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To improve the use experience of airport chairs, this study adopted morphological analysis to conduct systematic deconstruction, analysis, and statistics on the modeling features of existing airport chairs. The KJ method was used to determine the design requirements of airport chairs. The study combined the Kano model to classify the functional attributes and prioritize the requirements, and it merged the module and demand analysis to build a Function-Behavior-Structure mapping model. In this way, passengers’ demand for airport chairs can be clearly defined, and airport chair configuration planning can be carried out according to the difference in preferences. Further, different module combination schemes can be formed to improve the functional allocation efficiency of airport chairs, optimize the overall service quality of airports, and provide some basis and reference for the future design of airport chairs.

Virtual power plants （VPPs） represent a tangible implementation in the construction of modern power systems. Addressing the current challenges of limited applicable technical standards and a lag in the development of a standardized system for VPPs， this paper， based on the collection and organization of relevant standards， conducts a comprehensive analysis of the standardization status across various facets of VPPs， including basic general standards， planning and construction， operation and maintenance， supporting technologies， and energy efficiency assessments. Adopting both top-down and bottom-up approaches of system engineering and guided by the principles of directive， coordinating， systematic， and open VPP standard system construction， a system architecture has been designed. The architecture encompasses 15 subcategories and 52 standard series. Furthermore， based on a future demand analysis， key layout recommendations have been proposed to provide reference for the establishment and revision of VPP standards.

Abstract Promoting the shift from private cars to micromobility (e.g., bike, e-bike, scooter) can represent a valuable action to improve city sustainability and liveability. Micromobility can help to replace trips by individual private cars (e.g., daily short round trips) as well as to improve coverage and accessibility of transit services, and, subsequently, to reduce the traffic impacts (e.g., pollutant emissions). It can be seen as a potential solution to move people more efficiently in urban areas, as well as to push people towards a more active mobility behaviour, contributing to the well-being goals. In this context, the paper, rather than inferring the users’ propensity to change their travel mode, proposes a methodology to identify car trips that can be considered the most compatible with micromobility. Estimation of the potential demand (e.g., the upper level of car trips that could be replaced by micromobility) is carried out by exploiting the opportunity offered by floating car data (FCD) for characterising car trips. Its goodness is therefore evaluated through an application to a real case study (i.e., the city of Trani, Apulia Region, Southern Italy), divided into seventy traffic zones, and where a FCD dataset of about 5,200 trips was available. The FCD allowed the car trips to be characterised (e.g., origin and destination, path features) instead of using the traditional surveys. The results indicate that a significant share of daily car trips can be substituted (i.e., the most compatible) by micromobility (31% of car round trips in the case study), with considerable potential environmental gains (traffic emission reduction; less than 21% of total emissions from private cars). Results can be of interest to local authorities in integrating micromobility in urban mobility planning and promoting new sustainable transport alternatives, as well as to transport companies for designing new appeal services. The developed methodology is parametric and uses easy-to-obtain data available worldwide; thus, it can be easily transferred to other city contexts.

India is one of the world's largest producers of tree nuts, yet it paradoxically remains a net importer of these commodities. This study aims to analyze the demand for imported tree nuts in India, motivated by the need to understand the factors contributing to this imbalance. The primary objective is to calculate income elasticities and own- and cross-price elasticities for five categories of imported tree nuts using the linear approximate almost ideal demand system model. Data is sourced from monthly import records from the United Nations Comtrade database covering 2014 to 2022. The tree nuts considered are almonds, cashews, pistachios, walnuts, and hazelnuts. Key findings reveal all imported tree nuts are normal goods. Cashews exhibit income elasticity (1.2), indicating a significant demand increase with rising incomes, while other nuts show income inelasticity. Cashews are price-elastic (−1.3), while other nuts are price-inelastic. Compensated cross-price elasticities indicate notable substitution effects, particularly between almonds and cashews. The study recommends enhancing domestic cashew production to meet growing demand and developing targeted marketing strategies to address competitive dynamics within the tree nut market. These strategies aim to reduce India's dependency on imports and promote a balanced, sustainable domestic market.

This paper introduces an innovative methodology for conducting demand analysis within various domains across multiple countries, presenting insights derived from a comprehensive analysis conducted in seven distinct nations. The proposed methodology provides a systematic process for gathering, processing, and analyzing textual data to discern global talent demand within specified domains. Three fundamental steps characterize the methodology: identification of areas of interest, calculation of relative demand, and execution of analysis and forecasting. Areas of interest within the job market are pinpointed through a combination of manual curation and automated techniques, ensuring the inclusion of only pertinent job postings. Relative demand for jobs within each specified domain is then computed for each country, furnishing a standardized metric for cross-country comparisons. Subsequently, analysis and forecasting unveil trends and patterns in job demand, enabling stakeholders to anticipate shifts in the job market landscape. Application of this methodology to scrutinize demand analysis across seven countries - the US, Canada, the UK, France, India, Singapore, and Australia - reveals substantial variations in demand across diverse regions, along with correlations and instances of skill shortages. These findings offer invaluable insights for policymakers, businesses, and researchers, facilitating informed decision-making and fostering growth and innovation within the specified domains.

