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Within the framework of EU policies and measures to develop a just and fair green energy transition model. This paper aims to offer valuable insights into a paramount concern not so well debated in the literature, i.e. the spatial variation of energy poverty.

This empirical analysis investigates the regional variation of energy poverty we draw on a sample of more than 300,000 Spanish households, extracted from the Spanish Household Budget Survey (HBS) for the period 2006–2022. To characterize the probability of a household finding itself in a situation of energy poverty the authors use a discrete choice univariate probit model.

The results confirm that energy poverty is a phenomenon that is asymmetrically distributed across Spain, and mainly occurs in un-densely populated regions. In addition, the findings demonstrate that the incidence of energy poverty drivers is highly heterogeneous across regions.

The paper ends with some recommendations for policymakers suggesting that countries need to design an energy poverty policy for the households that jointly pursue both a correct identification of vulnerable groups and a match with the type of measure to the characteristics of each region.

This study enhances previous research by considering the case of areas at a lower level of aggregation (i.e. on the NUTS two regions in Spain called autonomous communities) and offers the opportunity to tailor policies to those regions most in need. Furthermore, to provide a more realistic picture of the complex phenomenon of energy poverty, the authors use the information for the period 2006–2022 differentiating by economic micro-cycle. This timespan allows the authors to understand the dynamics of energy poverty in periods of economic crisis, including the effects of the 2008 crisis and the present global energy crisis.

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.

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.

The existing literature has examined the determinants of post-purchase behavioral intentions. However, less attention has been devoted to the factors that contribute to perceived usefulness of fast-food restaurants attributes. The current study considers the servicescapes and social servicescapes of restaurants as well as their relationship with customers' perceived usefulness, with the moderating role of customer experience. It also explores how perceived usefulness influences choice process satisfaction and subsequent behavioral responses, including revisit intention and negative word-of-mouth.

Data from 485 fast-food restaurant consumers in Pakistan were collected using purposive sampling. The data were analyzed using both structural equation modeling (SEM) through AMOS 24.0 and the PROCESS macro in IBM SPSS 27.0.

The research revealed that perceived usefulness in fast-food restaurant industry is positively influenced by servicescapes and social servicescapes. Similarly, choice process satisfaction is primarily caused by perceived usefulness and affects behavioral responses. It also found that choice process satisfaction is positively associated with revisit intentions and negative word-of-mouth. Customer experience significantly moderates the relationship between ambient condition, facility aesthetic, layout, perceived similarity and perceived usefulness. However, customer experience insignificant moderates the relationships of physical appearance and suitable behavior with perceived usefulness.

The findings provide insightful information for both academic and managerial fields, contributing to the literature on consumer psychology, consumer behavior, servicescapes and the stimulus-organism-response theory. The study also assists restauranteurs in the fast-food restaurant industry in overcoming the challenges posed by a highly competitive environment and developing strategies based on consumer perceptions.

This study, conducted in Pakistan, took a pioneer step in testing and confirming a novel perceived usefulness model that incorporates not only servicescapes but also social servicescapes in consumer behavior. It enhances the knowledge of consumer visit intentions by quantifying the significance of perceived usefulness developed by different servicescapes.

The purpose of this study is to examine the extent to which using accounting as a multidimensional practice that encompasses technical, social and moral dimensions facilitates the instigation and advancement of a culture of sustainable development.

A qualitative approach was used to analyse the case of Waratah Coal Pty Ltd vs Youth Verdict Ltd – a dispute over a lease to establish a coal mine. The study draws on Carnegie et al.’s (2021a, 2021b) multidimensional definition of accounting and the Carnegie et al.’s (2023) framework for analysis to explore how different parties drew on accounting concepts to support their position over the sustainability of the mining lease proposal.

A multidimensional perspective on accounting appears to have clear transformative potential and can be used to champion a culture of sustainable development. This approach also has broad societal, environmental and moral implications that transcend Western financial metrics. This study shows that relying solely on accounting as a technical practice to pursue economic benefits can result in contested arguments. Overall, this analysis illustrates how the wider public, and notably First Nations communities, might challenge accounting methodologies that marginalise cultural and social narratives.

This paper expands accounting research by demonstrating how fully embracing accounting’s capacities can create a space for hearing multiple voices, including those silenced by Western accounting practices. Specifically, this study presents a unique case in which the authors incorporate the voices and views of those affected by accounting-based decisions.

Recent scholarship has called for researchers to recognize the urgency of place-based education as a critical component of social studies pedagogy. This study seeks to understand better the relationship between place-based education, sacrificial listening and difficult history.

In this qualitative, arts-based research study, collaging is used to investigate how students use the theory of sacrificial listening while trying to make sense of difficult histories during a place-based history education experience. Students enrolled in a PBE experience received instruction about the theory of sacrificial listening at the beginning of a two-week course on the lasting impact of the civil rights movement. Students created a collage and responded to a reflection prompt about the course after engaging in course experiences, including travel to Oklahoma, Arkansas, Tennessee and Alabama.

