Implementation Of Effective Management Research Articles

The Role of Information Processing and Digital Supply Chain Technology in Supply Chain Resilience through Supply Chain Risk (Management in Manufacturing Companies in DKI Jakarta)

The 2019 COVID-19 pandemic highlighted the importance of supply chain resilience in the face of global disruptions. Supply chain disruptions caused by isolation measures during the pandemic triggered market turmoil, logistical uncertainty, and reduced production capacity, which sometimes led to shutdowns. In this context, research on supply chain resilience is crucial to prepare companies for future disruptions. This research aims to examine the impact of supply chain resilience on supply chain continuity in manufacturing companies in DKI Jakarta, focusing on the role of digital supply chains, information processing capabilities, and supply chain risk management. This research method uses a quantitative approach. Data were collected from 300 respondents in the basic and chemical industry, miscellaneous industries, and consumer goods sectors through purposive sampling techniques. The analysis was conducted using Structural Equation Modeling (SEM) to identify the relationship between variables. The results showed that supply chain resilience has a significant positive influence on supply chain continuity. In addition, digital supply chains, information processing capabilities, and effective supply chain risk management were shown to support supply chain resilience in the studied sectors. The implication of this research is that it is important for companies to invest in digital technology, develop better information processing capabilities, and implement effective risk management to strengthen their supply chain resilience and continuity in the face of future global uncertainty.

Exploring the trend of age-standardized mortality rates from cardiovascular disease in Malaysia: a joinpoint analysis (2010–2021)

IntroductionCardiovascular disease (CVD) is a major health concern worldwide, particularly in low- and middle-income countries. The COVID-19 pandemic that emerged in late 2019 may have had an impact on the trend of CVD mortality. This study aimed to investigate the trend and changes in CVD mortality rates in Malaysia, using age-standardized mortality rates (ASMR) from 2010 to 2021.MethodsThe Malaysian population and mortality data from 2010 to 2021 were obtained from the Department of Statistics Malaysia (DOSM). ASMRs from CVD per 100,000 population were calculated based on the World Health Organization (2000–2025) standard population using the direct method. The ASMRs were computed based on sex, age groups (including premature mortality age, 30–69 years), and CVD types. The annual percent change (APC) and average annual percent change (AAPC) of the ASMR with corresponding 95% confidence intervals (95% CI) were estimated from joinpoint regression model using the Joinpoint Regression Program, Version 4.9.1.0.ResultsThroughout the study period (2010–2021), ASMRs for CVD exhibited an increase from 93.1 to 147.0 per 100,000, with an AAPC of 3.6% (95% CI: 2.1 to 5.2). The substantial increase was observed between 2015 and 2018 (APC 12.6%, 95% CI: 5.4%, 20.3%), with significant changes in both sexes, and age groups 50–69, 70 years and over, and 30–69 (premature mortality age). Notably, the ASMR trend remained consistently high in the premature mortality age group across other age groups, with males experiencing higher rates than females. No significant changes were detected before or after the COVID-19 pandemic (between 2019 and 2021), except for females who died from IHD (10.3% increase) and those aged 0–4 (25.2% decrease).ConclusionOverall, our analysis highlights the persistently high burden of CVD mortality in Malaysia, particularly among the premature mortality age group. These findings underscore the importance of continued efforts to address CVD risk factors and implement effective prevention and management strategies. Further research is needed to fully understand the impact of the COVID-19 pandemic on CVD mortality rates and to inform targeted interventions to reduce the burden of CVD in Malaysia.

Understanding the influence of religion on pro-environmental behaviors: an investigation in Muslim families using the theory of planned behavior customized with a religiosity-based subjective norm

This study is to examine the effect of religion on pro-environmental behaviors in a Muslim developing country, using a religiosity-based subjective norm structure rather than important others in the theory of planned behavior. Data collected from 460 families revealed important insights into the religiosity-based subjective norm, planned behavior theory, and three pro-environmental behaviors. The findings implied that an important minority with a strong foundation or belief may have been more influential than many important others in the formation of a subjective norm. The research model worked seamlessly for pro-environmental behaviors at home and in purchasing. However, for pro-environmental transportation behavior, all predictors failed, including intention. Religiosity-based subjective norm had significant power in both influencing other planned-behavior structures and indirectly influencing pro-environmental behavior at home and in purchasing. These results could be used by governments, policymakers, and researchers to design and implement effective environmental management systems.

