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This paper aims to highlight the degree of diffusion and intensity of use of knowledge management systems (KMSs) among small and medium enterprises (SMEs) in Brazil and apply a taxonomy that synthesizes the strategies of use of KMSs by the SMEs. In addition, it seeks to better understand the processes, practices and technologies of KM by SMEs, pointing improvements in the KMS of Brazilian SMEs and contributing to obtain better results in the search for efficiency and innovation.

Based on a literature review on KMSs used by SMEs, an empirical investigation was conceived, developed and conducted through online questionnaires involving 49 selected SMEs operating in several sectors.

This paper reinforces the results of the previous work of Cerchione and Esposito (2017) that point to the existence of a reciprocal relationship between KM-Tools and KM-Practices: one reinforces the other and vice versa. On the other hand, it indicates a difference in the behavior of Brazilian companies in relation to the sample of Italian companies studied by Cerchione and Esposito (2017), which presented a negative correlation between the general differentiation index and the general use intensity index of SMEs, while the Brazilian ones showed a positive correlation.

The study points out the need for greater dissemination of practices and tools to support knowledge management (KM), as well as greater support for the implementation and effective use of these practices and tools within the organizational context of SMEs.

This paper identifies the main practices and tools to support KM used by Brazilian SMEs, indicating the need for investments in employee training and acquisition of tools.

SMEs represent an important part of the generation of jobs and income in Brazil. Initiatives that lead to the successful implementation of tools and practices to support KM can increase the efficiency and productivity of these organizations.

This paper applies in a sample of Brazilian companies the taxonomy proposed by Cerchione and Esposito (2017) combining strategies of SMEs for the use of KMSs.

This paper aims to propose a taxonomic scheme of knowledge management systems (KMSs) and a set of technologies and managerial practices supporting supply firms in knowledge management processes.

Based on a field analysis involving a sample of suppliers operating in high-tech manufacturing and service industries, this paper investigates the use of KMSs in the sample investigated.

The paper shows that suppliers are generally reluctant to use updated and innovative KMSs replacing traditional ones. This gap confirms that suppliers have difficulties in facing rapid technological changes. The field analysis also points out that suppliers investigated perceive knowledge management mainly as an issue of knowledge transfer and knowledge storage while appear to be neglected the phase of knowledge creation.

Moreover, the paper highlights a misalignment between the intensity of use of knowledge management practices that support the phase of knowledge creation and knowledge management tools that should support such practices.

This paper aims to conduct a tertiary review to analyse the state of the art of literature reviews on knowledge management (KM) published in academic journals and provide an overview of their evolution. From 2000 to 2022, about 500 reviews have been published in the KM field, with most systematic studies compared to bibliometric or meta-analytic studies, and an absence of previous tertiary studies. Therefore, given the lack of previous tertiary research, this paper provides a complete picture of the evolution of review topics in the past and presents implications for both researchers and practitioners.

A classification scheme was defined to cluster and evaluate the literature reviews, both in terms of methodological approach and content. Regarding the content, the various secondary papers were classified according to the purpose of the research (state of the art, taxonomy, research agenda and research framework), the unit of analysis (small and medium enterprise, large company, start-up and university), the KM models adopted and the thematic areas addressed. Furthermore, a tertiary review methodology was identified integrating two main approaches: a bibliometric approach for cluster identification and a systematic approach for the discussion.

Two categories of contributions emerge from the results: those concerning research topics that have found a continuous interest over time and those that have not yet found a constant research interest. This latter aspect is relevant to help researchers conduct future literature analysis in KM research to bridge existing research gaps.

This paper provides a unique compendium of search directions to offer a comprehensive overview of the scientific debate about KM. This overview can also be used as a managerial panacea to identify best KM practice guidelines from existing reviews.

This is a unique attempt to conduct a tertiary study on KM for more than two decades by providing insights into the structural body of knowledge through academic progress in the subject of KM. Thus, this study expands the field of KM and provides original approaches for research in the field.

