Consumer-citizen willingness to pay for healthy eating messages

2019 ◽  
Vol 31 (2) ◽  
pp. 890-909 ◽  
Author(s):  
Yuxia Ouyang ◽  
Amit Sharma
Keyword(s):  
Willingness To Pay ◽  
Descriptive Analysis ◽  
Content Type ◽  
Health Warning ◽  
Warning Messages ◽  
Related Information ◽  
Warning Message ◽  
Home Context ◽  
Health Related ◽  
Amazon's Mechanical Turk

PurposeThe purpose of this study was to investigate the preference of health-warning message labeling in an eating-away-from-home context. The authors assessed individuals’ preference valuation of such messaging from a dual – consumer and citizen – perspective and with associated expected risk reduction (RR) level.Design/methodology/approachIn an online stated choice experiment on Amazon’s Mechanical Turk (N = 658), participants were asked to provide willingness to pay (WTP) preferences for health-warning messages and based on the expected RR from health-warning messages. Two types of multiple price list questions were used for consumer and citizen contexts. Interval regression and descriptive analysis methods were applied to analyze the data.FindingsThe study found that individuals placed a higher value (higher WTP) on health-warning message labeling when acting as citizens rather than as consumers. An RR expectation of 50 per cent was most effective in increasing participants’ WTP. Individuals who ate out frequently were more concerned about healthier food messages, and the influence of gender and age on WTP was conditional on individuals’ roles as consumers versus citizens.Originality/valueThis study extends the theory of consumer-citizen duality to the context of health-related information labeling, thus opening the discussion to extending such labeling from traditionally risky behavior such as alcohol and tobacco to also including food choice behavior. The authors also highlight implications on policy and industry practices to promote healthy food choices through such messages.

scholarly journals Reducing Packet Losses in Mobile Ad Hoc Network Using the Warning Message Generated from a Routing Node

2015 ◽  
Vol 62 (2) ◽  
pp. 141-145 ◽  
Author(s):  
Rezvi Shahariar ◽  
Abu Naser
Keyword(s):  
Energy Level ◽  
Total Energy ◽  
Packet Loss ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Critical Energy ◽  
Packet Losses ◽  
Warning Message ◽  
Mobile Ad Hoc

In mobile ad hoc network communication is performed usually by using only send and receive messages and every node is powered by limited energy from low capacity battery. Every send or receive message takes particular amount of energy from the node. So node’s total energy level gradually decreases each time while it is sending or receiving something. In this way node will die out and packets coming from the source will be dropped since one of the routing node on the current route is no longer functioning. These packet loss events are observed and minimized in this paper. In the proposed approach, when source receives Warning Message from any routing node on the ongoing route then it will stop sending packets on the ongoing route. Critical energy level of routing node has been defined to generate a Warning Message when routing node’s energy level reduces to critical energy level. DOI: http://dx.doi.org/10.3329/dujs.v62i2.21979 Dhaka Univ. J. Sci. 62(2): 141-145, 2014 (July)

scholarly journals The impact of pictorial warning attached on cigarette packet to the attitude of smoking habit

2020 ◽  
Vol 2 (Number 1) ◽  
pp. 20-23
Author(s):  
Dr. Kamrun Nahar ◽  
Prof. Dr. Belal Ahmed ◽  
Prof. Dr. Md. Khorshed Alam
Keyword(s):  
Smoking Habit ◽  
Sampling Technique ◽  
Age Group ◽  
Cross Sectional ◽  
Face To Face ◽  
Quit Smoking ◽  
Warning Message ◽  
Attitude And Practice ◽  
The Impact ◽  
Structured Questionnaire

This was a cross sectional descriptive study conducted to assess the effect pictorial warning message on cigarette packets to the attitude and practice of smokers using a semi-structured questionnaire employing purposive sampling technique with a sample size of 214 by face to face interview carried out in different cities, towns, and villages of Bangladesh from August 2016 to February 2017. Almost 97.6% were male and Most of the respondents (40.9%) belonged to the 20-29 years age group. Majority (58.3%) of them were educated from secondary to graduate few percent below primary. Highest 22.9% respondents were students followed by 17.6% private job holder, 16.9% day labor and only 1.4% was jobless. About 40.2% started smoking by the influence of friends, 26.2% started on curiosity and 20% due to depression and majority 41.0% smoked 1-5 cigarette sticks per day. More than half (65.5%) of respondents felt relax to refreshing by smoking and about two third 77.6% continued their smoking due to habitual act or psychological pleasure Almost 93.4% gave attention to the pictorial warning on the cigarette packets. About 46.4% thought pictorial warning in cigarette packets alarms for not to smoke and only 23.8% thought smoking will cause cancer; 21.4% thought smoking is injurious to health. After seeing the pictorial warning on cigarettes 57.6% reduced the smoking number of sticks per day also attempted to quit smoking. To reduce this restricting the advertisement of tobacco, arranging campaign to raise awareness among people about the health and environmental hazards of smoking and increase the tax on tobacco.

