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<front> <journal-meta>
<journal-id journal-id-type="publisher-id">Russian Journal of Labour Economics</journal-id>
<journal-title-group>
<journal-title xml:lang="en">Russian Journal of Labour Economics</journal-title>
<trans-title-group xml:lang="ru">
<trans-title>Экономика труда</trans-title>
</trans-title-group>
</journal-title-group>
<issn publication-format="print">2410-1613</issn>
<issn publication-format="electronic">2412-8929</issn>
<publisher>
<publisher-name xml:lang="en">BIBLIO-GLOBUS Publishing House</publisher-name>
</publisher>
</journal-meta><article-meta>
<article-id pub-id-type="publisher-id">119791</article-id>
<article-id pub-id-type="doi">10.18334/et.10.11.119791</article-id>
<article-id custom-type="edn" pub-id-type="custom">MQRMYP</article-id>
<article-categories>
<subj-group subj-group-type="toc-heading" xml:lang="en">
<subject>Articles</subject>
</subj-group>
<subj-group subj-group-type="toc-heading" xml:lang="ru">
<subject>Статьи</subject>
</subj-group>
<subj-group subj-group-type="article-type">
<subject>Research Article</subject>
</subj-group>
</article-categories>
<title-group>
<article-title xml:lang="en">Влияние особенностей человеческого капитала на зарплатные ожидания: исследование рынка труда Санкт-Петербург</article-title>
<trans-title-group xml:lang="ru">
<trans-title>The influence of human capital traits on salary expectation disclosure: a study of the St. Petersburg labor market</trans-title>
</trans-title-group>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">https://orcid.org/0009-0001-8584-0484</contrib-id>
<name-alternatives>
<name xml:lang="en">
<surname>Mahar</surname>
<given-names>Daniyal Haider</given-names>
</name>
<name xml:lang="ru">
<surname>Mahar </surname>
<given-names>Daniyal Haider</given-names>
</name>
</name-alternatives>
<bio xml:lang="ru">
<p>Ph.D. Student, HSE University</p>
</bio>
<email>dmakhar@hse.ru</email>
<xref ref-type="aff" rid="aff1"/>
</contrib>

<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">https://orcid.org/0009-0008-3437-2271</contrib-id>
<name-alternatives>
<name xml:lang="en">
<surname>Ramadhani</surname>
<given-names>Bima Yatna</given-names>
</name>
<name xml:lang="ru">
<surname>Ramadhani </surname>
<given-names>Bima Yatna</given-names>
</name>
</name-alternatives>
<bio xml:lang="ru">
<p>Lecturer, Universitas Negeri Surabaya</p>
</bio>
<email>bimaramadhani@unesa.ac.id</email>
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<aff>
<institution xml:lang="en">National Research University - Higher School of Economics</institution>
</aff>
<aff>
<institution xml:lang="ru">National Research University Higher School of Economics</institution>
</aff>
</aff-alternatives>        
        <aff-alternatives id="aff2">
<aff>
<institution xml:lang="en">Universitas Negeri Surabaya</institution>
</aff>
<aff>
<institution xml:lang="ru">Universitas Negeri Surabaya</institution>
</aff>
</aff-alternatives>        
        
<pub-date date-type="pub" iso-8601-date="2023-11-30" publication-format="print">
<day>30</day>
<month>11</month>
<year>2023</year>
</pub-date>
<volume>10</volume>
<issue>11</issue>
<issue-title xml:lang="en">VOL 10, NO11 (2023)</issue-title>
<issue-title xml:lang="ru">ТОМ 10, №11 (2023)</issue-title>
<fpage>1681</fpage>
<lpage>1704</lpage>
<history>
<date date-type="received" iso-8601-date="2023-11-01">
<day>01</day>
<month>11</month>
<year>2023</year>
</date>
<date date-type="accepted" iso-8601-date="">
<day></day>
<month></month>
<year></year>
</date>
</history>

<permissions>
<copyright-statement xml:lang="en">Copyright ©; 2023, Mahar D.H., Ramadhani B.Y.A.</copyright-statement>
<copyright-statement xml:lang="ru">Copyright ©; 2023, Mahar D.H., Ramadhani B.Y.A.</copyright-statement>
<copyright-year>2023</copyright-year>
<copyright-holder xml:lang="en">Mahar D.H., Ramadhani B.Y.A.</copyright-holder>
<copyright-holder xml:lang="ru">Mahar D.H., Ramadhani B.Y.A.</copyright-holder>
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<self-uri xlink:href="https://1economic.ru/lib/119791">https://1economic.ru/lib/119791</self-uri>
<abstract xml:lang="en"><p>Человеческие характеристики действительно влияют на решения людей во всех аспектах жизни. Целью данного исследования является анализ характеристик, которые могут повлиять на решение соискателей включить свои зарплатные ожидания в свое резюме при подаче заявления на новую должность. В частности, сюда входят уровень образования, опыт работы, возрастные и гендерные различия. Данные были собраны с одного из ведущих российских порталов вакансий HH.ru. Набор данных состоял из претендентов, подавших заявки на руководящие должности. Для изучения этих переменных и их связи с ожиданиями заработной платы были использованы два разных метода анализа. Анализ Т-теста использовался для сравнения средних значений переменных. На втором этапе были использованы 3 модели логистического регрессионного анализа с различной комбинацией переменных для изучения взаимосвязей и их влияния. Наше исследование показало значительное влияние уровня образования и навыков, опыта работы и пола на ожидания по заработной плате. Авторы пришли к выводу, что люди с большим количеством навыков, опыта работы и более высоким уровнем образования, как правило, не упоминают в резюме свои зарплатные ожидания, и наоборот. Это исследование может быть полезно работодателям, занимающимся персоналом, которые хотят нанять новых сотрудников.</p>
</abstract>
<trans-abstract xml:lang="ru"><p>Human characteristics do impact the decisions of the people in every aspect of life. This study aims to analyze the characteristics that can impact the applicants’ decision to include their salary expectations in their resume when applying for a new position. Specifically, this includes education level, working experience, age differences and gender gap. The data was collected from one of the leading Russian job portal websites, i.e., HH.ru. The dataset consisted of applicants’ who applied for the managerial positions. Two different methods of analysis were used to study these variables and the relationship with the salary expectations. T-test analysis was used to compare the means of the variables. In the second step, 3 models of logistic regression analysis were used with different combination of variables to study the relationship and their impacts. Our study showed the significant impacts of education level and skills, working experience and gender on the salary expectations. The authors concluded that people with higher number of skills, working experience and possess higher education level, tends to not mention their salary expectations in their resume and vice versa. This study can be useful for the Human resources employers who want to hire new employees.</p>
</trans-abstract>
<kwd-group xml:lang="en">
<kwd>зарплатные ожидания</kwd>
<kwd>рынок труда</kwd>
<kwd>опыт работы</kwd>
<kwd>навыки</kwd>
<kwd>уровень образования</kwd>
<kwd>гендерный разрыв</kwd></kwd-group><kwd-group xml:lang="ru">
<kwd>salary expectations</kwd>
<kwd>labor market</kwd>
<kwd>working experience</kwd>
<kwd>Skills</kwd>
<kwd>education level</kwd>
<kwd>gender gap</kwd></kwd-group>
</article-meta>
</front>
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