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This study aims to focus on a key unanswered question about how digitalization and the knowledge processes it enables affect firms’ strategies in the international arena.

The authors conduct a systematic literature review of relevant theoretical and empirical studies covering over 20 years of research (from 2000 to 2023) and including 73 journal papers.

This review allows us to highlight a relationship between firms’ international strategies and the knowledge processes enabled by applying digital technologies. Specifically, the authors discuss the characteristics of patterns of knowledge flows and knowledge processes (their origin, the type of knowledge they carry on and their directionality) as determinants for the emergence of diverse international strategies embraced by single firms or by populations of firms within ecosystems, networks, global value chains or alliances.

Despite digital technologies constituting important antecedents and critical factors for the internationalization process, and international businesses in general, and operating cross borders implies the enactment of highly knowledge-intensive processes, current literature still fails to provide a holistic picture of how firms strategically use what they know and seek out what they do not know in the international environment, using the affordances of digital technologies.

Deployment of knowledge management systems (KMSs) suffers from low adoption in organizational reality that is attributed to a lack of perceivable added value for people in actual work situations. Poor task/technology fit in the process of knowledge retrieval appears to be a major factor influencing this issue. Existing research indicates a lack of re-contextualizing stored information provided by KMSs in a particular situation. Existing research in the area of organizational memory information systems (OMISs) has thoroughly examined and widely discussed the topic of re-contextualization. The purpose of this paper, thus, is to examine how KMS design can benefit from OMIS research on approaches for re-contextualization in knowledge retrieval.

This paper examines OMIS literature and inductively derives a categorization scheme for KMS according to their strategy of re-contextualizing knowledge. The authors have validated the scheme validated in a multiple case study that examines the differentiatory value of the scheme for approaches with various re-contextualization strategies.

The classification scheme allows a step-by-step selection of approaches for re-contextualization of information in KMS design and development derived from OMIS research. The case study has demonstrated the applicability of the developed scheme and shows that the differentiation criteria can be applied unambiguously.

Because of the chosen case study approach for validation, the validation results may lack generalizability.

The scheme enables an informed selection of KMSs appropriate for a particular OMIS use case, as the scheme’s attributes serve as design rationale for a certain architecture or constellation of components. Developers can not only select from various approaches when designing re-contextualizaton but also come up with rationales for each candidate because of structured representation. Hence, stakeholders can be supported in a more informed way and design KMSs more effectively along organizational change processes.

The paper addresses an identified need for systematic characterization of KMS approaches and systems intending to meet the objectives of OMISs. As such, it allows streamlining further research in this field, as approaches can be judged according to their originality and positioned relative to each other.

In this study, reasons for proving the relevancy of personalisation of e-learning systems to act as a knowledge management system in which tacit to tacit type of knowledge (socialisation) can be delivered, are being provided. Nonaka’s knowledge conversion model is being used as the basis of the investigation. The relationship between ‘the strategic knowledge conversion model’ drawn from the ‘identifying list of strategies’ and ‘an individual’s decision-making method’ has been investigated in relation to knowledge transferring systems and individual’s learning styles. The outcome of the qualitative as well as quantitative investigation defines a set of frameworks in which different types of e-learning systems utilizing different learning philosophies and learners learning preferences to support the learner’s learning curve.

In recent years, there has been a growing dialogue around community-based and systems-based approaches to security risk management through the introduction of top-down and bottom-up knowledge acquisition. In essence, this relates to knowledge elicited from academic experts, or security subject-matter experts, practitioner experts, or field workers themselves and how much these disparate sources of knowledge may converge or diverge. In many ways, this represents a classic tension between organisational and procedural perspectives of knowledge management (i.e. top-down) versus more pragmatic and experience focussed perspectives (i.e. bottom-up).

This chapter considers these approaches and argues that a more consistent approach needs to address the conflict between procedures and experience, help convert field experience into knowledge, and ultimately provide effective training that is relevant to those heading out into demanding work situations. Ultimately, ethics and method are intricately bound together in whichever approach is taken and the security of both staff and at-risk populations depends upon correctly managing the balance between systems and communities.

This article proposes an architecture of an intelligent and autonomous recommendation system to be applied to any virtual learning environment, with the objective of efficiently recommending digital resources. The paper presents the architectural details of the intelligent and autonomous dimensions of the recommendation system. The paper describes a hybrid recommendation model that orchestrates and manages the available information and the specific recommendation needs, in order to determine the recommendation algorithms to be used. The hybrid model allows the integration of the approaches based on collaborative filter, content or knowledge. In the architecture, information is extracted from four sources: the context, the students, the course and the digital resources, identifying variables, such as individual learning styles, socioeconomic information, connection characteristics, location, etc. Tests were carried out for the creation of an academic course, in order to analyse the intelligent and autonomous capabilities of the architecture.

