Specialists believe that organizational actors use both formal and informal collaborations to achieve their goals. Although informal relations have been caused restrictions in organization efficiency, but recognition and proper management of these relations could be useful in organizational workflow. Natural Resources Organization of Hormozgan Province, in spite of usual inefficiencies such as lack of sufficient experienced human resources, totally has been successful until now. This research was done in order to delineate and analysis the formal and informal relationship networks between the staffs of this organization and also to answer to these questions: whether informal relations of this organization form a network? Whether this network has positive impacts on formal relations or negative? Is formal relationship network similar to existing organizational chart? In this regard, Network Analysis Approach, UCINET and NetDraw softwares, and input and output degree centralities and betweenness centrality were used. Results showed that informal relations of this organization form a network and its strengths caused to positive impacts on formal relations.Also formal relationship network, more and less, is similar to existing organizational chart. Finally, it is concluded that network analysis as a new approach in managerial problem solving could be so helpful for managers in recognition of effective actors in formal and informal relationship networks and also to increase the human resource efficiency.

Purpose: The purpose of this applied research is to study the effectiveness of gamification on corporate training.  Methodology: A gamified course was designed and implemented to train the location of Fire Hosing Cabinet for 24 employees of a firefighting maintenance company in Iran Mall shopping Center in Tehran. Using a quantitative quasi-experimental research plan (post-test only control group design) the participants of the study were randomly assigned to treatment (12) and control (12) groups and trained for a week.  Conclusion: The descriptive and interpretive result of the posttest analyses indicated the effectiveness of gamification of the training performed for the employees of the firefighting maintenance company in Iran Mall shopping Center in Tehran. Moreover, the descriptive result of Gamification Acceptance Questionnaire answered by the members of the experimental group after gamified training indicated that all the participants in the experimental group were satisfied with the gamified training course.

The central issue of the present paper is the study of the causes of the mother tongue decline in the Sahne city in Kermanshah province. The issue of language is beyond the dialect of people and is refer to the form of life and the matter of macroeconomic and political relations. From this perspective, the form of life and the language associated with it explain the praxis of the members of the society. The appropriate method of examining the problem should be able to analyze the justification of agents to their situation, that is why Grounded Theory is chosen as the method of this research and data analysis is taken from abduction reasoning. The results of the analysis introduced the categories of globalizing, modernizing, de-use of language, economic necessity and the government as the most important factors of local language fading. In this essay the meaning of globalization is the globalizing of special type of economic relation that explain other categories role in the process of fading of languages.

