Agreement between a web collaborative dataset and an administrative dataset to assess the retail food environment in Mexico.

BACKGROUND: Latin American countries are often limited in the availability of food outlet data. There is a need to use online search engines that allow the identification of food outlets and assess their agreement with field observations. We aimed to assess the agreement in the density of food outlets provided by a web collaborative data (Google) against the density obtained from an administrative registry. We also determined whether the agreement differed by type of food outlet and by area-level socioeconomic deprivation. METHODS: In this cross-sectional study, we analyzed 1,693 census tracts from the municipalities of Hermosillo, Leon, Oaxaca de Juarez, and Tlalpan. The Google service was used to develop a tool for the automatic acquisition of food outlet data. To assess agreement, we compared food outlet densities obtained with Google against those registered in the National Statistical Directory of Economic Units (DENUE). Continuous densities were assessed using Bland-Altman plots and concordance correlation coefficient (CCC), while agreement across tertiles of density was estimated using weighted kappa. RESULTS: The CCC indicated a strong correlation between Google and DENUE in the overall sample (0.75); by food outlet, most of the correlations were from negligible (0.08) to moderate (0.58). The CCC showed a weaker correlation as deprivation increased. Weighted kappa indicated substantial agreement between Google and DENUE across all census tracts (0.64). By type of food outlet, the weighted kappa showed substantial agreement for restaurants (0.69) and specialty food stores (0.68); the agreement was moderate for convenience stores/small food retail stores (0.49) and fair for candy/ice cream stores (0.30). Weighted kappa indicated substantial agreement in low-deprivation areas (0.63); in very high-deprivation areas, the agreement was moderate (0.42). CONCLUSIONS: Google could be useful in assessing fixed food outlet densities as a categorical indicator, especially for some establishments, like specialty food stores and restaurants. The data could also be informative of the availability of fixed food outlets, particularly in less deprived areas.

Intelligence level evaluation and influencing factors analysis of equipment manufacturing industry in the Yangtze River Delta.

The Yangtze River Delta (YRD) bears the vital task of driving the growth of China's equipment manufacturing industry (EMI) intelligence as an advanced region. Fostering the transformation and upgrading of the EMI in the YRD and constructing a modern production mode is vital to developing and reforming China's manufacturing industry. This paper uses industrial robot data to assess the level of intelligence (LoI) in the EMI from 2016 to 2019. The OLS (ordinary least squares) model is used for the measurements, and the MQ (the modified contribution index) is used to estimate the degree of contribution from a host of variables. It is identified that the LoI is on the rise. However, excluding railways, aerospace, shipbuilding, and other transportation equipment manufacturing, the LoI is significantly higher than in other subsectors. It is also identified that technological innovation ability, human capital density, and enterprise cost pressure govern the industry's LoI. Moreover, while there is a difference in the main influencing factors in LoI within different industries, R&D investment, technological innovation ability, and enterprise cost pressure have the most significant impact across most equipment manufacturing sub-industries.

Tobacco price elasticity by socioeconomic characteristics in Ecuador.

Smoking is a worldwide epidemic and increased prices are one of the most cost-effective measures to reduce tobacco consumption. This article aims to estimate the price and income elasticity of cigarettes for different population groups in Ecuador. The National Survey of Urban and Rural Household Income and Expenditures (ENIGHUR) 2011-2012 was used, which has information on household cigarette consumption and its sociodemographic characteristics. Deaton's Almost Ideal Demand System, which decouples the effect of quality on the price of the good, was applied. The elasticities were calculated for several groups: urban/rural, income levels (tertiles), education level, sex and age ranges of the household head, and frequency of cigarette purchases in households. The estimated price elasticity nationwide is -0.89 and the income elasticity is 0.41, both statistically significant. Households headed by women (-2.22) are more sensitive to an increase in cigarette prices than those headed by men (-0.65) and households headed by people between 20 and 40 years of age (-2.32) have a higher price elasticity compared to country-level estimations. Differences within other groups are not statistically significant.

Consumer preferences for attributes in sweet beverages and market impacts of beverage innovation.

