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This article investigates the determinants of knowledge management system (KMS) adoption, specifically with reference to Malaysian organizations across various industries.

The structural equation modelling approach using PLS technique was utilized to analyze the hypotheses developed, based on the survey data from 830 respondents comprised of information technology or knowledge management managers in Malaysian organizations from various industries.

Knowledge management (KM) enabling processes, perceived usefulness of KMS, knowledge sharing culture, knowledge taxonomy, and policy and procedure for KMS work, display significant positive effects on the KMS adoption level, with KM enabling processes having the strongest significant positive influence. Meanwhile, incentive and reward, management commitment, and KMS perceived ease of use possess no significant direct effect. However, management commitment was found to have an indirect effect on the KMS adoption level, where its effect is mediated by knowledge sharing culture.

This article outlines several managerial implications for enhancing the adoption of KMS, which include establishing appropriate KM enabling processes, identifying pertinent information to be preserved, shared, and reuse, and generating initiatives to instil a culture of knowledge sharing.

The empirical findings support the relevancy of the technology acceptance model (TAM) construct of perceived usefulness in KMS adoption context and advances the understanding that knowledge sharing culture is a highly influential factor for this construct. This study enriches and extends technology acceptance theory by presenting a more holistic model for KMS adoption with the integration of influencing factors that are inherent to organization.

This paper aims to identify the impact of demographical and organizational variables such as age, gender, experiences use of knowledge management system (KMS), education and job level on knowledge sharing (KS) performance of knowledge workers in knowledge activities of a KMS. Specifically, it seeks to explore that is there any relationship between the KS behavior patterns of high KS performance knowledge workers with their performance. Furthermore, this study using its conceptual attitude model aims to show that whether knowledge workers’ behavior patterns in sharing information and knowledge throughout a KMS have any specific effect or not.

This paper proposed a framework to mine knowledge workers’ raw data using data mining techniques such as clustering and association rules mining. Also, this research uses a case-based approach to a knowledge-intensive company in Iran that works in the field of information technology with 730 numbers of workers.

Findings suggest that demographical and organizational variables such as age, education and experience use of KMS have positive effects on knowledge worker’s KS behavior in KMSs. In fact, people who have lower age, higher education degrees and more experience use of KMS, have more participation in KS in KMS. Also, results depict that the experienced use of KMS has the most impact on the intention of KS in this KMS. Findings emphasize on the importance of the influence of the behavioral, organizational environments and psychological factors such as reward system, top management support, openness and trust, on KS performance of knowledge workers in the KMS. In fact, according to data, the KMS reward system caused to increasing participation of the users in KS, also in each knowledge activity that top managers participate in, the scores were higher.

This research helps top managers in designing policies and strategies to improve the participation of knowledge workers in KS and helps human resource managers to improve their membership policies. Also, assist Information Technology (IT) managers to enhance KMSs’ design to leverage with organization strategies in the field of improving KS and encourage people to participate in KMS.

This research has two key values. First, this paper applies a data mining framework to mining and analyzing data and this paper uses actual data of a KMS in a specialist company in Iran, with about 27,740 real data points. Second, this paper investigates the impact of demographical and organizational attributes on KS behavior, which little is empirically known about the impact of demographical variables on KS intention.

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.

This paper aims to consolidate the state of research on information behaviour. Regardless of the scholarly surge on information behaviour using numerous models and extended ones, gaps still exist on the development of more pragmatic frameworks that explain and/or predict the information behaviour across different fragmented environmental situations. Therefore, this paper extends technology-organization-environment (T-O-E) framework and synthesizes different research positions into a multi-dimensional framework that assists small and medium enterprises (SMEs) to understand their information behaviour and to make informed decisions on the adoption of emerging information communication technology (EICT).

This study deployed an inductive approach; data were generated from unstructured and semi-structured interviews with 20 participants drawn purposively from Luton directories.

This study developed a more integrated framework underpinned by T-O-E framework, which helped to identify how EICT adoption is critically shaped by perceived information need, information sources selection and the factors determining information source selection.

Qualitative research is normally subjective, inductive, interpretive and limited on the sample used. However, because of the limited number of interviews used, as well as industry-specific nature of the study, the generalization of the framework and the findings will be difficult, hence, the need to test the framework on a broader population and cross-context testing.

The T-O-E framework is extended to Expectancy (T-O-E-E) to provide a more robust insight into information behaviour of SMEs from a multi-dimensional perspective. It also offers a more analytical framework for exploring critical issues identified and demonstrates the capacity to provide a reliable explanation to the findings. Further, it serves as a tool for assessing the benefits or challenges of SMEs information behaviour especially on the EICT adoption decision.

The purpose of this study is to propose the research model integrating the expectation-confirmation model with the views of learning engagement (LE) and extending DeLone and McLean information systems (IS) success model to examine whether quality determinants as antecedents to students' beliefs can influence students' continuance intention of massive open online courses (MOOCs).

Sample data for this study were collected from students enrolled in a comprehensive university in Taiwan. A total of 600 questionnaires were distributed, and 363 (60.5%) useable questionnaires were analyzed using structural equation modeling in this study.

This study proved that students' perceived knowledge quality, system quality, interface design quality, learner–instructor interaction quality, and collaboration quality all positively caused students' perceived usefulness, confirmation and LE in MOOCs, which jointly explained students' satisfaction with MOOCs and subsequently resulted in students' continuance intention of MOOCs.

