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This paper deals with the complex relationship between innovation and the labor market, analyzing the impact of new technological advancements on overall employment, skills, and wages. After a critical review of the extant literature and the available empirical studies, novel evidence is presented on the distribution of labor-saving automation [namely robotics and artificial intelligence (AI)], based on natural language processing of US patents. This mapping shows that both upstream high-tech providers and downstream users of new technologies—such as Boeing and Amazon—lead the underlying innovative effort. [ABSTRACT FROM AUTHOR]

Eva Kocher's book, "Digital Work Platforms at the Interface of Labour Law: Regulating Market Organisers," explores the legal status and rights of digital platform workers. Kocher takes an integrative approach, combining management and organizational theories with labor law models. The book discusses worker classifications and labor law theory, as well as the unique characteristics of digital platform work. Kocher proposes the creation of an intermediate category for digital platform workers, which would provide them with labor rights and collective bargaining power. While the book is rich in theories and legal analysis, it does not fully address the power dynamics and technological aspects of digital platform work. [Extracted from the article]

In retail operations, free sample trial (FST) and product return with money-back guarantee (MBG) both serve as important strategies to reduce consumers' worries and valuation uncertainty. This paper is the first study which analytically examines when and whether an online retailer should provide both strategies simultaneously, and when one strategy outperforms the other. We consider an online retailer selling to consumers who are uncertain about the product values when making purchasing decisions. The retailer decides whether to offer MBG or FST. We develop analytical models to examine four strategies: strategy NN (both FST and MBG are not provided), strategy NS (FST is provided and MBG is not offered), strategy MN (FST is not provided and MBG is provided), and strategy MS (both FST and MBG are offered). Comparing among these four strategies, we find that when only FST is offered, the retailer surprisingly should decrease the price if the product cost is low. If the retailer only provides MBG, he will charge a higher price compared with the situation when MBG is not provided. When the size of free sample is very small, strategy NS (MS) is the optimal strategy if the product's cost is low (high). When the size of free sample is large, strategy MN is the optimal strategy. Then, we extend our model to consider three situations, namely: (a) the retailer offers coupons to consumers to experience the free sample, (b) consumer returns incur a cost, and (c) the size of free sample is endogenous. We find the main conclusion remains robust. Our findings may help explain some real-world practices, such as why some retailers (e.g., Amazon and Walmart) provide consumers with low volume toners to decrease the free sample cost; skincare product retailers such as Lancôme, Estee Lauder, and Guerlain implement both MBG and FST. We also interestingly show that a bigger size of free sample may not necessarily benefit consumers. [ABSTRACT FROM AUTHOR]

The existing graph neural network sequence recommendation methods only focus on the temporal information of sequences without considering the time interval information of sequences, and only use single-task mode for sequence recommendation, ignoring the auxiliary tasks that can enhance the data and improve the generalization ability, which will lead to the dynamic interaction preferences of users and interaction time information cannot be captured clearly. To alleviate the impact of these problems, a dynamic graph neural network sequence recommendation algorithm with enhanced time awareness (TaDGSR) is proposed, which has two advantages. Firstly, the method constructs a sequence as a dynamic graph with temporal information, incorporates time interval information and adds a time-gated attention network module to enhance the utilization of temporal information while capturing the higher-order dynamic connections between sequences. Secondly, the method adopts the long short-term prediction task with temporal threshold segmentation as its auxiliary task to enhance the utilization of temporal interval information representation, so that the model can better capture the dynamic preferences of users at different interaction intervals, and finally improve the performance of the sequence recommendation task. Experiments on the Beauty dataset, Games dataset, and CDs dataset of Amazon.com show that: (1) the proposed method achieves average improvements of 4.47%, 4.37%, 2.72%, 1.16%, 4.61% and 3.97% in the Hit@10 and NDCG@10 metric values for the three datasets, respectively, compared to the current newer benchmark method; (2) adding time interval information can effectively improve the recommendation performance of dynamic graph neural networks, and the use of a time-gated attention module and a long- and short-term prediction assistance task can both bring positive improvements to the prediction performance. [ABSTRACT FROM AUTHOR]

