cars have proven useful in reducing transportation costs by replacing expensive fuels with cheaper electricity. The proposed electric vehicle charging infrastructure structure eliminates the need to stop for charging, as the electric vehicle can be charged on the go. The system runs on solar energy, which eliminates the need for an additional power source. This research will contribute to ongoing efforts to make electric car charging more efficient and environmentally friendly. Keywords: Electric Vehicle, Wireless Charging, Solar Panels, Arduino Uno, Transmitter and Receiving Coils, LCD display, wireless Power Transfer

Low-Carbon Logistics Distribution Vehicle Routing Optimization Based on INNC-GA

In order to tackle the issue of carbon emissions in logistics and distribution, a vehicle routing model was proposed with the aim of minimizing the overall cost, which includes the vehicle’s fixed cost, transportation costs, and carbon emission costs. An enhanced genetic algorithm, based on a modified Nearest Neighbor Construction (NNC) method, was developed to solve this model. A comparative analysis was conducted using the Solomon dataset to study the impact of carbon emissions on vehicle routing optimization, comparing scenarios with and without considering carbon emission costs. The research findings revealed that the Improved NNC (INNC) method exhibited faster convergence compared with the random generation and random insertion methods. Despite a slight increase of 0.5127% in transportation cost when factoring in carbon emission costs, there was a decrease of 4.6914% in carbon emission costs and 0.3578% in total cost. These results offer theoretical insights and empirical evidence to inform the development of models for the logistics industry in the context of a low-carbon economy.

Development of Transportation Modes in Basra Sanjak: 1945-1958

Land transportation is the oldest means used by humans to transport various goods. This method has evolved over the centuries to what we see today in the use of trucks of various types in transportation operations. Truck transportation is considered the best type of transportation in various countries of the world. If money is the lifeblood of the economy, then transportation in its various forms and means, such as water transportation (maritime and riverine), air transportation, and land transportation (rail and truck), is considered the lifeblood of the economy at all times. It is considered a necessity for development and a support for foreign trade and tourism activities. It is a link between different countries of the world. Several laws have been enacted and many international agreements have been concluded to regulate the work of these means. Therefore, land transportation is of great importance in Iraq in general and Basra in particular, due to its distinguished geographical location, as well as the low cost of land transportation compared to other means of transportation. The research was divided into three sections. The first section dealt with land roads, railways, the Public Transport Authority, and the bus project. The second section dealt with river transport, and the third section dealt with air traffic. 

Customer Recognition and Mobile Geo-Targeting

AbstractWe consider competing mobile marketers that complement geo-targeting with behavior-based pricing and send personalized offers to customers. Firms observe consumers’ locations and can infer their (heterogeneous) responsiveness to discounts from purchase histories. The overall profit effect of behavioral targeting is driven by firms’ discount factor and consumers’ transport cost and can be neutral, positive, or negative. We are the first to show that the profitability of behavioral data may depend on firms’ time preferences. We derive conditions for when firms prefer more rather than less behavioral targeting.

Enhancing Multi-Channel Consumer Behavior Analysis: A Data-Driven Approach using the Optimized Apriori Algorithm

Purpose –In the dynamic arena of retail and e-commerce, understanding customer behavior is crucial. This research paper investigates the strategies customers use to balance convenience and cost. It notes that consumers often divide their purchases, choosing online platforms for items they perceive as reasonably priced, while preferring physical stores for products associated with high shipping costs, lack of express shipping, or higher online prices. Traditional retail analysis methods, such as identifying frequently purchased and co-occurring items, are critical to the sector. However, these insights may be skewed if the analysis is solely confined to the online shopping cart, neglecting related purchases made at physical stores either before or after the online transaction. This paper addresses this analytical gap by looking into the complex interplay between online and offline purchases. The objective is to provide a more comprehensive, detailed understanding of multi-channel shopping behaviors, allowing retailers to better cater to their customers' needs and preferences while optimizing their strategies for a more effective market presence. This comprehensive approach attempts to uncover deeper insights into the interactions between online and offline purchases, thereby contributing to a more comprehensive understanding of consumer behavior in the retail and e-commerce industries.
 Design/methodology/approach- A detailed survey questionnaire was administered, obtaining 2465 responses. The questionnaire was specifically designed to capture the complexities of online and offline purchases, with an emphasis on Apple's purchase channels. The Apriori algorithm was used twice to find frequently co-occurring items that were purchased online and then online clubbed with offline. Essential metrics like support and confidence were calculated for both online and offline purchases. To determine any significant differences between the groups, an independent-samples t-test was used. This comprehensive methodology ensures a thorough examination of multi-channel shopping behaviors, providing valuable insights into consumer behavior in the retail and e-commerce sectors.
 Findings–We find that cross channel switching in a multi-channel distribution environment occurs due to price differences, convenience and flexibility. The paper illustrates the flaws of drawing inferences with data from a single channel emphasizing the need for a more holistic, multi-channel approach to data analysis in order to capture the full range of consumer behavior.
 Research limitations/implications –
 This study assumes that self-reported purchases or acquisitions of products accurately reflect actual consumer behavior. The insights derived from this research have significant implications for various marketing strategies, including pricing, product bundling, cross-selling, and promotional activities. However, it’s important to note that the reliance on self-reported data may introduce certain limitations, as it may not fully capture the complexity of actual consumer behavior. Despite these limitations, the insights gained from the study will add value for several marketing decisions like pricing, bundling, cross-selling and promotions.
 Originality value– While there is an abundance of literature on the application of Association Rule Mining for Market Basket Analysis, the existing body of work exploring its application within a multi-channel context is notably sparse. This study aims to address this gap in the literature, offering a unique perspective and making a substantial contribution to the existing body of knowledge in this area.

