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The below-average innovative capacity of the tourism sector raises the question on the potentials of digital business ecosystems (DBEs) to overcome these shortages at a destination level – especially within a smart city environment. Using the example of the German Capital Berlin, this article aims to discuss both the possibilities and inhibitors of innovative knowledge-creation by building scenarios on one specific design option: the integration of digital deep learning (DL) functionalities and traditional organizational learning (OL) processes.

Using the qualitative GABEK-method, major characteristics of a DBE as resource-, platform- and innovation systems are analyzed toward their interactions with the construction of basic action models (as the basic building blocks of knowledge).

Against the background of the research findings, two scenarios are discussed for future evolution of the Berlin DBE, one building on cultural emulation as a trigger for optimized DL functionalities and one following the idea of cultural engineering supported by DL functionalities. Both scenarios focus specifically on the identified systemic inhibitors of innovative capabilities.

While this study highlights the potential of the GABEK method to analyze mental models, separation of explicit and latent models still remains challenging – so does the reconstruction of higher order mental models which require a combined take on interview techniques in the future.

The resulting scenarios innovatively combine concepts from OL theory with the concept of DBE, thus indicating possible pathways into a tourism future where the limitations of human learning capacities could be compensated through the targeted support of general artificial intelligence (AI).

The link between theory and practice in innovation studies still has some gaps, despite scholars’ efforts to illustrate and identify them in real-world situations. To fully understand the dynamics of the innovation ecosystem, it is crucial to consider key actors and their roles and recognize their impact on ecosystem outcomes. Therefore, this paper seeks to discuss how analytical structures of innovation ecosystems address the dynamics of actors and their contribution to the ecosystem outcomes.

A research protocol was developed to query the Web of Science database to identify analytical structures of innovation ecosystems based on pre-established criteria.

The dynamics of actors interfere with their contribution to value creation. That is, the actor changes his contribution. Therefore, depending on the ecosystem's value proposition, the activities and dynamics of the actors change over time.

It contributes to advancing the discussion of innovation ecosystems, addressing insights into the dynamics of actors in different analytical structures. The essay proposal considers innovation ecosystems' evolutionary aspects, value propositions and exchange. In addition, the importance of orchestration in the various stages of the ecosystem is highlighted.

This study aims to perform a bibliometric and systematic literature review (SLR) to elucidate the current landscape and to propose a framework that defines and explores research strands to guide the formulation of business process management (BPM) strategies anchored in digital innovations.

A bibliometric analysis of 238 papers from the last 10 years (2014–2023) that were correlated to BPM strategies and digital innovations was conducted. Additionally, a SLR was performed on 15 selected papers, making it possible to propose a framework that explored research strands through the content analysis.

A framework comprising eight research strands (value creation; ambidexterity; governance; agility in processes; strategic process management; external context and culture and integrated systems) was developed. It proposes a research agenda and provides valuable insights as a reference for formulating BPM organizational strategies anchored in digital innovations.

This study acknowledges the limitation of utilizing a single software for bibliometric analysis. The framework developed in this study has not yet been validated.

This paper provides insights to assist managers in comprehending BPM strategies anchored in digital innovations and calls for organizations to prepare for future digital needs.

This paper contributes to advancing our understanding of BPM aligned with the demands of a digital age society.

The developed framework sheds light on the current landscape and research strands that explore the association between digital innovations and BPM strategies. This provides a valuable opportunity for future qualitative and quantitative studies to explore the eight research strands presented in the framework.

This study aims to explore how health-care organisations learn from failures, challenging the common view in management science that learning is a continuous cycle. It focuses on understanding how the context of a health-care organisation and the characteristics of failure interact.

Systematically collected empirical studies that examine how health-care organisations react to failures, both in terms of learning and non-learning, were reviewed and analysed. The key characteristics of failures and contextual factors are categorised at the individual, team, organisational and global level.

Several factors across four distinct levels are identified as being susceptible to the situational impact of failure. In addition, these factors can be used in the design and development of innovations. Taking these factors into account is expected to stimulate learning responses when an innovation does not succeed. This enhances the understanding of how health-care organisations learn from failure, showing that learning behaviour is not solely dependent on whether a health-care organisation possesses the traits of a learning organisation or not.

This review offers a new perspective on organisational learning, emphasising the situational impact of failure and how learning occurs across different levels. It distinguishes between good and bad failures and their effects on a health-care organisation’s ability to learn. Future research could use these findings to study how failures influence organisational performance over time, using longitudinal data to track changes in learning capacity.

Knowledge is a vital strategic resource for multinational enterprises (MNEs). As MNEs expand internationally, knowledge transfer through expatriates is a crucial part of the value proposition of outward foreign direct investment. However, this is undermined if knowledge is hidden rather than shared. Given the scarcity of research on knowledge hiding in MNEs, this paper aims to investigate this phenomenon among expatriates and develops a new framework to analyze knowledge hiding.

Survey data from 201 Chinese MNE expatriates is collected and analyzed using Partial Least Squares – Structural Equation Modeling to test the relationships between knowledge hiding, organizational practices, cultural intelligence and job embeddedness. Relevant organizational practices based on the ability-motivation-opportunity enhancing framework were identified, based on 24 semi-structured qualitative interviews which guided the quantitative analysis.

