A Study on People’s Attitude to the Use of Elevators for Fire Escape

Abstract

Currently, elevators are not considered as a proper means of escape in fires and people have been educated and trained to use staircases for fire escape. However, it is difficult for all the occupants to evacuate only by staircases timely and safely in super high-rise buildings, especially for the old and disabled. Considering the fact that super high-rise buildings are constructed in increasing numbers in many Asian cities, it becomes much more necessary to reconsider the use of elevators for emergency escape. Besides a mechanically safe elevator system, people’s cooperation is of critical importance to assure an efficient egress process. To explore people’s attitude to the use of elevators for fire escape in high-rise buildings and the diversity based on demographics, a study was conducted via face-to-face interviews in two different cities of China. Respondents’ demographics and their responses to hypothetical fire scenarios were collected via a set of structured questions. The results showed that most people would consider using elevators for fire escape in super high-rise buildings. The main influencing factors of their attitude were firemen’s instruction and the height of their location in the building. Statistical diversity was found based on demographics. These results indicated that people’s attitude to elevator evacuation was positive and further study should be very important.

Appendices

Appendix 1: Questions in the Interview

The survey was conducted by means of face-to-face interviews instead of questionnaires. Therefore, an interview outline was offered for reference. Interviews were based on but not limited to the questions in the outline.

Appendix 2: Introduction of WMW Test

In statistics, the Mann–Whitney U test [33] (also called the Mann–Whitney–Wilcoxon or Wilcoxon rank-sum test) is a non-parametric statistical hypothesis test for assessing whether one of two samples of independent observations tends to have larger values than the other. It is one of the most well-known non-parametric significance tests. It is a method for the comparison of two independent random samples (x and y) [34].

The Mann–Whitney U statistic is defined as:

$$ U = n_{1} n_{2} + \frac{{n_{1} (n_{2} + 1)}}{2} - \sum\limits_{{i - n_{1} + 1}}^{n2} {R_{i} } $$

where samples of size n ₁ and n ₂ are pooled and R _i are the ranks.

U can be resolved as the number of times observations in one sample precede observations in the other sample in the ranking.

In most circumstances a two sided test is required; here the alternative hypothesis is that x values tend to be distributed differently to y values. For a lower side test the alternative hypothesis is that x values tend to be smaller than y values. For an upper side test the alternative hypothesis is that x values tend to be larger than y values.

Assumptions of the Mann–Whitney test:

• random samples from populations

• independence within samples and mutual independence between samples

• measurement scale is at least ordinal

A confidence interval for the difference between two measures of location is provided with the sample medians. The assumptions of this method are slightly different from the assumptions of the Mann–Whitney test:

• random samples from populations

• independence within samples and mutual independence between samples

• two population distribution functions are identical apart from a possible difference in location parameters

Confidence intervals are constructed for the difference between the means or medians (any measure of location in fact). The level of confidence used will be as close as is theoretically possible to the one you specify.