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The purpose of this paper is to investigate the factors affecting consumer demand for and the effects on tax on sparkling and non-sparkling bottled water in the USA.

Using nationally representative data from 62,092 households and tobit econometric procedure, conditional and unconditional factors affecting the demand for sparkling and non-sparkling bottled water were estimated.

The own-price elasticity of demand for sparkling and non-sparkling bottled water is −0.664 and −0.229, respectively. Coffee, fruit drinks, whole milk and tea are substitutes for non-sparking bottled water. Non-sparking bottled water, coffee, fruit drinks and whole milk are substitutes for sparking bottled water. Household income, race, region and presence of children significantly affect the demand for bottled water. A 10 percent increase in price due to a tax on bottled water decreased plastic use by 50 grams per household per year. This is equivalent to saving 9.5m pounds of plastic annually.

Data used in this analysis only captured at-home consumption of bottled water by US households. While tax on bottled water may reduce the consumption of bottled water, it may increase the consumption of competitive beverages such as carbonated soft drinks or fruit drinks. Although the use of plastic with regards to water bottles may go down as a result of the tax, the plastic consumption could go up with regards to consumers’ increased purchase of other beverages. This might contribute net increase plastic bottle consumption, undermining the effects of a bottled water tax.

To the best of the authors’ knowledge, this study is the first to look at demand and tax aspects with regards to disaggregated bottled water products.

This paper aims to expand the application area of Inconel 718 alloy in marine environment, the sensitivity of pitting corrosion should be analyzed and discussed, especially the effect of block carbides.

Effect of carbides on the sensitivity of pitting corrosion for Inconel 718 alloy was carried out at 30°C in 3.5% NaCl solution using dynamic electrochemical impedance spectroscopy and anodic polarization techniques. In addition, the initiation of pitting corrosion was investigated by immersion test in 0.05 M HCl + 6% FeCl₃ solution.

As a result, the precipitation of carbides, as the initiation of pitting corrosion, increased pitting corrosion susceptibility, especially the block carbides could lead to deep-spalling. Within that process, temperature and potential acted as the main controlling factors, and the effect of the latter was more distinct.

The initiation of pitting corrosion was revealed by the immersion test. The mechanism of pitting corrosion was analyzed and discussed.

Drawing on protection motivation theory (PMT) and expectancy theory, this study aims to investigate consumers’ lodging consumption intentions during a pandemic crisis.

The research survey was conducted during the ongoing COVID-19 pandemic (August, 2020) in the USA to investigate consumers’ lodging intentions amidst the pandemic crisis. PLS-SEM and multiple regression were conducted to explore answers to proposed research questions.

The research finds that, during the pandemic crisis, consumers’ lodging consumption intentions are subject to both their internal protection motivation evaluations and the external prevention practices implemented by the lodging facilities regardless of property types and travel purposes. Notably, the research finds that consumers are willing to make efforts and pay extra for a safe stay at lodging facilities.

This research contributes to the literature regarding the applications of PMT and expectancy theory from a crisis management perspective, and it provides implications and guidelines to the crisis management practices in the lodging industry.

The current research examines the specific protection motivation appraisal factors and prevention practices significantly impacting consumers’ decisions in terms of willingness to stay at various lodging facilities (hotels and non-hotel homestay/short-term rental properties) for different purposes (business and leisure) and to pay premiums for a safe stay.

As the flourish of today’s supply chain, the traditional model of replenishment will cause accumulation of excessive inventory to the retailers and customers, or cause shortages and inability to meet the demands. To solve this problem, Theory of Constraints (TOC) proposed the replenishment model of demand‐pull, combined with the establishment of factory‐warehouse to achieve performance improvement. In the absence of empirical research, this study applied the Bean Game developed by Dr. Goldratt to design a supply chain system for different scenarios, in order to allow players and managers better understanding and supporting the TOC replenishment method through the operations of the game.

This study sets out to make in‐depth comparisons between major political campaigns in the UK and Taiwan, and generate contemporary insights into the creative development process, the working relationships between campaign managers and professional agencies, and the “spin doctor” phenomenon, all through the eyes of very senior professionals.

Material gathered in “élite interviews” was subjected to interpretive analysis and synthesised with secondary data and the findings of an extensive literature review.

