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We examine the relationship between pre-grant patent disclosure and analyst forecast accuracy. We take advantage of the passage of the American Inventor’s Protection Act (1999), which mandates the pre-grant public disclosure of all information in patent application documents within 18 months of the initial filings. We find that, on average, the pre-grant patent disclosure of corporate inventions significantly improves the accuracy of analyst forecasts about the patenting firm and this improvement is greater for firms with higher research and development intensity. Nevertheless, improvements in the accuracy of analysts’ forecasts are smaller when firms issue more original and scientifically broader patents. Also, this effect is weaker for firms in states without legal protection for trade secrets. This paper was accepted by Brian Bushee, accounting. Funding: Ali Mohammadi gratefully acknowledges support from the Danish Finance Institute. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2022.4420 .

Purpose: Digital extension is widely embraced in African agricultural development, promising unprecedented outcomes and impact. Especially phone-based services attract attention as tools for effective and efficient agricultural extension. To date, assessments of digital extension services are generally ex-post in nature, thus consideration of users and broader systems occurs once an intervention is broadly identified. However, early understanding of user needs, readiness, and relevant context is a prerequisite for successful adoption and sustainable use of digital extension services. We conducted an ex-ante assessment of user readiness (UR) for phone-based services. Design/Methodology/Approach: We developed an ex-ante framework to assess UR, considering capabilities, opportunities, and motivations of targeted users. The case study of Rwandan banana farmers served to verify the UR framework, using survey data from 690 smallholder farmers. Findings: Findings demonstrate limited capacity to access and use phone-based extension services, especially those requiring a smartphone, and a mismatch between expected UR and actual UR, current capabilities and opportunities. Findings provide entry points for designing suitable digital extension projects and interventions, suggesting a need for capacity building. Practical implications: The UR-framework provided understanding about current limitations in farmer readiness for digital extension. This ex-ante approach to explore UR before designing digital interventions for African farmers is recommended. It points at the importance of embedding digital technologies into existing practices and creating blends of ‘digital’ and ‘analogue’ or 'high-tech' and 'low-tech'. Theoretical implications: The UR-framework provides a structured approach to developing pre-intervention insights about users and use-context, supporting informed strategizing and decision-making about digital extension. It is a relevant addition to existing readiness frameworks, participatory design methods, and ex-post intervention performance assessments, as part of a balanced readiness level assessment. Originality/Value: This is the first ex-ante assessment of UR for digital extension services in an African context, and the first attempt to analyse Rwandan farmers’ readiness for digital extension services.

What are the consequences of the rise of foreign state-led investment for international politics? Existing research oscillates between a 'geopolitical' and a 'commercial' logic driving this type of investment and remains inconclusive about its wider international reverberations. In this paper, I suggest going beyond this dichotomy by analyzing its systemic consequences. To do so, I conceptually delineate a geoeconomic approach that emphasizes the globalized nature of foreign state investment. I argue that foreign state investment creates system-level patterns, which can be studied by observing similar sectoral and geographic investment behavior. I map this phenomenon globally for the first time, drawing on the largest dataset on foreign state investment. Empirically, I show how foreign state investment is highly concentrated in Europe, North America and East Asia, and is owned by a handful of dominant states. It is especially European geo-industrial clusters that represent the hotspots of such concentration. The findings also suggest that three global industries - energy production, high-tech manufacturing, and transportation and logistics - form the key areas for current and future state-led investment concentration. With these contributions, the paper illuminates the increasing presence of states as owners in the global political economy, and facilitates its study as a geoeconomic phenomenon.

This study investigates biases in tax decisions. In a series of four laboratory experiments with 303 students and 62 tax professionals, we document a systematic tax-rate bias in decisions under time constraints. Specifically, decision makers overestimate the relevance of less complex tax-rate information compared to more complex tax-base information. This behavior leads to suboptimal tax decisions. We also find that decision making, on average, is unaffected by professional experience: Students and tax professionals are similarly prone to tax-rate bias. However, senior tax professionals are more rationally inattentive. These decision makers are less likely to exhibit a tax-rate bias when exhibiting such bias is relatively costly. Overall, our findings suggest that resource constraints impede the use of complex tax-base information, which results in suboptimal tax decisions. Interviews with senior tax professionals indicate potential for tax-rate biases in real-world tax decisions and thereby provide directions for future research. JEL Classifications: C91; D03; H32; K34; M21; M41.

Purpose: While new rich learning opportunities emerged through the introduction of Innovation Platforms (IPs) in agricultural value chains, the extent to which IPs enhance farmer experiential learning is still unclear.Design/methodology/approach: This paper brings clarity to the above question by interviewing 91 coffee IP farmers. Data were analyzed through content analysis to generate overarching themes for farmers’ experiences, learning activities, and outcomes.Findings: Results reveal that participation in IP learning activities generates farmers’ knowledge to cope with coffee value chain challenges. Specifically, farmers’ making-meaning of challenges and generating new solutions represents an iteration between individual critical reflection and experimentation of value chain activities. The IPs facilitated multi-directional knowledge flowsamong farmers by mobilizing necessary resources.Practical implications: As many Sub-Saharan Africa (SSA) governments cannot provide sufficient extension support, farmers increasingly rely on IPs whose processes stimulate members’ learning commitment and endeavors. Nevertheless, Governments can use these findings to tailor the design and implementation ofIPs to farmers’ experiential learning processes.Theoretical implications: The study contributes to experiential theory in the context of agriculture by advancing a model on how IPs can accelerate farmers’ experiential learning processes based on the challenges experienced.Originality/value: This article extends knowledge of experiential learning in IPs context.

