Razie Hormoznejad, Anahita Mansoori, Seyed Ahmad Hosseini, Marzie Zilaee, Maryam Asadi, Mojdeh Fathi and Fateme Kiany
The purpose of this paper with meta-analysis is to clarify the effects of cranberry consumption on features of the metabolic syndrome of interest of all relevant randomized…
Abstract
Purpose
The purpose of this paper with meta-analysis is to clarify the effects of cranberry consumption on features of the metabolic syndrome of interest of all relevant randomized controlled trials (RCTs).
Design/methodology/approach
A systematic literature search was conducted on ISI web of science, PubMed, Embase, the Cochrane library and Google Scholar databases, to include trials published up to March 2019. Weighted mean differences (WMD) were calculated from a random or fixed-effects models. Between‐study heterogeneity was assessed by Cochrane’s test and I2 index.
Findings
Ten RCTs were included in this review which involving a total of 371 subjects. Our meta-analysis showed that cranberry consumption had beneficial effects on waist circumference (WMD −0.49, 95% CI −0.96 to −0.036; p = 0.034). No significant effect of cranberry consumption on fasting blood glucose, high-density lipoprotein cholesterol, triglycerides and blood pressure was found in this meta-analysis.
Originality/value
To the best of the authors’ knowledge, this is the first systematic review with meta-analysis of RCTs that investigate the effect of cranberry consumption on features of the metabolic syndrome.
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Seyed Mohammad Arab, Seyed Reza Hosseini Zeidabadi, Seyed Ahmad Jenabali Jahromi, Habib Daneshmanesh, Seyed Mojtaba Zebarjad and Kamal Janghorban
A self-lubricant surface composite including Al matrix and Babbitt alloy 11 reinforcement has been fabricated via friction stir processing (FSP).
Abstract
Purpose
A self-lubricant surface composite including Al matrix and Babbitt alloy 11 reinforcement has been fabricated via friction stir processing (FSP).
Design/methodology/approach
The optimum processing condition is estimated by statistical analysis of a L9 Taguchi design of experiment. The results of Taguchi analysis suggested four passes of FSP, traverse speed of 40 mm/min and rotational speeds of 1,250 rpm as the optimum parameters to achieve higher hardness and wear resistance.
Findings
The needle-shaped particles are fragmented into the finer particles after FSP. There is uniform distribution of precipitations after FSP. The microhardness of manufactured surface bearings has been increased. Finer particles, smaller grains and in situ formed intermetallic precipitations (AlSb) can be responsible for hardness enhancement. Wear resistance of base metal also has been remarkably enhanced after FSP.
Originality/value
The originality of this paper lies in the following: new self-lubricating surface composite; a tough and resistant to wear sheets; and using a solid-state method to fabricate a surface bearing.
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Ahmad Hajebrahimi, Khalil Alimohammadzadeh, Seyed Mojtaba Hosseini, Ali Maher and Mohammadkarim Bahadori
High quality health-care delivery is not only the governments’ responsibility but also every prisoner’s right. Health care in prison and, particularly, of Iranian prisoners is…
Abstract
Purpose
High quality health-care delivery is not only the governments’ responsibility but also every prisoner’s right. Health care in prison and, particularly, of Iranian prisoners is increasingly important topic because of the rising number of the prison population. This paper aims to explore health-care managers’ perspectives and experiences of prisons and the barriers to health-care delivery in Iranian prisons.
Design/methodology/approach
A qualitative research design was conducted in Iran from October 2018 to August 2019. The participants consisted of 51 health-care managers (50 men and one woman) from Iranian prisons. A combination of face-to-face (N = 42) and telephonic (N = 9) semi-structured interviews were used because of the geographical distribution of the respondents. The first part of the interview guide consisted of demographic characteristics, and the second part consisted of three main open ended-questions. Interviews were recorded and transcribed, and thematic descriptive analysis was used to interpret the data.
