The coastal area of Bohai Bay of China has a wide distribution of salt-accumulated soils which could pose a problem to the sustainable development of the local ecology. As a result, the land remains largely degraded and unsuitable for biophysical and agricultural purposes. In this study, we characterized the soil and native plants in the area, to properly understand and identify species with satisfactory adaptation to saline soil and of high economic or ecological value that could be further developed or domesticated, using appropriate cultivation techniques. The goal was to determine the salinity parameters of the soil, identify the inhabiting plant species and contribute to the ecosystem data base for the Bay area. A field survey involving soil and plant sampling and analyses was conducted in Yanshan and Haixing Counties of Hebei Province, China, to estimate the level of salt ions as well as plant species population and type. The mean electrical conductivity (EC) of the soils ranged from 0.47 in more remote locations to 23.8 ds/m in locations closer to the coastline and the total salt ions from 0.05 to 8.8 g/kg, respectively. Each of the salinity parameters, except HCO₃⁻ showed wide variations as judged from the coefficient of variation (CV) values. The EC, as well as chloride, sulphate, Mg and Na ions increased significantly towards the coastline but the HCO₃⁻ ion showed a relatively even distribution across sampling points. Sodium was the most abundant cation and chloride and sulphate the most abundant anions. Therefore, the most dominant salinity-inducing salt that should be properly managed for sustainable ecosystem health was sodium chloride. Based on the EC readings, the most remote location from the coastline was non-saline but otherwise, the salinity ranged from slightly to strongly-very strongly saline towards the coast. There were considerably wide variations in the number and distribution of plant species across sampling locations, but most were dominated entirely Phragmites australis, Setaria viridis and Sueda salsa. Other species identified were Aeluropus littoralis, Chloris virgata, Heteropappus altaicus, Imperata cylindrica, Puccinellia distans, Puccinellia tenuiflora and Scorzonera austriaca. On average, the sampling points furthest from the coast produced the most biomass, and the point with the highest elevation had the most diverse species composition. Among species, Digitaria sanguinalis produced the highest dry mass, followed by Lolium perenne and H. altaicus, but there were considerable variations in biomass yield across sampling locations, with the location nearest the coastline having no vegetation. The observed variations in soil and vegetation should be strongly considered by planners to allow for the sustainable development of the Bahai bay area.

The use of infrastructure as a catalyst for Indonesia’s economic growth faces significant challenges. One example is the construction projects, which have not reached the intended goal and have led to an increase in investment cost compared to the original plan. Additionally, the interaction between the government and companies involved in toll-road construction projects under the public-private partnerships (PPP) mechanism has yet to produce good quality project governance and expected project performance. This study aimed to find empirical data on the determination of project intellectual capital and project ownership structure through good project governance on toll-road project performance in Indonesia. This study adopted a quantitative approach that involved data collected through a survey conducted among toll-road projects from 2015 to 2019. The data was analyzed with Structural Equation Modeling Partial Least Square (SEM-PLS). The results showed that project intellectual capital and project ownership structure significantly affected good project governance. Good project governance Practices significantly affected project performance. Project intellectual capital and project ownership structure influenced project performance through the mediation of good project governance. Conversely, two hypotheses were not supported by the data, i.e., the effect of project intellectual capital and project ownership structure on project performance. The findings of this research contributed to the literature regarding the implementation of collaborative governance in PPPs toll road development projects in Indonesia by providing a framework and assessment tools, which could be valuable for researchers and policymakers in analyzing and evaluating the governance and performance of toll road construction PPP projects.

This study aims to identify the causes of delays in public construction projects in Thailand, a developing country. Increasing construction durations lead to higher costs, making it essential to pinpoint the causes of these delays. The research analyzed 30 public construction projects that encountered delays. Delay causes were categorized into four groups: contractor-related, client-related, supervisor-related, and external factors. A questionnaire was used to survey these causes, and the Relative Importance Index (RII) method was employed to prioritize them. The findings revealed that the primary cause of delays was contractor-related financial issues, such as cash flow problems, with an RII of 0.777 and a weighted value of 84.44%. The second most significant cause was labor issues, such as a shortage of workers during the harvest season or festivals, with an RII of 0.773. Additionally, various algorithms were used to compare the Relative Importance Index (RII) and four machine learning methods: Decision Tree (DT), Deep Learning, Neural Network, and Naïve Bayes. The Deep Learning model proved to be the most effective baseline model, achieving a 90.79% accuracy rate in identifying contractor-related financial issues as a cause of construction delays. This was followed by the Neural Network model, which had an accuracy rate of 90.26%. The Decision Tree model had an accuracy rate of 85.26%. The RII values ranged from 68.68% for the Naïve Bayes model to 77.70% for the highest RII model. The research results indicate that contractor financial liquidity and costs significantly impact construction operations, which public agencies must consider. Additionally, the availability of contractor labor is crucial for the continuity of projects. The accuracy and reliability of the data obtained using advanced data mining techniques demonstrate the effectiveness of these results. This can be efficiently utilized by stakeholders involved in construction projects in Thailand to enhance construction project management.

In response to the rapid and dynamic changes in the economic environment, companies must improve their processes to maintain competitiveness. This includes enhancing their intellectual capital, with particular emphasis on effective onboarding processes, which play a crucial role in integrating new employees and retaining talent. This enhances the value of the organization’s intellectual capital and emphasizes onboarding—the training and integration of new employees—whose proper functioning impacts staff retention. Drawing on both Hungarian and predominantly foreign literature, we highlight onboarding processes and examine their implementation in Hungarian companies of various sizes. The research employed a mixed-method approach, combining semi-structured interviews and questionnaires. In-depth interviews were conducted with HR leaders from 13 Hungarian organizations to explore the existence of mentoring programs. Additionally, 161 employees across Hungary completed questionnaires, which examined their perspectives on onboarding processes and the relationship between mentoring programs and company size. We analyzed the data using chi-square tests to assess the strength of these relationships. While all large companies in our sample had formal mentoring programs, smaller companies displayed more variability, with some relying on informal or ad-hoc onboarding processes. Based on these results, we identified several key areas for improvement in onboarding processes. These include enhancing the structure of feedback interviews, ensuring more comprehensive communication channels, and strengthening mentoring programs across companies of all sizes. By addressing these gaps, companies can improve employee retention, engagement, and overall integration during the onboarding process, contributing to a more stable and motivated workforce.