When multiple retailers hold inventory to satisfy random demand, retailer inventory-sharing strategies can potentially reduce the supply-demand mismatch and increase overall supply chain performance. In this paper, we experimentally investigate alternative inventory-sharing strategies in a two-tier supply chain with an upstream manufacturer and two downstream retailers. In one setting, retailers act as if they are centralized and use a single quantity to fulfill joint demand. In the other, retailers are decentralized and face separate demands, but they can transfer inventory after demands are realized. In this latter decentralized scenario, we also consider whether the manufacturer or retailers have decision authority over the inventory transfer price. One key result is that when the retailers are decentralized and the manufacturer sets the transfer price, both retailers and the manufacturer earn higher profits than in the centralized retailer strategy, which runs counter to theory. We also find that when retailers are decentralized and set their own transfer price, the most equitable distribution of profits is achieved. In an effort to account for these results, we find that a model of fairness captures decisions well. Overall, by investigating how different inventory-sharing strategies affect the distribution of profits in a two-tier supply chain, our results provide guidance to firms considering how, if at all, they should enter such arrangements. This paper was accepted by Jay Swaminathan, operations management. Funding: The authors acknowledge financial support from Cornell University and the University of Virginia. Supplemental Material: The data files and electronic companion are available at https://doi.org/10.1287/mnsc.2022.4323 .

This article aimed to discuss the scope of reverse mentoring and intergenerational learning in nursing. Accordingly, it discusses the characteristics, significance, benefits, conceptual framework, implementation strategy and application of reverse mentoring in nursing. Reverse mentoring occurs when a technically competent younger employee mentors a senior experienced employee and reciprocally exchanges the work culture and soft skills. Diverse intergenerational learning spurs innovation through the sharing of knowledge, skills, competencies, norms and values. Thus, reverse mentoring helps to enhance the quality of education, practice-outcomes and employee development. It should be adopted for a multigenerational workforce to promote diversity, keep employees technically competent and updated in ever changing nursing profession. Presently, the COVID-19 pandemic has given rise to an urgent need for technical competency and knowledge sharing among the diverse multigenerational nursing workforce. Therefore, a reverse-mentoring strategy is proposed as a sustainable cost-effective intergenerational knowledgesharing tool for the current era of economic crisis.Keywords: Mentoring; COVID-19; Cultural Diversity; Learning; Nursing; Preceptorship; Intergenerational Relations; Mentorship.

This paper describes how the contemporary technology innovation ecology is hostile to community-driven design. These hostilities are important to understand if we want to intervene in the policy landscape of technology innovation to support viable alternatives to big tech consolidation and more democratic ways of developing and maintaining technology. We contribute a thick description of the hostile ecologies faced by transportation workers, community organizers, and allied technology researchers as they work toward building a cooperatively-owned taxi business with a digital dispatching technology. Our findings show that the hostile innovation ecology manifests as constrained access to resources, an inequitable regulatory framework, diminished agency in the software design process, and limits to the will of our community partners. We discuss the paths toward innovation for United Taxi Workers San Diego as compared with transportation network companies (e.g. Lyft, Uber) in terms of access to funding, regulation, labor, expertise, and market. We argue that a critical examination of institutions and policies in the innovation ecology is a necessary step toward charting fair, equitable, and community-strengthening pathways for technology innovation in the future.

Following state-level legal changes that increase labor dismissal costs, firms increase their innovation in new processes that facilitate the adoption of cost-saving production methods, especially in industries with a large share of labor costs in total costs. Firms with high innovation ability exhibit larger increases in process innovation and capital-labor ratios - an effect driven by both increases in capital investment and decreases in employment. By facilitating the adjustment of the input mix when conditions in input markets change, innovation ability allows firms to mitigate value losses and is a key driver of their performance.

High voltage/high power capacitor chargers are primarily interested in many industrial applications. Resonant converters have been a proper choice in such applications because of their advantages. However, the performance of the resonant converter is highly affected by the parasitic elements of the high voltage/high power transformer. Also, short circuit condition is a frequent event in high voltage applications, so that the resonant converter should be robust against the short circuit condition. This paper presents a novel LCCL resonant converter with current source characteristics used as a high voltage capacitor charger. The proposed resonant converter eliminates the undesirable effect of the stray capacitance in high voltage devices and is robust against the short circuit condition inherently. It also provides a semi-trapezoidal resonant current wave which produces a lower crest factor. Furthermore, a frequency-sweep operation is applied, which has advantages in reducing the resonant current's peak value and the resonant network's size. Simulation results show a satisfactory performance of the proposed resonant converter. Moreover, experimental results confirm the effectiveness of the proposed resonant converter in the application of capacitor charging.

This note provides an evaluation of the contributions of the M5 Competition to the construction of prediction intervals. We consider the choice of criteria used in the evaluations, the relative performance of designed and benchmark methods and the take-home lessons both for statistical forecasters and for those interested in forecasting retail sales.

The “buy online and pick up in store” (BOPS) mode is gaining tremendous popularity among retailers since it is convenient for consumers and brings additional store sales to retailers. However, operating the BOPS channel requires additional investment, which is a challenge for retailers. This article considers the pricing strategies of competing dual-channel retailers, focuses on whether and when they should adopt the BOPS strategy, and explores the impacts of market factors on the equilibrium outcomes. Since retailers’ decisions are usually made sequentially in reality, we use the Stackelberg game model to analyze retailers’ optimal strategies. First, we show that the follower's price is not always lower than the leader's price. Specifically, when the unit additional profit from cross-selling of the follower is low enough, the follower will set a higher price than the leader. Second, we find that retailers prefer the BOPS strategy when the fixed costs for offering BOPS channels are low enough, or when the difference between the additional profits from cross-selling of two retailers is sufficiently large. Third, we present an interesting insight: an increase in product return probability or retailer cost of handling a returned product can be beneficial to retailers.

