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Research Methodology Selection and Process

  • Evaluate the research purpose and propose appropriate research methods (qualitative method, quantitative method, mixed methods)

  • Develop the research process for the selected method

Research Design Development

  • Research design: propose detailed research designed based on the research purpose and methods (survey, experiment, archival, case study, interview); calculate sample sizes, prepare the data collection procedure

  • Measurement: develop the steps for the instrument development and reliability and validity assessment

Data treatment and statistical analysis

  • Data examination and coding: explore and examine the customer’s datasets, identify variables and parameters, code data

  • Data treatment and merging: prepare data for analysis, merge data

  • Statistical data analysis: determine appropriate statistical methods based on the analysis purpose, perform statistical analysis, interpret the results

  • Qualitative data analysis: code data, assess coding reliability and validity, perform qualitative data analysis, interpret the results

Data mining, text mining, and big data analytics

  • Machine learning algorithms: classification and regression modeling, decision tree, random forest, gradient boosting, subject vector machine, bayesian network, neural network

  • Text mining: text parsing, text filter, text cluster, text topic

  • Data mining using machine learning: data partition, data transformation, modeling, model assessment and comparison, ensemble learning

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