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This study's main objective is to examine the effect of learning from entrepreneurial failure on performance, with a type of failure as a moderator variable. Interactions between internal and external causes of failure and learning from entrepreneurial failure are also investigated, as well as entrepreneurs' aspects (i.e. age, experience and education) and organisational contextual factors (i.e. size, sector and location).

This study employed a hypothetico-deductive approach through a survey of 250 purposively sampled entrepreneurs who had suffered business failures. The survey data were subjected to regression analysis and moderated regression using WarpPLS software and an independent sample t test for an in-depth analysis.

The results indicated that learning from entrepreneurial failure positively affected business performance, an effect moderated by the type of failure, particularly with large failures. Only perceived internal causes of failure exerted a positive effect on learning from entrepreneurial failure; the external causes did not. The effect of failure on business performance was stronger on entrepreneurs who were older and experienced, had non-university educations and operated small- and medium-sized enterprises (SMEs) outside Java–Bali islands.

This study's findings provide empirical evidence that supports the experiential learning theory and attribution theory in explaining the interaction between learning and failure, its cause, its consequences and its magnitude as perceived by entrepreneurs of SMEs in Indonesia, where the rate of failure is relatively high. The authors’ study also emphasises the roles of the entrepreneur and organisational contextual factors, which matter in learning to improve performance.

The purpose of this research study is to empirically investigate the Figma prototyping technology adoption factors among entrepreneurship and innovation libraries for providing support to startups by developing and evolving the prototype solutions in collaboration with health libraries.

This study uses the technology adoption model (TAM) as a framework and the partial least squares structural equation modeling (PLS-SEM) method of structural equation modeling (SEM) using SmartPLS 3.2.9 software version to investigate the prototyping adoption factors among entrepreneurship and innovation libraries for rural health innovations. A total of 40 libraries, spread over 16 entrepreneurship and innovation libraries, participated in this survey, including participants from Europe (35%), Asia (15%) and USA (50%).

The findings show that previous experience, social impact, brand image and system quality have a significant positive impact on entrepreneurship and innovation libraries' perceived usefulness (PU) of prototyping technology. Perceived ease of use of prototype technology is positively influenced by usability, training materials and documentation, experience and self-efficacy. Together, perceived usefulness and perceived ease of use have a significant influence on behavioural intention. Behavioural intention is positively impacted by minimal investment and shallow learning curve. Technology adoption is furthered by behavioural intention. The control variables, for instance location, gender and work experience (as librarian), were found not having any impact on Figma technology adoption.

Through strategic partnerships with other libraries (including health libraries), policymakers, and technology providers, the adoption of prototype technology can be further accelerated. The important ramifications for policymakers, technology providers, public and entrepreneurship and innovation libraries to create a self-reliant innovation ecosystem to foster rural health innovation based on entrepreneurship are also listed in the article.

This research is distinctive since it integrates several areas of study, including entre, advances in rural healthcare and libraries. A novel idea that hasn't been thoroughly investigated is the collaboration between entrepreneurship and innovation libraries and health libraries for supporting businesses. This study offers insights into the factors that drive technology adoption and offers practical advice for policymakers and technology providers. It also advances understanding of the adoption of Figma prototyping technology among libraries for rural health innovation. Overall, this study provides a novel viewpoint on the nexus between different disciplines, showing the opportunity for cooperation and innovation in favour of rural health.

This study aims to evaluate the effectiveness of different prefabricated construction (PC) policies using a case study in Wuhan, considering the local context.

The effectiveness of PC policies is falling behind expectations. The main reason lies in an insufficient understanding of the policy impacts. An agent-based model was built by choosing the residential sector in a typical large city of Wuhan, China, as the study case. Different cost reduction scenarios were introduced for investigating the PC policy effectiveness. The proposed model and simulation approach can be used for other cities and generalized to the whole Chinese PC industry with the potential to include more local policies and corresponding data.

Simulation results show that carbon emission reduction will be between 60,000 and 80,000 tons with policy incentives, nearly double that of the no policy intervention scenario. The target of 30% PC in all new buildings by 2026 in China is achievable with the subsidy policies of linear cost reduction, or cost reduction conforms to the learning curve.

Simulation results of three kinds of policy show that subsidy policy optimization is necessary regarding reducing the level of subsidy needed. The carbon credit policy is not essential since it has little influence on PC development. Implementing the project procurement restriction policy is not recommended if the scale of development of PC is more important than achieving the development target.

This study can help the government and developers make better policy and strategic decisions on PC development and boost the sustainability transition of the construction industry.

The purpose of this paper is to apply systems modeling to explore the usability of the online learning platform in the future compared to its usefulness during the pandemic era.

The applied systems research methodology has been used to develop a stock-flow model encompassing enablers and constraints for learning platform usage from the primary data collected through a survey of 163 respondents.

The model simulation observed promising trends over one year for online learning platforms provided the challenges are reduced in seven to eight months. Challenges linked to the Internet and interaction need must be removed for future usage.

The results of the survey and model simulation suggest actions for product planning and development of online learning platforms based on customer insights. Product customization and feature enhancement will be required for the continued usability of online learning products. Actions for Internet service providers are to capture the online learner market by removing issues of Internet access bandwidth, and quality of content. Also, there should be sufficient teacher–student interaction in the online learning mode.

