The dairy industry is considered one of the most needed industries in almost every country; this is due to the continuous daily demand of its different products. Nevertheless, this industry consumes large amount of water, energy and material resources, and generates large quantities of liquid and solid wastes. In the sequel, under the pressure of fulfilling the 17 sustainable development goals (17 SDGs), it is important to address the sustainability of this sector in the world and particularly in developing countries. This study aims at assessing the impact of environmental, economic and social sustainability practices on the organizational performance of dairy industry in Palestine. To this end, a quantitative-research approach, based on a questionnaire for data collection, was adopted. Data has been collected from a convenient sample of 15 dairy factories working in West Bank in Palestine during a three-month period from March to May, 2023. Inferential statistical analyses were conducted as well. The results revealed that there is a difference between the median values of environmental and economic practices. In addition, the results showed that there is a medium relationship between sustainability practices and organizational performance. However, the economic practices proved to have the strongest impact then social practices; while, there is no impact of environmental practices on organizational performance. Furthermore, the results showed that this industry consumes larger amount of water as well as it generates large amounts of wastewater that mainly discharged to the drainage system without treatment for recycling or reuse. Several sound recommendations are given at the end of this paper. It worth mentioning that there are no previous studies conducted on the dairy industry sector in Palestine about sustainability assessment.

This study explores the determinants of auditor performance, focusing on the moderating role of organizational commitment within the Tangerang City Inspectorate. Employing stratified random sampling, a sample of 250 auditors was chosen to ensure diversity across experience, departmental affiliation, and roles. Quantitative analysis used SPSS to examine the relationships between auditor performance, organizational commitment, and other relevant variables. Findings indicated that organizational commitment significantly moderates the effects of various social pressures on auditor performance. This underscores the necessity for auditing organizations to foster organizational commitment to enhance auditor efficacy and uphold ethical standards. These results hold substantial implications for governance and audit quality assurance, suggesting that reinforced organizational commitment could lead to more robust auditor performance and ethical conduct within similar urban governance settings. This study contributes valuable insights into the influence of organizational dynamics on auditor behaviour and performance outcomes.

Identify and diagnosis of homogenous units and separating them and eventually planning separately for each unit are considered the most principled way to manage units of forests and creating these trustable maps of forest’s types, plays important role in making optimum decisions for managing forest ecosystems in wide areas. Field method of circulation forest and Parcel explore to determine type of forest require to spend cost and much time. In recent years, providing these maps by using digital classification of remote sensing’s data has been noticed. The important tip to create these units is scale of map. To manage more accurate, it needs larger scale and more accurate maps. Purpose of this research is comparing observed classification of methods to recognize and determine type of forest by using data of Land Cover of Modis satellite with 1 kilometer resolution and on images of OLI sensor of LANDSAT satellite with 30 kilometers resolution by using vegetation indicators and also timely PCA and to create larger scale, better and more accurate resolution maps of homogenous units of forest. Eventually by using of verification, the best method was obtained to classify forest in Golestan province’s forest located on north-east of country.