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In this paper, we use choice architecture techniques to activate both social and personal norms, seeking to increase pro-environmental choices and to better understand the effect of such norm types on post-choice emotional responses. In four experiments, we make different social or personal norms salient by aligning choice environments with psychosocial mechanisms that activate different types of norms. We use different choice architecture techniques to change information, alter product sets, and generate the social consequences of choices. The target behavior, purchasing a recycled paper notebook, is captured through direct purchase behaviors or willingness to pay commitments. We find that choice architecture activates personal but not social norms, and that associated positive and negative emotions (guilt, shame, regret and pride) are elicited by choices but not by willingness to pay. Moreover, manipulating choice environment moderates the relationship between choice and norm-related emotions, such that positive emotional responses seem to be stronger than negative ones. The results suggest that choice architecture interventions can activate individual level beliefs about sustainability and help reduce the attitude-behavior gap. [ABSTRACT FROM AUTHOR]

Sustainability issues such as food insecurity, climate change, land degradation, economic development and food waste are the actual most important challenges at the global level. Among them, the food waste (FW) challenge has a great magnitude, emphasizing the importance of examining this issue. Specifically, there is a need to focus on the household level. Thus, this study aims to investigate and identify the main factors influencing FW household behaviors on which policymakers and stakeholders could outline specific and sustainable strategies. Starting from a large number of published studies on this subject with a similar aim but focusing on specific Countries or contexts, the goal of our study is achieved through the implementation of a systematic literature review followed by a bibliometric review using the VOSviewer software. The selected query generated a total of 235 matching papers from which only 111 papers were collected for the bibliometric review because of the inclusion criteria. The analysis showed the existence of four major research strands: the largest one analyses the antecedents of behavior during food management, including the implementation of the Theory of Planned Behavior (TPB). Other detected topics are the economic impact of FW, the effects generated by the Covid-19 pandemic on consumer behaviors, and finally, the environmental and social effects of FW. The objective of this study is to investigate and identify the main factors influencing FW household behaviors. The obtained output represents useful information for policymakers and stakeholders to outline specific and sustainable strategies to reduce FW. [ABSTRACT FROM AUTHOR]

Tourism consumption as a typical representative of service consumption, has strong comprehensiveness and driving force, continuously expanding new consumption upgrade space. In the context of the digital economy, the development of the mobile internet has opened up new opportunities for the tourism industry acting as an important factor influencing the consumer behaviour of the residents. Based on 9007 resident survey data from the China General Social Survey (CGSS) in 2017, this paper explores the relationship between Internet use, access to information and residents' travel consumption behavior by means of probit model and mediating effect model. First, according to the findings, Internet use has a positive impact on residents' travel consumption behavior, increasing residents' tourism expenditure. Second, the mechanism suggests that access to information plays a partially mediating role between Internet use and travel consumption behavior. Third, further analysis revealed that, for the retired population, the more frequently they use the Internet, the more likely they are to spend on travel. Compared to those with lower incomes, those with higher incomes will spend less on travel after retirement. With this in mind, in order to promote residents' tourism consumption, speed and fee reduction should be continuously promoted, urban and rural information infrastructure should be strengthened, and accessibility of tourism information for residents should be improved. At the same time, there is a need to innovate the way tourism products are promoted, improve the types of tourism products and launch diversified tourism products. [ABSTRACT FROM AUTHOR]

Based on 908 consumer questionnaire data from 15 urban areas in Shanghai, we use the binary logit model to empirically analyze the impact of traceability label trust on consumers' traceable pork purchase behavior and the moderating effect of food safety identification. After constructing the theoretical analysis framework, this paper verifies it from the two aspects of statistical analysis and econometric analysis and tests the robustness of the final results. The results show that: first, traceability label trust has a significant positive impact on consumers' traceability pork behavior. Second, food safety identification can significantly strengthen and promote this process. Third, consumers' purchasing behavior is significantly positively affected by traceable pork consumption scenarios and price labels, but the permanent elderly in the composition of family members significantly negative impact on it. Therefore, we put forward relevant policy suggestions, such as strengthening the knowledge popularization and publicity based on the advantageous commodity attributes of traceable pork, carrying out food safety knowledge popularization education, and enhancing consumers' risk perception and food safety identification ability. [ABSTRACT FROM AUTHOR]

To reduce financial pressure and operational risk, and improve match between supply and demand, an increasing number of enterprises are adopting presales to launch new products. In this context, this paper investigates three presale models for innovative products, namely, the no-presale model, the manufacturer presale model and the retailer presale model. A Hotelling model is used to describe the impact of channel preferences and valuation differences on the two-stage competition between innovative products. Aiming at evaluating the purchase behavior of consumers under three presale modes, a game optimization model is established to analyze the presale decision problem for innovative products under different presale entities. The research shows that: (1) Compared with no-presale, presales can help enterprises obtain more profits. The overall profit of the supply chain is optimal under the retailer presale mode. (2) When the difference in channel preferences is small, the manufacturer obtains the greatest profit by choosing the direct presale model. In contrast, the selection of different presale entities has a significant impact on product sales and supply chain enterprise profits. At this point, the manufacturer should choose the retailer presale model. (3) When the product valuation discount is high, the manufacturer can increase the spot and wholesale prices to induce consumers to choose the presale method to purchase the product. In the opposite situation, the manufacturer should lower the presale price to improve the presale utility of consumers and encourage them to participate in the presale. These conclusions provide more targeted suggestions for enterprises to formulate presale strategies, which can help them grasp market demand and improve market competitiveness. [ABSTRACT FROM AUTHOR]

Innovative products entering the market will cause dynamic changes in market demand, and consumers' purchase regret and their return behavior make the market environment more and more complex, which in turn affects the dynamic decision-making in the supply chain. In this paper, under the situation of discrete decision time, combining with the objective reality, we make discrete modification to the classical Bass diffusion model (Bass model), construct a manufacturer-led, retailer-followed supply chain differential game model, analyze the optimal decision-making of the manufacturer and the retailer by combining with the theory of discrete optimal control, and then verify the conclusions by numerical simulation. The results show that: when retailers purchase directly from the manufacturer and sell in the market, the optimal pricing of the innovative product can make the supply chain as a whole, realizing Pareto optimality; consumer's purchase regret will increase the amount of returns, which will lead to the decrease of product sales and the profits of the manufacturer and the retailer; when the innovative product accounts for a different share of the market, the impact of purchase regret on the wholesale price and the retail price are also different. Therefore, manufacturers need to have an extensive comprehension of the market to minimize the negative effects of consumer regret and returns, and to formulate a reasonable pricing strategy for their products to gain as much profit as possible., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Mu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Major product safety incidents often cause widespread concern among consumers, and these product safety incidents will stimulate consumers' psychology, change their risk perception, and affect the demand for products and services of risk consumers. The change in consumer demand will eventually lead to a change in firm innovation decisions. Using Chinese firm-level data, this paper employs the news reporting of the Bawang event as a quasi-natural experiment to study the impact of risk perception changes on innovation. The empirical results of this study show that increasing consumers' risk perception caused by the negative news coverage of defective products motivates firms to increase their innovation. The effects are heterogeneous, where firms with private ownership and in developed regions are more likely to increase innovation activities. This study suggests that the relationship between consumers' risk perception and firm innovation is primarily driven by market demand. Moreover, the positive effects of risk perception on innovation are more prominent for downstream firms and those having a smaller technological distance., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Cao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

