The study explores improving opportunities of forecasting accuracy from the traditional method through advanced forecasting techniques. This enables companies to optimize inventory management, production planning, and reducing the travelling time thorough vehicle route optimization. The article introduced a holistic framework by deploying advanced demand forecasting techniques i.e., AutoRegressive Integrated Moving Average (ARIMA) and Recurrent Neural Network-Long Short-Term Memory (RNN-LSTM) models, and the Vehicle Routing Problem with Time Windows (VRPTW) approach. The actual milk demand data came from the company and two forecasting models, ARIMA and RNN-LSTM, have been deployed using Python Jupyter notebook and compared them in terms of various precision measures. VRPTW established not only the optimal routes for a fleet of six vehicles but also tactical scheduling which contributes to a streamlined and agile raw milk collection process, ensuring a harmonious and resource-efficient operation. The proposed approach succeeded on dropping about 16% of total travel time and capable of making predictions with approximately 2% increased accuracy than before.

This paper reviews the emerging potential of mid-tier transit, articulating how a complex set of established and new factors could contribute both to better transit outcomes and the associated urban regeneration around station precincts. The analysis is based on two structured literature reviews, supported by insights from the authors’ original research. The first provides an overview of the established and new rationale for mid-tier technologies such as the established Light Rail Transit (LRT) and Bus Rapid Transit (BRT) as well as the new Trackless Tram Systems (TTS). The established role for mid-tier transit is now being given extra reasons for it to be a major focus of urban infrastructure especially due to the need for net zero cities. The second review, is a detailed consideration of established and new factors that can potentially improve patronage on mid-tier transit. The established factors of urban precinct design like stop amenities and improved accessibility and density around stations, are combined with new smart technology systems like advanced intelligent transport systems and real-time transport information for travellers, as well as new transport technologies such as micro-mobility and Mobility on Demand. Also explored are new processes with funding and development models that properly leverage land value capture, public private partnerships, and other entrepreneurial development approaches that are still largely not mainstreamed. All were found to potentially work, especially if done together, to help cities move into greater mid-tier transit.

The concept of sustainable urban mobility has gained increasing attention in recent years due to the challenges posed by rapid urbanization and environmental degradation. The objective of this study is to explore the role of on-demand transportation in promoting sustainable urban mobility, incorporating insights from customer interests and demands through survey analysis. To fulfill this objective, a mixed-methods approach was employed, combining a systematic literature review with survey analysis of customer interests and demands regarding on-demand transportation services. This study combines a systematic literature review and a targeted survey to provide a comprehensive analysis of sustainable urban mobility, addressing gaps in understanding customer preferences alongside technological and financial considerations. The literature review encompassed various aspects including technological advancements, regulatory frameworks, user preferences, and environmental impacts. The survey analysis involved collecting data on customer preferences, satisfaction levels, and suggestions for improving on-demand transportation services. The findings of the study revealed significant insights into customer interests and demands regarding on-demand transportation services. Analysis of survey data indicated that factors such as convenience, affordability, reliability, and environmental sustainability were key considerations for customers when choosing on-demand transportation options. Additionally, the survey identified specific areas for improvement, including service coverage, accessibility, and integration with existing transportation networks. By providing flexible, efficient, and environmentally friendly transportation options, on-demand services have the potential to reduce congestions, improve air quality, and enhance overall urban livability.

The Mass Rapid Transit (MRT) Purple Line project is part of the Thai government’s energy- and transportation-related greenhouse gas reduction plan. The number of passengers estimated during the feasibility study period was used to calculate the greenhouse gas reduction effect of project implementation. Most of the estimated numbers exceed the actual number of passengers, resulting in errors in estimating greenhouse gas emissions. This study employed a direct demand ridership model (DDRM) to accurately predict MRT Purple Line ridership. The variables affecting the number of passengers were the population in the vicinity of stations, offices, and shopping malls, the number of bus lines that serve the area, and the length of the road. The DDRM accurately predicted the number of passengers within 10% of the observed change and, therefore, the project can help reduce greenhouse gas emissions by 1289 tCO₂ in 2023 and 2059 tCO₂ in 2030.

In recent years, enological tourism, also known as wine tourism, has emerged as a globally popular tourism product. The role of wine tourism in Slovakia is similarly significant, given the country’s favourable conditions for the development of wine tourism products. The objective of this study is to analyze the current demand for wine-themed experiences among tourists in the Nitra region. This paper presents a characterization of wine tourism based on an analysis of secondary sources. Following the processing of the initial findings from a demand-oriented questionnaire survey, the authors endeavor to delineate the profile of the wine tourism visitor by examining the demand for wine tourism from the vantage point of domestic consumers. It is the authors’ contention that an understanding of the profile of the wine tourism visitor is beneficial in optimising the provision of wine tourism products and stimulating the development of tourism infrastructure.

Although various actors have examined the user acceptance of e-government developments, less attention has so far devoted to the relationship between attitudes of certain commuter groups against digital technologies and their intention to engage in productive time-use by mobile devices. This paper aims to fill this gap by establishing an overall framework which focuses on Hungarian commuters’ attitudes toward e-government applications as well as their possible demands of developing them. Relying on a representative questionnaire survey conducted in Hungary in March and April 2020, the data were examined by a machine learning and correlations to identify the factors, attitudes and demands that influence the use of mobile devices during frequent commuting. The paper argues that the regularity of commuting in rural areas, as well as the higher levels of qualification and employment status in cities show a more positive, technophile attitude to new ICT and mobile technologies that strengthen the demands for digital development, with special regard to optimising e-government applications for certain types of commuting groups. One of the main limitations of this study is that results suggest a picture of the commuters in a narrow timeframe. The findings suggest that developing e-government applications is necessary and desirable from both of the supply and demand sides. Based on prior scholarly knowledge, no research has ever analysed these correlations in Hungary where commuters are among the European citizens who spend extensive time with commuting.