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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.

Sarcasm is a linguistic expression that usually carries the opposite meaning of what is being said by words, thus making it difficult for machines to discover the actual meaning. It is mainly distinguished by the inflection with which it is spoken, with an undercurrent of irony, and is largely dependent on context, which makes it a difficult task for computational analysis. Moreover, sarcasm expresses negative sentiments using positive words, allowing it to easily confuse sentiment analysis models. This paper aims to demonstrate the task of sarcasm detection using the approach of machine and deep learning.

For the purpose of sarcasm detection, machine and deep learning models were used on a data set consisting of 1.3 million social media comments, including both sarcastic and non-sarcastic comments. The data set was pre-processed using natural language processing methods, and additional features were extracted and analysed. Several machine learning models, including logistic regression, ridge regression, linear support vector and support vector machines, along with two deep learning models based on bidirectional long short-term memory and one bidirectional encoder representations from transformers (BERT)-based model, were implemented, evaluated and compared.

The performance of machine and deep learning models was compared in the task of sarcasm detection, and possible ways of improvement were discussed. Deep learning models showed more promise, performance-wise, for this type of task. Specifically, a state-of-the-art model in natural language processing, namely, BERT-based model, outperformed other machine and deep learning models.

This study compared the performance of the various machine and deep learning models in the task of sarcasm detection using the data set of 1.3 million comments from social media.

Considering the potential of Collaborative International Online Learning (COIL) for cross-boundaries interacting and collaborating effectively, this study aims to explore the intercultural awareness of pre-service language teachers after participating in a COIL project.

Following a quantitative research approach and an exploratory cross-sectional method, the authors administered a 13-item questionnaire to unveil the perceptions of 64 future language teachers from Spain after their online experience with counterparts from the USA.

Participants consider that COIL may have enhanced their intercultural and global awareness and equipped them with valuable skills and knowledge for the future, being women more positive than men. Moreover, the results also suggest that those participants who have not traveled abroad consider COIL to be a good opportunity to compensate for the lack of knowledge or experience with other cultures resulting from not having had the opportunity to visit other countries.

COIL needs to be seen as a powerful tool to promote global learning, intercultural understanding and the development of skills among students that will be vital for success in today’s interconnected world. Nevertheless, universities and teacher training centers need to rethink the preparation of future teachers for the increasing demands to prepare students for the requirements of the global world, and to do so, they need to consider that COIL may offer them significant benefits.

This work offers an interesting exploration of teachers’ attitudes toward COIL, providing insights into the potential of online collaboration for developing intercultural awareness.

The purpose of this paper is to present a framework of ideation pathways that organically extend the current stock of knowledge to generate new and useful knowledge. Although detailed, granular guidance is available in the strategy literature on all aspects of empirically testing theory, the other key aspect of theory development – theory generation – remains relatively neglected. The framework developed in this paper addresses this gap by proposing pathways for how new theory can be generated.

Grounded in two foundational principles in epistemology, the Genetic Argument and the open-endedness of knowledge, I offer a framework of distinct pathways that systematically lead to the creation of new knowledge.

Existing knowledge can be deepened (through introspection), broadened (through leverage) and rejuvenated (through innovation). These ideation pathways can unlock the vast, hidden potential of current knowledge in strategy.

The novelty and doability of the framework can potentially inspire research on a broad, community-wide basis, engaging PhD students and management faculty, improving knowledge, democratizing scholarship and deepening the societal footprint of strategy research.

Knowledge is open-ended. The more we know, the more we appreciate how much we don’t know. But the lack of clear guidance on rigorous pathways along which new knowledge that advances both theory and practice can be created from prior knowledge has stymied strategy research. The paper’s framework systematically pulls together for the first time the disparate elements of transforming past learning into new knowledge in a coherent epistemological whole.

The involvement of clients in service encounters and service development has become a central principle for contemporary health and social care organizations. However, in day-to-day work settings, the shift toward client involvement is still in progress. We examined how health and social care professionals, together with clients and managers, co-develop their conceptions of client involvement and search for practical ways in which to implement these in organizational service processes.

The empirical case of this study was a developmental intervention, the client involvement workshop, conducted in a Finnish municipal social and welfare center. The cultural-historical activity theory (CHAT) framework was used to analyze the development of client involvement ideas and the modes of interaction during the intervention.

Analysis of the collective discussion revealed that the conceptions of client involvement developed through two interconnected object-orientations: Enabling client involvement in service encounters and promoting client involvement in the service system. The predominant mode of interaction in the collective discussion was that of “coordination.” The clients' perspective and contributions were central aspects in the turning points from coordination to cooperation; professionals crossed organizational boundaries, and together with clients, constructed a new client involvement-based object. This suggests that client participation plays an important role in the development of services.

The CHAT-based examination of the modes of interaction clarifies the potential of co-developing client-involvement-based services and highlights the importance of clients' participation in co-development.

