ghasem zarei

Supply chains increasingly rely on information technology and real-time updates within networks. Emerging technologies, integral to the Fourth Industrial Revolution, view the intelligent supply chain as a crucial component. Smart technology, with its unique blend of advanced features, has immense potential to transform supply chain operations from inception to performance enhancement. This fusion includes concepts such as artificial intelligence, the Internet of Things, virtual reality, augmented reality, extended reality, blockchain, and more. These intelligent technologies facilitate supply chain monitoring by tracking equipment and processes. This research aimed to design a balanced implementation strategy for smart technology in supply chain management using a descriptive approach.
 
To achieve this feat, data were collected through a purposeful and criteria-based sampling method, involving university-educated experts in business management across various marketing, strategic, and e-commerce fields. A semi-structured interview format and thematic analysis were employed to analyze the data. The qualitative section included 11 participants, based on theoretical saturation. SWOT analysis was utilized to examine the internal and external factors influencing the supply chain. Subsequently, the Analytical Hierarchy Process (AHP) was applied to rank and determine the impact of each factor based on the qualitative results.
 
The research findings identified and categorized concepts into four central criteria within a SWOT matrix: opportunity, strength, weakness, and threat, along with 28 sub-criteria. The results indicated that, among the opportunity themes, the highest priority was given to the synchronization of material, financial, and informational flow management, with a weight of 0.517. For the strength themes, ensuring transparency in the interaction among supply chain participants was the top priority, with a weight of 0.80. Within the weakness themes, the increase in costs due to the implementation of smart technology was the most significant, with a weight of 0.557. As for the threat themes, the absence of a global standard to ensure supply chain security was the primary concern, with a weight of 0.460. Consequently, these insights guided the ideation process and the development of a comprehensive strategy for managing, developing, and enhancing smart technology in supply chain management.
 
The study's findings confirm the high potential of smart technologies to optimize supply chain management. Implementing a systematic approach enables the evaluation of perspectives (advantages and challenges) and their integrated application. The development of alternative strategies stems from this systematic approach, which involves comprehensive studies of external and internal factors, their interrelationships, and the assessment of opportunities and potential threats. This paper significantly enriches the current marketing literature by demonstrating how smart technologies enhance supply chain management, addressing an issue previously overlooked in research.

In recent years, smart cities and smart tourism destinations have received wide attention due to providing effective solutions to solve the problems faced by the communities and promoting a sustainable competitive advantage from the point of view of tourism destination marketing. However, the consequences of its development on the residents from socio-cultural aspects have not been studied. The purpose of this study is to analyze the basic cultural and social functions of smart tourism development in Tabriz city. The current research is applied in terms of its purpose and descriptive survey in terms of its nature. In this research, a qualitative approach was used with the method of content analysis and using library resources and in-depth semi-structured interviews. The expert members were selected by the snowball method and theoretical saturation was obtained after interviewing 13 experts, but three more interviews were conducted for more certainty. After performing three stages of open, core and selective coding, the findings identified 19 concepts in the form of 7 sub-themes, including innovation acceptance, public value, sustainability, promotion of citizen participation, tourism co-creation, residents’ subjective well-being and new technologies ethical aspects. The results of this study can be of great help to policy-makers and managers of urban tourism destinations in order to understand and manage how its development affects people.

With the sustainable development of technology and innovation in people's travel styles, smart tourism(ST) technologies are widely used in various fields of tourism. Smart technologies, especially applications related to tourism, have changed the traditional travel experience and increased the competition of destinations. The purpose of this study is to identify the dimensions of tourists' experience of ST in Tabriz city.

In this study, a qualitative approach with a content analysis method was used. for collecting the data, while studying library resources, a field-method with an in-depth-interview technique was used to identify indicators in technological dimensions, services, psychology and new areas. The key beneficiaries of ST experience were selected by the snowball sampling method, and theoretical saturation was obtained after interviewing 18 of them. Next, MaxQuda software was used for content analysis.

The findings of the research indicate that 32 indicators in the form of 8 subcategories include personalized services (5-indicators), access (3-indicators), awareness (4-indicators), interaction (3-indicators), security and privacy private (4-indicators), technological developments (6-indicators), co-creation (3-indicators) and psychological aspects (4-indicators), form the experience dimentions of ST. This results confirmed that tourists get a richer experience when using smart technologies, which can affect their overall satisfaction with their trip and their behavioral tendencies in the future.

The results have provided valuable information and suggestions for the management of urban tourism destinations that are concerned about the development of ST in their city which can provides a clear view of what they should pay attention to.