An integrated causal framework to evaluate uplift value with an example on change in public transport supply

Many empirical applications aim to isolate the impact of implementing new public transport on real estate uplift value. While their conclusions generally point to positive impact, due to reduction in transportation cost, the methodological framework to investigate uplift value has largely evolved over time. This paper reviews the different methodological challenges in measuring causal uplift value and proposes an adjusted parametric approach inspired from the Alonso-Muth-Mills model, returning a complex 2-D price premium function allowing for spatial heterogeneous patterns of the average treatment effect. The proposed framework also accounts for other methodological challenges underlined by literature such as spatial autocorrelation, selectivity and representativity issues, and possible anticipation effects. To illustrate the importance of methodological choices on estimation results, the framework is applied to the case of the implementation of a bus rapid transit (BRT) system in Québec City, a medium-size Canadian city, as a specific case study.

Optimal Transportation Planning for a Do-It-Yourself Retailer with a Zone-Based Tariff

This article describes the development of a decision support tool for a Rich Vehicle Routing Problem (R-VRP) of a major European do-it-yourself (DIY) retailer. The tool enables more comprehensive and structured planning at the retailer and an average of 8% transportation cost savings, translating to total savings of more than € 1 million per year for this specific retailer compared with the status quo.

Sustainable urban farming using a two‐phase multi‐objective and multi‐criteria decision‐making approach

AbstractFor several reasons, recent attention has focused on urban agriculture in the context of sustainable and smart agriculture. Most of the global population has relocated from rural to urban areas. The ecological impact of agriculture is a rising concern. Furthermore, food insecurity, particularly food availability, remains a significant issue. Satisfying rising food demand with minimal environmental impact is a significant barrier to more sustainable food production. In this article, we study a sustainable location for urban farming that optimally balances economic and environmental objectives. We formulate the problem as a multi‐objective linear program that considers maximizing the ecological benefit and crop production yield and minimizing transportation cost, sensor cost, and CO2 emissions. The proposed mathematical model is then solved using a two‐phase method. The first phase uses several multi‐objective optimization (MOO) methods (weighted sum, epsilon‐constraint, augmented epsilon) to generate a pool of compromise solutions. The second phase uses multi‐criteria decision‐making (MCDM) methods (MARCOS, VIKOR, and Possibility Degree) to rank compromise solutions. We performed a sensitivity analysis first by studying the effect of different criteria weights (balanced, environmentally, and economically oriented) and then by investigating the rank reversal. Furthermore, we developed a thorough validity test that examines the impact of the dynamic elements of rank reversal by changing the importance of the model's input parameters. To provide a fusion ranking of the MCDM rankings, we devised an aggregated ranking approach using the half‐quadratic (HQ) method.

Fourth Party Logistics Routing Problem Under Uncertain Time and Random Demand

With the rapid development of the economy, the fourth party logistics (4PL) has become an indispensable part of economic development, and the path optimization is an important topic in the research of 4PL routing problem. This paper studies the fourth party logistics routing problem with random demand and uncertain transportation time and transfer time by considering the randomness and uncertainty of the environment. In order to solve the path optimization strategy that minimizes the total transportation cost, this paper establishes an uncertain random programming model under the constraints of the total transportation time, the carrying capacity of the logistics provider, the transfer capacity of the transfer station, and the demand of the distributor. Subsequently, this paper transforms the uncertain random programming model into an equivalent deterministic programming model based on the distribution functions of random demand and uncertain time, and verifies the effectiveness of the model through two examples. The results show that the uncertain random programming model can give a reasonable path optimization strategy.