Enhancing sustainability reporting practices in the notebook manufacturing industry: a multifaceted analysis integrating traditional reports and social media data

IF 4.4 3区 管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Annals of Operations Research Pub Date : 2024-11-21 DOI:10.1007/s10479-024-06343-4
Mehrdad Maghsoudi, Sajjad Shokouhyar, Nafiseh Sanaee, Sina Shokoohyar
{"title":"Enhancing sustainability reporting practices in the notebook manufacturing industry: a multifaceted analysis integrating traditional reports and social media data","authors":"Mehrdad Maghsoudi,&nbsp;Sajjad Shokouhyar,&nbsp;Nafiseh Sanaee,&nbsp;Sina Shokoohyar","doi":"10.1007/s10479-024-06343-4","DOIUrl":null,"url":null,"abstract":"<div><p>This study adopts a multidimensional approach to examining sustainability reporting practices among notebook manufacturers, integrating traditional corporate sustainability reports with social media data from platforms like Twitter, Facebook, and Reddit. Using advanced machine learning techniques, including multi-label classification and BERT-based sentiment analysis, the research highlights the key environmental, social, and economic dimensions that consumers prioritize. The findings reveal a significant misalignment between consumer concerns, reflected in social media discourse, and the focus of corporate sustainability reports. While companies emphasize environmental impacts and supply chain management, consumers prioritize product reliability, community obligations, and educational initiatives. This gap indicates a need for companies to realign their sustainability strategies to better meet consumer expectations, emphasizing trust-building, community engagement, and educational efforts. Despite these differences, the study also identifies shared concerns between consumers and producers, such as environmental impacts, supply chain sustainability, and transparency in sustainability claims. Based on these insights, the study recommends fostering transparent communication, engaging in inclusive dialogue, and committing to accountable actions across all sustainability dimensions. By aligning corporate reporting with consumer expectations, this research provides guidance to help companies advance towards a circular economy and enhance Extended Producer Responsibility (EPR) in the electronics industry, ultimately benefiting both companies and consumers in the pursuit of a more sustainable future.</p></div>","PeriodicalId":8215,"journal":{"name":"Annals of Operations Research","volume":"345 1","pages":"317 - 349"},"PeriodicalIF":4.4000,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10479-024-06343-4.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Operations Research","FirstCategoryId":"91","ListUrlMain":"https://link.springer.com/article/10.1007/s10479-024-06343-4","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
引用次数: 0

Abstract

This study adopts a multidimensional approach to examining sustainability reporting practices among notebook manufacturers, integrating traditional corporate sustainability reports with social media data from platforms like Twitter, Facebook, and Reddit. Using advanced machine learning techniques, including multi-label classification and BERT-based sentiment analysis, the research highlights the key environmental, social, and economic dimensions that consumers prioritize. The findings reveal a significant misalignment between consumer concerns, reflected in social media discourse, and the focus of corporate sustainability reports. While companies emphasize environmental impacts and supply chain management, consumers prioritize product reliability, community obligations, and educational initiatives. This gap indicates a need for companies to realign their sustainability strategies to better meet consumer expectations, emphasizing trust-building, community engagement, and educational efforts. Despite these differences, the study also identifies shared concerns between consumers and producers, such as environmental impacts, supply chain sustainability, and transparency in sustainability claims. Based on these insights, the study recommends fostering transparent communication, engaging in inclusive dialogue, and committing to accountable actions across all sustainability dimensions. By aligning corporate reporting with consumer expectations, this research provides guidance to help companies advance towards a circular economy and enhance Extended Producer Responsibility (EPR) in the electronics industry, ultimately benefiting both companies and consumers in the pursuit of a more sustainable future.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
求助全文
约1分钟内获得全文 去求助
来源期刊
Annals of Operations Research
Annals of Operations Research 管理科学-运筹学与管理科学
CiteScore
7.90
自引率
16.70%
发文量
596
审稿时长
8.4 months
期刊介绍: The Annals of Operations Research publishes peer-reviewed original articles dealing with key aspects of operations research, including theory, practice, and computation. The journal publishes full-length research articles, short notes, expositions and surveys, reports on computational studies, and case studies that present new and innovative practical applications. In addition to regular issues, the journal publishes periodic special volumes that focus on defined fields of operations research, ranging from the highly theoretical to the algorithmic and the applied. These volumes have one or more Guest Editors who are responsible for collecting the papers and overseeing the refereeing process.
期刊最新文献
A stochastic algorithm for deterministic multistage optimization problems A 2-approximation algorithm for the softwired parsimony problem on binary, tree-child phylogenetic networks Multi-channel retailing and consumers’ environmental consciousness Arctic sea ice thickness prediction using machine learning: a long short-term memory model Inexact proximal point method with a Bregman regularization for quasiconvex multiobjective optimization problems via limiting subdifferentials
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1