In the era of the rapid development of e-commerce, many retailers choose to launch promotional activities to become consumers' first choice for shopping. Since price discounts can greatly attract consumers, the e-commerce platforms have also begun to implement discount pricing. It is urgent for e-commerce platforms and retailers to formulate reasonable discount strategies to achieve sustainable business. In this paper, we construct a dynamic game model for implementing discount pricing on an e-commerce platform and two retailers, we study the market equilibrium between the two retailers and the e-commerce platform under various scenarios that considering consumers' strategic waiting behavior and competition between the two retailers, we further discuss the effectiveness of retailer discount pricing and the double discount pricing of the platform and retailers. We show that the optimal pricing decreases as the difference in product quality narrows under both pricing strategies. Low-quality retailers implementing a double discount pricing strategy are in relatively higher demand only when the difference in product quality is small. High-quality retailers implementing the retailer discount pricing strategy are in relatively higher demand only when the product quality difference is large. Double discount pricing is desirable for both e-commerce platforms and retailers and can be used to effectively achieve Pareto improvement in the market by increasing their expected profit. Our results emphasize the role of product quality and the value of the double discount pricing strategy. The double discount pricing strategy weakens the profit advantage that retailers and platforms gain from it as the rebate intensity and rebate redemption rates increase., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Li, Chen. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The paper aims to conduct an analysis of pricing strategies in a dual channel supply chain under external uncertainty, utilizing Interval numbers theory and Game theory as the theoretical basis. The focus is on maximizing the expected profits of manufacturers and retailers. Four models are considered: centralized decision-making, manufacturer's Stackelberg, retailer's Stackelberg strategy, and vertical Nash model, with the decision variable being the product price. By solving the game model, the paper compares the optimal decisions under the four models and conducts sensitivity analysis to reflect the influence of key parameters and analyze their relationships. The ultimate goal is to optimize profits under various circumstances by adjusting market potential and price parameters to determine the best price level. The findings suggest that decision-maker's risk indicators have a greater impact on decision results when market demand is less sensitive to price, and that the size of the market has a negative correlation with the impact of decision-maker's risk indicators on decision results., Competing Interests: The authors declared that they have no conflicts of interest to this work. We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted., (Copyright: © 2024 Zhao, Zhao. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

People are obtaining more and more information from social media and other online sources, but the spread of misinformation can lead to social disruption. In particular, social networking services (SNSs) can easily spread information of uncertain authenticity and factuality. Although many studies have proposed methods that addressed how to suppress the spread of misinformation on SNSs, few works have examined the impact on society of diffusing both misinformation and its corrective information. This study models the effects of effort to reduce misinformation and the diffusion of corrective information on social disruption, and it clarifies these effects. With the aim of reducing the impact on social disruption, we show that not only misinformation but also corrective information can cause social disruption, and we clarify how to control the spread of the latter to limit its impact. We analyzed the misinformation about a toilet-paper shortage and its correction as well as the social disruption this event caused in Japan during the COVID-19 pandemic in 2020. First, (1) we analyzed the extent to which misinformation and its corrections spread on SNS, and then (2) we created a model to estimate the impact of misinformation and its corrections on the world. Finally, (3) We used our model to analyze the change in this impact when the diffusion of the misinformation and its corrections changed. Based on our analysis results in (1), the corrective information spread much more widely than the misinformation. From the model developed in (2), the corrective information caused excessive purchasing behavior. The analysis results in (3) show that the amount of corrective information required to minimize the societal impact depends on the amount of misinformation diffusion. Most previous studies concentrated on the impact of corrective information on attitudes toward misinformation. On the other hand, the most significant contribution of this study is that it focuses on the impact of corrective information on society and clarifies the appropriate amount of it. [ABSTRACT FROM AUTHOR]

Green agriculture can minimize the negative impact of agriculture on the environment. As countries around the world strongly advocate green production and green life style, not only is consumers' awareness about green consumption rising, but the demand for green agricultural products at home and abroad is gradually increasing as well. Brand image has been a crucial factor for consumers to make their final purchasing decisions, thus playing a critical role in influencing the purchasing decisions of consumers. Based on the theory of the brand image, this paper undergoes a comprehensive theoretical and positive analysis and explores the influence mechanism of brand image of green agricultural products on consumers' purchasing intention. A hypothetical model with perceived value as mediators is constructed by us to examine the influence of brand image of green agricultural products on consumers' purchasing intention. A quantitative study was conducted for a random sample of 341 consumers who purchased green agricultural products in China according to a questionnaire-based survey using a cluster random sampling technique. The study showed that the overall image of agribusiness, the image of agricultural products, the social image of agribusiness, and the image of consumers are all positively related to consumption intention. The overall image of agribusiness, the image of agricultural products, the social image of agribusiness, and the image of consumers have a positive influence on perceived value. Moreover, perceived value plays a part in the mediating role in the influence of the overall image of agribusiness, the image of agricultural products, the social image of agribusiness, and the image of consumers on consumption intention. These findings shed lights on enterprises in establishing a scientific and effective brand strategy and building an excellent brand image. The research conclusion can provide new insight into how to enhance the consumption willingness for green agricultural products and promote sustainable development. [ABSTRACT FROM AUTHOR]

With the advancement of artificial intelligence (AI) and the Internet of Things (IoT), smart clothing, which has enormous growth potential, has developed to suit consumers' individualized demands in various areas. This paper aims to construct a model that integrates that technology acceptance model (TAM) and functionality-expressiveness-aesthetics (FEA) model to explore the key factors influencing consumers' smart clothing purchase intentions (PIs). Partial least squares structural equation modeling (PLS-SEM) was employed to analyze the data, complemented by fuzzy-set qualitative comparative analysis (fsQCA). The PLS-SEM results identified that the characteristics of functionality (FUN), expressiveness (EXP), and aesthetics (AES) positively and significantly affect perceived ease of use (PEOU), and only EXP affects perceived usefulness (PU). PU and PEOU positively impact consumers' attitudes (ATTs). Subsequently, PU and consumers' ATTs positively influence PIs. fsQCA revealed the nonlinear and complex interaction effects of the factors influencing consumers' smart clothing purchase behaviors and uncovered five necessary and six sufficient conditions for consumers' PIs. This paper furthers theoretical understanding by integrating the FEA model into the TAM. Additionally, on a practical level, it provides significant insights into consumers' intentions to purchase smart clothing. These findings serve as valuable tools for corporations and designers in strategizing the design and promotion of smart clothing. The results validate theoretical conceptions about smart clothing PIs and provide useful insights and marketing suggestions for smart clothing implementation and development. Moreover, this study is the first to explain smart clothing PIs using symmetric (PLS-SEM) and asymmetric (fsQCA) methods. [ABSTRACT FROM AUTHOR]

