Pub Date : 2024-11-08DOI: 10.1016/j.techsoc.2024.102759
Isaac Ankrah , Michael Appiah Kubi , Sampson Twumasi-Ankrah , Frank Gyimah Sackey , Richard Asravor , Brenya Boahemaa , Derrick Donkor , Lilian Arthur , Christopher Lamptey , Eric Ekobor-Ackah Mochiah
This study investigates the impact of Information and Communication Technologies (ICT) on electricity consumption in West Africa, employing a dynamic panel data model. The results show a significant long-term positive effect of ICT adoption on electricity consumption. Notably, internet connections increase the demand for electricity, with estimates ranging from 13.4 % to 19.3 %. While mobile phone subscriptions demonstrate modest positive effect of 6.85 %, personal computer ownership appears to have a negligible impact.
The study contributes to the existing literature by offering a detailed examination of the distinct effects of different ICT components on electricity consumption, incorporating a novel estimation approach and sensitivity analyses that account for the COVID-19 pandemic and the Anglo-French linguistic divide. What's more, the analysis constitutes an initial effort in the examining both short-term and long-term dynamics of the ICT-electricity relationship in West African region.
{"title":"Modeling ICT adoption and electricity consumption in emerging digital economies: Insights from the West African Region","authors":"Isaac Ankrah , Michael Appiah Kubi , Sampson Twumasi-Ankrah , Frank Gyimah Sackey , Richard Asravor , Brenya Boahemaa , Derrick Donkor , Lilian Arthur , Christopher Lamptey , Eric Ekobor-Ackah Mochiah","doi":"10.1016/j.techsoc.2024.102759","DOIUrl":"10.1016/j.techsoc.2024.102759","url":null,"abstract":"<div><div>This study investigates the impact of Information and Communication Technologies (ICT) on electricity consumption in West Africa, employing a dynamic panel data model. The results show a significant long-term positive effect of ICT adoption on electricity consumption. Notably, internet connections increase the demand for electricity, with estimates ranging from 13.4 % to 19.3 %. While mobile phone subscriptions demonstrate modest positive effect of 6.85 %, personal computer ownership appears to have a negligible impact.</div><div>The study contributes to the existing literature by offering a detailed examination of the distinct effects of different ICT components on electricity consumption, incorporating a novel estimation approach and sensitivity analyses that account for the COVID-19 pandemic and the Anglo-French linguistic divide. What's more, the analysis constitutes an initial effort in the examining both short-term and long-term dynamics of the ICT-electricity relationship in West African region.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"79 ","pages":"Article 102759"},"PeriodicalIF":10.1,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-06DOI: 10.1016/j.techsoc.2024.102755
Meng Qin , Yue Wan , Junyi Dou , Chi Wei Su
The rapid development of Artificial Intelligence (AI) is simultaneously fostering a proliferation of novel job opportunities while rendering some traditional roles obsolete and specific skills outdated. Previous research has failed to consider the short-, medium-, and long-term variations in AI's impact on unemployment, which may lead to an incomplete understanding of the AI-employment relationship. This paper examines daily data from January 4, 2013, to August 12, 2024, utilising advanced wavelet-based Quantile on Quantile Regression (QQR) methodology to assess AI's impact on the Unemployment Index (UI) across quantiles and time scales, with a sample size of 2820 drawn from a larger dataset totalling 4241 observations. The conclusions reveal that AI generally positively impacts UI in the short term, especially with AI at 0.6–0.7 quantiles, as automation replaces workers faster than new job roles emerge and skills transform. However, in the medium term, positive and negative effects balance as new jobs and skills emerge through continuous industrial restructuring. In the long run, AI predominantly mitigates UI by further enhancing economic development, fostering skill upgrading, and facilitating market adjustments, but this result does not hold during AI at 0.7 quantiles and UI at the highest quantiles, such as Coronavirus Disease 2019 (COVID-19). Under new technological revolution and industrial transformation, we formulate China-specific suggestions to avert potential AI-induced unemployment crisis from short-term, medium-term, long-term, and sector-specific perspectives.
