scholarly journals Are Online Shoppers Interested in Learning about Locally Grown Fresh Produce?

2018 ◽  
Vol 10 (3) ◽  
pp. 42
Author(s):  
Jean Dominique Gumirakiza ◽  
Thomas Kingery ◽  
Stephen King
Keyword(s):  
Clustering Algorithm ◽  
Word Of Mouth ◽  
Fresh Produce ◽  
Logit Models ◽  
Public Places ◽  
Online Shoppers ◽  
Locally Grown ◽  
To Receive ◽  
Analyze Data ◽  
Educational Information

This study describes online shoppers, explains their interests in learning about market outlets for locally/regionally grown fresh produce, and analyzes their preferences for channels to receive educational information concerning local/regional fresh produce. We used a K-mean clustering algorithm together with binary and ordered Logit models to analyze data collected in 2016 from a stratified randomly selected sample of 1,205 online shoppers within the U.S. South region. We found that the probability for online shoppers to be interested in learning about market outlets for local/regional grown fresh produce is 66 percent. Results also indicate that the likelihood for the word-of-mouth to be at least preferred (preferred, very preferred, and extremely preferred) as channel to receive educational information about local fresh produce is 69 percent. The probabilities for local radio/TV stations, Internet-based, newspapers, and ads on public places to be at least preferred are 61 percent, 48 percent, 57 percent, and 66 percent respectively. Findings from this study are useful for fresh produce growers, agricultural marketers and educators, online shoppers, and further research studies.

scholarly journals The Willingness to Pay for Local, Domestic, and Imported Bundled Fresh Produce by Online Shoppers

2018 ◽  
Vol 10 (12) ◽  
pp. 15
Author(s):  
Jean D. Gumirakiza ◽  
Taylor Choate
Keyword(s):  
United States ◽  
Willingness To Pay ◽  
Online Shopping ◽  
Positive Impact ◽  
Fresh Produce ◽  
The United States ◽  
Online Shoppers ◽  
Interest Level ◽  
Different Origins ◽  
Locally Grown

This study applies a Censored Normal Tobit Model on the 2016 survey data from 1,205 online shoppers in the South region of the United States to explain their Willingness To Pay (WTP) for a bundle of fresh produce from different origins. This study indicates that online shoppers are willing to pay $6.91, $6.38, and $5.22 for four pounds of bundled fresh produce that are locally, domestically grown, and imported respectively. We found that income category, interests in online shopping, interest level for local, interest level for organic, and monthly spending on fresh produce have a significant positive impact on the WTP for locally grown fresh produce. Results indicate that being married, high income, interests in online shopping, interests in local produce, interests in organic, and the monthly spending on fresh produce increase the WTP for domestically grown fresh produce, while age and being a female diminishes it. We further found that age, being a female, and interest in the freshness of the produce decrease the WTP for imported produce. Based on the findings from this study, we have suggested a couple of marketing implications and suggestions.

scholarly journals Most Preferred Market Venues for Locally Grown Fresh Produce among Online Shoppers

2017 ◽  
Vol 9 (10) ◽  
pp. 26 ◽  
Author(s):  
Jean D. Gumirakiza ◽  
Sarah M. VanZee
Keyword(s):  
Fresh Produce ◽  
Marketing Strategies ◽  
Farmers Markets ◽  
Grocery Stores ◽  
Relative Probability ◽  
Future Studies ◽  
Online Purchases ◽  
Online Shoppers ◽  
Locally Grown ◽  
On Farm

This paper examines the most preferred market venues online shoppers use when purchasing locally/regionally grown fresh produce. We surveyed 1,205 consumers who made online purchases at least twice within six months prior to participating in this study. We call these consumers “online shoppers”. The study was conducted in the Southern region of the U.S. We collected data using Qualtrics actively managed market research panels and social media such as Facebook, and Twitter. Results indicate that grocery stores are the most preferred market venue online shoppers use to purchase locally/regionally grown fresh produce with a relative probability of 44 percent. Farmers’ markets are the second most preferred market venues with a likelihood of 33 percent. The third market venue is on-farm/CSA programs with relative probability of seven percent. Online markets are currently the fourth most frequented with a likelihood of five percent. 11 percent have no particular most preferred market venue. This analysis is significant to fresh produce growers and marketers. Results suggest new marketing strategies to conveniently make fresh produce accessible among online shoppers. Furthermore, this study is useful for future studies with interests in explaining the preferred market venues for local/regional fresh produce among online shoppers.

scholarly journals The Most Preferred Food Labels Among Online Shoppers

2018 ◽  
Vol 10 (10) ◽  
pp. 76
Author(s):  
Jean D. Gumirakiza ◽  
Sarah M. VanZee
Keyword(s):  
Logistic Model ◽  
Fresh Produce ◽  
Food Products ◽  
Multinomial Logit Model ◽  
Food Labels ◽  
Relative Probability ◽  
Online Shoppers ◽  
Organically Grown ◽  
Binary Logistic Model ◽  
Locally Grown

