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The purpose of this paper is to investigate the impact of knowledge-based dynamic process capabilities (KBDPCs) on innovation performance, considering the mediator role of innovation processes in the Iranian knowledge-based high-tech companies.

Based on an in-depth review of previous studies, the indicators pertaining to the research constructs were extracted. Then, exploratory and confirmatory factor analyses were applied to identify and confirm the research constructs. Partial least squares-based structural equation modeling was used to investigate the intended relationships.

The results of the direct effect showed that KBDPCs have a significant positive effect on innovation performance. Further, moderation analysis demonstrated that innovation processes are moderated by the relationship between KBDPCs and innovation performance. Accordingly, the findings revealed that KBDPCs affect product innovation performance and exploratory innovation and transitional innovation increase this effect. Also, the mediator role of exploitation innovation in the relationship between KBDPCs and process innovation performance was proved.

As this research was performed in the Iranian context, caution should be taken regarding the generalizability of the findings.

This paper provides a roadmap based on existing scenarios to enhance innovation performance for the surveyed-companies, in particular, and other companies, in general.

The social implication of this study is to respond to the challenge of the managers of Iranian knowledge-based high-tech companies to improve innovation performance through KBDPCs and innovation processes and to grow and develop a sustainable business.

Given rare studies that have so far been conducted on the research field, this study extends the theories of KBDPCs, innovation processes and innovation performance. The constructs of the research model and relationships intended among them are also significant.

The purpose of this study is to identify and prioritize the critical success factors (CSFs) of knowledge management (KM) implementation through a novel hybrid model, namely, Fuzzy Delphi method (FDM), interpretive structural modeling (ISM) and revised Simos, which is one of group decision-making (GDM) approaches.

The CSFs of KM implementation were identified through a systematic literature review. FDM was adopted to determine the CSFs in the Iranian oil industry. Then, a novel hybrid model consisting of ISM and revised Simos techniques were used to classify and prioritize the CSFs.

The obtained results suggest that there are 13 CSFs of KM implementation. The result of ISM shows that the CSFs of KM implementation were classified into five levels. The result of revised Simos reveals that the “human resources management” obtained the highest priority and “leadership commitment and support” and “intellectual capital” ranked second and third, respectively.

As this research was performed in the Iranian oil industry, caution should be taken regarding the generalizability of the obtained results.

The top managers of the surveyed companies could get acquainted with CSFs of KM implementation in their organization and use a GDM technique that has various advantages to solve the relevant problems.

This paper provides a twofold contribution to expand KM and GDM literature and to the best knowledge of the authors, it is a novel hybrid GDM model of its kind.

The purpose of this paper is to present the factors affecting purchase intention of foreign food products in the Iranian context.

The present study is a survey research and has a quantitative approach. According to Morgan’s table, 384 people were selected as sample size. Based on an in-depth review of previous literature, a comprehensive set of sub-factors related to customer’s purchase intention was extracted to design questionnaire. Then, exploratory factor analysis and confirmatory factor analysis were applied to identify and confirm the factors affecting purchase intention of foreign food products in Iran.

The obtained results illustrate 13 factors as follows: “corporate social responsibility,” “customer knowledge and awareness,” “perceived risk,” “retailer’s commercial image,” “customer’s personality characteristics,” “social identity,” “product features,” “attitude,” “country-of-origin,” “perceived value,” “subjective norm,” “loyalty” and “perceived behavioral control.”

As the present research was carried out in the Iranian context, the generalization of the findings is limited and caution should be taken in this regard.

The identified factors could contribute to international food companies and retailers to understand customers’ expectations and to gain more market share in Iran.

The originality of this paper lies in identifying a comprehensive set of the factors affecting purchase intention of foreign food products and developing the theoretical literature in the field of the present research.

The purpose of this paper is to develop a measurement instrument toward knowledge management (KM) implementation in the Iranian oil industry.