In current business management, knowledge is considered to be a strategic resource that can strengthen an organization’s competitiveness. Today, under the process of continuous globalization, almost all companies are rapidly exposed to global competition regardless of their scale or type of business. However, multinational management is very complicated and uncertain and it is hard for multinationals to effectively coordinate and manage their global value chains. In light of this, the utility of multinational management based on knowledge is increased. The present study examines multinational firms’ knowledge management systems, knowledge creation processes and global supply chain performance and attempts to reveal any significant linkages between these latent variables. For this research interest, we proposed 18 items to measure four types of knowledge creation processes (SECI) designed by Nonaka (1994) and revised by authors considering the global business environment, in particular involving the global supply chain management concept. Utilizing the confirmed SECI model, 128 sample companies were classified into four groups according to the levels of their knowledge creation processes. The empirical results of this study reveal important linkages between a multinational firm’s knowledge management system and knowledge creation process, as well as between its knowledge creation process and global supply chain management performance. In particular, the current work suggests that the creation and conversion of tacit knowledge as well as explicit knowledge can be effectively supported by information and communication technology.

In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.

Using the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.

The results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.

The study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.

This research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.

This study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.

Knowledge- and communication-intensive domains still long for a better support of creativity that considers legal requirements, compliance rules and administrative tasks as well, because current systems focus either on knowledge representation or business process management. The purpose of this paper is to discuss our model of integrated knowledge and business process representation and its presentation to users.

The authors follow a design science approach in the environment of patent prosecution, which is characterized by a highly standardized, legally prescribed process and individual knowledge study. Thus, the research is based on knowledge study, BPM, graph-based knowledge representation and user interface design. The authors iteratively designed and built a model and a prototype. To evaluate the approach, the authors used analytical proof of concept, real-world test scenarios and case studies in real-world settings, where the authors conducted observations and open interviews.

The authors designed a model and implemented a prototype for evolving and storing static and dynamic aspects of knowledge. The proposed solution leverages the flexibility of a graph-based model to enable open and not only continuously developing user-centered processes but also pre-defined ones. The authors further propose a user interface concept which supports users to benefit from the richness of the model but provides sufficient guidance.

The balanced integration of the data and task perspectives distinguishes the model significantly from other approaches such as BPM or knowledge graphs. The authors further provide a sophisticated user interface design, which allows the users to effectively and efficiently use the graph-based knowledge representation in their daily study.

Due to the globalization of trade, hundreds of millions containers pass every year through world ports. Such a situation is extremely challenging in terms of securing freight transport operations. However, costs and lead-times are still very important components of supply chains' performance models. Therefore, the drive for enhanced safety and security cannot be made at the expense of these other two factors of competitiveness, and the processes implemented by the global supply chain links, including the maritime port one, should tend to a joint optimization of trade facilitation and operational safety / security.

The research on which this paper feeds back falls within the frame of this mixed performance requirement. More specifically, the paper presents a decision-support system dedicated to managing the risks associated with land and maritime container transportation; this system is based on the modeling of the knowledge of a group of experts, and covers the three phases of risk identification, assessment and avoidance / mitigation.

This paper aims to contribute to overcoming the gap existing in the supply chain literature related to digital servitization by bridging digital servitization with knowledge management and identifying the rise of digital knowledge servitization as a driver for changes in the supply chain business model towards open innovation.

The study follows an inductive grounded theory approach for theory building. To analyse the impact of digital knowledge servitization, in-depth interviews of managers in the main business units of the Volvo Group supply chain ecosystem were carried out.

The results show how the digital servitization process affects the supply chain business model, highlighting the central role of knowledge in the service ecosystem and the rise of the theoretical concept of digital knowledge servitization. In particular, through the Innovation Lab (Volvo Group) study, the paper contributes to bringing together the theoretical knowledge-based view of servitization with the digital servitization concept, which demonstrates the role of this combined perspective in the transformation of the supply chain; this is carried out by introducing a new business model based on open innovation in inbound and outbound processes.

The research offers interesting insights from a managerial perspective, as increasingly advanced and complex digital solutions require shorter times in supply chain management (SCM). Companies need to be able to quickly manage information and knowledge flows deriving from internal and external interactions and involvement with external actors upstream and downstream of the supply chain ecosystem. Therefore, the digital knowledge servitization of the supply chain also highlights implications for managers in terms of human resources management.

The novel research goal is to contribute to the supply chain literature by integrating the digital servitization with the knowledge view and analysing the impact on the inbound and outbound supply chain through the introduction of an open innovation business model.