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This paper attempted to present a simple workable accounting framework for allocating the costs of pollution damages on various polluting sources.The government and specialized authorities can use the cost allocation models to impose tax and fees on pollutant sources. Accordingly, pollutant sources are obliged to disclose taxes and fees explicitly in its financial statements as part of product or service costs. At the same time, the accounting profession could develop these measures while considering new projects that are expected to produce potential pollution damages. These measures will help as control devices to issuing licenses for establishment and operation of new enterprises. Also, usage of the proposed framework over a period of time will help in control the pollutant emissions within permissible levels internationally which is one necessary step of applying the concept of green accounting and sustainable development. A simple numerical example illustrates the theoretical discussion.

IntroductionThe primary objective of the current paper is to understand the impact of Generative AI Tools on the recruitment process, on their effectiveness in addressing bias, enhancing efficiency, and ensuring accurate candidate evaluation and looking at the moderating role of familiarity and the mediating role of the size of the organization and level of employee.MethodsA quantitative survey approach, with 469 professionals participating in an online survey, was used. Structural Equation Modelling (SEM) in Amos SPSS was used in the analysis of the relationships between Generative AI Tools, User Familiarity with AI, and key outcomes in the recruitment process.ResultsThe study reveals a significant reduction in bias during candidate screening, attributed to the algorithmic objectivity, data driven decision making, and consistency inherent in Generative AI Tools. Efficiency gains and heightened accuracy in shortlisting candidates were also observed. However, User Familiarity with AI emerged as a moderating factor in influencing the relationship between Generative AI Tools and efficiency improvement.DiscussionAs a recommendation, organizations are encouraged to invest in continuous training programs to harness the full potential of Generative AI Tools in optimizing efficiency and ensuring a fair and accurate recruitment process.