Psychosocial alterations during the COVID-19 pandemic and the global burden of anxiety and major depressive disorders in adolescents, 1990-2021: challenges in mental health amid socioeconomic disparities.

The coronavirus disease 2019 (COVID-19) pandemic, a global health crisis, profoundly impacted all aspects of daily life. Adolescence, a pivotal stage of psychological and social development, is heavily influenced by the psychosocial and socio-cultural context. Hence, it is imperative to thoroughly understand the psychosocial changes adolescents experienced during the pandemic and implement effective management initiatives. We examined the incidence rates of depressive and anxiety disorders among adolescents aged 10-19years globally and regionally. We utilized data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 to compare pre-pandemic (2018-2019) and pandemic (2020-2021) periods. Our investigation covered 204 countries and territories across the six World Health Organization regions. We conducted a comprehensive literature search using databases including PubMed/MEDLINE, Scopus, and Google Scholar, employing search terms such as "psychosocial", "adolescent", "youth", "risk factors", "COVID-19 pandemic", "prevention", and "intervention". During the pandemic, the mental health outcomes of adolescents deteriorated, particularly in terms of depressive and anxiety disorders. According to GBD 2021, the incidence rate of anxiety disorders increased from 720.26 [95% uncertainty intervals (UI) = 548.90-929.19] before the COVID-19 pandemic (2018-2019) to 880.87 per 100,000 people (95% UI = 670.43-1132.58) during the COVID-19 pandemic (2020-2021). Similarly, the incidence rate of major depressive disorder increased from 2333.91 (95% UI = 1626.92-3138.55) before the COVID-19 pandemic to 3030.49 per 100,000 people (95% UI = 2096.73-4077.73) during the COVID-19 pandemic. This worsening was notably pronounced in high-income countries (HICs). Rapid environmental changes, including heightened social anxiety, school closures, economic crises, and exacerbated racism, have been shown to adversely affect the mental well-being of adolescents. The abrupt shift to remote learning and the absence of in-person social interactions heightened feelings of loneliness, anxiety, sadness, and stress among adolescents. This change magnified existing socioeconomic disparities, posing additional challenges. These complexities profoundly impact adolescents' well-being, especially vulnerable groups like those from HICs, females, and minorities. Acknowledging the underreporting bias in low- to middle-income countries highlights the importance of addressing these mental health alterations in assessments and interventions within these regions as well. Urgent interventions are crucial as the pandemic-induced mental stress may have lasting effects on adolescents' mental health.

The Impact of Strategic Management on Organizational Performance: An Empirical Study

In today's era of globalization and intensifying market competition, business leaders, particularly in the food and beverage (F&B) industry, are compelled to pursue continuous innovation and implement effective strategic management practices to remain competitive and succeed in an increasingly complex market. In this study, we will delve deeply into the implementation of strategic management in an F&B enterprise, namely Ayam Guling Mister (AGM). It is the aim of this research to provide readers with an understanding of the concepts and basic principles of strategic management and their applicability to the F&B industry. Furthermore, the factors influencing the successful implementation of strategic management will be discussed. This research employs a qualitative approach, which is particularly suited to the investigation of the application of strategic management in the context of food and beverages production. This enables the perspectives of organisational leaders on the management of strategic initiatives to be elucidated, thereby facilitating an understanding of the processes involved in maintaining the viability of a product. The findings from this research indicate that the implementation of strategic management at AGM is crucial to ensure business success and sustainable growth.

