Search results

Social media is booming in the digital age, and its rich availability provides many opportunities for companies to innovate across borders. In reality, how enterprises use social media to achieve cross-border innovation also faces important challenges such as breaking path dependency.

This paper explores how social media can facilitate cross-border innovation from the perspective of strategic capability, combined with the path dependency theory and attention-based view. Hierarchical regression analysis and bootstrap method are adopted to test the hypotheses based on survey data provided by 173 firms in China.

The findings show a positive relationship between social media strategic capability and cross-border innovation, with path dependency playing a mediating role. In addition, two internal and external contextual factors, namely customer embeddedness and competitive pressure, play moderating roles, with customer embeddedness negatively moderating the negative relationship between social media strategic capability and path dependency and competitive pressure negatively moderating the negative relationship between path dependency and cross-border innovation.

These findings provide not only new insights into social media and cross-border innovation but also theoretical guidance on how companies can effectively use social media in practice.

Loitering aerial vehicle (LAV) swarm safety flight control is an unmanned system control problem under multiple constraints, which are derived to prevent the LAVs from suffering risks inside and outside the swarms. The computational complexity of the safety flight control problem grows as the number of LAVs and of the constraints increases. Besides some important constraints, the swarms will encounter with sudden appearing risks in a hostile environment. The purpose of this study is to design a safety flight control algorithm for LAV swarm, which can timely respond to sudden appearing risks and reduce the computational burden.

To address the problem, this paper proposes a distributed safety flight control algorithm that includes a trajectory planning stage using kinodynamic rapidly exploring random trees (KRRT*) and a tracking stage based on distributed model predictive control (DMPC).

The proposed algorithm reduces the computational burden of the safety flight control problem and can fast find optimal flight trajectories for the LAVs in a swarm even there are multi-constraints and sudden appearing risks.

The proposed algorithm did not handle the constraints synchronously, but first uses the KRRT* to handle some constraints, and then uses the DMPC to deal with the rest constraints. In addition, the proposed algorithm can effectively respond to sudden appearing risks by online re-plan the trajectories of LAVs within the swarm.

This study aims to answer the question of how incumbent firms cultivate dynamic capabilities through knowledge management so that they can efficiently adapt to the changing external environment.

This study adopts a case study approach and collects data through interviews and secondary public information on the lighting industry and two lighting firms in Lin'an, China. It qualitatively examines the challenges and strategic recommendations for incumbent firms in the context of discontinuous technological change from a knowledge management perspective.

Incumbent firms often face a variety of challenges when responding to discontinuous technological change. These challenges include identifying opportunities, overcoming path dependence and dealing with employee resistance to change. To overcome these difficulties, three strategies have been proposed to enhance the dynamic capabilities of incumbent firms through knowledge management: cross-border search helps firms improve their knowledge acquisition capabilities and better understand their environment to identify opportunities; building strategic leadership overcomes path dependence and improves knowledge integration capabilities; organizational learning deepens employees’ understanding of change and enhances organizational knowledge application capabilities.

Previous research attributes a firm's ability to cope with discontinuous technological change solely to its general resources, which weakens the importance of knowledge management in this context. This study emphasizes the importance of knowledge as a crucial strategic resource in developing the essential dynamic capabilities for incumbent firms to cope with discontinuous technological change.

This study provides an in-depth analysis of incumbent firms' coping strategies in the new context of discontinuous technological change and further promotes cross-disciplinary research.

This study provides an in-depth analysis of coping strategies in the new context of discontinuous technological change, furthermore theoretically advancing the interdisciplinary research of firm transformation and knowledge management. Meanwhile, it is crucial to identify the preconditions for cultivating dynamic capabilities, especially from a knowledge-based view, which enhances the depth of knowledge management research.

Community question answering (CQA) platforms play a significant role in knowledge dissemination and information retrieval. Expert recommendation can assist users by helping them find valuable answers efficiently. Existing works mainly use content and user behavioural features for expert recommendation, and fail to effectively leverage the correlation across multi-dimensional features.

To address the above issue, this work proposes a multi-dimensional feature fusion-based method for expert recommendation, aiming to integrate features of question–answerer pairs from three dimensions, including network features, content features and user behaviour features. Specifically, network features are extracted by first learning user and tag representations using network representation learning methods and then calculating questioner–answerer similarities and answerer–tag similarities. Secondly, content features are extracted from textual contents of questions and answerer generated contents using text representation models. Thirdly, user behaviour features are extracted from user actions observed in CQA platforms, such as following and likes. Finally, given a question–answerer pair, the three dimensional features are fused and used to predict the probability of the candidate expert answering the given question.

The proposed method is evaluated on a data set collected from a publicly available CQA platform. Results show that the proposed method is effective compared with baseline methods. Ablation study shows that network features is the most important dimensional features among all three dimensional features.

This work identifies three dimensional features for expert recommendation in CQA platforms and conducts a comprehensive investigation into the importance of features for the performance of expert recommendation. The results suggest that network features are the most important features among three-dimensional features, which indicates that the performance of expert recommendation in CQA platforms is likely to get improved by further mining network features using advanced techniques, such as graph neural networks. One broader implication is that it is always important to include multi-dimensional features for expert recommendation and conduct systematic investigation to identify the most important features for finding directions for improvement.

This work proposes three-dimensional features given that existing works mostly focus on one or two-dimensional features and demonstrate the effectiveness of the newly proposed features.

Since the “Standards + Certification” regional quality brand initiative has become a key component of China’s efforts to promote a quality-driven economy, this paper aims to examine the effect of perception, trust and satisfaction toward the regional quality brand on consumer loyalty.

Data were collected from 401 consumers who have bought “Zhejiang Manufacturing” regional quality brand products. The structural equation modeling (SEM) technique was applied to assess the relationship of the research model.

The results show that brand perception, trust and satisfaction toward regional quality brands all significantly positively impact both consumer behavioral and attitudinal loyalty. Further, the results confirmed that brand trust and satisfaction fully mediate the relationship between brand perception and behavioral loyalty and partially mediate the relationship between brand perception and attitudinal loyalty.

This study presents a conceptual model on the impact of perception toward regional quality brands on consumer loyalty in a field where little research has been done. It offers a consumer-focused analysis that advances the theoretical and empirical knowledge of regional quality brands.

This study addresses the gap in understanding text analytics within the service domain, focusing on new service development to provide insights into key research themes and trends in text analytics approaches to service development. It explores the benefits and challenges of implementing these approaches and identifies potential research opportunities for future service development. Importantly, this study offers insights to assist service providers to make data-driven decisions for developing new services and optimising existing ones.

This research introduces the hybrid thematic analysis with a systematic literature review (SLR-TA). It delves into the various aspects of text analytics in service development by analysing 124 research papers published from 2012 to 2023. This approach not only identifies key practical applications but also evaluates the benefits and difficulties of applying text analytics in this domain, thereby ensuring the reliability and validity of the findings.

The study highlights an increasing focus on text analytics within the service industry over the examined period. Using the SLR-TA approach, it identifies eight themes in previous studies and finds that “Service Quality” had the most research interest, comprising 42% of studies, while there was less emphasis on designing new services. The study categorises research into four types: Case, Concept, Tools and Implementation, with case studies comprising 68% of the total.

This study is groundbreaking in conducting a thorough and systematic analysis of a broad collection of articles. It provides a comprehensive view of text analytics approaches in the service sector, particularly in developing new services and service innovation. This study lays out distinct guidelines for future research and offers valuable insights to foster research recommendations.