No abstract

Marine Accident investigation multidimensional and complex, so this study aimed to provide a systematic approach to determining the degree of the most influential parameters (dimensions) in accident occurrence in order to improve marine safety in the direction of good governance. In this paper, two-phase procedures are proposed. The first stage utilizes the fuzzy Delphi method (FDM) to determine the critical factors of Marine Accident Investigation by interviewing the pertinent authorities. In the second stage, the fuzzy analytic hierarchy process (FAHP) is applied to pair fuzzy numbers as measurable indices and finally to rank by degree each influential criterion within accident investigation. This study considers 1 goal, 4 aspects, and 31 criteria (parameters) and establishes a ranking model that allows decision-makers to assess the prior ordering of reasons and sort by the most effective parameters involved in marine accident occurrence. The empirical study indicated that "People, working and living conditions, effect" is considered the highest ranking aspect, and "Ability, skills, and knowledge of workers" is considered the most important evaluation criterion overall by experts. These results were derived from fuzzy Delphi analytical hierarchy processing (FDAHP). A demonstration of the prior ordering of accident-causing parameters by authorities was addressed as well. Therefore, ranking the priority of every influential criterion (parameter) will help marine transportation decision makers emphasize the areas in which to improve in order to prevent future marine accidents.

Purpose Many industries accomplish green innovation for sustainable development, but it should play a significant role in the sustainable development and implementation of an organizations benefit. The purpose of this paper is to examine if green business innovation in terms of technology, organization, stakeholder and policies is able to develop competitive advantages. Design/methodology/approach This study was carried out in two stages and covered 4 variables and 21 indicators. Based on the experts’ opinions and literature review, a self-administered questionnaire was distributed among 113 experts of oil refining companies in Iran. The data were analyzed by the structural equation modeling technique. Findings The results indicated the effects of organizational factors, legislation, regulations and technology on green innovation. They also revealed the role of green innovation in reaching competitive advantages. Moreover, the relationship between stakeholder and green innovation was investigated. Practical implications The findings provide guidance on how firms can be better prepared for green innovation and get the most out of it and deal with the risks involved in green innovation, it is important that companies evaluate organization, technology and environment readiness and formulate corresponding strategies. Such a proactive approach can help enterprise control and minimize the risks of green innovation. A self-evaluation of the green innovation readiness of an enterprise helps the enterprise establish a mechanism to keep track of technological evolution. Originality/value This study contributes to the emerging field of green innovation which embed organization, technology, stakeholders, legislation and flows of the value created, delivered and captured in a value network. It also highlights the gaps in addressing the challenges of an innovative model for competitive advantages and suggests avenues for future research.

Dyslipidemia, a major risk factor for cardiovascular diseases, has become a global issue. Due to the variations in the prevalence of dyslipidemia, this study aimed to evaluate dyslipidemia and its associated factors in women of the Bandare-Kong Cohort Study (BKNCD). This study was conducted on women from the population-based BKNCD, as part of the Prospective Epidemiological Research Studies in IrAN (PERSIAN). Sociodemographic data, medical history, and anthropometric indices were collected. Dyslipidemia was defined as any lipid abnormality including low-density lipoprotein (LDL) ≥ 160, total cholesterol (TC) ≥ 240, high-density lipoprotein (HDL) < 40, or triglyceride > 200 mg/dl. From the 2223 women in this study (mean age: 48.28 ± 9.26 years), dyslipidemia was observed in 851 (38.3%). High TC was the most common lipid abnormality (18.5%) followed by high LDL (17.7%). Dyslipidemia was most prevalent among women aged 55–70 years, the married, those with < 6 years of education, the unemployed, the overweight or obese, with low socioeconomic status, diabetes, hypertension, and high waist circumference, those using the hookah and living in urban areas. Logistic regression revealed that women with high waist-to-hip ratio (WHR) (OR = 2.22, 95% CI 1.60–3.08), those aged 45–54 years (OR = 1.34, 95% CI 1.07–1.68) and 55–70 years (OR = 1.33, 95% CI 1.03–1.72), and those living in urban areas (OR = 1.35, 95% CI 1.05–1.73) were at significantly increased risk of dyslipidemia. In addition, the results were confirmed using deep neural network models. Dyslipidemia was highly prevalent in Iranian women in the southern coastal region. Central obesity, age over 45 years, and living in urban areas appear to be relatively significant risk factors for dyslipidemia among women.