A B S T R A C TFor choosing suitable place multiple methods are introduced, which examine the qualities, methods and patterns of location selection. The current methods use global approach and do not pay attention to spatial differences, environmental variation in variables, local changes modeled by local weighting indicators. It has been selected as a case study to evaluate the EMS center of Fars province and to evaluate the indicators of distance from the power plant, distance from logistics centers, industries, transportation terminals, hospitals, hotels and tourism, cities, rural areas and custom centers. has been used, using the AHP method to weight the qualities, and then for local weights, non-overlapping neighborhood filtering within a radius of 25 km are used and calculate the corresponding changes, quantity, ratio Presented in this article, the obtained weights, then the compute local weighted layers, and then local weight was multiplied in the normalized layers and the final layer were obtained. In the next step, it was combined and calculated to compare the data using the global method. The results of the two methods were transferred to the points of the EMS and the results were analyzedExtended AbstractIntroductionIn geographical studies and spatial planning, there are different approaches to choosing the right place for all kinds of applications and uses, and a process is followed to choose the best places. This process includes stating the research problem (cognition), choosing the criteria and preferences of decision makers and how to determine the weight of indicators, combining criteria (design) and finally, choosing the best option. In the current methods of spatial decision, the criteria are given a fixed weight, while in geographical locations, the distribution of geographical phenomena is not uniform. In this case, attention should be paid to the spatial distribution pattern of geographical phenomena based on the principle of sensitivity of the range of changes, the size of the range of changes affects the outputs, and the data with a smaller range of changes also have a lesser effect on the output. The data with a larger range of changes will have a more significant effect on the output. Therefore, in spatial analysis, indicators that have small changes are less important. Local models have been presented to model local changes in spatial multi-criteria decision-making; in this research, the main issue is how to model the local changes that affect the expected outputs. MethodologyThe research process is based on multi-criteria spatial decision-making methods (national and local). First, spatial patterns of indicators were analyzed through exploratory analyzes of ESDA spatial data. Then based on the review of the research criteria, the direct weighting method was used to calculate the weight of the indicators, and the experts were asked to specify the weight of the criteria in the range of 1 to 10. The opinions were combined, and the final weight was obtained. First, the data were spatially modelled to model and calculate the local weights. Then Block Statistics spatial filter without overlap was used to determine the neighborhood. The range of local changes, maximum and minimum values, were calculated, and local weights were obtained based on that. Finally, the information layers were descaled. After that, the unscaled criterion layers were multiplied by the national weights and the final national scores were obtained. In the next step, the data of the evaluated information layers (local and national) were transferred to the points of emergency databases. Based on the analysis, the fit was done. Results and discussionGeneral or global weights pay attention to the relative importance of indicators, which is the starting point for calculating local weights. Based on the research results, the most critical indicators are industries, cities and hospitals, which are more important in the location of road emergency stations. However, in order to achieve better results, it is necessary to build a local weight layer. The results of the research show that the indicators' weight and the difference in the criteria (general weight) are not equal in the entire geographical area, and the areas with a larger range of changes have a higher coefficient.Because, unlike general weights that are obtained based on different methods, local weights are estimated based on the principle of sensitivity of the range of changes and are changed spatially, and a fixed value is not considered for all areas. According to the research findings, the highest level in the general and local evaluation method corresponds to 0.5 to 0.7. Based on the local (geographic) weight method, it is less than the national or general method in the range of 0.9 to 1. Furthermore, this is due to the more precise nature of this method, which models the effects of local changes. To evaluate the compliance of the emergency centers with the final maps of suitability assessment, the information on the suitability maps was transferred to the map of the emergency center points of Fars province. Based on the evaluation of 207 emergency stations, according to the general method, 14 percent are in the high group (0.9-1), and according to the local or geographical method (16.9), percent are in this group. ConclusionAt the level of space and geographical regions, phenomena and geographical complications are not uniformly distributed, some phenomena have a homogeneous distribution, and some have a heterogeneous distribution. On the one hand, the phenomena and decision issues are affected by the context in which they are formed and evolve; on the other hand, these phenomena are placed in the network of mutual relations. Furthermore, the results of the set of phenomena may differ from the results of the phenomena individually and separately; in this article, an attempt has been made to address the issue that in spatial analysis and planning, it is necessary to pay attention to geographical differences in decision-making. Furthermore, it should not be evaluated in general terms of spatial decision problems; one of the methods of modelling these differences and spatial changes is to consider the local weight of the criteria. Based on the research findings, local (geographical) and national analysis results are different and can better show these changes. On the other hand, the pattern of spatial differences also has its spatial pattern, and paying attention to these differences in spatial differences can be the subject of further studies. FundingThere is no funding support. Authors’ ContributionAuthors contributed equally to the conceptualization and writing of the article. All of the authors approved the content of the manuscript and agreed on all aspects of the work declaration of competing interest none. Conflict of InterestAuthors declared no conflict of interest. Acknowledgments We are grateful to all the scientific consultants of this paper.

Purpose: The present study aims to identify and explain the futures of Iranian provinces in the competition for the development of NBIC technological convergence (synergy between nanotechnology, biotechnology, information technology and cognitive sciences) with a focus on Yazd province. Method: This research, which has been conducted with a qualitative and descriptive approach, is classified as an exploratory futures-study. In this way, the relevant research records were first reviewed to compile a list of drivers in the development of convergent technologies. The list was then refined and prioritized to identify two key drivers, with the Delphi process attended by fourteen experts. By intersecting the uncertainties of these two drivers, four scenarios of the province's future in technological convergence competition emerged. Findings: The two key drivers affecting the success of the province in the competition for convergent technologies are: the rate of development of the innovation ecosystem and the amount of financial resources allocated to this process. Based on this, four scenarios of the future situation of the province in this field were identified, which have been named as "Vanguard", "Buyer", "Remnant" and "Hired". Conclusion: In order for the provinces to be able to succeed in the forthcoming competitions in the production and operation of convergent technologies, it is necessary to plan for strengthening the ecosystem infrastructure from now; at the same time, it is necessary to make efficient efforts to provide sufficient financial resources for the research and commercialization of these technologies.

