{"id":4325,"date":"2021-08-19T15:51:25","date_gmt":"2021-08-19T15:51:25","guid":{"rendered":"https:\/\/multilatinasforbesllyc.enforb.es\/inicio\/"},"modified":"2021-10-27T09:43:45","modified_gmt":"2021-10-27T14:43:45","slug":"inicio","status":"publish","type":"page","link":"https:\/\/multilatinasforbesllyc.enforb.es\/pt-br\/","title":{"rendered":"In\u00edcio"},"content":{"rendered":"

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Introdu\u00e7\u00e3o<\/h2><\/div>
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As multilatinas no contexto COVID-19<\/p>\n

<\/div><\/div>[vc_separator color=”black” align=”align_left”][vc_empty_space][vc_column_text css=”.vc_custom_1632339017562{margin-bottom: 35px !important;}”]No contexto da crise sanit\u00e1ria da COVID-19, as empresas multilatinas passaram pelas mesmas etapas que suas contrapartes globais: rea\u00e7\u00e3o \u00e0 crise, adapta\u00e7\u00e3o transit\u00f3ria e planejamento para o chamado “novo normal”. Entretanto, este processo ocorreu sem planos de resgate robustos como os dos Estados Unidos e da Europa. Nos EUA, as administra\u00e7\u00f5es Trump e Biden injetaram trilh\u00f5es de d\u00f3lares na economia para mant\u00ea-la \u00e0 tona e proteger as fam\u00edlias, na UE a conta ultrapassou um trilh\u00e3o de euros.[\/vc_column_text][vc_column_text]Em termos percentuais, dos pa\u00edses da regi\u00e3o, somente o Brasil est\u00e1 entre os pa\u00edses que investiram uma parte maior do PIB no combate aos efeitos da pandemia.[\/vc_column_text][\/vc_column][vc_column width=”1\/2″ css=”.vc_custom_1630944276112{padding-top: 4% !important;padding-right: 4% !important;padding-bottom: 4% !important;padding-left: 4% !important;background-color: #0a263b !important;}”][vc_row_inner][vc_column_inner][vc_custom_heading text=”Porcentagem do PIB que os pa\u00edses investiram para cobrir os custos da pandemia” font_container=”tag:h4|text_align:left|color:%23ffffff” google_fonts=”font_family:Merriweather%3A300%2C300italic%2Cregular%2Citalic%2C700%2C700italic%2C900%2C900italic|font_style:700%20bold%20regular%3A700%3Anormal”][vc_progress_bar values=”%5B%7B%22label%22%3A%22Jap%C3%A3o%22%2C%22value%22%3A%2255%22%2C%22color%22%3A%22custom%22%2C%22customcolor%22%3A%22%23008089%22%2C%22customtxtcolor%22%3A%22%23ffffff%22%7D%2C%7B%22label%22%3A%22Su%C3%A9cia%22%2C%22value%22%3A%2223%22%2C%22color%22%3A%22custom%22%2C%22customcolor%22%3A%22%23008089%22%2C%22customtxtcolor%22%3A%22%23ffffff%22%7D%2C%7B%22label%22%3A%22Alemanha%22%2C%22value%22%3A%2220%22%2C%22color%22%3A%22custom%22%2C%22customcolor%22%3A%22%23008089%22%2C%22customtxtcolor%22%3A%22%23ffffff%22%7D%2C%7B%22label%22%3A%22Canad%C3%A1%22%2C%22value%22%3A%2219%22%2C%22color%22%3A%22custom%22%2C%22customcolor%22%3A%22%23008089%22%2C%22customtxtcolor%22%3A%22%23ffffff%22%7D%2C%7B%22label%22%3A%22Estados%20Unidos%22%2C%22value%22%3A%2218%22%2C%22color%22%3A%22custom%22%2C%22customcolor%22%3A%22%23008089%22%2C%22customtxtcolor%22%3A%22%23ffffff%22%7D%2C%7B%22label%22%3A%22Austr%C3%A1lia%22%2C%22value%22%3A%2217%22%2C%22color%22%3A%22custom%22%2C%22customcolor%22%3A%22%23008089%22%2C%22customtxtcolor%22%3A%22%23ffffff%22%7D%2C%7B%22label%22%3A%22Dinamarca%22%2C%22value%22%3A%2216%22%2C%22color%22%3A%22custom%22%2C%22customcolor%22%3A%22%23008089%22%2C%22customtxtcolor%22%3A%22%23ffffff%22%7D%2C%7B%22label%22%3A%22Fran%C3%A7a%22%2C%22value%22%3A%2216%22%2C%22color%22%3A%22custom%22%2C%22customcolor%22%3A%22%23008089%22%2C%22customtxtcolor%22%3A%22%23ffffff%22%7D%2C%7B%22label%22%3A%22It%C3%A1lia%22%2C%22value%22%3A%2215%22%2C%22color%22%3A%22custom%22%2C%22customcolor%22%3A%22%23008089%22%2C%22customtxtcolor%22%3A%22%23ffffff%22%7D%2C%7B%22label%22%3A%22Brasil%22%2C%22value%22%3A%2212%22%2C%22color%22%3A%22custom%22%2C%22customcolor%22%3A%22%23008089%22%2C%22customtxtcolor%22%3A%22%23ffffff%22%7D%2C%7B%22label%22%3A%22Espanha%22%2C%22value%22%3A%2211%22%2C%22color%22%3A%22custom%22%2C%22customcolor%22%3A%22%23008089%22%2C%22customtxtcolor%22%3A%22%23ffffff%22%7D%5D” bgstyle=”transparent” units=”%”][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row full_width=”stretch_row” css_animation=”fadeIn” disable_element=”yes” css=”.vc_custom_1629752726661{padding-top: 5% !important;padding-bottom: 5% !important;background-color: #000000 !important;}”][vc_column][vc_row_inner][vc_column_inner width=”5\/6″][vc_custom_heading text=”Em resumo, as multilatinas tinham todas as condi\u00e7\u00f5es para estar entre as empresas mais afetadas pela crise.” font_container=”tag:h4|text_align:left|color:%23ffffff” google_fonts=”font_family:Merriweather%3A300%2C300italic%2Cregular%2Citalic%2C700%2C700italic%2C900%2C900italic|font_style:700%20bold%20regular%3A700%3Anormal”][vc_progress_bar 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units=”%”][\/vc_column_inner][vc_column_inner width=”1\/6″][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row full_width=”stretch_row” css=”.vc_custom_1632252636708{padding-top: 5% !important;padding-bottom: 5% !important;background-color: #000000 !important;}”][vc_column][vc_separator color=”custom” accent_color=”#ffffff” css=”.vc_custom_1632252684637{margin-bottom: 15px !important;}”]

