scholarly journals Comparison between SAW and WASPAS Methods in Determining the Location of the Transit Warehouse of PT. TG

2021 ◽  
Vol 4 (2) ◽  
pp. 393-403
Author(s):  
Frainskoy Rio Naibaho
Keyword(s):  
Corporate Strategy ◽  
Assessment Method ◽  
Five Factors ◽  
Weight Calculation ◽  
Weight Method ◽  
Ease Of Access ◽  
Product Assessment ◽  
Social Environmental ◽  
Social Environmental Factors ◽  
Benefits And Costs

This study aims to determine the location of the transit warehouse of PT. TG. For reasons of corporate strategy, so that PT. TG conducted a search for warehouse transit locations by considering five factors. The five factors are population density, distance from the head office, ease of access to the location, land price factors, and social environmental factors. The search for the location of the transit warehouse was carried out precisely to support the progress of the company. The five criteria are grouped into two types, namely benefits and costs. Management of PT. TG provides six alternative warehouse transit locations. Selection of location for the transit warehouse of PT. TG is important because the warehouse is an important facility in a company. The warehouse has an important role in ensuring the supply chain for inventory goods. The method used is the Simple Additive Weight method and the Weight Aggregated Sum Product Assessment method. The results of the weight calculation against the criteria produce an option that can help the management of PT. TG in making the decision for the location of the transit warehouse. One of the six alternatives will be selected based on the value of the largest V or Q calculation. The results of the processing of the SAW method and the WASPAS method show that Sunggal Subdistrict is the best location, with results V = 0.773 and Q = 0.746.

scholarly journals A-164 Influence of Executive Function, Partner Support, and Environmental Structure on Behavioral Weight Management Outcomes

2020 ◽  
Vol 35 (6) ◽  
pp. 958-958
Author(s):  
Gettens K ◽  
Gorin A
Keyword(s):  
Weight Loss ◽  
Executive Functions ◽  
Weight Management ◽  
Autonomy Support ◽  
Multilevel Models ◽  
Partner Support ◽  
Household Structure ◽  
Low Levels ◽  
Social Environmental ◽  
Social Environmental Factors

Abstract Objective Executive functions (EF) are crucial to successful weight management, yet few studies have prospectively explored the influence of social-environmental factors on the EF-weight loss (WL) link. This study examined interactions between EF, partner support, and household structure on weight loss outcomes in a couples-based intervention, grounded in Self-Determination Theory (SDT). Method Cohabitating dyads attended weekly weight loss groups (Ncouples = 64), Mage =54.0 ± 9.5, MBMI = 34.2 ± 5.4 kg/m2, 50% female, 88.8% Caucasian). Weight was measured at baseline and 6 months. The Behavior Rating Index of Executive Functions-Adult assessed 9 EF domains; higher scores indicate greater difficulty. Partner autonomy support (AS) was measured using the Important Other Climate Questionnaire, household structure with the Confusion, Hubbub, and Order Scale (CHAOS), IQ with the WASI-II 2-subscale estimate. Results Multilevel models were specified with MIXED linear function in SPSS to account for dyadic interdependence, controlling for age, education, IQ and group. Moderators (AS and CHAOS) were grand-mean centered. High and low levels were created at +1SD and -1SD. At high levels of AS, Shifting (B = 1.50, p = .01) and Inhibition (B = 2.23, p = .01) were associated with greater 6-month WL. At low levels of AS, Working Memory was associated with greater WL (p < .01). Self-Monitoring was associated with greater WL at high chaos (B = .43, p = .01), but not low chaos (p = 0.1). Conclusions Findings suggest that context matters; recruiting specific EFs may promote more WL for individuals embedded in low support or chaotic home environments. Future interventions should address the complexity of successful weight management, targeting both individual and social-interpersonal factors.

scholarly journals Effects of Behavioral Risk Factors and Social-Environmental Factors on Non-Communicable Diseases in South Korea: A National Survey Approach

2021 ◽  
Vol 18 (2) ◽  
pp. 612
Author(s):  
Nam Jeong Jeong ◽  
Eunil Park ◽  
Angel P. del Pobil
Keyword(s):  
Risk Factors ◽  
Environmental Factors ◽  
South Korea ◽  
Communicable Diseases ◽  
Behavioral Risk Factors ◽  
Behavioral Risk ◽  
Non Communicable Diseases ◽  
Path Analyses ◽  
Social Environmental ◽  
Social Environmental Factors

