Area Of Management Research Articles

A Follow-Up Study on the Clinical Impact of Pre-Registration Extended Immersive Ward-Based Simulation

AimTo explore how extended immersive ward-based simulation influenced graduate nurses’ experiences six-months post-registration. BackgroundGraduates of nursing training programs are expected to enter the workforce meeting the role of a registered nurse. Extended immersive ward-based simulation has been adopted by nurse educators as a means of easing the transition to professional practice. To what degree transfer of learning occurs from these experiences is yet to be determined. DesignA qualitative descriptive design was used to conduct a series of face-to-face focus groups. MethodsParticipants were nine former students who had participated in a series of ward-based simulation workshops before graduating. A semi-structured interview process explored participants’ transition experiences. ResultsPast simulation experiences were used as a base for practice in areas of teamwork, communication, conflict, and time management. Simulations were used as a point of reference and built confidence for transition to practice. ConclusionsTransition to professional practice was supported by simulated experiences. Transfer of learning was demonstrated among participants.

Rock moisture reinforces belowground water storage under different precipitation scenarios and vegetation coverage

Rock moisture is rarely deliberated but crucial for hydrologic regulation in semiarid loess hilly regions. In this study, using in-situ monitoring observation and simulation, soil and rock moisture spatiotemporal variations under planting alfalfa and caragana were analyzed and sketched, and the water storage contributions by weathered bedrock layers (WBLs) under different rainwater scenarios were then simulated and estimated. The results showed that WBLs had apparent spatiotemporal changes in water distribution and storage with rainfall events. Under water scarcity scenarios, WBLs increased the variabilities of water storage, with an average increase of 89.9 % in alfalfa and 14.2 % in caragana, providing wider water supply boundaries for vegetation. However, higher volumetric water content was presented under relatively abundant water scenarios. The average soil water content was 0.08 cm3 cm−3 in alfalfa and 0.09 cm3 cm−3 in caragana, while the average rock water content was 0.12 cm3 cm−3 in alfalfa and 0.13 cm3 cm−3 in caragana. Profile water consumption goes to surface soil evaporation and plant transpiration over an entire growing season, while extrawater would be stored in WBLs to maintain vegetation growth during the water-scarce seasons. Moreover, water storage had a positive linear relationship with the thickness of WBLs. Rock water storage increased by 6.9 % in alfalfa and 3.7 % in caragana after adding 20 cm WBLs, while it increased by 23.6 % in alfalfa and 9.9 % in caragana after adding 50 cm WBLs. Furthermore, various exogenous rainwater simulations showed that differences in water storage were significantly increased with WBLs thickness. This study would provide new insights into the deep-rooted plant distribution planning in semiarid loess hilly regions, and could also be helpful for the rational water resources utilization and management in shallow soil areas.

Patient-oriented optimization of the quality of care in aspecialized outpatient clinic in atertiary rheumatology center : Aqualitative study

The adaptation of structures and processes in treatment procedures can contribute to increasing patient satisfaction and is the focus of patient-oriented quality assurance. To identify patient satisfaction as well as needs, expectations and preferences with respect to care and, based on this, to formulate recommendations for action to optimize the quality of care at alarge tertiary rheumatology center. As part of aqualitative research approach, semi-structured patient interviews and afocus group interview consisting of physicians in rheumatology training in outpatient specialist care were conducted. The quality dimensions of Donabedian were recorded. The data material was evaluated and analyzed using the content-structuring qualitative content analysis according to Kuckartz with the MAXQDA evaluation software. Using 12patient interviews and afocus group of 3future rheumatologists, recommendations for action to optimize the quality of care were derived on the basis of the structural, process and outcome quality. There was aneed for optimization in the areas of personnel management, internal practice processes, practice equipment and treatment processes in the outpatient clinic. The results from the patient interviews and the focus group revealed the aspects in need of optimization. The methodology and results of this study can serve as areference point for analyses of other rheumatology clinics in order to improve the quality of care within the framework of patient-oriented quality management and continuous further development.

Digitális kihívások a felsőoktatásban: Az NKE oktatóinak digitális készségeinek kvantitatív vizsgálata

The information society is not only transforming the process of education but also creating new positions and challenges in the labour market, and education must prepare for this. Research shows that the success of education depends mostly on teachers (Mourshed, Chijoka and Barber 2010). In this study, we investigate the digital competence of teachers at Ludovika University of Public Service (hereinafter: LUPC) (N=824). For the quantitative research, we used the DigCompEdu questionnaire. The level of digital competence of the teachers is assessed based on their own self-assessment. We assume that although their digital competences need improvement, but their motivation to use digital technologies in the classroom is positive. The instructors scored higher points in the areas of digital resource management, professional engagement and teaching & learning but they scored the lowest in the area of assessment.

