Page 133 - Proceedings of the 2017 ITU Kaleidoscope

3.4. Impact where the utility functions are defined below:
● UReg: score assigned for drone regulations
The Impact sub-index gauges the broad economic and social ● UInv: score given for investment in the drone sector
impacts accruing from drone projects. The observed impact is ● UR&D: score assigned for the research and development
assessed for countries that currently have or have had a drone being conducted in the sector
project in the past. We decided to assess impact of drones in ● Ucap: score allocated for the local capacity building done
countries that currently have or have had drone projects before. on drones as well as for the presence of repair and
An alternative approach would be to assess the potential benefit of maintenance facilities
drone projects in a country, which would result in a different
index. ● UCom&En: score given for the communication and energy
infrastructure in place
3.4.1. Economic impact ● UTech: score for the type of drone technology in place
● UProj: score assigned on the drone projects in place
The economic impact sub-index measures potential cost-saving ● UEco: score assigned for the economic impact
benefits, the effects drone projects have on job creation in the ● USoc: score assigned for the social impact
country, investment and transfer of capacity. Each country was assigned scores on the above attributes
following the score description in Table 1.
3.4.2 Social impact Swing weighting [9] was used for setting the value of the various
k constants in (1) representing the attribute weights. The weight
The Social impact sub-index measures the effect the drone assessment process can be summarized in the following steps
projects have had on the lives of the people in the country; this documented with the results in Table 2:
could be in the form of improved access to healthcare and service 1. Taking the various sub-indices as attributes, the best and
delivery. worst values of each attribute were determined to the
lowest and highest score in Table 1, zero and one
4. DESIGN OF THE PROPOSED DRONE READINESS respectively.
INDEX 2. Eleven fictional alternatives were devised following the
ten attributes in (1). Ten alternative cases where each
In this section, we provide a detailed description of the one of the 10 attributes were in turn set to the best score
computation of the Drone Readiness Index.
keeping all the other attributes low, as well as a worst-
4.1 Analysis and Evaluation of the Sub-indices case alternative where all attributes were considered to
be at their lowest score.
Figure 1 summarizes the overall components and sub-indices used 3. Ranks were then assigned to each case. The worst-case
to calculate the drone readiness index. Except for the indicator received the highest rank to indicate that this was the
scores retrieved from elsewhere and the score assigned for the least desirable case and the lowest rank was assigned to
number of projects, each indicator was assigned a value of 0, 0.5 the
or 1 depending on whether this specific aspect is not observable,
partially perceptible or extensively noticeable. A larger scale was most desirable case. The best alternative was chosen to
used for number of projects. Table 1 gives the details of the be that of the case where a country would have ready
different sub-indices indicators, the rationale behind the scores infrastructures in terms of communication and
assigned for each indicator and the data source. The Regulation electricity followed by the case of a country with only
and Impact sub-indices are evaluated using qualitative data while favorable regulations in place.
the rest of the scores were obtained using quantitative data. 4. Rates were assigned to each alternative case following
the rank that was assigned. The rating of the worst-case
4.1.1. The Drone Readiness Index (DRI) alternative was zero while the best alternative received a
value of 100. All the alternatives were rated following
The drone readiness index was computed using the additive utility how likely or unlikely they would contribute to the
function model. Equation (1) gives the expression of the readiness overall readiness of a country.
index using a utility function: 5. The rating of each alternative case was then normalized

by the division of each rating with the sum of all the
= 1 × + 2 × + 3 × & + 4 × + ratings to obtain the weight associated with each
5 × & + 6 × ℎ + 7 × + 8 × + 9 × attribute.
(1)

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