The production of horticultural products is faced with environmental stress; and heavy damages are caused to the products every year. The use of shade/net houses to reduce stress and to increase the quantity and quality of the product have been significantly developed in the last few years. Although after the columns, screens of the shade/net houses are the most important part of such protected agriculture, there is not much information about their behavior under the loads. The purpose of this article is to investigate and analyze the behavior of screens when different loads are applied to them. In this research, the samples of shade/net houses implemented in the country were examined. The stress analysis and calculation of the displacement of the screens according to the way of installation and operation, the snow load and the shape of their snow removal were done using SolidWorks software. The results showed that with the arrangement of the distance between the cenotes and the width used for the nets, the maximum allowable snow load is 40-52.5 kg/m2. It was also found that changing the distances of the columns and the width of the corridors could have a direct role in the stability of the structure while reducing the accumulation of snow, so that according to the load of the area, the distance between the columns could be adjusted in such a way that it was possible to strain with less stress in the screen and the screen could be loaded. Having no significant differences, the economic aspect can play a decisive role in the selection of column distances. This issue (changing the width of the columns) can be considered as an advantage in screens of shade/net houses. Also, the calculations showed that the conditions of yielding in the nets were strongly affected by the change of location in them. In other words, by choosing the appropriate distance between the columns in the row of the corridor and the possibility of creating more rise in the screens, the bearing capacity would increase, but it should be noted that the loading surface is wider and the screens of shade/net houses must bear more snow load.

In recent years, there has been an awareness of AI's ability to revolutionize traditional approaches to environmental protection, social equity, and economic development. Artificial intelligence has the potential to revolutionize the way of negotiation, regulation and implementation of contracts, nowadays the digital smart contract effectively replaces the traditional forms of paper contracts, so it can be imagined positive and negative consequences and effects for it, and on the other hand, it has also undergone many changes in legal rules and laws, so the purpose of this study is to identify the positive and negative consequences and effects of using artificial intelligence in commercial contracts from The perspective of commerce and tourism, and on the other hand, the study of its legal consequences. In terms of applied purpose, based on the nature of the data, the present study is qualitative and based on the data collection methods, it is a secondary study that was conducted using the seven-step meta-synthesis method of Sandlewski and Barroso (2007) through a systematic review of the literature and documentary records and open, axial and selective coding using MaxQDA2020 software. By arranging documents by open coding, finally 45 indicators were identified that using categorization or axial coding, related and conceptually homogeneous codes were merged with each other and new categories were formed, and as a result, 31 codes were categorized in the themes of positive consequences and negative consequences from the point of view of business, tourism consequences, and also legal consequences. The consequences of using artificial intelligence technology in business contracts with the tourism aspect include 7 indicators. The positive consequences of using artificial intelligence in business contracts with a commercial aspect can be categorized into 14 indicators, and its negative consequences include 4 indicators, and 4 legal consequences have been identified for this phenomenon.

Digital entrepreneurship is acknowledged as a novel concept in the business world, which pertains to utilizing opportunities provided by the internet, mobile technology, and new media. The primary goal of this investigation is to develop a digital entrepreneurship model that is tailored to the needs of women who operate home-based businesses. This research is applied in terms of purpose, qualitative in methodology, and employs the grounded theory approach of Strauss and Corbin. It is exploratory in nature. The statistical population of the research includes university professors and entrepreneurs who have established home-based businesses through social media and digital platforms and have over 5 years of work experience. In this study, purposive sampling and snowball sampling procedures were implemented. In-depth and semi-structured interviews were conducted with 14 individuals until theoretical saturation was attained. This was the data collection tool. Maxqda software was employed to analyze the interview transcripts, utilizing coding techniques and both manifest and latent content analysis. This process ultimately resulted in the presentation of a paradigmatic model.The findings indicate that entrepreneurial empowerment, technology, and individual factors serve as causal conditions, while opportunities, infrastructure, individual knowledge, and content serve as contextual factors. Internal factors and effective communication function as intervening conditions for digital entrepreneurship in home-based businesses. Proposed strategies include the potential of online advertising, specialized leadership and management, digital laws and regulations, and digital marketing strategies. The implementation of these strategies leads to the establishment of transnational networks, the creation of job value for women, and improved economic performance.

The current research was purposed to investigate the representation of gender roles in cultural branding with emphasis on women role from cultural psychology perspective. The research universal enfolded all studies and texts concerning the representation of gender roles in cultural branding. The sample encompassed texts related to women role from cultural psychology perspective. The research method was descriptive analytical. To collect data library procedure via note taking on index cards from published references and studies on psychology and women purview and cultural researches was processed. The data was analyzed by implementing content analysis. The results indicated that brands should avoid using traditional gender stereotypes that portray women as passive beings or mere symbols of attractiveness. Instead, brands should depict women as capable and independent individuals with human and cultural characteristics. This representation not only helps enhance brand credibility and strengthen consumer connections but can also promote gender inclusivity and equality in society.  Based on cultural and religious teachings, particularly in Islamic societies, women hold important roles not only within the family but also in social and economic spheres. Therefore, cultural branding must take cultural and religious sensitivities into account and pay special attention to highlighting the abilities and potentials of women in its representations. The brands that value human dignity, inclusivity, and gender equality can strengthen the social position of women and prevent the promotion of negative stereotypes. This research emphasizes the necessity of designing marketing strategies that align with cultural and religious values, which can help create positive and sustainable social identities.