Exposition of techno-functional components of intelligent food supply chain: a review and future research agenda

Purpose The new technology aspects of Industry 4.0 (I4.0), such as digital technologies including artificial intelligence (AI), block chain, big data analysis and the internet of things (IoT) as a digital cosmos, have the potential to fundamentally transform the future of business and supply chain management. By augmenting the functional components of the food supply chain (FSC), these technologies can transform it into an intelligent food supply chain (iFSC). The purpose of this study is to identify the I4.0 utilization for FSC to become an iFSC. Additionally, it suggests future research agendas to bridge the academic knowledge gaps. Design/methodology/approach This study utilizes the bibliometric analysis methodology to investigate the techno-functional components of iFSC in the context of I4.0. The study followed steps of bibliometric analysis to assess existing components’ knowledge in the area of intelligent food supply chain management. It further reviews the selected articles to explore the need for I4.0 technologies’ adoption as well as its barriers and challenges for iFSC. Findings This study examines the integration of emerging technologies in FSC and concludes that the main emphasis is on the adoption of blockchain and internet of things technology. To convert it into iFSC, it should be integrated with I4.0 and AI-driven FSC systems. In addition to traditional responsibilities, emerging technologies are acknowledged that are relatively uncommon but possess significant potential for implementation in FSC. This study further outlines the challenges and barriers to the adoption of new technologies and presents a comprehensive research plan or collection of topics for future investigations on the transition from FSC to iFSC. Utilizing artificial intelligence techniques to enhance performance, decision-making, risk evaluation, real-time safety, and quality analysis, and prioritizing the elimination of barriers for new technologies. Originality/value The uniqueness of this study lies in the provision of an up-to-date review of the food supply chain. In doing so, the authors have expanded the current knowledge base on the utilization of all I4.0 technologies in FSC. The review of designated publications yield a distinctive contribution by highlighting hurdles and challenges for iFSC. This information is valuable for operations managers and policymakers to consider.

Bi-objective optimization for last-mile routing of garbage trucks: Aesthetics and Public exposure.

In the area of Solid Waste Management, transportation of the collected waste is a critical aspect considering the substantial time spent by garbage trucks on public roads. Studies have reported that transporting garbage has challenges related to public exposure and aesthetics. This study presents a generalised bi-objective formulation for the optimal routing of garbage trucks from transfer stations to recycling sites/landfills considering the trade-off between public exposure and aesthetic loss and constraining the operating cost. The formulation uses the novel link capacity function to account for the delay at traffic signals and the mix of trucks and cars on link performance. The proposed formulation is solved using the weighted sum and ε-constraint methods and applied to a realistic case study of the City of Chicago, USA. The Pareto Front obtained for the bi-objective formulation offers diverse trade-off solutions catering to distinct performance metrics. The results highlight the disparity across the solutions; the solution (P0.95 on Pareto Front) for minimum operating cost (or travel time or distance travelled) is very different from the solution (P0.4 on Pareto Front) for aesthetic cost and public exposure. The parametric study indicated that a modest operating budget may suffice for achieving aesthetic benefits, but minimising public exposure requires a higher operating budget. Finally, the proposed framework is adaptable to address various challenges pertaining to waste transportation, thereby serving as a valuable tool for evaluating policies and practices geared towards sustainability objectives.

Combining prior and post‐release data while accounting for dispersal to improve predictions for reintroduction populations

AbstractAttempts to reintroduce species to managed areas may be compromised by dispersal into the surrounding landscape. Therefore, decisions regarding the selection and ongoing management of reintroduction areas require predicting dispersal as well as the survival and reproduction rates of the species to be reintroduced. Dispersal can potentially be measured directly by tracking animals, but this is often impractical. However, dispersal can also be inferred from re‐sighting surveys done within reintroduction areas if such data are available from multiple areas with varying connectivity to the surrounding landscape, allowing apparent survival and recruitment to be modelled as a function of connectivity metrics. Here, we show how data from 10 previous reintroductions of a New Zealand passerine, the toutouwai (Petroica longipes), were used to predict population dynamics at a predator‐controlled reintroduction area with high connectivity, and predictions then updated using post‐release data. Bayesian hierarchical modelling of the previous data produced prior distributions for productivity, adult survival and apparent juvenile survival rates that accounted for random variation among areas as well as rat density and connectivity. The modelling of apparent juvenile survival as a function of connectivity allowed it to be partitioned into estimates of survival and fidelity. Bayesian updating based on post‐release data produced posterior distributions for parameters that were consistent with the priors but much more precise. The prior data also allowed the recruitment rate estimated in the new area to be partitioned into separate estimates for productivity, juvenile survival and juvenile fidelity. Consequently, it was possible to not only estimate population growth under current management, but also predict the consequences of reducing the scale or intensity of predator control, facilitating adaptive management. The updated model could then be used to predict population growth as a function of the connectivity and predator control regime at proposed reintroduction areas while accounting for random variation among areas.

