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Available. Open Access. Open Access
Article
Publication date: 16 October 2024

Yang Li, Zhicheng Zheng, Yaochen Qin, Haifeng Tian, Zhixiang Xie and Peijun Rong

Drought is the primary disaster that negatively impacts agricultural and animal husbandry production. It can lead to crop reduction and even pose a threat to human survival in…

123

Abstract

Purpose

Drought is the primary disaster that negatively impacts agricultural and animal husbandry production. It can lead to crop reduction and even pose a threat to human survival in environmentally sensitive areas of China (ESAC). However, the phases and periodicity of drought changes in the ESAC remain largely unknown. Thus, this paper aims to identify the periodic characteristics of meteorological drought changes.

Design/methodology/approach

The potential evapotranspiration was calculated using the Penman–Monteith formula recommended by the Food and Agriculture Organization of the United Nations, whereas the standardized precipitation evaporation index (SPEI) of drought was simulated by coupling precipitation data. Subsequently, the Bernaola-Galvan segmentation algorithm was proposed to divide the periods of drought change and the newly developed extreme-point symmetric mode decomposition to analyze the periodic drought patterns.

Findings

The findings reveal a significant increase in SPEI in the ESAC, with the rate of decline in drought events higher in the ESAC than in China, indicating a more pronounced wetting trend in the study area. Spatially, the northeast region showed an evident drying trend, whereas the southwest region showed a wetting trend. Two abrupt changes in the drought pattern were observed during the study period, namely, in 1965 and 1983. The spatial instability of moderate or severe drought frequency and intensity on a seasonal scale was more consistent during 1966–1983 and 1984–2018, compared to 1961–1965. Drought variation was predominantly influenced by interannual oscillations, with the periods of the components of intrinsic mode functions 1 (IMF1) and 2 (IMF2) being 3.1 and 7.3 years, respectively. Their cumulative variance contribution rate reached 70.22%.

Research limitations/implications

The trend decomposition and periods of droughts in the study area were analyzed, which may provide an important scientific reference for water resource management and agricultural production activities in the ESAC. However, several problems remain unaddressed. First, the SPEI considers only precipitation and evapotranspiration, making it extremely sensitive to temperature increases. It also ignores the nonstationary nature of the hydrometeorological water process; therefore, it is prone to bias in drought detection and may overestimate the intensity and duration of droughts. Therefore, further studies on the application and comparison of various drought indices should be conducted to develop a more effective meteorological drought index. Second, the local water budget is mainly affected by surface evapotranspiration and precipitation. Evapotranspiration is calculated by various methods that provide different results. Therefore, future studies need to explore both the advantages and disadvantages of various evapotranspiration calculation methods (e.g. Hargreaves, Thornthwaite and Penman–Monteith) and their application scenarios. Third, this study focused on the temporal and spatial evolution and periodic characteristics of droughts, without considering the driving mechanisms behind them and their impact on the ecosystem. In future, it will be necessary to focus on a sensitivity analysis of drought indices with regard to climate change. Finally, although this study calculated the SPEI using meteorological data provided by China’s high-density observatory network, deviations and uncertainties were inevitable in the point-to-grid spatialization process. This shortcoming may be avoided by using satellite remote sensing data with high spatiotemporal resolution in the future, which can allow pixel-scale monitoring and simulation of meteorological drought evolution.

Practical implications

Under the background of continuous global warming, the climate in arid and semiarid areas of China has shown a trend of warming and wetting. It means that the plant environment in this region is getting better. In the future, the project of afforestation and returning farmland to forest and grassland in this region can increase the planting proportion of water-loving tree species to obtain better ecological benefits. Meanwhile, this study found that in the relatively water-scarce regions of China, drought duration was dominated by interannual oscillations (3.1a and 7.3a). This suggests that governments and nongovernmental organizations in the region should pay attention to the short drought period in the ESAC when they carry out ecological restoration and protection projects such as the construction of forest reserves and high-quality farmland.

