Coleção de Artigos Acadêmicos
URI permanente para esta coleçãohttps://repositorio.insper.edu.br/handle/11224/3227
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Artigo Científico Stakeholder Theory(2024) Beck, DonizeteStakeholder networks are an organizational and social phenomenon. Organizations are not alone, and managing stakeholders matters in strategic management. This encyclopedia entry aims: (1) to synthesize the theoretical thought behind the foundational publications; and (2) to introduce the main constructs, definitions, and approaches of Stakeholder Theory. In doing so, it explores the definition of stakeholder theory including; the normative, descriptive, and instrumental pillars; the convergent and divergent stakeholder theory debate; the difference between stakeholder issues and social issues; stakeholder salience (power, urgency, legitimacy, and proximity); mutual trust as instrumental value of ethical behavior; stakeholder influence strategies (withholding, usage, direct, and indirect); stakeholder value creation; and stakeholder capitalism.Artigo Científico Stakeholder Theory(2024) Beck, DonizeteStakeholder networks are an organizational and social phenomenon. Organizations are not alone, and managing stakeholders matters in strategic management. This encyclopedia entry aims: (1) to synthesize the theoretical thought behind the foundational publications; and (2) to introduce the main constructs, definitions, and approaches of Stakeholder Theory. In doing so, it explores the definition of stakeholder theory including; the normative, descriptive, and instrumental pillars; the convergent and divergent stakeholder theory debate; the difference between stakeholder issues and social issues; stakeholder salience (power, urgency, legitimacy, and proximity); mutual trust as instrumental value of ethical behavior; stakeholder influence strategies (withholding, usage, direct, and indirect); stakeholder value creation; and stakeholder capitalism.Artigo Científico Implantação de Value Based Management em uma indústria de produtos para saúde animal(2023) Poltronieri, Carlos Cristiano; Oyadomari, José Carlos Tiomatsu; Parisi, ClaudioIndústrias brasileiras de saúde animal tendem a competir com players globais, haja vista a importação de tecnologias produtivas fora do Brasil, trazendo produtos e processos produtivos que concorrem com as indústrias locais tendo uma competitividade favorecida. Também outros fatores fazem com que empresas do setor sejam altamente competitivos, por exemplo a entrada de empresas em saúde humana trazendo diversas sinergias para a indústria de animais. No caso específico foi observado ao longo de quatro anos como uma indústria de saúde animal de companhia implementou um processo de gestão baseada em valor (VBM), sendo observadas as motivações para a utilização, os mecanismos implementados e resultados alcançados. Essencialmente no início do processo e frente a realidade que enfrentam os seus negócios, os acionistas elaboraram uma avaliação da empresa com base na metodologia de fluxo de caixa descontado – para esse processo de avaliação foi desenhado um plano de negócios para um período de cinco anos, e sendo definido uma avaliação target. Dessa maneira, para a operacionalização do plano de negócios, além da forte conscientização de ações estratégicas e táticas baseadas na geração de valor e atingimento da avaliação target, diversos mecanismos de controle gerencial foram implementados, observado um pacote de ferramentas que encontra forte relação com o modelo proposto por Malmi e Brown (2008).Artigo Científico Trials of strength, paradoxes and competing networks in kaizen institutionalization(2024) Carneiro, Welington Norberto; Oyadomari, Jose Carlos Tiomatsu; Afonso, Paulo; Dultra-de-Lima, Ronaldo Gomes; Mendonça Neto, Octavio Ribeiro dePurpose – This paper seeks to understand kaizen in practice as it travels through time and space in the organisational setting. Design/methodology/approach – A qualitative case study was carried out at a multinational company using mainly interviews for the data collection that were analysed from an actor-network theory (ANT)perspective. Findings –This paper finds that the company deals with a series of paradoxes while managing the kaizen process. Efficiency and quality paradoxes are the basis for starting kaizen projects. Furthermore,intrinsic, and extrinsic motivation, emerge in these processes, and paradoxes relate to how spontaneous ideas emerge in a deliberated context of cost-saving objectives. The supply chain finance team coordinates kaizen projects with the collaboration of plant managers, promoting the paradox of autonomy and control. In addition, as kaizen mobilises and enrols the actors, some trials of strength emerge, showing actors who oppose the kaizen network and create competing networks that mutually exist in the firm. Practical implications – This study presents valuable insights for professionals to successfully implement kaizen methodologies that take advantage of developing a network for problem-solving in organizations. Originality/value – This study highlights the supply chain finance team’s role in enrolling the actors within a network built by practitioners engaged in kaizen projects. Usually, engineers, quality, or manufacturing teams lead kaizen projects, and only occasionally, accounting and financial teams participate, including multidisciplinary teams.Artigo Científico Environmental enforcement, property rights, and violence: evidence from the Brazilian Amazon(2024) Oliveira, Gustavo Magalhães de; BRUNO VARELLA MIRANDAConflicts over resources with poorly defined property rights have fuelled both deforestation and violence in the Brazilian Amazon. However, what happens when the State enhances its ability to monitor and enforce existing environmental laws? We study the case of the list of Municípios Prioritários, a policy that allocates additional resources to verify compliance with environmental laws in municipalities with high deforestation rates. Employing a difference-in-differences approach, our findings suggest that an improvement in the ability of the State to monitor and enforce environmental laws can reduce conflicts over the appropriation of value from resources with poorly defined property rights. Consistent with existing studies, we also find that the policy led to a reduction in deforestation rates in the Brazilian Amazon. Finally, we discuss the limitations of the current approach to curb violence in a region where the activity of mafias has considerably grown since the turn of the twenty-first century.Artigo Científico