000			03516nam a22006375i 4500
001			978-3-031-32064-4
003			DE-He213
005			20240507152730.0
007			cr nn 008mamaa
008			230727s2023 sz | s |||| 0|eng d
020			_a9783031320644 _9978-3-031-32064-4
024	7		_a10.1007/978-3-031-32064-4 _2doi
050		4	_aHG176.7
072		7	_aKFF _2bicssc
072		7	_aBUS017000 _2bisacsh
072		7	_aKFF _2thema
082	0	4	_a332 _223
082	0	4	_a658.15 _223
100	1		_aHornuf, Lars. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aData Privacy and Crowdsourcing _h[electronic resource] : _bA Comparison of Selected Problems in China, Germany and the United States / _cby Lars Hornuf, Sonja Mangold, Yayun Yang.
250			_a1st ed. 2023.
264		1	_aCham : _bSpringer Nature Switzerland : _bImprint: Springer, _c2023.
300			_aXIX, 149 p. 64 illus., 61 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aAdvanced Studies in Diginomics and Digitalization, _x2731-0485
505	0		_aChapter 1. Introduction -- Chapter 2. Players in the Crowdsourcing Industry -- Chapter 3. Data Protection Law in Germany, the United States, and China -- Chapter 4. Privacy Statements in China, Germany, and the U.S. -- Chapter 5. Summary and Conclusion.
506	0		_aOpen Access
520			_aThis open access book describes the most important legal sources and principles of data privacy and data protection in China, Germany and the United States. The authors collected privacy statements from more than 400 crowdsourcing platforms, which allowed them to empirically evaluate their data privacy and data protection practices. The book compares the practices in the three countries and develops empirically-grounded policy recommendations. A profound analysis on workers´ privacy in new forms of work in China, Germany, and the United States. Prof. Dr. Wolfgang Däubler, University of Bremen This is a comprehensive and timely book for legal and business scholars as well as practitioners, especially with the increasingly important role of raw data in machine learning and artificial intelligence. Professor Mingfeng Lin, Georgia Institute of Technology.
650		0	_aFinancial engineering.
650		0	_aData protection.
650		0	_aBusiness information services.
650		0	_aCommercial law.
650		0	_aNew business enterprises _xFinance.
650	1	4	_aFinancial Technology and Innovation.
650	2	4	_aData and Information Security.
650	2	4	_aIT in Business.
650	2	4	_aBusiness Law.
650	2	4	_aEntrepreneurial Finance.
700	1		_aMangold, Sonja. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aYang, Yayun. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
710	2		_aSpringerLink (Online service)
773	0		_tSpringer Nature eBook
776	0	8	_iPrinted edition: _z9783031320637
776	0	8	_iPrinted edition: _z9783031320651
776	0	8	_iPrinted edition: _z9783031320668
830		0	_aAdvanced Studies in Diginomics and Digitalization, _x2731-0485
856	4	0	_uhttps://doi.org/10.1007/978-3-031-32064-4
912			_aZDB-2-BUM
912			_aZDB-2-SXBM
912			_aZDB-2-SOB
999			_c37355 _d37355