The ability of plant communities in natural ecosystems to modify temperature has become increasingly important due to the profound impacts of global climate change, particularly in arid regions. However, previous studies have provided limited information on the long-term temperature feedback of these plant communities and the biotic drivers behind these changes. This study aimed to determine the functional traits and types of plant communities as biotic drivers of land surface temperature (LST) at the plant community scale, with a focus on identifying co-functioning communities in the Sirjan region of Kerman Province. To achieve this, we utilized the MODIS-LST 8-day composite product at the plant community scale and measured functional traits of dominant species through field operations. The results revealed that leaf dry matter content (LDMC), maximum height (MH), and leaf width (LW) traits significantly reduce LST. Additionally, cluster analysis indicated that the plant communities in the study area can be classified into five functional groups, which fall into two co-function categories. The S-strategized co-function (e.g., 26 communities), characterized by high LDMC values and a combination of abrupt and trend feedback in LST, was found to be more effective than the R-strategized co-function (e.g., 13 communities), which exhibited only trend feedback. Therefore, it can be argued that extreme temperatures, as a global concern, can be mitigated through careful selection of vegetation based on functional traits and strategies. This approach, particularly through rangeland improvement practices using species such as Astragalus spachianus, Cornulaca monacantha, and Launaea acanthodes, could play a significant role in addressing this challenge.

Objective: People who have higher social health can more successfully deal with the challenges and ups and downs of playing key social roles and participate more in collective activities and prevent social deviations and anomalies. In this regard, foresight and the development of a forward-looking strategy model by the media can play an important role in promoting the social health of their audience (individuals).Method: This research has been done qualitatively and quantitatively. In the qualitative phase, content analysis and Q methods were used, and in the quantitative phase, factor analysis was used to analyze the Q method data.Results: The content analysis of the media in this study showed that the most media production in the field of social deviations with 576 cases and the lowest media production in the field of violence with 237 cases. The field of social quality with 485 and the field of social issues with 312 cases are in the second and third ranks. A small questionnaire was made and based on it, the desired model was designed using PLS software. Conclusion: This model showed that the function of media is effective in promoting social health of society and can have the greatest impact on improving quality of life, reducing violence, reducing social deviations and social issues.

Raising agricultural graduates' unemployment and their inability to startup business and entrepreneurship is a crucial problem in Iran. The purpose of this study was to analyzing factors affecting agricultural graduates' business startup competencies. The statistical population consisted of all agriculture and natural resources, graduats during 2013-2016 in Mazandaran Province (N=2550), among them 364 were randomaly selected based on Cochran Formula. The research instrument used was a questionnaire.Its validity was confirmed by a panel of experts and also its reliability was estimated to be θ=0.912 using ordinal theta coeficient. In order to analyze the data, SPSSwin20 was used. The correlation tests, mann-whitney U and ordinal regression were used for data analysis. The results showed that, approximately 59 as percont of respondents ranked their business startup competencies at high and very high level. Appliying ordinal regression showed that, three variables including gender, education and character can estimate 67 percent of possibility of changing the dependent variable.

One of the weaknesses of the Staff Educational Programs (SEP) of Jihad –Agriculture Organization (JAO) is the less use of qualified and expert teachers. The purpose of this research was to investigate the factors affecting the participation of agricultural and natural resources faculty members in the SEP. This research used a quantitative paradigm through a survey and conducted in 2021. A sample of 82 out of 110 agricultural and natural resources faculty members of Urmia University was randomly selected. The research tool was a questionnaire that designed based on theory of planned behavior. The validity of the questionnaire was confirmed by 5 faculty members at Urmia University and its convergent validity was confirmed using AVE (0.52-0.73). The reliability of the questionnaire was calculated by the ordinal theta (0.71-0.90) and CR (0.81-0.95). The results showed that faculty members have a positive attitude towards SEP, but less than 10% of the faculty members have participated in pre or in-service SEP. Intention of them to educate the JAO staff is lower than the average. Based on the ordinal logistic regression analysis, faculty members' intention to participate in the SEP is influenced by the variables self-control, trust in the JAO, organizational community norms, and the experience of participating in SEP. Therefore, in order to strengthen the participation of the faculty members in the SEP, it is necessary to create a cooperation agreement between the universities and the JAO. It is also recommended that these programs should be strengthened in terms of payments for faculty member and be considered as the faculty member’s job promotion indicators.