Rapid growth rate indicates that the free-floating electric vehicle sharing (FFEVS) system leads to a new carsharing idea. Like other carsharing systems, the FFEVS system faces significant regional demand fluctuations. In such a situation, the rental stations and charging stations should be constructed in high-demand areas to reduce the scheduling costs. However, the planning of the FFEVS system includes a series of aspects of rental stations and charging stations, such as the location, size, and number, which interact with each other. In this paper, we first provide a method for forecasting the demand for car sharing based on the land characteristics of Beijing FFEVS station catchment areas. Then, the multi-objective MILP model for planning FFEVS systems is developed, which considers the requirements of vehicle relocation and electric vehicle charging. Afterward, the capabilities of the proposed models are demonstrated by the real data obtained from Beijing, China. Finally, the sensitivity analysis of the model is made based on varying demand and subsidy levels. From the results, the proposed model can provide decision-makers with useful insights about the planning of FFEVS systems, which bring great benefits to formulating more rational policies.

Energy demand forecasting is crucial for effective resource management within the energy sector and is aligned with the objectives of Sustainable Development Goal 7 (SDG7). This study undertakes a comparative analysis of different forecasting models to predict future energy demand trends in Brazil, improve forecasting methodologies, and achieve sustainable development goals. The evaluation encompasses the following models: Seasonal Autoregressive Integrated Moving Average (SARIMA), Exogenous SARIMA (SARIMAX), Facebook Prophet (FB Prophet), Holt–Winters, Trigonometric Seasonality Box–Cox transformation, ARMA errors, Trend, and Seasonal components (TBATS), and draws attention to their respective strengths and limitations. Its findings reveal unique capabilities among the models, with SARIMA excelling in tracing seasonal patterns, FB Prophet demonstrating its potential applicability across various sectors, Holt–Winters adept at managing seasonal fluctuations, and TBATS offering flexibility albeit requiring significant data inputs. Additionally, the investigation explores the effect of external factors on energy consumption, by establishing connections through the Granger causality test and conducting correlation analyses. The accuracy of these models is assessed with and without exogenous variables, categorized as economical, industrial, and climatic. Ultimately, this investigation seeks to add to the body of knowledge on energy demand prediction, as well as to allow informed decision-making in sustainable energy planning and policymaking and, thus, make rapid progress toward SDG7 and its associated targets. This paper concludes that, although FB Prophet achieves the best accuracy, SARIMA is the most fit model, considering the residual autocorrelation, and it predicts that Brazil will demand approximately 70,000 GWh in 2033.

Objective To establish a comprehensive, scientific, and reasonable smart home automation system for patients with ischemic stroke and functional impairment by conducting a questionnaire survey on the requirements of a smart home automation system. Methods The researchers developed a questionnaire titled "Requirements of a smart home automation system for patients with ischemic stroke and functional impairment" to assess the specific needs of patients who suffered from ischemic stroke and were unable to live independently. A total of 100 patients participated in the survey. Results The results of the questionnaire survey involving 100 individuals revealed that only 43. 00%(43/100)of the respondents were familiar with intelligent home systems, and a mere 21. 00%(21/100)had previous experience with similar smart systems. When asked about their willingness to accept a smart home automation system that could be installed and customized to provide convenience in daily life, including monitoring vital signs and medication usage, as well as aiding in rehabilitation training, 46. 00%(46/100) of the participants expressed their willingness of acceptance. Further investigation revealed that complex operation, impractical function and expensive cost were main reasons behind the reluctance of the rest 54 individuals to accept the system. The respondents expressed the highest demand for the electronic medication box monitoring system, followed by the sleep monitoring system and the vital sign monitoring system. Conclusion The findings indicated that patients with ischemic stroke and functional impairment had limited awareness and acceptance of smart home automation system. In order to ensure that the implementation of this automation system provides tangible benefits to patients, it is crucial to enhance its functionality, actively promote awareness among the target population, and establish an effective foundation for subsequent clinical trials of the intelligent home management system software. (目的 调查脑梗死伴功能障碍患者对智慧居家管理模块的需求, 为进一步建立完善、科学、合理的智慧居家管理模块提供依据。方法 采用自拟“脑梗死伴功能障碍患者对智慧居家模块的需求”调查问卷, 选取2020年4月—2023年4月医院收治的100例脑梗死伴功能障碍中生活不能完全自理的患者进行调查。结果 43(43. 00%)例患者了解智慧居家系统, 但只有21(21. 00%)例患者使用过类似的智能系统。当被问及“有一个智慧居家管理系统, 可在现有居家电器、门、窗等基础上进行安装改造, 旨在为您解决居家不便、进行生命体征及服药监测、帮助您进行康复训练等, 是否愿意接受”时, 46(46. 00%)例患者表示愿意接受, 而不愿意接受的原因包括操作复杂、实用性低、价格昂贵。患者对智慧居家管理系统功能的需求程度排前三位的分别是电子药盒监测系统、睡眠监测系统和生命体征监测系统。结论 脑梗死伴功能障碍患者对于智慧居家模块的了解程度低、接受意愿较低; 应通过加强功能完善、积极宣传普及等措施, 为智慧居家管理系统软件后期投入临床试验提供有效基础, 确保智慧居家模块的实施能够给患者带来确切益处。)