Tech media giants are no strangers to controversy in relation to the payment of corporate tax, such as the cases of Apple and Facebook (Meta) in Ireland, Alphabet (Google) in the UK and Amazon in Luxembourg. While the tech media giants are not the only global corporations that take advantage of international tax avoidance opportunities, this paper argues that their hypermobility and unprecedented cash assets place them especially well to take advantage of these practices. Moreover, the nature of some of the commodities, such as information, software or intellectual property that can be moved at the touch of a button; or even a simple re-conception of where the property resides can mean a state gaining or losing billions of dollars. This paper will explore how tech media giants are redefining property and commodity forms and how this allows for creative tax policies. Moreover, the conception of where immaterial commodities, such as pure information, is located (or not located) challenges tax collection strategies for the state. To explore these conceptions, this paper discusses the ideology surrounding the tech media industry, a particular brand of liberalism coined the 'Californian Ideology': An ideology that can sometimes be described as transgressive, but also one that may legitimise tax avoidance. The ideology gives a somewhat nebulous definition of what property is (and isn't) and its location or non-location, thereby negating justification for taxation. [ABSTRACT FROM AUTHOR]

Copyright of Retos: Nuevas Perspectivas de Educación Física, Deporte y Recreación is the property of Federacion Espanola de Asociaciones de Docentes de Educacion Fisica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article explores how surveillance capitalism affects international studies, highlighting its impact on knowledge production, power dynamics, and the balance between human and machine learning. It examines how the commodification of data by tech giants like Google, Amazon, and Meta has altered the academic landscape, making slow, deep engagement with global issues more challenging.

Amazon, as one of the dominant online retailers (platforms), cooperates with manufacturers under wholesale contract to develop its store brands. Simultaneously, Amazon offers manufacturers with a marketplace and serves manufacturers in the agency selling. In this paper, we build a model to investigate the platform's and the manufacturer's choices on the cooperation modes (i.e., wholesale contract or agency selling) and their quality decisions when they serve consumers with heterogeneous willingness to pay for quality and the platform can dictate the quality under the wholesale contract. We find that the platform and the manufacturer are more likely to align their preferences on selling modes when consumers are homogenous enough. Moreover, when the commission rate is relatively low, both of them may prefer the agency selling. In this case, the manufacturer is willing to offer high quality in the agency selling. In contrast, when the commission rate is sufficiently high, they can only align their preferences on selling modes by choosing the wholesale contract. The product quality under the wholesale contract is higher than that in the agency selling. Finally, we provide three extensions: the platform decides the commission rate, the platform decides the wholesale price and competition between manufacturers. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) technologies have been increasingly developed and applied in the audiovisual sector. Over-the-top (OTT) services, directly distributed to viewers via the Internet, are associated with a shift towards automation through algorithmic mediation in audiovisual content led by digital platforms. However, scientific knowledge regarding algorithmic recommender systems and automation in OTT services is not yet systemized; researchers, practitioners, and the public thus lack full awareness about the still largely opaque phenomena. To address this gap, we conduct a systematic literature review in the communication domain (2010–2022) and answer four key research questions: What research objectives have been pursued? What concepts have been developed and/or applied? What methodologies have been privileged? Which OTT platforms have received the most research attention? Challenges and opportunities are highlighted, and an agenda for future research is advanced. [ABSTRACT FROM AUTHOR]

The five largest firms by market capitalization, Alphabet, Amazon, Apple, Meta, and Microsoft have massively acquired companies during the last decades, mainly but not exclusively young tech startups. Interestingly, most of the acquired products are discontinued post-acquisition. In this paper, we have collected data on the acquisitions of the big techs for a period of 7 years spanning from 2015 to 2021 and we analyze the evolution of the acquired firms' products post-acquisition. To analyze the decision to continue or not a product post-acquisition, we classify acquisition in four categories: products that are still offered under their initial brand name, products integrated in the acquirer's ecosystem, products that are no longer available and products that are killed by the acquirer. We use these classifications to provide detailed information and statistics on the discontinuation decision of the acquiring firm and we run Probit estimation to explain their determinants. [ABSTRACT FROM AUTHOR]

