Technology in Society最新文献_第6页

The impact of circular economy, sustainable infrastructure, and green FinTech on biodiversity in Europe: A holistic approach

IF 10.1 1区社会学

Technology in Society Pub Date : 2025-02-14 DOI: 10.1016/j.techsoc.2025.102841

Shayan Khan Kakar , Jing Wang , Noman Arshed , Tran Thi Le Hien , Sehrish Akhter , Nazir Muhammad Abdullahi

{"title":"The impact of circular economy, sustainable infrastructure, and green FinTech on biodiversity in Europe: A holistic approach","authors":"Shayan Khan Kakar , Jing Wang , Noman Arshed , Tran Thi Le Hien , Sehrish Akhter , Nazir Muhammad Abdullahi","doi":"10.1016/j.techsoc.2025.102841","DOIUrl":"10.1016/j.techsoc.2025.102841","url":null,"abstract":"<div><div>As Europe strives for environmental sustainability, integrating a circular economy, sustainable infrastructure, and green FinTech is crucial for enhancing biodiversity conservation. This study investigates the intricate relationship between circular economy, sustainable infrastructure, green FinTech, and European biodiversity conservation. To this end, this study constructs a 24-year panel dataset from 39 European countries. It employs a novel econometric technique called time-specific heterogeneous factor analysis to create indices for a circular economy, sustainable infrastructure, and green FinTech. Additionally, the study employed an advanced econometric Panel Autoregressive Distributed Lag model with Pooled Mean and Fourier specification (PARDL-PMG-Fourier). The findings show that the implementation of green FinTech significantly boosts biodiversity in Europe; the circular economy dampens this impact. The implementation of sustainable infrastructure considerably enhanced the conservation of biodiversity in Europe; similarly, SIN1 shows a significant cyclical or seasonal impact on biodiversity in the short run. This study proposes solid policy recommendations for the European Union, European Commission, regulators, and policymakers. The European Commission and regulators must prioritize the adoption of green FinTech to boost financial market operations and activities, refine circular economy initiatives, and emphasize sustainable infrastructure development projects. Targeted investment is necessary for sustainable resource utilization, recycling, waste reduction, and eco-friendly infrastructure in European projects. By doing so, Europe can effectively boost biodiversity conservation by mitigating cyclical and seasonal risks. These policy implications offer a streamlined framework for achieving economic and environmental sustainability goals in Europe.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"81 ","pages":"Article 102841"},"PeriodicalIF":10.1,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143446140","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

Assessing the ecology of cluster-based enterprise trust networks through percolation theory: Is your business environment trustworthy?

IF 10.1 1区社会学

Technology in Society Pub Date : 2025-02-12 DOI: 10.1016/j.techsoc.2025.102839

Guanghui He, Shicheng Zhou

{"title":"Assessing the ecology of cluster-based enterprise trust networks through percolation theory: Is your business environment trustworthy?","authors":"Guanghui He, Shicheng Zhou","doi":"10.1016/j.techsoc.2025.102839","DOIUrl":"10.1016/j.techsoc.2025.102839","url":null,"abstract":"<div><div>Since 2023, bank failures in America and Europe have reignited concerns about trust in credit transactions. During financial turbulence, heightened attention tends to be directed towards inter-enterprise trust management. However, existing studies have mainly focused on individual enterprise credit credibility, leaving a gap in analysing trust ecology within entire enterprise clusters. This study proposes an enterprise trust ecology assessment based on percolation theory. First, we established cluster-based enterprise trust networks (C-ETNs) and employed an entropy method to calculate the trust values of enterprise nodes. Subsequently, based on percolation theory, we mapped the trust ecology evolution to point percolation model to quantify trust ecology. Through simulations and data analysis of Chinese A-shares from 2007 to 2021, we uncovered a phase-transition phenomenon in trust ecology improvement. Trust in A-shares moderately improved, with business and comprehensive industry sectors as well as midland and west areas showing prominent improvement. However, overall trust ecology remained in early-phase transition, and almost all sectors and regions experienced upward bottlenecks. This study provides a new technical method for improving credit management in inter-enterprise transactions, thus enhancing market credit construction. Its extensive application is also valuable for economic and societal trust concerns.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"81 ","pages":"Article 102839"},"PeriodicalIF":10.1,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429237","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

The ethics of generative AI in social science research: A qualitative approach for institutionally grounded AI research ethics