Soil Quality Assessment and Its Spatial Variability in an Intensively Cultivated Area in India

Intensive agricultural practices lead to a deterioration in soil quality, causing a decline in farm productivity and quality, and disturbing the ecosystem balance in command areas. To achieve sustainable production and implement effective soil management strategies, understanding the state and spatial variability of soil quality is essential. The study aims to enhance the understanding of soil quality variability and provide actionable insights for sustainable soil management. In this regard, principal component analysis (PCA) and digital soil mapping were used to assess and map the spatial variability of the soil quality index (SQI) in the Cauvery command area, Mandya district, Karnataka, India. A total of 145 georeferenced soil samples were drawn at 0–15 cm depth and analyzed for physico-chemical properties. PCA was used to reduce the dataset into a minimum dataset as eight important soil indicators and to determine relative weightage factors, which were used for assessing SQI with linear and non-linear scoring methods. For spatial assessment of SQI, the random forest algorithm with environmental covariates was used to map eight soil indicators selected in the minimum dataset. The soil property maps were subjected to linear and non-linear scoring, followed by multiplying with corresponding weightage factors and summation to produce SQI maps. Results reveal that values of SQI calculated using linear scoring, range from 0.10 to 0.64, with a mean of 0.39, while non-linear scoring exhibits a wider range of 0.12 to 0.78 and a mean of 0.48. With a slight higher sensitivity index of 6.5, non-linear scoring proved to be the better scoring method compared to linear scoring. Spatial assessment shows that the R2 and LCC between the calculated and predicted SQI were higher for non-linear scoring (0.66 and 0.66) compared to linear scoring (0.60 and 0.65). The SQI maps reveal high spatial variability with more than 40 percent of soils classified as moderate-to-low index. The soils with low SQI were distributed in eastern parts, whereas western parts exhibited high-to-very-high soil quality. To achieve production goals and improve soil quality in the eastern region, sustainable soil and crop management strategies must be developed, and their effects on soil quality should be assessed.

Maximizing daily rainfall prediction accuracy with maximum overlap discrete wavelet transform‐based machine learning models

AbstractRainfall is an important phenomenon for various aspects of human life and the environment. Accurate prediction of rainfall is crucial for a wide range of sectors, including agriculture, water resources management, energy production, disaster management and many more. The ability to predict rainfall in an accurate fashion enables stakeholders to make informed decisions and take necessary actions to mitigate the impacts of natural disasters, water scarcity and other issues related to rainfall. In addition, advances in rainfall prediction technologies have the potential to contribute to sustainable water management and the preservation of water resources by providing the necessary information for decision‐makers to plan and implement effective water management strategies. Hence, it is important to continuously improve the accuracy of rainfall prediction. In this paper, the integration of the maximum overlap discrete wavelet transform (MODWT) and machine learning algorithms for daily rainfall prediction is proposed. The main objective of this study is to investigate the potential of combining MODWT with various machine‐learning algorithms to increase the accuracy of rainfall prediction and extend the forecast time horizon to 3 days. In addition, the performances of the proposed hybrid models are contrasted with the models hybridized with commonly used discrete wavelet transform (DWT) algorithms in the literature. For this, daily rainfall raw data from three rainfall observation stations located in Turkey are used. The results show that the proposed hybrid MODWT models can effectively improve the accuracy of precipitation forecasting, based on model evaluation measures such as mean square error (MSE) and Nash‐Sutcliffe coefficient of efficiency (CE). Accordingly, it can be concluded that the integration of MODWT and machine learning algorithms have the potential to revolutionize the field of daily rainfall prediction.

Unravelling the non-linear response of ecosystem services to urban-rural transformation in the Beijing-Tianjin-Hebei region, China

In our transforming world, ecosystem services (ESs) and biodiversity are threatened by urban sprawl with rapid urban-rural transformation (URT), jeopardizing human well-being. Understanding the effect of URT on ESs is critical, particularly in areas those have undergone rapid urbanization. Taken the Beijing-Tianjin-Hebei (BTH) region of China as a typical case, this study measures the URT from the population-land-industry perspective and elucidates the influence of each index of URT on ESs at different stages. The URT process experienced a decline in population growth, an increase in land urbanization, and stability in non-agriculturalization rate. In particular, this study reveals an intricate and complex non-linear relationship between URT and ESs. URT negatively affects grain production (GP), habitat quality (HQ), soil retention (SR), and carbon sequestration (CS) and has a positive impact on water yield (WY). Furthermore, it was found that the response threshold of ESs to URTIs increased over time, indicating that ESs can maintain a certain degree of stability and resilience in the face of URT activities. However, ensuring the continued stability and resilience increasingly depends on the implementation of effective management and protection measures. This study advances our knowledge of the complex dynamics between URT and ESs in rapidly urbanizing areas and provides valuable insights for policymakers and planners to guide sustainable development and effective resource management.