In horticulture, to control biotic and abiotic stresses in a protected environment, the use of shade/net house or anti hail-net house can be a cost-effective solution. Unlike a greenhouse, a shade/net house is designed for non-extreme loads. In addition, the method of applying loads as a key point should be considered in the design of the structure. Therefore, the design of columns is a controversial issue considering the moments caused by wind load. These bending and twisting moments in the columns are created due to the imbalance of the wind load on the mesh. The columns cross-section used in shade/net structures have a direct effect on its strength, under different loads. Hence, stress analysis of columns with rectangular cross-section, C and U (sine) channels are considered for comparison. All these analyses were calculated and performed by SolidWorks software. This stress analysis was also performed for the mentioned columns sections that were placed next to each other in a double form. The results of the stress analysis of single columns showed that in front loading, the column with sinusoidal U section had more strength than that the columns with two other sections. It also had less deflection. In lateral loading, less stress was calculated for the sinusoidal U section. In terms of torsional load, the column with a rectangular cross-section performed better and had a much smaller angular deviation than the sinusoidal U-shaped and C-channel columns. In general, it can be concluded that in the mentioned single columns, the performance of the U-shaped section is more acceptable. The results of the loading and analysis of three types of double columns showed that the strength of the sinusoidal profile with a U-shaped cross-section was higher than that of rectangular tube and C channel. Also, the deflection created was less than that the other two types of columns. In lateral loading, the stress analysis showed that the sinusoidal U-section column had more strength and also had less deflection. In torsional loading, the double rectangular tube column had more strength and less deflection than that the other two sections. Finally, based on the stress analysis results, it was clarified that the double sinusoidal U-cross-section had more strength and successfully could be chosen in shade/net house infrastructures.

This article aimed to examine the impacts of acceptance factors for conversational assistants on customer attitudes and brand engagement, while also considering the moderating role of perceived risk. The study adopted a positivist paradigm, employed a comparative research strategy, and utilized a cross-sectional design. It was applied in purpose and descriptive in method. The target population comprised customers of banks in Isfahan with a minimum sample size of 396 determined using G-Power software; however, to enhance accuracy, a sample of 400 participants was selected. Data were collected using a standardized questionnaire. Validity was assessed through content validity based on expert opinions, as well as convergent and divergent validity. Reliability was evaluated using Cronbach's alpha, omega coefficient, and composite reliability. Descriptive statistics were computed using SPSS version 25, while Structural Equation Modeling (SEM) was performed using Smart PLS 3.0 to evaluate model fit and test hypotheses. Results indicated that perceived ease of use, perceived usefulness, perceived pleasure, and perceived trust significantly and positively influenced customer attitudes and brand engagement. Additionally, perceived risk moderated the relationship between customer attitude and brand engagement. If conversational marketing is effectively implemented in banking, and if conversational assistants are embraced by customers, this will foster a positive attitude and enhance customer engagement with the brand. Therefore, the banking industry should prioritize the development of appealing conversational assistants to provide optimal experiences and services that meet customer needs in a timely manner.

foreign products with the moderating role of product characteristics. This research is practical in terms of purpose and survey in terms of nature and method. The statistical population of the research includes consumers of foreign products in the city of Ardabil, due to the unlimited statistical population, the sample size was estimated to be 384 people, of which 288 people were able to complete the questionnaire. As mentioned, the data collection tool is a questionnaire that was distributed face-to-face. Structural equation modeling and confirmatory factor analysis, and SPSS and LISREL software were used to analyze the data. It is worth mentioning that the research results showed that nationalism has a positive and significant effect on consumer hostility. In addition, the negative and significant relationship between consumer hostility and consumption behavior of foreign products was also confirmed. Finally, it should be noted that although trust does not have a moderating role in the relationship between consumer hostility and consumption behavior of foreign products, perceived quality and perceived price (cost) play a moderating role in the relationship between consumer hostility and consumption behavior of foreign products.