Based on an in-depth study of the relevant literature, the critical success factors (CSFs) related to the sub-factors were identified. Then, exploratory and confirmatory factor analysis was used to validate the instrument. Finally, based on the developed instrument, the KM implementation was evaluated in the subsidiaries of the Iranian oil industry.

The obtained results reveal the 13 factors as follows: human resource management; KM processes; information technology; business strategy; intellectual capital; KM system; executive practices of KM; management information system; culture; partnership and cooperation with business partners; KM road map; leadership commitment and support; and organizational environment.

As this study was conducted in the Iranian oil industry, cautious should be taken regarding the generalizability of the results.

The proposed instrument can help policymakers and top managers of the subsidiaries of Iranian oil industry in successful implementation and measurement of their KM practices.

Identification and measurement of the CSFs of KM implementation through developing a comprehensive instrument in the context of the Iranian oil industry.

The purpose of this study is to conduct a numerical analysis of flow and heat transfer of water–aluminum oxide nanofluid in a channel with extended surfaces in the presence of a constant magnetic field. The channel consists of two parallel plates and five obstacles of constant temperature on the lower wall of the channel. The upper wall and the inlet and outlet lengths of the lower wall are insulated. A uniform magnetic field of the magnitude B0 is located beneath the obstacles. The nanofluid enters the channel with a uniform velocity and temperature, and a fully developed flow leaves the channel.

The control volume-based finite difference and the SIMPLE algorithm were used for numerical solution. In addition to examining the effect of the Reynolds number, the effects of Hartman number, the volume fraction of nanoparticles, the height of obstacles, the length of obstacles and the distance between the obstacles were investigated.

According to the results, the heat transfer rate increases with an increasing Reynolds number. As the Hartmann number increases, the heat transfer rate increases. The heat transfer rate also increases with an increase in the volume fraction of nanoparticles. The mean Nusselt number is reduced by an increasing height of obstacles. An increase in the distance between the obstacles in the presence of a magnetic field does not have a significant impact on the heat transfer rate. However, the heat transfer rate increases in the absence of a magnetic field, as the distance between the obstacles increases.

This paper is original and unpublished and is not being considered for publication elsewhere.

Plant materials continue to play a major role in primary health care as therapeutic remedies in many developing countries. Medicinal herbs contain physiologically active principles that over the years have been exploited in traditional medicine for the treatment of various ailments as they contain antimicrobial properties. This paper aims to determine the antibacterial activity of Iranian endemic plants.

Antibacterial activities of ethanol extract and essential oil of ten Iranian folklore herbs including Heracleum lasiopetalum Boiss., Hypericum scabrum L., Thymus daenensis Celak., Ziziphora teniur L., Echiophora platyloba L., Dracocephalum multicaule Benth., Kelussia odoratissima Mozff., Mentha longifolia Hudson., Achillea kellalensis Boiss. and Arnebia euchroma (Royle.) Johnston. were investigated against Yersinia enterocolitica PTCC 1151 by agar disc diffusion and serial dilution assays.

Most of the extracts and essential oils showed some antibacterial activity against the tested bacteria with the diameter of inhibition zone ranging between 9 and 16 mm. Of the plants studied, the most active extracts were those obtained from essential oil of H. lasiopetalum fruits and ethanol extract of A. euchroma roots. The MIC values for active extract and essential oil ranged between 0.039 and 0.156 mg/ml.

The results obtained appeared to confirm the antibacterial potential of the plants investigated.

The essential oil <0.039 mg/ml of H. lasiopetalum fruits could be used as natural antibacterial agent Y. enterocolitica in the food preservation and human health.

This paper aims to conduct a fuzzy discrete time cost quality risk in the ambiguous mode CO_{2 tradeoff problem} (FDTCQRP*TP) in a megaproject based on fuzzy ground.

A combinatorial evolutionary algorithm using Fuzzy Invasive Weed Optimization (FIWO) is used in the discrete form of the problem where the parameters are fully fuzzy multi-objective and provide a space incorporating all dimensions of the problem. Also, the fuzzy data and computations are used with the Chanas method selected for the computational analysis. Moreover, uncertainty is defined in FIWO. The presented FIWO simulation, its utility and superiority are tested on sample problems.

