LEK The 4th Annual New Mobility Study 2019

lek-the-4th-annual-new-mobility-study-2019 · 2019-01
arc beats above · slides in the middle · loops below · scroll → 0 LOOPS
SETUP TENSION ANALYSIS EVIDENCE RESOLUTION APPENDIX
HOVER FOR DETAILS · CLICK A SLIDE FOR FULLSCREEN · STEP 2
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Slide 1
front_matter
Open slide detailBeat · Setup
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other
Open slide detailBeat · Setup
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front_matter
Open slide detailBeat · Setup
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other
Open slide detailBeat · Setup
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establish_context
Open slide detailBeat · Setup
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present_framework
Open slide detailBeat · Setup
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The slide details the survey sample size per country and year, indicating the scope of the research methodology.establish_context
Open slide detailBeat · Setup
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summarize
Open slide detailBeat · Setup
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summarize
Open slide detailBeat · Setup
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The diagram uses a bullseye-style concentric layout to show the core mobility ecosystem surrounded by enabling layers.present_framework
Open slide detailBeat · Complication
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summarize
Open slide detailBeat · Complication
12
The slide uses a color-coded legend to distinguish between AVs, micro-mobility, ride hailing, electric vehicles, and P2P car rental.summarize
Open slide detailBeat · Complication
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summarize
Open slide detailBeat · Complication
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The chart uses a split Y-axis to accommodate the high usage of 'Driven Vehicle for Person Use' compared to other modes.analyze_data
Open slide detailBeat · Complication
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Data source: toddschneider.com. Visualizes the shift from traditional taxi services to ride-hailing apps.analyze_data
Open slide detailBeat · Complication
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The chart uses a 100-index baseline representing personal vehicle usage, with color-coded dots for different countries.compare_peers
Open slide detailBeat · Complication
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The charts use a scatter plot approach to demonstrate the gap between awareness (understanding) and usage.analyze_data
Open slide detailBeat · Complication
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The chart uses a series of stacked bar charts to compare usage patterns across UK, Australia, China, and India.compare_peers
Open slide detailBeat · Complication
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The slide uses S-curves to represent the adoption lifecycle of various mobility modes across different countries (represented by flags).present_framework
Open slide detailBeat · Complication
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transition
Open slide detailBeat · Complication
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quantify_impact
Open slide detailBeat · Evidence
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The chart highlights a trend where younger cohorts in India show less enthusiasm for car ownership compared to other age groups in the same country.analyze_data
Open slide detailBeat · Evidence
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summarize
Open slide detailBeat · Evidence
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The slide uses a process-flow style diagram to connect vehicle development to ecosystem orchestration.establish_context
Open slide detailBeat · Evidence
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The slide uses a circular flow diagram for drivers and a list-based influence model for outcomes.establish_context
Open slide detailBeat · Evidence
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The slide uses a simple transition diagram to show the shift from 'Individual Product' to 'Part of an Ecosystem'.establish_context
Open slide detailBeat · Evidence
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transition
Open slide detailBeat · Evidence
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The chart uses a split x-axis (age groups vs. geography).analyze_data
Open slide detailBeat · Evidence
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quantify_impact
Open slide detailBeat · Evidence
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compare_peers
Open slide detailBeat · Evidence
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The chart shows a consistent trend where city dwellers have a higher preference for leasing compared to non-city dwellers, with the exception of China where theanalyze_data
Open slide detailBeat · Evidence
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The chart uses a 100% stacked bar format to compare car ownership changes across six frequency segments of ride-hailing usage.analyze_data
Open slide detailBeat · Evidence
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Data from 2019 Fourth Annual Mobility Study.analyze_data
Open slide detailBeat · Evidence
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summarize
Open slide detailBeat · Evidence
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The chart uses a grouped bar format to compare interest levels across four years for seven different mobility categories.analyze_data
Open slide detailBeat · Evidence
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The chart displays data for 2019. The flags represent the countries: India, Canada, China, Spain, US, France, UK, Germany, Australia.analyze_data
Open slide detailBeat · Evidence
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The slide uses a grid of country-specific boxes to rank concerns, with icons representing cost, range, and infrastructure.diagnose
Open slide detailBeat · Evidence
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summarize
Open slide detailBeat · Evidence
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The slide uses grouped bar charts to compare 2018 and 2019 data for two categories of autonomous vehicles.analyze_data
Open slide detailBeat · Evidence
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The slide uses a grid of country-specific boxes to display ranked preferences.prioritize
Open slide detailBeat · Solution
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front_matter
Open slide detailBeat · Solution
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The slide uses a horizontal segmentation framework to map mobility services to trip distances.present_framework
Open slide detailBeat · Solution
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The chart shows a consistent gap between familiarity and actual usage across all listed countries.analyze_data
Open slide detailBeat · Solution
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The slide uses a grid of country-specific cards, each ranking the top 3 concerns.diagnose
Open slide detailBeat · Solution
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The slide uses a sequential process flow to show conversion rates.quantify_impact
Open slide detailBeat · Solution
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The slide uses a US flag icon to denote the geographic scope.decompose_segments
Open slide detailBeat · Solution
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The pie chart shows 52% Familiarity, 27% Convenience, 14% Future usage, and 7% Safety concerns.summarize
Open slide detailBeat · Solution
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front_matter
Open slide detailBeat · Solution
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The slide uses a 2x2 matrix framework to visualize the mobility market landscape.present_framework
Open slide detailBeat · Solution
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The slide uses a 2D conceptual space (Market Size vs Growth) to position the transition from retail sales to an integrated ecosystem.present_framework
Open slide detailBeat · Solution
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summarize
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summarize
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state_next_steps
Open slide detailBeat · Solution
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state_next_steps
Open slide detailBeat · Solution