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Building upon the results of a critical review of previous studies, the purpose of this paper is to present a framework to enhance the reliability of the theoretical model for international benchmarking of labour productivity (TMIBLP) method for construction project activities. The next part of the paper presents the results of implementing the proposed framework for construction activities in the Iranian construction industry.

This paper draws upon a critical review of the literature to highlight the drawbacks of the previous studies concerning implementing TMIBLP within the construction industry. Identifying these shortcomings, the authors propose a framework for construction projects, which presents the procedure for deploying TMIBLP for construction activities in a reliable manner. The final section of the paper demonstrates the empirical implementation of the proposed framework within the Iranian construction industry.

The primary contributions of the paper include: identifying the drawbacks of previous studies within the construction context, the framework that would lead construction managers towards more reliable implementation of benchmarking for construction projects, and determining the baseline of erecting steel structures in a developing country.

A practical implementation of the TMIBLP method was presented to address the lack of research in Iran and to show the feasibility of using the framework developed. The authors investigated the daily labour productivity for the activity of structural steel erection for six projects in Tehran in order to determine the values of the baseline productivity for each project. Accordingly, the disruption index, performance ratio and project management index as the project benchmarks were calculated for all six projects.

Underlining the necessity of implementing methods such as TMIBLP, this study outlines the outcomes of the first study on the benchmarking of construction activities deploying the proposed framework and using the data on erecting steel structures from six construction projects in Iran. The discussions provide guidelines for construction project managers regarding benchmarking labour productivity. The paper concludes with suggestions for future research opportunities.

Today’s, supply chain production and distribution of products to improve the customer satisfaction in the shortest possible time by paying the minimum cost, has become the most important challenge in global market. On the other hand, minimizing the total cost of the transportation and distribution is one of the critical items for companies. To handle this challenge, this paper aims to present a multi-objective multi-facility model of green closed-loop supply chain (GCLSC) under uncertain environment. In this model, the proposed GCLSC considers three classes in case of the leading chain and three classes in terms of the recursive chain. The objectives are to maximize the total profit of the GCLSC, satisfaction of demand, the satisfactions of the customers and getting to the proper cost of the consumers, distribution centers and recursive centers.

Then, this model is designed by considering several products under several periods regarding the recovery possibility of products. Finally, to evaluate the proposed model, several numerical examples are randomly designed and then solved using non-dominated sorting genetic algorithm and non-dominated ranking genetic algorithm. Then, they are ranked by TOPSIS along with analytical hierarchy process so-called analytic hierarchy process-technique for order of preference by similarity to ideal solution (AHP-TOPSIS).

The results indicated that non-dominated ranked genetic algorithm (NRGA) algorithm outperforms non-dominated sorting genetic algorithm (NSGA-II) algorithm in terms of computation times. However, in other metrics, any significant difference was not seen. At the end, to rank the algorithms, a multi-criterion decision technique was used. The obtained results of this method indicated that NSGA-II had better performance than ones obtained by NRGA.

This study is motivated by the need of integrating the leading supply chain and retrogressive supply chain. In short, the highlights of the differences of this research with the mentioned studies are as follows: developing multi-objective multi-facility model of fuzzy GCLSC under uncertain environment and integrating the leading supply chain and retrogressive supply chain.

This paper aims to study the impact of liquidity risk and transaction costs on stock pricing in Iran, a closed market operating under a financial embargo and compare the results with those of an important neighboring market, namely, Turkey.

This study follows Liu et al. (2016) and incorporates liquidity risk and transaction costs into the traditional consumption-based asset-pricing model (CCAPM) from 2009 to 2017. Effective transaction costs are estimated a la Hasbrouck (2009) and liquidity risk according to eight different criteria.

According to the results, both liquidity risk and transaction costs are higher in Iran, possibly due to the financial embargo. Thus, relative to Turkey, this paper should expect a higher increase in the CCAPM pricing performance in Iran when accounting for these two variables. The results are in line with this expectation and indicate that adjusting the CCAPM significantly increases its pricing performance in both countries, but relatively more in Iran.

This study compares liquidity risk and transaction costs in an economy under the extreme case of a financial embargo to an open yet in other important aspects similar economy from the same region.

Neuromarketing is a science that can examine human subconscious decisions and activities. The study aimed to investigate the neuropsychological responses of consumers to promotion strategies and the decision to buy sports products, in order to determine the more effective strategy.

An experimental design clarifies whether there is a significant difference between the neuropsychological responses resulting from selective promotional strategies (charity, endorsement, advertising and discount). The authors conducted the research with 40 young adults (20 males and 20 females; age range 25–35 years). The Enobio 20-channel electroencephalograph (EEG) is used to record waves, a two-item questionnaire is used to measure purchasing decisions and self-assessment forms are used to measure arousal and pleasure. Data analysis performed by Friedman's statistical methods and logistic regression using SPSS 22 software.

Based on the alpha wave, the results showed the two charity and endorsement strategies had the highest effect on consumer attentions. The pleasure had the highest value in the discount, and the arousal had the highest value in the charity strategy. Neuropsychological responses also explain a significant percentage of the consumer decision to buy.

Access to research samples is difficult due to the ignorance of the samples as well as the fear of possible harm from imaging and brain scanning methods.

Neuromarketing is a science that can examine human subconscious decisions and activities.

The information obtained neural methods are more accurate than traditional research methods.

This study showed the alpha brainwave (attention), arousal and pleasure explain a significant part of the consumer decision to buy. More scientific data can be obtained through new scientific approaches such as neuromarketing, which has a great impact on understanding consumer behavior. Therefore, marketers and researchers can make their promotional activities more effective in terms of them.

Equal distribution of health human resources is a major issue to achieve human rights in healthcare. Rural family physicians (RFPs) as a part of health human resources play an important role in delivering health services, so the purpose of this paper is to calculate amount of inequity in distribution of RFPs in Iran.

In this study, the authors tried to find inequity in the distribution of RFPs in the provinces of Iran. For this purpose, inequity indices containing concentration curves and indices were calculated by ranking health-adjusted life expectancy (HALE). Furthermore, a regression model was estimated to find the pattern and influencing factors of inequity in the distribution of RFPs.

The number of male RFPs was significantly higher in Sistan va Baloochestan, and in the same line, the number of female RFPs was higher in Zanjan province. Concentration index of total RFPs was 0.0568 (not significant) (males= 0.041, females= 0.0718). The results of regression model showed that HALE and per capita GDP did not have any significant relationship with RFPs distribution (HALE p=0.753, GDP p=0.792).

The RFP plan was successful in enhancing equal access to physician and health care services relatively. However, gender imbalance in distribution of RFPs was high especially in less-developed regions.