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Personalized news recommendations shape social media users' information environment. However, whether news recommendation algorithms asymmetrically influence users' news engagement remains largely unknown. Drawing on the three-level digital divide framework (access, use, and outcomes), we test a moderated mediation model in which social media usage motivations influence social capital via news engagement, conditional on using algorithmic news. Using two waves of survey data from South Korea (N = 948), the results show that the indirect effects of motivations for social media use on social capital via news enagement are conditional on the level algorithmic news usage. News algorithms enable information- and socialization-oriented users to increase news engagement and develop social capital but fail to help highly entertainment-focused users increase news engagement, and thus, they do not develop social capital well. We discuss the possibility that news recommendation algorithms lead to a Matthew effect in which the poor become poorer and the rich become richer, exacerbating information inequality. [ABSTRACT FROM AUTHOR]

We start out from Harriet Zuckerman's study of the US scientific ultra-elite of Nobel laureates, in which Robert Merton's idea of 'Matthew effects' as a key mechanism in the creation of social inequalities was first introduced. We then consider two issues arising from critical commentary on this study by Elisabeth Crawford, a historian of science. First, how far can a scientific ultra-elite be shown to exist as a collectivity that is socially distinctive? Second, how far is Zuckerman's account of the formation of the US ultra-elite trough 'bilateral associative selection' between scientific masters and their would-be apprentices historically specific to the US? In the UK case, we compare the social origins and educational careers of members of two possible scientific ultra-elites, defined by differing degrees of stringency, with those of other elite scientists. We find that as one moves from the elite to the less stringently defined ultra-elite, there is little evidence of increasing social stratification but that such evidence does emerge in moving to the more stringently defined ultra-elite. We also show through two contrasting Cambridge case studies, that the underlying social processes that Zuckerman identifies in ultra-elite formation in the US are also present in these UK contexts. [ABSTRACT FROM AUTHOR]

The goal of this study is to analyze the relationship between funded and unfunded papers and their citations in both basic and applied sciences. A power law model analyzes the relationship between research funding and citations of papers using 831,337 documents recorded in the Web of Science database. The original results reveal general characteristics of the diffusion of science in research fields: a) Funded articles receive higher citations compared to unfunded papers in journals; b) Funded articles exhibit a super-linear growth in citations, surpassing the increase seen in unfunded articles. This finding reveals a higher diffusion of scientific knowledge in funded articles. Moreover, c) funded articles in both basic and applied sciences demonstrate a similar expected change in citations, equivalent to about 1.23%, when the number of funded papers increases by 1% in journals. This result suggests, for the first time, that funding effect of scientific research is an invariant driver, irrespective of the nature of the basic or applied sciences. This evidence suggests empirical laws of funding for scientific citations that explain the importance of robust funding mechanisms for achieving impactful research outcomes in science and society. These findings here also highlight that funding for scientific research is a critical driving force in supporting citations and the dissemination of scientific knowledge in recorded documents in both basic and applied sciences. This comprehensive result provides a holistic view of the relationship between funding and citation performance in science to guide policymakers and R&D managers with science policies by directing funding to research in promoting the scientific development and higher diffusion of results for the progress of human society. [ABSTRACT FROM AUTHOR]

Scientific articles are used to be cited according to various factors, such as their quality, novelty, methodology, etc. There are also other factors which were identified to influence the citation impact of articles, such as the length of the articles, the number of authors, and the number of references etc. The influence of the number of references was analysed in this study. Journals from various research fields, such as Chemical Engineering, Mathematics, Computer Science, Neuroscience, and Psychology, were ranked according to their SCImago Journal Rank (SJR) values into deciles for the years 2000, 2005, 2010, 2015, 2020, and 2023. The number of references related to one article was calculated for each decile and then correlated against the decile ranking (from 1 to 10). Significant correlation coefficients ranging from -0.880 to -0.982 were obtained. This approach is different from the common approach to analyse the citations and references of the individual articles. The negative slopes of such linear plots demonstrate that the numbers of references are related to the citation impact of journals and, in turn, articles published by them. This is in line with the journal-article-level Matthew effect so that the authors prefer to read the higher-ranked journals and then cite their articles. [ABSTRACT FROM AUTHOR]

Digital service trade has become an important engine of world economic growth, and its competitive landscape is also evolving. We construct domestic value-added networks of digital service exports (DVAN-DSEs) from 1995 to 2018 based on the world input-output table, and explores their structural evolution and determinants using Temporal Exponential Random Graph Model. We find that (a) the DVAN-DSEs present the features of agglomeration, heterogeneity, reciprocity and unevenness. (b) The United States and European countries are the core in DVAN-DSEs. (c) Preference attachment, structural embeddedness, delayed reciprocity, stability, variability, Matthew effect in GDP, population and Internet coverage, geographical proximity, cultural similarities, and regional trade agreements play important roles in the evolution of DVAN-DSEs. (d) Structural embeddedness and geographic proximity only facilitate new relationship construction, while other factors influence both relationship establishment and maintenance. Countries should build network facilities, expand trading partners and promote trade agreement negotiations to facilitate the development of digital service trade. [ABSTRACT FROM AUTHOR]

China's manufacturing industry needs to change from a high-emission model to one that is more environmentally friendly to reduce air pollution and achieve sustainable growth. Therefore, it is important to decrease manufacturing waste gas emissions by improving green productivity. This paper expands on the theories of green economic growth and sustainable development to present a framework for analysis of manufacturing green productivity at various levels of air pollution. It applies the Metafrontier Malmquist Luenberger index and SBM model to data from 30 Chinese manufacturing sectors from 2012 to 2022 to identify the obstacles to developing green productivity in the manufacturing sectors. The results show that: (1) From 2012 to 2022, the overall waste gas emission efficiency and GTFP of China's manufacturing industry showed an increasing trend. (2) The manufacturing industry with light air pollution had the fastest growth in GTFP, followed by manufacturing with heavy air pollution, and manufacturing with moderate air pollution had the lowest. (3) The primary driver of GTFP growth is technological progress, while technical inefficiency has severely hindered GTFP growth. (4) There is a "Matthew effect" in the green productivity of China's manufacturing industry. High waste gas emission efficiency often accompanies high levels of GTFP, and vice versa. Finally, this paper proposes policy suggestions to improve the green productivity of the manufacturing industry and reduce air pollution. [ABSTRACT FROM AUTHOR]

