A Lifetime of Memories: Raymond Kesner’s Contributions of the Attribute Model in Understanding Amnesia

2015 ◽  
pp. 137-149
Author(s):  
Naomi J. Goodrich-Hunsaker ◽  
Ramona O. Hopkins
Keyword(s):  
Attribute Model

scholarly journals SIKAP DAN KEPUASAN KONSUMEN DALAM PEMBELIAN BOLEN PISANG CV MAYANG SARI DI KOTA BANDAR LAMPUNG

2021 ◽  
Vol 9 (4) ◽  
pp. 693
Author(s):  
Reza Dwi Meisanto ◽  
Rabiatul Adawiyah ◽  
Eka Kasymir
Keyword(s):  
Performance Analysis ◽  
Customer Satisfaction ◽  
Survey Method ◽  
Product Packaging ◽  
Satisfaction Index ◽  
Customer Satisfaction Index ◽  
Attribute Model ◽  
Purchasing Patterns ◽  
Data Analysis Methods ◽  
Good Attitude

This study aims to determine attitudes, purchasing patterns and customer satisfaction on banana bolen CV Mayang Sari. This research method uses a survey method. Samples of this study consisted of 40 consumers who had purchased and / or consumed banana bolen 3 times. The data analysis methods used were descriptive, Fishbein's Multi-attribute model, Customer Satisfaction Index (CSI) and Importance Performance Analysis (IPA). The attributes used in this study are price, taste, flavor variants, size, texture, product packaging, and accessibility). The results showed that consumers liked banana bolen or had a good attitude with an Ao value of 132.52, the pattern of buying banana bolen CV Mayang Sari by 52.50 percent consumers, namely two boxes (20 pieces) of banana bolen in one transaction with the flavor variant that consumers are most interested in is chocolate 55 percent. The frequency of consumer purchases is 90 percent made once a month, customer Satisfaction Index (CSI) in consuming banana bolen CV Mayang Sari is in the very satisfied criteria, which is equal to 83.82 percent. Based on Importance Performance Analysis (IPA), there is one attribute that falls into quadrant I (Main Priority), namely the taste attribute. In quadrant II (Maintain Achievement) there is one attribute, namely the price attribute, while in quadrant III (Low Priority) there are attributes of size and ease of obtaining products, and in quadrant IV (Excessive) there are several attributes, namely texture, flavor variants, and product packaging.Key words: attitude, banana bolen, CSI, IPA

A Multi-Brand/Multi-Attribute Model of Tourist State Choice

1978 ◽  
Vol 17 (1) ◽  
pp. 23-29 ◽  
Author(s):  
Douglas R. Scott ◽  
Charles D. Schewl ◽  
Donald G. Frederick
Keyword(s):  
Attribute Model

Research on Building and Analysis for Attribute Model in Quality Evaluation of Domain Software

2016 ◽  
pp. 752-758
Author(s):  
Jian Su ◽  
Lu Han ◽  
Yue Li ◽  
Shufen Liu ◽  
Zhilin Yao ◽  
...  
Keyword(s):  
Quality Evaluation ◽  
Attribute Model

Novel framework for image attribute annotation with gene selection XGBoost algorithm and relative attribute model

2019 ◽  
Vol 80 ◽  
pp. 57-79 ◽  
Author(s):  
Hongbin Zhang ◽  
Diedie Qiu ◽  
Renzhong Wu ◽  
Yixiong Deng ◽  
Donghong Ji ◽  
...  
Keyword(s):  
Gene Selection ◽  
Attribute Model

Energy-Oriented Maintenance Decision-Making for Sustainable Manufacturing Based on Energy Saving Window

2018 ◽  
Vol 140 (5) ◽  
Author(s):  
Tangbin Xia ◽  
Lifeng Xi ◽  
Shichang Du ◽  
Lei Xiao ◽  
Ershun Pan
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Energy Savings ◽  
Sustainable Manufacturing ◽  
Green Manufacturing ◽  
Energy Reduction ◽  
Efficient Manner ◽  
Line Energy ◽  
Industrial Enterprises ◽  
Attribute Model

In recent years, the industry's responsibility to join in sustainable manufacturing becomes huge, while innovating sustainability has been a new trend. Industrial enterprises are pursuing energy reduction to meet future needs for sustainable globalization and government legislations for green manufacturing. To run a manufacturing line in an energy-efficient manner, an energy-oriented maintenance methodology is developed. At the machine layer, the multi-attribute model (MAM) method is extended by modeling the energy attribute. Preventive maintenance (PM) intervals of each machine are dynamically scheduled according to the machine deterioration, maintenance effects, and environmental conditions. At the system layer, a novel energy saving window (ESW) policy is proposed to reduce energy for the whole line. Energy consumption interactivities, batch production characteristics, and system-layer maintenance opportunities are comprehensively considered. Real-time choice of PM adjustments is scheduled by comparing the energy savings of advanced PM and delayed PM. The results prove the energy reduction achieved by this MAM-ESW methodology. It effectively utilizes standby power, reduces energy consumption, avoids manufacturing breakdown, and decreases scheduling complexity. Furthermore, this energy-oriented maintenance framework can be applied not only in the automotive industry but also for a broader range of manufacturing domains such as the aerospace, semiconductor, and chemical industries.

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