{"title":"Artificial Intelligence: Intensifying or mitigating unemployment?","authors":"Meng Qin , Yue Wan , Junyi Dou , Chi Wei Su","doi":"10.1016/j.techsoc.2024.102755","DOIUrl":"10.1016/j.techsoc.2024.102755","url":null,"abstract":"<div><div>The rapid development of Artificial Intelligence (AI) is simultaneously fostering a proliferation of novel job opportunities while rendering some traditional roles obsolete and specific skills outdated. Previous research has failed to consider the short-, medium-, and long-term variations in AI's impact on unemployment, which may lead to an incomplete understanding of the AI-employment relationship. This paper examines daily data from January 4, 2013, to August 12, 2024, utilising advanced wavelet-based Quantile on Quantile Regression (QQR) methodology to assess AI's impact on the Unemployment Index (UI) across quantiles and time scales, with a sample size of 2820 drawn from a larger dataset totalling 4241 observations. The conclusions reveal that AI generally positively impacts UI in the short term, especially with AI at 0.6–0.7 quantiles, as automation replaces workers faster than new job roles emerge and skills transform. However, in the medium term, positive and negative effects balance as new jobs and skills emerge through continuous industrial restructuring. In the long run, AI predominantly mitigates UI by further enhancing economic development, fostering skill upgrading, and facilitating market adjustments, but this result does not hold during AI at 0.7 quantiles and UI at the highest quantiles, such as Coronavirus Disease 2019 (COVID-19). Under new technological revolution and industrial transformation, we formulate China-specific suggestions to avert potential AI-induced unemployment crisis from short-term, medium-term, long-term, and sector-specific perspectives.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"79 ","pages":"Article 102755"},"PeriodicalIF":10.1,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-06DOI: 10.1016/j.techsoc.2024.102756
Qinqin Wu , Qinqin Zhuang , Yitong Liu , Longyan Han
The release of ChatGPT has attracted widespread attention and triggered fluctuations in the capital market. This study employs difference-in-differences (DID) and event study (ES) to investigate the effects of ChatGPT's release on the cumulative abnormal return (CAR) of listed companies in China. The results reveal that a series of ChatGPT launch events, including GPT-3.5 and GPT-4, have a significantly positive impact on the firm value of the companies focused on ChatGPT, with dynamic effects. In the initial two months after the release of ChatGPT, the Chinese stock market exhibited an undervaluation of GPT-focused companies, indicating information asymmetry and competitive substitution effect. With the widespread promotion of generative AI, social recognition of ChatGPT's potential value increased. This study verifies the moderation effect of social attention in strengthening ChatGPT's impact, demonstrating that a higher search index for ChatGPT enhances stock returns for GPT-focused companies. Heterogeneity tests reveal that the impact of ChatGPT is significantly positive for large or non-state-owned companies, while small or state-owned companies show no significant effect. From the perspective of labor structure, companies dominated by technical and production personnel experience positive effects, whereas those dominated by sales personnel do not. In the eastern regions with more favorable digital economic innovation environments, companies experience a notably positive impact. This paper provides a theoretical explanation and empirical evidence for the microeconomic impact of generative AI in the Chinese context, offering valuable insights for both government and firms.
{"title":"Technology shock of ChatGPT, social attention and firm value: Evidence from China","authors":"Qinqin Wu , Qinqin Zhuang , Yitong Liu , Longyan Han","doi":"10.1016/j.techsoc.2024.102756","DOIUrl":"10.1016/j.techsoc.2024.102756","url":null,"abstract":"<div><div>The release of ChatGPT has attracted widespread attention and triggered fluctuations in the capital market. This study employs difference-in-differences (DID) and event study (ES) to investigate the effects of ChatGPT's release on the cumulative abnormal return (CAR) of listed companies in China. The results reveal that a series of ChatGPT launch events, including GPT-3.5 and GPT-4, have a significantly positive impact on the firm value of the companies focused on ChatGPT, with dynamic effects. In the initial two months after the release of ChatGPT, the Chinese stock market exhibited an undervaluation of GPT-focused companies, indicating information asymmetry and competitive substitution effect. With the widespread promotion of generative AI, social recognition of ChatGPT's potential value increased. This study verifies the moderation effect of social attention in strengthening ChatGPT's impact, demonstrating that a higher search index for ChatGPT enhances stock returns for GPT-focused companies. Heterogeneity tests reveal that the impact of ChatGPT is significantly positive for large or non-state-owned companies, while small or state-owned companies show no significant effect. From the perspective of labor structure, companies dominated by technical and production personnel experience positive effects, whereas those dominated by sales personnel do not. In the eastern regions with more favorable digital economic innovation environments, companies experience a notably positive impact. This paper provides a theoretical explanation and empirical evidence for the microeconomic impact of generative AI in the Chinese context, offering valuable insights for both government and firms.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"79 ","pages":"Article 102756"},"PeriodicalIF":10.1,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-05DOI: 10.1016/j.techsoc.2024.102750
