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Motivated by empirical features that characterize cryptocurrency volatility data, the authors develop a forecasting strategy that can account for both model uncertainty and heteroskedasticity of unknown form. The theoretical investigation establishes the asymptotic optimality of the proposed heteroskedastic model averaging heterogeneous autoregressive (H-MAHAR) estimator under mild conditions. The authors additionally examine the convergence rate of the estimated weights of the proposed H-MAHAR estimator. This analysis sheds new light on the asymptotic properties of the least squares model averaging estimator under alternative complicated data generating processes (DGPs). To examine the performance of the H-MAHAR estimator, the authors conduct an out-of-sample forecasting application involving 22 different cryptocurrency assets. The results emphasize the importance of accounting for both model uncertainty and heteroskedasticity in practice.

This paper aims to propose a research model with eight constructs, i.e. BDA leadership, BDA talent quality, BDA security quality, BDA privacy quality, innovation, financial performance, market performance and customer satisfaction.

The research model focuses on whether (1) Big Data Analytics (BDA) leadership influences BDA talent quality, (2) BDA talent quality influences BDA security quality, (3) BDA talent quality influences BDA privacy quality, (4) BDA talent quality influences Innovation and (5) innovation influences a firm's performance (financial, market and customer satisfaction). An instrument was designed and administered electronically to a diverse set of employees (N = 188) in various organizations in the USA. Collected data were analyzed through a partial least square structural equation modeling.

Results showed that leadership significantly and positively affects BDA talent quality, which, in turn, significantly and positively impacts security quality, privacy quality and innovation. Moreover, innovation significantly and positively impacts firm performance. The theoretical and practical implications of the findings are discussed. Recommendations for future research are provided.

The study provides empirical evidence that leadership significantly and positively impacts BDA talent quality. BDA talent quality, in turn, positively impacts security quality, privacy quality and innovation. This is important, as these are all critical factors for organizations that collect and use big data. Finally, the study demonstrates that innovation significantly and positively impacts financial performance, market performance and customer satisfaction. The originality of the research results makes them a valuable addition to the literature on big data analytics. They provide new insights into the factors that drive organizational success in this rapidly evolving field.

Digital technology is crucial to improving a firm’s core competitiveness. However, the existing research on the relationship therein shows heterogeneity. Using digital technology can enhance competitive advantage, which is crucial for enterprises and scholars. Thus, based on the digital technology affordance theory, this study explores the relationship between digital technology affordance and digital competitive advantage.

Survey data were collected from 509 large and medium-sized manufacturing enterprises in China, and multiple regression and structural equation modelling were used to test the hypotheses. Specifically, we discuss the mediating role of digital business capability and the moderating role of organisational legitimacy.

Editability, association and visibility positively affect digital competitive advantage, and their coordination is strong. Further, they can help enterprises gain a competitive advantage through the mediating role of digital business capability (digital strategy, digital integration and regulation). However, the influence effect and action path differ per in different dimensions. Organisational legitimacy positively moderates the mediating effect of digital integration and regulation, and there is a moderated mediating effect. However, the moderating effect on the mediating effect of digital strategy is not significant.

Existing studies neglect the relationship between the coordination of digital technology functions and digital competitive advantage. This study provides a new theoretical explanation for an in-depth understanding of these issues. These findings promote the development of innovation theory and provide valuable insights for guiding the application of digital technology in enterprises.

This study investigates the views of Italian aquaculture production science students, in their role of future operators, on the application of circular economy strategies.

A key step in the development of professional knowledge is to solicit the opinions of the future operators in the aquaculture sector. The authors used the Q methodology to assess the perceptions of the students on four different knowledge dimensions of the CE: operations, culture and organization, products and services, and ecosystem.

Four discourses emerge from the results, representing the respondents' views on the CE. The first discourse considers CE as business strategy applicable to products and services, the second a corporate mission and the fourth an operational efficiency strategy. Finally, the third discourse views CE as a multidimensional concept.

This study contributes to the scientific and institutional debate on how to accelerate the aquaculture's circular transition. First and foremost, it offers insights to guide policy makers in the development of appropriate knowledge and information systems. Second, it offers the opportunity to improve training programmes to enable current students to be prepared for the future challenges.

The results reflect a different perceived knowledge of CE among future operators, whose opinions are little explored in the literature.

