Technology in Society最新文献_第8页

Exploring determinants influencing artificial intelligence adoption, reference to diffusion of innovation theory 参考创新扩散理论，探索影响人工智能应用的决定因素

IF 10.1 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2024-11-05 DOI: 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.

一个组织接受创新的能力在很大程度上取决于其领导能力。尽管众所周知，领导力会影响采用的所有三个阶段（启动、采用和常规化），但文献尚未研究促进这些阶段的具体领导力要素。本文借鉴了有关变革型领导力和人工智能采用的现有文献，探讨了变革型领导力如何促进人工智能技术的成功实施。本文探讨了组织内变革型领导力与人工智能（AI）应用的交叉点。本研究利用来自 250 家公司的数据，开发并评估了一个将创新扩散（DOI）理论与变革型领导力（TL）相结合的框架。研究结果采用结构方程建模（SEM）技术进行分析。研究探讨了影响采用人工智能这一新技术的决定因素。研究发现，TL 是采用人工智能的关键驱动因素，而愿景和智力激励等要素对采用人工智能的意向至关重要。此外，这项研究还表明，采用人工智能这样的重大创新与领导者的愿景以及尊重和认识他人感受和需求的能力（两者都是提供个人帮助的指标）密切相关。此外，研究还为领导者提供了实际意义和建议，以便他们在采用人工智能的复杂环境中游刃有余。

{"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}

引用次数: 0

Advanced cryopreservation as an emergent and convergent technological platform 先进的冷冻保存技术是一种新兴的融合技术平台

IF 10.1 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2024-11-02 DOI: 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.

先进的低温保存技术有可能改变器官移植、生物医学研究、食品贮存、水产养殖、生物多样性储存库、生态恢复和许多其他应用。这些技术超越了现有冷冻保存技术的能力，可延长从细胞到组织、器官和整个生物体等不同规模的生物材料的寿命和活力。在本文中，我们将对先进低温保存技术的创新（我们将其分析为新兴的、融合的平台技术）提出新的研究伦理和协调、管理以及公平获取利益的问题。作为新兴技术，它们可能会扰乱市场或破坏社会机构的稳定，包括管理移植器官分配的系统。作为融合技术，它们的影响将通过与其他技术的互动而加剧。可能会加剧高级低温保存技术的社会和伦理影响的技术包括：能够管理复杂的储存和运输物流的信息技术、管理花卉和动物物种和种群的生物技术，以及能够开发和分发这一平台技术的可定制外围组件的三维打印技术。核心平台不同应用领域的发展速度可能因部门而异，这既要考虑到公众的支持，也要考虑到道德约束，而且任何部门的进步都将影响核心技术在各部门的可靠性。我们建议在开发外围组件和核心技术的具体情况下评估社会效益和风险。

{"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}

引用次数: 0

Industry 4.0 factors affecting SMEs towards sustainable manufacturing 影响中小企业实现可持续制造的工业 4.0 因素

IF 10.1 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2024-11-02 DOI: 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.

工业 4.0（I4.0）是研究领域广泛研究的重要课题之一。同样，也有一些研究可以检验工业 4.0 与可持续制造之间的联系。正是由于利益相关者对环境挑战的日益关注，制造单位常常受到指责。同样，在包括印度在内的世界上几乎所有发达或发展中经济体中，大部分制造业都是由中小企业完成的。因此，本研究工作旨在确定印度中小型企业使用 I4.0 进行可持续制造的关键因素。考虑到可持续发展模型的三重底线（TBL）方法，本研究从以往的研究中确定了六个因素，即技术因素（TF）、组织因素（OF）、环境因素（ENF）、社会因素（SF）、经济因素（ECF）和外部利益相关者因素（ESF）。每个因素由几个子因素组成，共制定了 35 个因素。应用最佳-最差法（BWM）和层次决策模型（HDM）得出结果。结果表明，OF 和 TF 分别排名第一和第二。ECF和ENF分别排在第三和第四位，而ESF和SF分别排在第五和第六位。本研究通过研究影响中小企业实现可持续制造的工业 4.0 因素，帮助企业管理者彻底改变其组织的可持续发展模式。当管理者和从业人员试图将其业务数字化时，本研究还能帮助他们优先考虑对其组织最重要的众多工业 4.0 因素。该模型在沙特阿拉伯的地区应用中得到了验证。

