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D. Vanegas and M. Bose
ters in their neighborhood, which means that this design “solution” contributes only
marginally to addressing the problem.
The Architectural and Town-Planning (PREQ_ArqPlan) variable has the greatest impact of all the variables on the RS of formal origin neighborhoods. Given
that the spatial features of these neighborhoods are the result of regulated, planned,
and approved design and construction processes, the aesthetics and neighborhood/complex layout met with a high level of acceptance.
The variable Green Spaces (PREQ_Green) is designed to elicit perceptions of
the quality, availability, and accessibility of areas for relaxation and contemplation.
Formal origin housing developments are required to include green areas as part of
the housing project (DAPD, Bogotá, nd), and residents see them as an important
feature of their neighborhoods. Green spaces in formal neighborhoods can be public
or private in nature. A closer examination of the nuances of residents’ perceptions
in this regard, therefore, is necessary.
Finally, the MLR model of residential satisfaction includes Recreational Services
(PREQ_RecServ) as a significant contributing variable for formal origin neighborhoods. As per the PREQI, this variable accounts for the number, variety, and accessibility of sports facilities as well as the entertainment and/or cultural activities offered
at venues designed for this purpose. Community centers and sports facilities are generally offered among the amenities in formal origin housing developments, which
means residents of such neighborhoods generally expect them to be available.
4 Discussion and Conclusion
The analysis showed statistically significant differences between the mean RS of
informal and formal origin neighborhoods. Yet, the explanatory power of the models
differs greatly. On the one hand, RS was higher in formal origin neighborhoods (M
= 10.55) but only 19.8% of the variation in RS was explained by the model. On the
other hand, for informal origin neighborhoods (M = 9.58), 51.2% of the variation
in RS was explained by the model. The fact that the best fit model found using the
backwards variable selection method for each group showed such a large difference
in explanatory power strongly supports the hypothesis that there is a difference in the
perceptions of environmental features, which, in turn, contributes to RS in formal
origin versus informal origin neighborhoods.
The considerable difference in explanatory power shown by the models (formal
origin versus informal origin) suggests that for residents of each group different
aspects of the residential environment contribute to RS. From the architecture and
planning perspective, every variable of the final regression model of RS for formal
origin neighborhoods (Unsafe, Architectural and Town-Planning, Green Spaces, and
Recreational Services) are at the core of formal housing delivery processes. This
could be interpreted as a good result, but the fact that it accounts for only 19.8%
of the variance in RS is cause for concern. Given this result, it can be inferred that
for this group other variables need to be considered in the model. We put forward
D. Vanegas and M. Bose
ters in their neighborhood, which means that this design “solution” contributes only
marginally to addressing the problem.
The Architectural and Town-Planning (PREQ_ArqPlan) variable has the greatest impact of all the variables on the RS of formal origin neighborhoods. Given
that the spatial features of these neighborhoods are the result of regulated, planned,
and approved design and construction processes, the aesthetics and neighborhood/complex layout met with a high level of acceptance.
The variable Green Spaces (PREQ_Green) is designed to elicit perceptions of
the quality, availability, and accessibility of areas for relaxation and contemplation.
Formal origin housing developments are required to include green areas as part of
the housing project (DAPD, Bogotá, nd), and residents see them as an important
feature of their neighborhoods. Green spaces in formal neighborhoods can be public
or private in nature. A closer examination of the nuances of residents’ perceptions
in this regard, therefore, is necessary.
Finally, the MLR model of residential satisfaction includes Recreational Services
(PREQ_RecServ) as a significant contributing variable for formal origin neighborhoods. As per the PREQI, this variable accounts for the number, variety, and accessibility of sports facilities as well as the entertainment and/or cultural activities offered
at venues designed for this purpose. Community centers and sports facilities are generally offered among the amenities in formal origin housing developments, which
means residents of such neighborhoods generally expect them to be available.
4 Discussion and Conclusion
The analysis showed statistically significant differences between the mean RS of
informal and formal origin neighborhoods. Yet, the explanatory power of the models
differs greatly. On the one hand, RS was higher in formal origin neighborhoods (M
= 10.55) but only 19.8% of the variation in RS was explained by the model. On the
other hand, for informal origin neighborhoods (M = 9.58), 51.2% of the variation
in RS was explained by the model. The fact that the best fit model found using the
backwards variable selection method for each group showed such a large difference
in explanatory power strongly supports the hypothesis that there is a difference in the
perceptions of environmental features, which, in turn, contributes to RS in formal
origin versus informal origin neighborhoods.
The considerable difference in explanatory power shown by the models (formal
origin versus informal origin) suggests that for residents of each group different
aspects of the residential environment contribute to RS. From the architecture and
planning perspective, every variable of the final regression model of RS for formal
origin neighborhoods (Unsafe, Architectural and Town-Planning, Green Spaces, and
Recreational Services) are at the core of formal housing delivery processes. This
could be interpreted as a good result, but the fact that it accounts for only 19.8%
of the variance in RS is cause for concern. Given this result, it can be inferred that
for this group other variables need to be considered in the model. We put forward