Technological Forecasting and Social Change最新文献

{"title":"Deploying explainable AI in entrepreneurial organizations: Role of the human-AI interface","authors":"Sanjay Chaudhary ,&nbsp;Ashraf Khalil ,&nbsp;Rekha Attri ,&nbsp;Peter Ractham","doi":"10.1016/j.techfore.2025.124324","DOIUrl":"10.1016/j.techfore.2025.124324","url":null,"abstract":"<div><div>The current advancement of artificial intelligence (AI) is the culmination of a prolonged effort to endow machines with human cognitive capabilities. Scholars and practitioners agree that AI has the potential to revolutionize decision-making in uncertain environments, with the potential role of AI in shaping entrepreneurial decision-making. Simultaneously, AI presents novel challenges, such as explainability, privacy, and data security, and may induce mistakes and ethical issues. As organizations and individuals expect AI decision-making processes to be transparent and understandable, the question of how entrepreneurial organizations adopt AI technologies remains unanswered. There is a lack of clarity on the implications of AI in the context of entrepreneurial organizations. To answer our research question, we conduct a qualitative study and use an interpretive research paradigm with an abductive approach to enrich the current understanding of the role of <em>Explainable</em> AI in shaping organizational processes and accomplishing organizational goals. The finding reveals that <em>Explainable</em> AI enables entrepreneurial organizations to align their decision-making. The role of the human-AI interface is crucial to leverage AI recommendations. We conclude with a discussion of future research on <em>Explainable</em> AI.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"220 ","pages":"Article 124324"},"PeriodicalIF":13.3,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144886140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI integration for climate risk mitigation: The role of organizational context","authors":"Muhammad Kaleem Khan ,&nbsp;Muhammad Jameel Hussain ,&nbsp;Muhammad Wasim Hussan ,&nbsp;Afifa Qadeer ,&nbsp;Anona Armstrong ,&nbsp;Shanshan Li","doi":"10.1016/j.techfore.2025.124327","DOIUrl":"10.1016/j.techfore.2025.124327","url":null,"abstract":"<div><div>This study examines the relationship between artificial intelligence (AI) adoption and Firm-Level Climate Change Risk (FLCCR) among Chinese enterprises. Using comprehensive firm-level data on AI implementation and FLCCR exposure, we analyze the contextual effectiveness of AI across diverse ownership structures, industry sectors, and corporate governance frameworks. Our empirical analysis reveals a robust association between AI adoption and reduced FLCCR, with findings consistent with established economic theories. The results remain statistically significant after addressing potential endogeneity concerns through multiple robustness checks. Our findings reveal that AI's climate risk-reduction potential is not uniform but context-dependent, varying significantly across ownership types, sectors, and governance characteristics. Notably, the risk-mitigating effects of AI appear particularly pronounced in state-owned enterprises, firms operating in pollution-intensive or high-technology sectors, and organizations with strong corporate governance mechanisms, specifically those characterized by board independence and gender diversity. These findings contribute to the growing literature on technological solutions for environmental challenges while providing actionable insights for corporate decision-makers and policymakers seeking to enhance climate resilience through strategic AI integration. The study underscores the potential role of AI as a tool for sustainable development while acknowledging the complex interplay between technological adoption and organizational factors in risk mitigation outcomes.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"220 ","pages":"Article 124327"},"PeriodicalIF":13.3,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144864178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"When things fall apart: Exploring brand hate in influencer endorsements","authors":"Yan-Rong Pan ,&nbsp;Garry Wei-Han Tan ,&nbsp;Eugene Cheng-Xi Aw ,&nbsp;Keng-Boon Ooi","doi":"10.1016/j.techfore.2025.124321","DOIUrl":"10.1016/j.techfore.2025.124321","url":null,"abstract":"<div><div>Driven by the growing popularity of live streaming, brands increasingly favor influencers for their extensive reach. However, realizing broader brand value requires a comprehensive understanding of not only the positive but also the negative implications of influencer endorsements. To address this gap, this study introduces and validates the impact of influencer-brand incongruence, symbolic incongruity, negative past experiences, ideological incompatibility, and negative publicity on attitudes towards both influencers and brands. An asymmetric model is employed to uncover the antecedents of consumer brand hate. A multi-method approach is adopted: Study 1 applies the Delphi method to identify key antecedents, while Study 2 analyzes data from 326 Chinese live streaming consumers using partial least squares structural equation modeling (PLS-SEM) and artificial neural networks (ANN). Findings indicate that negative past experiences and negative publicity significantly harm attitudes towards influencers and brands, respectively. These negative attitudes contribute to brand hate, which subsequently leads to brand avoidance, complaints, and negative word of mouth. This study advances the theoretical framework of influencer endorsement and offers practical insights for influencer marketing managers and brand managers to address negative consumer behaviors and to develop brand strategies that effectively manage risks associated with influencer partnerships.