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Given the need to simultaneously implement lean and agile (LeAgile) paradigms in supply chain, managers do not know which of these paradigms practices should be given priority. Not knowing this, not only will they fail to apply these paradigms properly, but they will also waste significant financial resources. The purpose of this paper is to investigate the relationship between the practices of LeAgile paradigms and their effects on the supply chain performance.

Because the military products play a key role in national security enhancement, this research is done in the military product supply chain. Research methodology is an exploratory, mixed and descriptive one. In terms of its purpose, it is an applied research based on identifying and searching for practices and the use of interpretive equations. First, the authors identify the most important and implementable LeAgile practices in the form of importance feasibility analysis matrices. Then, using fuzzy interpretative structural modeling, a model is presented to show the logical relationships and hierarchy between paradigms, practices and their impact on supply chain performance. The research tool in both main stages of the research was the questionnaire completed by industrial and academic experts. The selection of experts was done purposefully.

The results show that of total 100 practices introduced in the previous research for LeAgile supply chain, 21 practices in the lean and agility of the supply chain of military industries are important and implementable. The final model of this study illustrates the hierarchical relationships between 21 practices and its effect on supply chain performance key measures. This model shows that LeAgile paradigms are intertwined and their simultaneous implementation leads to improved supply chain performance. In this model, supplier-related practices play a driving and fundamental role and become a top priority for implementation.

Military products variation in land, air and sea areas and the large number of industries in each sectors, forced us to select the only land area. Although the results of this research can be used in the air and sea areas, one cannot say that Implementation of this study by its presented model will fully lead to the military industries supply chain (SC) lean and agility in air and sea sectors.

To the best of the authors’ knowledge, this is the first research on the SC legality in Iran’s military industry which tries to apply these two paradigms simultaneously in the SC and bridge the gap between theory and practice. Clustering LeAgile practices, based on two measures of importance and feasibility, and defining four strategies for implementing these measures, is a new approach to focus on deploying practices that are currently more feasible. Identifying a significant number of SC LeAgile practices (100 practices) and demonstrating the interactions between important and feasible practices in the military products SC are another innovation in this research.

Nowadays, the defense industry is considered a significant part of the manufacturing industries. Military products in the world have a high level of diversity, delivery speed and appropriative operational functionality. Therefore, various producing, high quality and high-speed delivery of military products are of great importance in enhancing Iran’s defensive power. Defense industries’ supply chain agility is a response to how to produce military products with these features. Therefore, the purpose of this paper is to provide a model for the agile supply chain of defense industries to show the relationship between agile practices and their hierarchy.

First, the authors identify the most important supply chain agility practices by expert’s questionnaire. Then, using factor analysis, practices are categorized and validated based on structural equation modeling (SEM). SEM showed a meaningful relationship between agile supply chain practices. Finally, using interpretative structural modeling, a model is presented to show the logical relationships and hierarchy between these practices.

The results show that out of a total of 62 practices introduced in the previous research for the agile supply chain, 37 practices in the agility of the supply chain of defense industries are effective. The 4 new agility practices were identified in this research. These 41 practices were classified into 8 categories including supplier relationship, workshop level management, organizational structure improvement, human resource management, product designing, improve and integrate the process, application of information technology and customer relationship. Improvement of organizational structure was at the highest level of the model. Therefore, managers first should focus on it.

Given the confidentiality of information in the defense industry, the distribution of questionnaires and their collection was one of the most important limitations. A variety of defense products in land, air and sea areas, and a large number of industries in each sector, forced the authors to select the only land area. Although the results of this research can be used in the air and sea areas, but cannot be said that the implementation of this study presented model will fully lead to the defense industries’ supply chain agility in air and sea sectors.

This is the first research on the supply chain agility of Iran’s defense industry that bridges the gap between theory and practice. The classification of 41 practices in the form of 8 measures and examining the relationship between them is a new and practical approach for understanding the relationships between different variables that affect supply chain agility. This study introduces four new agility practices including the use of new technology and equipment, human resource balance, the use of expert human resources, training and employee empowerment, which can be considered in many industries of developing or less developed countries. Considering the specific situation of defense industry supply chain in comparison with other industries, the results of this research can be used by other defense industries of similar countries.

Knowledge sharing (KS) of employees has numerous benefits for organizations. Therefore, the aim of this study is to provide a model for KS in research centers (RCs) that can facilitate the employee's knowledge sharing behavior (KSB).

Based on the extensive literature review, a valid instrument was adopted to collect the required data set on KS, KSB and intention to KS, and finally 317 complete questionnaires were collected from Iranian research centers. The structural equation modeling (SEM) was used to assess the measurement model and to test the research hypotheses.

The findings show that intrinsic and extrinsic motivational factors and intention to methods of KS play an important role in KSB. In other words, simultaneous supply of motivational factors and KS methods interesting for employees lead to their KSB. The SEM confirmed the research model and showed a good fit of it.