The farmland system in the global terrestrial ecosystem has dual attributes as both a carbon source and a carbon sink, playing a crucial role in controlling carbon emissions and mitigating global warming. Using carbon source and sink accounting of farmland ecosystems, we applied methods such as standard deviation ellipse, Tapio decoupling theory, and Markov chain to analyze the spatiotemporal changes, response mechanisms, and evolutionary trends of regional carbon effects. The results indicated that from 2011 to 2021, the farmland ecosystem in the middle and lower reaches of the Yangtze River consistently acted as a carbon sink. However, the net carbon sink showed slight fluctuations and significant spatial differences. The migration range of the net carbon sink center in the farmland ecosystem of the middle and lower reaches of the Yangtze River was relatively small, ranging from 115.52 to 115.77° E and 30.14 to 30.27° N. The decomposition of the Tapio decoupling index between the net carbon sink of the farmland ecosystem and agricultural output value showed the order of effects on their coupling relationship as follows: agricultural mechanization level > agricultural mechanization efficiency > agricultural output value > planting scale. The probability of maintaining the original state of net carbon sink in various cities in the middle and lower reaches of the Yangtze River (over 77%) was much higher than the probability of transfer, making it difficult to achieve a leapfrog growth in net carbon sink. The net carbon sink at the city scale exhibits the Matthew effect and spatial spillover effect. The above research results clarify the spatiotemporal changes in carbon effects in agricultural production at multiple levels, including city, province, and region. They also provide a theoretical basis for formulating differentiated regional emission reduction and sink enhancement strategies in the middle and lower reaches of the Yangtze River, promoting the rapid development of low-carbon agriculture in China. [ABSTRACT FROM AUTHOR]

The rapid pace of urbanization and global climate change necessitates a thorough assessment of urban ecological resilience to cultivate sustainable regional ecosystem development. Cities along the Yangtze River face an intensifying conflict between ecological preservation and socio-economic growth. Analyzing the ecological resilience of these urban centers is essential for achieving equilibrium in regional urban ecosystems. This study proposes a "system process space" attribute analysis framework, taking into account urban development processes, ecosystem structure, and resilience evolution stages. Utilizing data from 45 Yangtze River cities, we establish a "Driver, Pressure, State, Impact, and Response" (DPSIR) evaluation index system to evaluate changes in ecological resilience levels and evolution trends from 2011 to 2022. Our findings indicate that: (1) The ecological resilience index of Yangtze River cities increased from 0.177 to 0.307 between 2011 and 2022, progressing through three phases: ecological resilience construction, rapid development, and stable development. (2) At the city level, ecological resilience along the Yangtze River exhibits uneven development characteristics. Upstream cities display a significant "stepped" pattern, midstream cities exhibit a significant "Matthew effect", and downstream cities present a pyramid-shaped pattern. While regional differences in ecological resilience persist, overall polarization is gradually decreasing, intercity connections are strengthening, and there is a growing focus on coordinated regional development. (3) The spatial distribution of ecological resilience in Yangtze River cities demonstrates both continuity and evolution, generally forming a "core-edge" clustered pattern. Based on these findings, we recommend enhancing inter-city cooperation and connectivity, addressing imbalances in urban ecological resilience, and promoting high-quality ecological resilience development along the Yangtze River through tailored development strategies for each city. [ABSTRACT FROM AUTHOR]

A resilient innovation ecosystem is an important guarantee for enhancing industrial competitiveness. Knowledge spillover is the key driving force to enhance system resilience. Firstly, we use the MEREC-CoCoSo method to calculate the resilience level of the integrated circuit (IC) innovation ecosystem and analyze the evolution trajectory of the resilience before and after the emergence of the "stuck-neck" problem. Secondly, based on the panel data of 30 provinces (autonomous regions and municipalities directly under the central government) in China from 2011 to 2021, this paper analyzes the mechanism of the impact of intra-regional knowledge spillovers on the resilience of IC innovation ecosystems using the fixed-effect model and analyzes the spatial effect of inter-regional knowledge spillovers on the resilience of innovation ecosystems using the spatial Durbin model under the human capital matrix. Finally, we analyze the regulating role of contractual and relational governance mechanisms and try to open the "black box" of governance. The result shows the following: (1) The polarization of innovative ecosystem resilience of integrated circuits is gradually increasing, with strong spatial agglomeration, high–high agglomeration, low–low agglomeration, and low–high dispersion, and there is an obvious "matthew effect" and "siphon effect". (2) Both intra- and inter-regional knowledge spillovers contribute significantly to the resilience of IC innovation ecosystems. The contractual governance mechanism can effectively enhance the impact of knowledge spillovers on the resilience of innovation ecosystems in the region, and the relational governance mechanism has a positive impact on the resilience of innovation ecosystems in neighboring regions. (3) Heterogeneity results show that knowledge spillovers within the Pan-PRD region have a significant positive impact on innovation ecosystem resilience. Knowledge spillovers between regions with low innovation capacity have a double effect on innovation ecosystem resilience, and knowledge spillovers between regions with "talent highlands" have a facilitating effect on innovation ecosystem resilience. Accordingly, policy recommendations are put forward to open up channels for innovation knowledge spillover, realize effective allocation of innovation resources, and optimize the system of innovation talents. [ABSTRACT FROM AUTHOR]

In light of the crucial role of collaborative R&D in advancing technology within the new energy vehicle industry, this study seeks to explore ways to overcome the barriers to technological innovation by establishing an effective collaborative innovation network. Utilizing joint patent-authorized data from China's new energy vehicles between 2005 and 2019, the collaborative innovation network was developed, and the Exponential Random Graph Model (ERGM) was employed to analyze its formation and evolution mechanisms. The results indicate that the network has undergone significant expansion, closely linked to strong national policy support and the active involvement of innovation participants. The network exhibits effects of expansion, transfer, and closure. External attribute analysis revealed the Matthew effect and geographical compatibility effect and found that organizational compatibility tends to foster complementary cooperation. The findings offer insights into optimizing collaborative innovation networks in the NEVs industry and suggest strategies for policymakers and industry players to promote collaborative innovation. [ABSTRACT FROM AUTHOR]