Priyadarsini Patnaik , Mahmoud Bakkar
An organization's ability to accept innovation heavily depends on its leadership caliber. Although leadership is known to affect all three stages of adoption (initiation, adoption, and routinization), literature has yet to examine the specific leadership components that contribute to each of these phases. Drawing from existing literature on transformational leadership and AI adoption, this article examines how transformational leadership can facilitate the successful implementation of AI technologies. This paper explores the intersection of transformational leadership and artificial intelligence (AI) adoption within organizations. This study used data from 250 companies to develop and evaluate a framework combining the Diffusion of Innovation (DOI) theory with transformational leadership (TL). The results were analyzed using structural equation modeling (SEM) techniques. The study examined the determinants influencing the adoption of AI as a new technology. This study found TL is a crucial driver of adoption, whereas elements like vision and intellectual stimulation are essential for the Intention to adopt. Also, this research indicates that adopting a significant innovation like AI is intricately linked to leaders' vision and ability to respect and recognize the feelings and needs of others (both indicators of offering individual assistance). Additionally, practical implications and recommendations for leaders are provided to navigate the complex landscape of AI adoption.
{"title":"Exploring determinants influencing artificial intelligence adoption, reference to diffusion of innovation theory","authors":"Priyadarsini Patnaik , Mahmoud Bakkar","doi":"10.1016/j.techsoc.2024.102750","DOIUrl":"10.1016/j.techsoc.2024.102750","url":null,"abstract":"<div><div>An organization's ability to accept innovation heavily depends on its leadership caliber. Although leadership is known to affect all three stages of adoption (initiation, adoption, and routinization), literature has yet to examine the specific leadership components that contribute to each of these phases. Drawing from existing literature on transformational leadership and AI adoption, this article examines how transformational leadership can facilitate the successful implementation of AI technologies. This paper explores the intersection of transformational leadership and artificial intelligence (AI) adoption within organizations. This study used data from 250 companies to develop and evaluate a framework combining the Diffusion of Innovation (DOI) theory with transformational leadership (TL). The results were analyzed using structural equation modeling (SEM) techniques. The study examined the determinants influencing the adoption of AI as a new technology. This study found TL is a crucial driver of adoption, whereas elements like vision and intellectual stimulation are essential for the Intention to adopt. Also, this research indicates that adopting a significant innovation like AI is intricately linked to leaders' vision and ability to respect and recognize the feelings and needs of others (both indicators of offering individual assistance). Additionally, practical implications and recommendations for leaders are provided to navigate the complex landscape of AI adoption.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"79 ","pages":"Article 102750"},"PeriodicalIF":10.1,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-02DOI: 10.1016/j.techsoc.2024.102754
Evelyn Brister , Paul B. Thompson , Susan M. Wolf , John C. Bischof
Advanced cryopreservation technologies have the potential to transform organ transplants, biomedical research, food storage, aquaculture, biodiversity repositories, ecological restoration, and numerous other applications. These surpass the capability of existing cryopreservation technologies to extend the life and viability of biological materials at various scales from cells to tissues, organs, and entire organisms. In this article, we demonstrate why innovations in advanced cryopreservation, which we analyze as emergent, convergent platform technologies, raise novel concerns for research ethics and coordination, governance, and equitable access to benefits. As emerging technologies, they may disrupt markets or destabilize social institutions, including the systems that govern the distribution of organs for transplant. As convergent technologies, their impact will be heightened through interaction with other technologies. The technologies that may intensify the social and ethical effects of advanced cryopreservation include information technologies that permit the administration of complex logistics of storage and transport, biotechnologies for the management of floral and faunal species and populations, and 3D printing technologies that may enable the development and distribution of customizable peripheral components of this platform technology. The speed of development among diverse applications of the core platform is likely to vary between sectors in ways that are responsive to public support as well as to ethical constraints, and advancements in any sector will affect the achievement of reliability for the core technology across sectors. We recommend that societal benefits and risks be assessed both in the specific contexts for which peripheral components are developed and for the core technology.