IF 10.1 1区社会学

Technology in Society Pub Date : 2025-02-11 DOI: 10.1016/j.techsoc.2025.102836

June Jeon , Lanu Kim , Jaehyuk Park

{"title":"The ethics of generative AI in social science research: A qualitative approach for institutionally grounded AI research ethics","authors":"June Jeon , Lanu Kim , Jaehyuk Park","doi":"10.1016/j.techsoc.2025.102836","DOIUrl":"10.1016/j.techsoc.2025.102836","url":null,"abstract":"<div><div>Despite growing attention to the ethics of Generative AI, there has been little discussion about how research ethics should be updated for social science research practice. This paper fills this gap at the intersection of AI ethics and social science research ethics. Based on 17 semi-structured interviews, we present three narratives about generative AI and research ethics: 1) the equalizer narrative, 2) the meritocracy narrative, and 3) the community narrative. We argue that the ethics of AI-assisted social-scientific research cannot be reduced to universal checklists, and institutionally grounded research ethics principles are necessary. In all of the narratives, the technical functions of Generative AI were merely necessary conditions of unethical practices, while ethical dilemmas started to arise when such functions were situated in the institutional arrangements of academia. Our findings suggest that the ethics of AI-assisted research should encompass not only specific ethical rules concerning AI functionalities but also incorporate community engagement, educational imperatives, institutional governance, and the societal impact of such technologies to organize “ethics-in-practice.” This will require democratic deliberations to address the complex, emergent interactions between AI systems and societal structures.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"81 ","pages":"Article 102836"},"PeriodicalIF":10.1,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429154","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

Innovative resources driven artificial intelligence orientation: The moderating role of environmental and executives’ characteristics 创新资源驱动人工智能导向：环境和管理人员特征的调节作用

IF 10.1 1区社会学

Technology in Society Pub Date : 2025-02-11 DOI: 10.1016/j.techsoc.2025.102837

Wucheng Han , Weijie Zhu , Zhaoli Song , Ruoyu Lu

{"title":"Innovative resources driven artificial intelligence orientation: The moderating role of environmental and executives’ characteristics","authors":"Wucheng Han , Weijie Zhu , Zhaoli Song , Ruoyu Lu","doi":"10.1016/j.techsoc.2025.102837","DOIUrl":"10.1016/j.techsoc.2025.102837","url":null,"abstract":"<div><div>In the era of rapid artificial intelligence (AI) technology advancement, enterprises increasingly consider AI as a strategic imperative. However, the determinants of AI adoption and strategy formulation in enterprises remain elusive. Drawing on an integrated Resource-Based View (RBV) and Strategic Choice Theory (SCT) framework, this study presents a theoretical model that scrutinizes the factors and boundary conditions influencing enterprises in crafting AI strategies. Empirical assessments of theoretical hypotheses were conducted utilizing survey data gathered from 717 executives across global firms. We found strong evidence that internal innovation resources (IIR) and collaborative innovation networks (CIN) have a positive impact on firm's AI orientation. The study revealed that environmental uncertainty (EU) can negatively moderate the relationship between internal innovation resources, collaborative innovation networks, and AI orientation. A positive moderating effect was observed between corporate digital culture (DC) and the relationship between internal innovation resources, collaborative innovation networks, and AI orientation. Meanwhile, we found a positive moderating effect of Executives' Not-Invented-Here Syndrome (NIHS) on the relationship between internal innovation resources and AI orientation. This research contributes to the ongoing discourse on AI strategy in management and offers valuable guidance for organizations seeking to harness the potential of AI in a rapidly changing business environment.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"81 ","pages":"Article 102837"},"PeriodicalIF":10.1,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422628","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

Algorithmic trust and regulation: Governance, ethics, legal, and social implications blueprint for Indonesia's central banking

IF 10.1 1区社会学

Technology in Society Pub Date : 2025-02-11 DOI: 10.1016/j.techsoc.2025.102838

Arif Perdana , Saru Arifin , Novi Quadrianto

{"title":"Algorithmic trust and regulation: Governance, ethics, legal, and social implications blueprint for Indonesia's central banking","authors":"Arif Perdana , Saru Arifin , Novi Quadrianto","doi":"10.1016/j.techsoc.2025.102838","DOIUrl":"10.1016/j.techsoc.2025.102838","url":null,"abstract":"<div><div>Algorithm-driven financial systems significantly influence monetary stability and payment transactions. While these systems bring opportunities like automation and predictive analytics, they also raise ethical concerns, particularly biases embedded in historical data. Recognizing the critical role of governance, ethics, legal considerations, and social implications (GELSI), this study introduces a framework tailored for algorithmic systems in financial services, focusing on Indonesia's evolving regulatory environment. Using the Multiple Streams Approach (MSA) as our theoretical lens, we offer a framework that augments existing quantitative methodologies. Our study provides a nuanced, qualitative perspective on algorithmic trust and regulation. We proffer actionable strategies for the Central Bank of Indonesia (BI), emphasizing stringent data governance, system resilience, and cross-sector collaboration. Our findings highlight the critical importance of ethical guidelines and robust governmental policies in mitigating algorithmic risks. We combine theory and practical advice to show how to align problems, policies, and politics to create practical opportunities for algorithmic governance. This study contributes to the evolving discourse on responsible financial technology. Our study recommends a balanced way to manage the challenges of innovation, regulation, and ethics in the age of algorithms.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"81 ","pages":"Article 102838"},"PeriodicalIF":10.1,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143445697","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