We build a multi-period pricing model between a blockchain-technology-supported platform and a traditional platform, where the blockchain-technology-supported platform provides a higher value for customers. Customers are influenced by network effect, that is, they value a platform more if the platform has more users. As either platform can adopt static pricing or dynamic pricing, four scenarios may occur. By deriving the equilibrium of each scenario, we reveal the 'Matthew effect' caused by network effect, that platform advantage (from adopting blockchain technology) or disadvantage (from not adopting blockchain technology) accumulates as time goes by. Thus, platforms are advised to adopt the blockchain technology antecedent to the competitors. Network effect, which amplifies the benefit of initial users, may intensify price competition and harm both platforms. By comparing the four scenarios, we derive the equilibrium pricing strategies: when network effect is weak, one platform adopts static pricing and the other adopts dynamic pricing; when network effect is medium, the blockchain-technology-supported platform adopts static pricing and the traditional platform adopts dynamic pricing; and when network effect is strong, both platforms adopt dynamic pricing. Dynamic pricing is more desirable for the traditional platform relative to the blockchain-technology-supported platform. [ABSTRACT FROM AUTHOR]

Agritainment is one of the essential aspects of rural tourism and plays an important role in the economic transformation and revitalization of rural areas. Taking 9200 agritainment resorts in China as a research object, this paper systematically uses geospatial analysis methods to analyze their spatial distribution patterns and influencing mechanisms. The results indicate: (1) All types of agritainment have a condensed distribution in space and are oriented in the northeast—southwest direction, with a central axis generally located in the Beijing–Zhengzhou–Wuhan line. (2) The distribution of agritainment is uneven across different spatial scales, and there are high-density clusters in the Beijing–Tianjin–Hebei region, the Yangtze River Delta, and the Sichuan–Chongqing region as the core, and sub-high-density distribution areas in the Shaanxi–Gansu–Ningxia border, the southern coastal region, and the Xiangan–Jiang–Hubei border, manifesting prominent spatial distribution characteristics of large agglomeration and low dispersion. (3) Agritainment has a significant positive spatial autocorrelation. The Matthew effect is highly significant in space. The distribution of cold hot spots in the agritainment space shows a distribution pattern of "hot in the south and cold in the north." (4) The spatial distribution of agritainment is influenced by human factors such as society, economy, and the tourism industry as well as natural factors such as terrain, water systems, and climate. The intensity of influence of first-level human factors on the spatial distribution of agritainment ranks as follows: tourism industry factors (0.69) > social factors (0.37) > economic factors (0.30). The natural distribution of agritainment tends to be in humid plain and hilly areas with an altitude below 1000 m and annual precipitation above 800 mm. Agritainment is mainly distributed in the subtropical monsoon climate area adjacent to rivers. The research findings offer valuable insights for optimizing the spatial distribution pattern of agritainment in China, promoting the high-quality development of agritainment, and the sustainable development of rural tourism. [ABSTRACT FROM AUTHOR]

The History and Philosophy of Geography Research Group launched its undergraduate dissertation prize in 2008. This paper reflects on the dissertations submitted throughout its first decade, highlighting particular themes in Deleuzian-inspired vitalism and immanence, attention to the politics of knowledge production, and the emergence of critical physical geography. The paper also discusses the practice of awarding a prize, noting evidence that this is both shaped by, and reproduces, structural inequalities in academic work. The prize exhibits a particular geography and politics within the academic prestige economy. • Considers submissions to the Undergraduate Dissertation Prize of the History and Philosophy of Geography Research Group. • Highlights key themes from the dissertations reflecting trends in geography. • Notes that there is a geography and politics to undergraduate dissertation prizes. [ABSTRACT FROM AUTHOR]

Resilience serves as a crucial metric for gauging the sustainable development capacity of tourist destinations and has emerged as a novel focal point within the realm of "tourism man-land relationship." This study endeavors to formulate an evaluative index framework for the resilience of tourism destination environmental systems grounded in the "social-economic-ecological-facilities" dimension. Subsequently, employing the entropy weight model, spatial autocorrelation model, and Geodetector model, the research seeks to conduct a quantitative analysis of the spatio-temporal evolution characteristics and driving factors influencing the resilience of the tourism environmental system within the Yangtze River Economic Belt. The overarching objective is to offer a case-based reference that contributes to the interdisciplinary exploration of resilience theory and tourism environmental systems, enabling a scientific assessment of the sustainable development capacity of tourism destinations, and facilitating the optimization of the development habitat of the regional tourism industry. The results show that: (1) The resilience of the tourism environmental system demonstrates an overall ascending trajectory, albeit with a discernible fragility. The growth rate of resilience within each subsystem follows the sequence of "economic environment>social environment>facility environment>ecological environment." Moreover, the emergence of two resilience convergence clusters, namely "society-economy" and "facility-ecology," is observed. (2) The distribution of resilience levels within the tourism environmental systems of provinces and municipalities in the Yangtze River Economic Belt exhibits a noteworthy spatio-temporal transition. The resilience indices of the upstream, midstream, and downstream areas exhibit an upward trend, delineating a pattern of "upstream

Tourism is a strategic pillar industry of the national economy, playing a role in cultural prosperity, national unity and stabilizing the border. Border ethnic areas in western China are rich in cultural and tourism resources, and promoting the high-quality development of cultural and tourism integration is an important hand in promoting the interaction, communication and integration of various ethnic groups and casting a firm sense of Chinese national community. Taking the border ethnic areas as the research object, based on the multi-indicator panel data from 2011 to 2020, we measure the level of high-quality development of culture and tourism, analyze the spatiotemporal evolution of the coordination degree, and identify the driving factors. The study found that: (1) The level of high-quality development of culture and tourism in the border ethnic areas is generally on the rise, the impact of the new crown epidemic on tourism is obvious in 2020, and the level of high-quality development of culture is higher than the level of high-quality development of tourism due to the influence of historical and cultural precipitation and cultural exchanges. (2) The degree of coordination of high-quality development of cultural and tourism integration in all provinces and regions is rising in fluctuation, and the level of coordination is gradually optimized. The coordination level of high- quality development of cultural and tourism integration is higher in Guangxi and Yunnan, forming the "Matthew effect". (3) The investment level, policy support, market supply and transportation conditions are the important driving force for the high-quality development of cultural and tourism integration in the border ethnic areas, among which the investment level shows the strongest utility. The results of the study provide theoretical basis and data support for the high-quality development of culture and tourism integration in border ethnic areas, which can help strengthen the construction of cultural tourism, realize the transformation and upgrading of tourism, and enhance the vitality and influence of culture. [ABSTRACT FROM AUTHOR]