Ethiopia is a country in East Africa experiencing significant economic growth in recent years, with an increasing electricity demand. Ensuring sustainable and efficient energy for newly developed industries and economic zones is crucial. In this study, a 15-year electric power demand forecast for the new economic zone under construction is conducted. The electrical power demand forecast is done for the year 2025–2040 by using bottom-up forecasting approach for three different scenarios. Long-range Energy Alternatives Planning (LEAP) system software is used to analyze residential, industrial, and general business sector electric power demand. The analysis of the assessed scenario shows that the economic zone's electric power demand increases by 52.2 % from the base year 2025–2040 for the baseline scenario, due to anticipated rapid urbanization, growth in population, economic expansion, and anticipated political stability. Compared to the baseline scenario, the total power demand shows a growth of 68 % from the forecast year (2025) to 2040 for the aggressive scenario, which ensures sustainable and efficient energy options that can draw businesses from both domestic and international baselines. In contrast, the total power demand in the conservative scenario shows a growth of 30.3 % from the base year (2025) to 2040. This reduction in demand compared to the two scenarios indicates a reflection of how much electricity power demand could be if certain development conditions failed to be realized in the economy. In general, both results show a rapid increase in power demand compared to the base year. To address this increasing demand, a supply-side demand analysis can be done for reference and aggressive scenarios. The analysis result indicated that by 2040, supply-side demand from the national grid will increase by 93.5 % and 175.9 % for reference and aggressive scenarios, respectively, compared to the base year 2025 demand. Due to the huge gap between the supply and demand in the country, onsite off-grid generation can be considered to cover 25 % of the demand in the economic zone. Hence, with the support of off-grid generation, the demand from the national grid was reduced to 45 % and 107 % for reference and aggressive scenarios with the support of onsite generation. Hence, this research clearly shows that there is a serious need for large scale electricity generation and distribution planning and preparation to meet the continually increasing electric power demand in a sustainable manner to accommodate the growth and change required to develop the modern economic zones in the country.

Major arterial roads in city centres often face ever-increasing traffic demand periodically addressed through developments to ease congestion on road links and improve integrated road connectivity. Towards this end, three flyovers are proposed in the Slave Island area in Colombo. This high-investment project of the Sri Lankan Government expects the flyovers to prevent peak-hour traffic delays from the frequent road closures at two railway gates while providing for the higher traffic generated from the land use changes in the area. The project also expects to relieve congestion in the adjacent road network. This research investigates the outcomes expected of integrated traffic management from the project. A traffic analysis was carried out for the entire road network of the project impact area using the PTV Vissim software. Moreover, current and future land use was considered in assessing network connectivity over the design life. Alternative traffic management options were tested to identify the most feasible arrangement for connecting the proposed flyovers. Origin-Destination data from 2018 were used to determine intersection capacities and pedestrian movements. Results reveal that delays due to railway gate closure reduced, though a significant traffic diversion from the proposed flyover network was not evident.

In Latin America and developing countries, urban planners often lack sufficient data on cyclists’ modal share and profile to establish effective cycling lane networks. Mendoza, Argentina, is such a city. This research aimed to identify adequate locations for new cycle lanes by speculating on potential cycle trips from observed patterns of existing cyclists for a coherent demand-based network. The study proposed a novel, simple, cost-effective Geographic Information Systems model that uses spatial and human data and presents results cartographically for policymakers. Statistical analysis of observed bicycle trips enabled constructing a local profile of cyclists, from which ‘potential trips’ were speculated: trips made by other modes, but which could have been biked given their distance, duration, purpose, and the traveler’s age. Geo-referencing observed and potential trips to their ‘sub-zones’ of origin and destination produced a migratory synthesis map highlighting general flows and densities. Superimposing this on the current cycling infrastructure exposed the critical gaps. As a broader aim, this geomatic method is readily transferable to other developing world settings. Actions for Mendoza and broader applications are proposed, significant limitations discussed, and further research suggested, noting issues of gender equity and safety.

Rats were studied in social reinforcement procedures in which lever presses opened a door separating two adjacent spaces, permitting access to social interaction with a partner rat. The number of lever presses required for social interaction was systematically increased across blocks of sessions according to fixed-ratio schedules, generating demand functions at three different social reinforcement durations: 10 s, 30 s, and 60 s. The social partner rats were cagemates in one phase, and non-cagemates in a second phase. The rate at which social interactions were produced declined with the fixed-ratio price, and was well described by an exponential model that has been successfully employed with a range of social and non-social reinforcers. None of the main parameters of the model varied systematically with social interaction duration or with the social familiarity of the partner rat. On the whole, the results provide further evidence of the reinforcing value of social interaction, and its functional parallels with non-social reinforcers.