Consumption of sugar-sweetened beverages (SSB) is considered as an important risk factor for the development of overweight and obesity in populations worldwide, with a particular focus on the risks in the younger parts of the population - children and adolescents. Together with fiscal measures and information tools, innovation-based approaches such as the development of sugar-free or sugar-reduced versions of established beverages and development of new beverage products have been used to reduce this challenge, but the effects of product innovation on sugar intake are not well understood from the literature, as previous studies have largely ignored substitution effects of product innovation in the beverage domain. The objective of the present study was to investigate the potential effectiveness of product innovation as a strategy to affect consumers' intake of energy from sweetened non-alcoholic beverages. Using household panel shopping data from approximately 3000 Danish households over the years 2006-2014, we developed a hedonic pricing approach to estimate the influence of product attributes on consumers' utility, based on observed data for Danish households' purchases of sweet drinks. Overall, the study found that beverages' degree of sweetness positively affected the satiation effect of beverage consumption and in turn made the demand for these beverages less sensitive to e.g. price changes or introduction of competing products, whereas the energy density of the beverages positively affected the demand sensitivity to market changes. Findings like these can be useful for assessing market effects as well as environmental and public health impacts of changes to the market environment.

Green supply chain management practices and triple bottom line performance: Insights from an emerging economy with a mediating and moderating model.

The current study explores the dynamics of business practices in Pakistan's Small and Medium Enterprises (SMEs). This research focusing on how "green supply chain management" (GSCM), Industry 4.0 technologies (IND), total quality management (TQM) and sustainable performance (SP) are interconnected. The study collected data from 382 SMEs owners and managers and data analysis was conducted utilizing by SPSS and SmartPLS. The results indicate that employ GSCM pattern has constructive impact on SMEs overall performance in terms of their social and financial aspects. Interestingly IND act as intermediaries among GSCM and sustainable performance underscoring their potential to translate sustainability efforts into outcomes. Moreover, our survey reveals that TQM have a crucial function in enriching the relationship between Industry 4.0 technologies and sustainable performance by executing as a moderator. It further highlighting the value of adopting a quality focused approach to maximize the causal factor of advancements on sustainability output. The findings of this survey research offering insights for practitioners, SMEs, and policy makers alike by highlighting the significance of integrating practices such as GSCM, IND and effective quality management to enhance SME efficiency. These outcomes further contribute to an understanding of the mechanics at play, within SMEs while offering guidance for organizations maneuvering the changing landscape of sustainable business practices and IND.

Revolutionizing energy practices: Unleashing the power of artificial intelligence in corporate energy transition.

Corporate energy transition is crucial for long-term sustainable development. The widely discussed Artificial Intelligence (AI), as a disruptive technological innovation, is highly potential for enhancing environment performance. However, the specific impact of AI on the process of corporate energy transition and its underlying mechanisms have not been fully explored. This study focuses on A-share listed corporates in Shanghai and Shenzhen stock markets in China spanning from 2011 to 2021. Based on corporate annual report information and information from over 200,000 patent application texts, we innovatively construct indicators for corporate energy transition and AI technology application. Furthermore, we empirically investigate the impact of AI technology on corporate energy transition and its potential mechanisms through combining information asymmetry theory and institutional theory. The empirical results indicate that: 1) AI can drive corporate energy transition and the promoting effect of AI collaborative innovation on corporate energy transition should not be ignored. 2) AI can help corporates achieve energy transition through pathways such as mitigating information asymmetry, reducing financing constraints, adjusting sustainable development concepts and practices. 3) The driving effect of AI on corporate energy transition varies depending on the characteristics of different types of corporates, industries, and regions. This study provides strategic guidance and decision support for business managers and policymakers, assisting both corporates and governments in better utilizing AI technology during the social energy transition process to achieve a dual optimization of environmental and economic goals.

PFAS Contamination in Europe: Generating Knowledge and Mapping Known and Likely Contamination with "Expert-Reviewed" Journalism.

While the extent of environmental contamination by per- and polyfluoroalkyl substances (PFAS) has mobilized considerable efforts around the globe in recent years, publicly available data on PFAS in Europe were very limited. In an unprecedented experiment of "expert-reviewed journalism" involving 29 journalists and seven scientific advisers, a cross-border collaborative project, the "Forever Pollution Project" (FPP), drew on both scientific methods and investigative journalism techniques such as open-source intelligence (OSINT) and freedom of information (FOI) requests to map contamination across Europe, making public data that previously had existed as "unseen science". The FPP identified 22,934 known contamination sites, including 20 PFAS manufacturing facilities, and 21,426 "presumptive contamination sites", including 13,745 sites presumably contaminated with fluorinated aqueous film-forming foam (AFFF) discharge, 2911 industrial facilities, and 4752 sites related to PFAS-containing waste. Additionally, the FPP identified 231 "known PFAS users", a new category for sites with an intermediate level of evidence of PFAS use and considered likely to be contamination sources. However, the true extent of contamination in Europe remains significantly underestimated due to a lack of comprehensive geolocation, sampling, and publicly available data. This model of knowledge production and dissemination offers lessons for researchers, policymakers, and journalists about cross-field collaborations and data transparency.