Environmental tourism impacts are considered to be unbalanced. The implementation of environmental sustainability focuses on restoring a balance through environmentally responsible behavior. As Generation Z was found in recent studies to exhibit divergent levels of environmentally responsible behavior compared to other generations, but also to have intra-generational differences, this study aims to explore the underlying reasons and explanations behind their attitudes and behavioral attempts.

Four focus group discussions with young people belonging to Generation Z allow to probe deep into their environmental sustainability orientation.

The results of this study demonstrate that Generation Z’s environmental attitude is triggered by social pressure, social media, as well as by the COVID-19 pandemic. For their touristic behavioral intention, they concentrate predominantly on climate-friendly travel and on-site mobility, waste avoidance as well as emphasizing economic and social sustainability. By furthermore highlighting Generation Z’s responsibility ascription to the supply and the demand side, in addition to illustrating the demand for framework conditions to be created from governments and destinations, the knowledge scope on environmental sustainability is expanded.

In particular, this study enriches environmentally responsible behavior research by incorporating the perspective of Generation Z, while it deepens Generation Z’s behavioral understanding. Furthermore, the results of this study allow to derive implications for tourism policymakers.

环境旅游影响被认为是不平衡的。环境可持续性的实施侧重于通过对环境负责的行为来恢复平衡。由于最近的研究发现Z一代与其他几代人相比表现出不同的环境责任行为水平, 且存在代际差异, 本研究探讨了他们的态度和行为尝试背后的潜在原因和解释。

采用四个焦点小组与Z世代年轻人讨论, 深入探究他们的环境可持续性导向。

这项研究的结果表明, Z世代的环境态度是由社会压力、社交媒体以及COVID-19大流行引发的。对于他们的旅游行为意向, 他们主要关注气候友好型旅行和现场移动性, 避免浪费以及强调经济和社会的可持续性。通过进一步强调Z世代对供给侧和需求侧的责任归因, 并阐释政府和目的地对框架条件的需求, 扩大了环境可持续性的知识范围。

特别地, 本研究通过纳入Z世代的视角, 丰富了环境责任行为研究, 加深了Z世代的行为理解。此外, 本研究的结果可以为旅游政策制定者提供启示。

Los impactos medioambientales del turismo se consideran desequilibrados. La implementación de la sostenibilidad medioambiental se centra en restablecer el equilibrio mediante un comportamiento responsable con el medio ambiente. Estudios recientes señalan que la Generación Z muestra niveles divergentes de comportamiento responsable con el medio ambiente en comparación con otras generaciones, pero también presenta diferencias intra-generacionales. Este estudio explora las razones y explicaciones subyacentes a sus actitudes e intenciones de comportamiento.

Cuatro grupos de discusión con jóvenes de la Generación Z permiten profundizar en su orientación hacia la sostenibilidad medioambiental.

Los resultados de este estudio evidencian que la actitud medioambiental de la Generación Z está provocada por la presión social, medios sociales, así como por la pandemia del COVID-19. En cuanto a su intención de comportamiento turístico, se concentran predominantemente en los viajes respetuosos con el clima y la movilidad in situ, evitar residuos, así como en hacer hincapié en la sostenibilidad económica y social. Al destacar la responsabilidad que la Generación Z atribuye a la oferta y la demanda, además de inculcar la demanda para la creación de condiciones marco por parte de gobiernos y destinos, se amplía el alcance del conocimiento sobre la sostenibilidad medioambiental.

En particular, este estudio enriquece la investigación sobre el comportamiento responsable con el medio ambiente al incorporar la perspectiva de la Generación Z y profundizar en la comprensión del comportamiento de esta generación. Asimismo, los resultados de este estudio permiten desarrollar implicaciones para los responsables de las políticas turísticas.

This paper aims to identify the effect of environmental management systems (EMSs), commitment to stakeholders and gender diversity on corporate environmental performance (CEP) and the extent to which an economic crisis moderates these relationships.

A regression analysis was conducted on a sample of 14,217 observations from 1,933 firms from 26 countries from 2002 to 2010. The estimator used is ordinary least squares with heteroscedastic panel-corrected standard errors (PCSEs), which allows us to obtain consistent results in the presence of heteroscedasticity and autocorrelation.

The results show that EMSs and stakeholder engagement are mechanisms that drive CEP but lose their effectiveness in times of crisis. However, the presence of women on boards has a positive effect on CEP that is not affected by an economic crisis.

The study has some limitations that could be addressed in the future. We present board gender diversity as a governance mechanism because its role is strongly related to non-financial performance. Future studies could focus on other corporate governance mechanisms, such as the presence of institutional or long-term investors. In addition, other mechanisms could be found that can counteract poor environmental performance in times of crisis. Finally, it might be useful to contrast these results with the crisis generated by the coronavirus pandemic.

The results obtained have important practical implications at the corporate and institutional levels. At the corporate level, they highlight, as essential contributions, that environmental management systems and stakeholder orientation are not effective in times of economic crisis, except for with the presence of women on the board.