Today, consumer behavior analysis is one of the most important issues in marketing. Therefore, the correct understanding of consumer behavior is considered as the success factor of companies. researches have shown that people do not always behave in a functional way in their interactions with companies, and various factors make them perceive different tensions, which can cause changes in consumer behavior and create problems for companies. Therefore, the aim of the current research is to identify the types of Consumers' Tension-Indusing Behaviors. In this research, the meta-synthesis qualitative method based on the seven stages of Sandelowski and Barroso was used. The population studied included 117 sources in valid databases, among which, based on the critical assessment skills program and the screening process, 33 sources were selected as the final sources for further review and analysis, and finally, 68 codes were identified and They were classified in 10 concepts and 2 categories. The findings show that the category of consumer's internal tension-indusing behaviors includes concepts; Consumer interpersonal tensions with employees, consumer interpersonal tensions with other consumers, company-related consumer tensions, brand-related consumer tensions, and product-related consumer tensions. the category of external consumer tension-indusing behaviors includes concepts; voice of the consumer, consumer's passive confrontation, consumer's retaliation, consumer's misbehavior and destructive consumer's behavior. The results of this research help different companies to know the types of tension-indusing and negative behaviors of consumers and it is necessary to manage such behaviors correctly in order to succeed in the field of competition and implement marketing strategies.

In the article titled “The Effect of Magnetic Therapy on Postoperative Urinary Retention in Patients Undergoing Surgery: A Randomized Clinical Trial”, published on pages 417-23, Issue 4, Volume 29 of Iranian Journal of Nursing and Midwifery Research,[1] the name of the “Mohammad sadegh Aboutalebi” author is written incorrectly as “Mohammad Sadegh Abotalebi” instead of “Mohammad sadegh Aboutalebi”.The “How to cite this article” section should read correctly as “Zarei G, Mosleh S, Zare S, Aboutalebi MS. The effect of magnetic therapy on postoperative urinary retention in patients undergoing surgery: A randomized clinical trial. Iran J Nurs Midwifery Res 2024;29:417-23.”

A dividend is considered to represent the company's financial commitment to shareholders to pay a part of their investment returns, which requires the use of appropriate policies and the identification of factors affecting it in order to manage future cash flows for the company. Various studies have been conducted that have introduced various factors affecting the dividend policy, such as capital structure, agency cost, accounting reporting, and the effective tax rate, but the results have been contradictory and scattered. For this purpose, conducting comprehensive research with a meta-analysis approach regarding determining the importance of each of the effective factors on the dividend policy in order to achieve a general summary and resolve the contradictions and dispersion of the results seems necessary. To review the previous research, first, the desired variables were determined, and then the necessary information was collected for 196 studies until 2021. Based on systematic elimination sampling, the number of remaining studies that had the necessary characteristics to enter the meta-analysis process was equal to 123 studies. We coded and entered the extracted data into CMA2 statistical software. The effect size was calculated, and the homogeneity and heterogeneity of the effect size were evaluated. The results of this study showed that the factors of corporate governance mechanism and agency cost did not affect the company's dividend policy. However, the positive effect of free cash flow factors, profitability ratios, quality of financial reporting, effective tax rate, capital structure, institutional investors, information asymmetry, ability of managers, and concentration of ownership in dividend policy was confirmed.

To gain and maintain stable competitive advantages, hospitals are currently seeking novel strategies for Patient Satisfaction Development (PSD). To this end, hospitals are required to establish strategies for improvement and provide basic platforms; one of these strategies is Internal Marketing (IM). This type of marketing typically demands customer-oriented behavior and thinking by all hospital staff in terms of dealing with patients. Accordingly, the current research recommends a simulation pattern for PSD within hospitals in Ardabil Province, Iran, considering the predominant factors affecting IM.

This study, utilizing a qualitative-quantitative research design, was conducted on a statistical population of 17 theoretical (the university professors) and experimental (hospital managers) experts. The sampling technique was of the non-probability type and purposive, and the data collection tools were interviews and questionnaires. In the qualitative phase, the main themes and sub-themes of IM in the hospitals of Ardabil Province, Iran, were initially identified by thematic analysis. Then, in the quantitative phase, the major factors were prioritized via the fuzzy Delphi method, and finally, the effects of IM on PSD were simulated through agent-based modeling. Data analysis in the qualitative phase was done with MaxQDA 20 software, and Microsoft Excel and AnyLogic 8.9 were operated in the quantitative one.

Based on the study results, 35 primary codes, 12 sub-themes, and three main themes (organizational, occupational, and individual) were obtained. In light of this, the organizational factors were introduced as the most effective ones. Besides, the study results suggested that the PSD prospect in the hospitals of Ardabil Province, Iran, reached 70 % at the end of the simulation.

According to the study results, it is suggested that hospital managers devote much attention to the effective factors in IM, specially the organizational ones, as they play a leading role in PSD.