Findings
The barriers to health-care delivery in Iranian prisons were categorized into four main topics: human resources, financing, facilities and barriers related to the health-care delivery process. Data synthesis identified the following themes for barriers to human resources: barriers to human resources planning (with eight sub-themes); barriers to education (with three sub-themes); and motivational barriers (with seven sub-themes). Moreover, barriers to financing consisted of five sub-themes. The barriers to facilities consisted of barriers related to physical infrastructures (with two sub-themes) and barriers related to equipment (with six sub-themes). Finally, barriers to the health-care delivery process included the following themes: communication barriers (with six sub-themes); legal barriers (with five sub-themes); and environmental-demographic factors (with seven sub-themes).
Originality/value
Identifying the barriers to health-care delivery in Iranian prisons plays a critical role in the improvement of planning, decision-making and the health-care delivery process.
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Rouhollah Khakpour, Ahmad Ebrahimi and Seyed-Mohammad Seyed-Hosseini
This paper recommends a method entitled “SMED 4.0” as a development of conventional single minute exchange of die (SMED) to avoid defect occurrence during production and improve…
Abstract
Purpose
This paper recommends a method entitled “SMED 4.0” as a development of conventional single minute exchange of die (SMED) to avoid defect occurrence during production and improve sustainability, besides reducing setup time.
Design/methodology/approach
The method builds upon an extensive literature review and in-depth explorative research in SMED and zero defect manufacturing (ZDM). SMED 4.0 incorporates an evolutionary stage that employs predict-prevent strategies using Industry 4.0 technologies including the Internet of Things (IoT) and machine learning (ML) algorithms.
Findings
It presents the applicability of the proposed approach in (1) identifying the triple bottom line (TBL) criteria, which are affected by defects; (2) predicting the time of defect occurrence if any; (3) preventing defective products by performing online setting on machines during production as needed; (4) maintaining the desired quality of the product during the production and (5) improving TBL sustainability in manufacturing processes.
Originality/value
The extended view of SMED 4.0 in this research, as well as its analytical approach, helps practitioners develop their SMED approaches in a more holistic way. The practical application of SMED 4.0 is illustrated by implementing it in a real-life manufacturing case.
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Rouhollah Khakpour, Ahmad Ebrahimi and Seyed-Mohammad Seyed-Hosseini
This paper aims to integrate zero defect manufacturing (ZDM) with process mining (PM) to avoid defect occurrence during production and improve sustainability.
Abstract
Purpose
This paper aims to integrate zero defect manufacturing (ZDM) with process mining (PM) to avoid defect occurrence during production and improve sustainability.
Design/methodology/approach
The method is developed based on literature review in ZDM and PM. It uses PM for process discovery as an initial strategy in priority to predict-prevent strategies of ZDM.
Findings
It presents the applicability of the proposed approach in observing manufacturing process behavior, identifying dynamic causes of defects during production, predicting the time of defect occurrence and preventing defective products. It also identifies, explains and measures criteria for environmental, social and economic pillars of sustainability affected by defects and presents the impacts of the proposed approach on sustainability improvement.
Originality/value
The extended view of this research, as well as its analytical approach, helps practitioners to develop their ZDM and PM approaches more holistically. The practical application of this research is illustrated through implementing it in a real-life manufacturing case, where the outcomes prove its applicability in avoiding defect occurrence and improving all three pillars of sustainability.
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Rouhollah Khakpour, Ahmad Ebrahimi and Seyed-Mohammad Seyed-Hosseini
This paper aims to recommend a method entitled “lean process mining (LPM)” for mapping, analyzing and improving the material/information flows in the value stream of manufacturing…
Abstract
Purpose
This paper aims to recommend a method entitled “lean process mining (LPM)” for mapping, analyzing and improving the material/information flows in the value stream of manufacturing processes.
Design/methodology/approach
The method is developed based on literature review and in-depth explorative research in value stream mapping and process mining approaches. The proposed LPM framework consists of three phases including as-realized process state, improvement strategies and reengineered process state. Hence, firstly, extracts the as-realized model, measures the identified wastes and identifies the sources of wastes. Secondly, implements prediction-recommendation-prevention strategies. Thirdly, reengineers the process model and measures the improved wastes.