Responsible innovation is attracting theoretical and practical research attention worldwide due to global climatic changes, severe resource shortages and intensifying environmental deterioration. However, there are still no studies concerning the performance evaluation of responsible innovation in the marine industry. Based on the practices of blue economic zones in China, a responsible innovation performance evaluation system for the marine industry was developed. Based on the data from 2013 to 2018, the responsible innovation performance of the blue economic zone of the marine industry in Shandong Province was evaluated by principal component analysis. The results demonstrated that (1) There was a rank of regions in terms of the comprehensive responsible innovation performance from high to low: Qingdao > Yantai > Weifang > Weihai > Dongying > Binzhou > Rizhao. (2) Considering annual variations, the comprehensive performance of responsible innovation of different regions exhibited slight fluctuations; however, Weihai had demonstrated significant improvement since 2016. (3) The performance trends across various regions indicated that regions exhibiting high performance consistently expanded their advantage over the six-year period. There was a "Matthew effect" in regional development, particularly evident in the disparities between Qingdao and other regions. (4) In regions that rank at the lower end, such as Rizhao, Binzhou, and Dongying, the development of responsible innovation progressed slowly. Finally, some management suggestions to improve innovation performance in the blue economic zone of the marine industry were proposed. [ABSTRACT FROM AUTHOR]

The coupled and coordinated development of the digital economy and tourism economy has become an inevitable choice for achieving high-quality development in both sectors. This paper proposes a conceptual index system using entropy weight method and coupling coordination degree model for analysis of the coupling coordination relationship between digital economy and tourism economy. After that, the paper introduces the Moran's Index to examines the spatial heterogeneous effects of coupling coordination degree. This framework is applied to 41 cities in the Yangtze River Delta region during 2011–2021. The results show that the temporal changes of the coupling coordination relationship between digital economy and tourism economy in 41 cities are quite satisfactory, while the regional differences are large. Furthermore, the coupling degree between digital economy and tourism economy shows the strong spatial agglomeration effect, and the spatial proximity of regions with similar integration indicates that the "Matthew Effect" gradually highlights the clustering of high and low levels. Based on the results of analysis, this paper finally puts forward several policy recommendations to provide a referential path for the integration of digital economy and tourism. [ABSTRACT FROM AUTHOR]

In this paper, we study the problem of predicting popularities of questions in Community Question Answering (CQA). To address this problem, we propose a Posterior Attention Recurrent Point Process Model (PARPP) to take both the interaction of users and the Matthew effect into account for question popularity prediction. Our PARPP uses long short-term memory (LSTM) to encode the observed history and another LSTM network to record each step of decoding information. At each decoding step, it uses prior attention to capture answers that have a greater impact on the problem. When a new answer is observed, it uses Bayes' rule to modify prior attention and obtain posterior attention. Then, the posterior attention is used to update the decoding status. We further introduce a convergence strategy to capture the Matthew effect in CQA. We conduct experiments on a Zhihu dataset crawled from a famous Chinese CQA forum. The experimental results show that our model outperforms several state-of-the-art methods. We further analyze the attention mechanism in our model. Our analysis shows that the proposed attention mechanism can better capture the impact of each answer on the future popularity of the question, which makes our model more interpretable. Our study would shed light on other similar studies such as answer ranking in response to the question and finding experts who have expertise on the topics of the questions. [ABSTRACT FROM AUTHOR]

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The rapid development of intelligent technology characterized by robots under the fourth scientific and technological revolution provides a favorable opportunity for the accurate decision-making of urban pollution control and the effective achievement of the goal of carbon emission reduction in China. This research uses the robot penetration rate as a representative and characteristic index of industrial intelligence development, based on panel data from 108 cities in the Yangtze River Economic Belt (YEB) from 2006 to 2020. It then uses panel quantile regression, spatial measurement, and threshold effect models to provide a more thorough theoretical and empirical discussion of the impact, mechanism, and spatial effect of industrial intelligence development on urban carbon emission efficiency (CEE). Urban CEE may be greatly increased with the use of industrial intelligence, and this finding remains true even after endogeneity and robustness tests are controlled; From an action mechanism perspective, industrial intelligence advances technology, optimizes industrial structure, and ultimately enhances regional CEE; There is a Matthew effect on the degree of development of carbon emission efficiency, and the impact of industrial intelligence on CEE is more pronounced in non-resource-based cities and the lower portions of YEB; Urban CEE increases positively with the spatial spillover impact of industrial intelligence development. The ability for regional sustainable development will be significantly increased if cross-regional cooperative prevention and control of environmental governance can be successfully achieved. This study verifies the enabling effect of industrial intelligence development on the improvement of urban CEE, and provides enlightenment for China to improve industrial intelligence development strategies and policies to achieve regional high-quality development. [ABSTRACT FROM AUTHOR]

The patent transfer (PT) has been an essential means of technological catch-up and control for countries and regions. The development and diffusion of PT is influenced by space and network. Analyzing China’s patent transfer network (PTN) from 2001 to 2020 through spatial and complex network analysis, we found that the PTN became denser with significant Matthew effect, hierarchical and small-world properties. Beijing, Shanghai, and Shenzhen remained as national hubs, while new hubs like Suzhou, Guangzhou, Foshan, and Hangzhou, acting as intermediates, emerged. Network communities become more homogenised and geographically clustered due to the resonance effect. There was a shift from disperse hubs to spatial agglomerations, with the construction of long-distance shortcuts breaking spatial constraints on intercity patent transfer. [ABSTRACT FROM AUTHOR]

Resilience and efficiency are the key elements of sustainable development. Their synergistic advancement promotes the sustainable growth of the urban tourism economy. The study measures the resilience and efficiency of the urban tourism economy in 11 cities of Hebei Province, China, employing a weighting method and super-efficiency SBM model. Additionally, the study investigates the synergistic effects and evolutionary characteristics of resilience and efficiency using the Haken model. The research shows that the efficiency of the urban tourism economy acts as the order parameter, governing the evolutionary trajectory and direction of the urban tourism economy in Hebei Province. This parameter facilitates the dynamic transformation of the urban tourism economy from disorder to order and from low efficiency to high efficiency. The synergistic development of urban tourism economic resilience and efficiency in Hebei Province has gone through a benign evolution from a primary stage to a high stage, presenting a stable and sustained positive trend. However, significant spatial differences exist between cities, forming an "east-central-west" concave spatial pattern, and there is a "Matthew effect" among cities. [ABSTRACT FROM AUTHOR]