{"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}

引用次数: 0

Enhancing ESG performance through digital transformation: Insights from China's manufacturing sector 通过数字化转型提高环境、社会和公司治理绩效：中国制造业的启示

IF 10.1 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2024-11-01 DOI: 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}

引用次数: 0

Deconstruct artificial intelligence's productivity impact: A new technological insight 解构人工智能对生产力的影响：新的技术见解

IF 10.1 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2024-11-01 DOI: 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.

一些观点认为，在某些情况下，信息技术投资似乎无法显著提高企业的生产率。因此，揭示人工智能对企业生产率的影响，是分析索洛悖论在数字时代是否成立的重要课题。基于2007-2021年中国3235家上市公司的面板数据，我们采用固定效应模型、系统GMM模型和中介效应模型，全面探讨了人工智能对企业生产率的影响及机制。主要结论包括人工智能极大地提高了企业生产率，尤其是国有控股企业、具有国际视野的企业和创新型企业。缓解信息不对称是关键渠道，专业化分工和自主绿色创新是潜在渠道。供应链数字化转型政策增强了人工智能的生产率效应，而人工智能则显示出绿色发展效益。此外，动态分解效应表明，从长期来看，人工智能的生产率提升效应正在放缓。这项研究为理解人工智能在数字时代的作用提供了重要见解，对企业和政策制定者具有重要意义。

{"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}

引用次数: 0

Does artificial intelligence improve enterprise carbon emission performance? Evidence from an intelligent transformation policy in China 人工智能能否改善企业碳排放绩效？来自中国智能转型政策的证据

IF 10.1 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2024-11-01 DOI: 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}

引用次数: 0

Balancing the tradeoff between regulation and innovation for artificial intelligence: An analysis of top-down command and control and bottom-up self-regulatory approaches 平衡人工智能监管与创新之间的权衡：自上而下的命令与控制和自下而上的自我监管方法分析

IF 10.1 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2024-10-30 DOI: 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.

为了应对人工智能的快速发展，一些国家的政府针对这项技术制定了各种监管干预措施。一些国家通过严格监管优先保护消费者，而另一些国家则通过采取更加放手的方式促进创新。然而，这种权衡尚未得到系统分析。我们提出了一种经济理论，说明人工智能的福利最大化监管严格程度如何取决于各种制度参数。我们的博弈论模型是在比较欧盟、英国、美国、俄罗斯和中国的人工智能监管文件的基础上建立的。结果表明，如果政府努力在创新和消费者保护之间寻求适当的平衡，以实现消费者实际福利的最大化，那么当外国竞争程度较高或较低时，严格监管是最优选择，而当外国竞争处于中等水平时，轻触式监管是最优选择。同时，只有当政府在其议程中优先考虑其他目标，如创新、国内生产者盈余或消费者福利最大化时，最低限度的监管才是合理的。

{"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}

引用次数: 0

Green entrepreneurship success in the age of generative artificial intelligence: The interplay of technology adoption, knowledge management, and government support 生成式人工智能时代的绿色创业成功：技术采用、知识管理和政府支持的相互作用

IF 10.1 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2024-10-30 DOI: 10.1016/j.techsoc.2024.102744

Shaofeng Wang , Hao Zhang

This study investigates the integral role of generative artificial intelligence (GAI) in enhancing green entrepreneurship success, focusing on the interconnected dynamics of GAI adoption, green knowledge management, innovation, and government support. Despite the growing interest in GAI, existing research lacks an understanding of how GAI fosters green entrepreneurship success, particularly in green knowledge management and innovation pathways. Utilizing a robust theoretical framework grounded in resource orchestration and knowledge management theories, we examine the influence of GAI on acquiring and applying green knowledge and its subsequent impact on fostering green innovation. The study examines how government funding moderates these correlations. Employing PLS-SEM and fsQCA, the research elucidates complex interrelationships and causal paths. The findings reveal that GAI significantly enhances green knowledge management capabilities, which drives green innovation and entrepreneurship success. Additionally, government support plays a crucial role in amplifying these effects. This study contributes to technological change and social transformation discourse, offering practical insights for decision-makers and stakeholders in green entrepreneurship and policy-making.

