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Online medical teams (OMTs) have emerged as an innovative healthcare service mode that relies on the collaboration of doctors to produce comprehensive medical recommendations. This study delves into the relationship between knowledge collaboration and team performance in OMTs and examines the complex effects of participation patterns.

The analysis uses a dataset that consists of 2,180 OMTs involving 8,689 doctors. Ordinary least squares regression with robust standard error is adopted for data analysis.

Our findings demonstrate a positive influence of knowledge collaboration on OMT performance. Leader participation weakens the relationship between knowledge collaboration and team performance, whereas multidisciplinary participation strengthens it. Passive participation and chief doctor participation have no significant effect on the association between knowledge collaboration and OMT performance.

This study provides valuable insights into how knowledge collaboration shapes OMTs' performance and reveals how the participation of different types of members affects outcomes. Our findings offer important practical implications for the optimization of online health platforms and for enhancing the effectiveness of collaborative healthcare delivery.

This paper focuses on image-to-text manuscript processing through Handwritten Text Recognition (HTR), a Machine Learning (ML) approach enabled by Artificial Intelligence (AI). With HTR now achieving high levels of accuracy, we consider its potential impact on our near-future information environment and knowledge of the past.

In undertaking a more constructivist analysis, we identified gaps in the current literature through a Grounded Theory Method (GTM). This guided an iterative process of concept mapping through writing sprints in workshop settings. We identified, explored and confirmed themes through group discussion and a further interrogation of relevant literature, until reaching saturation.

Catalogued as part of our GTM, 120 published texts underpin this paper. We found that HTR facilitates accurate transcription and dataset cleaning, while facilitating access to a variety of historical material. HTR contributes to a virtuous cycle of dataset production and can inform the development of online cataloguing. However, current limitations include dependency on digitisation pipelines, potential archival history omission and entrenchment of bias. We also cite near-future HTR considerations. These include encouraging open access, integrating advanced AI processes and metadata extraction; legal and moral issues surrounding copyright and data ethics; crediting individuals’ transcription contributions and HTR’s environmental costs.

Our research produces a set of best practice recommendations for researchers, data providers and memory institutions, surrounding HTR use. This forms an initial, though not comprehensive, blueprint for directing future HTR research. In pursuing this, the narrative that HTR’s speed and efficiency will simply transform scholarship in archives is deconstructed.

The purpose of this paper is to study the importance of image data in hotel selection-recommendation using different types of cognitive features and to explore whether there are reinforcing effects among these cognitive features.

This study represents user-generated images “cognitive” in a knowledge graph through multidimensional (shallow, middle and deep) analysis. This approach highlights the clustering of hotel destination imagery.

This study develops a novel hotel selection-recommendation model based on image sentiment and attribute representation within the construction of a knowledge graph. Furthermore, the experimental results show an enhanced effect between different types of cognitive features and hotel selection-recommendation.

This study enhances hotel recommendation accuracy and user satisfaction by incorporating cognitive and emotional image attributes into knowledge graphs using advanced machine learning and computer vision techniques.

This study advances the understanding of user-generated images’ impact on hotel selection, helping users make better decisions and enabling marketers to understand users’ preferences and trends.

This research is one of the first to propose a new method for exploring the cognitive dimensions of hotel image data. Furthermore, multi-dimensional cognitive features can effectively enhance the selection-recommendation process, and the authors have proposed a novel hotel selection-recommendation model.

The organizational decision-making perspective (ODM) has a legacy regarding its concern for budgeting as an essential organizational routine in decision-making. Budgeting has also become a direct concern to organizational institutional theory (OIT) because of its prominent role in institution building, where budgeting can build trust in inter-organizational relationships. This paper builds on these two perspectives to explore organizational budget processes' formation, disruption, and re-creation over time.

We conducted a comprehensive review and critical analysis of the ODM and OIT perspectives, focusing on a fundamental paradox between ODM's emphasis on stability through organizational routines and OIT's focus on organizational legitimacy through the decoupled expression of organizational values. We then expanded on these paradoxical concerns in the context of budgeting, formalizing them into specific research propositions for future studies.

Tensions around the stability, decay, and re-creation of budgets as organizational routines emerge as a pressing issue requiring further empirical investigation from the ODM perspective. A critical issue in the OIT perspective is the potential for organizational budgets to provide an opportunity to decouple from practice through routinized expressions of rationality and to facilitate loose coupling in practice. These findings offer a fresh perspective and open up new avenues for future research in this area.

This paper contributes to the accounting and organizational research literature by shedding light on how organizations respond to the potential decay of budget routines and the manifestation of organizational values in decoupling processes by further re-creating and elaborating budget processes.