Conflict of interest: The authors declare that there is not conflict of interest regarding the publication

Relevance. Forests play a vital role in maintaining ecological balance and providing habitats, oxygen, and carbon sinks. However, deforestation resulting from mining, logging, infrastructure development, climate change, and agriculture is leading to their depletion.This paper aims to investigate the underlying factors driving deforestation and their socioeconomic and ecological consequences.Results and Discussion. Deforestation has resulted in the loss of 10 million hectares of global forest cover annually, with direct drivers including fires, logging, and converting forests to agricultural land. Indirect drivers encompass political elections, military conflicts, population density, and corruption. Economic growth, road expansion, and politics have exacerbated the pressure on forests, resulting in biodiversity loss. Deforestation is predicted to continue at a rate of 10 million hectares annually until 2025. To mitigate this issue, measures such as reducing emissions from deforestation, promoting sustainable forest management, and enhancing protected area management can be implemented. Furthermore, legal action should be pursued to address the issue of deforestation.

The Temporal and Spatial Evolution Characteristics and Driving Factors of Ecosystem Service Bundles in Anhui Province, China

Identifying ecosystem service bundles and their long-term evolutionary characteristics is essential for the overall enhancement of regional ecosystem services, as well as the division and management of functional areas, providing a basis for decision-making in formulating ecological and environmental protection policies, as well as regional development planning. Based on land use, remote sensing, and meteorological data obtained from Anhui Province, this study assessed six important ecosystem service functions, including food production (FP), water yield (WY), carbon sequestration (CS), soil conservation (SC), habitat quality (HQ), and landscape aesthetics (LA), at the township scale in 2000, 2010, and 2020. On this basis, the k-means clustering method was used to identify ecosystem service bundles, analyze the spatio-temporal evolution trajectory of service bundles, and explore the driving factors of the spatio-temporal evolution of ecosystem service bundles using GeoDetector 2015 The results indicate the following: (1) At the spatial level, diverse ecosystem services demonstrate pronounced spatial differentiation. The distribution pattern of HQ, carbon fixation, and SC services is generally lower in the north and higher in the south, with areas of high value predominantly located in the western Dabie Mountains and the mountains of Southern Anhui. Conversely, FP services exhibit the reverse pattern, and WY services display a gradual increase from north to south, while cultural services are more dispersed, with areas of high value primarily located in the western Dabie Mountains, the Yangtze River Basin, and other locations. On the temporal scale, WY, SC, and FP services mainly exhibit an increasing trend, marked by a significant increase, whereas other services tend to present a decreasing trend. (2) Anhui Province can be categorized into four distinct types of service bundles: the grain production bundle (GPB), mountain ecological conservation bundle (MECB), urban living bundle (ULB), and core protection bundle (CPB). Ecosystem service bundles exhibit clear spatial differentiation, and identical service bundles demonstrate substantial clustering in space. Between 2000 and 2020, ecosystem service bundles displayed a marked spatio-temporal evolution, with the prevalence of GPBs diminishing, whereas the share of ULBs progressively increased, and the number of MECBs and CPBs remained largely stable. (3) In the spatio-temporal evolution process, the average annual precipitation, the proportion of forest land, and slope constitute the principal natural factors influencing the spatio-temporal evolution of ecosystem service bundles, while the proportion of construction land represents the primary socio-economic factor, with natural factors exerting a more significant influence than socio-economic factors.