Nowadays, a prominent research area is the development of competitive advantages in companies, due to their environmental commitment and orientation. Based on resource-based view (RBV) and institutional theory (InT), this paper aims to investigate the influence of internal and external orientation on businesses' sustainable performance while considering the effect of sustainable supply chain management (SSCM) practices.

Data from 351 manufacturing companies in the Kingdom of Saudi Arabia have been collected and analysed through structural equation modelling (SEM) using the partial least squares (PLS) method.

The results indicated that both internal and external environmental orientation have important effects on SSCM practices, which in turn have a considerable beneficial effect on environmental, social and economic performance.

Although SSCM is constantly gaining ground in the literature, most SSCM research and models examine its effects, antecedents or motivation, mainly adopting a qualitative approach. Research on the topic adopting a large-scale empirical approach is still limited. In this context, this study contributes to the SSCM management literature by exploring the role of environmental orientation in facilitating the adoption of SSCM practices and improving companies' performance.

This paper aims to design, build and evaluate a blockchain platform in the accounting domain, taking an ecosystem perspective. To achieve this aim, the research provides evidence for developing a decentralised architecture rooted on blockchain technology, designing a proof of concept and modelling an accounting blockchain-based system.

Moving from the analysis of previous literature and leveraging on the design science approach, this paper provides a framework grounded on the main pillars of blockchain and accounting functions, identifying technical and non-technical issues that must be addressed embrace blockchain technology's full potential.

We propose and discuss a conceptual framework for a blockchain-based accounting context, moving from the identification of a typical accounting scenario. The framework is organised around three scalable levels: the first level is a technological infrastructure based on a distributed database with peer-to-peer storage; second, in the intermediate level, increasing control levels are assured through permissions and validation and third, in the higher level, the system provides the integration of business and security applications. The deployment of this system relies on a private network of nodes that validates transactions.

The proposed conceptual framework about blockchain development in accounting allows closing the knowledge gap between blockchain developers and accounting experts by suggesting technological and strategic issues for practitioners.

We provide practical guidelines to design and adopt blockchain in the accounting domain.

This paper aims to propose a new three-dimensional (3D) fuzzy logic methodology to evaluate the level of misalignment between an enterprise’s knowledge and the knowledge management systems (KMSs) it adopts.

The proposed methodology was implemented by means of a field analysis based on semi-structured face-to-face interviews involving a sample of 61 small and medium enterprises (SMEs) operating in high-tech and/or complex industries.

The paper highlights that while there is generally a high level of misalignment between an enterprise’s knowledge and the KMSs adopted, there are also a broad variety of behaviours. The paper identifies a taxonomy able to bring together the various types of behaviour associated with how an enterprise’s knowledge is related to KMS selection. Specifically, four behaviour patterns were identified, and the enterprises were then categorised accordingly as being guideposts, practice laggards, tool laggards or latecomers.

The proposed taxonomy provides an operational tool that can be used by enterprises and policy makers alike. The paper shows how enterprises can use this tool to understand which category they belong to and support decision-making to introduce changes leading to improved levels of alignment. Policy makers, on the other hand, can use the proposed taxonomy to identify measures to support the competitiveness of local systems by improving management processes and knowledge sharing among enterprises.

The paper highlights the difficulties that SMEs experience in adopting KMSs that are truly aligned with their knowledge and proposes a methodology to improve alignment.

The evolution of Knowledge-Management (KM)-related literature has highlighted that Knowledge Management Systems (KMSs) have undergone massive changes in collaborative environments. Information-Systems-enabled KM seems to be the necessary response to the recent challenges posed by globalisation and technology dynamics to both large companies (LCs) and small and medium enterprises (SMEs).

This paper provides a systematic review about KMSs to offer an analytical overview of their role in supporting innovative forms of knowledge translation occurring in collaborative relationships. A sample of 129 papers was selected and analysed according to three perspectives: unit of analysis (LCs, SMEs), phases of the KM process (adoption, translation) and topic area (KM Practices, KM Tools, KMSs).

