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Notably, Climate-impact-driven behavioral changes could see major changes in the way we work and when we work or even eat and drink.
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Almost 99 percent of more than 15,000 global early technology adopters consulted by Ericsson say that they expect to be proactively using internet and connectivity-based solutions by 2030 to personally address the impact of climate change and global warming.
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The statistic is included in the latest annual 10 Hot Consumer Trends research from Ericsson ConsumerLab, this year called Life in a Climate-Impacted Future. It outlines consumers’ concerns, expectations and personal technology actions related to climate issues in 2030.
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Main concerns include: the cost of living, access to energy and material resources, and the need for safe and reliable connectivity in turbulent times and chaotic weather.
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Some 59 percent of respondents believe that innovation and technology will be crucial to address everyday challenges caused by climate change in the 2030s.
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More than 15,000 early adopters of AR, VR and digital assistants in 30 cities globally were asked to evaluate 120 digital service ideas across 15 areas ranging from climate related adaptation efforts in everyday life to ways to handle dire weather events. From the resulting data, Ericsson created 10 trend areas to group consumers’ answers.
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1 . Cost Cutters : Digital services will help consumers control food energy and travel costs in unstable climate situations. More than 60 percent of urban early adopters are concerned about higher costs of living in the future.
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2 . Unbroken Connections : Reliable and resilient internet connection will become more important if and as extreme weather events increase. Some 80 percent of urban early adopters believe there will be smart signal locators that show optimal coverage areas during natural disasters in the 2030s.
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3 . No-Rush : Mobility Strict time schedules may become a thing of the past as climate regulations and energy efficiency change the meaning of flexibility. About 68 percent of respondents would plan activities using schedulers that optimize based on energy cost not time efficiency.
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