With the development of digital technologies and their increasing application in government, digital transformation is a wave rolling up the world. Previous studies had investigated some factors that affect digital transformation. But there is little research on the impact of organizational agility on digital transformation in government. To fill this gap, based on the dynamic capabilities view, this study aims to investigate how organizational agility affects digital transformation and dynamic capabilities as antecedents and factors impacting organizational agility. A survey study was conducted to empirically test the model. The data were collected from 313 government employees in government departments. The findings suggest that (1) organizational agility significantly influences digital transformation and (2) dynamic capabilities are important predictors of organizational agility.

To achieve sustainable urban development, many countries around the world are exploring the path of smart cities. The progress and development of digital technology has paved a promising road. Digital transformation of the government is an important factor for smart cities in China. Scholars are increasingly interested in the digital transformation of government, but there is little empirical research on the driving factors of digital transformation among local governments. Based on the technology–organization–environment (TOE) framework, this study explores the driving factors of digital transformation among local governments in China. A questionnaire survey and the structural equation model were used. Technological readiness, organizational efficiency, public service delivery, citizens’ expectations and superior pressure are significant driving factors. Technological readiness is the first factor affecting the government’s digital transformation. Applying the identified drivers, the results of this research could be used as orientation towards, and provide concrete practical approaches for, successful digital transformation among local governments, which would lay a foundation for smart city construction.

With the rapid development of information and communication technologies, digital transformation has already been underway in various fields around the world. In order to construct digital government and promote the modernization process of national management system and management capability, governments of different Countries have started the digital transition process. Government digital transformation has fascinated many experts and scholars, while there is little literature on the relations between digital transformation and government performance. Based on the theory of dynamic capabilities, this paper makes an empirical study on the impact of digital transformation on government performance using systematic review, questionnaire survey and structural methods. The results show that sensing capability, seizing capability, transformation capability and partnering agility have significant positive effects on government performance. Moreover, partnering agility plays a mediating role in the interactions of sensing capability, transformation capability and government performance variables. This paper enriches the research achievements in the field of government digital transformation and provides both theoretical and practical supports for the improvement of government performance.

Purpose: With the arrival of the big data era, governments have appointed a chief data officer (CDO) to meet the opportunities and challenges brought by big data. The existing research on the CDOs is very limited, and what does exist focuses primarily on what are CDOs do. Little research has explored how CDOs do. To fill this gap, this study employed ambidexterity theory to investigate the ambidexterity of CDOs’ impact on data-driven innovation. Design/methodology/approach: To empirically test the model, a survey study was conducted to empirically test the model. Data were collected from 261 CDOs in government and government employees in big data management centers or bureaus. The collected data were analyzed quantitatively to answer hypotheses using a structural equation model. Findings: The findings suggest that data exploitation and data exploration significantly influence data-driven leadership, culture and value propositions. Data-driven leadership and value propositions significantly impact government performance. Originality/value: This study is one of the first attempts to investigate how CDOs work, especially when promoting data-driven innovation. In addition, this study extends ambidexterity theory into the issue of the CDO in government.

AI misuse has become a significant challenge and concern in higher education. Existing research has focused separately on either antecedents or consequences of AI misuse and has relied on a single theoretical perspective. There is a notable lack of empirical research investigating the antecedents and consequences of AI misuse among university students. To address this gap, this study constructs an integrated research model for the antecedents and consequences of AI misuse based on the fraud triangle theory, deterrence theory, and social cognitive theory. Data were collected from 493 university students through a questionnaire survey and analyzed using structural equation modeling (SEM) to test the proposed hypotheses. The results indicate that ease of use, academic pressure, and peer influence significantly promote AI misuse. Policy deterrence and academic self-efficacy can effectively inhibit AI misuse. Furthermore, AI misuse impairs students’ innovation ability. This study advances the systematic understanding of AI misuse and consolidates its theoretical and empirical underpinnings. It enables universities to better govern AI misuse and foster students’ innovation ability.

Sustainability has emerged as a critical issue in development. Digital transformation functions as both an enabler and an effective tool for promoting sustainability. Strategy plays a pivotal role in the process of digital transformation. However, there is a paucity of existing research focused on strategic renewal in digital transformation within the context of China. This study employs organizational learning theory to examine the antecedents and consequences of strategic renewal in digital transformation. Data were collected from 389 government employees through a questionnaire survey and a quantitative analysis was performed to evaluate four hypotheses using structural equation modeling (SEM). The results indicate that knowledge acquisition and organizational memory significantly influence strategic renewal, which in turn affects government performance. The findings of this study could serve as a guide and provide concrete practical approaches for successful digital transformation among governments, thereby laying a foundation for sustainable development.