Evaluation of Heavy Metal Contamination and Associated Human Health Risk in Soils around a Battery Industrial Zone in Henan Province, Central China

This research investigated the contamination characteristics, sources, and health risks of five metals in soils from two villages named DK and SXC, downstream from a battery industry hub in Xinxiang city, Henan Province, China. The average concentrations of Cd, Pb, Ni, Cu, and Zn in DK were 5.93, 41.31, 71.40, 62.20, and 115.83 mg/kg, respectively, and in SXC were 2.04, 30.41, 41.22, 36.18, and 96.04 mg/kg, respectively. The single factor pollution index (Pi) revealed a consistent descending order of Cd > Cu > Zn > Ni > Pb in DK and SXC. The geo-accumulation index (Igeo) indicated that the Cd pollution in DK was extreme, and in SXC was at a heavy to extreme level. The potential ecological risk index (PERI) indicated that Cd presented a significantly high ecological risk while it was low for other metals. Principal component analysis classified them into the anthropogenic origin of Cd and common mixed origin of others. The elevated levels and pollution load of heavy metals with closer proximity to the battery factory imply that the factory is a probable source of contamination. Overall, the health risks posed by heavy metals were more pronounced for local children compared to adults, with Cd being the primary contributor to both pollution and health risks. This investigation provides a crucial basis for the heavy metal pollution management and related risk prevention in areas affected by electronic waste irrigation.

Top IT Challenges in ARL Libraries

The practice of information technology (IT) in academic libraries is changing rapidly, not only with new and evolving developments in the technologies themselves but also with the organization and management of IT at both the library and institution levels. This study presents the results of an online survey of Association of Research Libraries (ARL) academic library members to identify the biggest challenges they perceive in the area of information technology organization and management. This article compares their responses with challenges reported in earlier studies to identify new and changing trends as well as ongoing challenges that remain.

The Linkage Between Digital Transformation and Organizational Culture: Novel Machine Learning Literature Review Based on Latent Dirichlet Allocation

AbstractOrganizational culture is a crucial component of innovation in company success, particularly in the setting of the information economy. The purpose of this research is to conduct a bibliometric analysis in order to identify dominant research topics, their potential shifts, and recent developments in the fields of organizational culture and digital transformation. It demonstrates a machine learning–supported method for identifying and segmenting the current state of this research field. The literature was identified from the Scopus database through a search query. The analyzed amount of papers (3065) was published in 1619 sources (journals, proceedings, books, etc.) with various research impacts. Identifying the dominant research topics resulted in eight topics: Social Media Connectivity; Digital Innovation Ecosystems; Socio-economic Sustainability; Digital Workforce Transformation; Digital Competence and Cultural Transformation; Knowledge, Culture, and Innovation; Data and Resource Management; and Digital Transformation Maturity. The results showed a shift in the research field on organizational culture related to digital transformation towards the subject area of business, management, and accounting, with increasing research interest and impact for the Digital Workforce Transformation as well as for the Knowledge, Culture, and Innovation topics.

Directed conservation of the world's reef sharks and rays.

Many shark populations are in decline around the world, with severe ecological and economic consequences. Fisheries management and marine protected areas (MPAs) have both been heralded as solutions. However, the effectiveness of MPAs alone is questionable, particularly for globally threatened sharks and rays ('elasmobranchs'), with little known about how fisheries management and MPAs interact to conserve these species. Here we use a dedicated global survey of coral reef elasmobranchs to assess 66 fully protected areas embedded within a range of fisheries management regimes across 36 countries. We show that conservation benefits were primarily for reef-associated sharks, which were twice as abundant in fully protected areas compared with areas open to fishing. Conservation benefits were greatest in large protected areas that incorporate distinct reefs. However, the same benefits were not evident for rays or wide-ranging sharks that are both economically and ecologically important while also threatened with extinction. We show that conservation benefits from fully protected areas are close to doubled when embedded within areas of effective fisheries management, highlighting the importance of a mixed management approach of both effective fisheries management and well-designed fully protected areas to conserve tropical elasmobranch assemblages globally.

