The paper at hand analyses the principal-agent relationship, where comparative perspective between principals’ (municipalities) and agents’ (public utility providers) in the field of water and wastewater management is scrutinized. The goal of the paper is twofold: firstly, to present empirical results validating principal-agent relationships that emerged due to the reorganization process of public enterprises; secondly, to highlight the similarities and differences between the perspectives of principals and agents regarding motives, advantages and disadvantages, and price-setting in relation to the reorganization process. The empirical research is based on the primary data collected through two self-prepared and structured online questionnaires—one for municipalities, and the other for public utility providers. The results reveal similarities between public enterprises and municipalities in motivating factors for full municipal ownership. However, differences are seen among the advantages of the reorganization process. Price-setting by public utilities is recognized as a motivating mechanism for agents.

Nigeria’s palm oil processing industry poses significant environmental pollution risks, jeopardizing the country’s ability to meet the UN’s 17 Sustainable Development Goals (SDGs) by 2030. Traditional processing methods generate palm oil mill effluent (POME), contaminating soil and shallow wells. This study investigated water samples from five locations (Edo, Akwa-Ibom, Cross River, Delta, and Imo states) with high effluent release. While some parameters met international and national standards (WHO guidelines, ASCE, NIS, and NSDWQ) others exceeded acceptable limits, detrimental to improved water quality. Results showed, pH values within acceptable ranges (6.5–8.5), high total conductivity and salinity (800–1150 µS/cm), acceptable hardness values (200–300 mg/L), nitrite concentrations (10–45 mg/L), excessive magnesium absorption (> 50 mg/L), biochemical oxygen demand (BOD) indicating significant pollution (75–290 mg/L), total dissolved solids (TDS) exceeding safe limits in four locations, total solids (TS) exceeding allowable limits for drinking water (310–845 mg/L), water quality index (WQI) values ranged from “poor” to “very poor”. POME contamination by metals like magnesium, nitrite, chloride, and sodium compromised shallow well water quality. Correlation analysis confirmed robust results, indicating strong positive correlations between conductivity and TDS (r = 0.85, p < 0.01) and pH and total hardness (r = 0.65, p < 0.05). The study emphasizes the need for environmentally friendly palm oil processing methods to mitigate pollution, ensure safe drinking water, and achieve Nigeria’s SDGs. Implementation of sustainable practices is crucial to protect public health and the environment.

The purpose of this study is to examine the impact of tourist spending and the growth of Oman’s tourism industry on the country’s GDP from 1996 to 2018. The study uses the error correction model and other tests for assessing the link among variables, such as the cointegration test and the Granger causality test, to accomplish its aims. Findings from the error correlation model and cointegration test show that there is a link between the variables in Oman over the long and short term. There is a positive and statistically significant relationship between tourist expenditures and economic growth, as well as a negative and statistically significant relationship between tourism expansion and economic growth. We now use ARDL regression estimators to assess the robustness of the empirical results. There is no evidence of a direct relationship between increased tourism and GDP growth, according to the study’s results. According to the research, sustainable tourism development is an achievable economic growth driver, and Oman should prioritize economic policies that support this trend.

This paper mainly uses the idea of pedigree clustering analysis, gray prediction and principal component analysis. The clustering analysis model, GM (1,1) model and principal component analysis model were established by using SPSS software to analyze the correlation matrices and principal component analysis. MATLAB software was used to calculate the correlation matrices. In January, The difference in price changes of major food prices in cities is calculated, and had forecasted the various food prices in June 2016. For the first issue, the main food is classified and the data are processed. After that, the SPSS software is used to classify the 27 kinds of food into four categories by using the pedigree cluster analysis model and the system clustering. The four categories are made by EXCEL. The price of food changes over time with a line chart that analyzes the characteristics of food price volatility. For the second issue, the gray prediction model is established based on the food classification of each kind of food price. First, the original data is cumulated, test and processed, so that the data have a strong regularity, and then establish a gray differential equation, and then use MATLAB software to solve the model. And then the residual test and post-check test, have C <0.35, the prediction accuracy is better. Finally, predict the price trend in June 2016 through the function. For the third issue, we analyzed the main components of 27 kinds of food types by celery, octopus, chicken (white striped chicken), duck and Chinese cabbage by using the data of principal given and analyzed by principal component analysis. It can be detected by measuring a small amount of food, this predict CPI value relatively accurate. Through the study of the characteristics of the region, select Shanghai and Shenyang, by looking for the relevant CPI and food price data, using spss software, principal component analysis, the impact of the CPI on several types of food, and then calculated by matlab algorithm weight, and then the data obtained by the analysis and comparison, different regions should be selected for different types of food for testing.

This paper highlights the complex relationship between entrepreneurship, sustainable development, and economic growth in 41 European countries, using a reliable K-Means cluster analysis. The research thoroughly evaluates three key factors: the SDG Index for sustainable development, GDP per capita for economic well-being, and the New Business Density Rate for entrepreneurial activity. Our methodology reveals three distinct narratives that embody varying degrees of economic vitality and sustainability. Cluster 1 comprises the financially stable and sustainability-oriented countries of Western and Northern Europe. Cluster 2 showcases the variegated economic and sustainability initiatives in Central and Southern Europe. Cluster 3 envelopes the economic titans with noteworthy business expansion but with the potential for better sustainable practices. The analysis reveals a favourable association between economic prosperity and sustainable development within clusters, although with nonlinear intricacies. The research concludes with a series of strategic imperatives specifically crafted for each cluster, promoting economic variation, increased sustainability, invention, and worldwide collaboration. The resulting findings highlight the crucial need for policy-making that considers the specific context and the potential for combined European resilience and sustainability.

Ancient Minipe Anicut, Sri Lanka is world-famous for its engineering excellence. Due to its importance, conserving the ancient anicut, another anicut was constructed downstream in the 20th century. Nevertheless, the water diverted from the ancient anicut to the Minipe Left Bank (LB) Canal was kept as it was due to inherited agricultural importance. This research focuses on studying the contributions made by the adjacent catchment along the Minipe LB Canal. There are several level crossings along the Minipe Left Bank Canal from which the runoff of the local catchment flow into the Minipe LB Canal. Hydrologic Modeling System (HEC-HMS) is used to obtain the yield from each catchment into the Canal, which was compared with the annual diversions from Minipe anicut. The total yield from each stream has been compared with the annual diversion of the Minipe LB Canal from 2014 to 2020. The results obtained from this study reveal that there is sufficient water available for water augmentation in the basin, with an estimated annual average cumulative yield from the catchment of 453.6 MCM. This cumulative yield is 1.7 times the annual average diversion from the Mahaweli River, which is 271.9 MCM. With the findings, it is concluded that there is a potential to augment water from the catchment to address pertaining water shortages conveyance in the command area.