Because of modernization, local and national identities getting deformed and Have been lost their originality. Tabriz Bazaar which is considered as registered historical building never been out of this risks and there should be contextualist consideration in its designing and its improvement. The question that can be asked is what effect this kind of attention, ie contextualism, has on the Tabriz Bazar’s brand equity. This research has been done with a mixed method approach with a sequential exploratory scheme (first a qualitative method and then a quantitative method). In the first stage, experts were interviewed to extract the contextualist model of traditional commercial spaces, which did not exist before, and the data obtained from interviews with experts were evaluated using thematic analysis. The results of this analysis showed the pattern of contextualization of traditional commercial spaces. Then, after compiling the contextual questions in the form of a questionnaire, the complete questionnaire - which included the contextual questions and brand equity - was distributed and collected among 374 tourists in Tabriz Bazar. The data were then tested using Smart-Pls software and structural equation modeling. Findings show that from the perspective of Tabriz Bazar tourists, contextualism had a positive effect on brand equity. As a result, the contextualism model obtained in the present study and the preservation of social, cultural and historical values can be used to strengthen the special value of the Tabriz Bazar brand.

Urinary retention is a postoperative problem that causes pain and discomfort for patients, even when catheters are used. The potential role of magnetic therapy in treating postoperative urinary retention through acupuncture points remains uncertain. This research aims to assess the impact of magnetic therapy on urinary retention in patients undergoing surgery.

This single‑blind clinical trial study was conducted in a recovery department within an operating room and subsequently in the Surgery Department of Amin Hospital. The study took place in Isfahan in 2022, with a sample of 64 patients selected using a simple random sampling method and divided equally into two groups. In the intervention group, magnet plates were applied, while the control group received iron plates at seven specific points for duration of 35 ± 5 minutes. Demographic information, the type of urinary excretion, the duration of urinary retention, and the volume of excreted urine were recorded using a researcher‑made checklist for both intervention and control groups. These data were compared and subjected to descriptive and analytical statistical analysis.

Among the participants (N = 64), the majority were male (N = 37, 57.80%), and the mean age was 40.17 years. The Chi‑square analysis revealed no significant difference between the intervention and control groups in terms of the type of urinary excretion (p </em>= 0.106). However, the Mann–Whitney U‑test demonstrated significant difference between the two groups regarding the duration required to eliminate urinary retention and the volume of excreted urine (F2,41 = 62 and F1,76 = 62; p </em>< 0.001).

The use of a novel approach involving magnetic therapy applied to acupuncture and reflexology points has been shown to reduce the time required for the first urination and increase the volume of urine in post‑surgery patients.

 Sustainable marketing harnesses the power of social media as a technology tool, facilitating direct interactions between consumers and the potential influence on their beliefs and behavior. Influencers generate both organic and sponsored content across social media platforms. Despite the significance of sustainable marketing in production and consumption, this study seeks to enrich the existing academic discourse on the subject. By delving into a more intricate analysis and accurate examination, the research will focus on sustainable marketing within the social media environment, particularly through influencers. Sustainable marketing is emphasized as a process that involves sharing information about products and services, their applications, and fostering mindset transformations among consumers. The primary objective of this study is to propose a model for sustainable marketing by leveraging the influence of social media. This research aims to address the question of how social media influencers impact sustainable marketing. Consequently, the study seeks to offer a descriptive model that effectively utilizes influencer-based marketing within the context of social media. The research approach adopted for the study is qualitative, employing the theoretic method, and drawing upon Strauss and Corbin's database or the grounded theory approach. The research's statistical population includes experts in the fields of marketing management, sustainable marketing, social media, and influencers.In the context of this research, a series of interviews were conducted with a total of 13 experts and marketers specializing in sustainability and social media as well as influencers. The process of conducting these interviews continued until theoretical saturation was achievable, focusing on the development of a sustainable marketing model grounded in influencer-based strategies within the realm of social media. The main objective of these interviews was to identify the primary factors that underpin sustainable marketing influenced by influencers operating on social media platforms. The research employed the systematic methodology developed by Strauss and Corbin for its data analysis. This approach consists of three major phases: open coding, central coding, and selective coding.To ascertain the credibility of the interview utilizing the intra-subject agreement or two-coders method, an expert who possessed comprehensive knowledge in rapport with the subject matter of this research was enlisted as a research partner, functioning as a coder. To construct a paradigmatic model, as the ultimate objective of the grounded theory method, which is based on Strauss and Corbin's approach, it is necessary to analyze three consecutive levels of conditions, interactions, and consequences. These levels encompass causal factors, background conditions, and intervening variables. Through the data analysis process, three primary categories, seven subcategories, and 35 concepts, or open codes, emerged as key elements within the causal factors of the sustainable marketing model based on social media influencers. The principal categories of causal factors were identified as content competences, interaction competences, and influencing capabilities.Based on the analysis of the collected data, two main categories, four subcategories, and 21 concepts, or open codes, were delineated as the key elements constituting the background conditions of the sustainable marketing model grounded in social media influencers. Analyzing the data yielded two primary categories for the intervening factors of the sustainable marketing model grounded in social media influencers: (1) influencers' prominence and (2) social solidarity. This analysis resulted in the identification of 2 main categories, 4 subcategories, and 23 concepts or open codes.The primary categories of interfering conditions for the sustainable marketing model based on influencers in social media are identified as (1) influencers' personal branding and (2) restrictions in controlling the content they exhibit or advertise, particularly within social media contexts.The analysis of the data led to the identification of two primary categories, four subcategories, and 29 concepts or open codes, constituting the strategies of the sustainable marketing model grounded in social media influencers. Based on the analysis of data, the sustainable marketing model, reliant on influencers in the social media paradigm, was found to incorporate two principal strategies: marketing mix reorientation and online networking. In terms of the consequences of this model, three main categories were identified through this analysis: creating self-sustaining forces, inclusive value creation, and a sustainable identity. Within these main categories, 7 subcategories and 39 concepts or open codes were distinguished.As per the findings, a sustainable marketing paradigm model grounded in influencers on social media has been presented, which comprises the following categories: (1) causal conditions encompassing content competencies, interaction competences, and the potential to sway opinions; (2) background conditions, i.e. the authority of influencers and their social networks; (3) intervening conditions that encompass the influencers' personal branding and the constraints in handling the content they showcase; (4) strategies, which are twofold and entail marketing mix reorientation and online networking; finally, the outcomes of this model were divided into three categories, namely (1) cultivating self-sustaining forces