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"220 ","pages":"Article 124321"},"PeriodicalIF":13.3,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144861177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A system dynamics-based comprehensive investment benefit and carbon reduction evaluation for CCUS-EOR projects","authors":"Xiaorong Sun ,&nbsp;Xiangxiang Zhao ,&nbsp;Lichen Gu ,&nbsp;Chenhao Jin ,&nbsp;Xueping Pan ,&nbsp;Shinae Jang","doi":"10.1016/j.techfore.2025.124320","DOIUrl":"10.1016/j.techfore.2025.124320","url":null,"abstract":"<div><div>The Carbon Capture, Utilization, and Storage (CCUS) with Enhanced Oil Recovery (EOR) is one of the most promising technologies for reducing carbon emissions due to its substantial potential for environmental benefits. However, the large-scale development of CCUS-EOR projects faces challenges mainly from imbalanced investment returns. To address the difficulties, this paper develops a novel integrated CCUS-EOR business model and conducts comprehensive investment benefit assessment based on the system dynamics approach. It selects typical cases for comprehensive benefit evaluation and establishes various scenarios to analyse and assess long-term impacts of different benefit enhancement strategies, considering both enterprise and government perspectives. Simulation results indicate that fluctuations in oil prices can jeopardize projects with insufficient economic benefits. Companies can improve project economics by adjusting the initial production scale within a certain range, but excessive reductions may have adverse effects. Government investment subsidies provide the most significant boost to economic benefits but do not necessarily enhance the project's environmental benefits. Conversely, subsidies for electricity prices and carbon storage can improve both economic and environmental outcomes, although the economic benefits do not have significant improvement. This study can be a reference for CCUS-EOR project investments and provide suggestions and measures for enterprises and governments to improve the investment returns of these projects for sustainable development.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"220 ","pages":"Article 124320"},"PeriodicalIF":13.3,"publicationDate":"2025-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144852267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A data-driven approach to establishing a patent strategy by generating a patent map based on generative topographic mapping","authors":"Jaehoon Jung,&nbsp;Sunhye Kim,&nbsp;Byungun Yoon","doi":"10.1016/j.techfore.2025.124325","DOIUrl":"10.1016/j.techfore.2025.124325","url":null,"abstract":"<div><div>As competition among companies intensifies through patents, the need for the strategic utilization and visualization of these patents is growing. However, establishing a patent strategy often relies on subjective insights from experts, which presents a significant limitation. Accordingly, this study aims to develop an analytical methodology that identifies the competitive landscape in technology and business, visualizes patent strategies, and helps in formulating future patent strategies with a focus on technical feature information. Initially, the methodology involves extracting the subject–action–object (SAO) structure from patent data, followed by the visualization of a patent map using generative topographic mapping (GTM). K-means clustering is then applied to further segment sub-technical areas. Subsequently, technology nodes on the GTM map are characterized from the perspective of companies. This process helps in deriving patent strategy patterns that reflect both technological competition and strategic intentions. Future patent strategies are established by scoring these patterns based on predictions of company occupancy using GTM-based classification (GTC) model-based vacuum nodes and other strategic quantitative indicators. This methodology particularly highlights the intersections between technological advancement and corporate competitiveness. An empirical study focusing on the autonomous vehicle industry validates the effectiveness of this methodology in providing insights about leveraging patent strategies for technological leadership. The significant contribution of this study lies in its proposition of a patent map enriched with detailed technical information from patents and the quantification and visualization of patent strategies, guiding the direction for future patent strategizing.