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Companies are increasingly implementing business process management systems (BPMSs) to support their processes. However, there is a gap in the literature regarding whether users also use BPMSs to manage the knowledge needed for processes to be completed. This study aims to analyze the factors that cause users to use BPMSs to manage the knowledge required in business processes.

The paper proposes an original model that integrates two successful information system models applied to BPMSs and knowledge management systems. To test the hypotheses derived from this new model, data were collected from 242 mature BPMS users from 12 Spanish and Latin American companies. Structural equation modeling with AMOS was used to examine the model.

Users’ perceived usefulness of a BPMS when using it for knowledge management (KM) is the only factor influencing them to use it for KM.

This study has practical implications for managers wishing to successfully implement a BPMS to support processes and for employees to use the knowledge embedded in the tool. The latter will only happen if users perceive the tool’s usefulness for KM.

To the best of the authors’ knowledge, this model is the first empirically validated model to successfully analyze BPMS users’ tendency to use BPMSs as a tool to support necessary KM in processes.

The study examines the mediating effect of knowledge management (KM) in the relationship between the high-performance organisation (HPO) framework and high performance in financial institutions (FIs) in Uganda. The paper aims to develop a framework that promotes high performance in the FIs.

The conceptual model was tested on a sample of 28 financial instituitions using structural equation model.

The findings revealed that the high-performance framework is significantly related to high performance and KM is related high performance. KM mediates the relationship between the high-performance framework and high performance.

The findings revealed that the high-performance framework is significantly related to high performance and KM is related high performance. KM mediates the relationship between the high-performance framework and high performance.

The findings revealed that the high-performance framework is significantly related to high performance and KM is related high performance. KM mediates the relationship between the high-performance framework and high performance.

This study makes several empirical and theoretical contributions, addressing the gap in the literature about the role of the HPO framework in strategic management. This study tests the relationship between the HPO and the firm's performance by taking the mediating effects of KM. The designed model highlights a significant organisational performance approach that can influence the finance sector positively.

This study investigates the impact of entrepreneurial orientation (EO) and knowledge management (KM) on firm performance (PERF), as well as the mediating role of KM in the EO–PERF (EO-PERF relationship). In particular, this study aims to explain the impact of KM on the relationship between the EO dimensions and PERF; dimensions are risk-taking (RT), innovativeness (IN) and proactiveness (PR).

This study uses structural equation modelling and fuzzy-set qualitative comparative analysis (fsQCA) methodologies to explore target relationships. The sample consists of 150 small furniture manufacturers operating in Poland (out of 1,480 in the population).

The study findings show that KM partially mediates the IN–PERF relationship. Furthermore, fsQCA reveals that KM accompanied by IN is a core condition that leads to PERF. Moreover, the absence of KM (accompanied by the absence of RT and IN) leads to the absence of PERF. In addition, the results show that all the variables examined (RT, IN, PR and KM) positively impact PERF.

This study explores the role of KM in the context of EO and its impact on PERF in the low-tech industry. The study uses simultaneously two methodologies that represent different approaches in the search for the expected relationships. The findings reveal that KM mediates the EO-PERF relationship.

This study aims to examine the relationship between green technology implementation (GTI), knowledge management (KM) process and knowledge workers' operational performance (KWOP). The research postulates that a specific combination of GTI and KM processes can lead to improving KWOP.

The sample data (304) were taken from those manufacturing firms that are utilizing green technology. The examination was conducted by Smart PLS-SEM and fuzzy set qualitative comparative analysis (fsQCA). The Smart PLS 3.29 is used to verify certain variable relationships. Moreover, fsQCA is used to investigate multiple configuration paths to enhance KWOP.

The study's outcome indicated that GTI positively influences the KM process in manufacturing firms, and the KM process enormously improves KWOP. The fsQCA analysis result explores various integrations (communication, collaboration, supporting role and improved performance) with the KM (acquisition, sharing and utilization) process identified to enhance the performance of KWOP. The current study supports two merging methods to deepen understanding of employee operational performance.

The study methodologically contributes by integrating direct and configuration approaches to develop firms' operational performance. This study contributes to bridging research gaps in the prior literature and advances insight into the association between GTI, KM process and KWOP.

Organizations widely adopt knowledge management (KM) to develop and promote technologies and improve business effectiveness. Analytics can aid in KM, further augmenting company performance and decision-making. There has been significant research in the domain of analytics in KM in the past decade. Therefore, this paper aims to examine the current body of literature on the adoption of analytics in KM by offering prominent themes and laying out a research path for future research endeavors in the field of KM analytics.

A comprehensive analysis was conducted on a collection of 123 articles sourced from the Scopus database. The research has used a Latent Dirichlet Allocation methodology for topic modeling and content analysis to discover prominent themes in the literature.

The KM analytics literature is categorized into three clusters of research – KM analytics for optimizing business processes, KM analytics in the industrial context and KM analytics and social media.

Systematizing the literature on KM and analytics has received very minimal attention. The KM analytics view has been examined using complementary topic modeling techniques, including machine-based algorithms, to enable a more reliable, systematic, thorough and objective mapping of this developing field of research.

Based on an exploratory case-based approach, the purpose of this paper is to open the KM black box and examine the relationships that link knowledge management (KM) inputs (i.e. knowledge resources and KM practices) via knowledge processes to KM performance. This paper aims to identify the underlying mechanisms and explain how KM performance is enabled.