This study explains the most preferred food labels among online shoppers when purchasing food products. The study uses data from an online-based survey conducted in 2016. Participants are 1,205 online shoppers residing within the South region of the U.S. Using a binary logistic model, we found that the likelihood for online shoppers to consider food labels (other than prices) into their purchasing decision-making is 86 percent. Using a multinomial logit model, we found that the relative probability for “locally grown” labels to be the most important is 46 percent, 7 percent for “organically grown”, 24 percent for both local and organic, and 23 percent for other kinds of labels. The most common other important labels among this last group include nutrition contents, and country of origin. This study is significant to fresh produce growers and agricultural marketers because it provides an explanation of food labels those online shoppers consider to be the most important when shopping for fresh produce. It is significant to food products regulators who are interested in enforcing regulations related to food labels. Future researchers will find this analysis useful when furthering knowledge about this increasingly popular market venue.

A Study on Pre and Post-Purchase Behaviour Exhibited by Online Shoppers – Special Reference to Shoppers of Amazon.in

2019 ◽  
Vol 118 (6) ◽  
pp. 100-102
Author(s):  
D.David Winster Praveenraj ◽  
A. Prasanth
Keyword(s):  
Special Reference ◽  
Word Of Mouth ◽  
Online Delivery ◽  
Purposive Sampling ◽  
Online Shoppers ◽  
Delivery Services ◽  
Post Purchase ◽  
Consumer's Perception

Usually, in a process of purchasing products at Amazon.in, several steps are required to purchase the products where the consumer begins to navigate through the advertisements, internet and word of mouth, then search the products on search bar to purchase the products. In general, the process requires the customer to be seated before beginning. This study aims to discuss the consumer's perception of online products purchasing and delivery services in Karur. The survey was conducted among 100 respondents who were selected based on purposive sampling. The research focuses on the study and analysis of data collected from all those users who already use online delivery services.

scholarly journals The Impact of Diurnal Preferences on Customer Satisfaction, Word of Mouth and Repurchasing: A Study in Indian College Online Shoppers

2020 ◽  
Vol 16 (1) ◽  
pp. 21-30 ◽  
Author(s):  
Larry Sau Kei Leung
Keyword(s):  
Customer Satisfaction ◽  
Sampling Method ◽  
Word Of Mouth ◽  
Online Shopping ◽  
Snowball Sampling ◽  
Online Retail ◽  
Online Shoppers ◽  
Managerial Implications ◽  
Positive Word Of Mouth ◽  
The Impact

The importance of positive word of mouth (WOM) and repurchasing in competitive online retail environments demands their further study. Although customer satisfaction has been found to drive positive WOM and repurchasing, limited research has explored what type of customers feel more satisfied with online shopping. It was anticipated that the convenient nature of online shopping would better match the conscientious personality traits of customers with earlier sleep and wake times. Data collected from 334 Indian college students participating in this study using a snowball sampling method were analysed by multiple regression. As hypothesised, based on self-congruency theory, customers with earlier sleep and wake times were found to feel more satisfied with online shopping, which in turn enhanced their positive WOM and increased repurchase intention. Theoretical and managerial implications are discussed.

scholarly journals A study of the microbial contamination in imported and domestic fresh produce at retail level in Ontario.

2021 ◽  
Author(s):  
Rebecca Chung
Keyword(s):  
Microbial Contamination ◽  
Heterotrophic Bacteria ◽  
Statistical Significance ◽  
Fresh Produce ◽  
E Coli ◽  
Foodborne Outbreaks ◽  
Locally Grown

Globalization has enabled the year-round availability of imported fresh produce in Toronto, supplementing the variety of locally grown produce in Ontario. Increased consumption of produce has led to more foodborne outbreaks, with E. coli O157:H7 as the second most frequent cause of illnesses. In this study, the levels of heterotrophic bacteria, coliforms, and generic E. coli were compared between three types of imported and local produce. Significantly higher levels (p<0.04) of heterotrophic bacteria were found in imported basil. Local romaine (p<0.01) and local spinach (p<0.001) contained significantly higher levels of coliforms. Local spinach also had a significantly higher (p<0.005) number of samples with coliform levels above 100 CFU/g. Although no statistical significance was found between the presence of E. coli and origin of produce, the five imported samples positive for E. coli compared to zero local samples supports the hypothesis that imported produce is more susceptible to microbial contamination.

