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Insight
Published in Wanda Grimsgaard, Design and Strategy, 2023
Secondary data: Secondary data are information and research data not collected directly from the source but gathered by others, often for a different purpose and problem statement than the current one. The advantage of secondary data is that they are most often readily available, i.e. in surveys and statistics, reports, theses, books, research data and the like, and they are usually free of charge. It is important to examine the credibility of the source and to try to uncover possible factors allowing for error. The use of qualitative secondary data is about interpreting texts collected by others and making a critical assessment of whether the information is suitable for the problem statement at hand. It can be an advantage to use different types of data, both primary data and secondary data, because different data can be compared and used to verify each other, support each other and contrast different information and thereby help to strengthen the result.
Identifying and sourcing data for secondary research
Published in Emmanuel Manu, Julius Akotia, Secondary Research Methods in the Built Environment, 2021
Emmanuel Manu, Julius Akotia, Saad Sarhan, Abdul-Majeed Mahamadu
There should also be awareness of the danger of bias being introduced into some pre-existing datasets (e.g. data from social media, government data), because of potential manipulation of data for political purposes in an era of post-truth and fake news. To ensure the reliability of secondary data, it should be reproducible, ensuring that if the systematic processes used to obtain and analyse the data are repeated, the same or similar results would be achieved. With research that relies on API-generated, social media datasets such as data from Twitter, there are limitations in this regard owing to the unknown logic of the algorithm that is used to produce the data (Felt, 2016). Also, it might not be possible to replicate Twitter datasets fully using API tools, as this is constantly changing, making it difficult to replicate and verify the findings independently (Felt, 2016). In terms of timeliness, data must be checked to ensure that they reflect the time period that governs the analysis (Rabianski, 2003), avoiding the use of outdated data in exploring time-sensitive research questions. As a general guide, Johnston (2014) suggested that to apply secondary data for research successfully, a systematic process is required, in which the challenges of the existing data are acknowledged and the distinct characteristics of the data are addressed within the analysis.
Basic Instrumentation
Published in Vinayak Bairagi, Mousami V. Munot, Research Methodology, 2019
Pradeep B. Mane, Shobha S. Nikam
Skilled personnel are required for data collection. Unskilled person in data collection may give inadequate data of the research (ii) Secondary data:The data which has already been collected by someone else, analysed and statistically processed is called as secondary data. It has been collected by someone not related to the current research field but collected this data for some other motive and at different time in the past. If the researcher uses this data to make conclusions then this becomes secondary data for the researcher. Secondary data may be available in written, typed or in electronic forms. Sources of secondary information are available to the researcher for assembling data on an industry, market place and potential product applications. The researcher gains an initial insight into the research problem from secondary data. Secondary data can be of internal or external type. If information is acquired within the organization where research is being carried out the data is called as internal or in-house secondary data. If data is obtained from outside sources then data is called as external secondary data. Advantages and disadvantages of using secondary data are listed here.
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).
Forming and Living in a Seniors’ Cohousing: The Impact on Older Adults’ Healthy Aging in Place
Published in Journal of Housing For the Elderly, 2019
This study was a secondary data analysis of qualitative data from a previous study conducted to examine older adults’ quality of life (QOL). A secondary data analysis involves analyzing existing data to answer a new research question or conducting a new research with information from a primary data that was initially collected for another purpose (Koberich, Lohrmann, & Dassen, 2014; Riegel & Dickson, 2016; Szabo & Strang, 1997). Some of the advantages of secondary data analysis include gaining a new insight on a topic, contributing to knowledge, reducing burden on participants and cost to researchers (Koberich et al., 2014; Riegel & Dickson, 2016; Szabo & Strang, 1997). In this manuscript, the author conducted a secondary analysis of the qualitative data because of the fitness between the original research question and that of the secondary analysis (Koberich et al., 2014; Riegel & Dickson, 2016; Szabo & Strang, 1997).
Impact of digitalization on procurement: the case of robotic process automation
Published in Supply Chain Forum: An International Journal, 2020
The secondary data came from the company websites as well as internal documents (project documentation, examples of success stories/quick wins, digitalisation/RPA training materials). The data also covered field observations of the companies we visited. In addition, this process resulted in a verification study of the interviews. Secondary data can be helpful in the research design of subsequent primary research and can provide a baseline with which the collected primary data results can be compared to. The combination of the data collected enables us to assume internal validity.