The direct effects of organizational practices on all types of knowledge hiding are limited. However, organizational practices’ influence on knowledge hiding is mediated by the cultural intelligence of expatriates, and this relationship is moderated by job embeddedness.

The research advances current thinking about knowledge management and outlines both theoretical and practical implications at organizational and societal levels. It explores the mechanisms for remedying knowledge hiding through organizational practices, including the interactive effects of cultural intelligence and job embeddedness among expatriates. Organizational knowledge management strategies in MNEs need to recognize cultural differences and improve job embeddedness to form the basis of successful knowledge transfer.

Hyperinflation is a rare form of macroeconomic crisis that often results from extreme political events, such as revolution or regime change. The 1989–1990 Argentine hyperinflation is puzzling because it occurred in the absence of such an event. Moreover, conventional fiscal mechanisms linking political processes to hyperinflation do not sufficiently explain the Argentine case. Previous theories emphasizing distributional conflict and institutional weakness contain key elements of an explanation of the Argentine hyperinflation but do not capture the range of mechanisms that produced extreme financial instability. This chapter offers an elite theory approach that subsumes elements of these approaches within a broader theory of elite fragmentation, competition, and conflict. Elite fragmentation inhibits collective action in both economic and state elites, resulting in deficits in policymaking capacity. Fragmentation among state policy elites leads to policy volatility and incoherence, while fragmentation among politically mobilized economic elites results in elite stalemates constraining the options of policy elites. These policymaking patterns lead to prolonged delays in the adjustment of unsustainable organizational structures, resulting in explosive forms of crises.

This study aims to analyse the relationship between a patent’s network position in a knowledge search network and the likelihood and speed of patent transactions. Additionally, it explores whether patent scope moderates these relationships.

In this empirical study, the authors collected a sample of patents in the artificial intelligence industry over the period of 1985–2018. Then, the authors examined the direct roles of degree centrality, betweenness centrality and closeness centrality on the likelihood and speed of patent transactions and the moderating role of patent scope in the knowledge search network using the logit and accelerated failure time models.

The findings reveal that degree centrality positively affects both the likelihood and speed of patent transactions, while betweenness centrality enhances the likelihood, and closeness centrality significantly boosts both. However, regarding the speed of patent transactions, closeness centrality is the most impactful, followed by degree centrality, with no significant influence of betweenness centrality. Additionally, the patent scope moderates how betweenness centrality affects the likelihood of transactions.

This study has limitations owing to its exclusive use of data from the Chinese Intellectual Property Office, lack of visibility of the confidential terms of most patent transactions, omission of transaction directionality and focus on a single industry, potentially restricting the breadth and applicability of the findings. In the future, expanding the data set and industries and combining qualitative research methods may be considered to further explore the content of this study.

This study has practical implications for developing a better understanding of how network structure in the knowledge search network affects the likelihood and speed of patent transactions as well as the identification of high-value patents. These findings suggest future directions for patent holders and policymakers to manage and optimise patent portfolios.

This study expands the application boundaries of social network theory and the knowledge-based view by conducting an in-depth analysis of how the position characteristics of patents within the knowledge search network influence their potential and speed of transactions in the technology market. Moreover, it provides a theoretical reference for evaluating patent value and identifying high-quality patents by quantifying network positions. Furthermore, the authors construct three centrality measures and explore the development of patent transactions, particularly within the context of the developing country.

Pressure to address drug shortages is increasing, and calls for cross-national stockpiling solutions are on the rise. This paper argues that cross-national stockpiling presents an important opportunity for operations and supply chain management (OSCM) research to help improve medicine access in the short- and long-term.

To substantiate our claims for future research, we conducted an empirical analysis of shortage co-occurrence on twelve EU member-states, reviewed practice reports and academic literature, and held extensive discussions with pharmaceutical supply chain stakeholders.

We show that the potential for cross-national stockpiling is unmistakably there and that, although OSCM research has touched upon important facets of cross-national stockpiling, many open questions still require novel research.

We present opportunities for impactful research along various dimensions, including understanding barriers and stakeholder behavior, quantifying cost-effectiveness and potential knock-on effects, analyzing the positive and negative implications of product standardization and determining novel equitable mechanisms for allocation and financing cross-national stockpiles.

This study compares the motivation, perceived crowding and satisfaction differences among local climbers in three Asian countries. The study population consists of mountain climbers from Taiwan's Yushan, Japan's Mount Fuji and Malaysia's Mount Kinabalu. The study involves 3,112 respondents from Mount Fuji, 192 from Mount Kinabalu and 391 from Yushan. The results from the Multivariate Analysis of Variance (MANOVA) show significant differences among climbers on the three mountains concerning climbers' motivation, perceived crowding and satisfaction. Social factors are the most significant motivators, with climbers on Mount Kinabalu, representing the most salient motivation for mountain tourism. For perceived crowding, climbers on Mount Fuji perceive congestion on the trails, mountaintops, restrooms and mountain huts and regard those services as unacceptable. Concerning satisfaction, services provided by mountain huts are the most significant, with the highest satisfaction recorded at Yushan's mountain huts. The study findings may be used as a reference for relevant tourism stakeholders and guide future research directions.