Medical caregivers as auxiliary medical care personnel have become an indispensable labor supplement in nursing work. Given the public's rising awareness of health and rights protection, the quality of patients' nursing staff has also improved accordingly. In order to strengthen life care skills and professional quality, it's required to standardize professional training. However, there are still many problems in the training of medical nursing staff and content in China. This article analyzed the current employment conditions, management and training needs of medical caregivers, aiming to provide reference for further establishment of standardized training curriculums. (医疗护理员是辅助医疗护理的人员, 已成为护理工作中不可缺少的劳务补充。为加强护理员生活照护技能和职业素养, 需对医疗护理员进行规范化专业培训。目前, 国内关于医疗护理员的培训方式和内容尚存在着诸多问题。本文就医疗护理员目前的从业、管理和培训状况进行分析, 为进一步设置规范化的培训课程提供参考。)

First and last mile connectivity of public transport hubs is a key component in promoting multi-modal travel. The Dutch train station operator (NS Stations) promotes the combination of bike and train by offering a train station-based round-trip bikesharing (SBRT) scheme, known as ‘OV-fiets’, located at train stations throughout the country. This scheme allows users to rent a bike to travel between train stations and their destination and vice versa. The round-trip nature of the SBRT makes it unique in comparison to widely applied one-way bikesharing schemes. Little is known about the determinants of demand for round-trip bikesharing, especially when being integrated into an existing PT scheme. This paper aims to fill this gap by identifying potential temporal and weather-related determinants for SBRT-rentals of the Dutch SBRT-system using multiple linear regression (MLR) and an in-depth analysis for selected stations. The results are compared with the findings of one-way bikesharing schemes. The results show that for hourly rentals in an SBRT-system, the highest explanatory power is attributed to the number of train travelers leaving the corresponding train station, followed by temporal and weather-related determinants. Furthermore, the magnitude of the correlation between the determinants and the hourly demand varies considerably across stations, depending on the underlying demand patterns.

As the country implements the big data strategy and accelerates the construction of a digital China, data science has entered a new and dynamic era, and the demand for data science talents in all walks of life is increasing. Many talent training departments have added undergraduates or degrees to data science talents, but it is still unclear whether they can meet social and economic development needs. This article aims to improve the quality and adaptability of data science talent training and conduct an in-depth analysis of the demand for data science talents. The technology used in this article is data mining technology. The data information of data science talents is crawled out of the demand information of data science talents on the recruitment website. The core content of network relationship visualization is proposed and analyzed through machine learning methods and text subject word extraction models. Achieve a comprehensive exploration of the demand for data science talents and provide a reference for talent training units to formulate data science talent training models.

The ubiquitous power Internet of Things (UPIoT) is an intelligent service system with comprehensive state perception, efficient processing, and flexible application of information. It focuses on each link of the power system and makes full use of the mobile internet, artificial intelligence, and other advanced information and communication technologies in order to realize the inter-human interaction of all things in all links of the power system. This article systematically presents to the national and international organizations and agencies in charge of UPIoT layer standardization the status quo of the research on the Internet of Things (IoT)-related industry standards system. It briefly describes the generic standard classification methods, layered architecture, conceptual model, and system tables in the UPIoT application layer. Based on the principles of inheritance, innovation, and practicability, this study divides the application layer into customer service, power grid operation, integrated energy, and enterprise operation, emerging business and analyzes the standard requirements of these five fields. This study also proposes a standard plan. Finally, it summarizes the research report and provides suggestions for a follow-up work.

The purpose of the paper is to provide an ex-ante evaluation of banning price promotions for discretionary foods (e. g., such as confectionary, crisps, biscuits, sweet and savory snacks, cakes) in Scotland. The methodology consisted of the estimation of demand systems by socioeconomic groups (i.e., lifestage and income groups) for 19 food groups using a highly product disaggregated dataset. These results were used to simulate scenarios consisting of eliminating price promotions on the discretionary food products for the entire sample and by group and analyzing nutritional results. The results indicated a net impact of reducing energy by 651 kcal per capita per week (C.I. −695, −608)1. Similar results were found for macro nutrients. There were some significant differences across different income and lifestage groups, with kcal energy reductions being significantly greater amongst household with lower income, and in households where respondents were aged 45 years or over. The analysis concluded that restrictions on the promotion of foods considered to be high in saturated fat, sugar, or salt (HFSS) are seen as one measure to improve the overall nutritional quality of foods consumed. Results indicate that restricting promotions has the potential to reduce the number of calories, sugar, saturated fats and sodium for most food groups.