[Resources and utilization of medicinal plants in countries and regions involved in "the Belt and Road" Initiative].

The protection, development, and utilization of medicinal plant resources are important cornerstones of maintaining human health. However, due to factors such as the reduction of high-quality land resources, deterioration of ecological environments, and excessive and disorderly resource development, medicinal plant resources are becoming scarce, and some of them are insufficiently supplied. With the proposal of "the Belt and Road" Initiative, the cooperation between China and "the Belt and Road" partners(the countries and regions involved in "the Belt and Road" Initiative)is increasingly close, which provides a new opportunity for carrying out trade of medicinal plant resources and alleviating the problem of imbalance and relative inadequacy of medicinal plant resources in countries. This study first determined the distribution and species information of plant resources in countries and regions involved in "the Belt and Road" Initiative by investigating the database of plant distribution and that of medicinal plant resources. Then, according to the published data from the International Union for Conservation of Nature(IUCN) and the Convention on International Trade in Endangered Species of Wild Fauna and Flora(CITES), this study identified the rare and endangered medicinal plants and the medicinal plants under trade control in countries and regions involved in "the Belt and Road" Initiative and finally sorted out the list of potential medicinal plant resources in countries and regions involved in "the Belt and Road" Initiative that can be used by China. This data resource can not only be used for the overall protection of important endangered species but also scientifically guide the development and utilization of medicinal resources, providing guidance and a theoretical basis for the sustainable development of medicinal plant resources in countries and regions involved in "the Belt and Road" Initiative.

[Critical influencing factors on quality of traditional Chinese medicine preparations from perspective of process and equipment].

The quality of traditional Chinese medicine preparations is directly related to the safety of patients. Among the various factors, the process and corresponding critical equipment are critical factors influencing the quality of the preparations. To improve the quality of traditional Chinese medicine preparations, this article summarizes and analyzes the problems in the process links and corresponding critical equipment in the manufacturing process of traditional Chinese medicine preparations. Furthermore, a critical quality attribute evaluation system is established based on safety and effectiveness combined with the drug properties, preparation process, and preparation characteristics, providing a basis for the process and equipment improvements aimed at quality enhancement.

Advancing e-commerce user purchase prediction: Integration of time-series attention with event-based timestamp encoding and Graph Neural Network-Enhanced user profiling.

In recent years, the global e-commerce landscape has witnessed rapid growth, with sales reaching a new peak in the past year and expected to rise further in the coming years. Amid this e-commerce boom, accurately predicting user purchase behavior has become crucial for commercial success. We introduce a novel framework integrating three innovative approaches to enhance the prediction model's effectiveness. First, we integrate an event-based timestamp encoding within a time-series attention model, effectively capturing the dynamic and temporal aspects of user behavior. This aspect is often neglected in traditional user purchase prediction methods, leading to suboptimal accuracy. Second, we incorporate Graph Neural Networks (GNNs) to analyze user behavior. By modeling users and their actions as nodes and edges within a graph structure, we capture complex relationships and patterns in user behavior more effectively than current models, offering a nuanced and comprehensive analysis. Lastly, our framework transcends traditional learning strategies by implementing advanced meta-learning techniques. This enables the model to autonomously adjust learning parameters, including the learning rate, in response to new and evolving data environments, thereby significantly enhancing its adaptability and learning efficiency. Through extensive experiments on diverse real-world e-commerce datasets, our model demonstrates superior performance, particularly in accuracy and adaptability in large-scale data scenarios. This study not only overcomes the existing challenges in analyzing e-commerce user behavior but also sets a foundation for future exploration in this dynamic field. We believe our contributions provide significant insights and tools for e-commerce platforms to better understand and cater to their users, ultimately driving sales and improving user experiences.

An integrated model for rice supplier selection strategies and a comparative analysis of fuzzy multicriteria decision-making approaches based on the fuzzy entropy weight method for evaluating rice suppliers.