scholarly journals Dynamic Euclidean K-Means Clustering Algorithm in Data Mining

2019 ◽  
Vol 8 (4) ◽  
pp. 11129-11133
Keyword(s):  
Data Mining ◽  
Euclidean Distance ◽  
Clustering Algorithm ◽  
Threshold Value ◽  
Distance Metrics ◽  
Processing Data ◽  
Data Grouping ◽  
Logical Information ◽  
Analyze Data ◽  
Squared Euclidean Distance

Data mining was the practice of processing data in order to derive interesting patterns as well as designs from the system used to analyze data. Grouping was the process of grouping artifacts even though that items in almost the same category are more identical than items in other classes. The existing system main drawbacks are not able to show clear logical information about the market analysis and cannot summarize the strength, weakness, opportunities and threats. Among these clustering is considered as a significant technique to capture the structure of data. Data mining adds to clustering is complicated to retrieve Wide databases with either a variety of different forms of attributes. This includes special specific clustering strategies with Euclidean K-Means grouping process. The power of k-means algorithm is due to its computational efficiency and the nature of ease at which it can be used. In this technique the threshold value is used to determine the information is the same category or even a new team is formed. Proposing an Euclidean K-means algorithm is a necessity. The squared Euclidean distance metric results of the suggested algorithm are tested in this journal experimental results. Distance metrics are used to build reliable features and functionality including grouping for data mining. The simulation process is carried out in MATLAB tool and outperforms the proposed results.

Neurologic Complications in Obstetric Anesthesia

2018 ◽  
Author(s):  
Marjorie Gloff ◽  
Melissa Kreso ◽  
Richard Wissler
Keyword(s):  
Postpartum Period ◽  
Word Of Mouth ◽  
Obstetric Anesthesia ◽  
Neuraxial Anesthesia ◽  
Neurologic Complications ◽  
Mainstream Media ◽  
Neuraxial Analgesia ◽  
Obstetric Population ◽  
Word Of Mouth Communication ◽  
To Receive

Neuraxial analgesia and anesthesia is routinely requested for women in the peripartum and postpartum period. Given that there is widespread knowledge of the benefits of obstetricians, mainstream media, and word-of-mouth communication, many patients expect to receive some form of neuaxial anesthesia during their peripartum experience. Neuraxial anesthesia can provide both pain relief during induction and labor and can provide surgical anesthesia for a variety of surgical procedures in the peripartum and postpartum period. While generally considered safe, neuraxial anesthesia is not without risk. This chapter discusses the most common neurologic complications associated with neuraxial anesthesia in the obstetric population.

scholarly journals Optimal Frontier-Based Autonomous Exploration in Unconstructed Environment Using RGB-D Sensor

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6507 ◽  
Author(s):  
Liang Lu ◽  
Carlos Redondo ◽  
Pascual Campoy
Keyword(s):  
Clustering Algorithm ◽  
Information Gain ◽  
State Of The Art ◽  
Search And Rescue ◽  
Autonomous Exploration ◽  
Aerial Robots ◽  
Exploration Time ◽  
Feasible Path ◽  
Path Planner ◽  
To Receive

Aerial robots are widely used in search and rescue applications because of their small size and high maneuvering. However, designing an autonomous exploration algorithm is still a challenging and open task, because of the limited payload and computing resources on board UAVs. This paper presents an autonomous exploration algorithm for the aerial robots that shows several improvements for being used in the search and rescue tasks. First of all, an RGB-D sensor is used to receive information from the environment and the OctoMap divides the environment into obstacles, free and unknown spaces. Then, a clustering algorithm is used to filter the frontiers extracted from the OctoMap, and an information gain based cost function is applied to choose the optimal frontier. At last, the feasible path is given by A* path planner and a safe corridor generation algorithm. The proposed algorithm has been tested and compared with baseline algorithms in three different environments with the map resolutions of 0.2 m, and 0.3 m. The experimental results show that the proposed algorithm has a shorter exploration path and can save more exploration time when compared with the state of the art. The algorithm has also been validated in the real flight experiments.

The Effect of Review Characteristics on Website Diagnosticity: A Conceptual Framework

2015 ◽  
Vol 4 (3) ◽  
Author(s):  
Amar Raju G.
Keyword(s):  
Conceptual Framework ◽  
Conceptual Model ◽  
Word Of Mouth ◽  
Online Reviews ◽  
Online Review ◽  
The Past ◽  
Online Shoppers ◽  
Managerial Implications ◽  
The Many ◽  
Word Of Mouth Communication

Online review is a form of electronic word-of-mouth communication that has received much attention from authors in the past decade. There are several characteristics of online reviews which have been investigated in the literature. Also the many benefits that these reviews provide to online shoppers have been extensively studied. The present paper proposes a conceptual model to show how these benefits can make a website more diagnostic. Based on the model a few propositions have been discussed. Theoretical and managerial implications along with the limitations of the study are also provided.

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