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Antes da pandemia: a experi\u00eancia da incerteza<\/h3><\/div><\/div>[vc_separator color=”custom” accent_color=”#ffffff” css=”.vc_custom_1632252690033{margin-top: 15px !important;}”][vc_empty_space][vc_row_inner][vc_column_inner width=”1\/2″][vc_column_text css=”.vc_custom_1632342253443{margin-bottom: 35px !important;}” el_class=”white-text”]Multilatinas s\u00e3o as empresas estrelas da internacionaliza\u00e7\u00e3o na regi\u00e3o, marcadas por condi\u00e7\u00f5es especiais. A Am\u00e9rica Latina sempre foi uma regi\u00e3o menos previs\u00edvel do que os Estados Unidos ou a Europa. Para dar exemplos recentes, pa\u00edses como Brasil, Argentina e Venezuela passaram pelo super-ciclo de commodities no final da primeira d\u00e9cada do s\u00e9culo 21, apenas para entrar em per\u00edodos de crise no decorrer da segunda d\u00e9cada.[\/vc_column_text][vc_column_text css=”.vc_custom_1632342416989{margin-bottom: 35px !important;}” el_class=”white-text”]Nesse contexto vol\u00e1til, as empresas que integram o universo das multilatinas foram e seguem sendo pressionadas. Empresas que, em maior ou menor grau, aprenderam a ser flex\u00edveis, um valor chave para enfrentar os desafios surgiram a partir de 2020. A for\u00e7a de seus neg\u00f3cios sob estas condi\u00e7\u00f5es resultou em empresas resistentes, inovadoras e \u00e1geis na adapta\u00e7\u00e3o.[\/vc_column_text][\/vc_column_inner][vc_column_inner width=”1\/2″][vc_column_text css=”.vc_custom_1632342694281{margin-bottom: 35px !important;}” el_class=”white-text”]Antes da pandemia, a situa\u00e7\u00e3o das Multilatinas poderia ser resumida da seguinte forma:<\/p>\n
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  • A internacionaliza\u00e7\u00e3o da Multilatinas estava progredindo significativamente.<\/li>\n
  • O foco era a expans\u00e3o em regi\u00f5es de culturas parecidas.<\/li>\n
  • As empresas nasceram ou cresceram em tempos de crises locais ou globais.<\/li>\n<\/ul>\n