Findings
It presents the applicability of the proposed approach in (1) online observation of manufacturing process behavior and tracing the process deviations dynamically in real time to identify the sources of waste; (2) avoiding defective products occurring during the production and eliminating the relevant derived wastes including wasted material, wasted energy, waste of labor, excess inventory, increased production lead time and wasted operational costs.
Originality/value
The practical application of LPM is illustrated through implementing it in a real-life manufacturing case. The outcomes prove the remarkable applicability of this method in lean manufacturing to avoid waste occurrence in the value stream.
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Seyed Mehrshad Parvin Hosseini, Maryam Mirzaei and Mohammad Iranmanesh
This study aims to investigate the factors that motivate Muslim consumers to pay for halal-certified food.
Abstract
Purpose
This study aims to investigate the factors that motivate Muslim consumers to pay for halal-certified food.
Design/methodology/approach
Data were collected through a survey of 272 Muslim consumers in Malaysia. The data were analyzed using the partial least squares technique.
Findings
The results showed that animal slaughter, halal logo, food quality and religious commitment have a positive effect on the willingness to pay for halal food. Religious commitment positively moderates the relationship between storage and transportation and the willingness to pay for halal-certified food.
Practical implications
Policy makers as well as managers of halal food companies can benefit from this study which provides insight into ways to increase demand for halal food.
Originality/value
The findings contribute to the literature on halal foods by illustrating the factors that determine Muslim consumers’ willingness to pay for halal food. This study also extends the literature by testing the moderating role of religious commitment.
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Seyed Reza Zeytoonnejad Mousavian, Seyyed Mehdi Mirdamadi, Seyed Jamal Farajallah Hosseini and Maryam Omidi NajafAbadi
Foreign Direct Investment (FDI) is an important means of boosting the agricultural sectors of developing economies. The first necessary step to formulate effective public policies…
Abstract
Purpose
Foreign Direct Investment (FDI) is an important means of boosting the agricultural sectors of developing economies. The first necessary step to formulate effective public policies to encourage agricultural FDI inflow to a host country is to develop a comprehensive understanding of the main determinants of FDI inflow to the agricultural sector, which is the main objective of the present study.
Design/methodology/approach
In view of this, we take a comprehensive approach to exploring the macroeconomic and institutional determinants of FDI inflow to the agricultural sector by examining a large panel data set on agricultural FDI inflows of 37 countries, investigating both groups of developed and developing countries, incorporating a large list of potentially relevant macroeconomic and institutional variables, and applying panel-data econometric models and estimation structures, including pooled, fixed-effects and random-effects regression models.
Findings
The general pattern of our findings implies that the degree of openness of an economy has a negative effect on FDI inflows to agricultural sectors, suggesting that the higher the degree of openness in an economy, the lower the level of agricultural protection against foreign trade and imports, and thus the less incentive for FDI to inflow to the agricultural sector of the economy. Additionally, our results show that economic growth (as an indicator of the rate of market-size growth in the host economy) and per-capita real GDP (as an indicator of the standard of living in the host country) are both positively related to FDI inflows to agricultural sectors. Our other results suggest that agricultural FDI tends to flow more to developing countries in general and more to those with higher standards of living and income levels in particular.
Originality/value
FDI inflow has not received much attention with respect to the identification of its main determinants in the context of agricultural sectors. Additionally, there are very few panel-data studies on the determinants of FDI, and even more surprisingly, there are no such studies on the main determinants of FDI inflow to the agricultural sector. We have taken a comprehensive approach by studying FDI inflow variations across countries as well as over time.
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Hajar Pouran Manjily, Mahmood Alborzi, Turaj Behrouz and Seyed Mohammad Seyed- Hosseini
This study aims to focused on conducting a comprehensive assessment of the technology readiness level (TRL) of Iran’s oil field intelligence compared to other countries with…
Abstract
Purpose
This study aims to focused on conducting a comprehensive assessment of the technology readiness level (TRL) of Iran’s oil field intelligence compared to other countries with similar oil reservoirs. The ultimate objective is to optimize oil extraction from this field by leveraging intelligent technology. Incorporating intelligent technology in oil fields can significantly simplify operations, especially in challenging-to-access areas and increase oil production, thereby generating higher income and profits for the field owner.