Ecological values of Ourkiss wetland (Oum El Bouaghi province - Algeria), an overview of waterbirds diversity and richness

The monitoring of waterbirds’ abundance and richness serves as the primary method for scientists to characterize the ecological values and diversity profile of wetlands. This survey was specifically conducted in Ourkiss wetland, situated in the Oum El Bouaghi province of East Algeria, spanning from January to May 2013. The study aimed to elucidate the ecological significance of Ourkiss wetland by analyzing various parameters, including the abundance, richness, diversity profile, and conservation status of its waterbird population. A total of 23 species, representing 11 families, were documented during the survey period, with Anatidae and Rallidae emerging as the most prevalent taxa. Notably, Ourkiss wetland exhibited two distinct populations: the “wintering population” and the “breeding population,” with significant waterbird activity observed during migration between the northern and southern regions. The presence of the endangered species Oxyura leucocephala further underscores the ecological importance of this wetland. Noteworthy peaks in waterbird diversity were particularly observed in April, as indicated by richness and Shannon indices. To safeguard the ecological integrity of Ourkiss wetland, it is strongly recommended to intensify conservation efforts and implement effective management plans.

Genetic Diversity and Reproduction Trends of Phytophthora infestans in Estonia: EU_41_A2 Detected without an Indication of Clonal Reproduction.

This study explores the population dynamics of Phytophthora infestans in Estonia from 2005 to 2022, focusing on genetic diversity and potential shifts in reproductive strategies. In total, 153 P. infestans isolates were collected throughout Estonia over ten growing seasons. Genotyping revealed considerable genetic diversity, with most isolates not corresponding to known multilocus genotypes (MLGs). Still, instances of invasive clonal lineages were observed, notably EU_41_A2. The data indicate the likelihood of random mating rather than clonal reproduction in all the analyzed years. The principal coordinate analysis (PCoA) results revealed no distinct clustering among the sampling years. Statistical analysis and the minimum spanning network (MSN) indicated low genetic differentiation between years with minimal fluctuations in allele frequencies. The continuous monitoring of P. infestans populations is essential for detecting any changes from the current evolutionary trajectory and implement effective disease management strategies, especially considering the recent emergence of EU_41_A2 in the Nordics and the potential impacts of climate change.

Towards the hydrological effects of land use change in karst area, a case study in Lijiang River Basin, China

With economic and social development, the inevitable conflict between growing populations and land use change has become increasingly prominent. In karst areas, such as the Lijiang River Basin (LRB) in South China, land use has undergone rapid and intense changes over the past few decades due to urbanization and agricultural development. Assessing the hydrological effects of future land use change scenarios in karst areas is essential for estimating potential flood risks. In this study, we constructed hydrological models for the LRB based on a widely used hydrological model (SWAT, Soil and Water Assessment Tool), analyzed the runoff coefficient (Rc) at event scale, and evaluated the hydrological effects under future land use scenarios in 2100 based on five shared socio-economic pathways (SSPs). The results indicate that the simulated streamflow effectively replicated the hydrographs of the LRB. The model exhibited good performance, as evidenced by daily streamflow simulation with NSE greater than 0.65 and PBIAS within the range of ± 15 %. This demonstrates the applicability of SWAT in karst areas. The analysis of storm events revealed that severe storms in the LRB mainly took place between April and July and in November, with relatively long durations and high Rc values. Under all five SSP-based future land use scenarios, it is predicted that flood risk will increase in the LRB. Notably, the severity of flood events during the dry season is expected to escalate, with Rc potentially increasing by up to 16 %. To address environmental degradation and achieve sustainable development, it is imperative to adopt appropriate environment-friendly land use practices and implement effective land management strategies.