The Internet has become the fastest-growing way to sell luxury products. Purchase intention for luxury products in online stores has taken attention in the last few years since the sector has proliferated. The primary objective of this study is to examine the impact of various factors such as Product knowledge, Price consciousness, Perceived enjoyment, Perceived ease of usage, and usefulness on online luxury purchase intention in developing countries like Pakistan. Data was collected from 267 luxury fashion customers in Pakistan through an online questionnaire, and the results were analyzed using Smart PLS-SEM. In addition, the paper investigates the moderating effect of Perceived risk, Brand awareness and Web Atmospheric on the link between the Attitude and Online Luxury Purchase Intentions of the consumer to buy luxury fashion products online. The framework of this study is validated by structural equation modelling (SEM). The findings of this study show that perceived enjoyment, price consciousness, and Perceived ease of use significantly and positively impact online luxury purchase intention. Additionally, the findings indicated that brand awareness, perceived risk, and web atmospherics each intervened as moderators in the relationship between attitudes toward purchasing luxury products and online luxury purchase intentions. Product knowledge is not directly related to online purchase intention, but Attitude plays a mediating role in the relationship between product knowledge and online luxury buying purpose. In the context of luxury product intention, this study is one of the first to investigate the moderating effect that brand awareness, perceived risk, and web atmospherics play. It will help luxury brands develop the right tactics for selling luxury goods online in developing countries like Pakistan., Competing Interests: NO authors have competing interests, (Copyright: © 2024 Majeed et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The world production of plastic exceeded 360 million tonnes in 2020 alone, a considerable amount of which is not properly disposed of. The significant pressures and damages posed by conventional plastic to human and environmental health suggest that alternatives are urgently needed. One of them is "bioplastic", which is defined as bio-based plastic that is (or not) biodegradable. This paper reports on a study on the perceptions of bioplastics among consumers in 42 countries to identify their levels of information and concerns. The results suggest that most respondents have positive expectations regarding the future of bioplastics to replace conventional plastics fully or partially, especially for food containers, kitchenware, and boxes and bags for packaging. They also reported that the low costs and increased availability of bioplastic products on the market are likely to be the main drivers for their wide-scale adoption. However, many participants are unsure whether they would buy bio-based and biodegradable products if they are expensive. Overall, whereas a rather positive attitude to bioplastics has been identified, greater efforts are needed to address the many information needs of consumers towards upscaling the adoption of bioplastics. Relevant policies are therefore needed to encourage investments in the large-scale manufacture and market uptake of bioplastics. The paper reports on an initial study of consumer behavior, in a sample of countries spread across all geographical regions. [ABSTRACT FROM AUTHOR]

Remanufacturing is a sustainable product reutilization strategy to realize responsible consumption and production. However, remanufacturing practice can be subject to deficient consumer perception, production capacity constraint, uncertain demand and government intervention. This paper considers outsourced remanufacturing mode to establish and investigate a remanufacturing supply chain (RSC) network consisting of multiple manufacturers, retailers and remanufacturers. Optimality conditions with RSC network members are derived utilizing variation inequality. Numerical examples based on data accumulated from a remanufacturing enterprise and questionnaire survey on consumer perception for remanufactured products, are presented to put the proposed model into practice. Influences of product heterogeneity (new and remanufactured products), consumer preference, production capacity constraint, product price competitiveness, market demand fluctuation, and government financial measures on RSC network production and pricing strategies are investigated through numerical analyses. Analytical results indicate that pricing for the remanufactured product would be equivalent to that of the new product when consumers value the remanufactured product at a relatively high level, however an excessive penchant for the remanufactured product is less profitable especially from the perspective of the remanufacturer. In general, an upper-middle level of consumer preference for the remanufactured product is the most favourable scenario. When remanufacturing industry is just emerging, a high tax will be imposed on the manufacturer to accumulate remanufacturing subsidy for the government to achieve its balanced budget. As the remanufacturing industry develops and consumer environmental awareness enhances, it is especially essential for the government to establish a levy-subsidy mechanism to maintain sustainable progress of the industry. Combining main conclusions with the background of Chinese remanufacturing industry, managerial implications are provided from respective perspectives of enterprises' remanufacturing operation, government financial regulation, and consumer awareness enhancement. The analyses and results are especially relevant as a reference for remanufacturing decision-makings as well as government financial regulations, thus enhancing production sustainability as well as environmental benefits., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Since dual channel supply chain has become one of the main modes of supply chain, its research has acquired great significance. This paper constructs a low-carbon dual channel supply chain composed of one manufacturer and one retailer. The manufacturer produces low-carbon product and high carbon product with substitution relationship. The retailer sells high carbon product in traditional channel. The manufacturer also sells low-carbon product in direct channel. The government, manufacturer and retailer conduct a three-level Stackelberg game. This paper studies the optimal decisions of the government, manufacturer and retailer under the three modes of carbon tax + subsidy, carbon tax only and subsidy only. It has been found that for social welfare, the carbon tax + subsidy model is higher than the subsidy model and carbon tax model. For manufacturer profit, the subsidy mode is the highest, followed by the carbon tax + subsidy mode. For retailer profit, the carbon tax + subsidy model is equal to the carbon tax model. The increase in the proportion of consumers who prefer high carbon product in the total market or product cost of low-carbon product, will increase the profit of traditional channel and reduce the profit of direct channel., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Xu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The effect of regret on consumers' purchasing behavior is more and more obvious. The limited pre-sale can make retailers with limited production capacity allocate two periods of stock effectively and increase their income. This paper considers the heterogeneous consumers with regret behavior in the market and constructs a model to study the retailer's optimal limited pre-sale strategy. The results show that the high price regret sensitivity negatively affects the higher price of the products in the pre-sale strategy, while the out-of-stock regret sensitivity negatively affects the retailer's profit When the production capacity is relatively low, the proportion of rational consumers is large and the high price regret sensitivity coefficient is small, the retailer should pre-sell at a limited discount and the lowest valuation, and the highest valuation is on sale, otherwise, it should be sold at a price slightly lower than the highest valuation, but when the capacity is very sufficient, the sensitive coefficient of stock-out regret is small and the proportion of rational consumers is small, the retailer should pre-sell at an unlimited premium, and a price slightly lower than the highest valuation of the pre-sale, the lowest valuation of the sale, or should be pre-sold at the highest valuation., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Jiang, Qi. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Considering the carbon emissions caused by the fresh-keeping of fresh agricultural products, this paper studied the rules of fresh-keeping decision-making in the two-echelon fresh agricultural product supply chain led by suppliers under the carbon cap-and-trade policy. In addition, we designed two contracts, cost-sharing contract and two-part pricing contract, to coordinate the supplier's fresh-keeping decision and the supply chain's revenue. The results show that: whether the carbon cap-and-trade policy is implemented or not, the higher the consumer's preference for freshness and the lower the price sensitivity coefficient of consumers, the more favorable it is for suppliers to improve their fresh-keeping efforts. Under the implementation of carbon cap-and-trade policy, suppliers' fresh-keeping efforts are only related to the carbon transaction price, not the carbon cap; the higher the carbon transaction price, the less the supplier's fresh-keeping efforts, but the more the supplier's income; the smaller the cost coefficient of carbon emission reduction and the larger the coefficient of carbon emission reduction, the more favorable it is for suppliers to increase their fresh-keeping efforts; both cost-sharing contract and two-part pricing contract can coordinate the supply chain of fresh agricultural products, but they have different application scope and coordination effect. These conclusions are of great significance to the operation and management of fresh agricultural products suppliers, the improvement of consumers' quality of life and the protection of ecological environment under carbon cap-and-trade., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Yang, Yao. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Online shopping behavior has the characteristics of rich granularity dimension and data sparsity and presents a challenging task in e-commerce. Previous studies on user behavior prediction did not seriously discuss feature selection and ensemble design, which are important to improving the performance of machine learning algorithms. In this paper, we proposed an SE-stacking model based on information fusion and ensemble learning for user purchase behavior prediction. After successfully using the ensemble feature selection method to screen purchase-related factors, we used the stacking algorithm for user purchase behavior prediction. In our efforts to avoid the deviation of the prediction results, we optimized the model by selecting ten different types of models as base learners and modifying the relevant parameters specifically for them. Experiments conducted on a publicly available dataset show that the SE-stacking model can achieve a 98.40% F1 score, approximately 0.09% higher than the optimal base models. The SE-stacking model not only has a good application in the prediction of user purchase behavior but also has practical value when combined with the actual e-commerce scene. At the same time, this model has important significance in academic research and the development of this field. [ABSTRACT FROM AUTHOR]

