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The purpose of this study is to simultaneously investigate a comprehensive analysis of the extent to which strategic orientations, namely, imitation and innovation orientations, and knowledge management affect firm performance.

Drawing on the theoretical frameworks of the resource-based view and dynamic capability theory, this scholarly inquiry has proposed a comprehensive framework that delineates the relationships amongst imitation, innovation, absorptive capacity (ACAP), innovation performance and financial performance. To scrutinize the proposed research model, bootstrap routines were used through Smart partial least squares to estimate the procedures. To collect the necessary data, a questionnaire and financial statements were acquired from a sample of 100 Iranian firms listed on the Tehran Stock Exchange. The findings of the study have important implications for both scholars and practitioners seeking to enhance firm performance through the effective utilization of imitation, innovation and ACAP.

The results indicate that imitation activities have directly led to the improvement in innovation performance, even in the presence of innovation and ACAP. However, the relationship has not been confirmed by financial performance.

Imitation and innovation orientations have been identified as pivotal strategic orientations that can significantly affect firm performance. As far as the authors know, this investigation represents the first comprehensive examination of both imitation and innovation activities as a critical transition in emerging markets (EMs) characterized by complex economies, such as Iran. The findings may aid firms in enhancing their performance by providing insight into the strategic importance of imitation and innovation orientations in EMs.

Given the challenging economic conditions and unstable employment situation in developing countries like Iran, sustainable development has become a primary focus. With coastlines along both the north and south, the growth and development of coastal and marine tourism could provide a solid foundation for generating stable and continuous income streams. This research investigates the factors that facilitate and hinder communication between local communities and key stakeholders in the development of coastal tourism.

The research community comprised local communities, tourists, and government officials involved in tourism processes. Participants were selected based on specific criteria through targeted sampling, resulting in a total of 17 samples. The primary research tool utilized was semi-structured interviews. Interview questions were developed within the frameworks of two theories: social exchange and social network theory. Data analysis was conducted using thematic analysis methods.

The results indicated that all the promoting and inhibiting factors can be categorized into four themes: economic, socio-cultural, environmental, and institutional governance. According to the analyzed data, the inhibiting factors in the environmental sector significantly outnumber the driving factors. In contrast, in the other sectors, the gap between the driving and inhibiting factors is smaller.

This research provides a novel perspective on advancing green evangelism. By strengthening emotional connections with the brand, green evangelism lays the groundwork for developing green respect and green credibility. This approach, which focuses on enhancing emotional bonds with the brand, contributes to the expansion of the green brands in developing countries. Therefore, instead of direct advertising for green brands, the focus should be on attracting key customers to form a community dedicated to the green brand.

Purchase intention of consumers depends on their perception of the extent to which his expectations will be met through the product. This issue, in the context of the products that are immediately purchased by consumer, depends on the extent of relationship in the point of sale. Packaging is one of the most significant factors influencing purchase decision in the point of sale. In this research, the purpose is evaluating the impact of using Islamic symbols in food packaging on the purchase intention of Muslim consumers.

The authors surveyed Muslim consumers through a questionnaire and analyzed the gathered data through partial least squares (PLS).

The findings reveal the positive impact of Islamic symbols in food packaging on purchase intention of Muslim consumers. However, this effect was confirmed regarding people with high religiosity. The findings show that religious symbol in packaging increases perceived religious symbolic-value of the product among the customers with high religiosity.

Findings of this paper help marketers that are seeking to promote their products in Islamic markets identify the importance of religious symbols and understand when and how to use these symbols in packaging.

The purpose of this research is to address the need for a robust system to accurately determine a cutoff score by using the Angoff method and leveraging the Rasch infit and outfit statistics of item response theory by detecting and removing misfitting items in a test.

Researchers in educational evaluation support the use of grades as a complete measure to evaluate students’ overall academic performance. In higher education, determining cutoff scores is crucial for assessing academic progress and achievement. Higher education institutions worldwide set predefined minimal standards of success, sometimes referred to as cutoff thresholds. These thresholds serve as benchmarks for assessing performance quality and determining eligibility for academic credit or advancement.

The proposed approach combines the Angoff method with Rasch item fit statistics to precisely determine the cutoff score by excluding items that do not fit well (misfitting items) in a test. This methodology holds the potential to enhance the fairness and accuracy of grading practices, ensuring that assessments align with educational objectives and provide meaningful feedback to students.

The value of this research extends to various fields where cutoff scores are used for decision-making purposes. By using Rasch item fit statistics and the Angoff method, practitioners and researchers can enhance the quality and validity of their assessments.

Water/Al₂O₃ nanofluid with volume fractions of 0, 0.3 and 0.06 was investigated inside a rectangular microchannel. Jet injection of nanofluid was used to enhance the heat transfer under a homogeneous magnetic field with the strengths of Ha = 0, 20 and 40. Both slip velocity and no-slip boundary conditions were used.

The laminar flow was studied using Reynolds numbers of 1, 10 and 50. The results showed that in creep motion state, the constricted cross section caused by fluid jet is not observable and the rise of axial velocity level is only because of the presence of additional size of the microchannel. By increasing the strength of the magnetic field and because of the rise of the Lorentz force, the motion of fluid layers on each other becomes limited.