Amazon seems to be creating a new hybrid model of capitalism combining some elements of classical Fordist vertical integration, or even the over hundred-year-old "Taylorism" of scientific management, with 21st century elements of labor "flexibility" and reliance on gig labor and subcontracting. This hybrid model offers opportunities for organized labor to gain a foothold within some of Amazon's vertically integrated nodes as the firm lengthens its corporate commodity chain to grow increasingly close to consumers. Building on earlier work on opportunities for, and constraints on, labor in a variety of global commodity chains, our empirical cases examine how Amazon's corporate strategies may open opportunities for labor in three illustrative cases ensconced in fulfillment centers—the Fordist vertical integration side of the model—in the Inland Empire and Otay Mesa (both in southern California) and Northern Kentucky. [ABSTRACT FROM AUTHOR]

This paper examines the antitrust investigations by the European Commission (AT.40703 – Amazon Buy Box) and Italian Competition Authority (A528-FBA AMAZON), and the regulatory proceeding by the Italian Authority for Communications and Postal Services (AGCom's resolution 94/22/CONS), surrounding Amazon's Store, and the interplay with its logistics and delivery services. While these authorities have raised concerns about Amazon's alleged "self-preferencing", rapid growth, and its alleged ability to leverage its (upstream) e-commerce market power to strengthen its position in (downstream) logistics services, this paper highlights alternative perspectives that are often overlooked or neglected. To achieve a comprehensive understanding of Amazon's conduct related to the above-mentioned investigations, we consider its business model, monetisation strategy, and underlying incentives. By delving deeper into the Amazon Store and its connection to logistics services, we argue that the allegations do not fully capture the evidence surrounding Amazon's practices. [ABSTRACT FROM AUTHOR]

Increasing market concentration has become a topical issue in competition law worldwide. This article explores how firms, especially digital platform businesses, increase market concentration which may facilitate entrenched market power and anti-competitive conduct in their upstream or downstream markets. It considers in an Australian context two specific ways in which the power of a dominant firms including digital platforms may be constrained. The first is allowing the parties with lesser market power to collectively bargain, which can redress the imbalance in bargaining power to make the market work more effectively. A second and related option is the introduction of mandatory codes of conduct, which may be suitable in markets where perennial problems with market power imbalances exist. Australian experience suggests that these options can assist markets to function more effectively, and they may provide additional flexibility for other jurisdictions. [ABSTRACT FROM AUTHOR]

Background: Sporotrichosis is the most common subcutaneous mycosis caused by Sporothrix spp. Traditionally, it is transmitted through injuries involving plant debris. However, over the past few decades, there has been an epidemic increase in human cases resulting from contact with infected animals, particularly cats, in various regions of Brazil. In this report, we report a notable increase in both human and animal cases within the Brazilian Amazon state. Methodology/Principal findings: An ecological study was conducted by analyzing official records of human and animal sporotrichosis diagnosed in the state of Amazon from 2020 to 2023. Data including patient demographics, clinical manifestations, mycological examination results, and species identification through PCR confirmation were evaluated. During this period, a total of 950 human cases and 2,823 animal cases of sporotrichosis were reported at an exponential rate, since no human cases were registered in 2020. The spatial and temporal dispersion of human sporotrichosis followed that of animal cases, moving from downtown areas to the periphery. Contact with infected animals was reported in 77.7% of cases, with cats being the most commonly implicated (73.5%). Only 66.7% of individuals underwent mycological examination. Among the positive cultures for Sporothrix spp., 65.4% were identified as S. brasiliensis. All patients were treated with systemic antifungals. Conclusions/Significance: This study highlights a rising incidence of sporotrichosis among animals and humans in the Brazilian Amazon region over the past four years, with S. brasiliensis being the predominant agent. Collaborative efforts involving healthcare professionals, veterinarians, and public health authorities are crucial to implement effective control measures, educate populations at risk, and promote responsible guidance for pet guardians. These measures are essential to mitigate the burden of epidemic sporotrichosis in Brazil. Author summary: Sporotrichosis is the leading subcutaneous mycosis worldwide. In the last decades, Brazil has faced an epidemic of zoonotic cases. The Brazilian Amazon region had no human cases reported in 2020, nevertheless, a striking rise in both human and animal cases was observed from 2020 to 2023, totalizing 950 human and 2,823 animal sporotrichosis. The majority of cases were reported in Manaus, the largest city in the Amazon, but cases were also documented in other populous municipalities. The study emphasizes the correlation between animal and human cases, as well as the spatial and temporal progression of the disease, moving from downtown areas to the periphery. Cats were identified as the primary reservoirs, with contact with infected animals being a significant risk factor for transmission. Urban areas, particularly domestic environments, were identified as common sites of infection. The predominant species identified was Sporothrix brasiliensis, which exhibits distinct characteristics favoring zoonotic transmission. This study emphasizes the urgent need for collaborative efforts among healthcare professionals, veterinarians, and public health authorities to implement effective control measures and mitigate the impact of the epidemic sporotrichosis in Brazil. [ABSTRACT FROM AUTHOR]