Findings in the study demonstrate how sacrificial listening appeared, both explicitly and implicitly, in the ways students processed difficult history during a place-based education experience. Ultimately, the study found, though students organized their thoughts in distinct ways, they all leaned on the theory of sacrificial listening to make sense of what they learned.

Few studies have applied the theory of sacrificial listening as a pedagogical framework. Future research should build on this work, further investigating the theory as a pedagogical framework in conjunction with both place-based history education as well as other instructional settings.

There is little to no empirical research on the phenomenon of ways in which the racism of whiteness transpires within the faculties and classrooms of US-based ALA-accredited library and information science (LIS) education programs. We do have scholars publishing meaningful work exploring diversity-equity-inclusion topics and initiatives to evolve the LIS discourse on these issues (Honma, 2005; Chancellor, 2019; De LaRosa et al., 2021; Gibson, 2019; Mehra et al., 2023; Colón-Aguirre et al., 2022; Hands, 2022). This research substantiates the conceptual research that exists by empirically exposing the ways in which the racism of whiteness functions at the interpersonal level of work culture in LIS programs (i.e. the academy) in the US.

Adapting Baima and Sude’s (2020) modified Delphi Method, a focus group of 13 BIPOC (Black, Indigenous, and People of Color) library and information science faculty members in the United States were recruited to participate in a one-time 60-min virtual Zoom session. Participants were engaged in three iterative rounds of reflective inquiry to reach a consensus of experience. The study design was embedded with critical race theory-based (CRT) ethnographic methods such as testimony (counterstorytelling), collective affirmation (shared narratives), and silence.

BIPOC LIS faculty (tenure-track and tenured) have similar ideas about whiteness and how it is operationalized as micro- and macro-aggressions in the LIS academic workplace, most significantly inside the classroom. The experience of whiteness was prevalent among all study participants in two areas: workplace meetings with faculty colleagues and classroom sessions (face-to-face and online) with students.

The findings offer empirical evidence to support the prolific conceptual literature in LIS discourse concerning ways in which critical race theory (CRT) interrogates LIS’s socio-professional injustices and inequities (e.g. Gibson et al., 2018; Stauffer, 2020; Leung and Lopez-McKnight, 2021; Jennings and Kinzer, 2022; Snow and Dunbar, 2022). There remains a dearth of empirical research that reports how whiteness is reproduced in the practices, knowledge, and resources that make up the ethos of the LIS faculty meeting and classroom. Documenting the testimonies of BIPOC LIS faculty solidifies the existence of whiteness as a toxic reality in the LIS academy.

This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?

A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.

The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.

The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.

The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?

This study aims to provide a series of drivers that prompt the blockchain technology (BT) adoption decisions in circular supply chain finance (SCF) and also assesses their degrees of influence and interrelationships, which leads to the construction of a theoretical model depicting the influence mechanism of BT adoption decisions in circular SCF.

This study mainly uses the technology-organization-environment (TOE) framework, which focuses on the aspects based on the nature of innovation, intra-organizational characteristics and extra environmental consideration, to identify the drivers of blockchain adoption in circular SCF context, while the significance and causality of the drivers are explained using interpreting structural models (ISMs) and the decision-making trial and evaluation laboratory (DEMATEL) method.

The findings of this study indicate that government policy and technological comparative advantage are the underlying reasons for BT adoption decisions, management commitment and financial expectations are the critical drivers of BT adoption decisions while other factors are the receivers of the mechanism.

This study provides theoretical references and empirical insights that influence the technology adoption decisions of both BT and circular SCF by practitioners.

The theoretical research contributes significantly to current research and knowledge in both BT and circular SCF fields, especially by extending the existing TOE model by combining relevant enablers from technological, organizational and external environmental aspects with the financial performance objectives of circular SCF services, which refer to the optimization of the financial resources flows and financing efficiency.

This paper aims to examine the effects of the 2014 European regulatory reform on auditors’ activity, the audit outcome and the audit market, with a focus on the Spanish market.

The research is based on in-depth, semistructured interviews with partners of the main audit firms operating in the Spanish market. This qualitative approach provides a precise identification of the cause-effect relationships of the new measures introduced by the European audit regulation.

The findings indicate that, based on auditors’ opinions, the costs of the main regulatory changes outweigh the benefits. The European Union (EU) Audit Regulation imposes more demanding provisions, such as an extended auditor’s report, mandatory audit firm rotation, more banned nonaudit services and stricter quality controls, resulting in substantial side effects on audit activity and the audit market. This could undermine the objective of enhancing the quality of audit services.

To the best of the authors’ knowledge, this is the first study to analyze the effect of the 2014 EU regulatory reform on audit activity, audit market and audit outcome based on auditors’ perceptions. The findings may be of interest to academics, professionals and regulators alike, as they offer valuable insights for assessing the effectiveness of the new audit provisions. Additionally, the qualitative methodology used facilitates a causal analysis of the key elements introduced by the regulations, potentially paving the way for future research avenues.