In this article, we identify leader job anxiety as a critical leader emotion relevant to team innovation. Integrating the literature on job anxiety and innovation and treating leader self-serving behavior as a mediator, we explore the relationship between leader job anxiety and team innovation. Further, we hypothesize and examine leader psychological entitlement as a moderator of the relationship. We conducted two studies to test our hypotheses. In Study 1, we used multisource data gathered from 69 team leaders and 210 team members of a high-tech software company in Northern China. In Study 2, we used a multisource, time-lagged research design to collect data from 121 team leaders and 404 team members of a large biopharmaceutical company in Northern China. We found that leader job anxiety positively relates to leader self-serving behavior and that leader psychological entitlement positively moderates this relationship. In addition, leader self-serving behavior mediates the negative relationship between leader job anxiety and team innovation. Further, we discuss theoretical and practical implications related to work teams and team innovation.

This note updates the 2019 review article “Retail forecasting: Research and practice” in the context of the COVID-19 pandemic and the substantial new research on machine-learning algorithms, when applied to retail. It offers new conclusions and challenges for both research and practice in retail demand forecasting.

Research at the intersection of creativity and leadership has predominantly focused on how leaders support employees’ creativity. We break new ground by examining how creative project leaders gener...

The file attached to this record is the author's final peer reviewed version. Agricultural advancement over time has been an essential component of human civilization's evolution. The rapid progress of emerging technologies is driving digital empowerment in nearly every industry, including the agricultural sector. Regardless of the benefits derived from this evolution, there are several security threats involved, which can have a significant impact on the agricultural domain. This paper provides a review of digital agriculture from the security perspective. First, we provide a clear introduction to the digital agriculture ecosystem from a technological standpoint. Next, we highlight the key aspects of digital agriculture security to get the reader on board. Then, we focus on the current and potential threats facing these particular systems, as well as current and/or possible mitigation strategies to address these threats. Finally, we discuss future research directions and open challenges.

In this article, a dynamic-neighborhood-based switching PSO (DNSPSO) algorithm is proposed, where a new velocity updating mechanism is designed to adjust the personal best position and the global best position according to a distance-based dynamic neighborhood to make full use of the population evolution information among the entire swarm. In addition, a novel switching learning strategy is introduced to adaptively select the acceleration coefficients and update the velocity model according to the searching state at each iteration, thereby contributing to a thorough search of the problem space. Furthermore, the differential evolution algorithm is successfully hybridized with the particle swarm optimization (PSO) algorithm to alleviate premature convergence. A series of commonly used benchmark functions (including unimodal, multimodal, and rotated multimodal cases) is utilized to comprehensively evaluate the performance of the DNSPSO algorithm. The experimental results demonstrate that the developed DNSPSO algorithm outperforms a number of existing PSO algorithms in terms of the solution accuracy and convergence performance, especially for complicated multimodal optimization problems.

Rails of unhealthy conditions are considered as major targets in the rail surface inspection and this study focuses on inspecting five types of major rail surface flaws, corrugations, defects, the shelling, squats, and grinding marks, via analyzing railway images. We propose a deep learning powered rail surface multi-flaw identification framework composed of two main components, a novel rail extractor for extracting rails from the background and a cascading rail surface flaw identifier for precisely identifying different flaws. The novelty of the cascading rail surface flaw identifier includes: 1) An unhealthy rail detector developed based on a DenseNet backbone for recognizing the healthy/unhealthy status on rail surfaces and 2) A rail flaw classifier for identifying flaw types on unhealthy rail surfaces. A new feature joint learning process integrating latent features derived from selected hierarchies of the DenseNet backbone as well as two traditional feature extractors, the local binary pattern and the gray level co-occurrence matrix, is developed to facilitate the rail flaw classifier to offer accurate identification results. The effectiveness of the proposed framework for rail surface multi-flaw identification is validated with datasets provided by an industrial partner in China and collected from online sources. Based on collected datasets, the proposed framework is capable to identify the rail with unhealthy conditions and its flaw type. The overall identification performance can achieve a 98.2% accuracy. Three groups of benchmarking methods are employed to verify advantages of the proposed framework. Computational results demonstrate the impressive performance of the proposed framework in the rail surface multi-flaw identification and its applicability on new datasets.

Despite extensive research on the value of collaborative forecasting among supply chain partners, there has been limited attention to the actual mechanisms of forecast sharing. We propose using cost-function-based prediction markets as means of sharing demand forecasts. We consider a decentralized two-stage supply chain with a supplier who sells to a retailer, in which both partners receive demand forecast updates. In the first stage, the supplier and the retailer agree on a collaborative forecasting scheme to form a consensus forecast. We consider two schemes: collaborative forecasting using cost-function-based prediction markets in which partners pay a set-up cost to operate a prediction market, and direct collaborative forecasting in which partners directly share their forecasts with each other and resolve their forecast differences through costly actions. In the second stage, we analyze the game between the supplier and the retailer to determine the retailer’s optimal order quantity as well as the supplier’s optimal wholesale price. We show that demand forecast sharing using cost-function-based prediction markets results in a Pareto improvement of the partners’ profit over the alternative of directly sharing forecasts. Furthermore, we show that this Pareto improvement is monotone with respect to supply chain partners’ forecast accuracy. We conduct an extensive numerical study to provide further insights into the effect of the return on forecast sharing investment, forecast accuracy, and level of demand uncertainty on the benefits gained by implementing cost-function-based prediction markets.