Aims: The objective was to validate the initial beam parameters of the Davao Doctors Hospital's 6 MV Elekta Synergy Platform linac, which performs to the specification of the commissioning data per our records using the gamma-index analysis toolkit integrated inside PRIMO software. Materials and Methods: In PRIMO, a sequence of optimization processes is performed, in which the measured and simulated percent depth dose (PDD) and lateral beam profiles at various depths are compared, using the stringent gamma-index passing rate at 1%/1 mm criteria (GPR11). Using four fields of sizes 3 cm x 3 cm, 4 cm x 4 cm, 5 cm x 5 cm, and 10 cm x 10 cm, the dose is calculated on a water phantom measuring 16.2 cm x 16.2 cm x 30.0 cm. In addition, one field of size 20 cm x 20 cm is used on a 50.0 cm x 50.0 cm x 30.0 cm water phantom with a bin size of 0.2 cm x 0.2 cm x 0.2 cm at a source-surface distance of 100.0 cm. Results: For PDD and beam profiles comparison at the largest field size, the 6.5 MeV initial electron beam energy, 0.25 MeV full-width-half-maximum energy, 0.20 cm focal spot size, and 3° beam divergence tuned configuration yield GPR11 values of 94.0% and 97.7% (PRIMO PDD and lateral beam profile at 200 mm scan depth, respectively) with a statistical uncertainty of 2.9%. For lower field sizes, the GPR11 values are consistent at more than 90% for the PDD, whereas GPR11 values of 80.3% and 70.6% for the lateral beam profiles (at 15 mm and 200 mm scan depths) at 10 cm x 10 cm and 5 cm x 5 cm, respectively. The percentage difference between the measured and simulated PDD20,10 ratios of not more than 2.45% is observed in all field settings. Conclusions: These tuned beam parameters are remarkably in agreement with the suggested beam parameters listed on the PRIMO website for the 6 MV Elekta linac which was optimized with a different set of measurements. [ABSTRACT FROM AUTHOR]