Challenges of the Criminology Students during the Internship Program: A Qualitative Study

The internship program is a crucial component of criminology education, providing students with practical experience in law enforcement settings. This study investigates the multifaceted challenges that criminology intern‟s face during their internships, aiming to identify key areas that need improvement to enhance their overall learning experience and academic success. The study used a qualitative approach using the phenomenological research design to explore the lived experiences of ten (10) criminology interns from one of the universities in Misamis Occidental, who encountered a lot of challenges during their internship programs were considered as participants of the study. Analysis of the response was done using Moustakas phenomenological reduction. Results identified four themes: Emotional Stress and Nervousness, Transportation Challenges, Time Management, and Academic Pressure and Workload. Emotional stress arises from the pressure to perform and fear of making mistakes, impacting confidence and performance. Transportation challenges affect punctuality and overall performance, while managing academic and internship responsibilities leads to stress and fatigue. Financial constraints further exacerbate academic challenges. The study concludes that addressing these challenges is essential for improving the internship experience and academic performance of criminology interns. It is recommended to enhance transportation infrastructure, implement effective time management strategies, provide emotional support systems, and offer financial assistance to support criminology interns.

Impact of hierarchical, horizontal and team-based organisational structures on full time teachers’ performance in Chinese secondary schools

This research aimed to investigate the impact of various management structures on the teaching performance of full-time Chinese secondary school teachers and, consequently, on the education quality. Different management structures, including hierarchical, horizontal, and team-based were explored for their contributions to students' learning opportunities. A quantitative approach was employed, analyzing data from 50 full-time Chinese secondary school teachers. The findings were interpreted using relevant statistical methods to establish the relationship between management structures and teacher performance. The study reveals that the most effective and recommended management structure involves amalgamating the strengths inherent in these different structures to create a hybrid system that is responsive to the needs of teachers. This hybrid approach is shown to have a positive impact on teacher performance. The findings of this research hold significant practical implications. Understanding the effects of management structure empowers policymakers and educational leaders to design and implement effective management strategies that support and empower teachers. This, in turn, can lead to enhanced teacher performance, improved education quality, increased job satisfaction, and motivation among educators, ultimately resulting in better student outcomes. The study thus highlights the Chinese government's emphasis on education and serves as a reference for policy adjustments to improve management efficiency.

The Impact of Leadership, Character, and Sanctity of the Congregational Pastor on the Spiritual Growth of the Church Members

This study presents the influence of leadership, character, and sanctity of the congregational pastor on the spiritual growth of church members, specifically those attending the Alfa Omega Ketintang Baru Church in Surabaya. The aim of this research is to analyze the relationship between leadership, character, and sanctity of the congregational pastor and the spiritual growth of church members, particularly those attending the Alfa Omega Ketintang Baru Church in Surabaya. The study employs a survey method to collect data on the influence of leadership, character, and sanctity of the congregational pastor on the spiritual growth of church members. The research sample consists of 150 church members of GPdI Alfa Omega Ketintang Baru in Surabaya. Data is gathered through questionnaires and analyzed using linear regression analysis. The results of the analysis indicate a positive correlation between leadership, character, and sanctity of the congregational pastor and the spiritual growth of church members. The research finds that improvements in leadership, character, and sanctity of the congregational pastor are associated with an increase in the spiritual growth of GPdI Alfa Omega Ketintang Baru church members in Surabaya. The results are as follows: When looking at the population, a t-value of 4.321 for leadership, 3.378 for character, and 5.721 for sanctity is obtained, which is significant at a < 0.05 level. This implies that the variables of leadership, character, and sanctity of the congregational pastor significantly influence the spiritual growth of GPdI Alfa Omega Ketintang Baru church members in Surabaya. Future studies could expand the scope of this research by involving more variables that affect the spiritual growth of church members. Additionally, it is essential to conduct evaluations of church programs, collaborate with mission agencies, and implement effective management systems to enhance the spiritual quality of Christians, the analysis also yielded an R-squared value (Coefficient of Determination) of 0.790 or 79.0%. This means that the contribution of the variables Leadership, Character, and Sanctity of the Congregation's Leader in shaping the Spiritual Growth of the GPdI Alfa Omega Congregation in Ketintang Baru, Surabaya, is 79.0%, while the remaining 21% is influenced by other factors outside the research model.

