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Factors like bid price, submission time, and number of bidders influence the procurement process in public projects. These factors and the award criteria may impact the project’s financial compliance. Predicting budget compliance in construction projects has been traditionally challenging, but Machine Learning (ML) techniques have revolutionised estimations.

In this study, Portuguese Public Procurement Data (PPPData) was utilised as the model’s input. Notably, this dataset exhibited a substantial imbalance in the target feature. To address this issue, the study evaluated three distinct data balancing techniques: oversampling, undersampling, and the SMOTE method. Next, a comprehensive feature selection process was conducted, leading to the testing of five different algorithms for forecasting budget compliance. Finally, a secondary test was conducted, refining the features to include only those elements that procurement technicians can modify while also considering the two most accurate predictors identified in the previous test.

The findings indicate that employing the SMOTE method on the scraped data can achieve a balanced dataset. Furthermore, the results demonstrate that the Adam ANN algorithm outperformed others, boasting a precision rate of 68.1%.

The model can aid procurement technicians during the tendering phase by using historical data and analogous projects to predict performance.

Although the study reveals that ML algorithms cannot accurately predict budget compliance using procurement data, they can still provide project owners with insights into the most suitable criteria, aiding decision-making. Further research should assess the model’s impact and capacity within the procurement workflow.

Previous research predominantly focused on forecasting budgets by leveraging data from the private construction execution phase. While some investigations incorporated procurement data, this study distinguishes itself by using an imbalanced dataset and anticipating compliance rather than predicting budgetary figures. The model predicts budget compliance by analysing qualitative and quantitative characteristics of public project contracts. The research paper explores various model architectures and data treatment techniques to develop a model to assist the Client in tender definition.

This study aims to examine the price and income elasticities of short- and long-run industrial electricity demand in Brazil between 2003 and 2020. The research also examines the impacts of COVID-19 in Brazil’s industrial electricity sector, including an analysis in states more and less industrialized.

Dynamic adjustments models in panel data are used to present robust estimates and analyze the impact of different methodologies on reported elasticities.

The short-run price elasticity is estimated at −0.448, while the long-run values are around −1.60. Regarding income elasticity, the value is 0.069 in the short-run and is concentrated in 0.25 in the long-run. The inelastic results of income show that the industrial demand for electric energy follows the trend of loss of competitiveness of the Brazilian industry in the past years. In addition, the price of natural gas, the level of employment, and, in specific cases, the level of imports also influence industrial electricity demand.

The research is a pioneer in the investigation of the industrial behavior of electricity of the Brazilian industrial branch, using as control variables, the average temperature, and the level of rainfall, this one, so important for a country whose main source is hydroelectric. In addition, to the best of the authors’ knowledge, it is the first study, which is prepared to analyze the effects of COVID-19 on electric consumption in the industrial sector, investigating these impacts, including in the states considered more and less industrialized. The estimates generated may help in the design of the Brazilian energy policy.

This research aims to identify whether leaders' affective organizational commitment influences employees' affective commitment to both the leader and the organization. Additionally, the study explores the role of employees' emotional awareness in shaping these relationships.

Examining a sample of 154 leaders and 249 employees in multinational companies, this study adopts a multilevel approach.

The results reveal a positive influence between the two foci of commitment (leaders and organization) at both the leader and employee levels. Furthermore, it confirms that employees' emotional awareness plays a positive role in the commitment process.

This research highlights the significance of implementing internal policies and measures that consider the various foci of commitment. To foster employees' commitment, it is crucial to establish a robust alignment between human resources management and leaders.

This study delves into the exploration of two commitment foci to deepen our comprehension of the directional relationship between them in the workplace. More specifically, our research scrutinizes the impact of leaders' affective organizational commitment on employees' affective commitment to the organization, while also analyzing its reciprocal influence on employees' affective commitment toward their leaders.