Purpose: Purpose: The main purpose of the study is to understand the factors that facilitate correction behavior among individuals. In this study the authors examine the impact of self-perceived media literacy (SPML) and reflection on participants' correction behavior. Design/methodology/approach: Methods: Data for the study were collected from Amazon's MTurk using an online survey. Data were collected after a certificate of exemption was received by the Institutional Review Board in a research university in the United States (US) Qualtrics software was used to collect data. The total number of participants was 797. Findings: Findings: The findings show that although both SPML and reflection are positively associated with rumor refutation, higher SPML alone is not enough. Reflective judgment is critical for individuals to take part in this behavior online, such that individuals with higher reflective judgment indicated that they refute rumors online, irrespective of their SPML score. Originality/value: Originality: The authors tested the relationship of multiple variables with participants correction behavior. Although research shows the importance of social correction, there is not much knowledge about what facilitates actual misinformation correction. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to investigate the extent and pattern of the influence of one of the most important decision-making tools in the context of social commerce. This study demonstrates how much customer testimonials (including verified purchases and ordinary users) can influence the sales rank of experience and search goods. Design/methodology/approach: The data were collected by text mining and performing a content analysis on the XML documents of Web pages and processing them. For search goods, 22,311 opinions were recorded regarding 95 mobile phones. Additionally, for experience goods, 67,817 opinions were recorded regarding 162 books in the Amazon online store. The data were analyzed by functional regression method in longitudinal data analysis. Findings: In terms of importance, the opinions and recommendations of verified purchases had a 60% greater impact on the sales rank of experience goods than the opinions and recommendations of ordinary users. In search goods, the opinions of ordinary users had a greater impact than the opinions of verified purchases. The historical effect of the opinions of ordinary users at the end of the review period on sales rank was evident, while the historical effect of the verified purchase viewpoints during the review period had a nonlinear curve. The results showed that it was necessary to increase the volume of comments to increase their reliability in experience goods. Practical implications: Measuring the effect of customer testimonials helps the managers of retail websites design algorithms and online suggestion systems, thereby improving the sales of their products by providing information desired by customers. Social implications: Individuals can be a source of information and influence the buying decision process of others by sharing their experiences. This issue helps reduce the purchase risk and explains the importance of interaction and sharing the customer's experience. Originality/value: Analyzing the impact of customer testimonials by separating verified purchases and ordinary users is one of the advantages of this study. The quantitative estimation of the impact of recommendations and the provision of a model of their historical effect is one of the approaches not addressed in similar studies. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper was to examine consumer perceptions of aesthetic attributes of textile-based assistive devices (ADs) and the language used by consumers to express those perceptions and concerns. Previous investigations of user feedback for ADs have largely focused on functional attributes rather than aesthetics. Design/methodology/approach: An interpretivist research philosophy was selected to investigate the meaning behind consumer perceptions and to understand their viewpoints on the aesthetic dimensions of ADs. Using product reviews for two ADs sold on Amazon.com as data, the researchers conducted qualitative data analysis through coding and interpretation of meanings behind reviews to determine consumers' perceptions related to their ADs. Findings: The authors identified consumer concerns linking to aesthetics evidenced as a multisensory integration of visual, tactile and olfactory cues. Consumer-preferred language used to address aesthetic preferences was found to supplement the literature. Aesthetic considerations were found to be impactful on avoiding stigma and encouraging or discouraging continued use of the devices. Practical implications: Findings may contribute to the development of textile-based ADs with improved aesthetics to enhance user experiences. New ways of using consumer language to interpret user needs may assist in future research and design practice for consumer products. Originality/value: The use of consumer product reviews as a rich source of user data is discussed in this paper. As previous research on assistive technology has largely focused on functionality, results of this analysis offer insight into consumers' aesthetic judgments related to ADs and bring a sensory perspective to the research area. [ABSTRACT FROM AUTHOR]

The beauty products and cosmetics sector in India has grown rapidly due to shifting customer preferences and a greater focus on personal grooming. With the continued growth in sales of beauty products, it is critical for firms looking to succeed in this cutthroat industry to comprehend the dynamics of customer ratings and how they affect the quality of their products. Firstly, this study identifies major trends, obstacles, and possibilities influencing the nexus between artificial intelligence and the Indian beauty goods market by utilizing the body of current literature and empirical data. Secondary data is used in this research, two Kaggle datasets--Amazon Beauty Product Sales Rating and Amazon Beauty Product Recommendation--are analyzed in this study. We seek to provide insight on the complex relationship between customer ratings and product quality and how these aspects affect the success of beauty goods in the Indian market by contrasting these datasets. The objective of this study is to stimulate advancements in the domain of beauty product sales in India by establishing a connection between theoretical research and operational implementations. In the conclusion, our summary of the literature seeks to guide future initiatives focused at leveraging AI to promote innovation, growth, and sustainability in the ever-changing Indian beauty goods sector. The research's conclusions have ramifications for Indian consumers and producers of cosmetic products. This study has results for Indian consumers as well as cosmetic product manufacturers. Customer feedback may provide manufacturers with strategic insights to improve the quality of their products, and customers can use it to make well-informed decisions that suit their tastes. In the end, this research adds to the larger conversation on the dynamics of consumer happiness and product quality in India's thriving beauty and cosmetics industry. [ABSTRACT FROM AUTHOR]