Drawing on a recent online survey combined with city-level data, this paper examines the impact of the COVID-19 on consumers' online food purchase behavior in the short term. To address the potential endogeneity issues, we adopt an instrumental variable (IV) strategy, using the distance from the surveyed city to Wuhan as the instrumental variable. We show that our IV method is effective in minimizing potential bias. It is found that the share of confirmed COVID-19 cases increases the possibility of consumers purchasing food online. This is more likely to be the case for young people having a lower perceived risk of online purchases and living in large cities. Despite some limitations, this paper has policy implications for China and other countries that have been influenced by the COVID-19 epidemic. Specifically, government support and regulation should focus on (i) ensuring the safety of food sold on the internet, (ii) protecting the carrier from becoming infected, and (iii) providing financial support to the poor since they may have difficulties in obtaining access to food living in small cities. Moreover, how to help those who are unable to purchase food online because of their technical skills (e.g., the elderly who are not familiar with smart phones or the internet) also deserves more attention for the government and the public. [ABSTRACT FROM AUTHOR]

Home-purchase limit is a unique administrative housing policy of China and has non-negligible influences on the housing price. The objective of this study is to analyze the spillover effect of home-purchase limit policy on housing prices in 35 large and medium-sized cities. The panel data of these cities and the spatial Durbin model are employed in this study. The results indicate that the spillover effect of home-purchase limit policy is positive and significant in all of 35 cities. However, when we categorize these cities into high-risk, medium-risk, and low-risk based on housing price characteristics, the spillover effect of home-purchase limit policy is different. It is not significant in high-risk cities, is negatively significant in medium-risk cities, and is positively significant in low-risk cities. This paper suggests that local governments can pay more attention to the precise design and implementation of home-purchase limit policy, and maintain policy continuity to avoid further spillover fluctuations in housing prices., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Wu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The Recency, Frequency, and Monetary model, also known as the RFM model, is a popular and widely used business model for determining beneficial client segments and analyzing profit. It is also recommended and frequently used in superstores to identify customer segments and increase profit margins. Later, the Length, Recency, Frequency, and Monetary model, also known as the LRFM model, was introduced as an improved version of the RFM model to identify more relevant and exact consumer groups for profit maximization. Superstores have a varying number of different products. In RFM and LRFM models, the relationship between profit and purchased quantity has never been investigated. Therefore, this paper proposed an efficient customer segmentation model, namely LRFMV (Length, Recency, Frequency, Monetary and Volume) and studied the profit-quantity relationship. A new dimension V (volume) has been added to the existing LRFM model to show a direct profit-quantity relationship in customer segmentation. The V stands for volume, which is derived by calculating the average number of products purchased by a frequent superstore client in a single day. The data obtained from feature extraction of the LRMFV model is then clustered by using conventional K-means, K-Medoids, and Mini Batch K-means methods. The results obtained from the three algorithms are compared, and the K-means algorithm is chosen for the superstore dataset of the proposed LRFMV model. All clusters created using these three algorithms are evaluated in the LRFMV model, and a close relationship between profit and volume is observed. A clear profit-quantity relationship of items has yet not been seen in any prior study on the RFM and LRFM models. Grouping customers aiming at profit maximization existed previously, but there was no clear and direct depiction of profit and quantity of sold items. This study applied unsupervised machine learning to investigate the patterns, trends, and correlations between volume and profit. The traits of all the clusters are analyzed by the Customer-Classification Matrix. The LRFMV values, larger or less than the overall average for each cluster, are identified as their traits. The performance of the proposed LRFMV model is compared with the legacy RFM and LRFM customer segmentation models. The outcome shows that the LRFMV model creates precise customer segments with the same number of customers while maintaining a greater profit., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2022 Mahfuza et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Previous studies reveal the limited effectiveness of benefit-based and hedonic-based product recommendations provided by online recommenders, and recommender anthropomorphism is considered a remedy. This paper aims to investigate the positive effect of anthropomorphism by involving the online recommender's perceived ability to learn as a mediator. Based on schema congruity theory, perceived benefit/hedonic appeals appropriateness is considered a dependent variable. In Study 1, subtle anthropomorphic cues within an online recommender had a positive effect on perceived benefit-appeals appropriateness through the perceived ability to learn. Study 2 demonstrated the positive relationship between perceived anthropomorphism and perceived hedonic-appeal appropriateness, with the mediating role of the perceived ability to learn. The results advance the knowledge about consumer response to online recommenders from the perspective of anthropomorphism and schema congruity theory. Marketers and consumer organizations are advised on how to deal with online recommender systems providing benefit and hedonic appeals. [ABSTRACT FROM AUTHOR]

The maturity and growth of social media have empowered online customers to generate electronic word of mouth (eWOM), on various online websites and platforms, which may influence an individual's decision-making process. This paper explores eWOM information's impact on social media users' purchase intention by applying the information adoption model (IAM) and the technology acceptance model (TAM). PLS-SEM (SmartPLS V.3.3) has been utilized to test the hypotheses using data of 432 respondents. The research findings evinced that eWOM information quality, credibility, usefulness, and ease of use have been critical in determining online consumers' intention to adopt eWOM and form purchase behavior on social media. The study's outcomes offer the marketing managers a viewpoint to realize the significance of the effect of eWOM information on online purchase intention among social media users. Furthermore, the study findings will also enlighten marketing and business managers to utilize social media websites by gauging consumer behavior and focusing on characteristics of eWOM information on social media for better consumer insights., Competing Interests: No conflict of interest among the authors.

Organic food has gained much importance due to consumers' rising environmental and health concerns. Purchase intention of organic food has been explored widely, but the repurchase intention of organic food has gained little attention among researchers. So, it has become important to explore repurchase intention among generation Z; a generation considered more educated and aware of rising environmental concerns. Generation Z is more tech-savvy and brand conscious, so its impact on repurchase intention through consumer satisfaction has been explored. The data in this paper was collected from 400 respondents through a structured questionnaire in Islamabad, Pakistan. We used the PLS-SEM approach for data analysis and results; we found that social media influence and brand purchase impact brand awareness and positively impact brand awareness on consumer satisfaction. Moreover, it is also found that consumer satisfaction positively impacts the repurchase intention of organic food. Our study found that Generation Z has a strong social media influence, so marketers' managers must consider and address the issues when consumers consider social media for their concerns and suggestion. [ABSTRACT FROM AUTHOR]

This paper constructs a profit distribution model under centralized decision-making by taking the secondary agricultural supply chain as an example. Moreover, it introduces resources and risk as two factors to form significant weights and then designs a fair profit distribution mechanism of the supply chain according to the weights. Finally, this paper solves the optimal solution of the profit distribution coefficient by using fair entropy. Research results find that the distribution according to the optimal profit distribution coefficient can maximize the profit of each actor and achieves the matching of returns and inputs. Therefore, this paper puts forward some suggestions that include establishing a precise distribution mechanism based on contracts or property rights definitions, considering the cost and importance weight of each actor's input when formulating the profit distribution coefficient, and paying attention to information sharing., Competing Interests: The authors have declared that no competing interests exist.