Rice, being a staple food in many countries, necessitates the identification of reliable suppliers to ensure a steady supply. Consequently, it is vital to establish trustworthy vendors for various types of this essential grain who can meet stringent product quality standards. This study aims to identify, analyze, rank, and select primary rice suppliers. The study emphasizes the importance of selecting and managing suitable providers to meet customer demands, proposes a ranking model for rice suppliers, and introduces developed fuzzy MCDM techniques. It proposes an integrated model for selecting rice suppliers, considering factors related to the processes before, during, and after selecting providers within a defined framework. The outcomes shows that rice supplier selection strategy can efficiently identify reliable rice suppliers, improve buyer value, reduce procurement risk, enhance efficiency, and establish strong supply chain relationships in complex decision-making processes. To assess suppliers, the study introduces two advanced integrated approaches and compares them. The fuzzy entropy weight method (EWM) was used to determine the criteria weights. The ranking of rice suppliers was achieved using a fuzzy multi-objective optimization based on ratio analysis (MOORA), fuzzy complex proportional assessment (COPRAS), and combinations of these two methods in different approaches. The methodology supports decision-makers in a rapidly evolving global environment by assisting importers, traders, suppliers, procurement, and logistics management, particularly for non-rice-cultivating countries in rice importation and supplier selection. The numerical analysis is grounded in a real-world case study of selecting rice suppliers in Jordan. The findings reveal that the various strategies yield both similar and different results. Furthermore, the integrated method is considered the most accurate for evaluating rice imports and suppliers, aligning closely with the reality of the current situation.

Does the opening of producer services promote the wage growth of the downstream manufacturing industry?-Empirical evidence from Chinese manufacturing listed companies.

Based on the vertical connection between upstream and downstream industries, a unique theoretical model is constructed to analyse the impact mechanism of the opening of producer services on downstream manufacturing wage growth. The empirical tests are carried out using the data of China's manufacturing listed companies from 1999 to 2020. Our findings indicate that the opening of producer services has an inverted-U-shaped impact on downstream manufacturing wage growth, and the average level of the opening of producer services in the sample period is lower than the corresponding threshold. Overall, it is in the stage of promoting the wage growth of the downstream manufacturing industry. The opening of producer services mainly affects the wage growth of the downstream manufacturing industry through two channels: labour productivity and labour income share. The results of heterogeneity analysis show that the wages of capital and technology-intensive and low-competitive manufacturing industries are relatively strongly promoted by the opening of producer services. Therefore, promoting the orderly opening of producer services and strengthening the technological links between industries will help promote the wage growth of downstream manufacturing industries.

An empirical assessment of the influence of digital transformation on sports corporate sustainability.

The trend of digital transformation fosters enterprise change, helps cultivate enterprises' own competitive advantages and is crucial to the advancement of sports enterprises' sustainable development in the framework of the emerging digital economy as a national strategy. However, there have been few empirical studies on the microlevel of digital transformation and its impact on the sustainability of sports organizations. Therefore, the sustainable growth dynamic model is used to construct indicators of corporate sustainability by referencing 48 sports corporations listed on Shanghai and Shenzhen A-shares markets and the New Third Board in China from 2012 to 2021. The intrinsic relationship between digital transformation and the sustainable development of sports enterprises and the underlying mechanism of action are explored by constructing a panel fixed effects model, a chain mediating effects model, and a panel threshold model. The most important contribution is as follows: To provide a useful reference for analyzing enterprise digital transformation, a more complete indicator indicating the extent of corporate digital transformation is built. The micro viewpoint broadens our awareness of sustainable development in sports organizations and deepens our understanding of the interaction model between sustainable development and enterprise digital transformation. This study provides methodical evidence and insights for an accurate understanding of digital transformation for sustainable enterprise development, looking into the "black box" of the mechanism between digital transformation and sustainable business development. The results show that digital transformation significantly aids sports enterprises in their pursuit of long-term sustainability. Heterogeneity tests demonstrate the pivotal role of digital transformation in advancing the sustained growth of sports firms and high-tech sports enterprises situated in the eastern region of China. Regarding transmission mechanisms, the chain mediating effect of enterprises' digital transformation on improved technological innovation and TFP, which in turn promote long-term business growth, has yet to be validated. Further examination exposes that within the context of the correlation between digital transformation and the sustainability of corporations, there is a single threshold effect based on financing restrictions and operational costs and a double threshold effect based on operational efficiency.

Surveillance and Security in US Medicine and Equipment Supply Chains.

The COVID-19 pandemic exposed vulnerabilities of the United States' routine and emergency supply chains of medicines and critical equipment. These vulnerabilities underscore an urgent need to prevent routine and emergency shortages by making drug manufacturing more transparent and by tracking how key supplies get to end users. Near real-time surveillance systems must be developed to monitor fluctuations in supplies of medicines and equipment. Implementation of such systems will require getting key stakeholders (clinicians, administrators, community members, manufacturers, and policy makers) to collaborate.

Capturing artificial intelligence applications' value proposition in healthcare - a qualitative research study.

