Get quick answers to your questions about the article from our AI researcher chatbot
{'id': 'https://openalex.org/W4390274025', 'doi': 'https://doi.org/10.14293/pr2199.000574.v1', 'title': 'How to attract the best possible executive to be your new CEO', 'display_name': 'How to attract the best possible executive to be your new CEO', 'publication_year': 2023, 'publication_date': '2023-12-22', 'ids': {'openalex': 'https://openalex.org/W4390274025', 'doi': 'https://doi.org/10.14293/pr2199.000574.v1'}, 'language': 'en', 'primary_location': {'is_oa': True, 'landing_page_url': 'https://doi.org/10.14293/pr2199.000574.v1', 'pdf_url': 'https://www.scienceopen.com/document_file/5f9922f8-7284-4d9f-bdc1-5844087be587/ScienceOpenPreprint/RiessVictoria_ExecutiveCompensation_Final.pdf', 'source': None, 'license': 'cc-by', 'license_id': 'https://openalex.org/licenses/cc-by', 'version': 'submittedVersion', 'is_accepted': False, 'is_published': False}, 'type': 'preprint', 'type_crossref': 'posted-content', 'indexed_in': ['crossref'], 'open_access': {'is_oa': True, 'oa_status': 'green', 'oa_url': 'https://www.scienceopen.com/document_file/5f9922f8-7284-4d9f-bdc1-5844087be587/ScienceOpenPreprint/RiessVictoria_ExecutiveCompensation_Final.pdf', 'any_repository_has_fulltext': True}, 'authorships': [{'author_position': 'first', 'author': {'id': 'https://openalex.org/A5093261938', 'display_name': 'Victoria Riess', 'orcid': 'https://orcid.org/0009-0004-2714-5442'}, 'institutions': [{'id': 'https://openalex.org/I241749', 'display_name': 'University of Cambridge', 'ror': 'https://ror.org/013meh722', 'country_code': 'GB', 'type': 'education', 'lineage': ['https://openalex.org/I241749']}], 'countries': ['GB'], 'is_corresponding': True, 'raw_author_name': 'Victoria Riess', 'raw_affiliation_strings': ['University of Cambridge Economics, Organisations', 'university of cambridge'], 'affiliations': [{'raw_affiliation_string': 'University of Cambridge Economics, Organisations', 'institution_ids': ['https://openalex.org/I241749']}, {'raw_affiliation_string': 'university of cambridge', 'institution_ids': []}]}], 'institution_assertions': [], 'countries_distinct_count': 1, 'institutions_distinct_count': 1, 'corresponding_author_ids': ['https://openalex.org/A5093261938'], 'corresponding_institution_ids': ['https://openalex.org/I241749'], 'apc_list': None, 'apc_paid': None, 'fwci': None, 'has_fulltext': True, 'fulltext_origin': 'pdf', 'cited_by_count': 0, 'citation_normalized_percentile': {'value': 0.0, 'is_in_top_1_percent': False, 'is_in_top_10_percent': False}, 'cited_by_percentile_year': {'min': 0, 'max': 67}, 'biblio': {'volume': None, 'issue': None, 'first_page': None, 'last_page': None}, 'is_retracted': False, 'is_paratext': False, 'primary_topic': {'id': 'https://openalex.org/T11031', 'display_name': 'Game Theory and Applications', 'score': 0.9445, 'subfield': {'id': 'https://openalex.org/subfields/1803', 'display_name': 'Management Science and Operations Research'}, 'field': {'id': 'https://openalex.org/fields/18', 'display_name': 'Decision Sciences'}, 'domain': {'id': 'https://openalex.org/domains/2', 'display_name': 'Social Sciences'}}, 'topics': [{'id': 'https://openalex.org/T11031', 'display_name': 'Game Theory and Applications', 'score': 0.9445, 'subfield': {'id': 'https://openalex.org/subfields/1803', 'display_name': 'Management Science and Operations Research'}, 'field': {'id': 'https://openalex.org/fields/18', 'display_name': 'Decision Sciences'}, 'domain': {'id': 'https://openalex.org/domains/2', 'display_name': 'Social Sciences'}}], 'keywords': [{'id': 'https://openalex.org/keywords/adverse-selection', 'display_name': 'Adverse selection', 'score': 0.96434546}, {'id': 'https://openalex.org/keywords/moral-hazard', 'display_name': 'Moral hazard', 'score': 0.9097984}], 'concepts': [{'id': 'https://openalex.org/C32252159', 'wikidata': 'https://www.wikidata.org/wiki/Q380037', 'display_name': 'Adverse selection', 'level': 2, 'score': 0.96434546}, {'id': 'https://openalex.org/C2780202544', 'wikidata': 'https://www.wikidata.org/wiki/Q44454', 'display_name': 'Moral hazard', 'level': 3, 'score': 0.9097984}, {'id': 'https://openalex.org/C137577040', 