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[Purpose/Significance] Interdisciplinary research has emerged as a key driver of knowledge innovation, its essence being integration of knowledge from different disciplines. A deep and nuanced understanding of the research content of interdisciplinary knowledge integration is essential to foster innovation beyond traditional academic boundaries. Most of the research reviews on interdisciplinary research summarize theories, concepts and indicators from the macro level, while the content of interdisciplinary knowledge integration at the micro level is scattered, and lacks systematicity and logic. Therefore, this study attempts to classify and summarize the research methods, research content and research ideas involved in order to provide reference for scholars and researchers engaged in interdisciplinary knowledge integration. [Method/Process] Based on Web of Science (WOS) and China National Knowledge Infrastructure (CNKI) database as the primary data sources, we reviewed the relevant literature on interdisciplinary knowledge integration. By clarifying the intrinsic meaning of interdisciplinary knowledge integration, we have systematically reviewed and summarized the existing research findings from three aspects. First, research on the degree of knowledge integration mainly involves measurement methods. Second, research on the content of knowledge integration is based on citations and keywords. Third, research on the process of knowledge integration involves its integration path and process, and the characteristics of the integration stage. On this basis, this paper also summarizes the limitations and challenges of existing research, and provides research perspectives for subsequent research on interdisciplinary knowledge integration. [Results/Conclusions] The existing results have extensively explored the definition, measurement method, content, and process of interdisciplinary knowledge integration, but there are problems such as limited applicability of knowledge integration measurement methods, insufficient semantic disclosure, and the lack of systematic research on the degree of knowledge integration. Future research in this area should pay attention to the following three aspects. First, the applicability of methods for measuring interdisciplinary knowledge integration should be improved in order to better adapt to the development of interdisciplinary knowledge integration. Second, there is also a need to strengthen the study of knowledge integration from the perspective of knowledge increment, examining how new knowledge is created and how it contributes to the advancement of the area. In addition, efforts should be made to explore new theories and methods, grasp the development law of interdisciplinary knowledge integration, and expand the application scope and application value of interdisciplinary knowledge integration.

Purpose This study aims to explore the mechanism of boundary-spanning search on firm’s innovation performance under environmental dynamics from the perspective of strategic knowledge integration. Design/methodology/approach A survey was conducted among Chinese firm managers and R&D personnel, resulting in the collection of 315 valid samples. Hierarchical regression analysis was mainly adopted to demonstrate the hypothesized relationships, while the Sobel test and bootstrap method were used to further validate the mediating effects. Findings The results demonstrate that boundary-spanning search in different dimensions is a critical factor in the improvement of firm innovation performance (FIP). Two types of strategic knowledge integration are the main factors causing FIP and mediate the influence of boundary-spanning search on FIP. Furthermore, environmental dynamics moderate the relationship among boundary-spanning search, strategic knowledge integration and FIP. Practical implications Managers need to strengthen the boundary-spanning search for market and technical knowledge, which will promote firm innovative performance. Managers also need to implement strategic knowledge integration, which specifically includes using planned strategic knowledge integration to compensate for knowledge deficiencies, thereby achieving predetermined objectives; and using emergent strategic knowledge integration to update their understanding of internal and external environments, and to reset strategic objectives. In dynamic environments, managers should emphasize strategic knowledge management activities more. Originality/value From a strategic management perspective, this study categorizes strategic knowledge integration into planned and emergent forms. By applying the logic of knowledge acquisition, integration and creation, it explores how boundary-spanning search affects FIP through strategic knowledge integration as the intermediary and the boundary conditions of environmental dynamics. This not only provides a deeper understanding of the nature and effects of boundary-spanning research but also enhances the theory of strategic knowledge management.

Accurately estimating water flux in variably saturated soils is crucial, yet traditional methods, such as the Richardson‐Richards equation, often suffer from some limitations. As an advancement of Physics‐Informed Neural Networks (PINNs), we introduce the Adaptive Constrained Neural Network (ACNN), designed to estimate variably saturated soil water flux using sparse volumetric water content (VWC) data alone, without requiring initial conditions (ICs), boundary conditions (BCs), or soil hydraulic constitutive relationships. The framework integrates domain decomposition methods and adaptive constraints within a sequential training framework. Testing on synthetic cases and soil column experiments demonstrates its capability to achieve unified modeling of variably saturated flow, seamlessly linking the unsaturated and saturated zones. It effectively addresses issues of incomplete knowledge and noisy data, not only mitigating ill‐conditioning compared to traditional PINNs, but also reducing flux estimation errors caused by uncertainties in ICs and BCs compared to numerical methods. Notably, under conditions of rapid moisture content change, ACNN successfully captures instantaneous flux changes at the boundary with an accuracy of approximately R2 = 0.9, highlighting its potential in applications such as estimating surface infiltration, evapotranspiration, and groundwater recharge.