Originality/value

The findings enhance the understanding of the phasic and periodic characteristics of drought changes in the ESAC. Future studies on the stress effects of drought on crop yield may consider these effects to better reflect the agricultural response to meteorological drought and thus effectively improve the tolerance of agricultural activities to drought events.

Details

International Journal of Climate Change Strategies and Management, vol. 17 no. 1
Type: Research Article
ISSN: 1756-8692

Keywords

Available. Open Access. Open Access
Article
Publication date: 7 November 2024

Bin Lei, Zhuoxing Hou, Yifei Suo, Wei Liu, Linlin Luo and Dongbo Lei

The volume of passenger traffic at metro transfer stations serves as a pivotal metric for the orchestration of crowd flow management. Given the intricacies of crowd dynamics…

58

Abstract

Purpose

The volume of passenger traffic at metro transfer stations serves as a pivotal metric for the orchestration of crowd flow management. Given the intricacies of crowd dynamics within these stations and the recurrent instances of substantial passenger influxes, a methodology predicated on stochastic processes and the principle of user equilibrium is introduced to facilitate real-time traffic flow estimation within transfer station streamlines.

Design/methodology/approach

The synthesis of stochastic process theory with streamline analysis engenders a probabilistic model of intra-station pedestrian traffic dynamics. Leveraging real-time passenger flow data procured from monitoring systems within the transfer station, a gradient descent optimization technique is employed to minimize the cost function, thereby deducing the dynamic distribution of categorized passenger flows. Subsequently, adhering to the tenets of user equilibrium, the Frank–Wolfe algorithm is implemented to allocate the intra-station categorized passenger flows across various streamlines, ascertaining the traffic volume for each.

Findings

Utilizing the Xiaozhai Station of the Xi’an Metro as a case study, the Anylogic simulation software is engaged to emulate the intra-station crowd dynamics, thereby substantiating the efficacy of the proposed passenger flow estimation model. The derived solutions are instrumental in formulating a crowd control strategy for Xiaozhai Station during the peak interval from 17:30 to 18:00 on a designated day, yielding crowd management interventions that offer insights for the orchestration of passenger flow and operational governance within metro stations.

Originality/value

The construction of an estimation methodology for the real-time streamline traffic flow augments the model’s dataset, supplanting estimated values derived from surveys or historical datasets with real-time computed traffic data, thereby enhancing the precision and immediacy of crowd flow management within metro stations.

Details

Railway Sciences, vol. 3 no. 6
Type: Research Article
ISSN: 2755-0907

Keywords

Available. Open Access. Open Access
Article
Publication date: 19 June 2023

Fang Wen, Yun Bai, Xin Zhang, Yao Chen and Ninghai Li

This study aims to improve the passenger accessibility of passenger demands in the end-of-operation period.

403

Abstract

Purpose

This study aims to improve the passenger accessibility of passenger demands in the end-of-operation period.

Design/methodology/approach

A mixed integer nonlinear programming model for last train timetable optimization of the metro was proposed considering the constraints such as the maximum headway, the minimum headway and the latest end-of-operation time. The objective of the model is to maximize the number of reachable passengers in the end-of-operation period. A solution method based on a preset train service is proposed, which significantly reduces the variables of deciding train services in the original model and reformulates it into a mixed integer linear programming model.

Findings

The results of the case study of Wuhan Metro show that the solution method can obtain high-quality solutions in a shorter time; and the shorter the time interval of passenger flow data, the more obvious the advantage of solution speed; after optimization, the number of passengers reaching the destination among the passengers who need to take the last train during the end-of-operation period can be increased by 10%.

Originality/value

Existing research results only consider the passengers who take the last train. Compared with previous research, considering the overall passenger demand during the end-of-operation period can make more passengers arrive at their destination. Appropriately delaying the end-of-operation time can increase the proportion of passengers who can reach the destination in the metro network, but due to the decrease in passenger demand, postponing the end-of-operation time has a bottleneck in increasing the proportion of passengers who can reach the destination.