本研究调查了生成式人工智能（GAI）在提高绿色创业成功率方面所起的不可或缺的作用，重点关注 GAI 的采用、绿色知识管理、创新和政府支持之间相互关联的动态。尽管人们对 GAI 的兴趣与日俱增，但现有研究对 GAI 如何促进绿色创业成功缺乏了解，尤其是在绿色知识管理和创新途径方面。利用以资源协调和知识管理理论为基础的强大理论框架，我们研究了 GAI 对获取和应用绿色知识的影响，及其对促进绿色创新的后续影响。研究还探讨了政府资助如何调节这些相关性。研究采用 PLS-SEM 和 fsQCA，阐明了复杂的相互关系和因果路径。研究结果表明，GAI 能显著提高绿色知识管理能力，从而推动绿色创新和创业成功。此外，政府支持在放大这些效应方面发挥着至关重要的作用。这项研究有助于技术变革和社会转型方面的讨论，为绿色创业和政策制定方面的决策者和利益相关者提供了实用的见解。

{"title":"Green entrepreneurship success in the age of generative artificial intelligence: The interplay of technology adoption, knowledge management, and government support","authors":"Shaofeng Wang , Hao Zhang","doi":"10.1016/j.techsoc.2024.102744","DOIUrl":"10.1016/j.techsoc.2024.102744","url":null,"abstract":"<div><div>This study investigates the integral role of generative artificial intelligence (GAI) in enhancing green entrepreneurship success, focusing on the interconnected dynamics of GAI adoption, green knowledge management, innovation, and government support. Despite the growing interest in GAI, existing research lacks an understanding of how GAI fosters green entrepreneurship success, particularly in green knowledge management and innovation pathways. Utilizing a robust theoretical framework grounded in resource orchestration and knowledge management theories, we examine the influence of GAI on acquiring and applying green knowledge and its subsequent impact on fostering green innovation. The study examines how government funding moderates these correlations. Employing PLS-SEM and fsQCA, the research elucidates complex interrelationships and causal paths. The findings reveal that GAI significantly enhances green knowledge management capabilities, which drives green innovation and entrepreneurship success. Additionally, government support plays a crucial role in amplifying these effects. This study contributes to technological change and social transformation discourse, offering practical insights for decision-makers and stakeholders in green entrepreneurship and policy-making.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"79 ","pages":"Article 102744"},"PeriodicalIF":10.1,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142560736","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}

引用次数: 0

Back to the future: Entrepreneurial leadership and levelling up in the mobile-gaming sector 回到未来：移动游戏行业的创业领导力和水平提升

IF 10.1 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2024-10-29 DOI: 10.1016/j.techsoc.2024.102748

Colin Donaldson , Jorge Villagrasa , Joaquin Alegre , Eric W. Liguori

Start-ups in dynamic industries frequently pivot their focus, which can help them develop a clear strategic position and subsequently generate a competitive advantage. Whether to pivot or persevere becomes a real-time, critical, and multifaceted decision involving the founder, firm, and environment, but little is known about this complex interplay. Through an explorative case study, we tracked the founding, survival, and growth of Codigames, a high-performing Valencia-based mobile gaming start-up. We combine entrepreneurial leadership, decision-making, and perspective-taking theories to generate insight into critical moments in the start-up's lifepath, contributing to research on the contextualisation of entrepreneurship decision-making under uncertainty.