The implication emanating from this study is that the employees' KSB in RCs as a significant part depends on simultaneous supplying of motivational factors (especially intrinsic motivational factors) and methods of KS that are interesting for employees.

What distinguishes this study from other studies in KS domain could be implied in two subjects. First, the presented model is simple and prepared of the introduced factors, which will lead to KSB. Second, this study was conducted in diverse research fields such as electrical and electronics, telecommunications, materials, chemistry, biotechnology, information technology, management and industrial engineering, computer network security, mechanical and manufacturing. The research model was derived from the collected data of these areas that is unique in this domain.

The purpose of this study is to present a comprehensive hydrothermal analysis on an inclined mini-channel using numerical and experimental techniques. The fin array acts as heat source within the channel, and a wavy wall located at the top of the channel is heat sink. The side walls are insulated with curved profiles. Also, the channel is inclined with four known inclination angles. To solve the governing equations, the dual-multi-relaxation-time lattice Boltzmann method with D2Q9 and D2Q5 lattice models for flow and temperature fields is used, respectively. Also, the channel is filled with SiO2-glycol nanofluid.

Identifying the behavior of a thermal component during natural convective flow is a challenging topic due to its complexities. This paper focuses on analyzing the thermal and hydrodynamic aspects of a narrow channel equipping with fin array.

Two correlations are proposed considering temperature and volume fraction ranges for thermal conductivity and dynamic viscosity according to measured experimental data which are used in the numerical phase. Finally, the structure of flow, temperature distribution of fluid, local thermal and viscous dissipations, volume-averaged entropy production, Bejan number and heat transfer rate are extracted by numerical simulations. The results show that the average Nusselt number enhances about 57% (maximum enhancement percentage) when volume fraction increases from 1% to 3% at Ra = 10⁶ and θ = 90°. In addition, the value of entropy generation is maximum at φ = 1%, Ra = 10⁶ and φ = 90°. Also, the maximum enhancement of entropy generation in range of Ra = 103 to 106 is about 4 times at φ = 1% and θ = 90°.

The originality of the present study is combining a modern numerical method (i.e. dual/multi-relaxation-time LBM) with experimental observation on characteristics of SiO₂-glycol nanofluid to study the thermal and hydrodynamic properties of the studied mini-channel.

This paper aims to analyze the effect of absorber’s geometry and operating fluid on the thermal and hydrodynamic behaviors of a solar collector. Two different profiles are proposed for the absorber which is wavy and flat. Also, the inner tube of HTF (i.e. heat transfer fluid) is considered as single and double. The solar collector is filled with hybrid nanofluid of SiO₂-TiO₂/ ethylene glycol (EG) which its thermal conductivity and dynamic viscosity are measured using KD2 Pro and Brookfield LVDV III Ultra; respectively, in the temperature range of 30°C to 80°C and nanoparticle concentration in the range of 1.5% to 3.5%.

Among the solar collector, the parabolic-trough solar collector is one of the most efficient models for extracting solar thermal power. A parabolic trough solar collector with two different models of absorbers and included with two models of inner HTF tube is proposed.

The corresponding regression equations are derived versus temperature and volume fraction and used in the numerical process. For the numerical process, the thermal lattice Boltzmann method manipulated with a single-node curved scheme is used. Also, in the final step, the second law analysis is carried out in local and volumetric forms. The influential factors are Rayleigh number, the concentration of hybrid nano-powder and the structure of absorber profile.

The originality of the present work is combining a modern numerical method (i.e. double-population lattice Boltzmann method) with experimental observation on characteristics of SiO₂-TiO₂/EG nanofluid to analyze the thermal performance of parabolic trough solar collector.

This paper aims to propose an 18th-order nonlinear model for doubly fed induction generator (DFIG) wind turbines. Based on the proposed model, which is more complete than the models previously developed, an extended Kalman filter (EKF) is used to estimate the DFIG state variables.

State estimation is a popular approach in power system control and monitoring because of minimizing measurement noise level and obtaining non-measured state variables. To estimate all state variables of DFIG wind turbine, it is necessary to develop a model that considers all state variables. So, an 18th-order nonlinear model is proposed for DFIG wind turbines. EKF is used to estimate the DFIG state variables based on the proposed model.

An 18th-order nonlinear model is proposed for DFIG wind turbines. Furthermore, based on the proposed model, its state variables are estimated. Simulation studies are done in four cases to verify the ability of the proposed model in the estimation of state variables under noisy, wind speed variation and fault condition. The results demonstrate priority of the proposed model in the estimation of DFIG state variables.

Evaluating DFIG model to estimate its state variables precisely.

This article aims to describe the effect of an endoscope and heat transfer on the peristaltic flow of a Jeffrey fluid through the gap between concentric uniform tubes.

The mathematical model of the present problem is carried out under long wavelength and low Reynolds number approximations. Analytical solutions for the velocity, temperature profiles, pressure gradient and volume flow rate are obtained.