With the acceleration of 5G global commercial deployment process,various emerging immersive network applications represented by holographic communication have put forward significant requirements and tests on the structure and capability of the existing network architecture.The wide application of holographic communication services in many fields was introduced,and the current situation was analyzed that 5G network can not meet the rapid development needs of holographic immersion applications.The performance requirements of holographic communication applications in bandwidth,delay,computing power,synchronization,quality of service,reliability,security and other aspects of the future network performance were analyzed.The application scenarios and key technologies of holographic communication were summarized.Through the investigation and analysis of the possible evolution routes of the future network,the direction of the future network evolution and development was pointed out.

Standard system is the overall strategic planning and implementation guidance for standardization in professional field. In view of the missing of standard system on intelligent agricultural machinery, a standard system framework was contributed for the industry of intelligent agricultural machinery in this study. Currently, in China, standardization work for the industry of intelligent agricultural machinery is carrying out unplanned and disorderly. Published standard is of limited number, and could not meet the industry needs. The adopted international standards take a high percentage of national standards, however, China-made intelligent agricultural machinery standard has not been promoted abroad. Based on the development goals and principles of standard system framework, 9 dimensions of level, binding force, generality, property, object, standard category, reference model, industry classification and industry sector were identified for the standard system framework of intelligent agricultural machinery. Three dimensional standard system framework was contributed for intelligent agricultural machinery. The level dimension included 5 elements of national standard, industry standard, local standard, group standard, and enterprise standard. The category dimension included 8 elements of safety, health, environmental protection, basic, methods, management, products, and others. The industry sector dimension included 9 elements of power machinery, seeding and fertilizing machinery, plant protection machinery, harvester, seed breeding and selection machinery, agricultural product storage and transport machinery, facility agriculture, livestock and poultry breeding machinery, and agricultural product processing machinery. In order to clear standard level and intuitively guide standard system table development, the three dimensional standard system framework was decomposed in two dimensions. The first layer was basis, included terminology, safety, environmental protection and reliability. The second layer was common features, included information perception, navigation and positioning, control communication, big data analysis, agricultural management platform. The third layer was applications, included operating power, seeding and fertilization, plant protection, harvesting, selection and breeding of seed, agricultural product storage, facility agriculture, livestock and poultry breeding, and agricultural product processing. Suggestions were proposed for standardization of intelligent agricultural machinery in China. Firstly, priorities of the standard system table should be worked out based on industry need and technological maturity. Secondly, practicability of the standard was suggested to be improved by developing the standard content based on industry needs and market prospect. In addition, a variety of resources of industry, university and research institute was suggested to be organized together to contribute to standardization work. In addition, the progress of international standardization was suggested to be tracked, and the China-made standard was suggested to be internationalized. Finally, the standardization work should be operated by the professional organizations and specialized talents. This standard system framework could be used to systematically guide the development, revision, implementation, and service of intelligent agricultural machinery standards, and lead the rapid development of intelligent agricultural machinery industry in China.

This study aims to analyze Saudi demand for natural honey imported from Yemen, Pakistan, Australia, Argentina, Mexico, and Germany, which contribute around 73.7% of the value of natural honey imports during the period of study (1991–2017). Marshallian elasticities estimation using AIDS model shows all own-price elasticities were negative and significant except for own-price elasticity associated with demand for natural honey imported from Pakistan. Natural honey imported from Yemen has own-price inelastic demand. In addition, the results of cross-price elasticities show a relationship between different products of imported natural honey and the estimated values of expenditure elasticities. According to these study results, it is important to encourage the domestic production of honey to meet the increase in the demand of the natural honey. The future studies could examine whether the domestic natural honey might be close substitute of any of these imported natural honey. In addition, we recommend increasing sources of import natural honey, especially if a country might be closer substitute for others.

During the years 2009-2018, at the same time with the minimum interest rates, the increase of the gross disposable income and the GDP/inhabitant, the real estate investments became the safest. In the absence of an integrated database that raises the transparency of the real estate market in Romania, the main indicators are statistics on the dynamics of transactions and demographic indicators. This study involves a comprehensive analysis and correlation of statistical data to determine the links that contributed to the dynamics of the Romanian real estate market during 2009-2018. Without going through the extensive list of causes that have contributed to the dynamics of the market, a number of factors such as legislative, technological, demographic, micro and macroeconomic, attest that the level of real estate transactions can represent a good indicator of the economic situation. Once the Romanian economy showed signs of recovering from the last international economic crisis, and the purchasing power increased, the volume of real estate transactions began again. During the analyzed period, despite the fluctuation of the number of transactions, annually, the obtainable price of the properties increased fluctuating. However, the dynamics of transactions in 2018 fell below the values before the economic crisis.