Design/methodology/approach
This study evaluates the level of maturity of present oil field technologies from the perspective of an intelligent oil field by using criteria for measuring the readiness of technologies. A questionnaire was designed and distributed to 18 competent oil industry professionals. Using weighted criteria, a mean estimate of oil field technical maturity was derived from the responses of respondents. Researchers evaluated the level of technological readiness for Brunei, Kuwait and Saudi Arabia’s oil fields using scientific studies.
Findings
None of the respondents believe that the intelligent oil field in Iran is highly developed and has a TRL 9 readiness level. The bulk of experts believed that intelligent technologies in the Iran oil industry have only reached TRL 2 and 1, or are merely in the transfer phase of fundamental and applied research. Clearly, Brunei, Kuwait and Saudi Arabia have the most developed oil fields in the world. In Iran, academics and executive and contracting firms in the field of intelligent oil fields are working to intelligently develop young oil fields.
Originality/value
This study explores the level of maturity of intelligent technology in one of Iran’s oil fields. It compares it to the level of maturity of intelligent technology in several other intelligent oil fields throughout the globe. Increasing intelligent oil fields TRL enables better reservoir management and causes more profit and oil recovery.
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Seyed Mojtaba Taghavi, Vahidreza Ghezavati, Hadi Mohammadi Bidhandi and Seyed Mohammad Javad Mirzapour Al-e-Hashem
This paper aims to minimize the mean-risk cost of sustainable and resilient supplier selection, order allocation and production scheduling (SS,OA&PS) problem under uncertainty of…
Abstract
Purpose
This paper aims to minimize the mean-risk cost of sustainable and resilient supplier selection, order allocation and production scheduling (SS,OA&PS) problem under uncertainty of disruptions. The authors use conditional value at risk (CVaR) as a risk measure in optimizing the combined objective function of the total expected value and CVaR cost. A sustainable supply chain can create significant competitive advantages for companies through social justice, human rights and environmental progress. To control disruptions, the authors applied (proactive and reactive) resilient strategies. In this study, the authors combine resilience and social responsibility issues that lead to synergy in supply chain activities.
Design/methodology/approach
The present paper proposes a risk-averse two-stage mixed-integer stochastic programming model for sustainable and resilient SS,OA&PS problem under supply disruptions. In this decision-making process, determining the primary supplier portfolio according to the minimum sustainable-resilient score establishes the first-stage decisions. The recourse or second-stage decisions are: determining the amount of order allocation and scheduling of parts by each supplier, determining the reactive risk management strategies, determining the amount of order allocation and scheduling by each of reaction strategies and determining the number of products and scheduling of products on the planning time horizon. Uncertain parameters of this study are the start time of disruption, remaining capacity rate of suppliers and lead times associated with each reactive strategy.
Findings
In this paper, several numerical examples along with different sensitivity analyses (on risk parameters, minimum sustainable-resilience score of suppliers and shortage costs) were presented to evaluate the applicability of the proposed model. The results showed that the two-stage risk-averse stochastic mixed-integer programming model for designing the SS,OA&PS problem by considering economic and social aspects and resilience strategies is an effective and flexible tool and leads to optimal decisions with the least cost. In addition, the managerial insights obtained from this study are extracted and stated in Section 4.6.
Originality/value
This work proposes a risk-averse stochastic programming approach for a new multi-product sustainable and resilient SS,OA&PS problem. The planning horizon includes three periods before the disruption, during the disruption period and the recovery period. Other contributions of this work are: selecting the main supply portfolio based on the minimum score of sustainable-resilient criteria of suppliers, allocating and scheduling suppliers orders before and after disruptions, considering the balance constraint in receiving parts and using proactive and reactive risk management strategies simultaneously. Also, the scheduling of reactive strategies in different investment modes is applied to this problem.