This study fully evaluates IS-related and interaction-related quality determinants via an understanding of students' state of LE in explaining students' continuance intention of MOOCs that is difficult to expound with only their utilitarian perception of MOOCs. Hence, this study contributes to deep insights into an all-round quality evaluation in the field of MOOCs continuance intention and takes extrinsic and intrinsic motivators into account in the theoretical development of MOOCs continuance intention to acquire a more comprehensive and robust analysis.

The usefulness of technology for managing projects in the construction industry is indisputable. The potential utility of immersive technologies (ImTs), including virtual and augmented reality, has recently received significant attention. However, the construction industry, especially in developing countries, lags on the implementation of technology generally and ImTs specifically. Forecasting the potential successful ImTs acceptance at the individual level is essential to strategic planning. The study's objective was to develop and test a conceptual model of factors influencing ImTs acceptance at the individual level in the construction industry.

A survey of construction management-level professionals in South Africa was undertaken. The study extended two complementary models, the technology acceptance model (TAM) and the theory of planned behavior (TPB), to analyze behavior towards technology acceptance using structural equation modelling.

Results indicated that attitude significantly influenced the intention to use ImTs and perceived usefulness (PU) positively and significantly predicted the intention to use and usage attitude (UA). Further, the effects of perceived enjoyment (PEn) on UA, and social norms (SNs) and perceived behavioral control (PBC) on intention to use were positive and significant. Perceived ease of use (PEU) had negative and non-significant effects on intention to use and UA. By explaining 82% of the variance, the study established that the proposed model successfully evaluates how management-level professionals in the construction industry accept ImTs.

The study provides valuable insight into the acceptance of ImTs from the perspective of management-level stakeholders in the South African construction industry. It offers fundamental direction to create a general theory on integrating ImTs in construction.

This study systematically surveyed the intention to accept ImTs in the South African construction industry using an extension of the TAM and TPB models.

The purpose of this paper is to structure existing research on knowledge management (KM) in small- and medium-sized enterprises (SMEs) to offer a comprehensive overview of research strands and topics in KM in SMEs to determine their evolution over time.

The paper, which is considered a follow-up literature review, is based on a systematic literature review that covers 180 scientific papers that were published since the review paper by Durst and Edvardsson in 2012 that covered 36 papers.

The findings of this review and those of the aforementioned review are brought together in the form of an overview that structures research on KM in SMEs based on themes that, in turn, allow the derivation of promising research directions and research questions aimed at structuring future research on KM in SMEs.

By combining the findings of this review with the findings from the review published in this journal in 2012, this paper offers, to the best of the authors’ knowledge, the most comprehensive literature review on KM in SMEs produced to date.

Knowledge management effects on business performances are of great importance for companies. Yet, they are still overlooked by current literature. Moreover, the use of methods for bibliometric reviews and content analysis reinforces the need for relevant work on the current state of knowledge management application. To this end, this study aims to identify the main barriers for the application of knowledge management in small and medium-sized enterprises. A research agenda is then proposed.

A systematic literature review was performed using data collection, bibliometric analysis and content analysis' steps. The sample used in this study contained 45 papers. For the bibliometric analysis, the authors used the bibliometrix (in RStudio). The content analysis was then performed to infer barriers, factors of relevance and an agenda of questions for future research.

The authors found that using knowledge management techniques to optimize business performance results in competitive advantages for small and medium-sized companies. This study contributes to both practitioners and academics by providing a list of 19 barriers, 12 factors and 36 research questions related to knowledge management in small and medium-sized companies to develop future theoretical and practical studies.

This study demonstrates the propensity and interest of small and medium-sized companies in using knowledge management. However, some barriers might make it difficult to implement this approach.

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 paper aims to map the knowledge management research in small businesses and suggest future actions to strengthen managerial practices. Knowledge management practices foster the growth of small businesses. They allow innovation to grow within the institutions, enhance customer satisfaction and reduce employee absenteeism and attrition.

The study adopts a bibliometric protocol to retrieve the 686 articles published in the Web of Science (WoS) database. The WoS database is selected to ensure only quality and peer-reviewed publications are analysed in the study. It then identifies the top contributions, and existing thematic areas, and suggests future research and policy actions for boosting economic growth through small business. The study uses VOSviewer, Science of Science (Sci2) and Gephi to conduct the bibliometric and network analysis.

The results from keyword co-occurrence and co-citation analysis helps in identifying thematic areas. The findings highlight that there exist five major themes in knowledge management research for small businesses. The dynamic co-citation analysis helps in tracing the evolution of these clusters and suggests future themes, research directions and methodological advances in the theme. PageRank analysis helps in identifying the top articles published on high-impact journals in the theme.

The study helps researchers by summarising existing literature and identifying key thematic areas. It also assists policymakers by recommending actions to improve knowledge management practises in small businesses to gain a competitive advantage. The paper suffers from the limitations of bibliometric analysis. The sample is collected from a single data source and a single type (journal articles) and the statistical accuracy of the analysis depends on the quality of the sample.

The study’s originality lies in using fit-for-purpose software in clustering the research and suggesting actions. To the best of the authors’ knowledge, this study is one of its kind in applying bibliometrics in studying and covering several aspects of knowledge management in small businesses with a combination of software.