Copyright of Anuario Electrónico de Estudios en Comunicación Social 'Disertaciones' is the property of Colegio Mayor de Nuestra Senora del Rosario and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: Chewy, Inc. is a direct-to-consumer seller of pet food and supplies. Their approach involves a deep understanding of pet owners' needs and behaviors to provide personalized product recommendations and exceptional customer service. This case study aims to describe Chewy's growth strategies and how the company can remain a market leader. Design/methodology/approach: Using the customer value assessment tool, the authors examine Chewy's value proposition, including service, quality, image and price strategies. Findings: Chewy has built a loyal customer base that values the company's commitment to their pets' health and well-being. Future opportunities include focusing on pet wellness products and services, collaborating with veterinary providers in telemedicine and international expansion. Research limitations/implications: This work is largely conceptual and presents a descriptive case study which reviews Chewy's marketing strategy based on industry research as well as a customer value assessment via the service-quality-image-price framework. Practical implications: Corporate leaders must adapt to market change and create business strategies to deliver superior value for customers. This requires innovative products, services and processes. The strategic insights are applicable to retailers, service and technology firms and entrepreneurial companies seeking to scale their businesses. Originality/value: Chewy's highly competitive market includes Amazon, e-commerce pet supply companies and big-box pet stores. But it has dominated the online sector and has substantial growth prospects. This paper concludes with recommendations for management and questions for consideration. [ABSTRACT FROM AUTHOR]

This paper investigates the (un)making of borders as a form of labour governmentality in one of Amazon's warehouses in Poland. Guided by a critical theory of borders as a form of labour governmentality under global capitalism, we identify organizational practices through which socio-demographic categories traditionally deployed as principles of organizing work (e.g., gender, age, ability) are un made: the management of deskilled labour through an algorithmic system, the non-selective hiring of workers, the enforcement of social norms of interpersonal respect and a universal system of casualized employment. Together, these practices constitute workers as undifferentiated, interchangeable and equal labour, let them compete with each other under harshly exploitative conditions, and continuously dispose of the least productive among them, keeping all in structural uncertainty. The study contributes to the critical diversity literature by showing a 'post-diversity' governmentality that rests on equality, competition and precarization of labour as a whole, rather than segregation and marginalization through an 'ideal worker' norm. This labour governmentality operates by eliciting consent from historically subordinated workers and eliminating the advantage of historically relatively privileged ones. Unmaking borders within labour inside the organization, this governmentality at the same time crucially rests on borders outside it. [ABSTRACT FROM AUTHOR]

Copyright of Computer und Recht is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

You need new earbuds because one of yours just went missing. You log onto Amazon and scroll through the endless array of options. You finally select a pair "Sold by" Amazon and click "Buy Now." Amazon promises to have the earbuds to you tomorrow. Have you ever wondered how it's possible for Amazon to pull off this Santa-like feat? It's because of a little-known practice called commingling. Commingling gets you your earbuds in near record time. But commingling could also result in your getting earbuds that are duds-or, worse yet, that malfunction and cause ear damage. Commingling means that the same goods from different sellers are stored together and then sold interchangeably. The theory is great, so long as these goods are truly interchangeable. All it takes, however, is for some bad actors to co-opt the commingled supply chain and those goods are no longer interchangeable. Some goods are real. Some are fake. Some are junk. Some are dangerous. When you order something on Amazon, you don't know what you're going to get. You are told that goods are "Sold by Amazon, but the actual goods you get may be from a shady third-party seller based in Shenzhen, China. How can Amazon do this and not tell its customers? Good question. In this Article, I argue that Amazon should no longer be permitted to get away with its secret practice of commingling. Telling a buyer that they are getting goods from Seller A and then giving them goods from Seller B is deceptive-plain and simple. The law should not countenance such a practice. At the very least, Amazon should be required to disclose its practice of commingling before a buyer makes a purchase. It's time for Amazon's dirty little secret to be exposed and to let consumers decide for themselves whether they want to continue buying from, or on, Amazon. [ABSTRACT FROM AUTHOR]

Copyright of Revista Técnica Tributaria is the property of Asociacion Espanola de Asesores Fiscales and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

On most e-commerce websites, there are two crucial factors that customers rely on to assess product quality and dependability: customer reviews provided online and related ratings. Reviews offer feedback to customers about the product's merits, reasons for negative reviews, and feelings of satisfaction or dissatisfaction with the provided service. As for ratings, they express customer opinions about the product's quality as numerical values from one to five (one or two for the worst opinion, three for the neutral opinion, and four or five for the best opinion). Usually, the customer reviews may be inconsistent with their relevant ratings; the customer may write the worst review despite providing a four- or five-star rating or write the best review with only a one- or two-star rating. Due to this inconsistency, customers may need help to identify relevant information. Therefore, it is required to develop a model that can classify reviews as either positive or negative, depending on the polarity of thoughts, to demonstrate if there is an inconsistency between customer reviews and their actual ratings by comparing them with the ratings resulting from the model. This paper proposes an efficient deep learning (DL) model for classifying customer reviews and assessing whether there is inconsistency. The recommended model's performance and stability are examined on a large dataset of product reviews from Amazon e-commerce. The experimental findings showed that the proposed model dominates and significantly outperforms its peers regarding prediction accuracy and other performance measures. [ABSTRACT FROM AUTHOR]

