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In repetitive projects, repetition offers more possibilities for activity scheduling at the sub-activity level. However, existing resource-constrained repetitive scheduling problem (RCRSP) models assume that there is only one sequence in performing the sub-activities of each activity, resulting in an inefficient resource allocation. This paper proposes a novel repetitive scheduling model for solving RCRSP with soft logic.

In this paper, a constraint programming model is developed to solve the RCRSP using soft logic, aiming at the possible relationship between parallel execution, orderly execution or partial parallel and partial orderly execution of different sub activities of the same activity in repetitive projects. The proposed model integrated crew assignment strategies and allowed continuous or fragmented execution.

When solving RCRSP, it is necessary to take soft logic into account. If managers only consider the fixed logic between sub-activities, they are likely to develop a delayed schedule. The practicality and effectiveness of the model were verified by a housing project based on eight different scenarios. The results showed that the constraint programming model outperformed its equivalent mathematical model in terms of solving speed and solution quality.

Available studies assume a fixed logic between sub-activities of the same activity in repetitive projects. However, there is no fixed construction sequence between sub-activities for some projects, e.g. hotel renovation projects. Therefore, this paper considers the soft logic relationship between sub-activities and investigates how to make the objective optimal without violating the resource availability constraint.

This work aims to analyze the factors that influence the performance and efficiency of Portuguese companies, namely the influence of social and environmental features.

To achieve our aim, we have used the Portuguese benchmark index, the Portuguese stock index – PSI, during the period from 2016 to 2020. To test the hypothesis panel data methodology was used, specifically, the GMM system originally proposed by Arellano and Bond (1991) and the Value-Based DEA developed by Gouveia et al. (2008).

The results of the GMM model show that social performance has a negative relationship with the company’s performance, from the perspective of different stakeholders, reinforcing that the cost-benefit trade-off of social spending is not yet understood as advantageous for the company’s performance. On the other hand, environmental performance, for external stakeholders, positively influences the company’s performance, perhaps due to pressure from society and the tradition of disclosing environmental matters. The value-based DEA results reinforce that from the perspective of the external stakeholder, non-efficient companies must increase their environmental performance to become efficient, highlighting the role of environmental performance in explaining efficiency. It is unanimous that social performance is still not seen as a lever of efficiency.

This is the first work to use a hybrid methodology to understand the performance determinants of a small banking-oriented country, emphasizing environmental and social aspects.

This paper aims to examine the impact of bank managerial ability on the cost of loans using an extensive data set of US banks from 2001:Q1 to 2021:Q2.

First, the authors use multiple fixed-effects estimation to estimate the impact of managerial ability on bank loan pricing. In addition, the authors also perform different econometrics regression methods to test the robustness of the model including: Prais–Winsten regression, Newey–West regression and the Fama McBeth method, instrumental variable regression, propensity score matching method and quantile regression.

The results show that banks with higher managerial ability tend to provide loans with lower costs, and this effect is stronger at larger banks. In addition, research results from the quantile regression model show that the negative impact of managerial ability on the cost of loans will be stronger at banks with higher lending costs.

To the best of the authors’ knowledge, this study is one of the first to investigate this relationship between managerial ability and bank loan pricing from the supply side. In addition, this paper examines the impact of bank managerial ability on the loan costs of banks of different sizes, as well as differs across the distribution of the dependent variable. Therefore, this paper is of particular interest to regulators and policymakers.

The paper examines the effect of language negativity of US financial analysts’ ancestral origins on their earnings forecast behavior.

The paper first developed a dictionary of the most emotionally negative words in 25 languages, based on the study by Dodds et al. (2015). The authors constructed firm-year analyst-level earnings forecast data and applied multivariate regression model along with a series of robustness tests to examine the research question.

The empirical results indicate that financial analysts with their ancestral countries characterized by a high level of language negativity tend to issue less optimistic earnings forecasts than other analysts. Additional evidence suggests that the effect of language negativity on analysts’ forecast is strengthened (1) during periods of financial crisis, (2) for firms with losses and a high level of earnings volatility and (3) for younger analysts and analysts working for small brokerage firms. Finally, we find evidence that higher levels of language negativity increase analysts’ forecast accuracy.

Collectively, the findings of this study support the conjecture that the level of negativity across languages can have a significant impact on capital market participants’ behavior. Thus, the study sheds light on how culturally inherited emotion can affect analysts’ earnings forecast properties.