'wikidata': 'https://www.wikidata.org/wiki/Q431965', 'display_name': 'Information asymmetry', 'level': 2, 'score': 0.83501005}, {'id': 'https://openalex.org/C29122968', 'wikidata': 'https://www.wikidata.org/wiki/Q1414816', 'display_name': 'Incentive', 'level': 2, 'score': 0.73120576}, {'id': 'https://openalex.org/C144559511', 'wikidata': 'https://www.wikidata.org/wiki/Q2986279', 'display_name': 'Principal (computer security)', 'level': 2, 'score': 0.5706881}, {'id': 'https://openalex.org/C144133560', 'wikidata': 'https://www.wikidata.org/wiki/Q4830453', 'display_name': 'Business', 'level': 0, 'score': 0.539238}, {'id': 'https://openalex.org/C2778137410', 'wikidata': 'https://www.wikidata.org/wiki/Q2732820', 'display_name': 'Government (linguistics)', 'level': 2, 'score': 0.5069054}, {'id': 'https://openalex.org/C200707436', 'wikidata': 'https://www.wikidata.org/wiki/Q1053211', 'display_name': 'Principal–agent problem', 'level': 3, 'score': 0.48176858}, {'id': 'https://openalex.org/C18762648', 'wikidata': 'https://www.wikidata.org/wiki/Q42213', 'display_name': 'Work (physics)', 'level': 2, 'score': 0.458482}, {'id': 'https://openalex.org/C81917197', 'wikidata': 'https://www.wikidata.org/wiki/Q628760', 'display_name': 'Selection (genetic algorithm)', 'level': 2, 'score': 0.41590768}, {'id': 'https://openalex.org/C162118730', 'wikidata': 'https://www.wikidata.org/wiki/Q1128453', 'display_name': 'Actuarial science', 'level': 1, 'score': 0.3963958}, {'id': 'https://openalex.org/C162324750', 'wikidata': 'https://www.wikidata.org/wiki/Q8134', 'display_name': 'Economics', 'level': 0, 'score': 0.30963516}, {'id': 'https://openalex.org/C175444787', 'wikidata': 'https://www.wikidata.org/wiki/Q39072', 'display_name': 'Microeconomics', 'level': 1, 'score': 0.2026687}, {'id': 'https://openalex.org/C10138342', 'wikidata': 'https://www.wikidata.org/wiki/Q43015', 'display_name': 'Finance', 'level': 1, 'score': 0.20185378}, {'id': 'https://openalex.org/C38652104', 'wikidata': 'https://www.wikidata.org/wiki/Q3510521', 'display_name': 'Computer security', 'level': 1, 'score': 0.1467565}, {'id': 'https://openalex.org/C127413603', 'wikidata': 'https://www.wikidata.org/wiki/Q11023', 'display_name': 'Engineering', 'level': 0, 'score': 0.14082539}, {'id': 'https://openalex.org/C41008148', 'wikidata': 'https://www.wikidata.org/wiki/Q21198', 'display_name': 'Computer science', 'level': 0, 'score': 0.1367994}, {'id': 'https://openalex.org/C154945302', 'wikidata': 'https://www.wikidata.org/wiki/Q11660', 'display_name': 'Artificial intelligence', 'level': 1, 'score': 0.07171583}, {'id': 'https://openalex.org/C78519656', 'wikidata': 'https://www.wikidata.org/wiki/Q101333', 'display_name': 'Mechanical engineering', 'level': 1, 'score': 0.0}, {'id': 'https://openalex.org/C39389867', 'wikidata': 'https://www.wikidata.org/wiki/Q380767', 'display_name': 'Corporate governance', 'level': 2, 'score': 0.0}, {'id': 'https://openalex.org/C41895202', 'wikidata': 'https://www.wikidata.org/wiki/Q8162', 'display_name': 'Linguistics', 'level': 1, 'score': 0.0}, {'id': 'https://openalex.org/C138885662', 'wikidata': 'https://www.wikidata.org/wiki/Q5891', 'display_name': 'Philosophy', 'level': 0, 'score': 0.0}], 'mesh': [], 'locations_count': 1, 'locations': [{'is_oa': True, 'landing_page_url': 'https://doi.org/10.14293/pr2199.000574.v1', 'pdf_url': 'https://www.scienceopen.com/document_file/5f9922f8-7284-4d9f-bdc1-5844087be587/ScienceOpenPreprint/RiessVictoria_ExecutiveCompensation_Final.pdf', 'source': None, 'license': 'cc-by', 'license_id': 'https://openalex.org/licenses/cc-by', 'version': 'submittedVersion', 'is_accepted': False, 'is_published': False}], 'best_oa_location': {'is_oa': True, 'landing_page_url': 'https://doi.org/10.14293/pr2199.000574.v1', 'pdf_url': 'https://www.scienceopen.com/document_file/5f9922f8-7284-4d9f-bdc1-5844087be587/ScienceOpenPreprint/RiessVictoria_ExecutiveCompensation_Final.pdf', 'source': None, 'license': 'cc-by', 'license_id': 'https://openalex.org/licenses/cc-by', 'version': 'submittedVersion', 'is_accepted': False, 'is_published': False}, 'sustainable_development_goals': [{'display_name': 'Peace, justice, and