Traditional and innovative on-demand transport services, such as taxi, car sharing or dial-a-ride respectively, can provide a level of flexibility to the public transport with the aim to guarantee a better service and to reduce the exploitation costs. In this context, in order to point out the key-factors of on-demand services, this study focuses on traditional on-demand service (such as taxi one), and presents the results of a demand analysis and modelling, obtained processing taxi floating car data (FCD) available for the city of Rome. The GPS position of each taxi is logged every few seconds and it was possible to build a monthly database of historical GPS traces through around 27 thousands of GPS positions recorded per day (more than 750 thousands for the entire month). Further, the patterns of within-day and day-to-day service demand are investigated, considering the origin, the destination and other characteristics of the trips (e.g. travel time). The time-based requests for taxi service were obtained and used to analyse the trip distribution in space and on time. These analyses allow us to forecast trips generated/attracted by each zone within the cities according to land use characteristics and time slices. Therefore, a regression tree analysis was developed and different regressive model specifications with different set of attributes (e.g. number of subway stations, number of zonal employees, population) were tested in order to assess their contribution on describing such a service use.

Urban mobility is evolving today towards the concept of Mobility as a Service (MaaS). MaaS allows passengers to use different transport services as a single option, by using a digital platform. Therefore, according to the MaaS concept, the mobility needs of passengers are the central element of the transport service. The objective of this paper is to build an updated state-of-the-art of the main disaggregated and aggregated variables connected to travel demand in presence of MaaS. According to the above objective, this paper deals with methods and case studies to analyze passengers’ behaviour in the presence of MaaS. The methods described rely on the Transportation System Models (TSMs), in particular with the travel demand modelling component. The travel demand may be estimated by means of disaggregated, or sample, surveys (e.g., individual choices) and of aggregate surveys (e.g., characteristics of the area, traffic flows). The surveys are generally supported by Information Communication System (ICT) tools, such as: smartphones; smartcards; Global Position Systems (GPS); points of interest. The analysis of case studies allows to aggregate the existing scientific literature according to some criteria: the choice dimension of users (e.g., mode, bundle and path, or a combination of them); the characteristics of the survey (e.g., revealed preferences or stated preferences); the presence of behavioural theoretical background and of calibrated choice model(s).

Bikeshare programs in their current form have been in place for several years in many cities across the United States. Encouraging people to use bikeshare for their daily routine travel has numerous social, economic, environmental, and health benefits. Therefore, it is important to understand factors influencing bikeshare use in different urban areas to improve the system and encourage more use. This paper investigates how the built environment at both local and regional scales influences bikeshare use in seven large metropolitan areas in the U.S. The study areas include Boston, Chicago, Philadelphia, Minneapolis, San Francisco, San Jose, and Washington, D.C., and the data consists of about 12 million bike trips from approximately 2,000 stations over a one-year period. In addition to linear regression models built for each individual city for comparison purposes, a multi-level mixed effect regression model is built to predict the number of trips originated from each station with respect to the local and regional built environment pattern. The results are consistent with previous research on the effect of land use at the local level on bikeshare demand and show that residential density, regional diversity, pedestrian-oriented road network density, and job accessibility via transit all have a significant positive effect on bikeshare demand. At the regional level, results suggest that the overall level of mixed-use development and overall bike-friendliness in the region (i.e., exclusive bike routes, right-of-way, and bike facilities) and higher congestion level in the region are significant factors influencing bikeshare activities and demand. Models developed in this study could be applied to other communities that are seeking to improve and/or expand their bikeshare systems, as well as cities planning to launch new bikeshare programs.

The study estimates, compare and analyse the food demand patterns of households in the rural and urban Sindh. Estimates of the study are based on data of Household Integrated Economic Survey (HIES) 2010-11, using Linear Expenditure System (LES). The results show that substantial quantities of milk, eggs, vegetables, salt, sugar, wheat, and pulses are taken by households in both the urban and rural Sindh; whereas formers add vegetable oil and later, fruits to this list. There is a visible difference in the marginal budget share and luxuries, necessities, substitutes and complements for both types of households. The difference in results of both the rural and urban recommends that, separate policies should be chalked out for the two areas.

This study aims to analyze the factors that influence the demand of soybean in Indonesia. The research method uses descriptive analysis of secondary data which includes the price of imported soybeans, the price of chicken, per capita income, the rate of inflation and import tariff policy year period 1980-2013 which sourced from FAO and other sources. Estimation of demand function using multiple linear regression analysis were transformed in the form of natural logarithm. Regression analysis showed that soybean demand in Indonesia was influenced partially by prices of chicken, per capita income, and the rate of inflation. The price elasticity of demand of soybean in Indonesia is inelastic, that is equal 0,22. While the income elasticity of demand for soybeans is positive which means that soy is a staple item for the Indonesian people.

There is an increasing interest in specialty milk products such as soymilk, cholesterol free/lactose free (CFLF) milk and organic milk. While the market shares of these milk types are still small, specialty milk consumption is one of the fastest growing consumer segments in the dairy industry. Therefore, it is of interest to producers, consumers as well as the policy-makers to identify the consumer profile of these products and to determine policies based on the consumer choices. In the article, there are utilised the actual consumer sales data to see whether the USDA's dairy policy follows the consumers' milk preferences. The results indicate that the household demographics significantly affect milk preferences. Race is by far the most striking factor in the consumers' decision process. Minority households have a much higher probability of purchasing specialty milk types than the white households. They are also loyal customers of the specialty milk types and are less responsive to the changes in factors that affect their purchase decision. Based on these findings, there is recommend an alternative policy to the USDA's one-size-fits-all type of dairy guidelines.