{"title":"Advanced cryopreservation as an emergent and convergent technological platform","authors":"Evelyn Brister , Paul B. Thompson , Susan M. Wolf , John C. Bischof","doi":"10.1016/j.techsoc.2024.102754","DOIUrl":"10.1016/j.techsoc.2024.102754","url":null,"abstract":"<div><div>Advanced cryopreservation technologies have the potential to transform organ transplants, biomedical research, food storage, aquaculture, biodiversity repositories, ecological restoration, and numerous other applications. These surpass the capability of existing cryopreservation technologies to extend the life and viability of biological materials at various scales from cells to tissues, organs, and entire organisms. In this article, we demonstrate why innovations in advanced cryopreservation, which we analyze as emergent, convergent platform technologies, raise novel concerns for research ethics and coordination, governance, and equitable access to benefits. As emerging technologies, they may disrupt markets or destabilize social institutions, including the systems that govern the distribution of organs for transplant. As convergent technologies, their impact will be heightened through interaction with other technologies. The technologies that may intensify the social and ethical effects of advanced cryopreservation include information technologies that permit the administration of complex logistics of storage and transport, biotechnologies for the management of floral and faunal species and populations, and 3D printing technologies that may enable the development and distribution of customizable peripheral components of this platform technology. The speed of development among diverse applications of the core platform is likely to vary between sectors in ways that are responsive to public support as well as to ethical constraints, and advancements in any sector will affect the achievement of reliability for the core technology across sectors. We recommend that societal benefits and risks be assessed both in the specific contexts for which peripheral components are developed and for the core technology.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"79 ","pages":"Article 102754"},"PeriodicalIF":10.1,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142586838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-02DOI: 10.1016/j.techsoc.2024.102746
Nagendra Kumar Sharma , Vimal Kumar , Pratima Verma , Mahak Sharma , Ashwaq Al Khalil , Tugrul Daim
Industry 4.0 (I4.0) is one of the essential topics that has been researched extensively in the research domain. In the same way, there are also several research available to check the connections between I4.0 and sustainable manufacturing. It is because of the increasing concern of stakeholders over environmental challenges that manufacturing units are often blamed. It is also true that a major part of manufacturing is done by SMEs in almost every developed or developing economy of the world including India. Therefore, the present research work took place to identify the factors that are essential for sustainable manufacturing using I4.0 in Indian SMEs. In the present study, a total of six factors were identified from the previous studies, which are technological factors (TF), organizational factors (OF), environmental factors (ENF), societal factors (SF), economic factors (ECF), and external stakeholders' factors (ESF) considering the triple bottom line (TBL) approach of the sustainability model. Each factor consists of a few sub-factors, and a total of thirty-five factors were developed. The best-worst method (BWM) and Hierarchical Decision Model (HDM) were applied to bring the results. The result suggests that OF and TF are ranked number one and two respectively. ECF and ENF ranked at three and four whereas, ESF and SF ranked at five and six respectively. The study helps firm managers revolutionize their organizations’ approach to the sustainability model by looking at the Industry 4.0 factors affecting SMEs toward sustainable manufacturing. When managers and practitioners try to convert their business digitally, this study also enables them to prioritize the many I4.0 factors that are most important to their organization. The model was validated by a regional application in Saudi Arabia.