Newsjacking means that brands direct the wave towards themselves by reacting to a trending news story, whether it is breaking news or a planned event. This study, conducted with a qualitative approach using content analysis, investigates the effect of newsjacking on Iranian tourism brands from the perspective of marketing experts in the tourism sector. The statistical population included all marketing and content production specialists in the tourism field within the country. Ultimately, 15 experts were selected as the sample through theoretical sampling. To collect data, the interviewees observed and reviewed examples of both types of newsjacking (reaction to breaking news and planned events) published by Alibaba. They acknowledged that they are more likely to like, share, and engage with content related to breaking news.

The current research, which is practical and was conducted by Thematic analysis method and is among qualitative researches, was conducted with the aim of investigating the challenges and limitations of its use by Iranian tourism businesses. The statistical population was all marketing specialists, content production, activists and business owners in the field of tourism; 8 of these experts were selected through theoretical sampling and agreed to participate in the research. The data collection tool was in-depth interviews, the total duration of which varied from 50 to 70 minutes for each person, which were analyzed through open, central, and selective coding, and the research model was presented. Findings in the form of challenges and limitations related to: 1) the nature of newsjacking itself, 2) newsjacking in Iranian tourism, 3) external limitations of tourism businesses, 4) internal limitations of tourism businesses, 5) Challenges related to audience reaction were set.

The science of knowing the environmental conditions to build greenhouses in suitable climatic locations is one of the most important studies in the field of greenhouse construction and maintenance. After all, by obtaining information about environmental factors, especially temperature, it is possible to choose the most suitable place for the construction of these structures, which requires a spatial study of the studied areas. Spatial investigations require the existence of rich and integrated data, but due to many limitations it is not possible to collect information at all points; therefore, information is only collected in areas that are more sensitive or generally represent a broad area. As a result, it is never possible to study an area continuously, because to conduct such studies we need an infinite collection of data. The solution available to solve this problem is the use of geostatistical software and Geographic Information Systems (GIS) and interpolation methods. In the present study, for the first time in the study and evaluation of different methods for interpolating the heat demand index for heating and cooling greenhouses, the most suitable methods for this purpose have been introduced. The application of the results of this research can be used not only in the greenhouse industry but also in other industries related to energy and its consumption.

Heating of greenhouses is also necessary in countries with a temperate climate in order to achieve maximum production of greenhouse products in terms of quantity and quality, as well as to increase efficiency and productivity. The heating and cooling demand for a given period was extracted and used based on the degree day index. Since information from meteorological stations is represented in the form of points, interpolation will be the basic element of information generalization for use of the selected models. Through the generalization of these properties, interpolated maps will be available, which, in addition to using these drawings for individual investigation and processing of the conditions of the region, will also be the basis for heat demand calculations. There are various methods of parameter interpolation, and five widely used categories and a total of 24 methods (with their subcategories) were evaluated and reviewed in this study. These categories are Inverse Distance Weighting (IDW), Global polynomial interpolation (GPI), Local polynomial interpolation (LPI), Radial basis function (RBF) and Kriging methods.

