Online Sustainability Reporting and Firm Performance: Lessons Learned from Text Mining

Abstract

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.

Financially Distressed Firms: Environmental, Social, and Governance Reporting in Indonesia

“…Corporate reporting is crucial for management to convey their operational results during a specific period [39]. One of the reporting types that has empirically proven to increase firm value is ESG reporting [40,41]. In addition, recent study finds that more than 2000 studies document a positive relationship between ESG reporting and firm performance [7].…”

“…Lagged Variables ESG reporting studies are dominated by ones who focus on its impact, not the factor that determines the ESG reporting quality. For instance, firm performance [7,40,41] and risk of financial distress [11,44,45]. Thus, it will raise the causality issue that questions the "true" interested and dependent variables [38,63].…”

Sustainability reporting practices: an explorative analysis of luxury fashion brands

“…Scholars who have analysed paradox theory have focused on the communication of the paradox between CSR and luxury online (Wong and Dhanesh, 2017) and in some cases with respect to reporting (Ning et al. , 2021; Ebinger et al.…”

“…Scholars who have analysed paradox theory have focused on the communication of the paradox between CSR and luxury online (Wong and Dhanesh, 2017) and in some cases with respect to reporting (Ning et al, 2021;Ebinger et al, 2006). To the best of our knowledge, therefore, research conducted on sustainability communication through reporting and online communication is limited, as is the application to the world of luxury fashion, which becomes a communication tool for environmental positioning strategy.…”

Exploring Trends in Environmental, Social, and Governance Themes and Their Sentimental Value Over Time

“…For example, Te Liew et al (2014) used the term frequency-inverse document frequency (TF-IDF) methodology to analyze more than 100 companies. Recently, studies have applied the LDA model: Ning et al (2021) analyzed 680 company disclosure data, and Raghupathi et al (2020) derived automated results (topics) through 1,737 more reports.…”