{"title":"Industry 4.0 factors affecting SMEs towards sustainable manufacturing","authors":"Nagendra Kumar Sharma , Vimal Kumar , Pratima Verma , Mahak Sharma , Ashwaq Al Khalil , Tugrul Daim","doi":"10.1016/j.techsoc.2024.102746","DOIUrl":"10.1016/j.techsoc.2024.102746","url":null,"abstract":"<div><div>Industry 4.0 (I4.0) is one of the essential topics that has been researched extensively in the research domain. In the same way, there are also several research available to check the connections between I4.0 and sustainable manufacturing. It is because of the increasing concern of stakeholders over environmental challenges that manufacturing units are often blamed. It is also true that a major part of manufacturing is done by SMEs in almost every developed or developing economy of the world including India. Therefore, the present research work took place to identify the factors that are essential for sustainable manufacturing using I4.0 in Indian SMEs. In the present study, a total of six factors were identified from the previous studies, which are technological factors (TF), organizational factors (OF), environmental factors (ENF), societal factors (SF), economic factors (ECF), and external stakeholders' factors (ESF) considering the triple bottom line (TBL) approach of the sustainability model. Each factor consists of a few sub-factors, and a total of thirty-five factors were developed. The best-worst method (BWM) and Hierarchical Decision Model (HDM) were applied to bring the results. The result suggests that OF and TF are ranked number one and two respectively. ECF and ENF ranked at three and four whereas, ESF and SF ranked at five and six respectively. The study helps firm managers revolutionize their organizations’ approach to the sustainability model by looking at the Industry 4.0 factors affecting SMEs toward sustainable manufacturing. When managers and practitioners try to convert their business digitally, this study also enables them to prioritize the many I4.0 factors that are most important to their organization. The model was validated by a regional application in Saudi Arabia.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"79 ","pages":"Article 102746"},"PeriodicalIF":10.1,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.techsoc.2024.102753
Xiaowei Ding , Darko B. Vuković , Boris I. Sokolov , Natalia Vukovic , Yali Liu
This study uses sustainability and stakeholder theories to examine how corporate digital transformation (DIT) impacts ESG (Environmental, Social, Governance) performance, focusing on listed Chinese manufacturing firms from 2015 to 2020. The analysis employs two-stage least squares model (2SLS) and propensity score matching-differences in differences (PSM-DID) technique to address endogeneity, and a series of robustness checks to validate the results. Findings reveal that DIT enhances ESG performance by fostering green innovation, encouraging risk-taking, and optimizing resource allocation. Economic policy uncertainty and executives' gender diversity impede these benefits, while party organization embeddedness shows no moderating effect. Additionally, the study identifies spatial spillover effects of DIT on ESG performance, with synergistic effects observed among companies within the same locality and industry. These insights offer profound implications for governmental efforts to improve the business environment and promote green development, ensuring the equitable distribution of "digital dividends” among stakeholders.
本研究运用可持续发展理论和利益相关者理论，以2015-2020年中国制造业上市公司为研究对象，探讨企业数字化转型（DIT）如何影响ESG（环境、社会和治理）绩效。分析采用了两阶段最小二乘法模型（2SLS）和倾向得分匹配-差异（PSM-DID）技术来解决内生性问题，并进行了一系列稳健性检验来验证结果。研究结果表明，DIT 通过促进绿色创新、鼓励风险承担和优化资源配置，提高了企业的环境、社会和治理绩效。经济政策的不确定性和高管的性别多样性阻碍了这些益处的实现，而党组织的嵌入性则没有显示出调节作用。此外，研究还发现了 DIT 对环境、社会和公司治理绩效的空间溢出效应，在同一地区和行业的公司之间观察到了协同效应。这些见解为政府改善商业环境、促进绿色发展、确保在利益相关者之间公平分配 "数字红利 "提供了深远影响。
{"title":"Enhancing ESG performance through digital transformation: Insights from China's manufacturing sector","authors":"Xiaowei Ding , Darko B. Vuković , Boris I. Sokolov , Natalia Vukovic , Yali Liu","doi":"10.1016/j.techsoc.2024.102753","DOIUrl":"10.1016/j.techsoc.2024.102753","url":null,"abstract":"<div><div>This study uses sustainability and stakeholder theories to examine how corporate digital transformation (DIT) impacts ESG (Environmental, Social, Governance) performance, focusing on listed Chinese manufacturing firms from 2015 to 2020. The analysis employs two-stage least squares model (2SLS) and propensity score matching-differences in differences (PSM-DID) technique to address endogeneity, and a series of robustness checks to validate the results. Findings reveal that DIT enhances ESG performance by fostering green innovation, encouraging risk-taking, and optimizing resource allocation. Economic policy uncertainty and executives' gender diversity impede these benefits, while party organization embeddedness shows no moderating effect. Additionally, the study identifies spatial spillover effects of DIT on ESG performance, with synergistic effects observed among companies within the same locality and industry. These insights offer profound implications for governmental efforts to improve the business environment and promote green development, ensuring the equitable distribution of \"digital dividends” among stakeholders.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"79 ","pages":"Article 102753"},"PeriodicalIF":10.1,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.techsoc.2024.102752
Zhiyao Sun , Shuai Che , Jie Wang
Some viewpoints suggest that IT investment seems to fail to significantly stimulate enterprise productivity in some cases. Therefore, revealing the impact of AI on firm productivity is an important topic to analyze whether Solow's paradox can be valid in the digital age. Based on panel data of 3235 listed companies in China from 2007 to 2021, we comprehensively discuss the impact and mechanism of AI on firm productivity using fixed-effects model, systematic GMM model, and mediated-effects model. Key findings include: AI significantly improves firm productivity, especially in state-controlled, internationally minded, and innovative firms. Mitigating information asymmetry is a key channel, while specialized division of labor and independent green innovation are potential ones. Supply chain digital transformation policies enhance the productivity effect of AI, and AI shows green development benefits. Additionally, the dynamic decomposition effect shows that the productivity-enhancing effect of AI is slowing down in the long run. This research provides important insights into understanding AI's role in the digital age and holds significance for firms and policymakers.