Technological Adoption: The Case of PIX in Brazil(2024) Gabriel Bernardes Amboage; GUILHERME FOWLER DE AVILA MONTEIRO; ADRIANA BRUSCATO BORTOLUZZOPurpose This study investigates the primary determinants of consumers' intention to adopt PIX as a payment method in Brazil, as well as their actual usage behavior. Design/methodology/approach The study employs the Unified Theory of Acceptance and Use of Technology (UTAUT) to analyze both the intention to use and the actual period of use of PIX technology as a measure of practical usage. With this approach, researchers can determine whether people’s intention to use PIX translates into a higher rate of technology adoption and effective and sustained usage. The study collected data from 659 consumers across Brazil through a questionnaire and used structural equation analysis to analyze the data. Findings Research suggests that the intention to adopt PIX as a payment method is mainly determined by the perceived value, performance expectancy, and the habit of using mobile internet. Positive associations are also confirmed between adoption intention, the effective usage time of PIX, and the habit of using mobile internet in conjunction with PIX use. Originality/value The study’s uniqueness stems from its focus on the PIX usage, which is becoming the primary payment method in Brazil. It also measures the practical usage of the technology by examining the duration of user experience. This enables the assessment of whether the intention to use PIX effectively translates into a higher speed of technology adoption.Artigo Científico Capital structure determinants of private and public firms in an emerging economy: a panel data quantile regression analysis(2024) ADRIANA BRUSCATO BORTOLUZZO; Sanvicente, Antonio Zoratto; Bortoluzzo, Maurício MesquitaPurpose This study explores distinct capital structure patterns between private and public companies, examining the varying influence of determinants on debt choices contingent upon a firm’s existing debt position. Design/methodology/approach Employing annual data from 2012 to 2022 for 142 public firms and 660 private firms in a large emerging economy, we use quantile regression within a panel data framework to study the heterogeneous effects of debt determinants, incorporating firm and time random effects. Findings Our findings indicate that such factors as size and operating margin contribute to higher levels of debt, while investment opportunities reduce the debt level. Further analyses, when accounting for a firm’s likelihood of being publicly traded, reveal that dividend payout and operating margin significantly influence debt levels, exclusively in the presence of high debt proportions. Conversely, investment opportunities emerge as a substantial determinant in all debt scenarios. In addition, we found a strong persistence in the indebtedness of companies, and we conclude that the effect of the determinants of indebtedness is heterogeneous according to the level of debt of companies. Originality/value This research provides a comprehensive comparison between private and public firms, not only in terms of debt levels but also in key capital structure determinants, highlighting their significance within the context of varying debt levels.Artigo Científico Determinant factors of banking proftability: an application of quantile regression for panel data(2024) ADRIANA BRUSCATO BORTOLUZZO; Ciganda, Rodrigo Ricardo; Bortoluzzo, Mauricio MesquitaThis study examines the determinants of bank proftability using a quantile regression approach, ofering insights into factors afecting banks across diferent percentiles of proftability. Utilizing a comprehensive database from Orbis covering 1200 top-market institutions across 101 countries, the research uniquely employs dynamic panel quantile regression while addressing sample survival bias. Our fndings highlight that bank size and capital adequacy nega tively impact proftability, whereas market value exerts a positive infuence on higher proftability banks. Credit risk afects proftability diferently across levels of proftability, and infation rate shows signifcance only for higher proft ability banks. The study contributes to the existing literature by ofering valuable insights into the factors determining bank proftability and how they behave at diferent percentiles in the sample, suggesting the importance of bank efciency and competition in promoting economic growthArtigo Científico Deep learning models for inflation forecasting(2023) Theoharidis, Alexandre Fernandes; DIOGO ABRY GUILLEN; HEDIBERT FREITAS LOPES; Hosszejni, DarjusWe propose a hybrid deep learning model that merges Variational Autoencoders and Convolutional LSTM Networks (VAE-ConvLSTM) to forecast inflation. Using a public macroeconomic database that comprises 134 monthly US time series from January 1978 to December 2019, the proposed model is compared against several popular econometric and machine learning benchmarks, including Ridge regression, LASSO regression, Random Forests, Bayesian methods, VECM, and multilayer perceptron. We find that VAE-ConvLSTM outperforms the competing models in terms of consistency and out-of-sample performance. The robustness of such conclusion is ensured via cross-validation and Monte-Carlo simulations using different training, validation, and test samples. Our results suggest that macroeconomic forecasting could take advantage of deep learning models when tackling nonlinearities and nonstationarity, potentially delivering superior performance in comparison to traditional econometric approaches based on linear, stationary models.Artigo Científico Stochastic Volatility Models with Skewness Selection(2024) Martins, Igor; HEDIBERT FREITAS LOPESThis paper expands traditional stochastic volatility models by allowing for time-varying skewness without imposing it. While dynamic asymmetry may capture the likely direction of future asset returns, it comes at the risk of leading to overparameterization. Our proposed approach mitigates this concern by leveraging sparsity-inducing priors to automatically select the skewness parameter as dynamic, static or zero in a data-driven framework. We consider two empirical applications. First, in a bond yield application, dynamic skewness captures interest rate cycles of monetary easing and tightening and is partially explained by central banks’ mandates. In a currency modeling framework, our model indicates no skewness in the carry factor after accounting for stochastic volatility. This supports the idea of carry crashes resulting from volatility surges instead of dynamic skewness.