Rural areas provide ecosystem services (ESs) to urban metropolitan regions. These services are threatened by the constant pressure of urbanisation and new interest in rural development. This has heightened the conflict between environmental concerns and developmental needs, thereby presenting significant land management and rural planning challenges. Employing a quantitative measurement and optimisation framework, we investigate six representative ES variables to assess planning strategies that can address this contradiction. We used a suburban rural area around Nanjing, China, as our study area. We collected spatial data from 2005 to 2020 at two scales (village level and 500 m grid) to map ESs, quantify interactions (trade-offs and synergies among ES bundles), and identify the social, ecological, and landscape drivers of rural change. Based on this, rural planning strategies for optimising ESs at different scales have been proposed. Our findings include (1) spatial heterogeneity in the distribution of ESs, (2) the identification of seven synergistic and eight trade-off pairs among ESs, (3) a spatial scale effect in suburban rural areas, and (4) the spatial trade-offs/synergies of ESs exhibiting a 'Matthew effect'. The identification of key trade-offs and synergistic ES pairs and the categorisation of ES bundles form the basis for a multi-scale hierarchical management approach for ESs in the region. By examining the commonalities and variations in drivers across diverse scales, we established connections and focal points for spatial planning. We use these findings to propose spatial planning and landscape policy recommendations for rural suburban areas on multiple scales. This study aims to provide a comprehensive and detailed spatial optimisation strategy for rural areas that can help contribute to their revitalisation. [ABSTRACT FROM AUTHOR]

The goal of this study is a comparative analysis of the relation between funding (a main driver for scientific research) and citations in papers of Nobel Laureates in physics, chemistry and medicine over 2019-2020 and the same relation in these research fields as a whole.

Urban tourism is considered a complex system, and multiscale exploration of the organizational patterns of attraction networks has become a topical issue in urban tourism, so exploring the multiscale characteristics and connection mechanisms of attraction networks is important for understanding the linkages between attractions and even the future destination planning. This paper uses geotagging data to compare the links between attractions in Beijing, China during four different periods: the pre-Olympic period (2004–2007), the Olympic Games and subsequent 'heat period' (2008–2013), the post-Olympic period (2014–2019), and the COVID-19(Corona Virus Disease 2019) pandemic period (2020–2021). The aim is to better understand the evolution and patterns of attraction networks at different scales in Beijing and to provide insights for tourism planning in the destination. The results show that the macro, meso-, and microscales network characteristics of attraction networks have inherent logical relationships that can explain the commonalities and differences in the development process of tourism networks. The macroscale attraction network degree Matthew effect is significant in the four different periods and exhibits a morphological monocentric structure, suggesting that new entrants are more likely to be associated with attractions that already have high value. The mesoscale links attractions according to the common purpose of tourists, and the results of the community segmentation of the attraction networks in the four different periods suggest that the functional polycentric structure describes their clustering effect, and the weak links between clusters result from attractions bound by incomplete information and distance, and the functional polycentric structure with a generally more efficient network of clusters. The pattern structure at the microscale reveals the topological transformation relationship of the regional collaboration pattern, and the attraction network structure in the four different periods has a very similar importance profile structure suggesting that the attraction network has the same construction rules and evolution mechanism, which aids in understanding the attraction network pattern at both macro and micro scales. Important approaches and practical implications for planners and managers are presented. [ABSTRACT FROM AUTHOR]

Green technology transfer can help narrow the regional differences in green innovation, thereby contributing to a more coordinated green development. This study uses the social network analysis approach to explore the characteristics and regional differences in green technology diffusion in mainland China from 1985 to 2021. A unique dataset of patent transactions was used to construct green technology transfer networks. The findings demonstrate that energy-related technologies had the highest demand in the market. In addition, private sectors, especially multinational enterprises, were the most active network entities, whereas universities played a limited role in diffusion. Moreover, green patent transactions were highly localized and presented regional disparities. Resource-based regions with high pollution had lower green technology flows and formed a path dependence, whereas a few developed regions served as influential spreaders. The network exhibited a core-periphery pattern and dis-assortativity, thus creating a Matthew effect and widening the regional gaps. The absorbers and beginners tended to form connections with bilateral spillover, while peripheral provinces faced delinked risks. These findings help us understand the regional disparities and diffusion patterns of green technologies in China, thus accelerating the diffusion of green technologies. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is now present in nearly every aspect of our daily lives. Furthermore, while this AI augmentation is generally beneficial, or at worst, nonproblematic, some instances warrant attention. In this study, we argue that AI bias resulting from training data sets in the labor market can significantly amplify minor inequalities, which later in life manifest as permanently lost opportunities and social status and wealth segregation. The Matthew effect is responsible for this phenomenon, except that the focus is not on the rich getting richer, but on the poor becoming even poorer. We demonstrate how frequently changing expectations for skills, competencies, and knowledge lead to AI failing to make impartial hiring decisions. Specifically, the bias in the training data sets used by AI affects the results, causing the disadvantaged to be overlooked while the privileged are frequently chosen. This simple AI bias contributes to growing social inequalities by reinforcing the Matthew effect, and it does so at much faster rates than previously. We assess these threats by studying data from various labor fields, including justice, security, healthcare, human resource management, and education. [ABSTRACT FROM AUTHOR]

How digital economy (DE) empowers high-quality development of tourism (HQDT) has become a common concern among scholars. Given this, this study clarifies the theoretical connotation of DE enabling HQDT,and finds that: Micro, DE promotes efficiency improvements in tourism enterprises, with its economies of scale and Matthew effect reducing average costs, its economies of scope meeting diversified demand, and its long-tail effect improving supply-demand matching mechanism. Meso, DE can transform and upgrade tourism industry structure through industrial digitization and digital industrialization, and also form a new tourist industry form and value chain through cross-border integration. Macro, DE can stimulate innovation and flexibility of market players, increase new factor inputs in tourism, improve factor allocation efficiency, and advance macro regulation of the tourism market. Accordingly, the study conducts an empirical test based on panel data for 31 provinces in mainland China during 2011–2020. Results show that: ① DE positively influences HQDT, and the sub-dimensions all positively influence HQDT. ② DE has a heterogeneous impact on HQDT and shows spatial spillover effects. Finally, the study concludes with effective paths for DE promoting HQDT: "Promote digital infrastructure construction, accelerate tourism digital transformation, strengthen integration and innovation development, and overcome the challenges of tourism enterprises". [ABSTRACT FROM AUTHOR]