    [\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row full_width=”stretch_row” css=”.vc_custom_1632252644951{padding-top: 2% !important;padding-bottom: 2% !important;}”][vc_column][vc_separator color=”custom” accent_color=”#e2e2e2″ css=”.vc_custom_1629478150459{margin-bottom: 15px !important;}”]

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    E qual \u00e9 a percep\u00e7\u00e3o da opini\u00e3o p\u00fablica sobre as Multilatinas?<\/h3><\/div><\/div>[vc_separator color=”custom” accent_color=”#e2e2e2″ css=”.vc_custom_1629478119633{margin-top: 15px !important;}”][vc_empty_space][vc_row_inner][vc_column_inner width=”1\/2″][vc_column_text css=”.vc_custom_1632343306695{margin-bottom: 35px !important;}”]A fim de compreender de uma perspectiva social como as empresas multilatinas s\u00e3o entendidas e discutidas, realizamos uma an\u00e1lise utilizando nosso sistema chamado Data Analytics Suite.<\/strong> O estudo est\u00e1 focado em conversas sociais nas quais um ou mais dos seguintes aspectos foram mencionados empresas multilatinas mais importantes do mundo<\/strong>.[\/vc_column_text][vc_column_text css=”.vc_custom_1632343449515{margin-bottom: 35px !important;}”]Ficha t\u00e9cnica do estudo, sub-dividida em comunidades agrupadas em n\u00f3s, por pa\u00eds:<\/p>\n
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    • Analisamos 7.284.170 mensagens.<\/li>\n
    • Estudamos 2.278.663 perfis.<\/li>\n
    • A janela temporal do estudo foi de 1 de janeiro a 30 junho de 2021.<\/li>\n
    • Fontes: redes abertas e p\u00e1ginas p\u00fablicas.<\/li>\n<\/ul>\n

      [\/vc_column_text][\/vc_column_inner][vc_column_inner width=”1\/2″][vc_column_text css=”.vc_custom_1632343899767{margin-bottom: 35px !important;}”]Este estudo, que se baseia em uma an\u00e1lise dos territ\u00f3rios e comunidades mais importantes na conversa e resulta em um sociograma do que \u00e9 dito sobre as multilatinas, foi realizado atrav\u00e9s de uma segmenta\u00e7\u00e3o de acordo com as tr\u00eas dimens\u00f5es seguintes:<\/p>\n

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      • Tem\u00e1tica<\/strong>: aplicando t\u00e9cnicas de an\u00e1lise sem\u00e2ntica para extrair os principais subtemas da conversa. Em certas passagens da an\u00e1lise, foi realizada a an\u00e1lise do territ\u00f3rio relacionada aos principais objetivos de desenvolvimento sustent\u00e1vel (pois eles se referem aos 8 principais grupos de ODS definidos na Agenda 2030 da ONU).<\/li>\n
      • Setorial<\/strong>: por setor de atividade. Segmenta\u00e7\u00e3o e agrega\u00e7\u00e3o de resultados pelos setores econ\u00f4micos aos quais as empresas pertencem.<\/li>\n
      • Corporativa<\/strong>: conversa de contas corporativas versus a conversa do resto da sociedade. An\u00e1lise diferencial da conversa gerada pelas contas das empresas versus a conversa do resto da sociedade.<\/li>\n<\/ul>\n

        [\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row full_width=”stretch_row” css=”.vc_custom_1631122319448{padding-bottom: 35px !important;background-color: #000000 !important;}”][vc_column][vc_row_inner][vc_column_inner width=”2\/3″][vc_custom_heading text=”O que \u00e9 o DAS?” font_container=”tag:h2|text_align:left|color:%23ffffff” use_theme_fonts=”yes”][vc_column_text el_class=”white-text”]O Data Analytics Suite, DAS, \u00e9 um sistema da LLYC para an\u00e1lise de informa\u00e7\u00f5es usando big data para estabelecer modelos preditivos.[\/vc_column_text]