Chinese traditional cultural symbols possess great aesthetic and cultural value, and are widely utilized in product design. In this study, we explore the relationship between metaphor design based on traditional cultural symbols, customer experience and cultural identity, and further estimate how these three variables stimulate consumers' perceived value to generate consumers' purchase intention. Based on existing traditional cultural literature and Stimulus-organism-response theory (SOR), we proposed a theoretical research model to characterize the relationship among metaphor design based on traditional cultural symbols, customer experience, cultural identity, perceived value and consumers' purchase intention. A research survey was conducted and 262 questionnaires were collected in total with 241 valid. We used Smart PLS graph version 3.0 for data analysis. Results indicate that the cognition of metaphor design based on traditional cultural symbols and customer experience has a direct and significant impact on the emotional value thereby, eliciting consumers' purchase intention, metaphor design based on traditional cultural symbols is directly and indirectly (i.e., through customer experience or perceived value) positively associated with consumers' purchase intention, also customer experience is directly and indirectly (i.e., through perceived value) associated with consumer purchase intention, cultural identity mediates the indirect effect of customer experience and perceived value on purchase intention, the moderating role of cultural identity between customer experience and perceived value is not significant. Our findings help to expand the existing literature on consumer purchase intentions by rationally using traditional cultural symbols in the product metaphor design. [ABSTRACT FROM AUTHOR]

Sentiment Analysis (SA) is a category of data mining techniques that extract latent representations of affective states within textual corpuses. This has wide ranging applications from online reviews to capturing mental states. In this paper, we present a novel SA feature set; Emotional Variance Analysis (EVA), which captures patterns of emotional instability. Applying EVA on student journals garnered from an Experiential Learning (EL) course, we find that EVA is useful for profiling variations in sentiment polarity and intensity, which in turn can predict academic performance. As a feature set, EVA is compatible with a wide variety of Artificial Intelligence (AI) and Machine Learning (ML) applications. Although evaluated on education data, we foresee EVA to be useful in mental health profiling and consumer behaviour applications. EVA is available at https://qr.page/g/5jQ8DQmWQT4. Our results show that EVA was able to achieve an overall accuracy of 88.7% and outperform NLP (76.0%) and SentimentR (58.0%) features by 15.8% and 51.7% respectively when predicting student experiential learning grade scores through a Multi-Layer Perceptron (MLP) ML model. [ABSTRACT FROM AUTHOR]

Internet coupled with agricultural development in full swing, green agri-food product e-commerce has become a hot topic in the development of e-commerce. However, due to the seasonality, territoriality, weak quality, difference, and dispersion of agri-food products, e-commerce of green agri-food products are facing difficulties. Based on the gap between consumers' willingness and behavior to buy green agri-food products online, this paper quantitatively studied the factors that affect consumers' behavior deviation to buy green agri-food products online. The method of constructing the binary Logistic regression model was adopted, and analysis tools such as SPSS and Excel were used for analysis, to study the influence of various factors on consumers' purchase willingness and behavior. The research conclusion shows that: consumers' gender, age, understanding of online agri-food products, and monthly disposable income have a positive impact on the consistency of consumers' behavior and willingness, while the price of green agri-food products and online purchasing frequency have a negative impact on consumers' willingness and behavior of online purchasing. The results are discussed in the context of existing studies. Suggestions and research prospects are presented at the end of the article., Competing Interests: The authors have declared that no competing interests exist.

The advance selling (AS) has been widely applied in fresh industry for it can elevating the customer experience and increase flexibility thus profit for a retailer. However, the introduction of the AS will have an impact on spot market in pricing strategy, market share and the profit of the retailer. Hence, to coordinate the supply chain and improve the efficiency of the agricultural supply chain, a two-stage game theory model is constructed to analyze the effects of AS on three classic contracts: wholesale price, quantity discount and revenue-sharing contract. This paper also discusses the boundary conditions of whether a retailer should sell in advance. The conclusions of this paper are as follows: First, revenue-sharing contracts are superior to wholesale price and quantity discount contracts when retailers sell in advance, the wholesale price contract can perform better than the quantity discount contract in the presence of AS if the contract parameter is properly set. Second, a revenue-sharing contract that normally coordinates the supply chain can performs poorly when the retailer sells in advance that the social welfare would be higher if using a quantity discount contract instead. These conclusions have important implications for suppliers when retailers sell in advance. Such suppliers need to design appropriate contracts to distribute FAP that carefully take into consideration the AS activities in the market., Competing Interests: The authors have declared that no competing interests exist.

Short video platforms, which thrive along with the video-based consumption industry, have become a new channel adopted by an increasing number of enterprises to distribute products. Therefore, it is necessary to study the factors influencing the consumer's intention to re-purchase on short video platforms, which is helpful for firms to maintain their competitiveness. This paper, based on the customer value theory, seeks to establish a structural model for such factors. The intermediary effect of customer loyalty on customer satisfaction and repurchase intention of customers is also analyzed. Questionnaires were distributed and collected from users of short video platforms in China. Results show that short video content, customer experience, and perceived value have positive impacts on customer satisfaction, and customer satisfaction, along with customer loyalty, exert positive impacts on repurchase intention. Notably, customer loyalty plays an intermediary role between customer satisfaction and repurchase intention. Based on the aforesaid findings, theoretical implications are discussed and managerial implications to increase repurchase rate are offered., Competing Interests: All authors declare no conflicts of interest with respect to the authorship or the publication of this article.

The ongoing COVID-19 has led to an increase in negative emotions and health awareness among consumers. This paper discusses the emotion bias of Chinese consumers during the three periods: the pre-COVID-19 period, the COVID-19 lockdown period, and the COVID-19 normalization period. This study takes health products as the research object and crawls relevant reviews on the JD platform to classify products. The data were classified into emotion, the intensity of emotion was calculated, and the logistic regression model and variance analysis were used to analyze the difference in emotion expression. The study reveals that consumers are willing to express fear and sadness during the COVID-19 lockdown era and are willing to express like emotions before the pandemic compared to the three periods. There are also differences in the emotional intensity of different product reviews. The intensity of emotional expression is more vigorous for consumers who purchase nutritional products, while for those who purchase healthcare equipment, the intensity of emotional expression is lower. This study offers the emotion bias of consumers in response to COVID-19 to provide a theoretical basis and reference solution for implementing marketing strategies for health product companies. [ABSTRACT FROM AUTHOR]

Loot boxes are a popular mechanic within many video games, but it remains unclear if some forms of loot boxes can be seen of as gambling. However, the perspectives of players are often neglected, such as whether they see them as 'fair' game elements and how closely they feel this aligns with gambling. In this paper, we synthesise a conceptualisation for loot boxes through players' actual experience and explore if there are any parallels with gambling. Twenty-one participants who played video games took part in the research through either an interview or online survey. Thematic analysis suggested that six themes were core to exploring loot boxes: Random Chance Effects, Attitudes Towards Content, Implementation, Parallels with Gambling, Game Design, and The Player. The results suggested both indirect and direct parallels with gambling from the players experiences. Implications of game design and classifying loot boxes as gambling are discussed in relation to game design and risk factors of gambling and purchasing behaviour., Competing Interests: The authors have declared that no competing interests exist.