Scientists and funding agencies invest considerable resources in writing and evaluating grant proposals. But do grant proposal texts noticeably change panel decisions in single blind review? We report on a field experiment conducted by The Dutch Research Council (NWO) in collaboration with the authors in an early-career competition for awards of 800,000 euros of research funding. A random half of panelists were shown a CV and only a one-paragraph summary of the proposed research, while the other half were shown a CV and a full proposal. We find that withholding proposal texts from panelists did not detectibly impact their proposal rankings. This result suggests that the resources devoted to writing and evaluating grant proposals may not have their intended effect of facilitating the selection of the most promising science. [ABSTRACT FROM AUTHOR]

Gender equality in scientific research has gradually attracted attention from many countries. However, the possible interaction effect of gender on research funding has not been fully disclosed. This study conducts an empirical study to examine the possible influences of gender on research funding and its interaction effect with applicants' social influences, including their external cumulative advantages (Matthew effect) and internal cognition (halo effect). In total, 1465 research projects from 2015 to 2021 are analysed to examine the proposed hypotheses. The results reveal that there is no gender inequality in the association between the Matthew effect and future research funding. However, the halo effect is easily affected by gender. For male scientists, higher institutional reputation and past research performance lead to higher future research funding. However, female scientists have no such benefits. According to the findings, this study suggests that female scientists should give priority to accumulating their own external resource advantages and participate in academic activities more frequently to activate women's participation in scientific research and academia. [ABSTRACT FROM AUTHOR]

Increasing air pollution not only affects the population's health but also changes its consumption structures and patterns. Using China Family Panel Studies, this study investigates the relationship between air pollution and household consumption. The findings reveal that household consumption is considerably affected by air pollution: One standard deviation rise of PM2.5 concentration will decrease the household consumption by 8.7%. Moreover, this effect is irreversible in the short term. What is more, air pollution has significantly changed consumption structure and patterns. Heterogeneous analysis indicates that the influence of air pollution on consumption generates the so-called Matthew Effect, wherein medium and low-income and rural households are exposed to a greater negative effect. Mechanism tests indicate that air pollution may reduce household consumption through three channels: increase negative emotions, decrease outdoor activities, and depress future expectations. The conclusions drawn in this paper enrich our understanding of the economic impact caused by air pollution and bring important significance to the government in promoting the coordination and sustainable development of the environment and economy. [ABSTRACT FROM AUTHOR]

The road to the top is never easy. This study investigated whether the career trajectories of top-level men's and women's badminton players could be predicted by their age at first major debut and the time taken to reach the top 150. Data from the BWF from October 2009 to October 2022 were analyzed using a predictive linear regression model with Bayesian inference, adjusting for anthropometric factors. The results suggested that age at debut influences career high rankings among over 120 elite players. Additionally, observations challenged the Matthew effect in early-career success for young players, proposing that inherent talent may be more significant than early nurturing. The study also examined the potential impact of relative age and early specialization in sports. [ABSTRACT FROM AUTHOR]

Fluorescence imaging, a key technique in biological research, frequently utilizes fluorogenic probes for precise imaging in living systems. Tetrazine is an effective emission quencher in fluorogenic probe designs, which can be selectively damaged upon bioorthogonal click reactions, leading to considerable emission enhancement. Despite significant efforts to increase the emission enhancement ratio (IAC/IBC) of tetrazine‐functionalized fluorogenic probes, the influence of molecular aggregation on the emission properties has been largely overlooked in these probe designs. In this study, we reveal that an ultrahigh IAC/IBC can be realized in the aggregate system when tetrazine is paired with aggregation‐induced emission (AIE) luminogens. Tetrazine amplifies its quenching efficiency upon aggregation and drastically reduce background emissions. Subsequent click reactions damage tetrazine and trigger significant AIE, leading to considerably enhanced IAC/IBC. We further showcase the capability of these ultra‐fluorogenic systems in selective imaging of multiple organelles in living cells. We term this unique fluorogenicity of AIE luminogen‐quencher complexes with amplified dark‐bright states as "Matthew effect" in aggregate emission, potentially providing a universal approach to attain ultrahigh IAC/IBC in diverse fluorogenic systems. [ABSTRACT FROM AUTHOR]

The inclusion of scientific journals in prestigious indexers is often associated with higher citation rates; journals included in such indexers are significantly more acknowledged than those that are not included in them. This phenomenon refers to the Matthew effect on journal citations, according to which journals in exclusive rankings tend to be increasingly cited. This paper shows the opposite: that the inclusion of journals in local indexers ruled by inclusive logic reduces the Matthew effect on journal citations since it enables them to be equally exposed. Thus, we based our arguments on the comparison of 68 Brazilian journals before and after they were indexed in the Scientific Periodicals Electronic Library (Spell), which ranks journals in the Brazilian management field based on local citations. Citation impact indicators and iGini (a new individual inequality analysis measure) were used to show that the inclusion of journals in Spell has probably increased their impact factor and decreased their citation inequality rates. Using a difference-in-differences model with continuous treatment, the results indicated that the effect between ranking and inequality declined after journals were included in Spell. Additional robustness checks through event study models and interrupted time-series analysis for panel data point to a reduction in citation inequality but follow different trajectories for the 2- and 5-year impact. The results indicate that the indexer has reduced the Matthew effect on journal citations. [ABSTRACT FROM AUTHOR]

As urbanization has accelerated, China has started to build smart cities, which have formed smart-city clusters. It is critical to coordinate development within smart-city clusters to enhance the efficiency of city-cluster construction. From the perspective of demographic economics, this study innovatively constructed an evaluation system for the coordinated development of smart-city clusters and utilized the coupled coordination degree model to conduct an in-depth study of smart-city clusters in Jiangsu Province. The results show that there are clear differences in the development between the three regions of Jiangsu Province: Southern Jiangsu, Central Jiangsu, and Northern Jiangsu. The development within Jiangsu Province is imbalanced, where the overall development trend is high in the southern region and low in the northern region. The main driving factors include geography, the Matthew effect, game thinking, and industrial structure. Accordingly, the results suggest the following recommendations for the coordinated development of smart-city clusters: strengthening cross-regional cooperation, promoting data sharing and interoperability, deepening synergistic industrial development, and expanding innovation capacity. [ABSTRACT FROM AUTHOR]