To evaluate the best interpolation method, available data was analyzed and validated for use in zone models. This information was used in 162 stations, which had relatively complete information for the period studied (20 years). The values of these stations for the annual heating demand data of the Iran’s greenhouses with a minimum value of zero and a maximum value of 3205 (degree days) have a skewness of 0.262 and are normally distributed. The best interpolation method for cooling and heating demand data is the IDW method. Among the potencies used in this procedure, the optimized power has the highest correlation and the best results. After that, the kriging methods and the RBF are each evaluated to interpolate the data related to the cooling and heating needs of the Iran's greenhouses. Examination of the other methods examined showed that with the GPI method, results improved by increasing the power up to the fifth order, and after has been shown decrease in correlation and an increase in error. Also with the method of the RBF, all sub-methods except TPS are in the same error range and the best result relates to the CRS method. According to the results, the best result for the LPI method relates to the exponential function, while other methods are in the same error range and in the next higher order. In general, the results of all three kriging methods used in this study are close to each other in the margin of error where ordinary kriging is relatively superior to other methods. Universal and Simple Kriging are also in the next ranks respectively.

Nowadays, most meteorological parameters have been studied by many researchers and they have recommended different interpolation methods for each parameter. Since the nature of the heating and cooling needs of greenhouses differs from other climatic parameters and is calculated and used cumulatively on an annual basis, for the purpose of interpolation and zoning it is necessary to determine and represent an appropriate method. In this study, by examining the types of common and widely used interpolation methods, the IDW method provided the best estimate of interpolation, after which ordinary kriging methods and RBF are placed in the next ranks.

A considerable amount of research has been conducted to explore the concept of supply chain agility as the primary management strategy for achieving a competitive edge in a constantly changing and unstable business environment. Much of this research has focused on understanding the impact of supply chain agility on performance outcomes. However, the findings from empirical studies have been scattered and, in many cases, contradictory in terms of the functional implications of supply chain agility. To address this, it is crucial to consolidate and compare the results of these experimental studies using a meta-analysis approach. Therefore, the present research aimed to examine the influence of supply chain agility on both relational and operational performance by employing a meta-analysis approach. Nineteen final studies were identified and their information was entered into the CMA2 software based on the Prism protocol. The results clearly demonstrate that supply chain agility significantly affects relational and operational performance, with a stronger influence observed on relational performance compared to operational performance. Furthermore, the analysis conducted identified the moderating variable of the type of industry, where the agility of the supply chain has a particularly strong impact on relational and operational performance within unique industries.

The development of the digital environment in most areas of business has led to an increase in deceptive practices and unconventional behaviors. With the advancement of the digital environment, unconventional channels have emerged, leading to various risks such as life, financial, and behavioral risks affecting individuals and businesses. Marketing operations face significant challenges without the presence of the digital environment, which serves as a crucial marketing platform. Certain profit-driven individuals exploit this expansive environment for fraudulent and unethical business practices. To curb criminal activities in the marketing sector, this study aims to introduce an anti-marketing model tailored for online and digital businesses and provide practical solutions. It seeks to address the gaps in the extant literature that have remained almost untouched by researchers.
 

This research uses a qualitative, applied, and exploratory approach. The statistical population of the research includes specialists and experts in marketing, particularly in digital marketing, along with owners of established online businesses. To ensure the collection of precise and relevant data, an effort was made to employ indicators for sample selection so the experts could have closer connections and sufficient experience related to the subject under investigation. The data collection was also carried out by employing targeted sampling and semi-structured interviews. It should be noted that this research employed the opinions of 16 experts to identify factors and issues relevant to the research subject. Furthermore, the research employed a Grounded theory outlook to identify categories that influence the research subject.
 
 

The interview section provided 238 primary codes, 106 secondary codes, and 26 sub-categories in six main categories, namely: causing categories, intervening factors, background factors, the central phenomenon, strategies, and outcomes. Ultimately, employing ATLAS.ti software, “the anti-marketing model aimed at preventing criminal behaviors in the online business environment” was derived.
 

Based on the findings, it could be stated that introducing the anti-marketing model aimed at preventing criminal behaviors in the online business environment is an initial model in this field that has not caught the attention of researchers and can contribute to improving the literature on the subject. The development of the anti-marketing model aimed at preventing criminal behaviors in the online business environment has led to significant and positive outcomes that were revealed by the contents of the interviews. These outcomes include the prohibition of criminal behavior, strengthening digital marketing, promoting moral integrity online, strengthening the legal framework for online transactions, strengthening a positive culture in the online environment, and strengthening the digital community. Additionally, the study's findings offer recommendations for preventing criminal behavior in the online and digital business environment.