The results indicate that the effect of the wave amplitude, radius ratio, Grashof number, the ratio of relaxation to retardation times and the radius are very pronounced in the phenomena. Also, a comparison of obtaining an analytical solution against previous literatures shows satisfactory agreement.

Analytical solutions for the velocity, temperature profiles, pressure gradient and volume flow rate are obtained. Numerical integration is performed to analyze the pressure rise and frictional forces on the inner and outer tubes.

A growing body of research from various domains has investigated Airbnb, a two-sided market platform for peer-based accommodation sharing. The authors suggest that it is due time to take a step back and assess the current state of affairs. This paper aims to conflate and synthesize research on Airbnb.

To facilitate research on Airbnb and its underlying principles in electronic commerce, the authors present a structured literature review on Airbnb.

The findings are based on 118 articles from the fields of tourism, information and management, law and economics between 2013 and 2018. Based on this broad basis, the authors find that: research on Airbnb is highly diverse in terms of domains, methods and scope; motives for using Airbnb are manifold (e.g. financial, social and environmental); trust and reputation are considered crucial by almost all scholars; the platform’s variety is reflected in prices; and the majority of work is based on surveys and empirical data while experiments are scarce.

Based on the present assessment of studied topics, domains, methods and combinations thereof, the authors suggest that research should move toward building atop of a common ground of data structures and vocabulary, and that attention should focus on the identified gaps and hitherto scarcely used combinations. The set of under-represented areas includes cross-cultural investigations, field experiments and audit studies, the consideration of dynamic processes (e.g. based on panel data), Airbnb’s “experiences” and automated pricing algorithms and the rating distribution’s skewness.

This study provides a comprehensive overview of work on the accommodation sharing platform Airbnb, to the best of the auhtors’ knowledge, representing the first systematic literature review. The authors hope that researchers and practitioners alike will find this review useful as a reference for future research on Airbnb and as a guide for the development of innovative applications based on the platform’s peculiarities and paradigms in electronic commerce practice. From a practical perspective, the general tenor suggests that hotel and tourism operators may benefit from: focusing on their core advantages over Airbnb and differentiating features and aligning their marketing communication with their users’ aspirations.

Environmental taxes have been in place for many years to reduce environmental damage and pay more attention to the environment. However, some of the adverse socio-economic impacts that may result from such taxes and the many challenges facing developing countries have necessitated policy reform. Therefore, identifying and prioritizing the factors related to environmental tax reform (ETR) is necessary to help governments and environmental protection agencies (EPAs) focus on this prioritizing to develop and improve this process. Awareness of the benefits of ETR encourages governments to use this policy to reduce adverse environmental impacts and contribute to economic growth.

The primary purpose of this work is to prioritize and taxonomy the factors related to ETR using the Fuzzy Analytic Hierarchy Process (FAHP) approach. In the first stage, 25 factors were extracted from the available literature. These factors were divided into five categories for more accessible review. In the second stage, the FAHP as a Multiple-Criteria Decision-Making (MCDM) Technique was used to prioritize and develop the taxonomy of identified factors and the categories of these factors.

The results show that reducing carbon emissions (DF4) is the essential prioritization factor that governments and environmental organizations can achieve if the ETR is implemented. Following that, reducing greenhouse gas emissions (DF1), double benefit (EcF7) and increase sustainability reports (EnF4) can be achieved by implementing ETR.

This study is geographically limited to Iran. In terms of the study population, this study is limited to 25 academic, tax and public policy experts. Moreover, in this study, FAHP is the only approach used. For further research, the results of this study can be compared with that of other multi-criteria techniques like FAHP, fuzzy TOPSIS or BWM.

Ratings of factors related to ETR can guide and help governments identify important factors that affect environmental tax reform, which can, in addition to controlling ecological pollution will, increase the economic benefits of governments.

This study is the first to identify factors related to environmental tax reform and to develop an MCDM technique for prioritizing these factors and finding important ones.

The aim of this study is to design a guidance method to generate a smoother and feasible gliding reentry trajectory, a highly constrained problem by formalizing the control variables profile.

A novel accelerated fractional-order particle swarm optimization (FAPSO) method is proposed for velocity updates to design the guidance method for gliding reentry flight vehicles with fixed final energy.

By using the common aero vehicle as a test case for the simulation purpose, it is found that during the initial phase of the longitudinal guidance, there are oscillations in the state parameters which cause to violate the path constraints. For the glide phase of the longitudinal guidance, the path constraints have higher values because of the increase in the atmosphere density.

The violation in the path constraints may compromise the flight vehicle safety, whereas the enforcement assures the flight safety by flying it within the reentry corridor.

An oscillation suppression scheme is proposed by using the FAPSO method during the initial phase of the reentry flight, which smooths the trajectory and enforces the path constraints partially. To enforce the path constraints strictly in the glide phase, ultimately, another scheme by using the FAPSO method is proposed. The simulation results show that the proposed algorithm is efficient to achieve better convergence and accuracy for nominal as well as dispersed conditions.