Available. Open Access. Open Access
Article
Publication date: 2 July 2018

Xuemei Li, Ya Zhang and Kedong Yin

The traditional grey relational models directly describe the behavioural characteristics of the systems based on the sample point connections. Few grey relational models can…

1081

Abstract

Purpose

The traditional grey relational models directly describe the behavioural characteristics of the systems based on the sample point connections. Few grey relational models can measure the dynamic periodic fluctuation rules of the objects, and most of these models do not have affinities, which results in instabilities of the relational results because of sequence translation. The paper aims to discuss these issues.

Design/methodology/approach

Fourier transform functions are used to fit the system behaviour curves, redefine the area difference between the curves and construct a grey relational model based on discrete Fourier transform (DFTGRA).

Findings

To verify its validity, feasibility and superiority, DFTGRA is applied to research on the correlation between macroeconomic growth and marine economic growth in China coastal areas. It is proved that DFTGRA has the superior properties of affinity, symmetry, uniqueness, etc., and wide applicability.

Originality/value

DFTGRA can not only be applied to equidistant and equal time sequences but also be adopted for non-equidistant and unequal time sequences. DFTGRA can measure both the global relational degree and the dynamic correlation of the variable cyclical fluctuation between sequences.

Details

Marine Economics and Management, vol. 1 no. 1
Type: Research Article
ISSN: 2516-158X

Keywords

Available. Open Access. Open Access
Article
Publication date: 15 February 2022

Martin Nečaský, Petr Škoda, David Bernhauer, Jakub Klímek and Tomáš Skopal

Semantic retrieval and discovery of datasets published as open data remains a challenging task. The datasets inherently originate in the globally distributed web jungle, lacking…

1426

Abstract

Purpose

Semantic retrieval and discovery of datasets published as open data remains a challenging task. The datasets inherently originate in the globally distributed web jungle, lacking the luxury of centralized database administration, database schemes, shared attributes, vocabulary, structure and semantics. The existing dataset catalogs provide basic search functionality relying on keyword search in brief, incomplete or misleading textual metadata attached to the datasets. The search results are thus often insufficient. However, there exist many ways of improving the dataset discovery by employing content-based retrieval, machine learning tools, third-party (external) knowledge bases, countless feature extraction methods and description models and so forth.

Design/methodology/approach

In this paper, the authors propose a modular framework for rapid experimentation with methods for similarity-based dataset discovery. The framework consists of an extensible catalog of components prepared to form custom pipelines for dataset representation and discovery.

Findings

The study proposes several proof-of-concept pipelines including experimental evaluation, which showcase the usage of the framework.

Originality/value

To the best of authors’ knowledge, there is no similar formal framework for experimentation with various similarity methods in the context of dataset discovery. The framework has the ambition to establish a platform for reproducible and comparable research in the area of dataset discovery. The prototype implementation of the framework is available on GitHub.

Details

Data Technologies and Applications, vol. 56 no. 4
Type: Research Article
ISSN: 2514-9288

Keywords

Available. Open Access. Open Access
Article
Publication date: 26 January 2023

Doaa Salman and Doaa Ismael

This paper aims to assess whether digital financial inclusion (DFI) supports Egypt's CO2 reduction efforts. More specifically, this paper examines the dynamics between digital…

4726

Abstract

Purpose

This paper aims to assess whether digital financial inclusion (DFI) supports Egypt's CO2 reduction efforts. More specifically, this paper examines the dynamics between digital finance, traditional financial inclusion (TFI) and renewable energy on carbon emission in Egypt.

Design/methodology/approach

The study employed the autoregressive distributive lag (ARDL) model for Egypt over the period 1990–2020 to estimate an extended STIRPAT model for long-run linkages of DFI, traditional bank-based financial inclusion and renewable energy on carbon emissions, along with other control variables.

Findings

The results showed that using digital financial services limits carbon emissions in the long run but not in the short run, indicating that Egypt is still in its early stage of digitalization (DFI < 0.5). Moreover, renewable energy proved to have a significant negative impact on carbon emissions in the long run, implying that more investments in renewable energy projects will improve environmental quality.