Status Quo of Artificial Intelligence’s Role in the HRM Operations

Coexistence of technology and business dates back to the late 18th century when the first ever use of a computer was for recording the census by the US government in 1890. The use of technology in business can be ascribed to different organisations in the different nations on the parallel lines of time. It includes invention of cash machines and their use by Barclays in England in the early 1960s, the induction of telephone-based modems for order management by Baxter Pharmaceuticals and use of small desktop computing device called Minitel for processing customer orders in France were the other notable developments in the history of coexistence of technology and business. Increasing operations in the business functions have created an urge for the technological innovation in the industry to handle the operations electronically. Figueiredo and Cohen (2019) say that technology has become an indispensable component of every business function by delivering ease in operations and productivity. The end of the 20th century had witnessed the leaping progress in computing in the form of artificial intelligence (AI) performing the tasks that were unimaginable to comprehend a decade back in time. Developments in the technological research and development prove that organisations have started inducting AI into as many fields as possible at a considerable pace. As a part of the shifting technological dynamics in the industry HR function has also transformed digitally. Tools like enterprise applications have forayed intensely into the operations of human resources management (HRM). These enterprise resource planning (ERP) tools remain to primarily serve the integration of HRM to the other functions. However, enterprise tools could not serve the purpose of supporting decisiveness in the areas of HR planning, workforce design and performance management at large. However, Tuck (2019) argues that AI is assuming increased responsibilities in the different sections of the society and business including the HRM function. At present, the amount of knowledge on the status quo of the role of AI in the HRM functions is scarcely available. Literature related to this disruptive technology in the HR function is still at the nascent stage. This study will examine the role of AI as a key component in the HRM function, which is regarded to be highly human-driven.

Alternate use of fresh and saline waters to improve water productivity and soil sustainability of drip irrigated wheat in a semi-arid region

Severe problems of rising groundwater and secondary soil salinization demand holistic agricultural water management in canal command areas. Drip irrigation with alternate use of fresh and saline waters is an excellent irrigation approach to mitigate salinity stress caused by highly saline ground water and also to avoid soil sodicity hazards from canal water. Therefore, a study on cyclic mode conjunctive use of good quality surface water (SW) and highly saline ground water (GW) having average electric conductivity 0.3 and 7.6 dS m−1, respectively was carried out in wheat with five treatments of drip viz. 1SW1GW (1:1 :: SW:GW), 1SW2GW (1:2 :: SW:GW), 2SW1GW (2:1 :: SW:GW), SW (all SW), GW (all GW), and one treatment of conventional border ­irrigation method (BI). Highest grain yield was observed in SW (2.99 t ha−1) in 2017–2018 and BI (3.83 t ha−1) in 2018–2019 season. However, yield of SW and BI were statistically at par in both seasons. Grain yield of 1SW1GW, in which only 50% freshwater was used was found statistically at par with SW and BI. Physical Water Productivity was highest for SW, amounting 9.34 and 14.13 kg ha−1.mm−1 during 2017–2018 and 2018–2019, respectively. Soil salinity build up was highest for GW and lowest for SW, whereas it was almost similar for BI and 1SW1GW. Thus, 1SW1GW showed added benefits as its grain yield was statistically at par with SW and BI along with 50% fresh water saving over SW and higher water productivity than BI for similar salinity levels.

Global drivers of mangrove loss in protected areas.

Despite increasing efforts and investment in mangrove conservation, mangrove cover continues to decline globally. The extent to which protected area (PA) management effectively prevents mangrove loss globally across differing management objectives and governance types is not well understood. We combined remote sensing data with PA information to identify the extent and the drivers of mangrove loss across PAs with distinct governance types and protection levels based on categories developed by the International Union for Conservation of Nature (IUCN). Mangrove loss due to storms and erosion was prevalent across all governance types and most IUCN categories. However, the extent of human-driven loss differed across governance types and IUCN categories. Loss was highest in national government PAs. Private, local, shared arrangement, and subnational government agencies had low human-driven mangrove loss. Human-driven loss was highest in PAs with the highest level of restrictions on human activities (IUCN category I) due to mangrove conversion to areas for commodity production (e.g., aquaculture), whereas PAs that allowed sustainable resource use (e.g., category VI) experienced low levels of human-driven mangrove loss. Because category I PAs with high human-driven loss were primarily governed by national government agencies, conservation outcomes in highly PAs might depend not only on the level of restrictions, but also on the governance type. Mangrove loss across different governance types and IUCN categories varied regionally. Specific governance types and IUCN categories thus seemed more effective in preventing mangrove loss in certain regions. Overall, we found that natural drivers contributed to global mangrove loss across all PAs, whereas human-driven mangrove loss was lowest in PAs with subnational- to local-level governance and PAs with few restrictions on human activities.