strong institutions', 'id': 'https://metadata.un.org/sdg/16', 'score': 0.59}], 'grants': [], 'datasets': [], 'versions': [], 'referenced_works_count': 13, 'referenced_works': ['https://openalex.org/W2025716023', 'https://openalex.org/W2102253817', 'https://openalex.org/W2112798681', 'https://openalex.org/W2126937117', 'https://openalex.org/W2197010448', 'https://openalex.org/W2584349946', 'https://openalex.org/W2796949850', 'https://openalex.org/W306823279', 'https://openalex.org/W3121287648', 'https://openalex.org/W3121745729', 'https://openalex.org/W3123686229', 'https://openalex.org/W4211070003', 'https://openalex.org/W4239875810'], 'related_works': ['https://openalex.org/W4390707278', 'https://openalex.org/W4390274025', 'https://openalex.org/W3150206884', 'https://openalex.org/W3124477927', 'https://openalex.org/W2591230998', 'https://openalex.org/W2388090699', 'https://openalex.org/W2348627368', 'https://openalex.org/W2273907187', 'https://openalex.org/W2232481811', 'https://openalex.org/W131093761'], 'abstract_inverted_index': {'The': [0, 48, 79, 170, 220, 268], 'two': [1, 23], 'information': [2, 41, 101, 109, 273], 'asymmetry': [3, 19, 102], 'problems': [4, 20, 106, 171], 'I': [5], 'face': [6], 'in': [7], 'hiring': [8], 'my': [9], 'next': [10], 'CEO': [11], 'are': [12, 110, 196, 278], 'adverse': [13, 111, 156, 198, 202], 'selection': [14, 112, 117, 157, 199, 203], 'and': [15, 113, 162, 191, 235], 'moral': [16, 114, 164, 221], 'hazard.': [17, 115], 'Information': [18], 'arise': [21], 'when': [22, 100], 'parties': [24], 'have': [25, 175], 'different': [26], 'levels': [27], 'of': [28, 53, 66, 107, 121, 126, 188, 257], 'information.': [29], 'For': [30, 140], 'example,': [31, 141], 'if': [32, 142, 274], 'an': [33, 36, 86], 'employer': [34, 49, 83], 'hires': [35, 85, 148], 'employee,': [37], 'each': [38], 'party': [39], 'has': [40, 152, 250, 271], 'which': [42], 'the': [43, 51, 55, 61, 76, 82, 88, 119, 123, 131, 134, 143, 155, 160, 163, 168, 172, 178, 189, 197, 229, 244, 251, 255, 258, 266, 283], 'other': [44, 215], 'does': [45, 231], 'not': [46, 232], 'have.': [47], 'knows': [50, 63], 'difficulty': [52, 256], 'how': [54], 'work': [56, 67, 91, 239], 'is': [57, 69, 74, 81, 118, 130, 182, 209, 224, 236, 282], 'to': [58, 71, 90, 153, 176, 184, 211, 225, 238, 253, 260], 'manage': [59], 'but': [60], 'employee': [62, 89], 'what': [64], 'amount': [65], 'he': [68], 'willing': [70, 183, 210, 237], 'contribute.': [72], 'This': [73], 'called': [75], 'principal-agent': [77, 95], 'problem.': [78, 200], 'principal': [80], 'who': [84, 181, 208], 'agent,': [87], 'for': [92, 192, 213, 248], 'him.': [93], 'A': [94], 'problem': [96, 158, 166, 223], 'only': [97], 'comes': [98], 'up': [99], 'exists.': [103], 'Two': [104], 'major': [105], 'asymmetric': [108], 'Adverse': [116], 'issue': [120, 132], 'pitching': [122], 'right': [124], 'type': [125], 'agent.': [127], 'Moral': [128], 'hazard': [129, 165, 222], 'that': [133, 228], 'agent': [135], 'shirks': [136], 'after': [137, 167], 'being': [138], 'hired.': [139], 'British': [144], 'Secret': [145], 'Intelligence': [146], 'Service': [147], 'James': [149, 246], 'Bond,': [150], 'it': [151], 'consider': [154], 'before': [159, 243], 'hire': [161], 'hire.': [169, 245], 'government': [173, 194, 269], 'would': [174, 204], 'select': [177], 'ideal': [179], 'candidate': [180, 230], 'kill': [185, 212], 'on': [186, 265], 'behalf': [187], 'country': [190], 'a': [193, 206, 218], 'paycheck': [195], 'An': [201], 'be': [205], 'person': [207], 'any': [214], 'reason': [216], 'like': [217], 'psychopath.': [219], 'make': [226], 'sure': [227], 'change': [233], 'behaviour': [234], 'as': [240, 242], 'hard': [241], 'Bond': [247, 281], 'example': [249], 'incentive': [252], 'exaggerate': [254], 'assignment': [259], 'extend': [261], 'his': [262], 'exotic': [263, 276], 'life': [264], 'assignment.': [267], 'instead': [270], 'no': [272], 'Bonds': [275], 'requests': [277], 'justified': [279], 'because': [280], 'expert.': [284]}, 'cited_by_api_url': 'https://api.openalex.org/works?filter=cites:W4390274025', 'counts_by_year': [], 'updated_date': '2025-01-08T09:44:54.370274', 'created_date': '2023-12-28'}