Background: Currently, to the best of our knowledge, no findings exist concerning the needs of professionals in specialized pediatric palliative care (PPC) regarding electronic health records (EHRs). Several studies have highlighted benefits concerning the use of EHRs in pediatrics. However, usability is strongly affected by the degree of adaptivity to the context of application. The aim of this study is to examine the needs of professionals concerning an EHR in the specialized PPC inpatient and outpatient settings. Methods: A qualitative research design was chosen to address the complex aspects of user demands. Focus group interviews and semi-structured one-on-one interviews were conducted with PPC professionals. N = 23 participants from inpatient and N = 11 participants from outpatient settings of specialized PPC representing various professions took part in the study. Results: The findings could be grouped into four categories: (1) attitude towards the current methods of documentation, (2) attitude towards electronic documentation in general, (3) general requirements for an EHR, and (4) content requirements for an EHR. Conclusions: Professionals in specialized PPC expect and experience many benefits of using electronic documentation. Their requirements for an EHR for inpatient and outpatient settings of PPC are largely consistent with EHRs for pediatrics. However, individual specifications and adaptations are necessary for this particular setting.

The declining trend of Tabalong Regency’s economic growth in recent years adversely affected the poverty rate. Further, the recent energy subsidy policy applied by the Indonesian Government has pushed the subsidy’s budget down for some energy goods. Therefore, there should be an awareness regarding the current energy policy and the impact on the poverty particularly in Tabalong Regency. This paper investigates the demand system for the three main energy goods; premium fuel, electricity, and Liquid Petroleum Gas (LPG) in Tabalong Regency of the South Kalimantan Province. Although the same method was previously used on the different topics, this paper uniquely utilizes the combined Linear Approximation and Quadratic Almost-Ideal Demand System on the particular energy policy topic. This paper utilizes the National Social Economics Survey conducted by BPS-Statistics of Tabalong Regency in 2016. The results show that the income elasticity of demand for the top 60% and the bottom 40% of the income groups were positive; however, slight differences could be seen. For the top 60% of the income group, the income elasticities of demand were 0.97, 1.02, and 1.08 for premium fuel, electricity, and LPG respectively. On the other hand, the bottom 40% of the income group had 0.99, 1.07, and 0.91 of income elasticity of demand for premium, electricity, and LPG. The price elasticity of demand for both income groups had negative signs, which is agreeing with the theoretical demand function. These results indicate that the current energy policy should continue with securing the poor households from the possible effect.

Although mass-produced beers still represent the vast majority of U.S. beer sales, there has been a significant growth trend in the craft beer segment. This study analyzes the demand for beer as a differentiated product and estimates own-price, cross-price, and income elasticities for beer by type: craft beer, mass-produced beer, and imported beer. We verify that beer is a normal good with a considerably inelastic demand and also find that the cross-price elasticity across types of beer is close to zero. The results suggest that there are effectively separate markets for beer by type.

Some health problems at work, increased by ever more intense work demands, result in absenteeism, turnover, stress, work exhaustion, and MSDs. These problems are treated with more appropriate preventive measures when ergonomic interventions take into account the differences between the work situations of women and men. It is through data analysis (population, health, human resources) and work analysis that the intervention can objectify these differences and encourage their discussion in the company. Four causal factors have been identified : the sexual division of labor, the invisibility of risks and of work strenuousness in female-dominated sectors, differences in occupational paths, and differing exposures to time constraints in occupational and domestic work. This type of interpretation makes it easier for changes to occur in companies. That being said, interventions in companies encounter resistance insofar as these differences reflect gender inequalities between women and men resulting from social dynamics that are still difficult to address.

The article considers issues on searching the methods of using marketing instruments for solving the railway transport development problems and functioning this branch in the market conditions.

The purpose of this study, at a private hospital in Ankara between October 2009-October 2010 to determine particulars of outpatients and inpatients that using health care service and therefore profile of outpatients and inpatients build up in the future and thus aid to health care management who make planning of patient services. The population consists of 270 patients. The data collected from patient satisfaction surveys and electronic patients records are used by public relations department of hospital. Chi square test is implemented in statical analysis of the data. At the end of study, significant level of correlation between educational background of patients with patients’ electing to hospital in next health problems are found 0,059 and reached the conclusion that correlation is not significant. In addition to when are analyzed results about profession of patients, significant level of correlation are found 0,01 and concluded that correlation is significant.

Using data from the 2000 National Survey on Recreation and the Environment, this study explores factors affecting visits by the American population to farms and the economic value of the rural landscapes for farm visitors. The number of farm recreation trip visits was estimated to have own-price elasticity of -0.43 and an income elasticity of 0.24. Location of residence, race, and gender were found to be important determinants of the number of farm trips. The calculated consumer surplus is estimated at $174.82/ trip, of which $33.50 is due to the rural landscape.