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"220 ","pages":"Article 124325"},"PeriodicalIF":13.3,"publicationDate":"2025-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144852270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unpacking the decision-making evolution mechanism of governance actors towards smart municipal solid waste (MSW) management: an insight from game approach","authors":"Xinyu Hao ,&nbsp;Tingting Tian ,&nbsp;Kaiqin Li ,&nbsp;Xiaoling Zhang ,&nbsp;Liang Dong","doi":"10.1016/j.techfore.2025.124319","DOIUrl":"10.1016/j.techfore.2025.124319","url":null,"abstract":"<div><div>Digital technology is reshaping the engagement patterns and decision-making ways of the involved municipal solid waste (MSW) governance actors and the internal interactions. However, this shift hasn't yet been well-illustrated. This paper, considering the impacts of technological shock on government, households, and recyclers, employs a game approach to investigate their decision-making mechanisms in smart MSW management. The findings suggest that responsible government actively promotes digital technology, notwithstanding fence-riding behaviors between recyclers and households are detected. The interplay analysis demonstrates that single-agent-based incentives cannot consistently achieve systematic equilibrium optimization, and the transmission effects between agents' interactions should be noticed. Echoing previous work, financial incentives and environmental awareness matter. In the digital era, however, recyclers' operation mode needs to evolve from the waste-flow-centered to the community-centered. Accordingly, improved perceived utility of tokens and enhanced easy-to-use smart equipment assist in engaging different groups in smart MSW management. This study enriches the discourse about MSW management by unpacking the actors' decision-making mechanisms while providing a theoretical model basis for follow-up discussions on smart MSW management. Through enhanced understanding, this research fuels the construction of ‘zero-waste’ cities and smart cities by advancing the synergy of urban digitalization and greening, thereby propelling sustainable practice under technological empowerment.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"220 ","pages":"Article 124319"},"PeriodicalIF":13.3,"publicationDate":"2025-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144852269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mapping public perception of artificial intelligence: Expectations, risk–benefit tradeoffs, and value as determinants for societal acceptance","authors":"Philipp Brauner,&nbsp;Felix Glawe,&nbsp;Gian Luca Liehner,&nbsp;Luisa Vervier,&nbsp;Martina Ziefle","doi":"10.1016/j.techfore.2025.124304","DOIUrl":"10.1016/j.techfore.2025.124304","url":null,"abstract":"<div><div>Public opinion on artificial intelligence (AI) plays a pivotal role in shaping trust and AI alignment, ethical adoption, and the development equitable policy frameworks. This study investigates expectations, risk–benefit tradeoffs, and value assessments as determinants of societal acceptance of AI. Using a nationally representative sample (N = 1100) from Germany, we examined mental models of AI and potential biases. Participants evaluated 71 AI-related scenarios across domains such as autonomous driving, medical care, art, politics, warfare, and societal divides, assessing their expected likelihood, perceived risks, benefits, and overall value. We present ranked evaluations alongside visual mappings illustrating the risk–benefit tradeoffs. Our findings suggest that while many scenarios were considered likely, they were often associated with high risks, limited benefits, and low overall value. Regression analyses revealed that 96.5% (<span><math><mrow><msup><mrow><mi>r</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>=</mo><mn>0</mn><mo>.</mo><mn>965</mn></mrow></math></span>) of the variance in value judgments was explained by risks (<span><math><mrow><mi>β</mi><mo>=</mo><mo>−</mo><mn>0</mn><mo>.</mo><mn>490</mn></mrow></math></span>) and, more strongly, benefits (<span><math><mrow><mi>β</mi><mo>=</mo><mo>+</mo><mn>0</mn><mo>.</mo><mn>672</mn></mrow></math></span>), with no significant relationship to expected likelihood. Demographics and personality traits, including age, gender, and AI readiness, influenced perceptions, highlighting the need for targeted AI literacy initiatives. These findings offer actionable insights for researchers, developers, and policymakers, highlighting the need to communicate tangible benefits and address public concerns to foster responsible and inclusive AI adoption. Future research should explore cross-cultural differences and longitudinal changes in public perception to inform global AI governance.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"220 ","pages":"Article 124304"},"PeriodicalIF":13.3,"publicationDate":"2025-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144852268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mitigating liabilities of foreignness in migrant entrepreneurship: The role of AI in building virtual embeddedness","authors":"Stoyan Stoyanov ,&nbsp;Veselina Stoyanova","doi":"10.1016/j.techfore.2025.124323","DOIUrl":"10.1016/j.techfore.2025.124323","url":null,"abstract":"<div><div>This study explores how Generative Pretrained Transformer (GPT) Artificial Intelligence (AI) aids migrant entrepreneurs (MEs) in overcoming the social interactions' impact liabilities of foreignness has on their embeddedness and collaboration prospects within host business environments. Drawing upon a qualitative interpretivist approach, semi-structured interviews were conducted with 20 Bulgarian MEs in the UK actively using this technology. Thematic analysis of the collected data revealed that GPT AI serves as a critical tool for establishing virtual embeddedness, consequently reducing liabilities of foreignness in the host country.