British supermarket-panel data suggest no increases in overall sales and purchases of alcohol following COVID-19 lockdowns, yet survey and mortality data suggest otherwise. This paper attempts to unravel the paradox. Based on purchase data of 79,417 British households from Kantar Worldpanel, we undertake controlled interrupted time series analysis of the impact of COVID-19 confinement introduced on 23rd March 2020, and variably applied during 2020, compared to purchases during 2015 to 2019 as controls. We also undertook Poisson regression analyses to estimate if changes in purchases differed by household socio-demographic and economic factors. Excess off-trade household alcohol purchases (expressed as grams of ethanol) following the introduction of confinement, were 29.2% higher (95% CI = 25.8% to 32.5%) for the post-confinement months of 2020, being larger until mid-July 2020 (37.5%, 95%CI = 33.9 to 41.26%) when pubs re-opened with restrictions, and smaller (24.6%, 95%CI = 21.6 to 27.7) thereafter. During the time of complete pub closures, and fully adjusting for no on-trade purchases, household purchases of alcohol did not change when compared with the same time period during 2015-2019 (coefficient = -0.9%, 95%CI = -5.6 to 3.8). Excess purchases from 23rd March to 31st December 2020 varied by region of Great Britain, being higher in the north of England, and lower in Scotland and Wales. Excess purchases were greater in the most deprived households, compared with the least deprived households. Excess purchases increased substantially as the amount of alcohol normally purchased by a household increased, with the top one fifth of households that normally bought the most alcohol increasing their purchases more than 17 times than the bottom one fifth of households that bought the least alcohol. That the heaviest buyers of alcohol increased their purchases the most, with some independent impact of socio-economic disadvantage, might explain why reported alcohol problems and recent alcohol-related death rates might have increased. A conclusion of this is that alcohol policy to reduce high consumption of alcohol, and the availability of help and treatment to reduce alcohol consumption become more important during extraordinary times, such as COVID lockdowns., Competing Interests: E.J.L., A.O.’D. and E.K. declare no competing interests and declare no financial relationships with any organizations that might have an interest in the submitted work in the previous three years. Within the previous five years, P.A. has received financial support from AB InBev Foundation outside the submitted work, which does not alter our adherence to PLOS ONE policies on sharing data and materials.

Economic globalization has swept the whole world. To focus on their main business, enterprises that are referred to as original equipment manufacturers (OEMs) outsource non-core production activities to contract manufacturers (CMs). By constructing a two-level supply chain consisting of two competing OEMs and one upstream CM, the strategic interaction of the OEMs between outsourcing and purchasing is studied. Specifically, the CM can offer custom- and predefined modes of original equipment manufacturing (namely, CO mode and PO mode, respectively). The former mode enables OEMs to determine product quality, while the latter only allows them to purchase from several quality configurations. The results show that, first, since the CO mode allows the adopter to lead the product design, whether to choose this mode depends on the required R&D cost. Interestingly, however, a lower R&D cost does not necessarily result in the adoption of the CO mode if the product quality difference is small under the PO mode. Second, the optimal purchasing strategy of an OEM is indifferent to the outsourcing mode (CO and PO) of its rival but significantly affected by the quality cost. However, compared to the PO mode, choosing the CO mode would cause the competitor to suffer more profit losses. Third, differing from the prior literature, this paper finds that when the downstream OEM can make quality decisions, although this may lead to profit loss of the contract manufacturer in some channels, it could benefit the CM overall., Competing Interests: The authors have declared that no competing interests exist.

Online virtual museum tours combine museum authority and an academic approach with the diversity and interactivity of online resources; such tours have become an essential resource for online scientific research and education. Many important museums around the world are developing this type of online service. Comprehensive evaluation of such tours is, however, urgently needed to ensure effectiveness. This paper establishes a heuristic evaluation scale based on the literature. Taking the online virtual tour of the Exhibition of Architecture of the Forbidden City as a case study, confirmatory factor analysis was then carried out to improve the scale. Interviews were conducted to discuss and analyze the research results. The developed evaluation scale has four dimensions: authenticity, interaction, navigation, and learning. The results from the case study showed, first, that the exhibition had visual authenticity, but the behavioral authenticity was insufficient; second, the exhibition was generally interactive, but this aspect could be improved by enriching the links; third, the lack of effective navigation design for the exhibit was the main factor affecting experience quality. Fourth, the exhibition was informative and supported learning, but needs further improvement to the quantity and quality of information provided. Finally, the interviews revealed that the online exhibition did not entirely support people of different ages and abilities, so it needs further improvement to be wholly inclusive., Competing Interests: The authors have declared that no competing interests exist.

Understanding the digital jump of bank customers is key to design strategies to bring on board and keep online users, as well as to explain the increasing competition from new providers of financial services (such as BigTech and FinTech). This paper employs a machine learning approach to examine the digitalization process of bank customers using a comprehensive consumer finance survey. By employing a set of algorithms (random forests, conditional inference trees and causal forests) this paper identities the features predicting bank customers' digitalization process, illustrates the sequence of consumers' decision-making actions and explores the existence of causal relationships in the digitalization process. Random forests are found to provide the highest performance–they accurately predict 88.41% of bank customers' online banking adoption and usage decisions. We find that the adoption of digital banking services begins with information-based services (e.g., checking account balance), conditional on the awareness of the range of online services by customers, and then is followed by transactional services (e.g., online/mobile money transfer). The diversification of the use of online channels is explained by the consciousness about the range of services available and the safety perception. A certain degree of complementarity between bank and non-bank digital channels is also found. The treatment effect estimations of the causal forest algorithms confirm causality of the identified explanatory factors. These results suggest that banks should address the digital transformation of their customers by segmenting them according to their revealed preferences and offering them personalized digital services. Additionally, policymakers should promote financial digitalization, designing policies oriented towards making consumers aware of the range of online services available. [ABSTRACT FROM AUTHOR]

When consumers are faced with the choice of competitive chain facilities that offer exclusive services, current rules do not properly describe the behavior pattern of these consumers. To eliminate the gap between the current rules and this kind of customers behavior pattern, the partially proportional rule with a threshold is proposed in this paper. A leader-follower model for discrete competitive facility location problem is established under the partially proportional rule with a threshold. Combining with the greedy strategy and the 2-opt strategy, a heuristical algorithm (GFA) is designed to solve the follower's problem. By embedding the algorithm (GFA), an improved ranking-based algorithm (IRGA) is proposed to solve the leader-follower model. Numerical tests show that the algorithm proposed in this paper can solve the leader-follower model for discrete competitive facility location problem effectively. The effects of different parameters on the market share captured by the leader firm and the follower firm are analyzed in detail using a quasi-real example. An interesting finding is that in some cases the leader firm does not have a first-mover advantage. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has had a lasting impact on many economies around the globe. One area where significant changes have been documented is consumer behavior. A questionnaire survey was carried out to understand the impact of COVID-19 on grocery purchase behavior of Canadian consumers and evaluate the permanence of these effects. With a focus on online grocery shopping, this work integrates multiple existing theories of consumer behavior to explore the influence of different factors on consumers' adoption of online mode of grocery shopping during the pandemic and their intentions to continue the use of this mode in the post-pandemic world. A total of more than 600 usable survey responses were analyzed using statistical analysis and a Logit econometrics technique. The results reveal that 72% of the survey participants had to alter their grocery shopping habits as a result of the COVID-19 pandemic; 63% of these consumers claim that the changes that occurred would prevail in the future, with no return to the "pre-COVID normal". The results also show that the pandemic resulted in significant proliferation of online grocery shopping among Canadian consumers. Further, the findings show that the important factors that explain adoption of online grocery shopping and the shift towards higher reliance on online grocery purchases in the future include the perceived threat of COVID, pre-COVID shopping habits, socio-demographic characteristics, and the variables that capture technological opportunities and abilities. [ABSTRACT FROM AUTHOR]