The company benefits greatly from online word-of-mouth (OWM) for its products through e-commerce platforms. However, previous research neglects the critical influence mechanism of OWM for products sold in online stores, especially the relationships between consumers' past subjective impressions and OWM. This study innovatively explores the influence mechanism of key halo effect and Matthew effect on product OWM considering the moderating role of online store PSQ namely store trust. We propose a research model and influencing factors for the halo effect and Matthew effect in the e-commerce platform scenario. Collecting about 30,000 online reviews and 160,000 historical consumer reviews from Amazon, we use a semantic similarity model to match online reviews with a standard scale for the relevant variables, combining text mining and econometric analysis. Our results show that the selected hierarchical regression model has better fit than existing common models. And the halo effect and Matthew effect are indeed beneficial to increase product OWM including the indicators of consumer satisfaction and future consumption intention. And there is a reverse effect with low perceived service quality and star rating Matthew effect on product OWM is not supported. These findings help us understand consumers' online comment behaviors, and have deep implications for e-commerce platforms and related companies. [ABSTRACT FROM AUTHOR]

The digitization of consumption, led by information and communications technology (ICT), has reshaped the urban commercial spatial structure (UCSS) of restaurants and retailers. However, the impacts of ICT on UCSS and location selection remain unclear. In this study, based on on-demand food delivery data and real-time traffic data, we used two types of machine learning algorithms, random forest regression (RFR) and the density-based spatial clustering of applications with noise (DBSCAN), to study the spatial distribution patterns, driving factors, and new geographical location phenomena of 'brick-and-click' (B&C) stores in Xinjiekou's central business district (CBD) in Nanjing, China. The results show that the UCSS in the CBD is being decentralized, but the degree of influence is related to the business type. Additionally, the scale of demand and the distance from core commercial nodes greatly affect the scales of B&C stores. Moreover, the agglomeration of high-sales B&C stores seems to indicate a micro-location advantage, characterized by the concentration of delivery riders, which is usually located in the commercial hinterland with dense traffic. This makes stores situated in traditionally advantageous locations more attractive for online sales. Thus, ICT enhances the Matthew effect in business competition. These findings deepen our understanding of urban digital planning management and business systems. [ABSTRACT FROM AUTHOR]

Crowdworkers on platforms like Amazon Mechanical Turk face growing competition as a result of the global excess supply of digital labour. As a result, many crowdworkers turn to automated scripts, which help them locate better tasks faster and to boost their earnings. However, to date, it is not clear whether and to what extent the use of such scripts influence the opportunities for those crowdworkers who do not use them. This an important aspect that warrants further exploration because it can have negative implications for the health of crowdwork platforms. In this study, we use Discrete Event Simulation to identify and quantify the unintended consequences of the excessive use of automated scripts. Our findings show that, while the use of scripts allows some crowdworkers to identify and accept far more tasks than others, in the long run, this behaviour results in their competence persistence and reputational persistence and progressively to detrimental impacts for those workers who do not use scripts, and who may ultimately be forced to exit the platform. As a result, automated scripts have negative consequences, whereby their excessive use leads to a tragedy of the commons for all platform stakeholders, including the crowdworkers, the job requesters and the platform itself. [ABSTRACT FROM AUTHOR]

With increasing ecological damage caused by regional development, many countries seek to promote sustainable development through spatial regulation. This study treated China's development of National Key Ecological Functional Zones (NKEFZ) as a quasi–natural experiment, applying a time–varying difference–in–differences model to data from 148 water quality monitoring cross–section points of major river systems in China from 2004 to 2018. The results revealed that NKEFZ improved the mean of comprehensive water quality (CWQ) and individual water quality indicators of dissolved oxygen and ammonia nitrogen content index by restricting urbanization and increasing government investment. The mean value of CWQ was improved by about 0.22 grades, and the optimization effect of spatial regulation on average water quality was more prominent in coastal cities, cities with high–pollution levels, and large–sized cities. Nevertheless, the impact of NKEFZ on water quality exhibited a "Matthew effect", in which NKEFZ were not effective in improving the bottom line standard of water quality in the pilot zones, as NKEFZ did not significantly improve the peak values of CWQ or individual pollutant indicator. In addition, an economic effect estimation indicated that NKEFZ significantly facilitated local economic growth and primary industry development and had a significantly negative impact on secondary industry growth and foreign investment. This study contributes new evidence for measuring the effect of the trans–regional spatial regulation, eliciting policy implications for improving ecological spatial regulation and incentive mechanisms, and promoting the sustainable development of the regional environment and economy. [ABSTRACT FROM AUTHOR]

Digital economy takes data as its core input element and has high green value, but does the development of digital economy necessarily promote sustainable development? We use 286 Chinese cities from 2011 to 2019 as a case study to examine the impact of digital economy on urban sustainable development, and discuss the mechanisms of digital economy on urban sustainable development, heterogeneous impacts, threshold effects of environmental regulations, and the role of National Big Data Comprehensive Pilot Zone. It was found that: (1) The digital economy has green value and can effectively contribute to urban sustainable development. (2) The digital economy can achieve urban sustainable development by enhancing green technological innovation and human capital. (3) Environmental regulation has a threshold effect in the digital economy driving urban sustainable development. (4) The establishment of National Big Data Comprehensive Pilot Zone can promote urban sustainable development. (5) The polarization effect of the level of urban sustainable development in first‐tier and second‐tier cities is still increasing under the background of digital economy, which intensifies the "Matthew effect" among different levels of cities, and the inclusiveness of digital economy has not really been reflected in China. This study explores the influence and mechanism of digital economy on urban sustainable development in the context of China, which is of great theoretical and practical significance for developing countries to solve Solow productivity paradox and realize urban sustainable development in the new development stage. [ABSTRACT FROM AUTHOR]