This is an original study using systems modeling to evaluate factors contributing to students' intention to use online learning conducted at Dayalbagh Educational Institute (Deemed to be University) Dayalbagh Agra, UP, India, 282005.

This study aims to empirically analyze the significance of various knowledge management (KM) elements to the environment in a military organization and establish the efficacy of performance indicators of civil organizations for a military organization.

The research methodology includes the development of a research model based on a comprehensive literature review. A sample of 454 Indian Air Force Veterans was obtained and structural equation modeling (SEM) analysis using statistical package for the social sciences (SPSS) analysis of moment structures (AMOS) was conducted to test the hypotheses. The study first employed exploratory factor analysis (EFA) for redefining the theoretical constructs and then confirmatory factor analysis (CFA) to test the hypotheses.

The study empirically establishes the significance of various KM elements on the knowledge environment that creates, stores, transfers and applies knowledge to achieve military objectives. Findings indicate the complexity of KM in a military setup while applying the performance measures used in the civil organization.

The study expects to expand the scope of the KM literature to the militaries of developing countries and provide a methodology to the leaders and practitioners in the military organizations, and to study the available KM practices, models and tools in the civil world.

To the best of the authors’ knowledge, the present research is one of the first to generate empirical insights into a knowledge environment in military organizations and test its relation with parameters used in civil organizations. The paper would significantly contribute to the underexplored area of KM in military organizations and infuse a theoretical rigor into the KM literature.

This study aimed to examine the similarities and differences between the ability to analyze the environment and exploit new knowledge (absorptive capacity) and the skills to generate value from innovation (appropriation). These fields have similar origins and are sometimes confused by practitioners and academics.

A review was conducted based on a full-text analysis of 681 and 431 papers on appropriation and absorptive capacity, respectively, from Scopus, Science Direct and Lens, using methodologies such as text mining, backward citation analysis, modularity clustering and latent Dirichlet allocation analysis.

In business disciplines, the fields are considered different; however, in other disciplines, it was found that some authors defined them quite similarly. The citation analysis results showed that appropriation was more relevant to absorptive capacity, or vice versa. From the dimension perspective, it was found that although appropriation was considered a relevant element for absorptive capacity, the last models did not include it. Finally, it was found that studies on both topics identified the importance of appropriation and absorptive capacity for innovation performance, knowledge management and technology transfer.

This is one of the first studies to examine in-depth the relationship between appropriation and absorptive capacity, bridging a gap in both fields.

The use of structured literature review methods like bibliometric analysis is growing in the management fields, but there is limited knowledge on how they can be facilitated by technology. Hence, we conducted a broad overview of software tools, their roles, and limitations in structured (bibliometric) literature reviewing activities. Subsequently, we show that several software tools are freely available to aid in searching the literature, identifying/ extracting relevant publications, screening/assessing quality of the extracted data, and performing analyses to generate insights from the literature. However, their applications may be confronted with several challenges such as limited analytical and functional capabilities, inadequate technological skills of researchers, and the fact that the researcher's insights are still needed to generate compelling conclusions from the results produced by software tools. Consequently, we contribute toward advancing the methodologies for performing structured reviews by providing a comprehensive and updated overview of the knowledge base of key technological software tools and the conduct of structured or bibliometric literature reviews.

This paper aims to examine the effect of R&D laboratories on the perceived performance of MNE subsidiaries during recession.

Employing resource-based view and knowledge-based theory, the authors investigate a unique sample of 171 technologically heterogenous foreign MNE subsidiaries located in Greece over the period of recession 2009–2016. The sample subsidiaries operate different types of R&D laboratories.

The authors find that MNE subsidiaries with advanced R&D laboratories such as locally integrated laboratories (LILs) and internationally interdependent laboratories (IILs) perform better in recession than subsidiaries with support laboratories (SLs) or subsidiaries without R&D laboratories. Overall, the authors find an asymmetric performance contribution of R&D laboratories at subsidiary level.

The study provides useful insights into the environmentally derived “knowledge-based - performance” context, so filling an important research gap, since little is known about the performance impact of the input-side of technological activity at MNE subsidiary level, especially as regards R&D facilities/infrastructure. Based on the findings the authors identify important managerial implications.

The purpose of this paper is to investigate and quantify the impact of product complexity, including architectural complexity, on operator learning, productivity and quality performance in both assembly and disassembly operations. This topic has not been extensively investigated in previous research.

An extensive experimental campaign involving 84 operators was conducted to repeatedly assemble and disassemble six different products of varying complexity to construct productivity and quality learning curves. Data from the experiment were analysed using statistical methods.

The human learning factor of productivity increases superlinearly with the increasing architectural complexity of products, i.e. from centralised to distributed architectures, both in assembly and disassembly, regardless of the level of overall product complexity. On the other hand, the human learning factor of quality performance decreases superlinearly as the architectural complexity of products increases. The intrinsic characteristics of product architecture are the reasons for this difference in learning factor.

The results of the study suggest that considering product complexity, particularly architectural complexity, in the design and planning of manufacturing processes can optimise operator learning, productivity and quality performance, and inform decisions about improving manufacturing operations.

While previous research has focussed on the effects of complexity on process time and defect generation, this study is amongst the first to investigate and quantify the effects of product complexity, including architectural complexity, on operator learning using an extensive experimental campaign.