درخت حوزه‌های تخصصی

ChatGPT is an AI model designed for conversational purposes. This field has gained significant popularity in digital marketing, providing organizations with a vital tool for interacting with customers and enhancing their marketing efforts. The primary objective of this research is to examine the impact of ChatGPT on customer experience in digital marketing. Additionally,this study aims to investigate the moderating effects of business type, familiarity and comfort with technology on customer experience. Furthermore, the research explores the moderating roles of gender, age, and education level. Data for this study was collected electronically from 394 customers who interacted with ChatGPT in digital marketing using an open-access questionnaire. The results confirm the importance of the moderating role of familiarity and comfort with technology, business type, age, and education level in the relationship between customer experience with ChatGPT andOverall Satisfaction (OS)with digital marketing, while gender has no significant impact. The findings of this paper contribute to the existing literature on the use of conversational AI models in digital marketing and customer experience, providing insights and recommendations for future research

One of the techniques for evaluating a supplier's sustainability is Data Envelopment Analysis (DEA). DEA is a non-parametric tool for measuring the relative efficiency of Decision-Making Units (DMUs). This paper develops a new double frontier DEA model based on the Slacks-Based Measure (SBM) for assessing suppliers' sustainability. Our proposed double frontier SBM model considers pessimistic and optimistic efficiencies. A case study is presented to demonstrate the applicability of the proposed model. The results show that the proposed model can completely rank the DMUs, and there is no tie between the overall efficiency scores

 Urban agriculture promotes sustainable development and fosters societal participation, including the rehabilitation of various groups, such as inmates. Therefore, this research aimed to analyze the effectiveness of prison-farm rehabilitation programs in Dizel Abad Prison in Iran. The research population consisted of two groups: one with 130 inmates, of whom 97 were selected and studied through systematic sampling via Cochran's formula, and the second group included 14 managers, offenders, and prison experts interviewed through a census. The data collection instrument was a researcher-developed questionnaire based on the Kirkpatrick evaluation model. The reliability of the questionnaire was confirmed using Cronbach's alpha coefficient, while its face and content validity were validated by a panel of experts. The findings at the first level of evaluation (i.e., reaction) showed that, with a confidence interval of 99%, the inmates were satisfied with participating in the urban agriculture training course. At the second level (i.e. learning), results indicated a significant increase in the inmates’ knowledge, with a statistically significant difference between their pre- and post-test scores (p<0.01). At the third level (i.e., behavior), the findings suggested that urban agriculture in prisons could lead to significant behavioral changes in inmates, with 95% confidence. At the fourth level of evaluation (i.e., results), the findings showed that although the urban agriculture training course in Dizel Abad Prison caused moderate changes in the inmates, the difference in pre-and-post-test scores was not statistically significant. Overall, the findings demonstrated that the urban agriculture training course in Dizel Abad Prison could bring about changes in inmates’ behavior, knowledge, and attitude. These findings support the potential of prison-farm programs within urban agriculture initiatives as viable methods for rehabilitation.