Purpose Building on the resource- and knowledge-based views, this paper aims to explore how coopetition affects radical innovation and the roles of knowledge structure and external knowledge integration in the relationship between coopetition and radical innovation. Design/methodology/approach This study proposes a research model to examine the mediating role of external knowledge integration on the coopetition-radical innovation link, where the mediation is moderated by the firm’s knowledge structure (including component knowledge and architectural knowledge). The authors use regression and bootstrapping to test the proposed model with survey data from 241 Chinese technology firms. Findings This study finds that coopetition positively affects radical innovation and the effect is fully mediated by external knowledge integration. Additionally, component knowledge negatively moderates the coopetition-external knowledge integration link and architectural knowledge positively moderates this relationship. Further, the mediating effect of external knowledge integration is also moderated by component knowledge and architectural knowledge. Practical implications Firms should engage in coopetition to promote radical innovation. Further, it is necessary for firms to appropriately manage coopetition according to their internal knowledge structure. Originality/value This study explains why scholars have different ideas about the relationship between coopetition and radical innovation by exploring the mediating role of external knowledge integration and the moderating effect of knowledge structure. Firms possess increased possibilities for knowledge leakage and partner opportunism with high levels of component knowledge, which will reduce the positive effect coopetition on external knowledge integration; thus, they are less likely to realize radical innovation. Instead, firms possess increased opportunities for resource sharing with high levels of architectural knowledge, thus improving the positive effect coopetition on external knowledge integration and they are more likely to achieve radical innovation.

PurposeIn the context of the environmental degradation challenge in manufacturing firms, greening the supply chain (SC) is the most widely endorsed method to mitigate the adverse repercussions of climate change. Based on organizational learning and resource dependence theories, the aim of this research is to know how green supply chain external integration (GSCEI) and green supply chain internal integration (GSCII) influence ambidextrous green innovation (AGI). It also examines the mediating roles of green absorptive capacity (GAC) and green knowledge integration capability (GKIC), as well as the moderating role of green technology dynamism (GTD).Design/methodology/approachTo assess the hypothesized model, data were obtained with 386 questionnaires from managers employed in manufacturing firms in Pakistan applying a cross-sectional approach. A partial least square structural equation modeling technique was implemented to evaluate the data.FindingsThe results revealed that GSCEI and GSCII substantially impact AGI. Moreover, GAC and GKIC serve as mediators between GSCEI and AGI. GAC and GKIC also intervene in the relationship between GSCII and AGI. GTD was significant as a moderator for the correlation between GSCEI and AGI. However, it does not moderate the relationship between GSCII and AGI.Practical implicationsThis research offers significant comprehension and an innovative approach for manufacturing organizations to curb environmental corrosion by stimulating AGI through green SC integration. It suggests to practitioners that integrating internal knowledge with external partners expands communication and collaboration to ensure that resources connected with environmental preservation flow smoothly.Originality/valueThis research is a valuable addition to the field, as it explores for the first time the missing link among the studied constructs. It opened the black box of how knowledge-related capabilities facilitate knowledge resources to elicit AGI, an area that has not yet been explored.

Complex sustainability problems (e.g., climate change) are challenging to understand and manage, leading to an increase in approaches that connect scholars to society and research to action (collaborative approaches). The transdisciplinary approach (TDA) represents one such approach. While TDA is new to many, there are several prior collaborative approaches including collaborative adaptive management, knowledge integration, participatory action research, and indigenous/local knowledge. Other contemporary and parallel approaches include citizen science, translational science, evidence-based practice, and knowledge with action. The varied disciplinary roots and problem areas contribute to a lack of interaction among these parallel but distinct approaches, and among the scholars and stakeholders who practice them. In this paper, we consider the connections, complementarities and contradictions among these distinct but related collaborative approaches. This review offers insights into the interaction between science and practice, including the importance of social processes and recognition of different ways of knowing, as well as how to conduct collaborative approaches on a variety of scales and think about how to generalize findings. The review suggests a need to rethink roles and relationships in the process of knowledge co-creation, both extending the roles of researchers and practitioners, creating new hybrid roles for “pracademics”, and placing greater awareness on issues of power.