Usually, studies on the informal economy focus mainly upon those working in the informal economy (supply side). However, many exchanges in the informal economy are initiated by purchasers asking how much a good or service costs if paid cash in hand. Therefore, the aim of this paper is to advance understanding of who make purchases in the informal economy and the reasons of the consumers making these purchases (demand side). Two potential explanations are evaluated. Firstly, consumers are explained as rational economic actors seeking a more convenient deal or profit maximisation (i.e., lower price or better value for money), making purchases from the informal economy due to the lack of availability of the product or service they need on the formal market, or they make such purchases involuntarily, due to the lack of perfect information necessary to make a fully rational economic decision when purchasing. Secondly, the consumers are portrayed as social actors pursuing community help. Using a multilevel mixed-effects logistic regression analysis on a 2019 Eurobarometer interviews in 27 EU member states and the UK reveal how the prevalence of these motives significantly varies across populations and regions. The theoretical and policy implications of the findings are discussed in the concluding section., Competing Interests: No competing interests

Front-of-package labeling (FOPL) is a policy tool that helps consumers to make informed food choices. South Africa has not yet implemented this labeling system. The aim of this study was therefore to explore adult South African consumers' perceptions of front-of-package warning labels on foods and non-alcoholic beverages (referred to as drinks in this paper) and their insights into features that could influence the effectiveness of the warning label. Using a qualitative approach, the study purposively selected consumers diversified by urbanization, gender, socioeconomic status, and literacy. We collected data from a total of 113 participants through 12 focus group discussions. Data were systematically coded and divided into five themes namely, positive attitudes toward warning labels, perceived benefits of warning labels, perceived behavior modification, perceived beneficiaries of warning labels, and effective attributes of warning labels. Almost all participants from all socio-economic backgrounds were positive about warning labels, reporting that warning labels concisely and understandably educated them about the nutritional composition of foods. Other perceived advantages were that warning labels warn of health implications, are easily understandable and could benefit child health. Some participants anticipated that warning labels would reduce their purchases of unhealthy foods, while others thought the labels would have no effect on their purchasing habits. Participants found the warning labels attention grabbing and stated that they preferred a black triangle placed on a white background (referred to as a holding strap henceforth), the words "high in" and "warning" in bold and uppercase text, an exclamation mark, and an icon depicting the excessive nutrient. In South Africa warning labels may improve consumer understanding of nutrition information and assist consumers in determining the nutritional quality of packaged foods and drinks., Competing Interests: The authors have declared that no competing interests exist.

As the Internet retail industry continues to rise, more and more consumers choose to shop online, especially Chinese consumers. Using consumer behavior data left on the Internet to predict repurchase behavior is of great significance for companies to achieve precision marketing. This paper proposes an improved deep forest model, and the interactive behavior characteristics of users and goods are added into the original feature model to predict the repurchase behavior of e-commerce consumers. Based on the Alibaba mobile e-commerce platform data set, first construct a feature engineering that includes user characteristics, product characteristics, and interactive behavior characteristics. And then use our proposed model to make predictions. Experiments show that the model's overall performance with increased interactive behavior features is better and has higher accuracy. Compared with the existing prediction models, the improved deep forest model has certain advantages, which not only improves the prediction accuracy but also reduces the cost of training time., Competing Interests: The authors have declared that no competing interests exist.

While there has been much speculation on how the pandemic has affected work location patterns and home location choices, there is sparse evidence regarding the impacts that COVID-19 has had on amenity visits in American cities, which typically constitute over half of all urban trips. Using aggregate app-based GPS positioning data from smartphone users, this study traces the changes in amenity visits in Somerville, MA from January 2019 to December 2020, describing how visits to particular types of amenities have changed as a result of business closures during the public health emergency. Has the pandemic fundamentally shifted amenity-oriented travel behavior or is consumer behavior returning to pre-pandemic trends? To address this question, we calibrate discrete choice models that are suited to Census block-group level analysis for each of the 24 months in a two-year period, and use them to analyze how visitors' behavioral responses to various attributes of amenity clusters have shifted during different phases of the pandemic. Our findings suggest that in the first few months of the pandemic, amenity-visiting preferences significantly diverged from expected patterns. Even though overall trip volumes remained far below normal levels throughout the remainder of the year, preferences towards specific cluster attributes mostly returned to expected levels by September 2020. We also construct two scenarios to explore the implications of another shutdown and a full reopening, based on November 2020 consumer behavior. While government restrictions have played an important role in reducing visits to amenity clusters, our results imply that cautionary consumer behavior has played an important role as well, suggesting a likely long and slow path to economic recovery. By drawing on mobile phone location data and behavioral modeling, this paper offers timely insights to help decision-makers understand how this unprecedented health emergency is affecting amenity-related trips and where the greatest needs for intervention and support may exist., Competing Interests: The authors have declared that no competing interests exist.

Increased availability of epidemiological data, novel digital data streams, and the rise of powerful machine learning approaches have generated a surge of research activity on real-time epidemic forecast systems. In this paper, we propose the use of a novel data source, namely retail market data to improve seasonal influenza forecasting. Specifically, we consider supermarket retail data as a proxy signal for influenza, through the identification of sentinel baskets, i.e., products bought together by a population of selected customers. We develop a nowcasting and forecasting framework that provides estimates for influenza incidence in Italy up to 4 weeks ahead. We make use of the Support Vector Regression (SVR) model to produce the predictions of seasonal flu incidence. Our predictions outperform both a baseline autoregressive model and a second baseline based on product purchases. The results show quantitatively the value of incorporating retail market data in forecasting models, acting as a proxy that can be used for the real-time analysis of epidemics., Competing Interests: The authors have declared that no competing interests exist.

This paper examines long-term developments in stadium attendance in professional football in the Netherlands. As in many other European countries attendance had a U-shaped development with the lowest numbers in the mid-1980s. The developments in the Netherlands do not seem to have been affected by hooliganism but by socioeconomic factors. Furthermore, the association with stadium attendance in other European leagues in particular the English Premier League is very high. This suggests that stadium attendance is affected not only by national developments but also by common international trends in the interest in football matches., Competing Interests: I do not have competing interests.

The Data Availability link for this paper is incorrect. The correct link is: https://www.researchgate.net/publication/361344644%5fdata%5ffor%5fthe%5freusable%5ftableware%5fpackagingBy Chao Gu; Jiangjie Chen; Wei Wei; Jie Sun; Chun Yang; Liao Jiang; Jingyue Hu; Baiwan Lv; Shuyuan Lin and Qianling JiangReported by Author; Author; Author; Author; Author; Author; Author; Author; Author; Author [Extracted from the article]