By increasing the digitalization of commercial services citizens' expect more from public services. First of all, this study will strive to identify which problems citizens encounter when they use a complex public service: preparation of an application for a building permit. In the light of the popularity of omnichannel approaches, the study then explores how omni-channel could help to address the problems which have been identified.

We implement the first phases of an action design science research project. We collect data both from citizens and public agencies and frame them as transparency problems. These abstract problems are then addressed by an omnichannel service provision as an abstract solution. The abstract solution is then instantiated in a design in the form of a user scenario developed in collaboration with current and future public officials.

The analysis uncovers multiple transparency issues: it distinguishes between process, case, language, cross-channel and cost transparency. One root cause of the transparency issues observed is the lack of service transparency which defines the purpose and scope of a ser-vice. We therefore recommend defining a service-strategy before informational and technical aspects of an omnichannel approach can be implemented. Following this strategy, omnichannel offers public administrations unique opportunities to excel in citizens' service provision.

The study provides insights into how citizens view complex public services. For researchers, this study offers the conceptualization as transparency issues. Practitioners from the public administrations can also benefit from the concept and vision of omnichannel public services.

Organizational technologies can be classified according to the roles they play as either commodity or strategic. Commodity technologies support common operations, while strategic technologies address perceived threats to competitiveness, often identified by strategic foresight. These must go through an adoption process before playing an effective role in strategy execution. The adoption process includes known activities, ranging from sourcing (itself from in-house development to turn-key acquisition) to operational integration. This paper aims to reveal strategic technology adoption risks that arise during strategy execution.

A gradually developed causal loop diagram model, supported by general literature, introduces three general classes of technology adoption risks: mismatched requirements, supplier dependence and unmanaged life cycles.

Rather than managed, these risks are incurred or avoided depending on decisions made during the adoption process.

Despite the scarce literature coverage for the approach, examples revealing the presence of adoption risks are nevertheless available in the well-documented history of enterprise resource planning (ERP).

Although ERP is presented as a general-purpose strategic technology, the unique business features of maritime container terminals pose serious challenges to its adoption, which provides additional support to the discussion and reinforces the conclusions.

The approach to identifying risks in strategic technology adoption departs from the current risk paradigm in two significant ways. First, it emphasizes policy decision-making rather than external events. Second, it views risks as systemic rather than occurring independently.

The purpose of this paper is to systematically review the history and current state of lesson study (LS) in Germany. In particular, this paper describes the development of LS over time and its stakeholders.

Conducting a systematic literature review, we searched three scientific databases and Google Scholar, examined 806 results and included 50 articles in our final sample, which we analyzed systematically.

The spread of LS in Germany can be divided into three phases, characterized by their own LS projects as well as their own ways of understanding LS. Although interest in LS has increased significantly in recent years, it is only present at a small number of schools and universities in Germany if compared internationally. Furthermore, this paper identifies the so-called learning activity curves as a tool frequently used for observation and reflection that appears to be unknown outside German-speaking countries.

This paper may act as an outline for countries without large-scale LS projects and with limited support from policymakers. The experience from Germany demonstrates the outcomes and challenges that can arise in such a situation and shows how unique LS features and proceedings have emerged.

Design-based research (DBR) involves multiple iterations, and innovations are needed in analytical methods for understanding how learners experience a learning experience in ways that both embrace the complexity of learning and allow for data-driven changes to the design of the learning experience between iterations. The purpose of this paper is to propose a method of crafting design moves in DBR using network analysis.

This paper introduces learning experience network analysis (LENA) to allow researchers to investigate the multiple interdependencies between aspects of learner experiences, and to craft design moves that leverage the relationships between struggles, what worked and experiences aligned with principles from theory.

The use of network analysis is a promising method of crafting data-driven design changes between iterations in DBR. The LENA process developed by the authors may serve as inspiration for other researchers to develop even more powerful methodological innovations.

LENA may provide design-based researchers with a new approach to analyzing learner experiences and crafting data-driven design moves in a way that honors the complexity of learning.

LENA may provide novice design-based researchers with a structured and easy-to-use method of crafting design moves informed by patterns emergent in the data.

To the best of the authors’ knowledge, this paper is the first to propose a method for using network analysis of qualitative learning experience data for DBR.