How AI use in organizations contributes to employee competitive advantage: The moderating role of perceived organization support DOI
Liang Ma, Peng Yu, Xin Zhang

и другие.

Technological Forecasting and Social Change, Год журнала: 2024, Номер 209, С. 123801 - 123801

Опубликована: Окт. 4, 2024

Язык: Английский

The AI transformation of product innovation DOI Creative Commons
Robert G. Cooper

Industrial Marketing Management, Год журнала: 2024, Номер 119, С. 62 - 74

Опубликована: Апрель 11, 2024

Язык: Английский

Процитировано

32

AI capability and environmental sustainability performance: Moderating role of green knowledge management DOI

Sachin Kumar,

Vinod Kumar, Ranjan Chaudhuri

и другие.

Technology in Society, Год журнала: 2025, Номер unknown, С. 102870 - 102870

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

2

The impact of artificial intelligence on the green and low‐carbon transformation of Chinese enterprises DOI
Tingting Liu, B.B. ZHOU

Managerial and Decision Economics, Год журнала: 2024, Номер 45(5), С. 2727 - 2738

Опубликована: Март 6, 2024

Abstract Artificial intelligence (AI) plays a crucial role in addressing resource and environmental constraints achieving sustainable economic social development. This study examines the impact mechanisms of AI on green low‐carbon transformation enterprises using sample companies listed Shanghai Shenzhen stock exchanges from 2009 to 2021. The research findings indicate that has capability effectively mitigate corporate carbon emissions (CCE) enhance level innovation (GI) enterprises. Mechanism analysis reveals energy consumption mediating relationship between CCE. Heterogeneity inhibitory effect CCE is more pronounced private non‐heavy polluting industries. However, GI greater state‐owned heavy‐polluting sheds light influence enterprises, as well its transmission mechanisms. It provides theoretical empirical insights for promoting GI, reducing emissions, improving efficiency

Язык: Английский

Процитировано

8

Analyzing Factors That Affect Korean B2B Companies’ Sustainable Performance DOI Open Access
Sungchang Lee, Young Jun Kim

Sustainability, Год журнала: 2024, Номер 16(5), С. 1719 - 1719

Опубликована: Фев. 20, 2024

This study empirically examines factors that can influence the sustainable corporate performance of Korean business-to-business (B2B) companies with help unique survey data. Factors such as technological capability, chief executive officer (CEO)’s risk-taking propensity, B2B seller skill, and key account management (KAM) are analyzed to clarify their impact on financial non-financial performance. In particular, given environment, society, governance (ESG) reporting has recently been widely recognized an important evaluation factor for companies, we look at mediating effects ESG business The results show CEO’s propensity skill significantly company’s performance, while capability fact a affects both indicates importance entrepreneurial competency in sustainability company. Furthermore, findings reveal plays crucial role allows KAM significantly. Likewise, all explanatory contribute through management. practitioners scholars because they emphasize need establish optimal strategy survival sustainability. this underscores should be implemented by organizational members, from CEOs employees. Future research will include more comprehensive samples analyze various strategic not covered derive effective ways which increase We also explore good practices.

Язык: Английский

Процитировано

7

Enhancing SMEs Sustainable Innovation and Performance through Digital Transformation: Insights from Strategic Technology, Organizational Dynamics, and Environmental Adaptation DOI
Shaofeng Wang, Hao Zhang

Socio-Economic Planning Sciences, Год журнала: 2024, Номер unknown, С. 102124 - 102124

Опубликована: Ноя. 1, 2024

Язык: Английский

Процитировано

7

Investigating AI Adoption, Knowledge Absorptive Capacity, and Open Innovation in Chinese Apparel MSMEs: An Extended TAM-TOE Model with PLS-SEM Analysis DOI Open Access
Chen Qu, Eunyoung Kim