The reproduction, rearrangement and maintaining elite invasive weeds in FIWO can lead to a higher level of accuracy, convergence and strength for solving FDTCQRP*TP fuzzy rules and a risk ground in the ambiguous mode with the emphasis on the necessity of CO₂ pollution reduction. The results reveal the effectiveness of the algorithm and its flexibility in the megaproject managers' decision making, convergence and accuracy regarding CO₂ pollution reduction.

This paper offers a multi-objective fully fuzzy tradeoff in the ambiguous mode with the approach of CO₂ pollution reduction.

As a human right, people need to arrive early at the hospitals when they are injured in traffic accidents. Both the mean and equality of the time of arriving at the hospital are important. This study aimed to investigate inequality in arrival time of emergent traffic accident patients to the hospital in 2018–2019 in a city in the North of Iran.

The authors extracted the data from the Guilan province trauma system databank in Poursina Hospital in Rasht in 2018 and 2019. The Gini coefficient was used to calculate inequality, and a regression model was estimated for determining the reason for inequality in time to receive hospital services.

The study showed that patients’ arrival time from the time of the accident to the time of arrival to the hospital was 64.48 ± 47.63 min (minimum of 9 min and maximum 462 min). Gini coefficient was 0.31 (p <0.001), which does not show high inequality. Regression results showed that the transfer time of patients by car was 40 min longer (p-value <0.001) than ambulances (p = 0.036). In children, the transfer time was 42 min less (p = 0.003). Other variables did not explain the inequality (p > 0.05).

According to the time of arrival of patients and Gini index, in Rasht, inequality in providing services is not in a bad condition. This indicates that the emergency department does not systematically transport people to the hospital late.

When a manipulator captures an unknown space object, inertia parameters of endpoint payload should be timely obtained to handle possible unexpected parameter variations and monitor the system’s operating conditions. Therefore, this study aims to present an identification method for estimating the inertia parameter of the payload carried by a flexible two-link space manipulator.

The original nonlinear dynamics model of the manipulator is linearized at a selected working point. Subsequently, the system modal frequencies with and without payload are determined using the subspace identification algorithm, and the difference of these frequencies is computed. Furthermore, by adjusting the structural configuration of the manipulator, multiple sets of frequency differences are obtained. Therefore, the inertia parameters of the payload, i.e. the mass and the moment of inertia, can be derived from the frequency differences by solving a least-squares problem.

The proposed method can effectively estimate the payload parameters and has satisfactory identification accuracy.

The approach’s implementation provides a practical reference for determining inertia parameters of an unknown space target in the capture process.

The study proposes a novel method for identifying the inertia parameters of the payload of a flexible two-link space manipulator using the estimated system frequencies.

The purpose of this study is to manufacture composites from sawdust and polymer high-density polyethylene (HDPE) with different loading from alum as natural and cheap flame retardant and subsequently characterized using standard analytical tools.

Artificial wood plastic composites (WPCs) were prepared by mixing HDPE with sawdust as a filler with constant ratio (2:1) using hot press. Polyethylene-graft-maleic anhydride (PE-g-MAH) used as a coupling agent between two parents of the composites with different ratios (2.5, 5, 7 and 10). Alum as a flame retardant was incorporated into HDPE with 5 phr polyethylene grafted with maleic anhydride (PE-g-MAH) with different ratios (10, 15 and 20). Flame retardant efficiency was investigated using differential scanning calorimetry, thermal gravimetric analysis and the technique of ASTM E162.

The results revealed that the composite containing 5 phr from (PE-g-MAH) exhibited higher mechanical properties and this proved that (PE-g-MAH) act as an efficient coupling agent using the aforementioned ratio. The results also revealed that incorporation of alum as a flame retardant increased the thermal stability of the composites.

Artificial WPCs are ecofriendly materials with a wide range of applications in the constructions field. Moreover, they have high mechanical and physical properties with low cost. Evaluate alum as a natural and cheap flame retardant.