The Matthew Effect refers to a pattern of accumulated advantage, specifically how social status can lead to increased wealth and recognition. The Physician Payments Sunshine Act of the Affordable Care Act requires industry payments and the affiliated hospital to be publicly available through the Open Payments Database (OPD). The US News and World Report (USNWR) publishes a ranking of best medical school (research) programs yearly. The Blue Ridge Institute for Medical Research (BRIMR) ranks medical schools annually by the amount of funding from the National Institutes of Health (NIH). Whether medical school–affiliated hospitals with higher social ranking and more NIH funding receive more industrial support is unknown. This study aims to evaluate the relationship between open payment of medical school–affiliated hospitals and USNWR and BRIMR ranking. We performed a cross-sectional analysis of the OPD for the fiscal year of 2021. Hospital industry payment information was collected for affiliated hospitals in general and research categories. NIH funding data and program rankings were collected from BRIMR and USNWR, respectively. All data were collected for the fiscal year of 2021. The open payments of schools ranked in the top 50 for USNWR (n = 50) and BRIMR (n = 49) were compared to the schools not ranked in the top 50 using SPSS with chi-squared and Mann–Whitney U tests. A multivariate linear regression was performed to evaluate the association between open payments, USNWR ranking, and BRIMR ranking. A total of 91 medical schools were included in this study. The top 50 ranked medical schools by BRIMR were found to have a higher median of total open payment ($5,652,628 versus $2,558,372, P < 0.001), open payment in research ($4,707,297 versus $1,992,597, P = 0.003), and general open payment ($1,083,018 versus $392,045, P < 0.001). When ranked by USNWR, the top 50 ranked medical schools were found similarly to have a higher median of total open payment (P < 0.001), open payment in research (P < 0.001), and general open payment (P < 0.001). USNWR ranking was an independent predictor of more total open payment (Coefficient 0.016, 95% confidence interval 0.002-0.029, P = 0.026) and research open payment (coefficient 0.018, 95% confidence interval 0.002-0.034, P = 0.028). USNWR ranking was not found to predict general open payments. BRIMR ranking was not associated with open payment in total, research, or general. Hospital open payments were associated with the social reputation of their medical schools. NIH funding was not associated with open payments. A Matthew effect exists in current industry payments to medical school–affiliated hospitals. [ABSTRACT FROM AUTHOR]

This paper first proposes the talent cultivation model of industry-academia integration on the basis of multiple intelligence theory and constructs the mathematical model of knowledge base expansion based on the three dimensions of coupling compatibility, interaction intensity and interaction time. Secondly, based on the knowledge transformation theory, it constructs the information and knowledge transformation model of industry-academia organizations and conducts the existence test of the Matthew effect. Finally, the tourism management major of University J as a research object is selected to analyze the operational development trend of the industry-academia integration talent cultivation model combined with multiple intelligences by analyzing the role relationship between system variables derived from the data. The results show that in 100 simulations, the coupling compatibility of the industry-academia fusion system of tourism management majors rises by 1.286 gradients for every 1.286 gradients, and the Matthew effect of the incremental knowledge of colleges and universities rises by one grade, indicating that the model, which has a more significant effect on the success rate of innovative talent cultivation in tourism management majors, has a more significant effect on the enhancement of the success rate of innovative talent cultivation.

Purpose : This response cautions against narrowly interpreting Hallinger's bibliometric findings on the intellectual structure and impact of Educational Administration Quarterly (EAQ). It highlights two main issues when using citations to measure influence. Response Argument : First, citations reflect a variety of motivations beyond acknowledging intellectual contribution, such as persuasion, allegiance-signaling, and preferential attachment. The sleeping beauty phenomenon and citation bias can further distort the interpretation of bibliometric findings. Second, setting thresholds for co-citation networks renders the periphery invisible; however, the periphery contains anomalies that could spur future paradigm shifts. Implications : The response urges embracing diverse views and nuanced interpretations to prevent perpetuating existing inequalities. [ABSTRACT FROM AUTHOR]

With the deepening of urbanization in China, the coordinated development of cities in different regions is an important part of the sustainable development of the country, and the reasonable quantification of the unbalanced development of cities in different regions is an important issue facing the society nowadays. Previous studies usually use population data to analyze the power-law distribution law to quantify the imbalance of urban development in different regions, but China's population data span a large number of years and numerous division criteria, and the results obtained from different population data are widely disparate and have obvious limitations. The paper starts from a fractal perspective and utilizes OpenStreetMap (OSM) data to extract national road intersections from 2015 to 2022, calculates critical distance thresholds for eight years using urban expansion curves, generates urban agglomerations in China, and quantifies the imbalance of urban development in different regions by calculating the urban agglomeration power-law index. The results indicate that (1) the critical distance threshold of urban expansion curves exhibits a slight overall increase and stabilizes within the range of 120–130 m, (2) the number of urban agglomerations in China has been increasing significantly year by year, but the power-law index has been decreasing from 1.49 in 2015 to 1.36 in 2022, and (3) the number of urban agglomerations and the power–law index of the Beijing–Tianjin–Hebei, Yangtze River Delta, Pearl River Delta, and Chengdu–Chongqing regions, which is consistent with the national scale trend, indicates that the scale distribution of urban agglomerations in China at this stage does not conform to Zipf's law, and there is a certain Matthew effect among cities in different geographic areas with a large unevenness. The results of the study can provide new ideas for assessing the coordinated development of cities in different regions. It compensates for the instability of population and economic data in traditional studies. [ABSTRACT FROM AUTHOR]

The Matthew effect is widely used by researchers across disciplines. However, few studies have focused on this effect's magnitude variation on the background of the open access movement and expanded avenues to obtain information. Citation is the most widespread and basic form of scholarly recognition in the reward system of science, therefore, scientists are motivated to refer to the work of their peers where reference is due. This study assumes that the Matthew effect may not play a major role in science anymore and uses citations as a proxy to measure this effect, and calculates the citation fluctuation of Noble Laureates' key publications before and after winning the award during 1901–2016. The results show that the coefficient of variation of citations is smaller for publications published after 1980 than for those published before. The median of citations in chemistry is higher than that for in physics, physiology, or medicine. Additionally, over 90% of publications published after 1980 were recognized by their community pre-award, while the ratio consisted of 84% and 75% for 1940–1980 and 1900–1940, respectively. Furthermore, the time range between publication and year awarded plays a role in this phenomenon. The study suggests a potential magnitude decrease in the Matthew effect, which is a reminder that most researchers nowadays will recognize the importance of scientific breakthrough in its early stage. [ABSTRACT FROM AUTHOR]

Psychologists have identified heuristics and biases that can cause people to make assumptions about factors that contribute to the success of individuals and firms, whose outcomes may have actually resulted primarily from randomness. Yet the interpretation of these biases becomes ambiguous when they represent reasonable cognitive shortcuts that offer certain advantages. This paper addresses this ambiguity by presenting four versions (weak, semi-weak, semi-strong, strong) of a normative theory of luck that integrates insights from psychology with the chance model approach to predict the circumstances under which performance non-monotonicity occurs: higher performance may not only indicate greater luck, but also lower expected merit or quality. The semi-strong version is illustrated by examining the decoupling of citations of academic publications and their impact, illuminating when higher citations indicate lower quality. We conclude by discussing the broader implications of a normative theory of luck, emphasizing strategies to address situations where people mistake luck for skill. [ABSTRACT FROM AUTHOR]