在充满活力的行业中，初创企业经常会调整自己的重点，这有助于它们形成清晰的战略定位，进而产生竞争优势。是转向还是坚持，是一个涉及创始人、公司和环境的实时、关键和多方面的决定，但人们对这种复杂的相互作用知之甚少。通过一项探索性案例研究，我们追踪了 Codigames 公司的创立、生存和成长过程，这是一家位于巴伦西亚的移动游戏初创企业，业绩优异。我们结合了创业领导力、决策和视角选择理论，对这家初创企业生命历程中的关键时刻进行了深入分析，为不确定性环境下的创业决策背景研究做出了贡献。

引用次数: 0

Tech for social good: Artificial intelligence and workplace safety 科技造福社会：人工智能与工作场所安全

IF 10.1 1区社会学 Q1 SOCIAL ISSUES

Technology in Society

Pub Date : 2024-10-29 DOI: 10.1016/j.techsoc.2024.102745

Xi Zhong, Jianquan She, Xiaojie Wu

The impact of artificial intelligence on the interests of corporate shareholders has been widely explored, but how it affects the interests of employees, particularly their workplace safety, has not yet been explored properly. This study examines the impact of artificial intelligence on workplace safety by applying Heinrich's domino theory. Using empirical data from listed companies in China from 2011 to 2022, we find that artificial intelligence will improve workplace safety. We attribute this to the fact that artificial intelligence reduces employees' unsafe behavior and suppresses the unsafe state of objects, which in turn promotes workplace safety. In addition, we find that military CEOs enhance the relationship, but foreign shareholders have no effect on it. Further tests show that the role of artificial intelligence in improving workplace safety is more pronounced in SOEs and firms that disclose corporate social responsibility (CSR). By incorporating Heinrich's domino theory, we provide new insights into the literature on artificial intelligence and workplace safety and new insights for governments and firms to improve workplace safety.

人工智能对企业股东利益的影响已被广泛探讨，但它如何影响员工利益，特别是他们的工作场所安全，还没有得到很好的探讨。本研究运用海因里希的多米诺骨牌理论，探讨人工智能对工作场所安全的影响。通过使用 2011 年至 2022 年中国上市公司的经验数据，我们发现人工智能将改善工作场所安全。这是因为人工智能减少了员工的不安全行为，抑制了物体的不安全状态，从而促进了工作场所的安全。此外，我们还发现，军方首席执行官会增强这种关系，但外资股东对其没有影响。进一步的测试表明，人工智能在改善工作场所安全方面的作用在国有企业和披露企业社会责任（CSR）的企业中更为明显。通过结合海因里希的多米诺骨牌理论，我们为有关人工智能和工作场所安全的文献提供了新的见解，也为政府和企业改善工作场所安全提供了新的启示。

{"title":"Tech for social good: Artificial intelligence and workplace safety","authors":"Xi Zhong, Jianquan She, Xiaojie Wu","doi":"10.1016/j.techsoc.2024.102745","DOIUrl":"10.1016/j.techsoc.2024.102745","url":null,"abstract":"<div><div>The impact of artificial intelligence on the interests of corporate shareholders has been widely explored, but how it affects the interests of employees, particularly their workplace safety, has not yet been explored properly. This study examines the impact of artificial intelligence on workplace safety by applying Heinrich's domino theory. Using empirical data from listed companies in China from 2011 to 2022, we find that artificial intelligence will improve workplace safety. We attribute this to the fact that artificial intelligence reduces employees' unsafe behavior and suppresses the unsafe state of objects, which in turn promotes workplace safety. In addition, we find that military CEOs enhance the relationship, but foreign shareholders have no effect on it. Further tests show that the role of artificial intelligence in improving workplace safety is more pronounced in SOEs and firms that disclose corporate social responsibility (CSR). By incorporating Heinrich's domino theory, we provide new insights into the literature on artificial intelligence and workplace safety and new insights for governments and firms to improve workplace safety.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"79 ","pages":"Article 102745"},"PeriodicalIF":10.1,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572069","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}

引用次数: 0