Rinse-off cosmetic products, primarily shampoos, are frequently implicated in the onset of allergic contact dermatitis (ACD) caused by alkyl glucosides (AGs). AGs are increasingly popular surfactants and known contact allergens. Glucoside-induced ACD was most frequently observed with shampoos and skin-cleansing products in both consumer and occupational settings. Thereby, studies have shown that atopic individuals are the most susceptible to ACD. Also, several investigations have indicated that individuals with sensitive skin might be more prone to skin allergies. This is why the presence of AGs was investigated in shampoos and body cleansers marketed as hypoallergenic or for sensitive skin. For this purpose, the website of Amazon.com was surveyed. Four groups of cosmetics were obtained by using the following keywords: "hypoallergenic shampoo for adults," "sensitive skin shampoo for adults," "hypoallergenic body cleanser for adults," and "sensitive skin body cleanser for adults." The first 30 best-selling cosmetics in each group were investigated for the presence of AGs, by analyzing the product information pages. The results showed that as much as 56.7% of hypoallergenic shampoos contained AGs, as ingredients, whereas the percentage was somewhat lower for other product categories. Even though decyl and lauryl glucoside were nearly ubiquitously used AGs in cosmetics over the past decade, the most commonly present AG in our analysis was coco-glucoside. The results of this study indicated a necessity to include coco-glucoside in the baseline series of patch testing allergens. Industry, regulators, and healthcare providers should be made aware of the frequent presence of AGs in rinse-off cosmetic products marketed as hypoallergenic or for sensitive skin to ensure the safety and well-being of consumers and patients. [ABSTRACT FROM AUTHOR]

During the time of COVID-19, the use of face masks has become an essential control and prevention measure. The wide usage of disposable face masks has presented a great challenge to governments to face the impact of plastic waste on humans health and the environment. The quality of reusable face masks was assessed in previous research based on general measures such as the fabric, size fit, arrival time, price, and convenience, and based on more-specific measures related to the number of layers and the included filters. However, as the quality of reusable face masks includes several other dimensions, the general measures cannot be enough to ensure a comprehensive evaluation of these products during the COVID-19 outbreak. Nowadays, however, digital social media has provided venues and convenient tools for users to share their opinions, preferences, and experiences on the quality of reusable face masks. Considering reusable face masks, several types have been launched on online platforms to meet the increasing demand during COVID-19. The main goal of this study is to investigate how reusable face masks can be evaluated through online customers' reviews. This study proposes a combination of qualitative (text mining) and quantitative (survey-based analysis) approaches to provide the researchers with a method of data analysis to inspect the most influential quality factors for the evaluation of reusable face masks. We performed a literature review on the previous works and also collected online customers' reviews from Amazon.com to find the quality factors of reusable face masks. The review of previous literature on reusable face masks and the result of online reviews analysis indicated that several factors impact customers' experiences, including filteration efficiency, fabric quality, breathability, design, functionality, environmental impact, comfort, easy to use, easy to clean, economic impact, donning/doffing, quality of seal, vision, communication and safety protection. The presented framework can be complementary to the existing evaluation research methods, which use the strengths of one method to overcome the shortcomings of the other. [ABSTRACT FROM AUTHOR]

The recent trend for large global digital platforms, such as Amazon Web Services and Microsoft, to establish data centres in New Zealand has renewed the debate surrounding data sovereignty in the digital era. This article discusses the relevance of data privacy law for data sovereignty. It explores motivating factors underlying sovereignty claims, emerging cloud models in respect to access and control over data, and the benefits of localisation before examining the territorial as well as extraterritorial application of the Privacy Act 2020, and how these provisions might be applied to data clouds both in New Zealand and overseas. It draws on emerging organisational and technical solutions such as use of data trustees and encryption, to ensure sovereignty over data governance. Finally, it draws on overseas data privacy jurisprudence to demonstrate the current shortcomings of existing legislative provisions, before proposing solutions, including reform of the Privacy Act 2020. [ABSTRACT FROM AUTHOR]