{"title":"Deconstruct artificial intelligence's productivity impact: A new technological insight","authors":"Zhiyao Sun , Shuai Che , Jie Wang","doi":"10.1016/j.techsoc.2024.102752","DOIUrl":"10.1016/j.techsoc.2024.102752","url":null,"abstract":"<div><div>Some viewpoints suggest that IT investment seems to fail to significantly stimulate enterprise productivity in some cases. Therefore, revealing the impact of AI on firm productivity is an important topic to analyze whether Solow's paradox can be valid in the digital age. Based on panel data of 3235 listed companies in China from 2007 to 2021, we comprehensively discuss the impact and mechanism of AI on firm productivity using fixed-effects model, systematic GMM model, and mediated-effects model. Key findings include: AI significantly improves firm productivity, especially in state-controlled, internationally minded, and innovative firms. Mitigating information asymmetry is a key channel, while specialized division of labor and independent green innovation are potential ones. Supply chain digital transformation policies enhance the productivity effect of AI, and AI shows green development benefits. Additionally, the dynamic decomposition effect shows that the productivity-enhancing effect of AI is slowing down in the long run. This research provides important insights into understanding AI's role in the digital age and holds significance for firms and policymakers.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"79 ","pages":"Article 102752"},"PeriodicalIF":10.1,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.techsoc.2024.102751
Jianlong Wang , Yong Liu , Weilong Wang , Haitao Wu
In the pursuit of climate change mitigation and carbon neutrality, climate policy uncertainty (CPU) poses a threat to enterprises' green, low-carbon, and sustainable development. The intelligent transformation of enterprises is a crucial strategy for addressing climate risks and enhancing energy efficiency. However, there is a lack of research on how intelligent transformation impacts low-carbon development from the perspective of micro-enterprises. Based on this gap, we analyze data from Shanghai and Shenzhen A-share listed manufacturing enterprises from 2010 to 2022 to empirically test the impact of intelligent manufacturing (IM) on enterprise carbon emission performance (ECEP) using a difference-in-differences model. We also explore the moderating effect of IM on the relationship between CPU and ECEP. Our findings indicate that IM significantly enhances ECEP. IM boosts the ECEP of enterprises in the eastern region, state-owned enterprises, and capital- and technology-intensive sectors. Green technological innovation, human capital, and organizational resilience are key mechanisms through which IM enhances ECEP. Further analysis reveals that CPU significantly inhibits ECEP, whereas IM positively moderates the impact of CPU. In the context of external environmental uncertainty, this study offers crucial insights into how intelligent technology can strengthen the real economy and facilitate the low-carbon transformation of manufacturing enterprises.
