Research Methodology is the process used to collect information and data for the purpose of making business decisions. The success of a research project is entirely dependent on the research methodology adopted by the company. Research Methodology and Scope We have implemented a mix of primary and secondary research for our market estimate and forecast. Secondary research formed the initial phase of our study, where we conducted extensive data mining, referring to verified data sources such as independent studies, company annual reports, white papers, case studies, government and regulatory published articles, technical journals, magazines, and paid data sources. It was also used to obtain important information about the key players and market classification & segmentation according to industry trends to the bottom-most level, and key developments related to market and technology perspectives. A database of the key industry leaders was also prepared using secondary research.

In the primary research process, various primary sources from both supply and demand sides have been interviewed to obtain qualitative and quantitative information important for respective regions. The primary sources from the supply side included industry experts such as CEOs, VPs, marketing directors, technology and innovation directors, and related executives from key companies and organizations operating in the respective regions. The primary data has been collected through questionnaires, e-mails, and telephonic interviews, end-user surveys, consumer surveys, technology distributors and wholesaler’s surveys.

  • Quantitative methods (e.g. surveys) are best for measuring, ranking, categorizing, identifying patterns and making generalizations
  • Qualitative methods (e.g. interviews) are best for describing, interpreting, contextualizing, and gaining in-depth insight into specific concepts or phenomena
  • Mixed methods allow for a combination of numerical measurement and in-depth exploration.

Market drivers and restraints, along with their current and expected impacts, technological scenario and expected developments, end-use industry trends and dynamics  and consumer behavior trends  these forecasting parameters were considered.

Ethical approach, attention to detail, consistency, latest trend in the market and highly authentic source these are benefits of company’s research methodology.

Global Industry Reports

Market size estimation methodology top-down and bottom-up approaches

Both top-down and bottom-up approaches have been used to estimate and validate the total size of the virtual reality market. These methods have also been extensively used to estimate the sizes of various market subsegments. Estimating the size of the market in each region by adding the sizes of country-wise markets and tracking the ongoing and upcoming implementation of virtual reality projects by various companies in each region and forecasting the size of the virtual reality market based on these developments and other critical parameters, including COVID-19 related impacts

Data Triangulation

After arriving at the overall market size—using the market size estimation processes explained above—the market has been split into several segments and subsegments. To complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment, data triangulation, and market breakdown procedures have been employed, wherever applicable. The data has been triangulated by studying various factors and trends from both the demand and supply sides. It provide detailed information regarding the major factors (drivers, restraints, opportunities, challenges, company profiles, key player strategies competitive developments and key developments) influencing the virtual reality market growth.

Statistical Model

Our market estimates and forecasts are derived through simulation models. A unique model is created customized for each study. Gathered information for market dynamics, technology landscape, application development and pricing trends is fed into the model and analyzed simultaneously. These factors are studied on a comparative basis, and their impact over the forecast period is quantified with the help of correlation, regression and time series analysis.