The main objective of this research is to quantify for the first time the phenomenon of books authored by ChatGPT for sale through Amazon. To do this and with the help of a quantitative descriptive methodology, this work analyzes the evolution of books written by ChatGPT, and the characteristics of these works—typology, language, price, extension and type of edition—are determined. Also, this research studies those authors using ChatGPT and discusses the scope of this phenomenon, proposing measures and actions that promote transparency and good practices in the publishing industry regarding books written by artificial intelligence (AI) tools. Finally, this work concludes that ChatGPT is having a significant impact on the publishing world, from both the creation and distribution of content, so the appropriate balance between the use of AI and human intervention will continue to be essential to maintain a diverse and creative publishing industry. [ABSTRACT FROM AUTHOR]

Since 1990, global forest area has been reducing; tropical forests have suffered from different anthropogenic and natural factors that account for forest loss. Tropical deforestation is the second driver of anthropogenic emissions; increasing demand and investments in tropical forests drive these emissions. These forests attract significant foreign direct investments, but the effects of these investments on carbon emissions from land use, land-use change, and forestry are not well enshrined in the literature for the countries under study. This paper seeks to analyse the impact of foreign direct investments on carbon emissions from land use, land-use change, and forestry amongst 30 tropical forest countries from 1996 to 2019. The sampled countries were disaggregated by tropical blocs: Amazon, Congo basin, Australasia, and Southeast Asia, and by income levels; low-income, lower-middle, upper-middle, and high-income. The findings reveal a U-shape structure of the impact of FDI on carbon emissions from LULUCF within Congo basin and Amazon countries; at higher levels of FDI, emissions from LULUCF will increase while Australasia and Southeast Asian countries show an inverted U-shape impact, thus at higher levels of FDI, there will be a negative and significant impact on carbon emissions from LULUCF. The income levels reveal an inverted U-shape for low-income and high-income countries and a U-shape for upper-middle-income countries; the impact for lower-middle-income countries is not significant. Overall, for the whole sample, the impact depicts a U-shape. This paper proposes high-level development of environmental conditions for FDI for different sectors that align with country and regional green growth plans. Enhancing national and regional governance systems to enforce decisions and fight corruption effectively can significantly promote green FDI for green growth. [ABSTRACT FROM AUTHOR]

We develop a framework for creating distortion functions that are used to construct new bivariate copulas. It is achieved by transforming non-negative random variables with Lomax-related distributions. In this paper, we apply the distortions to the base copulas of independence, Clayton, Frank, and Gumbel copulas. The properties of the tail dependence coefficient, tail order, and concordance ordering are explored for the new families of distorted copulas. We conducted an empirical study using the daily net returns of Amazon and Google stocks from January 2014 to December 2023. We compared the popular Clayton, Gumbel, Frank, and Gaussian copula models to their corresponding distorted copula models induced by the unit-Lomax and unit-inverse Pareto distortions. The new families of distortion copulas are equipped with additional parameters inherent in the distortion function, providing more flexibility, and are demonstrated to perform better than the base copulas. After analyzing the data, we have found that the joint extremes of Amazon and Google stocks are more likely for high daily net returns than for low daily net returns. [ABSTRACT FROM AUTHOR]

Sellers on online marketplaces such as Amazon.com use a variety of retail and retail media advertising services to improve their brand performance, including awareness, consideration, and revenue. But how can they measure their progress and drive these metrics? For 122,000 brands, we measure Amazon shoppers' brand awareness, consideration, and purchases and test how they change with ad and retail actions. Furthermore, we compare these brands' past media mix with the recommended allocation based on the model's coefficients. We find that new product launches and upper-funnel retail media advertising are particularly effective for small brands. Medium-sized and large brands benefit most from lower-funnel advertising. For the funnel stages, all three metrics benefit from the number of new reviews, % discount, negative keywords, and geo-reach campaigns. These results are robust across different product categories, but we find notable differences in how upper- and middle-funnel ad products succeed in driving sales. [ABSTRACT FROM AUTHOR]