In modern society, science and technology has become the core competitiveness of a company or a country. Discovering the development trajectory a technological domain is of great significance. In this article, we propose a framework to answer this question by analyzing the semantics of patent texts and the citation relationships among patents, because patents in a specific technological domain provide rich resources of technological development process. First, we collect the patent data of a specific domain from the database of United States Patent and Trademark Office. Second, we extract different topics from these patents’ texts by Latent Dirichlet Allocation. Third, an index for evaluating the correlation between two patents is defined according to the semantic similarities and citation relationship between them. Fourth, we found the global and local important patents through the global and local important index (LII). Finally, we discover some community of the network constructed by the important patents filtered by LII and statistical analysis methods to obtain some meaningful results. Furthermore, we take the patents in the technological domain of robotics as an example to examine the proposed method and reveal the technological development trends in this domain.

A world with large disparities in development between rural and urban areas could never achieve sustainable development goals (SDGs). Issues related to agriculture, rural areas, and farmers are fundamental to the stability and people's welfare of China as well as other developing countries. Despite the growing demand and national initiative for rural revitalization, rural innovation has received little attention in the innovation literature. Drawing from the new growth theory, institutional theory and innovation system theory, this paper proposes the rural innovation system, which is a complex socioeconomic network that aims to revitalize the countryside and achieve balanced and sustainable development. This paper compares the rural and urban innovation system, introduces a theoretical structural model of the rural innovation system, including a) technology innovation, b) institutional and management innovation, and c) community-based network and intermediary platform innovation. Then it outlines the future challenges in fostering a strong rural innovation system. The rural innovation system proposed makes direct contributions to the literature of rural studies, innovation system, and public policy, and offers both China and the world a new perspective for realizing rural revitalization, anti-poverty and global sustainable development.

At present, China’s economic development is in a critical period of transformation, which needs to get rid of the dependence on the real estate industry and low-end export processing industry, and is in urgent need of new growth engines. The emergence of the digital economy has provided a boost to economic upgrading, but to give full play to the potential of the digital economy, we must have an accurate and full understanding of it. At present, the development of digital economy has become the focus of all circles. Digital economy is a multilevel and complex concept, so this paper establishes a multi-index comprehensive evaluation system and uses AHP-entropy weight method to measure the development level of China’s digital economy and, on this basis, analyzes the development level, dynamic changes, and regional differences of China’s digital economy. The results show that China’s digital economy is on the rise, which is mainly driven by the construction of digital infrastructure and the application of digital technology. By region, there is a big gap between different regions in the development of digital economy, and this gap is expanding continuously. The digital economy in the eastern region is in a leading position, but only in the development of the digital industry.

Chinese contemporary music has made tremendous progress in the twentieth century. After entering the twentieth century, with the rise of pop music, Chinese contemporary music has gradually been forgotten by people. Apparently, Chinese contemporary music has a long history and covers huge varieties. Nevertheless, the diffusion of Chinese contemporary music is restricted by many factors. The fundamental reason is that people’s cognition of Chinese contemporary music has changed. However, the rise of social networks provides a new opportunity for the diffusion of Chinese contemporary music. By searching nodes with high influence in social networks, where the node is enabled by the sensor, we transform the problem for maximizing public opinion into a process of searching nodes set of maximum influence, thus providing power for the diffusion of Chinese contemporary music. In this paper, from the perspective of percolation, the network connectivity changes caused by node failure are considered, and the set selection problems of high-influence individuals are mapped to the optimal percolation problem when the network has a percolation transition. Then an influence maximization algorithm is proposed based on the network percolation process, and the efficiency of the proposed algorithm is optimized. Through experiments, we can infer the reasonable range of maximum searching times for the influence maximization algorithm. Meanwhile, compared with other baselines, the searching time of the algorithm proposed in this paper is also the least. The experimental results reveal that the proposed algorithm is feasible to diffuse Chinese contemporary music and maximize its public opinion and has a strong impetus for the revival of Chinese contemporary music.

International students are expected to become highly skilled human resource and labor force in industries with labor shortages in Japan. However, challenges have been identified regarding their retention after employment. Watabe (2021) conducted an interview survey on life career satisfaction factors of former international science student employees working in Japan to explore their career decision-making factors such as retention and returning home. The survey results were analyzed with the aid of Shockley's (2015) Subjective Career Success Inventory (SCSI) to identify subjective career items and how they are related to career decision-making. This study aims to quantitatively examine the validity of the subjective career items identified in Watabe's qualitative study. The findings indicate that the subjective career items from Watabe's study are generally valid, that there are subjective career items specific to different occupations, and that satisfaction does not necessarily influence the intention to return home.

This paper investigates the effect of the Internet on tax revenue instability, notably through the international trade channel. It has used a sample of 142 countries over the period 1995-2017, and relied primarily on the two-step system Generalized Methods of Moments (GMM) estimators (but also incidentally on the Error Component Two-Stage Least Squares estimator). Tax revenue instability is primarily measured by the instability of non-resource tax revenue, but also by the instability of total tax revenue (for robustness check). The findings indicate that the Internet exerts a negative effect on tax revenue instability. Interestingly, this effect genuinely translates through the international trade channel, regardless of the measure of tax revenue instability considered. Countries enjoy a higher negative effect of the Internet on tax revenue instability as they enjoy a greater participation in international trade. These findings, therefore, add to the potential benefits of the Internet adoption (e.g., strengthening countries' participation in international trade, enhance their tax revenue performance and promote tax reform, including in developing countries) by showing that it could also help to stabilize tax revenue, particularly through the degree of countries' participation in international trade.

