Advertisement of the product is an important factor in inventory analysis. Also, price and stock have an important role to attract more customers in the competitive business situations. Trade credit policy is another important role in inventory analysis. We have combined these three factors together in a two-warehouse inventory model and represented it mathematically. In addition, we have added deteriorating factor of our proposed problem with price-and stock-dependent demand under partial backlogged shortage and solved. The frequency of advertisement is considered constant for a year in this paper. The proposed model is highly nonlinear in nature. Due to highly nonlinearity, we could not find the closed form solution. In this paper, trade credit facility is taken in the perspective of retailer, and all the possible cases and subcases of the model are discussed and solved using lingo 10. 0 software. The results of sensitivity analysis prove the effectiveness of the proposed model.

The present study proposes a hybrid model for taxpayer credit scoring. In this regard, after examining taxpayer behavior, and in order to present a taxpayer credit scoring model, the steps of the Compliance Risk Management Program of the Organization for Economic Co-operation and Development (OECD, 2004) were applied to the Iranian tax system. This program includes the stages of determining the operational context of the compliance risk management program (internal and external), identifying the risks of taxpayer non-compliance, ranking, prioritizing, and assessing risks, as well as implementing strategies to address and mitigate risks. Accordingly, in this stage, 44 non-compliance risks were identified and classified into four categories: non-registration and identification, non-submission, failure to provide accurate information (income concealment), untimely tax payment, and the availability of skilled and competent human resources. The identified risks were then validated through a fuzzy Delphi approach and expert consultation in the field. The proposed model consists of two main phases: pre-registration analysis and post-registration analysis. In the pre-registration phase, it is necessary to implement controls regarding the legal grounds for applicants’ registration. As part of the registration process, the tax authority can cross-check the information provided in the taxpayer’s application form with other registrations using the same postal code, residential addresses, mobile phone numbers, bank accounts, suspicious databases, and data from other governmental agencies. Moreover, making initial contact with taxpayers to verify the accuracy and authenticity of the submitted information constitutes an effort to prevent fraud. In the post-registration analysis phase, in addition to providing education and counseling services regarding the risks of tax filing, payment, and declaration, the involvement of the tax authority occurs only when risks are realized, and this takes place after the registration process. Overall, the findings of this study highlight the need for special attention by tax authorities to improve processes and increase transparency within the tax system.

Inventory control systems are supposed that the purchasing cost is paid at the time of delivery of product. But sometimes in order to motivate the customers to buy more, supplier lets customers to pay the purchasing cost under delay payment method as an incentive policy. In this paper a periodic inventory control model is considered in which the interval between two replenishments is a random variable. Indeed the economic order quantity model is developed under two policies including delayed payment and stochastic replenishment interval. It is proved that the profit function of retailer is concave and the main aim of this paper is to determine the maximum level of inventory such that the profit of retailer is maximized. In continue in order to show the applicability of the proposed model, several numerical examples and sensitivity analyses have been presented.

Credit risk issues and methods for identifying and predicting it have been constantly evolving over the past few decades. When a company deals with a financial problem, it may not be able to fulfill its financial obligations, which can cause direct and indirect financial losses to shareholders, creditors, investors and other people in the community. Advanced credit risk models that are based on market value include improving credit quality as well as reducing or decreasing credit ratings. In the present study, we have Investigated two models of advanced credit risk models, so two samples were selected, namely companies with financial problems and companies with financial health, in each group probabilities of default are estimated by two models which are KMV and ZPP, and then we compared probabilities of default. We have concluded that the ZPP model has more predictive ability than the KMV model. This method is denoted the Zero-Price Probability or simply the ZPP model. The main focus is on the new simulation based approach rather than the older established models.