Search results

This study aims to explore the cross-level effect of the top management team (TMT) on group ambidextrous innovation and to analyze the mediating role of group behavioral integration and the moderating effect of group expertise heterogeneity.

We conducted a multi-source and multi-stage survey. We collected valid data from 43 companies in China, resulting in 141 samples from 43 TMTs and 462 valid responses from 111 organizational groups. The proposed theoretical model and hypotheses were tested using structural equation modeling.

The study findings demonstrated that TMT behavioral integration was positively related to group behavioral integration. Group behavioral integration mediates the relationship between TMT behavioral integration and these two types of innovations. Furthermore, we found that group expertise heterogeneity magnified the positive effect of group behavioral integration on exploratory innovation.

This study reveals the cross-level effects of TMT behavioral integration on other organizational groups and enriches the existing literature on TMT behavioral integration and ambidextrous innovation.

As an important part of national governance, the online communication of education policies usually attracts the attention of many subjects, including the public and the media. Existing research mainly focuses on analysing communication behaviour of a single subject. However, with the rapid development of social media, policy information communication is often accompanied by the participation of multiple subjects and forms diversified communication behaviours and interaction patterns. The comprehensive identification of multiple subjects and their interactions can accurately depict the communication process and effectively support the efficient communication of policies. Therefore, this paper aims to conduct fine-grained analysis on the multiple subjects in information communication of the education policy.

This paper explored the communication and interaction process of the education policy via multidimensional analysis. Specifically, the authors firstly obtained multi-source communication data to identify key communication subjects. Secondly, the authors mined the communication contents generated by communication subjects to measure the diversified correlations between subjects. Finally, the authors depicted the interaction of subjects in policy information communication.

The experimental results reveal that there are multiple key subjects in the policy information communication, and the communication roles of the subjects change with the communication process, including dominance role, one-way or two-way effect role. This further indicates the need to allocate resources dynamically in the process of policy communication.

Analysing the process of policy communication and identifying the dynamic interaction between communication subjects can provide more a comprehensive and detailed decision-making basis for policy formulation and implementation. In addition, the research ideas and methods presented in this paper expand the perspective of information communication research.

The rapid advancement of digital technologies compels companies across all industries to develop new capabilities to foster innovation and sustain competitiveness. Consequently, scholarly debates have intensified regarding how these new capabilities contribute to companies’ innovation endeavors. This study addresses this imperative by exploring two primary research questions: first, identifying the essential organizational capabilities for digital innovation; and second, examining how these capabilities facilitate innovation. The objective is to develop a comprehensive conceptual framework that classifies digital innovation capability as a higher-order organizational capacity, offering valuable insights for both academic scholarship and practical applications in digital innovation management.

Using a qualitative approach, this study combines a systematic literature review with grounded theory principles to analyze 38 empirical papers from Scopus and Web of Science databases. The rigorous multi-stage coding process – open, axial and selective coding – facilitated the identification and synthesis of valuable insights for digital innovation capabilities. This approach ensures a comprehensive yet focused review, supporting the development of a robust theoretical framework.

Four critical capability clusters were identified to shape digital innovation capabilities: sensing, analytic-driven, digital platform and orchestration. Sensing capabilities enhance environmental awareness and enable organizations to detect market needs and opportunities, fostering customer-centric innovations. Analytic-driven capabilities leverage data for insightful decision-making and trend analysis. Digital platform capabilities highlight the strategic use of technological infrastructures to enable collaborative innovation, integrating diverse capabilities and objectives. Orchestration capabilities focus on effective coordination of resources and partnerships, ensuring sustained digital innovation by bridging capability gaps and reconfiguring resources. Collectively, these clusters offer a holistic framework for excelling in the dynamic digital innovation landscape.

While previous literature has focused on the impact of individual capabilities on digital innovation, this study offers a novel and integrative framework that categorizes digital innovation capabilities into four distinct yet interconnected clusters: sensing, analytic-driven, digital platforms and orchestration. This framework delineates the unique roles each capability plays in the digital innovation process. By synthesizing empirical studies and constructing a robust theoretical framework, this research significantly contributes to both academic scholarship and practical applications, offering essential strategies for organizations to enhance their digital innovation efforts through sustainable capability development.

With limited empirical evidence, prior studies have proposed that green practices can be leveraged to enhance carbon neutrality. This study draws on the contingent natural resource-based view (NRBV) to theorize and validate how pressure from supply chain (SC) stakeholders could amplify the effect of green logistics practices (GLPs) on carbon-neutral supply chain performance (CNSCP) among firms in developing countries. Specifically, this study contends that high levels of supply chain pressures (SCPs) (customers and suppliers) amplify the influence of GLPs on CNSCP.

An integrated model was tested using survey data gathered from 208 managers of logistics firms in Ghana. SPSS 23 and structural equation modeling were used for the data analyses.

Findings showed that all five dimensions of GLPs (transportation, warehousing, packaging and distribution, logistics information sharing and sustainable waste management) significantly enhance CNSCP. This study also found varying interactive effects of SCPs (customers and suppliers) on the link between GLPs (green transportation, green packaging and distribution) and CNSCP, such that different practices exert varying interactive effects at varying levels of SCPs.

This study offers fresh insights into how managers can leverage GLPs to achieve enhanced benefits in the form of CNSCP. The outcome of this study offers a comprehensive understanding of the GLPs-CNSCP link while shedding light on how firms can manage SCP to drive enhanced carbon-neutral performance through GLPs.

This study contributes to policymakers in enhancing the decarbonization of global SCs through sustainable logistics practices.

To the best of the authors’ knowledge, this is the first study to theorize and empirically validate the influence of GLPs on CNSCP. This study identified five practices and demonstrated how these practices uniquely drive CNSCP, as opposed to previous studies that examined GLPs from a one-dimensional perspective. This study also expands the borders of sustainable logistics literature by theorizing and empirically validating SCPs (customers and suppliers) as necessary conditions to amplify the benefits of GLPs. In essence, the novelty of the present study lies in the integration of NRBV and stakeholder theories to unearth the mechanism for optimizing the GLP-CNSCP relationship, which is rare in the sustainable logistics literature.

This study analyzes the performance implications of adopting blockchain to support supply chain business processes. The technology holds as many promises as implementation challenges, so interest in its impact on operational performance has grown steadily over the last few years.

Drawing on transaction cost economics and the contingency theory, we built a set of hypotheses. These were tested through a long-term event study and an ordinary least squares regression involving 130 adopters listed in North America.

Compared with the control sample, adopters displayed significant abnormal performance in terms of labor productivity, operating cycle and profitability, whereas sales appeared unaffected. Firms in regulated settings and closer to the end customer showed more positive effects. Neither industry-level competition nor the early involvement of a project partner emerged as relevant contextual factors.

This research presents the first extensive analysis of operational performance based on objective measures. In contrast to previous studies and theoretical predictions, the results indicate that blockchain adoption is not associated with sales improvement. This can be explained considering that secure data storage and sharing do not guarantee the factual credibility of recorded data, which needs to be proved to customers in alternative ways. Conversely, improvements in other operational performance dimensions confirm that blockchain can support inter-organizational transactions more efficiently. The results are relevant in times when, following hype, there are signs of disengagement with the technology.