Fast Recognition and Counting Method of Dragon Fruit Flowers and Fruits Based on Video Stream.

Dragon fruit (Hylocereus undatus) is a tropical and subtropical fruit that undergoes multiple ripening cycles throughout the year. Accurate monitoring of the flower and fruit quantities at various stages is crucial for growers to estimate yields, plan orders, and implement effective management strategies. However, traditional manual counting methods are labor-intensive and inefficient. Deep learning techniques have proven effective for object recognition tasks but limited research has been conducted on dragon fruit due to its unique stem morphology and the coexistence of flowers and fruits. Additionally, the challenge lies in developing a lightweight recognition and tracking model that can be seamlessly integrated into mobile platforms, enabling on-site quantity counting. In this study, a video stream inspection method was proposed to classify and count dragon fruit flowers, immature fruits (green fruits), and mature fruits (red fruits) in a dragon fruit plantation. The approach involves three key steps: (1) utilizing the YOLOv5 network for the identification of different dragon fruit categories, (2) employing the improved ByteTrack object tracking algorithm to assign unique IDs to each target and track their movement, and (3) defining a region of interest area for precise classification and counting of dragon fruit across categories. Experimental results demonstrate recognition accuracies of 94.1%, 94.8%, and 96.1% for dragon fruit flowers, green fruits, and red fruits, respectively, with an overall average recognition accuracy of 95.0%. Furthermore, the counting accuracy for each category is measured at 97.68%, 93.97%, and 91.89%, respectively. The proposed method achieves a counting speed of 56 frames per second on a 1080ti GPU. The findings establish the efficacy and practicality of this method for accurate counting of dragon fruit or other fruit varieties.

Changing the diagnostic paradigm for sugarcane: development of a mill-based diagnostic for ratoon stunting disease in crude cane juice.

The availability of efficient diagnostic methods is crucial to monitor the incidence of crop diseases and implement effective management strategies. One of the most important elements in diagnostics, especially in large acreage crops, is the sampling strategy as hundreds of thousands of individual plants can grow in a single farm, making it difficult to assess disease incidence in field surveys. This problem is compounded when there are no external disease symptoms, as in the case for the ratoon stunting disease (RSD) in sugarcane. We have developed an alternative approach of disease surveillance by using the crude cane juice expressed at the sugar factory (mill). For this purpose, we optimized DNA extraction and amplification conditions for the bacterium Leifsonia xyli subsp xyli, the causal agent of RSD. The use of nucleic acid dipsticks and LAMP isothermal amplification allows to perform the assays at the mills, even in the absence of molecular biology laboratories. Our method has been validated using the qPCR industry standard and shows higher sensitivity. This approach circumvents sampling limitations, providing RSD incidence evaluation on commercial crops and facilitating disease mapping across growing regions. There is also potential is to extend the technology to other sugarcane diseases as well as other processed crops.

Effective Government Management of Flood Discharge in Drainage Channels using HEC-RAS 6.3.1 Application

Flooding remains one of the most significant natural disasters affecting communities around the world. Proper management of flood discharge in drainage channels is essential to mitigate its impacts on public safety, infrastructure, and the environment. In recent years, advancements in hydrodynamic modeling tools, such as the Hydraulic Engineering Center's River Analysis System (HEC-RAS) 6.3.1, have provided governments with powerful tools to analyze and manage flood discharges effectively. This research aims to investigate the role of government-led management strategies in handling flood discharge within drainage channels using the HEC-RAS 6.3.1 application. The study assesses how the application's features and capabilities can be harnessed by governmental agencies to make informed decisions and implement effective flood management plans. The research methodology involves a combination of field surveys, data collection, and computer simulations using the HEC-RAS 6.3.1 software. Geographic information systems (GIS) data, topographical surveys, and historical flood records are utilized to calibrate and validate the model's accuracy. Various flood scenarios are simulated to assess the performance of different government-led management strategies. The findings of this study reveal that the integration of HEC-RAS 6.3.1 with government-led management approaches enhances the understanding of flood dynamics within drainage channels. The application facilitates the identification of critical flood-prone areas, prediction of potential flood events, and evaluation of flood mitigation measures. The government can utilize this valuable information to formulate more effective flood management policies and allocate resources efficiently.