Non-communicable diseases (NCDs) are one of the major health threats in the world. Thus, identifying the factors that influence NCDs is crucial to monitor and manage diseases. This study investigates the effects of social-environmental and behavioral risk factors on NCDs as well as the effects of social-environmental factors on behavioral risk factors using an integrated research model. This study used a dataset from the 2017 Korea National Health and Nutrition Examination Survey. After filtering incomplete responses, 5462 valid responses remained. Items including one’s social-environmental factors (household income, education level, and region), behavioral factors (alcohol use, tobacco use, and physical activity), and NCDs histories were used for analyses. To develop a comprehensive index of each factor that allows comparison between different concepts, the researchers assigned scores to indicators of the factors and calculated a ratio of the scores. A series of path analyses were conducted to determine the extent of relationships among NCDs and risk factors. The results showed that social-environmental factors have notable effects on stroke, myocardial infarction, angina, diabetes, and gastric, liver, colon, lung, and thyroid cancers. The results indicate that the effects of social-environmental and behavioral risk factors on NCDs vary across the different types of diseases. The effects of social-environmental factors and behavioral risk factors significantly affected NCDs. However, the effect of social-environmental factors on behavioral risk factors was not supported. Furthermore, social-environmental factors and behavioral risk factors affect NCDs in a similar way. However, the effects of behavioral risk factors were smaller than those of social-environmental factors. The current research suggests taking a comprehensive view of risk factors to further understand the antecedents of NCDs in South Korea.

scholarly journals Location Selection for Smog Towers Using Zadeh’s Z-Numbers Integrated with WASPAS

2021 ◽  
Author(s):  
Janani Bharatraj
Keyword(s):  
Air Pollution ◽  
Fuzzy Sets ◽  
Degrees Of Freedom ◽  
Assessment Method ◽  
Weighted Sum ◽  
Membership Degree ◽  
Residential Areas ◽  
Location Selection ◽  
Degree Of Membership ◽  
Product Assessment

Fuzzy sets have been extensively researched and results have been developed based on the extensions of fuzzy sets. In this chapter, fuzzy sets and its extensions are discussed. Z-numbers along with weighted sum product assessment method is used to obtain a feasible solution to the location selection problem for installation of smog towers in a densely populated locality. The degrees of freedom namely degree of membership, degree of non-membership and the degree of hesitancy have been expressed as Zadeh’s Z-number with probability quotient for the degrees. Further, ranking of the alternatives based on Z-numbers and WASPAS to allocate smog towers to residential areas stricken by air pollution.

Association between autistic traits and home nurture environment: A community-based study

2020 ◽  
Author(s):  
Sheng Qian ◽  
Xin Xu ◽  
Ying-Quan Wang ◽  
Jia-vu Li ◽  
Rui-xia Jia ◽  
...  
Keyword(s):  
Multivariate Logistic Regression Analysis ◽  
Autistic Traits ◽  
Living Environment ◽  
Kindergarten Children ◽  
Physical And Mental Health ◽  
Public Health Programs ◽  
Health Domains ◽  
Social Environmental ◽  
High Level ◽  
Social Environmental Factors

Abstract Background: Increasing attention has been directed toward understanding the ways in which social environmental factors influence children’s behavior, in physical and mental health domains. Autistic traits are continuously distributed in general population and children with autistic traits have great risk of additional mental diseases. However, no literature has demonstrated the relation between autistic traits and home nurture environment.Methods: Caregivers of 408 kindergarten children (68% male) were recruited to complete a series of survey measures in China. The measures used were the Clancy Autistic Behavior Scale and the Home Nurture Environment Scale. Multivariate logistic regression analysis was used to examine the associations.Results: Frequent language/cognition stimulation (aOR 0.520, 95%CI 0.302-0.896), high level of parental warmth (aOR 0.596, 95%CI 0.392-0.905) and high quality of physical living environment (aOR 0.332, 95%CI 0.196-0.561) were the protective factors of autistic traits after controlling the confounding factors. Results were generally not moderated by the child’s gender or birth order.Conclusions: These findings highlight the importance of high levels of home nurture environment for autistic traits and indicate that public health programs should focus on guidance of parents for developing more adequate parenting skills and favorable home nurture environment.

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