Practical implications

The findings from this study help policymakers incorporate DFI policies into climate change adaptation strategies and execute better green growth policies that integrate DFI with energy-efficient technologies investments for a better environment.

Social implications

Foster economic growth and sustinabaility.

Originality/value

This study contributes to the literature by quantifying the DFI in Egypt using a two-stage principal component analysis and then examines its impact on carbon emission reduction efforts. In addition, this paper extends the research on the environment from the perspective of digital finance, making it possible to excavate more deeply into the relationship between financial inclusion and carbon emission and draw more explicit policy implications for sustainable economic growth.

Details

Journal of Economics and Development, vol. 25 no. 2
Type: Research Article
ISSN: 1859-0020

Keywords

Available. Open Access. Open Access
Article
Publication date: 13 February 2024

Ke Zhang and Ailing Huang

The purpose of this paper is to provide a guiding framework for studying the travel patterns of PT users. The combination of public transit (PT) users’ travel data and user…

422

Abstract

Purpose

The purpose of this paper is to provide a guiding framework for studying the travel patterns of PT users. The combination of public transit (PT) users’ travel data and user profiling (UP) technology to draw a portrait of PT users can effectively understand users’ travel patterns, which is important to help optimize the scheduling of PT operations and planning of the network.

Design/methodology/approach

To achieve the purpose, the paper presents a three-level classification method to construct the labeling framework. A station area attribute mining method based on the term frequency-inverse document frequency weighting algorithm is proposed to determine the point of interest attributes of user travel stations, and the spatial correlation patterns of user travel stations are calculated by Moran’s Index. User travel feature labels are extracted from travel data containing Beijing PT data for one consecutive week.

Findings

In this paper, a universal PT user labeling system is obtained and some related methods are conducted including four categories of user-preferred travel area patterns mining and a station area attribute mining method. In the application of the Beijing case, a precise exploration of the spatiotemporal characteristics of PT users is conducted, resulting in the final Beijing PTUP system.

Originality/value

This paper combines UP technology with big data analysis techniques to study the travel patterns of PT users. A user profile label framework is constructed, and data visualization, statistical analysis and K-means clustering are applied to extract specific labels instructed by this system framework. Through these analytical processes, the user labeling system is improved, and its applicability is validated through the analysis of a Beijing PT case.

Details

Smart and Resilient Transportation, vol. 6 no. 1
Type: Research Article
ISSN: 2632-0487

Keywords

Available. Open Access. Open Access
Article
Publication date: 27 August 2024

Talshyn Tokyzhanova and Susanne Durst

The purpose of this systematic literature review (SLR) is to examine the theoretical landscape of knowledge hiding (KH) research, identifies prevailing theories, the different…

793

Abstract

Purpose

The purpose of this systematic literature review (SLR) is to examine the theoretical landscape of knowledge hiding (KH) research, identifies prevailing theories, the different ways KH is understood within these theories and the underlying assumptions that shape these views. Based on this, ideas for further research are derived to advance the theoretical basis of KH studies.

Design/methodology/approach

Using a theory-based SLR, the authors analysed 170 scientific papers from Scopus and Web of Science. This involved thematic analysis to categorise theories frequently applied in KH research and a detailed examination to link core assumptions to these theoretical perspectives.

Findings

The analysis revealed a reliance on 86 distinct theories, with a notable emphasis on social exchange theory and conservation of resources theory. KH is predominantly conceptualised as a negative, objective, reactive and relational behaviour rooted in social reciprocity and resource conservation. The review uncovers the multifaceted nature of KH, challenging the field to incorporate broader theoretical views that encompass positive aspects, subjective experiences, strategic intentions and non-relational determinants of KH.