Sustainability, Год журнала: 2025, Номер 17(5), С. 1873 - 1873

Опубликована: Фев. 22, 2025

The rapid evolution of artificial intelligence (AI) has significantly transformed industries, positioning the fashion sector as a critical area study due to its mass production and pressing sustainability challenges. As world’s largest apparel producer, China faces unique hurdles in terms integrating AI technologies, highlighting intersection technological innovation within this industry. In context, aims provide initial exploratory correlations between adoption open from manufacturing micro-, small-, medium-size enterprises (MSMEs) managers’ perspectives, identifying knowledge absorptive capacity (KACAP)’s significant impacts through an integrated extended TAM-TOE model. We conducted PLS-SEM empirically validate antecedents consequential effects on KACAP by collecting information 269 MSMEs’ top managers. results show that structural model explains 60.7% variance adoption, 47.4% KACAP, 55.4% innovation, which suggests good explanatory capacity, all these Q2 values indicate sizeable predictive accuracy threshold. Drawing proposed model, identified (e.g., perceived usefulness) environmental factors competitive pressure, market uncertainty, government support policy) impact while organizational readiness) directly supplier involvement, uncertainty) innovation. Subsequently, construct is having influence KACAP. This fills existing theoretical gaps linking technology processes demonstrates mediating Also, provides foundation for future research exploring similar industries.

Язык: Английский

Процитировано

1

Artificial Intelligence Capabilities in Digital Servitization: Identifying Digital Opportunities for Different Service Types DOI
Néstor Fabián Ayala,

Jassen Rodrigues da Silva,

Maria Auxiliadora Cannarozzo Tinoco

и другие.

International Journal of Production Economics, Год журнала: 2025, Номер unknown, С. 109604 - 109604

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

1

The impact of AI assimilation on firm performance in small and medium-sized enterprises: A moderated multi-mediation model DOI Creative Commons
Mohamad Deeb Abdul Wahab, Mehrshad Radmehr

Heliyon, Год журнала: 2024, Номер 10(8), С. e29580 - e29580

Опубликована: Апрель 1, 2024

Artificial intelligence (AI) and other advanced technologies are increasingly recognized as essential catalysts for enhancing productivity due to their capability transform nearly all operations within outside firms. However, the empirical research on how AI assimilation may promote firm-level outcomes such absorptive capacity (AC), customer agility (CA), firm performance (FP) is still in its infancy. Drawing from dynamic view using 417 valid responses collected through cross-sectional methods small medium-sized enterprises (SMEs) Lebanon, this study examines effect of performance. The mediating roles AC CA were investigated. moderating role organizational (OA) was also explored. findings support hypothesized assumptions that continual advancement technology evolves industrial organizations' with parallel mediators, partially link between FP OA a moderator, positive relationship FP. provide crucial insights practitioners advance framework. They compelling evidence enriches understanding assimilation, demonstrating impact critical yielding benefits SMEs.

Язык: Английский

Процитировано

6

Environmental analysis and impact on green business strategy and performance in SMEs post the Covid-19 pandemic DOI Creative Commons
Sabihaini Sabihaini, Arief Kurniawan, Januar Eko Prasetio

и другие.

Cogent Economics & Finance, Год журнала: 2024, Номер 12(1)

Опубликована: Март 26, 2024

Purpose This study aims to obtain empirical evidence on the effect of environmental analysis environmentally friendly business strategies and performance in SMEs after Covid-19 Pandemic.

Язык: Английский

Процитировано

4

Does AI elevate corporate ESG performance? A supply chain perspective DOI
Boqiang Lin, Yitong Zhu

Business Strategy and the Environment, Год журнала: 2024, Номер unknown

Опубликована: Окт. 16, 2024

Abstract As a pivotal catalyst for sustainable development, the evolution and integration of AI are propelling both companies society toward more efficient trajectory. Utilizing multi‐period difference‐in‐difference (DID) model, study assesses impact 2019 China Artificial Intelligence Pilot (AIP) policy on corporate environmental, social, governance (ESG). The study's findings following: (1) Optimizing through artificial intelligence (AI), AIP has significantly bolstered ESG performance in pilot areas. (2) Mechanistic analysis demonstrates that elevates by bolstering efficiency supply chains. (3) Heterogeneity testing shows exerts pronounced effect non‐state‐owned companies, with high energy consumption, those new sector. This manuscript furnishes empirical insights evaluating implications development initiatives.

Язык: Английский

Процитировано

3