Because of the limitation of sudden changes of fluid in jet injection areas, the magnetic force compresses the fluid to the bottom wall, and this behavior limits the vertical velocity gradients. In the absence of a magnetic field and under the influence of the velocity boundary layer, the fluid motion has more variations. In creeping velocities of fluid, the presence or absence of the magnetic field does not have an essential effect on Nusselt number enhancement.

In lower velocities of fluid, the effect of the jet is not significant, and the thermal boundary layer affects the entire temperature field. In this case, for Hartmann numbers of 40 and 0, changing the Nusselt number on the heated wall is similar.

For years, traditional techniques have been used for diabetes treatment. There are two major types of insulin: insulin analogs and regular insulin. Insulin analogs are similar to regular insulin and lead to changes in pharmacokinetic and pharmacodynamic properties. The purpose of the present research was to determine the cost-effectiveness of insulin analogs versus regular insulin for diabetes control in Yazd Diabetes Center in 2017.

In this descriptive–analytical research, the cost-effectiveness index was used to compare insulin analogs and regular insulin (pen/vial) for treatment of diabetes. Data were analyzed in the TreeAge Software and a decision tree was constructed. A 10% discount rate was used for ICER sensitivity analysis. Cost-effectiveness was examined from a provider's perspective.

QALY was calculated to be 0.2 for diabetic patients using insulin analogs and 0.05 for those using regular insulin. The average cost was $3.228 for analog users and $1.826 for regular insulin users. An ICER of $0.093506/QALY was obtained. The present findings suggest that insulin analogs are more cost-effective than regular insulin.

This study was conducted using a cost-effectiveness analysis to evaluate insulin analogs versus regular insulin in controlling diabetes. The results of study are helpful to the government to allocate more resources to apply the cost-effective method of the treatment and to protect patients with diabetes from the high cost of treatment.

This paper proposes a novel deep learning based method towards the identification of a pistachio tree cultivar from its image.

The investigated scope of this study includes Iranian commercial pistachios (Jumbo, Long, Round and Super long) trees. Effective use of high-resolution images with standard deep models is addressed in this study. A novel image patches extraction method is also used to boost the number of samples and dataset augmentation. In the proposed method, handcrafted ORB features are used to detect and extract patches which may contain identifiable information. An innovative algorithm is proposed for searching and extracting these patches. After extracting patches from initial images, a Convolutional Neural Network, named EfficientNet-B1, was fine-tuned on it. In the testing phase, several patches were extracted from the prompted image using the ORB-based method, and the results of their prediction were consolidated. In this method, patch prediction scores were in descending order, sorted by the highest score in a list, and finally, the average of a few list tops was calculated and the final decision was made.

Examining the proposed method on the test images led to an achievement of a recognition rate of 97.2% accuracy. Investigation of decision-making in the test dataset could reveal that this method outperformed human experts.

Cultivar identification using deep learning methods, due to their high recognition speed, lack of specialist requirement, and independence from human decision-making error is considered as a breakthrough in horticultural science. Variety cultivars of pistachio trees possess variant characteristics or traits, accordingly recognising cultivars is crucial to reduce the costs, prevent damages and harvest the optimal yields.

Few reports considering drug use among earthquake survivors exist. The present study aims to examine the Bam earthquake's impact on prescribing patterns and drug use among residents five years post‐disaster.

In this study, 297,104 prescriptions, issued by general practitioners in Bam city in 2008, were investigated for drugs/prescriptions, drug name, drug category, using WHO appropriate general practice prescribing indicators.

Mean drugs per prescription was 3.1. Drugs affecting the central nervous system were the most frequently used among Bam residents, representing 25.1 per cent, followed by antimicrobials, respiratory, cardiovascular and gastrointestinal tract drugs. Benzodiazepines were the most frequently used central nervous system drugs (15.8 per cent) followed by narcotic analgesics and tricyclic antidepressants. Penicillins (6.4 per cent) and cephalosporines (2.3 per cent) were the most frequently used antimicrobial drugs.

Results emphasize increased drug use for psychological disturbances and the need for strategies to improve mental health among disaster survivors.

This chapter presents a comprehensive framework for advancing smart cities in Bahrain, focusing on innovation, development, transformation, and prosperity. The framework integrates technological advancements with sustainable practices to enhance societal well-being, economic growth, and overall development. It aligns with Bahrain’s 2030 Vision, aiming to create Next Generation Smart Cities. The chapter emphasizes enhancing social impact, healthcare access, and promoting a healthy lifestyle, driving economic growth through digital infrastructure, and promoting sustainability through renewable energy and smart urban planning. It provides a roadmap for integrating smart technologies into urban planning, infrastructure development, and service delivery, improving residents’ quality of life and promoting economic growth. The framework highlights the importance of sustainability, emphasizing environmentally friendly practices and energy-efficient solutions. Bahrain’s smart city initiatives are multifaceted, encompassing social, economic, and sustainability agendas. Socially, the focus is on promoting cohesion and community engagement through smart parks, community centers, and digital platforms that facilitate communication and collaboration. Economically, Bahrain aims to drive growth and innovation by investing in digital infrastructure and deploying smart technologies across sectors like finance and tourism. Additionally, the kingdom is developing a skilled workforce in emerging technologies to enhance competitiveness. Sustainability is a key pillar, with Bahrain investing in renewable energy sources and smart grid technologies to reduce reliance on fossil fuels and improve energy efficiency. These initiatives collectively aim to enhance the quality of life, drive economic prosperity, and promote environmental sustainability in Bahrain’s smart cities.