scholarly journals COVID-19: Role of Deep Learning and Cloud Through Identification of Kidney, Pancreas and Intestine

2021 ◽  
Author(s):  
Arulmozhiselvan L ◽  
Uma E ◽  
Jayasri R
Keyword(s):  
Neural Network ◽  
Cloud Computing ◽  
Acute Pancreatitis ◽  
Vital Role ◽  
Patient Records ◽  
Smart System ◽  
Warning Message ◽  
User Data ◽  
Post Infectious

Worldwide human health and economic has been affected due to the ongoing pandemic of corona virus (COVID-19). The major COVID-19 challenges are prevention, monitoring and FDA approved vaccines. IOT and cloud computing play vital role in epidemic prevention and blocking COVID-19 transmission. Mostly lungs and hearts are affected. Other than lungs many parts are affected which are not considered as prominent conversational cue. In this paper, we have proposed smart system that is effective through detection of pancreas, kidney and intestine. It detects acute pancreatitis, protein leak, microscopic blood leak, post infectious dysmotility and gastrointestinal bleeding. The data from the edge devices are collected and mapped into the cloud layer. The cloud consists of COVID-19 patients medical records which compare the user data with the existing patient records. Once the data matches it sends warning message to the user regarding the result of affected parts. Based on the result from KPI system, it analyzes with all data and using deep Convolutional Neural Network (CNN) it classifies whether the pancreas, kidney and intestine are affected or not due to COVID-19.

Development of Method for Measurement Sound Pressure Level to Use Earphone

2013 ◽  
Vol 717 ◽  
pp. 378-383
Author(s):  
Seok Hoon Kang ◽  
Hyuk Moon
Keyword(s):  
Hard Of Hearing ◽  
Sound Pressure ◽  
Measured Data ◽  
Pressure Level ◽  
Experimental Equipment ◽  
Warning Message ◽  
The Hours ◽  
Set Up ◽  
And Control ◽  
Widespread Dissemination

Earphone use has skyrocketed due to the widespread dissemination of portable acoustic-apparatus. As the result, hearing loss due to noise-induced is becoming a big social problem. As the existing method, warning message is only used to prevent the hard of hearing according to the earphone use. However, it is hard for users to know the effect of the hours of earphone use and volume on their hearing, and control the earphone use by themselves. Therefore, in this paper, the method is suggested that users measure the effect of the time and volume of earphone use on their hearing with the simple experimental equipment and program. The method suggested in this paper is based on the simple experimental equipment to set up the similar environment to the real ear, and the program to find out the effect on hearing with the measured data.

New Lane Departure Warning System Based on Side-View Cameras

2015 ◽  
Vol 764-765 ◽  
pp. 1361-1365
Author(s):  
Cheng Yu Chiu ◽  
Chih Han Chang ◽  
Hsin Jung Lin ◽  
Tsong Liang Huang
Keyword(s):  
Warning System ◽  
Side View ◽  
Lane Departure Warning ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Warning Messages ◽  
Warning Message ◽  
Lane Departure ◽  
Assistance Systems ◽  
The Right

This paper addressed a new lane departure warning system (LDWS). We used the side-view cameras to promote Advanced Driver Assistance Systems (ADAS). A left side-view camera detected the right lane next to vehicle, and a right side-view camera detected the right lane. Two cameras processed in their algorithm and gave warning message, independently and separately. Our algorithm combined those warning messages to analyze environment situations. At the end, we used the LUXGEN MPV to test and showed results of verifications and tests.

scholarly journals Toward Intelligent Human Machine Interactions

2017 ◽  
Vol 139 (06) ◽  
pp. S4-S8 ◽  
Author(s):  
Yingzi Lin
Keyword(s):  
Control Strategy ◽  
Driver Assistance System ◽  
Effective Means ◽  
Rehabilitation Robotics ◽  
Driver Assistance ◽  
Human Errors ◽  
Important Method ◽  
Warning Message ◽  
Powerful Research Tool ◽  
Assistance Systems

This article discusses the concept of human assistance systems (HAS) and research works to design the interface of HAS. It also focuses on the issue of how humans and HAS collaborate with each other during such interactions. HAS are expected to detect and compensate for human errors. In a case that a machine is a part of the team to complete an operation, it is highly desired that HAS collaborate with humans effectively. Advances on HAS have been made within application areas including vehicle driving, pilot–flight interfaces, healthcare and rehabilitation, robotics, etc. One important method for studying driver assistance system (DAS) is the availability of a powerful research tool, as the simulator is an effective means to generate real-world traffic scenarios without putting drivers in any real danger. A control strategy for HAS been investigated, especially for DAS. The goal is to provide a warning message and/or intervention to the driver if necessary to avoid hitting objects on road while not frustrating the user.

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