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TopIllustrative Model And Data
Our illustrative model contains only two variables, e-collaboration technology use (ETU) and new product quality (NPQ), and one causal link: ETU → NPQ. E-collaboration technology use (ETU) measures the extent to which a web-based e-collaboration tool has been used by teams of employees of a multinational company. The fictitious multinational company was assumed to develop and sell consumer products. Each team developed a new product, such as a new brand of toothpaste, whose market success was measured through the variable new product quality (NPQ). Both variables were measured through single indicators.
We employed the Monte Carlo method (Robert & Casella, 2005) to create sample data based on this model. The sample size was 250; meaning 250 rows of data, with each row referring to a new product development team. In addition to the two variables ETU and NPQ, we also created a numeric column and a column of text labels referring to three countries. The data sample was created based on the assumption that it was comprised of three subsamples, each coming from a country where the multinational company conducted operations. This is illustrated in Figure 1, where each of the data points represents a new product development team.
Figure 1. Underlying nonlinear relationship and country-specific patterns
TopData Segmentation Results
Table 1 shows the linear path coefficients and corresponding P values, for each of the three countries. The “View or change data modification settings” option in WarpPLS 5.0 allows users to run their analyses with subsamples defined by a range restriction variable, which we chose to be our numeric column referring to each of the countries by a number: 1 for Country1, 2 for Country2, and 3 for Country3. Using this option, we were able to conduct linear analyses for each separate country without having to use different datasets in WarpPLS for each of the countries.