Originality/value

To the best of the authors’ knowledge, this is the first study to systematically map and analyse the theoretical underpinnings of KH research. It offers a unique contribution by categorising the diverse theories applied in KH studies and explicitly linking these theories to their inherent assumptions about KH. This approach provides a comprehensive overview that not only identifies gaps in the current research landscape but also proposes alternative theoretical perspectives for exploring KH, thereby setting a new direction for future studies in this field.

Details

VINE Journal of Information and Knowledge Management Systems, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2059-5891

Keywords

Available. Open Access. Open Access
Article
Publication date: 22 September 2021

Jin Tang, Weijiang Li, Jiayi Fang, Zhonghao Zhang, Shiqiang Du, Yanjuan Wu and Jiahong Wen

Quantitative and spatial-explicit flood risk information is of great importance for strengthening climate change adaptation and flood resilience. Shanghai is a coastal megacity at…

2104

Abstract

Purpose

Quantitative and spatial-explicit flood risk information is of great importance for strengthening climate change adaptation and flood resilience. Shanghai is a coastal megacity at large estuary delta with rising flood risks. This study aims to quantify the overall economic-societal risks of storm flooding and their spatial patterns in Shanghai.

Design/methodology/approach

Based on multiple storm flood scenarios at different return periods, as well as fine-scale data sets including gridded GDP, gridded population and vector land-use, a probabilistic risk model incorporating geographic information system is used to assess the economic-societal risks of flooding and their spatial distributions.

Findings

Our results show that, from 1/200 to 1/5,000-year floods, the exposed assets will increase from USD 85.4bn to USD 657.6bn, and the direct economic losses will increase from USD 3.06bn to USD 52bn. The expected annual damage (EAD) of assets is around USD 84.36m. Hotpots of EAD are mainly distributed in the city center, the depressions along the upper Huangpu River in the southwest, the north coast of Hangzhou Bay, and the confluence of the Huangpu River and Yangtze River in the northeast. From 1/200 to 1/5,000-year floods, the exposed population will rise from 280 thousand to 2,420 thousand, and the estimated casualties will rise from 299 to 1,045. The expected annual casualties (EAC) are around 2.28. Hotspots of casualties are generally consistent with those of EAD.

Originality/value

In contrast to previous studies that focus on a single flood scenario or a particular type of flood exposure/risk in Shanghai, the findings contribute to an understanding of overall flood risks and their spatial patterns, which have significant implications for cost-benefit analysis of flood resilience strategies.

Details

International Journal of Climate Change Strategies and Management, vol. 13 no. 4/5
Type: Research Article
ISSN: 1756-8692

Keywords

Available. Open Access. Open Access
Article
Publication date: 16 July 2019

Tuotuo Qi, Tianmei Wang, Yanlin Ma and Xinxue Zhou

Knowledge sharing has entered the stage of knowledge payment with the typical models of paid Q&A, live session, paid subscription, course column and community service. Numerous…

7281

Abstract

Purpose

Knowledge sharing has entered the stage of knowledge payment with the typical models of paid Q&A, live session, paid subscription, course column and community service. Numerous knowledge suppliers have begun to pour into the knowledge payment market, and users' willingness to pay for premium content has increased. However, the academic research on knowledge payment has just begun.

Design/methodology/approach

In this paper, the authors searched several bibliographic databases using keywords such as “knowledge payment”, “paid Q&A”, “pay for answer”, “social Q&A”, “paywall” and “online health consultation” and selected papers from aspects of research scenes, research topics, etc. Finally, a total of 116 articles were identified for combing studies.

Findings

This study found that in the early research, scholars paid attention to the definition of knowledge payment concept and the discrimination of typical models. With the continuous enrichment of research literature, the research direction has gradually been refined into three main branches from the perspective of research objects, i.e. knowledge provider, knowledge demander and knowledge payment platform.

Originality/value

This paper focuses on discussing and sorting out the key research issues from these three research genres. Finally, the authors found out conflicting and contradictory research results and research gaps in the existing research and then put forward the urgent research topics.

Details

International Journal of Crowd Science, vol. 3 no. 2
Type: Research Article
ISSN: 2398-7294

Keywords

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