We present an analysis of markets for fresh strawberries, blueberries, blackberries and raspberries in the United States during 2008–2011. We use weekly panel data covering supermarket purchases in 52 cities. The primary goal is to estimate demand elasticities for fresh berries and thereby provide a better understanding of consumer behaviour in response to price changes and the nature of competition among these crops. We estimate fixed and random effects models for double log demand equations and a complete demand system, the Almost Ideal Demand System. The latter specification can be used to estimate demand relationships that conform to utility maximising behaviour. The elasticity estimates are very robust across the different specifications and estimation methods. This increases confidence in our findings and provides some assurance that choice of functional form or estimation method is not driving our results. We find that retail demands for all berry crops are in the elastic range and that the different berries are substitutes for one another. The demand for strawberries was the least elastic with an own price elasticity of –1.26 and blackberries were the most elastic with a demand elasticity of –1.88. Blackberry demand was also the most responsive to the prices of competing berry crops. The study provides clearer insight into markets for berries in the United States. In addition, it fills a gap in the present lack of up-to-date consumer demand elasticities for these crops and will be useful for growers, decision makers and consumers.

O caminho usual para que os consumidores dêem suas respostas aos atributos de qualidade de serviço passa pelo uso efetivo do serviço. No entanto, estas ocasiões únicas não cobrem todos os casos de interesse. Uma alternativa para reduzir parcialmente essa limitação consiste em coletar e analisar as preferências dos consumidores com o auxílio de um experimento estatístico chamado pesquisa de preferência declarada ou análise conjunta. Para isso, os atributos são combinados, variando-se sistematicamente seus valores de forma a cobrir uma grande área de interesse, e representando assim cenários realistas. Estes cenários são usualmente apresentados na forma de cartões (textos, esquemas). Pede-se, às pessoas entrevistadas, após uma explicação introdutória, que classifiquem os cenários em ordem decrescente de preferência. Num segundo estágio, uma técnica de calibração é utilizada para ajustar os coeficientes de uma função utilidade. A classificação hoteleira no Brasil considera somente atributos físicos, tais como, quartos, garagem, recepção, etc. Os elementos relacionados ao serviço, como atendimento, acessibilidade e conforto não são explicitamente incluídos. Este trabalho descreve uma pesquisa de preferência declarada e um modelo de preferência do consumidor, com aplicação específica ao serviço hoteleiro de Balneário Camboriú.The usual way that customers show their response to service quality attributes is when they use the service effectively. But those occasions alone do not cover all the cases of interest. One way to partially reduce this limitation is to collect and analyze the customers' preferences with the aid of a statistical experiment called stated preference surveying, or conjoint analysis. In order to do this, the attributes are combined such that their values cover a range of interest, representing realistic scenarios. These scenarios are usually presented in the form of cards (text, drawings), and the interviewed person is asked, after the introductory explanations, to rank them in a decreasing order of preference. A two-stage calibration technique is used to adjust a logit model, yielding the coefficients of a utility function. In Santa Catarina, a southern Brazilian state, resort beaches receive lots of Argentinean tourists in the summer. The official hotel classificatory system in Brazil considers only physical attributes of the facilities (bedroom and reception characteristics, garage, etc). Service factors such as comfort, attendance, accessibility, etc are not included. The paper describes a stated preference survey and customers' preference modeling with regard to hotel services in Balneário Camboriú.

We present an inverse demand that can be estimated in a linear form. The model is derived from a specification of the distance function which is parametrically similar to the cost function underlying the Almost Ideal Demand System. Simulation results suggest that this linear inverse demand system has good approximation properties.

ABSTRACT: Along the last ten years fish and fishery product trade in Brazil has been on a downward trajectory turning a profit of US$ 98.6 million in 2005 into a loss of US$ 1.25 billion by 2014. On the other hand, the country is a leading producer of grains and has the third largest animal feed industry in the world, which has added 5.5 million hectares of freshwater reservoirs and 3.5 million km2 of an exclusive marine economic zone in the same period, a sizable potential for development of the aquaculture industry. This study aims at unveiling strategies for the reduction of the deficit in the Brazilian seafood trade balance, based on critical analysis of the quantitative and qualitative characteristics of imported fishery products. The fish and fishery product trade in Brazil, from 2005 to 2015, was studied considering import and export data mined from the Brazilian Ministry of Development, Industry and Commerce databases through the Aliceweb system, and clustered as follows: processing; product species; origin; conservation; and group. The main imported products were gutted fresh fish, highest price (salmon); salted dried fish, higher price (cod); frozen fish fillets, lowest price (fish and hake). The replacement of fish imports by domestic production is not enough to enable consumers to identify the equivalence between products (technical, qualitative or organoleptic). Developing strategies for the production of fish and fishery products at competitive prices and quantities that meet consumer demand is an immediate need, and the development of the aquaculture industry a rational strategy.