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Sustainable Supply Chain Based on News Articles and Sustainability Reports: Text Mining with Leximancer and DICTION
The purpose of this research is to explore sustainable supply chain management (SSCM) trends, and firms’ strategic positioning and execution with regard to sustainability in the textile and apparel industry based on news articles and sustainability reports. Further analysis of the rhetoric in Chief executive officer (CEO) letters within sustainability reports is used to determine firms’ resoluteness, positive entailments, sharing of values, perception of reality, and sustainability strategy and execution feasibility. Computer-based content analysis is used for this research: Leximancer is applied for text analysis, while dictionary-based text mining program DICTION and SPSS are used for rhetorical analysis. Overall, contents similar to the literature on environmental, social, and economic aspects of the triple bottom line (TBL) are observed, however, topics such as regulation, green incentives, and international standards are not readily observed. Furthmore, ethical issues, sustainable production, quality, and customer roles are emphasized in texts analyzed. The CEO letter analysis indicates that listed firms show relatively low realism and high commonality, while North American firms exhibit relatively high commonality, and Europe firms show relatively high realism. The results will serve as a baseline for providing academia guidelines in SSCM research, and provide an opportunity for businesses to complement their sustainability strategies and executions.
Sustainable Supply Chain Based on News Articles and Sustainability Reports: Text Mining with Leximancer and DICTION
The purpose of this research is to explore sustainable supply chain management (SSCM) trends, and firms’ strategic positioning and execution with regard to sustainability in the textile and apparel industry based on news articles and sustainability reports. Further analysis of the rhetoric in Chief executive officer (CEO) letters within sustainability reports is used to determine firms’ resoluteness, positive entailments, sharing of values, perception of reality, and sustainability strategy and execution feasibility. Computer-based content analysis is used for this research: Leximancer is applied for text analysis, while dictionary-based text mining program DICTION and SPSS are used for rhetorical analysis. Overall, contents similar to the literature on environmental, social, and economic aspects of the triple bottom line (TBL) are observed, however, topics such as regulation, green incentives, and international standards are not readily observed. Furthmore, ethical issues, sustainable production, quality, and customer roles are emphasized in texts analyzed. The CEO letter analysis indicates that listed firms show relatively low realism and high commonality, while North American firms exhibit relatively high commonality, and Europe firms show relatively high realism. The results will serve as a baseline for providing academia guidelines in SSCM research, and provide an opportunity for businesses to complement their sustainability strategies and executions.
Sustainable Supply Chain Based on News Articles and Sustainability Reports: Text Mining with Leximancer and DICTION
Dongwook Kim (author) / Sungbum Kim (author)
2017
Article (Journal)
Electronic Resource
Unknown
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