The answer to the challenging question, “Should one either invest in tangible resources or intangible resources/capabilities?” is still fragmented. In prior studies, more emphasis is given to tangible resources, while intangible resources have comparatively received minor attention, despite their significant role in the success of small and medium enterprises (SMEs). Particularly the role of the intangible skills; intellectual capital, financial literacy (FL), and business experience (BE) in resource acquisition and sustainable competitive performance has missed in prior studies. Grounded on the resource-based view and upper echelon theory, this study examines the role of intellectual capital in sustainable competitive performance with a mediating role of resource acquisition. This research also assesses the moderating role of financial literacy and business experience between intellectual capital and resource acquisition. Data are collected through structured questionnaires from 384 owners/managers of Pakistani SMEs. After analyzing the data through structural equation modeling (SEM), the results indicate that intellectual capital helps managers in acquiring valuable resources, which in turn enhance sustainable competitive performance. Resource acquisition partially mediates the relation between intellectual capital and sustainable competitive performance. Financial literacy is a significant predictor of resource acquisition, but it does not significantly moderate the relation between intellectual capital and sustainable competitive performance. Business experience significantly boosts the acquisition of resources and strengthens the path between intellectual capital and resource acquisition. SMEs should encourage their managers to acquire unique, rare, and immutable external resources in the turbulent markets.

Carbon trading as a vital tool to reduce carbon dioxide emissions has developed rapidly in recent years. Reasonable prediction of the carbon price can improve the risk management in the carbon trading market and make healthy development of the carbon trading market. This paper aims to enhance the predictive performance of carbon price in the China‘s carbon markets, especially the China’s national carbon market, by adding the online news sentiment index which is a kind of unconstructed data, to a deep learning model using traditionally constructed predictors innovatively. Long Short Term Memory (LSTM) network was applied as the primary model to predict carbon price and Random Forest as the additional experiment to validate the effectiveness of online news sentiment. The results in the China’s national carbon market and Hubei pilot carbon market both proved that the model including the sentiment index performed better than the model does not, and the improvement was significant.

Carbon trading as a vital tool to reduce carbon dioxide emissions has developed rapidly in recent years. Reasonable prediction of the carbon price can improve the risk management in the carbon trading market and make healthy development of the carbon trading market. This paper aims to enhance the predictive performance of carbon price in the China’s carbon markets, especially the China’s national carbon market, by adding the online news sentiment index which is a kind of unconstructed data, to a deep learning model using traditionally constructed predictors innovatively. Long short–term memory (LSTM) network was applied as the primary model to predict carbon price and random forest as the additional experiment to validate the effectiveness of online news sentiment. The results in the China’s national carbon market and Hubei pilot carbon market both proved that the model including the sentiment index performed better than the model does not, and the improvement was significant.

As starting university is a critical independence milestone for many young people, it would also be the best time to provide them with some financial education (FE). Although there have been many initiatives aimed at enhancing individual financial literacy (FL) and/or financial decision-making, meta-analyses have shown that the effectiveness of FE has been mixed. This study examined the driving forces behind the decision by college students to enroll in a targeted financial literacy curriculum (FLC) and the impact of this attendance on their FL. An endogenous switching model (ESM) was employed to account for the heterogeneity in the decision to attend or not attend the FLC and to counteract any unobservable characteristics. It was found that students with higher self-perceived FL did not prefer to attend the FLC; however, for others, FLC attendance was found to significantly boost their FL in areas such as financial knowledge (FK), financial attitude (FA), and financial behavior (FB), especially for the non-attendees under the counterfactual framework. These “non-attendees” were observed to have some characteristics (e.g., prior knowledge) that made them more financially literate regardless of attendance; however, if they had attended the FLC, they would have gained a greater FL than the attendees. As the FL of the attendees would have been much lower if they had not attended, the FLC appeared to be particularly important for the attendees, which strengthened the case for making the FLC a compulsory part of a general college education.