Inclusive finance can help rural low-income groups, township small and microenterprises, and other groups in China to improve their living and economic standards and can meet the relevant credit needs of relevant rural personnel under the condition of risk prevention. The integration of AI and HP finance has built a more professional information and data platform for customers with different credit needs in the agricultural economy. Based on the development and integration of agricultural economy, this study makes effective analysis and judgment on poor customers with credit needs through the artificial intelligence system platform under the application of inclusive finance, so as to scientifically and effectively identify and screen the big data of different credit data of customers and finally select the most qualified high-quality credit customers, so as to effectively improve the overall economic income of customers with agricultural credit needs. It has laid a foundation for the development of agricultural economy and more effectively extracting high-quality credit customers, so that the development of agricultural economy has been widely used.

As the basis and material source of human production and life, land is an important part of natural resources. With the deepening of the concept of sustainable development, more and more attention has been paid to the sustainable development of land use. Reasonable assessment of land resources and environment is the premise of accelerating agricultural infrastructure construction, optimizing ecological environment construction, and rationally disposing land use structure. This paper proposes an evaluation method of rural land resources and environment based on the improved GIS system and takes Lingshan County as an example, based on the powerful spatial processing and rich spatial query and analysis capabilities of GIS, to analyze the current situation and sustainable development of its land use. It has established a representative and operable evaluation index system, which has certain reference significance for rural land and environmental evaluation.

To build an agricultural product network marketing system in the era of e-commerce, it is necessary for agricultural product business enterprises or farmers to recognize the benefits of using e-commerce to market agricultural products and face up to its influencing factors and to build a support system, application system, and guarantee system with the support of the government to promote agricultural product e-commerce marketing to obtain healthy development. In this study, we study the construction mode of e-commerce agricultural product online marketing system based on the end of blockchain and improved genetic algorithm. This study adopts the design idea of coalition chain and proposes a multichain agricultural product trading information blockchain application technology including agricultural product trading information chain, user information chain, and agricultural product information chain. The agricultural product information chain provides detailed information of agricultural products and ensures the traceability and non-tamperability of the information. It automatically divides the profits of transactions through smart contracts to improve execution efficiency and reduce transaction costs and finally establishes a transparent, efficient, and applicable blockchain architecture for agricultural product transactions.

The increasingly extensive socialization trend has led to the comprehensive innovation of sports. The development of Chinese basketball should be based on the successful experience of the development of professional basketball in the United States. The development of China’s basketball has a solid cultural and mass foundation, but we should not be proud and arrogant. It is necessary to make full use of the critical and inherited attitude to learn and absorb the excellent and advanced knowledge of American basketball culture. At present, there are still some problems that need to be further explored. The purpose of this paper is to research and discuss the cultural differences of basketball between China and the United States and their concepts in basketball teaching based on the background of wireless network intelligence technology. This paper firstly analyzes and introduces the difference between the wireless network and wireless sensor network. The main design goal of traditional wireless networks is to improve service quality and efficiently use bandwidth and then consider energy saving, while the main design goal of sensor networks is to use energy efficiently, which is one of the most important differences between sensor networks and traditional networks, to analyze the differences between Chinese and American basketball cultures, to understand the impact of Chinese and American basketball cultural differences on basketball teaching concepts, and to compare and study the differences between Chinese and American basketball culture and their teaching philosophy in basketball. Using the method of this article, through the analysis of experimental data, we understand the impact of Chinese and American basketball cultural differences on basketball teaching concepts and find that Chinese and American basketball cultural differences play an important role in basketball teaching concepts, with a satisfaction rate of 66%. Through theory and experiments, based on the data, it is analyzed that the impact of the differences between Chinese and American basketball cultures on basketball teaching concepts reaches 50%. The research results show that the differences between Chinese and American basketball cultures play an important role in basketball teaching concepts and can be used to promote the development of basketball culture and skills.

It is common that airlines encounter a disruption of a flight schedule, which is mainly caused by resource shortages. In case of a disruption, subject to scarce resources, most of airlines lose flexibility of performing aircraft recovery on the basis of business interest priorities and need to delay, swap, and cancel flights. This paper proposes an air-rail inter-modal strategy to incorporate a High-Speed Rail (HSR) transport mode into an aviation network for aircraft recovery. The air-rail inter-modal strategy focuses on occasionally operational integration of existing airside and HSR infrastructure capacities. It is different from air-rail cooperation implemented in Europe which emphasizes a long-term strategy. In addition to modelling the air-rail inter-modal strategy, an inter-modal time-band network is presented. Modelling is applied to a pure aviation network and the inter-modal network. Comparison results show that the inter-modal air-rail strategy helps to reduce the number of cancelled flights and the total disruption cost.

Networking behaviors are a potentially important factor driving gender differences in social networks and contributing to the gender gap in career achievement, yet we know little about how and why ...

One advantage of online retail is that a large number of products can be displayed at low cost. However, online retailers must decide which of these products to carry in inventory (stock items) and which to order from suppliers when a customer places an order (nonstock items). In this paper, we empirically investigate how carrying a product in inventory affects its online sales. We use data from a European furniture and interior design retailer consisting of daily sales transactions and inventory data covering 18 months. We use a quasi-natural experiment—random transitions of products in and out of inventory at the retailer’s central warehouse—to estimate the causal effect of carrying inventory on sales. Our results show a strong and statistically significant increase in sales of, on average, 65% associated with having the product available in stock. More interestingly, this effect differs between products and is moderated by the price of the product: sales of more expensive products are less sensitive to the product being in stock. We use these results to draw insights on which types of items to carry in inventory. This paper was accepted by Victor Martínez-de-Albéniz, operations management. Supplemental Material: Data are available at https://doi.org/10.1287/mnsc.2023.4777 .