The putative Americanization of political marketing has not been as complete as some authors suggest, but one of its features was an important element in campaign development in both countries: the centrality of the party leader's persona in an image‐building strategy. The culture and history of the party were an important determinant of the style of the campaigns examined. It was generally agreed that political marketing and advertising have been strongly influenced by commercial branding, though important differences remain.

Despite the richness of the data and the authority of the respondents, the small number of willing participants in the study limits the scope for generalisation.

The findings offer usable insights into the creative development process and the nature of client‐agency relationships, in political campaign planning.

The paper contributes the first expert‐insider perspective in published studies and commentaries concerning political marketing literature. It cuts across disciplines of political science, communication, management, marketing and advertising, and may contain lessons for marketing planners in other non‐commercial contexts.

This paper aims to use the Monodepth method to improve the prediction speed of identifying the obstacles and proposes a Probability Dueling DQN algorithm to optimize the path of the agent, which can reach the destination more quickly than the Dueling DQN algorithm. Then the path planning algorithm based on Probability Dueling DQN is combined with FastSLAM to accomplish the autonomous navigation and map the environment.

This paper proposes an active simultaneous localization and mapping (SLAM) framework for autonomous navigation under an indoor environment with static and dynamic obstacles. It integrates a path planning algorithm with visual SLAM to decrease navigation uncertainty and build an environment map.

The result shows that the proposed method offers good performance over existing Dueling DQN for navigation uncertainty under the indoor environment with different numbers and shapes of the static and dynamic obstacles in the real world field.

This paper proposes a novel active SLAM framework composed of Probability Dueling DQN that is the improved path planning algorithm based on Dueling DQN and FastSLAM. This framework is used with the Monodepth depth image prediction method with faster prediction speed to realize autonomous navigation in the indoor environment with different numbers and shapes of the static and dynamic obstacles.

The purpose of this paper is to investigate the impacts of institutional quality (IQ) in exporting and importing countries on agro-food exports from the world's leading emerging economies: Brazil, the Russian Federation, India and China (BRIC countries).

Measuring is based on using the gravity trade model and econometric panel data analysis for the period 1998-2009.

Agro-food exports from the BRIC countries, particularly Brazil and China, have increased. The Russian Federation has experienced stagnating and volatile patterns. Brazil and India have strengthened market shares in the existing importing markets, while the Russian Federation has experienced severe deterioration. The export of existing products is more important than of new products. Agro-food exports are positively associated with IQ and the size of the gross domestic product in exporting and importing countries, but negatively with distance.

Among IQ variables, the focus is on the indices of legal structure and security of property rights and freedom to trade internationally in agro-food importing countries and the BRIC exporting countries.

Different institutions and their quality can affect agro-food exports differently. The impact of institutions is not uniform across product groups.

This paper adds the impacts of IQ on agro-food exports. Except for processed products for final household consumption, agro-food exports from the BRIC countries are positively associated with the quality of the legal structure, the security of property rights and the freedom to trade internationally as IQ in exporting and importing countries.

This paper aims to propose a novel active SLAM framework to realize avoid obstacles and finish the autonomous navigation in indoor environment.

The improved fuzzy optimized Q-Learning (FOQL) algorithm is used to solve the avoidance obstacles problem of the robot in the environment. To reduce the motion deviation of the robot, fractional controller is designed. The localization of the robot is based on FastSLAM algorithm.

Simulation results of avoiding obstacles using traditional Q-learning algorithm, optimized Q-learning algorithm and FOQL algorithm are compared. The simulation results show that the improved FOQL algorithm has a faster learning speed than other two algorithms. To verify the simulation result, the FOQL algorithm is implemented on a NAO robot and the experimental results demonstrate that the improved fuzzy optimized Q-Learning obstacle avoidance algorithm is feasible and effective.

The improved fuzzy optimized Q-Learning (FOQL) algorithm is used to solve the avoidance obstacles problem of the robot in the environment. To reduce the motion deviation of the robot, fractional controller is designed. To verify the simulation result, the FOQL algorithm is implemented on a NAO robot and the experimental results demonstrate that the improved fuzzy optimized Q-Learning obstacle avoidance algorithm is feasible and effective.