Background: Taxes on sugar-sweetened beverages (SSBs) have been implemented globally to reduce the burden of cardiometabolic diseases by disincentivizing consumption through increased prices (e.g., 1 peso/litre tax in Mexico) or incentivizing industry reformulation to reduce SSB sugar content (e.g., tiered structure of the United Kingdom [UK] Soft Drinks Industry Levy [SDIL]). In Germany, where no tax on SSBs is enacted, the health and economic impact of SSB taxation using the experience from internationally implemented tax designs has not been evaluated. The objective of this study was to estimate the health and economic impact of national SSBs taxation scenarios in Germany. Methods and findings: In this modelling study, we evaluated a 20% ad valorem SSB tax with/without taxation of fruit juice (based on implemented SSB taxes and recommendations) and a tiered tax (based on the UK SDIL) in the German adult population aged 30 to 90 years from 2023 to 2043. We developed a microsimulation model (IMPACTNCD Germany) that captures the demographics, risk factor profile and epidemiology of type 2 diabetes, coronary heart disease (CHD) and stroke in the German population using the best available evidence and national data. For each scenario, we estimated changes in sugar consumption and associated weight change. Resulting cases of cardiometabolic disease prevented/postponed and related quality-adjusted life years (QALYs) and economic impacts from healthcare (medical costs) and societal (medical, patient time, and productivity costs) perspectives were estimated using national cost and health utility data. Additionally, we assessed structural uncertainty regarding direct, body mass index (BMI)-independent cardiometabolic effects of SSBs and cross-validated results with an independently developed cohort model (PRIMEtime). We found that SSB taxation could reduce sugar intake in the German adult population by 1 g/day (95%-uncertainty interval [0.05, 1.65]) for a 20% ad valorem tax on SSBs leading to reduced consumption through increased prices (pass-through of 82%) and 2.34 g/day (95%-UI [2.32, 2.36]) for a tiered tax on SSBs leading to 30% reduction in SSB sugar content via reformulation. Through reductions in obesity, type 2 diabetes, and cardiovascular disease (CVD), 106,000 (95%-UI [57,200, 153,200]) QALYs could be gained with a 20% ad valorem tax and 192,300 (95%-UI [130,100, 254,200]) QALYs with a tiered tax. Respectively, €9.6 billion (95%-UI [4.7, 15.3]) and €16.0 billion (95%-UI [8.1, 25.5]) costs could be saved from a societal perspective over 20 years. Impacts of the 20% ad valorem tax were larger when additionally taxing fruit juice (252,400 QALYs gained, 95%-UI [176,700, 325,800]; €11.8 billion costs saved, 95%-UI [€6.7, €17.9]), but impacts of all scenarios were reduced when excluding direct health effects of SSBs. Cross-validation with PRIMEtime showed similar results. Limitations include remaining uncertainties in the economic and epidemiological evidence and a lack of product-level data. Conclusions: In this study, we found that SSB taxation in Germany could help to reduce the national burden of noncommunicable diseases and save a substantial amount of societal costs. A tiered tax designed to incentivize reformulation of SSBs towards less sugar might have a larger population-level health and economic impact than an ad valorem tax that incentivizes consumer behaviour change only through increased prices. In a modeling study, Karl MF Emmert-Fees and team estimate the health and economic impact of national sugar-sweetened beverages taxation scenarios in Germany. Author summary: Why was this study done?: Taxation of sugar-sweetened beverages (SSBs), recommended by the World Health Organization (WHO) and implemented in many jurisdictions globally, aims to reduce the noncommunicable disease burden by disincentivizing consumption through increased consumer prices or incentivizing industry reformulation to reduce SSB sugar content. No tax on SSBs is currently enacted in Germany and the national government is preparing a new national strategy on food seeking evidence-based recommendations to establish policy priorities until 2050. In Germany, the potential long-term health and economic impacts of SSB taxation have not been evaluated. What did the researchers do and find?: We developed and validated a microsimulation model based on national data and international evidence to model the impact of SSB taxation on dietary exposure of added sugar from beverages, body mass index (BMI), cardiometabolic diseases, and related economic costs. We evaluated 3 SSB taxation scenarios in Germany with the simulation model: (1) 20% ad valorem tax on SSBs; (2) extended 20% ad valorem tax on SSBs and fruit juice; (3) tiered tax leading to reformulation of SSBs towards 30% lower sugar content. Taxation of SSBs in Germany could prevent or postpone 132,100 to 244,100 cases of type 2 diabetes, gain 106,000 to 192,300 quality-adjusted life years (QALYs) and save €10.8 to €16.0 billion in societal cost from 2023 to 2043 with the highest impacts estimated for tiered taxation. The absolute long-term health impacts are largely dependent on the relevance of direct, BMI-independent cardiometabolic effects of SSBs. What do these findings mean?: All modelled SSB taxation scenarios are likely to improve population health and reduce societal costs in Germany by preventing cardiometabolic disease. Considering all sources of uncertainty, we find that modelled SSB taxation scenarios that lead to reformulation towards less sugar might have a larger population-level health and economic impact than those that incentivize consumer behaviour change only through increased prices. From a public health perspective, taxation of SSBs should be considered as a policy option for German decision-makers to reduce consumption of added sugar and improve population health. [ABSTRACT FROM AUTHOR]

In this paper, the authors use survey data from over 800 households to examine the impact of demonstration plots and associated activities (distribution of small packs of agricultural inputs) on smallholder farmers' decisions to buy agricultural inputs in Tanzania. Using propensity score matching and inverse probability-weighted adjustment models, the authors estimated the effect of access to demonstration plots alone and demonstration plots combined with small packs of agricultural inputs on a household's decision to purchase improved inputs. The results indicate that access to demonstration plots and demonstration plots with small packs increased the probability of purchasing improved inputs by 13-17 percentage points. This paper suggests that demonstration plots and demonstration plots with small packs are an effective model for enhancing improved technology adoption and are further increased when those inputs are available within a 5km radius. The results point to the importance of strengthening farmers' organizations and last-mile agricultural input suppliers in order to enhance and facilitate access to information, appropriate production techniques, and improved inputs. The results also indicate the importance of investing in infrastructure to reduce transportation costs that limit market efficiency for appropriate technologies., Competing Interests: The authors have declared that no competing interests exist.

The Supplemental Nutrition Assistance Program (SNAP) provides millions of low-income Americans food benefits and other forms of nutrition assistance. Evidence indicates that SNAP reduces food insecurity. However, there is a concern that the food benefit may increase the demand for less healthy foods more than healthier foods, thereby reducing the overall nutritional quality of the participant's food basket. This paper aims to examine the association of SNAP participation with the nutritional quality of food-at-home purchases of low-income households and to investigate the potential heterogeneity among consumers with different levels of nutrition attitude. This analysis used food purchase data from the USDA National Household Food Acquisition and Purchase Survey (FoodAPS). Our study sample included 2,218 low-income households, of which 1,184 are SNAP participants, and 1,034 are income-eligible nonparticipants. Multivariate regressions were performed to explore the SNAP-nutritional quality association. A household's nutrition attitude was measured using its response to a question on whether the household searched for nutrition information online in the last 2 months. Households that affirmed they had an online nutrition search were treated as nutrition-oriented households (21.2% of the low-income sample), and households that did not were considered less nutrition-oriented households (78.8%). For robustness, we also created an alternative nutrition attitude measure based on reported use of the nutrition facts label. We found that among less nutrition-oriented households, SNAP participants had a statistically significant 0.097 points (p = 0.018) lower Guiding Stars rating than low-income nonparticipants. However, there was no significant SNAP-nutritional quality association among nutrition-oriented households. In conclusion, SNAP participation was associated with lower nutritional quality of food purchases among less nutrition-oriented households, but not among nutrition-oriented households. The results suggest that the intended nutritional benefits of restrictions on purchases of healthy foods may not reach the subgroup of nutrition-oriented SNAP participants., Competing Interests: The authors have declared that no competing interests exist.

The prediction of web service quality plays an important role in improving user services; it has been one of the most popular topics in the field of Internet services. In traditional collaborative filtering methods, differences in the personalization and preferences of different users have been ignored. In this paper, we propose a prediction method for web service quality based on different types of quality of service (QoS) attributes. Different extraction rules are applied to extract the user preference matrices from the original web data, and the negative value filtering-based top-K method is used to merge the optimization results into the collaborative prediction method. Thus, the individualized differences are fully exploited, and the problem of inconsistent QoS values is resolved. The experimental results demonstrate the validity of the proposed method. Compared with other methods, the proposed method performs better, and the results are closer to the real values., Competing Interests: The author(s) received no specific funding for this work.