Following the crisis, the European Commission has promoted gender diversity on boards as a mechanism to improve the governance of entities – improving, among other aspects, sustainability. In this sense, another one of the practical implications of the study is support for the policies that the European Union has implemented over the last two decades.

The paper analyses how a crisis affects the moral and cultural institutional mechanisms that promote CEP. Gender diversity on the board of directors not only promotes environmental performance but also appears to be a governance mechanism that ensures this performance in times of crisis when the other mechanisms lose their effectiveness. The study proposes specific policies that help maintain environmental performance in an economic crisis.

Responding to calls for deeper analysis of the conceptual foundations of service infusion in manufacturing, this paper examines the underlying assumptions that: (i) manufacturing firms incorporating services follow a pathway, moving from pure-product to pure-service offerings, and (ii) profits increase linearly with this process. We propose that these assumptions are inconsistent with the premises of behavioural and learning theories.

Machine learning algorithms are applied to test whether a successive process, from a basic to a more advanced offering, creates optimal performance. The data were gathered through two surveys administered to USA manufacturing firms in 2021 and 2023. The first included a training sample comprising 225 firms, whilst the second encompassed a testing sample of 105 firms.

Analysis shows that following the base-intermediate-advanced services pathway is not the best predictor of optimal performance. Developing advanced services and then later adding less complex offerings supports better performance.

Manufacturing firms follow heterogeneous pathways in their service development journey. Non-servitised firms need to carefully consider their contextual conditions when selecting their initial service offering. Starting with a single service offering appears to be a superior strategy over providing multiple services.

The machine learning approach is novel to the field and captures the key conditions for manufacturers to successfully servitise. Insight is derived from the adoption and implementation year datasets for 17 types of services described in previous qualitative studies. The methods proposed can be extended to assess other process-based models in related management fields (e.g., sand cone).

Entrepreneurs are generally considered to be committed in order to strive for highly desirable goals, such as growth or commercial success. However, commitment is a multidimensional concept and may have asymmetric relationships with positive or negative entrepreneurial outcomes. This paper aims to provide a nuanced perspective to show under what conditions commitment may be detrimental for entrepreneurs and lead to overinvestment.

Using a sample of entrepreneurs from incubators in France (N = 437), this study employs a configurational perspective, fuzzy-set qualitative comparative analysis (fsQCA), to identify which commitment profiles lead entrepreneurs to overinvest different resources in their entrepreneurial projects.

The paper exposes combinations of conditions that lead to overinvestment and identifies five different commitment profiles: an “Affective profile”, a “Project committed profile”, a “Profession committed profile”, an “Instrumental profile”, and an “Affective project profile”.

The results show that affective commitment is a necessary condition for entrepreneurs to conduct overinvesting behaviors. This complements previous linear research on the interdependence between affect and commitment in fostering detrimental outcomes for nascent entrepreneurs.

The authors investigate the impact of the stringency of environmental policy on the financial performance of European automobile manufacturers. This paper contributes to the debate about the impact of environmental policy on a firm's competitive performance.

The authors use cross-country sector-level panel data for 71 firms from 18 European countries from 2010 to 2019. The authors apply a fixed-effect model and then, to address the endogeneity issues, the authors use the generalized method of moments (GMM) model. To further examine the validity of the results, the authors use a data-mining modeling approach as a robustness test.

By considering the dynamic impact of environmental policy and overcoming the endogeneity issues, the results show that the impact of the stringency of environmental policy on a firm's financial performance depends on the time horizon: the stringency of environmental policy has a short-term negative impact but a long-term positive impact on a firm's financial performance.

The authors limited the study to the auto industry in Europe. In addition, future research could consider the impact of environmental policy on other financial performance indicators such as Return on Sales or Return on Equity. Also, it would be interesting to conduct a similar study in the United States or China using a firm-level data set to examine the robustness of the results.

Stringency of environmental policy improves a firm's financial performance in the long term. It is essential for firms and managers to consider the dynamic impacts of environmental policy on their financial performance and adopt a long-term perspective when evaluating the costs and benefits of complying with environmental regulations. The findings help management develop a long-term vision for investment and budget allocation. The results support management's view for strategic decision-making against the common budget argument and challenges for stockholders when it comes to adopting new technologies and planning long-term investment.

It is crucial for firms to recognize the broader societal benefits that come with environmental policy. Firms must not only focus on their financial performance but also on their social responsibility to protect the environment and contribute to the greater good. Therefore, firms must take a long-term perspective and recognize the broader societal benefits of environmental policy in order to make informed decisions that support both their financial success and their social responsibility.

This paper contributes to the literature by helping to explain the inconsistent results of studies about the impact of environmental policy on a firm's competitiveness. Using a firm's financial performance as one of the main metrics for competitiveness, this study takes into account both endogeneity and contemporaneity in evaluating the impact of the stringency of environmental policy on a firm's financial performance.