The professional socio-psychological competence of a mentor in the field of physical culture is a complex multifaceted system that aims to obtain and develop a sufficient level of competence for productive professional activity in the process of learning and practice. The content of the socio-psychological competence of the mentor in the field of physical culture carries a set of knowledge, skills and abilities, the possession of which allows you to work in the chosen profile. The task of the mentor is to accompany constantly. In practice, mentoring is understood as a tougher, authoritarian type of relationship. The mentor directs his efforts to support and open opportunities for beginners and «young people». The model of the mentor's relationship is determined by the relationship between him and the ward, as well as expectations of the results of the parties regarding the topic and form of cooperation. The mentor's work with the ward is based on a developed action plan called a process. The mentoring process is not homogeneous. The socio-psychological competence of a mentor in the field of physical culture becomes effective if it is carried out based on sound theoretical and practical principles that reveal the readiness of physical culture mentors to organize physical culture and health environment, considering the developed concept and appropriate organizational support., Професійна соціально-психологічна компетентність ментора у галузі фізичної культури є складною багатогранною системою, що спрямована на здобуття та розвиток достатнього для продуктивної професійної діяльності рівня компетентності у процесі навчання та практичній діяльності. Завдання ментора супроводжувати постійно. Він спрямовує свої сили на підтримку, розкриття можливостей у початківців і «молодих». Модель стосунків ментора визначається взаєминами між ним і підопічним, а також очікуванням результатів сторін відносно теми і форми співпраці. Соціально-психологічна компетентність ментора у галузі фізичної культури набуває ефективності, якщо вона здійснюється на основі обґрунтованих теоретичних і практичних засад, що розкривають готовність менторів фізичної культури до організації фізкультурно-оздоровчого середовища з урахуванням розробленої концепції та відповідного організаційно-методичного супроводу.

Biodiversity is crucial for supporting ecosystem functioning, yet some species play a disproportionate role in maintaining complex ecological processes. Ecosystem engineers are species that directly influence ecosystems by modifying biophysical environments, creating novel habitats, altering biogeochemical cycles, increasing biodiversity and/or modulating ecological processes. Although these species may substantially influence ecosystem functioning, their role is often overlooked and difficult to quantify. Understanding the status, dynamics and trends of ecosystem engineers is essential for mitigating biodiversity loss and maintaining healthy ecosystems. This review reveals the common but underappreciated roles that ecosystem engineers play in ecosystem functioning across many different taxa, biomes and ecological processes. We first synthesise how knowledge of ecosystem engineering improves our understanding of species interactions and the ecological processes underlying both ecosystem functioning and BEF relationships. We provide a conceptual model for addressing the effects of ecosystem engineers in BEF research and ecological dynamics. We provide a ‘how to’ analytical framework for monitoring and quantifying changes in ecosystem engineers and their effects on ecosystem functioning. This framework includes (i) what variables to measure, how and at which scale; (ii) experiments involving species exclusion or removal, introduction and comparative designs when experimental manipulation is not feasible and (iii) statistical, data-driven and theory-driven models. We discuss how to leverage ecosystem engineering in the context of current global change and ecosystem restoration efforts. Including ecosystem engineers in conservation and restoration programs, when implemented in the appropriate context and supported by an understanding of ecological mechanisms and processes, may be crucial for sustaining biological diversity and functional ecosystems.

A designer is privately informed about the state and chooses an information-disclosure mechanism to influence the decisions of multiple agents playing a game. We define interim-optimal mechanisms, a subset of incentive-compatible mechanisms that are optimal in the sense that the informed designer cannot credibly find an alternative mechanism that strictly improves his interim payoff. We prove that an interim-optimal mechanism exists and that every interim-optimal mechanism is a perfect Bayesian equilibrium outcome of the informed-designer game. An ex-ante optimal mechanism may not be interim optimal, but it is when it is ex-post optimal. Likewise, the unraveling outcome in disclosure games is interim optimal. We provide a belief-based characterization of interim-optimal mechanisms and compare them with ex-ante optimal ones in common economic environments. In settings with strategic complements and binary actions, every ex-ante optimal mechanism is interim optimal. We compare interim optimality to other solutions of informed-principal problems.

This exploratory case study finds evidence that the development of a storage technology niche in Ontario is being strategically managed through different stages by stakeholders within the system. It suggests that the complementary relationship between storage innovations and smart grid transitions supports the strategic management of a storage niche. It also suggests that the development of this niche supports the electricity system transition to smart grid. The study employs the Technology Innovation System (TIS) and Strategic Niche Management (SNM) analysis frameworks predominantly used by authors to study systems in Europe. By presenting empirical data from a jurisdiction outside of Europe, this research contributes to the growing theory on the formation of niches and the influence of complementarity on innovations in large technical systems. It also offers insights to practitioners within this sector, including the new entrants, incumbents and policy makers. Further research is recommended to determine the generalizability of these findings.

Teaching Chinese as a foreign language is a very important part of teaching Chinese as a foreign language, and morphemes account for a large proportion of Chinese characters. In this paper, a questionnaire survey on the cognition of morphemes was conducted for each grade of students in the School of International Cultural Education of Heilongjiang University. Through the survey, it was concluded that international students in the Chinese culture circle and non-Chinese culture circle affect the cognition of morphemes at the primary stage, and a study on the teaching of morphemes in teaching Chinese as a foreign language based on the assistance of Internet of Things was proposed to analyze that students learning Chinese no longer affect the cognition of morphemes. In teaching Chinese as a foreign language, the use of the Internet of Things system and the introduction of video sensors (mainly for the access and computer analysis of spoken Chinese as a foreign language learner model) and voice sensor (mainly for the Chinese as a foreign language learner voice access and computer analysis), with the standard spoken language pattern in the software and the comparison of standard pronunciation, the oral mode and pronunciation of TCSL learners can be corrected. The experiment knows the biases that international students are prone to when learning Chinese characters and summarizes the implications for teaching Chinese characters to foreigners; in addition, the higher the level of learning, the higher is the degree of cognition of morphophonetic characters.

