احسان بخشی خورده بلاغ

Management of sustainable hospital services, while giving importance to patient care, also considers economic and environmental issues. The aim of the current research is to identify, analyze the scenario and analyze the effective drivers of sustainable service management in the hospitals of Kerman

The present study is a quantitative study that was conducted in 1402. The statistical population of this research is all the experts of Kerman hospitals (including doctors, hospital managers, development and support assistants and administrative assistants) with at least 10 years of work experience and working experience as managers or consultants in Kerman hospitals. 10 experts were selected as samples by snowball method. Based on this, at first, according to the research literature and soliciting opinions from hospital experts, the drivers of sustainable service management in the health field were identified. Then, the data was analyzed with the method of fuzzy cognitive mapping, and then forward and backward scenarios were performed.

The results showed that there are 18 drivers in the management of sustainable services in the health field, the driver of reforming the organizational structure with a weight of 5.90 has high effectiveness and the driver of hospital waste management system with a weight of 2.40 has high effectiveness. Also, the forward scenario showed that reforming the organizational structure will lead to the perceived reputation of the hospital, and in the backward scenario, in order to achieve hospital waste management, first attention should be paid to the construction of the green hospital building.

According to the results of the research, it is suggested to pay special attention to the incentive to reform the organizational structure in hospitals. Because it provides stability in the supply chain and services of the hospital, and the result is creating a positive image of the hospital. Also, with the construction of the green hospital building, the hospital waste management system will be improved.

The perishable food supply chain is a critical system that includes the production, processing, distribution and consumption of food and ensures the availability and access to food for the population. Today, the complexities of the business environment, uncertainty and environmental fluctuations have made the supply chain vulnerable to various types of challenges. The aim of this research is to identify and prioritize the challenges of the perishable food supply chain and provide effective insights and solutions to reduce the impact of these challenges.The current research is Qualitative and Quantitative . Fuzzy Delphi method and Ordinal Priority Approach (OPA) were used for data analysis. At first, 18 challenges of the perishable food supply chain were extracted by reviewing the research literature in reliable scientific databases, then the final 13 challenges were selected using the fuzzy Delphi method. In the following, by preparing a questionnaire and experts' opinions, the challenge of the perishable food supply chain was ranked using the OPA method. The statistical population of the research is made up of academic experts, managers of the agricultural jihad and the food and drug organization of Kerman province. For this purpose, 10 people were selected as a sample using the purposeful sampling method. By prioritizing the challenges, the first to third place was awarded to "weak demand management", "lack of regulations and government support" and "lack of product quality control". The results of this research have been obtained based on scientific texts and the opinion of domestic experts. Therefore, it can be new and comprehensive insights for organizations, experts and researchers in this field.

The Internet of Things (IoT) is considered a modern concept in the production industry, based on which the physical and digital worlds are connected using the potential of the Internet. Since this technology is new, its acceptance and implementation in the oil and gas industry are associated with barriers. Therefore, this study aims to identify and analyze such barriers.

This study has been performed with a mixed approach in two phases. The qualitative phase was conducted to identify the barriers to using the Internet of Things in the oil and gas industry, and the quantitative phase was conducted to model and analyze the scenario. To identify and extract the barriers to using IoT in the oil and gas industry, it is identified through a literature review and content analysis method. In this research, 58 articles were analyzed and 10 industrial and academic experts analysed extracted barriers by using the Fuzzy cognitive mapping method. To analyze the scenarios, two categories of backward and forward scenarios have been designed. FCMapper software has been used for scenario design.

The results of the content analysis showed 10 barriers, which are subcategories of four aspects. The barriers identified are "limited coordination and collaboration" "lack of automation in organizations", "insufficient leadership support", "weak staff knowledge and abilities", "limited scalability", "opposition to change", "lack of Certain rules and standards for the adoption of the IoT", "the cost of data storage and analysis", "the high cost of implementation and maintenance", "security and confidentiality issues". Finally, these barriers were categorized into four main subcategories: "Organizational", "Integration", "Economic" and "Technical". The results of the fuzzy cognitive mapping method indicate that the barrier "security and confidentiality issues" with a factor of 4.34 has the highest level of influence, and the barrier "high implementation and maintenance cost" with a factor of 4.95 has the highest level of influence, and the barrier "security and confidentiality issues" has the highest centrality with a coefficient of 6.45.

Like any other research, this research has been faced with limitations. Considering that the research was limited to a specific industry, its findings may be affected by the opinions and biases of experts involved in the process, and we cannot generalize the results to another industry. Another limitation of this research is the complexity and time-consuming methods used in it. The methods of content analysis and fuzzy cognitive map may be complex and require sufficient time and a high level of expertise to use them, which can limit their application in some fields.

Considering that the IOT is an emerging and new technology, the adoption of this concept in the oil and gas industry can have several operational advantages, such as reducing testing and calibration time, minimizing production downtime, improving performance, and predicting maintenance performance. One of the important barriers to the use of IoT in the oil and gas industry is "security and data confidentiality" issues in different parts, and this issue causes the unwillingness of stakeholders and decision-makers to use this technology. Conducting research in the field of raising and increasing the security of these systems and ways to increase the security of privacy will greatly help in solving this barrier.

The study offers valuable insights for researchers, managers, and policymakers in the oil and gas industry concerning the adoption of Internet of Things (IoT) technologies. To facilitate the adoption of IoT in the oil and gas industry, companies should invest in comprehensive training programs for managers and stakeholders to improve awareness and understanding of IoT technologies and their benefits.

Since several barriers have prevented the widespread adoption of the IOT in the oil and gas industry, in this research, the identification and extraction of these factors have been done comprehensively for the first time. Modelling and scenario analysis of these barriers with fuzzy cognitive mapping were also performed for the first time.

The purpose of this research was to identify and analyze the drivers of the smart sustainable circular supply chain. Twelve samples were selected by the snowball method from among industry experts in the edible oil sector. Drivers were finalized with expert opinions and analyzed using the DEMATEL and AISM methods. The results showed that organizational competence and human resource competence are the most effective drivers, while economic sustainability and environmental sustainability drivers have the highest levels of effectiveness compared to other drivers. According to the results of the research, officials in the edible oil industry should pay special attention to organizational competence to advance towards a sustainable and smart circular supply chain, as this driver has the greatest impact compared to others.