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Strategic alliances are an important option for small and medium-sized enterprises (SMEs) when obtaining knowledge and information. Although existing studies suggest that entrepreneurial competencies (ECs) enable SMEs to form alliances and achieve alliance success, they overlook the role played by external knowledge absorption and mutual trust. Our study was thus aimed to address this issue by exploring and understanding the relationship between ECs and alliance success. The analysis of survey data drawn from 246 UK manufacturing SMEs suggests that the absorption of external knowledge mediates the relationship between ECs and alliance success. Moreover, mutual trust enhances the strength of the relationship between ECs and external knowledge absorption. By drawing on the relational view, our study contributes to the strategic alliance and SMEs literatures and supports a moderated mediation mechanism.

The pandemic COVID 19 has altered individuals' daily lives across the globe. It has led to preventive measures such as physical distancing to be imposed on individuals and led to terms such as 'lockdown,' 'emergency,' or curfew' to emerge in various countries. It has affected society, not only physically and financially, but in terms of emotional wellbeing as well. This distress in the human emotional quotient results from multiple factors such as financial implications, family member's behavior and support, country-specific lockdown protocols, media influence, or fear of the pandemic. For efficient pandemic management, there is a need to understand the emotional variations among individuals, as this will provide insights into public sentiment towards various government pandemic management policies. From our investigations, it was found that individuals have increasingly used different microblogging platforms such as Twitter to remain connected and express their feelings and concerns during the pandemic. However, research in the area of expressed emotional wellbeing during COVID 19 is still growing, which motivated this team to form the aim: To identify, explore and understand globally the emotions expressed during the earlier months of the pandemic COVID 19 by utilizing Deep Learning and Natural language Processing (NLP). For the data collection, over 2 million tweets during February-June 2020 were collected and analyzed using an advanced deep learning technique of Transfer Learning and Robustly Optimized BERT Pretraining Approach (RoBERTa). A Reddit-based standard Emotion Dataset by Crowdflower was utilized for transfer learning. Using RoBERTa and the collated Twitter dataset, a multi-class emotion classifier system was formed. With the implemented methodology, a tweet classification accuracy of 80.33% and an average MCC score of 0.78 was achieved, improving the existing AI-based emotion classification methods. This study explains the novel application of the Roberta model during the pandemic that provided insights into changing emotional wellbeing over time of various citizens worldwide. It also offers novelty for data mining and analytics during this challenging, pandemic era. These insights can be beneficial for formulating effective pandemic management strategies and devising a novel, predictive strategy for the emotional well-being of an entire country's citizens when facing future unexpected exogenous shocks.

This paper aims to explore and understand the digital divide in older adults when accepting and using smart devices within an organization. Using an in-depth single case study, the digital divide is explored and understood using technology-mediated learning for older adults when using smart devices; ie. tablet devices. The case study is based on a group of educated, older Indian adult volunteers at a local Punjabi radio station. A qualitative approach used the data collection techniques of interviews, observations, informal conversations and reference to archival documents and interpretivism for analysis. Our findings revealed that older adults with ailments have shorter lives, contrary to popular perception, can be very active in their communities, are able to use basic IT and are willing to use technology when it leads to significant tangible or intangible benefits without considering the remaining time of their lives. Contributions for policymakers and industry are also offered in this paper.