With the promotion of China’s international status, the study of Chinese characters has become the trend of scholars all over the world. Nowadays, the international promotion of Chinese has become an important part of the national diplomatic strategy. With the rapid development of big data visualization technology, Chinese culture can be spread quickly, and it is easy to achieve the above requirements to achieve visual accessibility. In view of the problems existing in the current dissemination of Chinese culture, such as too scattered dissemination content, unsystematic dissemination channels, and poor dissemination effect, this paper puts forward a method of Chinese character culture dissemination based on big data visualization. Firstly, the visual features of Chinese characters are recognized, and the rules of Chinese characters are detected; secondly, the large data visualization analysis of Chinese character imaging is carried out, and the performance comparison under different iterations is compared. Chinese visual technology has obvious advantages in the effect and performance of Chinese character transmission. Finally, the development trend of Chinese communication is analyzed, and the acceptance, speed, coverage, understanding, learning degree, and practical degree of Chinese communication abroad are compared. The big data visualization model has certain advantages in functional comparison.

The expansion of event majors in China is still unable to satisfy the demand of the fast-growing event industry. Keeping graduates in the event industry could help solve the labor shortage of the industry. However, existing literature has overlooked the influencing mechanism on Chinese event students' job pursuit intention. To address this research gap, the current study aims to investigate how career awareness affects Chinese event students' job pursuit intention. This research also examines the mediating effect of career satisfaction and the moderation effect of career self-efficacy. Based on the signaling theory and self-efficacy theory, the present study develops an integrated research model that includes career awareness, career satisfaction, career self-efficacy, and job pursuit intention. A total of 198 usable responses from 18 event undergraduate programs were collected in China. Results show that Chinese event students' career awareness positively associates with enhanced career satisfaction, which subsequently improves their intention to stay in the event industry. This effect is fully mediated by career satisfaction. Moreover, the current study demonstrates the moderating effect of career self-efficacy between career satisfaction and job pursuit intention.

China Internet plus agriculture was first put forward in 2015 by the Chinese government’s work report, laying the foundation for the development of Internet plus agriculture and promoting the rapid growth of e-commerce marketing of agricultural products. The combination of agricultural product marketing and e-commerce effectively reduces the intermediate links of agricultural product sales. Many e-commerce professional villages have sprung up in some rural areas across the country, and the number of rural e-commerce stores has continued to grow. At this stage, rural e-commerce has become a new way of agricultural trade, and rural e-commerce has formed a unique rural e-store. At present, the e-commerce market share of agricultural products in rural stores is very large, and its advantages are favored by the government, scientific research institutions, and agricultural products processing enterprises. However, with the gradual development of rural e-commerce, it has also encountered many difficulties. Based on this point, this study applies deep learning and data mining to optimize e-commerce marketing. First, with the growth of the online scale of agricultural product transaction data, the creation of traditional shallow model cannot meet the needs of online data processing. Therefore, this study decides to use the deep learning theory for optimization. It has excellent performance in the technical fields of big data processing and image and voice processing and has strong construction ability, which can effectively represent the characteristics of the model. Combined with the characteristics of e-commerce agricultural products processing and consumer practice, this study designs and develops a new customer value evaluation model based on data mining and e-commerce agricultural products value characteristics in the field of e-commerce. By combining deep learning and data mining technology, this study applies it to the field of e-commerce, so as to promote the transformation of marketing optimization.

This article aims to explain the dimensions, models, stages, and affecting factors in the curriculum innovation process. Curriculum becomes very important in educational institutions because the curriculum is the "heart" of education. This research uses a descriptive qualitative approach with library research methods, using synthesis and content analysis. The results showed that the curriculum is a set of tools to achieve a goal, ranging from planning, and implementation to evaluation. Innovation or curriculum renewal needs to be done because education practitioners must adjust to the development of a society that is always changing and continues to grow. Innovations appear to answer critical issues in education. There are two models of innovation processes: the individual and the organizational models. Effecting factors in the curriculum innovation process are the vision-mission of education, population growth, the development of science-technology, and the relevant educational demands. Innovation must be the result of original and creative thinking. The application of innovation must be efficient, easy to use, and serves comfort for students, teachers, and practitioners of education.

The rapid development of online technology has facilitated the gradual growth and development of e-commerce and online marketing, creating a new business model and new opportunities. This has had a major impact on the future development of the market economy and the international competitiveness of companies and countries. At the same time, its appearance has also subverted the traditional retail market, and the convenience, reliability, and security of payment have been quickly recognized by people. Technological innovations represented by artificial intelligence have driven the development of the digital economy for decades. In order to better strengthen the statistics of the online shopping market and promote the development of the real economy, this study discusses the analysis of consumer behavior in online shopping based on the market changes of artificial intelligence and digital economy. Through the questionnaire, it can be found that all age groups have been exposed to online shopping, most of them are young people, and the number of shopping per month is still concentrated between 4 and 11 times. The study also examined the size of China’s online retail market and found that there were 820 million Internet shoppers in China by December 2021, which is forecast to be 910 million by 2022. The report also found that the B2C market share will reach nearly 61% in 2021 due to the B2C model featuring higher quality goods and more guaranteed services.