Knowledge differences impede the work of cross-functional teams by making knowledge integration difficult, especially when the teams are faced with novelty. One approach in the literature for overcoming these difficulties, which we refer to as the traverse approach, is for team members to identify, elaborate, and then explicitly confront the differences and dependencies across the knowledge boundaries. This approach emphasizes deep dialogue and requires significant resources and time. In an exploratory in-depth longitudinal study of three quite different cross-functional teams, we found that the teams were able to cogenerate a solution without needing to identify, elaborate, and confront differences and dependencies between the specialty areas. Our analysis of the extensive team data collected over time surfaced practices that minimized members' differences during the problem-solving process. We suggest that these practices helped the team to transcend knowledge differences rather than traverse them. Characteristic of these practices is that they avoided interpersonal conflict, fostered the rapid cocreation of intermediate scaffolds, encouraged continued creative engagement and flexibility to repeatedly modify solution ideas, and fostered personal responsibility for translating personal knowledge to collective knowledge. The contrast between these two approaches to knowledge integration—traverse versus transcend—suggests the need for more nuanced theorizing about the use of boundary objects, the nature of dialogue, and the role of organizational embeddedness in understanding how knowledge differences are integrated.

Purpose Despite the importance of green supply chain integration (GSCI) in advancing green innovation (GI) is recognized, it remains unclear how firms can translate their GSCI efforts into GI. Therefore, this study aims to understand how GSCI affects GI, with its dimensions (exploitative GI and exploratory GI), as well as to investigate the mediating role of green knowledge integration capability (GKIC) and the moderating role of blockchain technology (BCT) adoption. Design/methodology/approach On the basis of data collected from 247 managers working in Indian firms in the automotive industry, the authors tested the proposed model using the PROCESS macro tool via SPSS software. Findings The empirical results indicate that GSCI is positively associated with both exploitative and exploratory GI, with a higher effect on exploitative GI. In addition, GKIC mediates the link between GSCI and exploitative GI in contrast to exploratory GI. Notably, the relationship between GSCI and GKIC is stronger when BCT adoption is high. Originality/value This study opens the black box of how GSCI affects exploitative and exploratory GI by revealing the mediating role of GKIC and the moderating role of BCT adoption. It provides valuable insights for practitioners to translate GSCI efforts into GI through developing GKIC and adopting BCT.

With the growing need for intelligent decision-support systems, the development of high-quality knowledge graphs has become essential for improving operational efficiency and decision reliability. However, the specialized nature, distributed sources, and sensitive aspects of this knowledge present unique challenges to conventional knowledge management approaches. Current general-purpose large language models often struggle with domain-specific text comprehension, particularly in accurately interpreting technical parameters and operational guidelines. To address these limitations, this paper introduces a framework for building and refining specialized knowledge graphs using adapted large language models. Our approach involves fine-tuning base LLMs with domain-specific datasets, enabling them to better handle complex terminology and semantic nuances. The framework incorporates a multimodal knowledge integration pipeline that combines rule-based systems with ontological structures to extract and link entities from diverse data sources, creating an adaptive knowledge network. Experimental results demonstrate that our fine-tuned model achieves substantial gains in relationship extraction accuracy, while the resulting knowledge graph shows strong performance in semantic coherence and operational reasoning assessments, offering robust support for critical decision-making processes. This research presents a novel approach for effective knowledge integration and cross-functional collaboration in specialized domains.

PurposeThe purpose of this study is to extend the existing literature on knowledge management, which generally focuses on knowledge sharing. The model of this article explains how knowledge creation and team performance can be increased through the integration of social and technological factorsDesign/methodology/approachTo empirically test the model, multi-wave and multi-source data were collected from 80 teams whose members use social media as a tool for communication and interaction.FindingsThe analysis results provide insights into some interesting findings. The results show transactive memory system (TMS) as an important factor that can significantly contribute to knowledge creation in teams. Especially, the TMS strengthens the significant positive effect of enterprise social media (ESM) and insignificant positive effect of knowledge complementarity on knowledge creation. Furthermore, knowledge creation is found to be a significant predictor of team performanceOriginality/valueMuch of the knowledge management literature focuses on the ways to increase the quantity of accessible knowledge to organization members. Such knowledge management studies are more relevant to knowledge exchange among individual employees, teams and organizations. However, this study takes a nuanced approach to explore how knowledge creation can be increased in teams by implementing a knowledge integration mechanism. A general model of knowledge creation is proposed, but the strength of this model lies in the moderating effect of TMS which strengthens the effect of knowledge complementarity and ESM on knowledge creation in teams which eventually increases team performance.