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Online Sustainability Reporting and Firm Performance: Lessons Learned from Text Mining
by
Khuntia, Jiban
, Ning, Xue
, Yim, Dobin
in
Algorithms
/ Brand loyalty
/ Corporate social responsibility
/ Customers
/ Data mining
/ Disclosure
/ Employees
/ Information systems
/ Markov processes
/ Natural resources
/ Reputation management
/ Social investing
/ Social responsibility
/ Sustainability reporting
2021
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Online Sustainability Reporting and Firm Performance: Lessons Learned from Text Mining
by
Khuntia, Jiban
, Ning, Xue
, Yim, Dobin
in
Algorithms
/ Brand loyalty
/ Corporate social responsibility
/ Customers
/ Data mining
/ Disclosure
/ Employees
/ Information systems
/ Markov processes
/ Natural resources
/ Reputation management
/ Social investing
/ Social responsibility
/ Sustainability reporting
2021
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Do you wish to request the book?
Online Sustainability Reporting and Firm Performance: Lessons Learned from Text Mining
by
Khuntia, Jiban
, Ning, Xue
, Yim, Dobin
in
Algorithms
/ Brand loyalty
/ Corporate social responsibility
/ Customers
/ Data mining
/ Disclosure
/ Employees
/ Information systems
/ Markov processes
/ Natural resources
/ Reputation management
/ Social investing
/ Social responsibility
/ Sustainability reporting
2021
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Online Sustainability Reporting and Firm Performance: Lessons Learned from Text Mining
Journal Article
Online Sustainability Reporting and Firm Performance: Lessons Learned from Text Mining
2021
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Overview
As a corporate social responsibility (CSR) initiative, firms are increasingly disclosing sustainability indicators on online platforms to attract stakeholders’ interests. It is vital to understand what indicators reflect more on a firm’s performance and valuations. This study focuses on deriving value-oriented business intelligence from the voluntary disclosure of sustainability reports. The analysis in this study involves a three-stage approach: (1) Latent Dirichlet allocation (LDA) based topic modeling algorithm to identify and summarize typical contents expressed in various documents, (2) firm’s sustainability maturity modeled as a function of its strategic intent using a latent Markov model (LMM) to estimate the statistical significance and the extent of their relationships, and (3) empirical analysis using random effect linear and non-linear probit models to explore the impact of antecedents and firm performance consequences of three strategic intents. This study highlights using an advanced business analytics approach, specifically with latent Dirichlet allocation (LDA) topic modeling, to codify intangible knowledge embedded in annual sustainability reports to infer a firm’s strategic intent behind voluntary disclosure. In addition, this study aims to analyze the influence of the firm’s sustainability strategic intent on its financial performance. A secondary panel dataset consisting of information on 680 firms in 3 years was constructed by matching the text mined data with information from other sources. Results indicate that, on the one hand, while external stakeholder engagement is the primary motivation behind voluntary disclosure of sustainability reporting, firms are starting to engage internal stakeholders through workforce practices. On the other hand, internal employee-oriented intent has more influence on firm performance than external customer-oriented intent. This study demonstrates a toolset to index firms’ sustainability indicators and evaluates firms’ sustainability practice as an intangible asset and its impact on firms’ financial performance.
Publisher
MDPI AG
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