Artificial intelligence (AI) applications pave the way for innovations in the healthcare (HC) industry. However, their adoption in HC organizations is still nascent as organizations often face a fragmented and incomplete picture of how they can capture the value of AI applications on a managerial level. To overcome adoption hurdles, HC organizations would benefit from understanding how they can capture AI applications' potential.We conduct a comprehensive systematic literature review and 11 semi-structured expert interviews to identify, systematize, and describe 15 business objectives that translate into six value propositions of AI applications in HC.Our results demonstrate that AI applications can have several business objectives converging into risk-reduced patient care, advanced patient care, self-management, process acceleration, resource optimization, and knowledge discovery.We contribute to the literature by extending research on value creation mechanisms of AI to the HC context and guiding HC organizations in evaluating their AI applications or those of the competition on a managerial level, to assess AI investment decisions, and to align their AI application portfolio towards an overarching strategy.

Modeling and simulating the multi-generation product sales, production and inventory system within the context of quality upgrades.

The rapid development of science and technology has led to an increasing number of high-tech enterprises offering new products through successive generations of product upgrades. This trend presents a new challenge for the sustainable operations of enterprises. Based on the Norton-Bass model, this study begins by constructing a multi-generation product diffusion model within a single enterprise in the context of a monopoly under the quality upgrade scenario. Subsequently, a supply model is established based on this foundation, and these two models are seamlessly integrated using product sales volume as an interface, culminating in a comprehensive sales-supply system. This study analyzes the effects of new-product pricing, quality levels, initial stock, and production capacity on the performance of this system. The system dynamics (SD) method was used to simulate and solve the system in the decentralized and centralized decision-making modes, and the two decision-making modes were compared and analyzed. The research reveals several key findings. i) Comprehensive decision optimization yields enhanced profitability through joint optimization calculation of the multi-generation product diffusion system and the supply adjustment system. ii) consumer price sensitivity significantly affects product quality upgrades and profits. A negative correlation exists between consumer price sensitivity and both factors. The upgrades of product quality should be carefully traded off with consideration of pricing and quality costs. iii) Maximizing profits by maintaining a certain order level of backlog or stock shortage is beneficial for overall enterprise profitability. Additionally, optimal production capacity has been identified as a crucial element in efficient operational inventory management. This study expands the multi-generation product diffusion operational theory and provides valuable theoretical support and decision-making foundations for the sustainable management of enterprises.

Indonesian martial artists' preferences in martial arts schools: Sustaining business competitiveness through conjoint analysis.

The popularity of martial arts in the present times has become apparent, therefore, it is necessary to explore martial artists' preferences and the schools' competitiveness. The purpose of this study was to assess martial artists' preferences concerning the services offered by martial arts schools. Conjoint analysis was utilized to analyze the responses of fifty-five (55) martial artists based on the seven (7) martial arts schools' attributes. The results showed that the type of martial arts was found to be the most important attribute (30.449%) followed by distance (27.970%), price range (22.706%), social environment (11.097%), class preference (5.080%), goal (1.562%), and schedule (1.135%). Furthermore, Muay Thai or Kickboxing was the most preferred martial art, Mixed Martial Arts (MMA) was the second priority, next was Taekwondo, then Karate, and finally Boxing. In addition, the martial artists' preferred distance was less than 8 km, and a monthly training cost of 150,000 to 450,000 IDR (10 to 20 USD). Martial artists liked attending open classes, treated martial arts as a hobby, and favored attending classes once or twice weekly. With the lack of conjoint-related studies in the martial arts industry, the findings contributed to academicians and addressed issues of inadequate studies. Most importantly, the researchers presented managerial implications to leverage marketing techniques and develop the business operations of martial arts schools.

Does structural social capital lead to proactive green innovation? a three-part serial mediation model.

Enhancing green innovation for business sustainability represents a pressing global challenge. In the context of the manufacturing industry, the relationship between proactive green innovation (PGI) and structural social capital (SSC) remains a profoundly under-researched area. Drawing upon the theories of social capital and dynamic capability (DC), this study investigated the relationship between SSC and PGI within manufacturing enterprises via three individual and sequential mediating factors, namely cognitive social capital (CSC), relational social capital (RSC), and DC. Adopting a cross-sectional quantitative design, this study collected survey data from 485 manufacturing sector employees in China using purposive sampling. Structural equation modeling analysis of the data revealed no significant direct impact of SSC on PGI, but a strong indirect impact through the sequential mediating influences of CSC, RSC, and DC. The findings suggests that PGI within manufacturing enterprises is not wholly shaped by SSC; rather, firm-level dynamic capabilities, characterized by a sequential mechanism, plays a crucial role in achieving PGI within these enterprises. This paper offers both theoretical and practical contributions and provides recommendations for future research based on its limitations.