This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

This study empirically tests the use of loan loss provisions (LLPs) for earnings and capital smoothing when emphasis is laid on banks' riskiness and adoption of the International Financial Reporting Standards (IFRSs) in Nigeria.

Annual bank-level data are hand-extracted between 2007 and 2017 from annual reports of a sample 16 deposit money banks (DMBs), and analysed using appropriate panel regression models subsequent to a number of diagnostic tests including heteroscedasticity, autocorrelation and cross-sectional dependence. The use of both reported LLPs (TLLP) and discretionary LLPs (DLLP) for earnings and capital management is tested to advance the practice in the literature.

Generally, the study finds that Nigerian DMBs manage capital via LLPs, while mixed results are obtained for earnings smoothing. However, during IFRS, Nigerian DMBs' management of capital is identifiable with TLLP, while smoothing of earnings is peculiar to DLLP. Additionally, evidence of the improvement in loan loss reporting quality expected during IFRS for riskier Nigerian DMBs, could not be attained. This is corroborated by the study's findings of the use of both TLLP and DLLP for earnings and capital management during IFRS by DMBs in solvency crisis against the only use of TLLP to manage capital found for the entire period.

The evidential capital and earnings lopsidedness may subject Nigerian DMBs' going-concern to a lot of questions.

The study sets a foremost record in the empirical test of managerial opportunistic behaviour embedded in earnings and capital concurrently while accounting for loan losses by all categories of Nigerian DMBs in terms of riskiness, following accounting regime change.

Organisational slack has been widely considered in strategic management, but there is a gap in understanding the process of accumulation and application of slack resources. From a dynamic perspective and over an extended period of time, this paper analyses the management of slack resources and evaluates whether the different behaviours, in relation to the accumulation and consumption of slack resources, have any effect on performance.

The resource-based view and the dynamic extension of this theory, i.e. resource management and resource orchestration, were analysed in order to evaluate how slack resources can be managed and generate value. Assuming a configurational approach, the analysis was structured into two stages to answer the proposed hypothesis. The first stage studied whether there were different patterns of management of slack resources over time using the DistatisR package. The second stage evaluated which behaviours had the greatest impact in terms of profitability by using a dynamic panel data regression.

Three different types of slack resource management were found in companies: efficient, effective and erratic. Different types do not have the same impact on performance.

The dynamic management of slack resources has scarcely been considered, even during periods of crisis and economic expansion. This research advances the understanding of how firms transform slack resources into performance from a dynamic perspective.

The impact of dependence on self-care on people’s lives is very significant, with consequences for the person and their caregivers. The purpose of this study is to map the evidence on the factors that influence the empowerment of the person dependent on self-care on returning home.

Scoping review according to the criteria proposed by the Joanna Briggs Institute: population (people with a dependence on self-care), concept (factors that influence training) and context (return home after hospitalization in a medical-surgical context). The research was carried out from March 1 to April 30, 2022, in the databases CINAHL and MEDLINE (via EBSCO), Scielo, LILACS, Cuiden and MedicLatina; Gray literature searched RCAAP, DART-Europe and OpenGrey. Studies published in Portuguese, Spanish and English were included, with no time limit.

One hundred and eighty-one articles were obtained, which, after analysis according to the criteria, resulted in seven studies included for review, ranging from 2007 to 2021, with a level of evidence between 2. c and 4. a (according to Joanna Briggs Institute), and two thematic areas/four categories emerging.

The need for information and training, the relationship and proximity with the health-care team, the design of nursing care targeted at the person’s level of dependence, education, gender, type of surgical intervention and postoperative period, physical space and lack of privacy and audiovisual media.

The perception of these factors proves to be important in the person’s training process, with the nurse’s role being highlighted due to their emphasis on the transition home.

Businesses are increasingly called upon to support the improvement of society and the environment, and one way to do so is by expanding into international markets, particularly through exports. Despite the importance and recognised challenges of a global approach to sustainable value creation, sustainability research tends to focus on domestic contexts. This paper aims to identify the boundary conditions linking sustainable value creation practices with firm performance in the international context.

