Hotel industry

Background: The present study was conducted with the aim of designing a model of normal ethical marketing in the hotel industry. Method: This research is qualitative in terms of purpose, exploratory in terms of approach, and qualitative in terms of data analysis. The statistical population was a group of hotel industry experts from whom a total of 9 people were selected as the sample by purposive sampling and theoretical saturation. The research tool was in-depth interviews. Data were analyzed using theme analysis methodology. Results: According to the results of the study, the main category in this study was "the attention of hotel industry managers to ethical marketing norms." Causal conditions include knowledge of ethical norms, emphasis on upstream rules on ethical norms in marketing, modeling of the world hotel industry, training courses for hotel managers and staff on ethical norms in marketing and reforming and improving the reward and punishment system in line with ethical norms He was in the marketing of the hotel industry. Areas included "Emphasis on Ethical Decision-Making at All Levels of the Organization" and "Ethical Organizational Culture", and environmental conditions included "Societychr(chr('39')39chr('39'))s desire to comply with ethical marketing norms in the hotel industry" and "Economic problems in the country." Strategies also included the categories of "ethical hospitality" and "compliance with organizational social responsibility", which led to the consequence of "customer satisfaction of the hotel industry". Conclusion: The results of the research led to the design of a model of ethical marketing in the hotel industry and showed that ethics is a fundamental element and in developing marketing models for the hotel industry, special attention should be paid to this important issue.

In this research, we try to determine the strategic planning and the most appropriate strategic options for hotels through a case study, considering the current situation of hotel industry in Iran. For this purpose, Parsian Evan hotel, a four star located in Tehran was selected as a case study. Initially, the mission and vision of the hotel were expressed; then a questionnaire was prepared for investigating the internal and external environment of hotel and determining its strengths, threats and opportunities of the hotel and distributed among 5 senior managers in Evin Hotel. In the next step, the information of the questionnaires was extracted and the evaluation matrices of internal and external factors were formulated based on that information. Next, the related strategies were provided after comparing the weaknesses, strengths, opportunities and threats. The most important strategic options were identified based on the views and comments of the above-mentioned senior managers and consultations with two of the elites of the hotel industry in Iran, according to which the SWOT matrix and internal and external factors (IE) were prepared. Finally, the related strategies were introduced and the quantitative strategy planning matrix (QSPM) was formulated by identifying the hotel’ position in the IE matrix. The results of the matrices indicated that Evin Hotel is currently in an aggressive position and can use the most important strategies related to the comparison of strengths and opportunities (SO) to overcome the competitors. In addition to Evin hotel, the top managers of other hotels can also use the presented process for their strategic planning according to their capabilities.

The purpose of this research is to Developing a dynamic model for the impact of Servicescape on customer experience in the hotel industry. The present study is a mixed research method. In the qualitative part, the strategy is qualitative content analysis and in the quantitative part, it is applied in terms of purpose and descriptive-survey in terms of research method. To gather information in the qualitative section a collection of articles, books and thesis has been used systematically and in the quantitative part, a standard questionnaire was used to collect information. 700 loyal customers of five-star hotels in Northwest of Iran were selected for the study. A clustered sampling method was used to select statistical sample. In qualitative part, To analyze the data of this research, special content analysis processes including open coding,, axial coding were used to emerge concepts and categories. In the quantitative part, the research hypotheses were tested using structural equation modeling technique. The results of the research showed that the substantive staging and communicative staging have a positive impact on the customer experience and the effect of communicative staging on customer experience at different stages of the relationship life cycle is different.

Artificial intelligence enhances energy infrastructure efficiency, reduces waste in distributed energy systems, and ensures long-term durability. Additionally, green Internet of Things technology is positively linked to green innovation practices promoting sustainability. In this context, the primary objective of this study is to examine the impact of the Internet of Things and artificial intelligence on environmental sustainability performance, considering the mediating influence of green supply chain management within the hotel industry. This study is designed as applied research, and the data collection method is descriptive and correlational. The statistical population comprises hotel managers in Urmia City, with a sample size of 34 hotels determined using "Krejcie and Morgan" and "Cohen" tables. Sixty-four questionnaires were distributed among hotel managers in Urmia City. A standard questionnaire, validated by experts, was used to collect data. Its reliability was estimated using Cronbach's alpha coefficient. Structural equation modeling was used for data analysis, revealing that the Internet of Things and artificial intelligence positively impact green supply chain management. Furthermore, a positive relationship was observed between green supply chain management practices and environmental sustainability performance. This study suggests that adopting the Internet of Things and artificial intelligence technologies can enhance the efficiency of green supply chain management processes, emphasizing the importance for managers to grasp the impact of these two emerging technologies on overall supply chain performance.