An important sign of the accessibility of Braille information is the realization of the mutual translation between Chinese and the Braille. Due to the irregularity and uncertainty of the Prevailing Mandarin Braille, coupled with the lack of a large-scale Braille corpus, the quality of Chinese-Braille translation seems to be poor. In July 2018, the National Language Commission released the “Chinese Common Braille Scheme” and advocated replacing the “Prevailing Mandarin Braille.” Aimed at improving translation accuracy, this research, which is based on the self-built Chinese Common Braille corpus and combined with the HanLP (Han Language Processing) dictionary and the Chinese-Braille word corpus (a Braille word segmentation and concatenation dictionary for generating a unigram language model), uses the n-gram language model to design and implement a Chinese-Braille intertranslation system that integrates Chinese and Braille Word Segmentation and Concatenation Rules. More importantly, this research proposes an experimental plan for improving the Braille Word Segmentation and Concatenation Rules using a Chinese-Braille word corpus. Experiments show that in the field of educational literature, the accuracy rate of translation from Chinese to Chinese Common Braille has reached 95.01%, and the accuracy of Chinese Common Braille to Chinese translation has reached 90.15%.

China is a large agricultural country, but the family-based business model restricts agricultural production, resulting in the relatively backward intellectualization of agriculture. With the development of new science and technology, the application of Internet of Things technology in agricultural production can intelligently manage and monitor the production, processing, transportation, and sales of agricultural products at any time, improve product quality, safety, and production efficiency, increase economic income, and guide the support of agricultural supply chain financial services to agricultural production. In order to explore the role of agricultural supply chain financial services in agricultural development and the application of Internet of Things technology in agricultural production, this paper constructs a model and finds that the effective use of agricultural supply chain financial services is conducive to the development of agriculture and provides convenience for the realization of agricultural diversification and intelligent construction.

We investigate whether a firm’s financial statement comparability is associated with the firm’s tax strategy. We hypothesize that external observers (e.g., press, shareholders, analysts, and tax authorities) can better detect a firm’s atypical tax strategy when the firm has high financial statement comparability with its industry peers. Detection and its consequent penalties should restrain firm managers from choosing tax strategies that deviate significantly from those of industry peers. Using firms’ uncertain tax benefits (UTBs) as a proxy for tax avoidance, we find that the UTBs of firms with high financial statement comparability move toward their industry peers in subsequent periods. Results suggest that comparability reduces tax aggressiveness for high tax-avoidance firms and enhances tax aggressiveness for low tax-avoidance firms, in comparison with those of industry peers. Overall, these findings indicate a strong within-industry harmonization in tax avoidance for firms with high financial statement comparability.

The self-impedance of the steel rail, as the signal transmission medium in the electrified railway track circuit, has a direct impact on the track circuit’s transmission performance. The finite element method is the most common method for calculating rail impedance, although it has a number of drawbacks, including a complicated model, a long computation time, and poor accuracy. The partial element equivalent circuit (PEEC) approach is used in this paper to provide a method for determining rail self-impedance. Firstly, the rail equivalent method is determined by analyzing the physical model of the rail. Considering the skin effect, the PEEC model of the rail is established. The internal impedance of the rail can be obtained by solving the equivalent circuit. The external impedance considering the influence of the earth is calculated by the Carson impedance calculation formula, which is processed by the segmented linear approximation method. The rail’s self-impedance is determined using the two procedures together. Finally, the actual measurement data verified the PEEC method to calculate the rail impedance. Compared with the finite element method (FEM), the calculation accuracy of the PEEC method is higher. The current frequency, the height of the rail from the ground, and the earth’s conductivity impact on the rail’s self-impedance are analyzed. The results show that the PEEC technique can be used to calculate the rail’s self-impedance and that the impact of current frequency, rail height above the ground, and ground conductivity on the rail’s self-impedance may be accurately represented. The self-impedance computation of the track circuit provides a theoretical basis.

In this article, we study the distribution, ordering, and pricing strategies when the supplier has a limited output and the retailer has substitute suppliers in a fresh agricultural product supply chain. The Stackelberg game method is adopted to study the optimal strategy of suppliers and retailers with suppliers as the leader and retailers as the follower. The results show that the wholesale price and selling price of suppliers are related to the price of substitutes and the substitution rate, the wholesale price and online selling price increase when the retailer introduces high-quality substitutes. When substitutes exist, the supplier is willing to distribute more fresh agricultural products to retailers. As the substitution rate increases, suppliers are willing to distribute more quantities. Therefore, retailers should choose more suppliers and fresh agricultural products with a higher substitution rate.

We consider a three-level fresh agricultural product supply chain consisting of a producer, a supplier, and a retailer, where the producer plants the initial fresh agricultural products with yield uncertainty, the supplier is the leader of the supply chain and the designer of the contracts, and the retailer sells processed products with random demand and spot price. This paper discusses coordination mechanism of wholesale price contracts or option contracts between the supplier and the retailer and wholesale price contracts between the supplier and the producer. Based on this, we not only explore the conditions for supply chain full coordination and Pareto improvement but also analyze the effect of the retailer’s spot market volatility by comparing two scenarios of the retailer with or without a random spot market. Results show that the wholesale price contract cannot coordinate the supply chain regardless of whether the retailer has a random spot market or not. The supply chain can be simultaneously fully coordinated and achieve Pareto improvement by setting reasonable option contract parameters, but the conditions for coordination are rigorous. When the expected value of reduction from the retailer’s spot market in unit shortage loss cost is greater, the total profit of supply chain will increase. Numerical analysis shows that the option exercise price must be set higher when the retailer has a spot market to achieve Pareto improvement. The loss rate in distribution process and other volatility risks will also affect the coordination of the agricultural supply chain.

The use of cloud technology has increased in many businesses.Cloud providers should handle privacy and security concerns as a top priority. Customers are increasingly less interested in dealing with "individual cloud" suppliers due to potential issues such as availability and performance failure and the threat of hostile intruders in the individual cloud. This study focuses on the problems regarding cloud computing's data security. Usage of cloud computing wish to avoid using an unscrupulous cloud provider because their information and data will be transferred with a third party. Protecting sensitive and confidential information from attackers or malicious insiders. Keywords: Security, Individual cloud, Multi-cloud.