Discovery of an endemism hotspot of freshwater mussels (Bivalvia: Unionidae) in Assam, with a description of two new genera

Abstract The Indian subcontinent houses a unique fauna of freshwater mussels. Tectonic and biogeographic reconstructions indicate that this fauna represents a derivative of Mesozoic Gondwanan biota and that it arrived in Asia on the Indian Plate, using this tectonic block as a ‘biotic ferry’. Though a preliminary integrative revision of the Indian Unionidae was published recently, the level of endemism and taxonomic richness of regional assemblages are unsatisfactorily known. Here, we revise the taxonomy of freshwater mussels from the Brahmaputra River basin based on a large DNA-sequence and morphological dataset that was sampled in Assam, north-eastern India. We managed to collect and sequence topotypes for nearly all nominal species described from the region, except for Lamellidens friersoni and Parreysia smaragdites. Our phylogenetic and morphology-based research reveals that the regional Unionidae assemblage contains nine species, belonging to a single subfamily, the Parreysiinae. Seven species and three genera (Balwantia, Pseudoscabies Bolotov, Sonowal, Kardong, Pasupuleti and Subba Rao gen. nov., and Assamnaia Bolotov, Sonowal, Kardong, Pasupuleti and Subba Rao gen. nov.) appear to be endemic to the region, indicating that the Brahmaputra River may represent an endemism hotspot of global significance. Our findings highlight that this region should be considered a high-priority area for freshwater conservation management.

Deliberative Governance Principles in Forest Areas Management with Special Purposes

Apart from having educational and development goals, the management of Diponegoro University's Wanadipa Special Purpose Forest Area (KHDTK) also aims to carry out sustainable forest use activities. The management carries out efforts to achieve these goals through a deliberative governance approach, including public consultation. However, the management is not yet satisfied with the results, considering that the community around the forest has not participated well in managing the KHDTK. Therefore, this research aims to analyze deliberative governance in KHDTK forest management by testing three deliberative governance criteria: representation, participation, and deliberation process. This approach is a collaborative effort between managers of Special Purpose Forest Areas (KHDTK) and farming communities around the forest. Mixed research methods were used in this research, with a concurrent embedded model. The qualitative research approach uses key informants as data sources, while quantitative research uses respondents consisting of forest farmers. The results of the research show that KHDTK forest management based on aspects of representation, participation, and deliberation has not run optimally. Therefore, it is recommended that intensive and open communication between KHDTK managers and forest farming communities be improved in KHDT forest management, which will provide benefits to both parties.

Earthquake, flood and resilience management through spatial planning, decision and information system

Assessment and planning of crisis management with the natural disasters approach include many components. In this regard, floods and earthquakes are some of the fundamental pillars in this field. With this view, paying attention to the current and future planning and research priorities of the world shows that crisis management in flood-prone and earthquake-prone areas and increasing resilience are the most important priorities for sustainable development studies and planning in the world. The western region of Iran (Lorestan province) has a special place due to the prominent features of flood and seismicity. This study aims to investigate the current situation regarding floods and earthquakes and increase the resilience of settlements with emphasis on the study area. After studying the current structure of flood and earthquake zoning according to multi-factor criteria, zoning was performed based on the integration of GIS and AHP information systems, and at the output of the work, high-risk settlements were determined separately for rural and urban areas with geographical coordinates, and then areas with low, very low, medium, high, and very high resilience were presented separately for rural and urban settlements. Also, after analyzing the SWOT model, strategies to increase the resilience of settlements to floods and earthquakes were presented. The study method of this research and the results, strategies, and operational options presented while being used in the study area are also applicable in other areas.

Moving Trend Analysis Methodology for Hydro-meteorology Time Series Dynamic Assessment

AbstractIn the last 30 years, there are many publications in the literature due to global warming and climate change impacts exhibiting non-stationary behaviors in hydro-meteorology time series records especially in the forms of increasing or decreasing trends. The conventional trend analyzes cover the entire recording time with a single straight-line trend and slope. These methods do not provide information about up and down partial moving trends evolution at shorter durations along the entire record length. This paper proposes a dynamic methodology for identifying such evolutionary finite duration moving trend method (MTM) identifications and interpretations. The purpose of choosing MTM was to investigate the dynamic partial trend evolution over the recording period so that dry (decreasing trend) and wet (increasing trend) segments could be objectively identified and these trends could assist in water resources management in the study area. The moving trend analysis is like the classical moving average methodology with one important digression that instead of arithmetic averages and their horizontal line representations, a series of finite duration successive increasing and decreasing trends are identified over a given hydro-meteorology time series record. In general, partial moving trends of 10-year, 20-year, 30-year and 40-year occur above or below the overall trend and thus provide practical insight into the dynamic trend pattern with important implications. The moving trend methodology is applied to annual records of Danube River discharges, New Jersey state wise temperatures and precipitation time series from the City of Istanbul.