A Review of Rhodolith/Maerl Beds of the Italian Seas

Coralline algal beds are comprised of biogenic calcareous formations considered a habitat of high conservation interest, hosting a high great biodiversity. To assess the status of this habitat in the Italian seas, we report results from a systematic analysis of the available scientific literature. Italian rhodolith/maerl beds are reported on 31 Italian sites mostly located around islands, shoals, banks, terraces, and gentley sloping shelves, from 9 m to 130 m water depth (with a mean depth of about 56 m). The dominant species occurring in the Italian submarine sites are Phymatolithon calcareum and Lithothamnion corallioides, with a rich associated fauna including sponges, bryozoans, hydrozoans, polichaetes, molluscs, amphipods, gastropods, echinoderms. Despite the high biodiversity characterizing the Italian rhodolith/maerl beds, only seven submarine sites hosting this sensitive habitat are part of Marine Protected Areas (MPAs). This evidence highlights the need for actions focused on the implementation of effective management and proper conservation measures to preserve such precious habitats. Protection of this habitat cannot be effectively provided without access to multidisciplinary data (e.g., geospatial, biological, geophysical, geomorphological data) capable of assessing its spatial distribution and biological characteristics over wide areas. An increased research effort to improve the production of fine-scale distribution maps and monitoring activities is therefore needed.

Residents’ valuation of ecosystem services in a Mediterranean coastal dune ecosystem: The case of the Ritoque dunes in central Chile

Coastal dunes provide a variety of cultural and ecological ecosystem services to local communities. However, most of these ecosystems are globally threatened by anthropic factors. Chile is home to important dune ecosystems such as the emblematic Ritoque coastal dunes located in the hotspot for biodiversity conservation in central Chile where there is a delicate relationship between conservation and human development interests, among local communities and authorities. Here, we performed a choice experiment study to determined willingness to implement conservation measures in the Ritoque dunes. In particular, we assessed residents’ preferences for improvements of the current state of local ecosystem services such as scenic beauty, biodiversity and archaeological sites. Residents showed preferences for improvements in Ritoque coastal dunes’ ecosystem services, and a high willingness to pay for protecting biodiversity and archeological sites, rather than for recreational infrastructure. Our study highlights the importance of place-based research that specifically addresses residents and stakeholders’ conservation priorities, which could be used to design and implement effective conservation management strategies for coastal ecosystems and coastal cities near them.

Knowledge Management Framework Implementation In Government To Increase Organization Performance

The Jak preneur Program is one of Dinas PPUMKM's most successful MSME empowerment and development initiatives in Jakarta. MSMEs are critical to the global economy, contributing to job creation, innovation, and economic growth. However, they frequently face challenges in effectively harnessing and utilizing their knowledge assets to drive competitiveness, particularly for the DKI Jakarta Provincial Government (Pemprov DKI Jakarta). This study investigates the implications of knowledge management in a government organization's Jak preneur program under the supervision of Dinas PPUKM (Provincial Government Department of Industry, Trade, Small and Medium-sized Enterprises). Furthermore, the study's findings will help MSMEs overcome the lack of knowledge-based growth barriers. This thesis investigates the concept of knowledge management (KM) in the context of public government organizations. The goal of this study is to provide a comprehensive analysis of Knowledge Management practices in government organizations, examining current approaches, challenges, and potential strategies and frameworks for improvement. The study employs a qualitative approach that includes in-depth interviews and focuses on group discussions (FGD) with multiple perspectives from MSME owners, managers, mentors, and facilitators in order to identify knowledge gaps, which will be classified into four categories: people, processes, technology, and governance. Each stakeholder is expected to participate in the knowledge management process, accelerating the organization's goal of raising the standard of its MSMEs. The study's findings can help policymakers, MSME practitioners, and researchers design and implement effective knowledge management initiatives. The proposed system is intended to be used to clarify the management of Dinas PPUMKM (Provincial Government Department of Industry, Trade, Small and Medium-sized Enterprises), including not only roles and responsibilities but also how the knowledge management system can improve the company's day-to-day performance.