This in-depth case study conducted at a medium-sized consultancy in the supply chain management industry empirically examines knowledge flows to uncover the relationships between KM inputs, knowledge processes and KM performance. We adopt the viable system model (VSM) as a theoretical lens to identify KM mechanisms.

By identifying six KM mechanisms, we contribute to the theoretical understanding of how KM inputs are interconnected and lead to KM performance via knowledge processes.

Based on the insights gained, we provide propositions that organizations should consider in designing viable KM. Our findings help organizations in understanding their KM with the help of knowledge flow analysis and identifying how critical KM elements are interconnected.

This paper aims to understand the spatiotemporal influence of metro rail connectivity on housing prices in surrounding areas. The study assesses the average annual price shift for apartments around metro stations in Delhi during the previous decade, specifically from 2010 to 2019. The authors examine the spatiotemporal extents to which housing prices are determined by the prominence of metro stations and spatial development around metro stations.

The authors perform the cross-tabulation analysis to calculate chi-square values to test the hypotheses concerning the responsiveness of the housing market in Delhi to the number of locational variables in the areas connected with the mass public transportation system.

The empirical findings verify the existence of a housing market overvaluation in Delhi around metro stations until 2013, which was eventually re-adjusted after 2014. The key findings of the study suggest the role of location variables concerning metro rails in the shooting up of the housing prices in the city. In addition, the research establishes the association of annual housing price shifts to the metro rails in the short-term, mid-term and long-term in conjunction with the distance from the metro station.

In the market, the prices are often overvalued by real estate agents due to better connectivity to the metro stations. The overvaluation eventually causes massive downfalls in housing markets and rollouts as a risk for the investors. However, the effect of mass transportation on housing prices is mixed in nature, limited to a certain extent only and not as influential as frequently portrayed by the market forces. This effect loses colour with time.

This study examines the relationship between higher education improvement and tacit knowledge importance. In this context, the scarcity of empirical and theoretical studies on acquiring tacit knowledge to enhance academic performance in higher education suggests that this research area holds significant importance for experts and policymakers. Consequently, this study aims to explore the factors that influence academic research performance at Chinese universities by acquiring tacit knowledge.

To achieve the study aims, the current approach utilizes the research technique based on the socialization, externalization, internalization and combination (SECI) model and knowledge management (KM) theory. To analyze the study objective, the authors collected data from post-graduate students at Chinese universities and analyzed it using structural equation modeling (SEM) to test the model and hypotheses.

The results indicated that social interaction, internalization and self-motivation have a positive impact on academic research performance through the acquisition of tacit knowledge. Furthermore, the findings suggest that academic researchers can acquire more knowledge through social interaction than self-motivation, thereby advancing research progress.

This study addresses the critical issues surrounding the acquisition of tacit knowledge and presents a comprehensive framework and achievements that can contribute to achieving exceptional academic performance.

This paper aims to analyze factors based on organizational knowledge management (KM; transactional memory systems and knowledge-oriented leadership [K-OL]) that help firms to mitigate conflicts based on task management at work, with the aim to improve their innovation capabilities (IC). The knowledge-based view of the firm, conflict management theory and cognitive collective engagement theory have been used to build a model of relationships that connects the development of positive KM contexts and management of dysfunctional conflict with IC improvement.

Data survey collected from inland hotel establishments in Spain is used to test seven hypotheses by means of structural equations modeling, applying the partial least squares technique. Direct, indirect and mediating relationships between variables are examined from the structural path model.

The results confirm that, as expected, IC improve when K-OL and transactive memory systems (TMSs) are properly implemented by hotel establishments, which leads them to reduce negative effects of task management conflict (TMC). Significant direct effects are found between the key variables of the study and also a significant indirect effect between K-OL and IC through TMS reinforcement and the mitigation of TMC.

This paper provides useful ideas for hotel managers about how to improve KM contexts in their establishments while avoiding TMC. Efforts devoted to creating those contexts by hotel establishments are shown to be effective to improve their IC and create competitive advantages.

The analysis of IC improvement by studying TMC mitigation had not been researched to date by the KM literature. The consideration and testing of a model that integrates KM-related tools such as K-OL and TMS to avoid TMC in the hotel industry is the main contribution of this study.

This study aims to extend and explore patterns and trends of research in the linkage of big data and knowledge management (KM) by identifying growth in terms of numbers of papers and current and emerging themes and to propose areas of future research.

The study was conducted by systematically extracting, analysing and synthesizing the literature related to linkage between big data and KM published in top-tier journals in Web of Science (WOS) and Scopus databases by exploiting bibliometric techniques along with theory, context, characteristics, methodology (TCCM) analysis.

The study unfolds four major themes of linkage between big data and KM research, namely (1) conceptual understanding of big data as an enabler for KM, (2) big data–based models and frameworks for KM, (3) big data as a predictor variable in KM context and (4) big data applications and capabilities. It also highlights TCCM of big data and KM research through which it integrates a few previously reported themes and suggests some new themes.

This study extends advances in the previous reviews by adding a new time line, identifying new themes and helping in the understanding of complex and emerging field of linkage between big data and KM. The study outlines a holistic view of the research area and suggests future directions for flourishing in this research area.

This study highlights the role of big data in KM context resulting in enhancement of organizational performance and efficiency. A summary of existing literature and future avenues in this direction will help, guide and motivate managers to think beyond traditional data and incorporate big data into organizational knowledge infrastructure in order to get competitive advantage.

To the best of authors’ knowledge, the present study is the first study to go deeper into understanding of big data and KM research using bibliometric and TCCM analysis and thus adds a new theoretical perspective to existing literature.