Combining a conjoint experiment and machine learning model to include end-users in a constructive technology assessment: The case of seasonal thermal energy storage

IF 10.1 1区社会学

Technology in Society Pub Date : 2025-02-11 DOI: 10.1016/j.techsoc.2025.102833

Guillaume Zumofen

{"title":"Combining a conjoint experiment and machine learning model to include end-users in a constructive technology assessment: The case of seasonal thermal energy storage","authors":"Guillaume Zumofen","doi":"10.1016/j.techsoc.2025.102833","DOIUrl":"10.1016/j.techsoc.2025.102833","url":null,"abstract":"<div><div>By definition, the mapping of technological development occurs in the context of uncertainty and with a risk of failure. Decisions taken at the onset of the development phase are significant because the technology has not reached the market yet. The technology loses its malleability during the development phase because of entrenchment. Thus, the objective of a constructive technological assessment is to embed social aspects – additional perspectives – in the context of technological developments. In line with extant literature, a pivotal perspective is the (future) end-user of the technology. Hence, market acceptance remains a constraining factor in technological development, notably for renewable energy technology. However, existing studies have not included (future) end-users in development phases. They have always taken place after the technology has reached the market.</div><div>To bring technological development and market acceptance closer, this study develops an innovative method that combines a conjoint experiment with a supervised machine learning model to predict the behavioural intention of end-users to accept a new (energy) technology. This study illustrates the proposed methodology through a conjoint experiment on seasonal thermal energy storage. The ML model uses input from a survey with a conjoint experiment to predict end-users’ market acceptance. With N = 12,096 (1008 participants exposed to 6 x 2 conjoint tasks), the ML model predicts behavioural intention with an accuracy of RMSE = 1.55 on a 10-point scale. The model is then used to predict hypothetical acceptance from mock end-users’ profiles and varying technological features. Thus, this study opens new perspectives for constructive technology assessment and conjoint experiment literature, and furthers discussions on social acceptance of energy technologies.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"81 ","pages":"Article 102833"},"PeriodicalIF":10.1,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429155","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

Designing engagement: Exploring affordances in freemium digital games

IF 10.1 1区社会学

Technology in Society Pub Date : 2025-02-11 DOI: 10.1016/j.techsoc.2025.102840

Ha Eun (Grace) Park

引用次数: 0

Enhancing SME resilience through artificial intelligence and strategic foresight: A framework for sustainable competitiveness 通过人工智能和战略远见增强中小企业的应变能力：可持续竞争力框架

IF 10.1 1区社会学

Technology in Society Pub Date : 2025-02-06 DOI: 10.1016/j.techsoc.2025.102835

Elias G. Carayannis , Roman Dumitrescu , Tommy Falkowski , George Papamichail , Nikos - Rigert Zota

引用次数: 0

Digital transformation and socio-economic development in emerging economies: A multinational analysis

IF 10.1 1区社会学

Technology in Society Pub Date : 2025-02-04 DOI: 10.1016/j.techsoc.2025.102834

Lemuel Kenneth David , Jianling Wang , William Brooks , Vanessa Angel

引用次数: 0

Sustainable crowdshipping: Navigating technological fit and security risks

IF 10.1 1区社会学

Technology in Society Pub Date : 2025-01-31 DOI: 10.1016/j.techsoc.2025.102832

Rachel Chua, Min Wu, Kum Fai Yuen

{"title":"Sustainable crowdshipping: Navigating technological fit and security risks","authors":"Rachel Chua, Min Wu, Kum Fai Yuen","doi":"10.1016/j.techsoc.2025.102832","DOIUrl":"10.1016/j.techsoc.2025.102832","url":null,"abstract":"<div><div>‘Crowdshipping’ (CS), a burgeoning trend propelled by the upsurge in e-commerce after the COVID-19 pandemic, combines crowdsourcing and shipping, giving rise to a novel logistical paradigm. While shipping entails the physical transportation of goods, crowdsourcing involves task delegation to a network of individuals through an open call. This departure from conventional courier services for last-mile delivery leverages the collective potential of the online public. Using the health belief model and task–technology fit (TTF) theory, this study introduces a theoretical model that delves into the fundamental factors influencing consumer acceptance of CS as a last-mile delivery service within urban landscapes, encompassing its technological alignment. A comprehensive analysis of 450 survey responses, using structural equation modelling, revealed that expected outcome, self-efficacy, perceived threat (security and privacy) and cues to action directly influence consumers acceptance. Contrarily, task and technology characteristics can indirectly influence consumer acceptance through TTF. Analysis of the total effects revealed that cues to action have the strongest impact on consumer acceptance. The study aimed to illuminate consumer perspectives regarding the integration of CS as a last-mile delivery alternative and to enrich urban green logistical planning and regulatory frameworks for policymakers accordingly.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"81 ","pages":"Article 102832"},"PeriodicalIF":10.1,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143103619","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