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The role of social media marketing and environmental knowledge on green skincare purchase intention
Published in Siska Noviaristanti, Contemporary Research on Management and Business, 2023
The present study used a non-probability sampling technique using a purposive method. Data were collected by an online questionnaire to 372 respondents in Indonesia and 356 usable questionnaires were obtained after removal of the outliers. Only social media active users and consumers who had never bought green skincare were allowed to complete the questionnaire. All measurement items on questionnaires were obtained from previous research and measured using a five-point Likert scale (1=Strongly Disagree, 5=Strongly Agree). The collected data were analyzed using structural equation modeling (SEM) with Amos 26.0 software package. Firstly, the outliers were removed to obtain clean data before further analysis and a normality test was performed using SPSS 25 to achieve a normal distribution result for SEM analysis. In SEM analysis, the researchers conducted measurement model testing to perform CFA and structural model testing to analyze the relationship between variables. In this study, the researchers examined the direct and indirect effect of variables to better understand which variables showed a significant effect toward green skincare products purchase intention.
Inference from probability and nonprobability samples
Published in Uwe Engel, Anabel Quan-Haase, Sunny Xun Liu, Lars Lyberg, Handbook of Computational Social Science, Volume 2, 2021
Rebecca Andridge, Richard Valliant
Nonprobability surveys capture participants through various methods. The AAPOR task force on nonprobability sampling (Baker et al., 2013a) characterized these samples into three broad types: Convenience samplingSample matchingNetwork sampling Convenience sampling is a form of nonprobability sampling in which easily locating and recruiting participants is the primary consideration. No formal sample design is used. Some types of convenience samples are mall intercepts, volunteer samples, river samples, observational studies, and snowball samples. In a mall intercept sample, interviewers try to recruit shoppers to take part in a study. Usually, neither the malls nor the people are probability samples.
The influence of financial attitudes, financial literacy, and parental income on personal financial management (A case study of students of Bandung)
Published in Indira Rachmawati, Ratih Hendayani, Managing Learning Organization in Industry 4.0, 2020
We examined three main research questions: whether financial attitude, financial literacy, and parental income have a significant influence on personal financial management. This study used three independent variables – X1 (financial attitude), X2 (financial literacy), and X3 (parental income) – and used Y for the dependent variable (personal financial management). This study also examined whether students’ personal financial management in Bandung can be categorized as good. The sampling technique used in this study was a nonprobability sampling technique. Four hundred respondents were used as samples in this study with the limitation of Bandung students age fifteen to twenty-four years, with the determination of the sample using the Slovin method. n=N1+Ne2n=240.9431+240.943(5%)2n=240.943603,3575n=399,33~400
Breaking Status-Quo Inertial Use of Incumbent Payment to Adopt Mobile Payment: A Contingency Perspective
Published in International Journal of Human–Computer Interaction, 2023
This study applies a non-probability sampling method with purposive sampling technique. Non-probability sampling is a common technique in surveying mobile payment adoption (Andavara et al., 2021). It involves selecting samples based on the research subjects rather than via random selection (Etikan & Bala, 2017). Purposive sampling is a type of non-probability sampling technique which is used to select sample units according to the researchers’ judgment (Chou & Liu, 2016). This sampling method is based on deliberate choices of a participants due to participants’ qualities, which makes up for the improper collection of data. It also quickly extracts the required samples in line with the researchers’ judgment and sets out to find highly motivate people who are willing to provide information of their knowledge and experience. Therefore, collecting samples through a purposive sampling technique not only improves research efficiency but also reduces experimental costs. More importantly, it ensures that the samples are representative of the topic discussed in this study (Baltes & Ralph, 2022).
Mobile 3D body scanning applications: a review of contact-free AI body measuring solutions for apparel
Published in The Journal of The Textile Institute, 2023
Sadia Idrees, Simeon Gill, Gianpaolo Vignali
In the first phase, the applications were identified writing keywords ‘3D body scanning mobile applications, 3D body scanner, 3D body scanning application’. The keyword searches and identified applications names further lead to identifying various 3D body scanning apps. The data was obtained from peripheral databases sources such as Google, Google scholar, App store, Google play and academic publication for initial search of 3D body scanning apps. The sampling method adopted for data collection was snowball sampling. Snowball sampling is a non-probability sampling method. In this sampling technique the existing subjects provide referrals for recruitment of identical samples needed for a research study (Goodman, 1961). Therefore, this sampling technique has been employed to find out the existing 3D Body scanning mobile applications through online secondary data sources. Secondary data is the data compiled from prior studies, interfaces and books (Ghauri & Gronhaug, 2010). Secondary data is essential as it supports identification of the research problem and describing the research questions, assisting to formulate project, elucidate the data, provide awareness and validate the conclusions (Malhotra et al., 2012).
The impact of COVID-19 on academic aeromobility practices: Hypocrisy or moral quandary?
Published in Mobilities, 2023
Sherry H. Y. Tseng, Craig Lee, James Higham
At the end of the phase 1 survey, a question was included asking respondents to indicate their willingness to participate in follow-up interviews. This process generated 120 expressions of interest. Because of the high interest levels, a quota sampling procedure was implemented to select interviewees to ensure time efficiency and to gain various and balanced insights across different genders, divisions, and academic positions (Moser 1952). Quota sampling is a non-probability sampling method that allows researchers to access the sample representing the population (Etikan and Bala 2017). When selecting the interview participants, the study set out to interview one person from each position within each division while maintaining gender balance. Following the UoO’s structure, one Professor, one Associate Professor, one Senior Lecturer, and one Lecturer from each division were selected. In addition, due to the unique structures of the Divisions of Health Sciences and Sciences, one Post-doctoral Fellow and one Research Fellow were also selected. In some cases, participants were reselected when the gender or position distribution was imbalanced or participants refused to attend.