5.3 APPENDIX 2: BENCHMARKING WITH OTHER INNOVATION STUDIES Dubai Private Sector Innovation Index HOW IS IT DIFFERENT? Innovation Study

Global Innovation Index

Data Collection Modes

• Macro data - quantitative/ objective/ hard data (55 indicators),

Data evaluation methodology Weight

36/79 indicator assigned half weight

- composite indicators/ index data (19 indicators), • survey/ qualitative/ subjective/ soft data (5 indicators)

Abu Dhabi Innovation Index

• Macro data - quantitative/ objective/hard data - survey/ qualitative/ subjective/soft data

the scoring is a non-weighted average

Scaling

41 indicators were scaled at source for economy comparisons to be valid – This was done through division by gross domestic product (GDP) in current US dollars, purchasing power parity GDP in international dollars (PPP$ GDP), population or the total unit corresponding to the particular statistic. (The scaling factor in each case was the value corresponding to the same year of the particular indicator)

Normalising

Averaging

The 79 indicators were normalized into the [0, 100] range, with higher scores representing better outcomes. Normalization was made according to the min-max method

The GII relies on seven pillars. Each pillar is divided into three sub-pillars, and each sub-pillar is composed of two to five individual indicators.

‘Min-max’ normalization method.

the scoring is a non-weighted average

Each sub-pillar score is calculated as the weighted average of its individual indicators. Each pillar score is calculated as the weighted average of its sub-pillar scores. For the sake of transparency and replicability of results, no additional effort was made to fill missing values. Missing values are indicated with ‘n/a’ and are not considered in the sub-pillar score.

This approach scales the data for each indicator over a common range [in this case, 1 to 7, 1 being the lowest].

• Survey questionnaire (survey conducted in person)

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5.3 APPENDIX 2: BENCHMARKING WITH OTHER INNOVATION STUDIES Dubai Private Sector Innovation Index HOW IS IT DIFFERENT? Innovation Study

Data Collection Modes

Data evaluation methodology Weight

Scaling

Normalising

Averaging

Innovation in Public Sector Organisations – NESTA UK

• Survey questionnaire

the scoring is a non-weighted average

The different approaches to scoring for each answer were harmonized by attributing each answer either ‘1’ or ‘0’ to indicate whether the associated variable was having an overall positive impact (‘1’) on this aspect (sub-category) of innovation or not (‘0’) and then averaged the scores for each of these sub-categories, representing each score as an indices of 0-100 per cent.

the scoring is a non-weighted average

European Public Sector Innovation Scoreboard

• Macro data

the scoring is a non-weighted average

Weights were rescaled for countries with some but not all of the factors in the Postsecondary education and patent activity metrics

the scoring is a non-weighted average

- quantitative/ objective/hard data - composite indicators/index data survey/ qualitative/ subjective/soft data

Bloomberg Innovation Index

• Macro data - quantitative/ objective/hard data - composite indicators/index data

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5.3 APPENDIX 2: BENCHMARKING WITH OTHER INNOVATION STUDIES

Innovation Study

Data Collection Modes

Innovation in Government Services – Thomson Reuters

• Macro data

Dubai Innovation Index

• Macro data

- quantitative/ objective/hard data

- quantitative/ objective/hard data - composite indicators/index data • Survey questionnaire

Data evaluation methodology Weight

Scaling

Given the list of stakeholders, government goals and their representative metrics, each sector was then scored by a weighted average on baseline, excellence and innovation-level score. The weights are 0.2 (20%), 0.3 (30%) and 0.5 (50%) respectively. the scoring is a non-weighted average

Normalising

Averaging

In order to mitigate the effect of different units/ scale on sectorscore formulas, metric data were normalized (to be between 0 and 1)

All indicators that are ratio measurements are first multiplied by the ratio base to obtain the actual value and then scaled by city-country population ratio or city-country GDP ratio depending on the nature of the value, i.e. whether it is population dependent or economic performance dependent.

Once the scale values have been computed, all values of a particular indicator are normalized across cities on a 0 – 100 scale using the min-max normalization method.

the scoring is a non-weighted average

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