</div><div>Addressing this issue from a micro-foundation’ perspective, the study reveals the systematic socio-structural mechanisms and the micro foundations they entail, emerging from MEs' use of GPT AI over three phases – calibrating, coordinating, and consolidating social interactions. By proposing a micro-foundations framework to explain the socio-interactional dynamics of MEs using GPT AI for virtual embeddedness, we respond to call for a deeper understanding of the modern factors (i.e., use of AI technology) influencing social embeddedness – particularly virtual such.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"220 ","pages":"Article 124323"},"PeriodicalIF":13.3,"publicationDate":"2025-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144841395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Customer behavior in the presence of algorithmic marketing agents: The role of hedonic values","authors":"Alvaro Chacon ,&nbsp;Carolina Martínez-Troncoso ,&nbsp;Edgar E. Kausel","doi":"10.1016/j.techfore.2025.124322","DOIUrl":"10.1016/j.techfore.2025.124322","url":null,"abstract":"<div><div>Artificial intelligence (AI) marketing agents have increasingly emerged as a viable alternative to human representatives for direct customer interactions. In this research, we investigated customer behaviors in response to sales scenarios managed by AI agents considering individual customers' values. In three pre-registered studies, we examined the willingness of 1417 participants to engage in promotional activities related to purchasing real estate and vehicles. Using regression and simple slope analyses, we examined how the interaction among agents (human or algorithm), response types (negative or positive), and customers' hedonic values influence the likelihood of becoming promoters. Our results revealed a moderation effect in which the relationship between the type of marketing agent and the response type was influenced by customers' hedonic values. We found a positive relationship between hedonic values and promotion behavior when negative feedback was delivered by a human agent and when positive feedback came from an algorithmic agent. In contrast, algorithmic agents tend to elicit flatter responses across hedonic levels when delivering negative feedback, indicating reduced emotional engagement but also less potential for dissatisfaction. These insights emphasize the importance of aligning the source of communication with individual consumer characteristics to enhance customer promotion.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"220 ","pages":"Article 124322"},"PeriodicalIF":13.3,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144841394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of e-waste regulations on firms' R&D and marketing expenditures: Insights for a circular economy","authors":"Ashutosh Singh ,&nbsp;Ankit Mehrotra ,&nbsp;Rsha Alghafes ,&nbsp;Jasmine Mohsen","doi":"10.1016/j.techfore.2025.124306","DOIUrl":"10.1016/j.techfore.2025.124306","url":null,"abstract":"<div><div>Shorter product lifecycles and rising consumer demand drive the rapid expansion of electronic garbage, or e-waste, presenting environmental and public health issues. Governments worldwide have implemented e-waste recycling regulations to control the collection, recycling, and disposal of electronic trash. These regulations are intended to reduce harmful pollution, preserve resources, and promote a circular economy. However, firms associated with the electronic products industry have to limit the resource allocation on long-term strategies due to compliance with these e-waste regulations. We investigate the impact of e-waste regulations on the R&amp;D and marketing expenditures of firms producing or selling electronic products. Using Standard Industrial Classification codes to identify industries linked to electronic equipment, this study examines the effects of state-level e-waste legislation in the U.S. on business practices, with a particular emphasis on R&amp;D and marketing expenditures. We examine changes in businesses impacted by e-waste regulations compared to those in states with no regulations, using a difference-in-differences methodology using a 30-year dataset (1993–2023). The results highlight trade-offs between satisfying regulatory requirements and promoting innovation, showing that e-waste regulations result in lower R&amp;D and marketing expenditures. These findings are validated by robustness testing that uses bootstrapping and extended DID. Our research has several theoretical and practical recommendations.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"220 ","pages":"Article 124306"},"PeriodicalIF":13.3,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144831496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}