The findings highlight five literature gaps: (1) the role of KM practices supporting knowledge translation; (2) the impact of the alignment among KM practices, firm's complexity, dimension and culture on KM process; (3) the effect of KM tools on knowledge translation; (4) the variety of KMSs exploited in both LCs and SMEs; and (5) the alignment between organisational structure and information systems in KM context. Accordingly, 13 research questions were formulated.

The proposed research questions define a formal research agenda that could steer further research efforts about the KMS topic for improving the body of knowledge in the KM field. Scientific literature is currently lacking a contribution assessing the role of KMSs in supporting innovative forms of knowledge translation that occur in collaborative relationships.

The purpose of this paper is to propose an artificial intelligence-based framework to support decision making in wholesale distribution, with the aim to limit wholesaler out-of-stocks (OOSs) by jointly formulating price policies and forecasting retailer’s demand.

The framework is based on the cascade implementation of two artificial neural networks (ANNs) connected in series. The first ANN is used to derive the selling price of the products offered by the wholesaler. This represents one of the inputs of the second ANN that is used to anticipate the retailer’s demand. Both the ANNs make use of several other input parameters and are trained and tested on a real wholesale supply chain.

The application of the ANN framework to a real wholesale supply chain shows that the proposed methodology has the potential to decrease economic loss due to OOS occurrence by more than 56 percent.

The combined use of ANNs is a novelty in supply chain operation management. Moreover, this approach provides wholesalers with an effective tool to issue purchase orders according to more dependable demand forecasts.

This paper aims to propose a framework investigating the diffusion and adoption process of big data (BD) in the supply chain (SC) as a tool to manage process innovation at technological, operational and strategical levels.

A comprehensive systematic literature methodology is used to develop the theoretical conceptual framework, which comprehensively describes and captures the innovative stages of BD technology adoption process in SC with a multilevel perspective.

Results show that BD has modified the supply network concept, starting from the dyadic relationships, triads up to the creation of a streamlined and integrated network. These changes are reflected in a novel integrated vision including both benefits and barriers.

The proposed framework supports companies in redesigning the processes affected by the adoption of BD, helping them in identifying the critical elements, barriers, benefits and expected performance. One limitation is the focus of the study on the analysis of the processes of adoption of BD technology in the SC considering a particular structure of SC characterized by only two levels of supply and by a reduced number of members.

Although the role of BD in supply chain operations management (SCOM) is well acknowledged in the literature, its adoption and diffusion process from an interorganizational perspective is still missing. Specifically, the adoption stages of BD in SC have been defined at a strategic level, and successively the SC operations and technological perspective have been integrated to depict the operationalization of BD implementation and diffusion.

The modern knowledge-based economy acknowledges the role of the third mission of universities related to the process of knowledge transfer as a driving force to face sustainability issues, in addition to the two traditional missions focusing on research and teaching. The purpose of this paper is to investigate the relationships between internal environment, external environment, knowledge exploitation, knowledge exploration and university performance.

This study applies confirmatory factor analysis and structural equation modelling to test the conceptual model in the Chinese education system.

The findings confirm the higher impact of internal environment on both knowledge exploitation and knowledge exploration as compared to external environment. Knowledge exploitation is more strongly related to university performance than knowledge exploration. These results highlight the imperative role of internal university stakeholders in fostering knowledge management strategies. In addition, they encourage academicians, practitioners and policy makers to focus their attention on the impact of knowledge management models, tools and practices in universities to achieve the entrepreneurial development which, in turn, has a positive impact on individual graduates and innovation ecosystems.

The necessity to develop a more entrepreneurial university, as well as the lack of evidence of their development in emerging countries, highlights the need to investigate how specific factors and knowledge management processes are impacting the universities’ performance. In fact, although previous studies provide an explanation of the impact of internal and external factors on a university’s performance, contributions integrating these concepts with strategic knowledge management processes are still lacking.