the vendor is compatible with Technology share-% Market share of the technologies covered by the core product in the market segment # of product vendors Number of software product vendors in the market segment Market segment volume Total annual revenue of the market segment (M$) Table 10 Min and max values, and the correlation matrix of the variables used Variable Internal-% Product-% Service-% SW vendor Technology Technology coverage-% share-% vendors Internal-% Product-% -0.902** Service-% -0.991** 0.834** SW vendor size 7,818 0.853** -0.818 -0.830** Technology coverage-% 0.768** -0.774 -0.735* 0.858** Technology share-% 0.751* -0.785** -0.710* 0.839** 0.991 ** # of product vendors -0.383 0.311 0.390 -0.531 -0.063 -0.085 Market segment 5,370 -0.356 0.183 0.397 -0.212 0.058 0.041 0.853** volume In the table, the statistically significant results (p <0.01) are marked with ** , and close to significant results (p <0.05) are marked with * L. Frank et al. Technology SW Vendor Size Coverage -% Internal -% Technology Share -% # of SW Prod. Vendors Service -% Market Segment Volume Product -% Fig. 4 Correlations of indicator variables in the OSS/BSS software market. Positive correlations are marked with solid lines and negative correlations with dotted lines. Statistically significant correlations (0.01 level) are marked with thick lines and close to significant correlations (0.05 level) with thin lines volume, but there were no significant or even close to significant correlations between these two and other variables. The data suggests that the share of software products used is very limited, and that a large portion of in-house software development is still taking place. This indicates strongly that the market has not reached the final phases according to any of the theoretical models presented, although the number of software vendors operating in the market seems already to be decreasing (based on Dittberner data). The empirical market segment data supports the above hypothesis (derived from the vertical software ma