2020
Autores
Sun, SL; Li, TT; Ma, H; Li, RYM; Gouliamos, K; Zheng, JM; Han, Y; Manta, O; Comite, U; Barros, T; Duarte, N; Yue, XG;
Publicação
SUSTAINABILITY
Abstract
This paper investigated the impact of employee quality on corporate social responsibility (CSR). Based on data from China A-share-listed companies for the years 2012-2016 and using ordinary least squares, our empirical results show that the educational level of the workforce, as a proxy for employee quality, is positively associated with CSR, which suggests that higher education can promote CSR implementation. Additional analyses found that this positive relationship is more pronounced in non-state-owned enterprises, enterprises in regions with lower marketisation processes, and firms with lower proportions of independent directors. This study extends the literature on human capital at the level of firms' entire workforce and CSR by elaborating the positive effect of employee quality on CSR in the context of an emerging economy (China). The results suggest that it is necessary to consider the educational level of employees when analysing CSR, which is of strategic significance for corporate sustainable development.
2020
Autores
Shtul, A; Baquero, C; Almeida, PS;
Publicação
CoRR
Abstract
2020
Autores
Muhammad, SH; Brazdil, P; Jorge, A;
Publicação
ECIR (2)
Abstract
Sentiment lexicon plays a vital role in lexicon-based sentiment analysis. The lexicon-based method is often preferred because it leads to more explainable answers in comparison with many machine learning-based methods. But, semantic orientation of a word depends on its domain. Hence, a general-purpose sentiment lexicon may gives sub-optimal performance compare with a domain-specific lexicon. However, it is challenging to manually generate a domain-specific sentiment lexicon for each domain. Still, it is impractical to generate complete sentiment lexicon for a domain from a single corpus. To this end, we propose an approach to automatically generate a domain-specific sentiment lexicon using a vector model enriched by weights. Importantly, we propose an incremental approach for updating an existing lexicon to either the same domain or different domain (domain-adaptation). Finally, we discuss how to incorporate sentiment lexicons information in neural models (word embedding) for better performance.
2020
Autores
Oliveira, BMPM; Ozturk, ME; Poinhos, R; Afonso, C; Ayhan, NY; de Almeida, MDV;
Publicação
PROCEEDINGS OF THE NUTRITION SOCIETY
Abstract
2020
Autores
Are, M; Santos, E; Oliveira, BMPM; Correia, F; Poínhos, R;
Publicação
PROCEEDINGS OF THE NUTRITION SOCIETY
Abstract
2020
Autores
Pato, ML; Teixeira, AAC;
Publicação
EUROPEAN PLANNING STUDIES
Abstract
The literature focusing on rural and urban entrepreneurship has so far overlooked the conditions in which different institutional contexts can affect firms' performance. The present study addressed this gap by investigating the extent to which institutional factors impact distinctively the performance of rural and urban newly created ventures. Based on data gathered through a direct questionnaire, we obtained 408 responses from newly created ventures located in Portuguese business incubators and science parks. Resorting to econometric binary (logit) models, we found that certain institutional factors, namely EU policy support, financial support from other sources than not banks, business advice for starting up/ ongoing activities, and collaboration to access new markets, are critical for new venture export performance, particularly those located in rural settings. To a larger extent than for urban, rural new venture economic-related performance positive and significantly depend on central government policy support, close relatives' role models, and technological support at the R&D collaboration level. Given the relevance of embeddedness-related factors in rural municipalities, public authorities should follow strategies that involve a growing connection between rural entrepreneurs and a variety of actors from industry, academia and the public and private sectors in order to foster newly created venture performance.
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