Impulse buying behavior is a significant aspect of customer behavior and a crucial concept in the retail environment. Currently, this behavior has garnered the attention of retailers and wholesalers, particularly chain stores, as it substantially impacts their sales and profits. To address this, retailers can design a pleasant and relaxing atmosphere for customers, providing a soothing and attractive environment to evoke their feelings and perceived pleasure. The primary purpose of this research was to examine the model of situational factors influencing customer’s impulse buying behavior. The study's statistical population comprised all customers of Shahrvand chain stores in Tehran. Using Morgan's table, a sample size of 384 individuals was selected through stratified random sampling. A standard questionnaire was employed to measure the variables and the instrument's diagnostic, convergent, and divergent validity, as well as its reliability using Cronbach's alpha coefficient, were evaluated. The research model was tested using the Partial Least Squares (PLS) method and the Smart-PLS 3 software. The results of data analysis indicated that physical factors, including music, lighting, and color, had a significant effect on the consumers’ emotional responses, while the layout effect was not confirmed. The significant influences of social factors, including the seller and the crowd, on the consumers’ emotional responses were also confirmed. The mediating role of consumer's emotional response in the impacts of physical (excluding layout) and social factors on impulse buying behavior was supported. However, demographic factors (gender, age, and income), psychological factors (stimulation and self-esteem), and situational factors (available money and time) did not have a moderating role in the relationship between the consumers’ emotional responses and impulse buying behaviors..

Effective decision-making and management in the field of sustainable development of natural resources require access to accurate and up-to-date climatic information. This information enables the examination of the role of climate change in various issues and the formulation of effective management strategies accordingly. In this context, temperature as one of the most important climatic indicators plays a key role in environmental analyses and research. Given the fundamental role of temperature in various situations, access to precise and comprehensive temperature data is of high importance. Such data should be sufficiently detailed to provide a clear and complete picture of temperature patterns over time. Unfortunately, climatic data often faces problems such as statistical discontinuities and measurement errors, which can lead to incorrect decisions and inefficient planning. In this research, statistical methods have been employed to analyze existing temperature data and their statistical discontinuities. These methods include geographical coordinates (graphical), normal ratio, weighted correlation coefficient, and arithmetic mean, which are well-established and widely used in completing climatic data. Selecting the most appropriate method from among these can enhance the accuracy of temperature data estimation and play a pivotal role in decisions based on more comprehensive and reliable data. The objective of this research is to identify the optimal methodology for estimating data and addressing statistical discontinuities. This will assist researchers, managers, and policymakers in the field of sustainable development and in better understanding climatic conditions, enabling them to make more informed and effective decisions.

In order to address the statistical gap, a number of well-known and popular classical statistical methods were evaluated for estimating Iran temperature data. These included geographical coordinates, normal ratio, weighted correlation coefficient, and arithmetic mean. In order to determine the best method for completing missing information, data from 125 stations with complete information (without any missing data) over 21 years (2000 to 2020) were used. Given the extensive and time-consuming nature of the calculations, a random selection of 10% of the stations with an appropriate spatial distribution was employed to carry out the data filling operations. The information of the selected stations was removed at each stage separately and reconstructed based on their five nearest stations. To evaluate the aforementioned methods, statistical evaluation criteria such as R-squared (R2), root mean square error (RMSE), and mean absolute deviation (MAD) were used.

The results of the analysis of computational values through the normal ratio method were evaluated against observational values. It was found that all the stations under study exhibited a high correlation, indicating the acceptability of the normal ratio method to data estimation. The average values obtained from the evaluation of results indicate that the methods of normal ratio, weighted correlation coefficient, geographical coordinates, and arithmetic mean are prioritized in order, with RMSE values of 3.05, 3.28, 3.30, and 3.51 degrees Celsius, respectively. Consequently, the normal ratio method is the most suitable among the other studied methods and can be employed to address issues such as a lack of information, existing data errors, and also the expansion of the study period.

Among the methods reviewed, the normal ratio method is generally more acceptable and of higher quality than the other methods and is recommended for use in future research within similar study ranges. In subsequent ranks, the methods of geographical coordinates, weighted correlation, and arithmetic mean are placed, respectively. It is notable that, although the other methods are considered of secondary importance, they nevertheless demonstrate satisfactory efficacy in certain locations. Consequently, under varying circumstances, a range of methods may be employed to address data deficiencies, and the optimal approach should be selected and utilized in accordance with the specific study area.

Since the emergence of the concept of supply chain agility as the primary management asset for gaining a competitive edge in the dynamic and uncertain business environment, extensive studies have been conducted in this area. A significant portion of this studies has focused on the impact of supply chain agility on financial performance. Analysis of empirical studies reveals that the influence of a strategic asset like supply chain agility is varied across different studies, often yielding contradictory results. Therefore, it is imperative to aggregate and compare the findings of experimental studies using a meta-analysis approach. Consequently, the current research was undertaken to investigate the impact of supply chain agility on financial performance, employing a meta-analysis approach and examining the moderating role of industry type. In this study, 18 final studies were identified in accordance with the PRISMA protocol and their data was inputted into the CMA2 software. The results of the meta-analysis demonstrated that supply chain agility does indeed affect financial performance. Furthermore, the analysis of moderator variables revealed that supply chain agility has a more pronounced effect on financial performance in single industries.