在追求减缓气候变化和碳中和的过程中，气候政策的不确定性（CPU）对企业的绿色、低碳和可持续发展构成了威胁。企业智能化转型是应对气候风险、提高能源效率的重要战略。然而，目前还缺乏从微型企业角度研究智能转型如何影响低碳发展。基于这一空白，我们分析了 2010 年至 2022 年沪深 A 股上市制造业企业的数据，采用差分模型实证检验了智能制造（IM）对企业碳排放绩效（ECEP）的影响。我们还探讨了智能制造对 CPU 与 ECEP 之间关系的调节作用。我们的研究结果表明，智能制造能显著提高企业碳排放绩效。对于东部地区企业、国有企业以及资本和技术密集型部门而言，企业即时信息能促进其 ECEP。绿色技术创新、人力资本和组织复原力是 IM 增强 ECEP 的关键机制。进一步的分析表明，CPU 对 ECEP 有明显的抑制作用，而 IM 对 CPU 的影响有积极的调节作用。在外部环境不确定的背景下，本研究为智能技术如何加强实体经济、促进制造企业低碳转型提供了重要启示。
{"title":"Does artificial intelligence improve enterprise carbon emission performance? Evidence from an intelligent transformation policy in China","authors":"Jianlong Wang , Yong Liu , Weilong Wang , Haitao Wu","doi":"10.1016/j.techsoc.2024.102751","DOIUrl":"10.1016/j.techsoc.2024.102751","url":null,"abstract":"<div><div>In the pursuit of climate change mitigation and carbon neutrality, climate policy uncertainty (CPU) poses a threat to enterprises' green, low-carbon, and sustainable development. The intelligent transformation of enterprises is a crucial strategy for addressing climate risks and enhancing energy efficiency. However, there is a lack of research on how intelligent transformation impacts low-carbon development from the perspective of micro-enterprises. Based on this gap, we analyze data from Shanghai and Shenzhen A-share listed manufacturing enterprises from 2010 to 2022 to empirically test the impact of intelligent manufacturing (IM) on enterprise carbon emission performance (ECEP) using a difference-in-differences model. We also explore the moderating effect of IM on the relationship between CPU and ECEP. Our findings indicate that IM significantly enhances ECEP. IM boosts the ECEP of enterprises in the eastern region, state-owned enterprises, and capital- and technology-intensive sectors. Green technological innovation, human capital, and organizational resilience are key mechanisms through which IM enhances ECEP. Further analysis reveals that CPU significantly inhibits ECEP, whereas IM positively moderates the impact of CPU. In the context of external environmental uncertainty, this study offers crucial insights into how intelligent technology can strengthen the real economy and facilitate the low-carbon transformation of manufacturing enterprises.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"79 ","pages":"Article 102751"},"PeriodicalIF":10.1,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-30DOI: 10.1016/j.techsoc.2024.102747
Keith Jin Deng Chan , Gleb Papyshev , Masaru Yarime
In response to the rapid development of AI, several governments have established a variety of regulatory interventions for this technology. While some countries prioritize consumer protection through stringent regulation, others promote innovation by adopting a more hands-off approach. However, this tradeoff has not been analyzed systematically. We developed an economic theory on how the welfare-maximizing level of regulatory stringency for AI depends on various institutional parameters. Our game-theoretic model is motivated and built upon the comparison of regulatory documents for AI from the EU, the UK, the US, Russia, and China. The results show that if a government strives to find the right balance between innovation and consumer protection to maximize actual consumer welfare, stringent regulation is optimal when foreign competition is either high or low, whereas light-touch regulation is optimal when foreign competition is intermediate. Meanwhile, minimal regulation is rationalizable only if a government prioritizes other objectives in its agenda, such as maximizing innovation, domestic producer surplus, or perceived consumer welfare.
{"title":"Balancing the tradeoff between regulation and innovation for artificial intelligence: An analysis of top-down command and control and bottom-up self-regulatory approaches","authors":"Keith Jin Deng Chan , Gleb Papyshev , Masaru Yarime","doi":"10.1016/j.techsoc.2024.102747","DOIUrl":"10.1016/j.techsoc.2024.102747","url":null,"abstract":"<div><div>In response to the rapid development of AI, several governments have established a variety of regulatory interventions for this technology. While some countries prioritize consumer protection through stringent regulation, others promote innovation by adopting a more hands-off approach. However, this tradeoff has not been analyzed systematically. We developed an economic theory on how the welfare-maximizing level of regulatory stringency for AI depends on various institutional parameters. Our game-theoretic model is motivated and built upon the comparison of regulatory documents for AI from the EU, the UK, the US, Russia, and China. The results show that if a government strives to find the right balance between innovation and consumer protection to maximize actual consumer welfare, stringent regulation is optimal when foreign competition is either high or low, whereas light-touch regulation is optimal when foreign competition is intermediate. Meanwhile, minimal regulation is rationalizable only if a government prioritizes other objectives in its agenda, such as maximizing innovation, domestic producer surplus, or perceived consumer welfare.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"79 ","pages":"Article 102747"},"PeriodicalIF":10.1,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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