The authors merge the sustainable value creation and the international marketing literature to develop two propositions that capture the emerging nature of the field and the lack of concluding evidence regarding the link between international sustainable value creation practices and firm performance. The authors test these propositions empirically by analysing 519 responses to a survey of exporting firms in Portugal, using fuzzy-set qualitative comparative analysis.

The authors identify seven configurations that support sustainable value creation in an international context. These consist of varying levels of standardised and tailored offers, management experience and competitive intensity.

The identification of seven different configurations helps managers decide whether and how to innovate when pursuing sustainable value creation opportunities in international markets.

The authors propose that an effective way for governments to achieve national and transnational social and environmental agendas is to help businesses that pursue sustainable value creation to succeed in international markets. Given that four of the seven pathways to improve export performance that the authors identified require international management experience, the authors posit that an effective way to support the internationalisation of those businesses is through targeted training programmes and knowledge-sharing initiatives.

The authors respond to calls for research to integrate the sustainable value creation and the international marketing literatures, to identify how and when firms can create sustainable value creation in an international context and thus support the resolution of global, social and environmental problems. The finding that there are multiple configurations that support this goal explains why empirical evidence collected thus far is inconclusive and helps identify the boundary conditions of existing theory.

The paper has a twofold purpose: (1) to test the application of means-end theory to providers of hospitality goods and services, and (2) to explore this question in the context of winery tasting rooms when they had a unique opportunity to restructure their hospitality experience due to government restrictions in response to COVID.

A qualitative approach was adopted, and a convenience sample was used to conduct semi-structured laddering interviews. Forty interview transcripts were coded as means-end ladders, which were analyzed using a custom computer program to develop the implication matrix and the hierarchical value map.

This paper demonstrates that means-end is a useful approach to investigate the values and behaviors of the producer, specifically hospitality hosts. It finds that the principal goal of tasting rooms is to generate sales, and offering a compelling guest experience is the characteristic that contributes the most to achieving that goal. The staff and the atmosphere created for the guests are the two factors with the greatest influence on the guest experience.

This is the first paper to use means-end theory to study the hospitality host, or the producer of goods and services in general, and the first to study winery hospitality primarily through the lens of means-end theory. The study also helps fill a gap in research on tasting room sales focused on the winery’s goals.

In this vein, this paper aims to provide empirical evidence on the following questions: Which expansion strategies offer better operational and economic performance? What effects does performance-related diversification have? How do other factors such as size, quality, service offered, location or seasonality interact with performance.

In this paper, the analysis of the effects of growth strategies and hotel attributes on performance is carried out with a sample of 255 hotels that operate internationally. Using panel data and quantile regression, this study evaluates the effect of expansion and diversification on the hotels’ performance.

From these findings, it appears that the equity strategy (own hotels) outperforms non-equity strategies (hotels under rental, franchise and management contract) at the operational level. However, the economic return of the property, both adjusted and unadjusted to risk, is lower under the property ownership strategy than under the franchise and management strategies because, in general, it requires a higher investment. Regarding diversification, the growth strategy based on related diversification in food and beverage services has a negative impact on performance, calling into question the synergies between the two businesses. However, an exception to this effect is seen among those hotels, mainly those in the Caribbean, that opt to provide all-inclusive services, since these hotels achieve better occupancy rates and more stable results.

This study has not taken into account the effect of hotel property revaluation on the performance of the ownership strategy, as there is no information on the historical average revaluation at the level of each individual hotel. This study has also been unable to include information regarding the level of competition and seasonality of sales.

This paper considers a wide number of factors that can influence the performance of hotels. Second, this is the only paper that studies the impact of growth strategies from the point of view of the hotel chain. Also, the sample considered uses data at the individual level on hotels and this research analyses not only operational performance but also economic performance.