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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.

Is there a secret recipe for economic growth?

No, there is no recipe, but we can extrapolate some pieces of advice from Adam Smith.

An economy can leave behind its “dull” stagnant state and grow when its markets expand, when the productivity of its workers increases thanks to high compensations, which are seen as incentives to work harder and when lobbying and cronyism are kept at bay. Luck plays a role too, but these three ingredients are necessary, even if not sufficient, for an economy to grow and thus be “cheerful.”

These three aspects – expansion of market, liberal compensation of workers and lobbying – especially combined, have often been underestimated in Smith’s understanding of the possible sources of economic growth.

The purpose of this study is to contribute with knowledge about how valid research data in biodiversity citizen science are produced through information practices and how notions of credibility and authority emerge from these practices.

Data were collected through an empirical, interview-based study of the information practices of 15 participants active in the vicinity of the Swedish biodiversity citizen science information system Artportalen. Interview transcripts were analysed abductively and qualitatively through a coding scheme by working back and forth between theory and data. Values of credibility, authority and validity of research data were unfolded through a practice-oriented perspective to library and information studies by utilising the theoretical lens of boundary objects.

Notions of credibility, authority and validity emerge through participant activities of transforming species observations to data, supplementing reports with objects of trust, augmenting identification through authority outreach and assessing credibility via peer monitoring. Credibility, authority and validity of research data are shown to be co-constructed in a distributed fashion by the participants and the information system.

The article extends knowledge about information practices in emerging, heterogeneous scholarly settings by focussing on the complex co-construction of credibility, authority and validity in relation to data production.

Supply chain (SC) professionals and their competence play a key role in creating value and competitive advantage for companies. A considerable amount of this competence is developed at work, but little is known about how this takes place. Drawing on constructivist learning theory, the authors investigate how SC professionals develop their competence at work.

The study takes off from a theoretical framework of workplace learning mechanisms, followed by a series of in-depth interviews with an expertise panel of profoundly competent and experienced SC professionals.

The results provide detailed insights into the learning process of SC professionals. The key findings show that SC professionals use a wide range of learning mechanisms throughout their careers, and that the contribution and complexity of these mechanisms differ and change dynamically with seniority. The findings also show that learning mechanisms should not be viewed as isolated phenomena, but closely related to every-day SCM work as well as learning attitude.

By conceptualizing learning as a process, and congregating the fragmented literature into a framework of workplace learning mechanisms, this research provides a theoretical reference point for future studies. The empirical findings bring a new level of detailed knowledge on how SC professionals learn at work.

The results can assist SC professionals, HR managers and academic program leaders in their quest to develop competence in the field of SCM.

This paper makes a unique contribution to the human aspects of SCM literature by presenting the first study that investigates in depth the crucial but complex process of how workplace learning takes place for SC professionals in practice.

This study aims to enhance merging of additive manufacturing (AM) techniques with powder injection molding (PIM). In this way, the prototypes could be 3D-printed and mass production implemented using PIM. Thus, the surface properties and mechanical performance of parts produced using powder/polymer binder feedstocks [material extrusion (MEX) and PIM] were investigated and compared with powder manufacturing based on direct metal laser sintering (DMLS).

PIM parts were manufactured from 17-4PH stainless steel PIM-quality powder and powder intended for powder bed fusion compounded with a recently developed environmentally benign binder. Rheological data obtained at the relevant temperatures were used to set up the process parameters of injection molding. The tensile and yield strengths as well as the strain at break were determined for PIM sintered parts and compared to those produced using MEX and DMLS. Surface properties were evaluated through a 3D scanner and analyzed with advanced statistical tools.

Advanced statistical analyses of the surface properties showed the proximity between the surfaces created via PIM and MEX. The tensile and yield strengths, as well as the strain at break, suggested that DMLS provides sintered samples with the highest strength and ductility; however, PIM parts made from environmentally benign feedstock may successfully compete with this manufacturing route.

This study addresses the issues connected to the merging of two environmentally efficient processing routes. The literature survey included has shown that there is so far no study comparing AM and PIM techniques systematically on the fixed part shape and dimensions using advanced statistical tools to derive the proximity of the investigated processing routes.

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.

The article takes its point of departure in the current labor market debate on immigration policy and attempts to explore the way private labor market mediators involved in the integration of immigrants contribute to reproducing cultural stereotypes reminiscent of colonial ideas.

Findings are based on respondent-driven interviews with nine labor market mediators (seven women and three men) from eight private labor market agencies in Sweden.

The findings showed that the private labor market mediators put their trust in the neoliberal system and rely on the colonial discourses when convincing immigrants to assimilate into the dominant culture. At the same time, the findings also show that there is no evidence that the assimilating activities they offer will lead to long-term employment.

Given that migration across national borders has become a common phenomenon, the author suggests a call for critical reflections on the taken-for-granted notions of both self and others and the influences colonial discourses have on integration.

The author would suggest a shift of focus from immigrants' cultural adjustment to society's and employers' responsibilities and readiness to adjust to prevailing conditions.

The study contributes to the labor market literature and the diversity management literature by adding insights from public labor market mediators' experiences of the help they offer immigrants to enter the labor market. It shows how mediators make use of dominating discourses to secure cultural hegemony.

Within education, the online forum is becoming a preferred mode of study across the globe and the COVID-19 era highlights its importance. Research around online education has concentrated on the USA and Europe, and this study sought to redress the Western bias by exploring and comparing the perceptions of six post-graduate East-African students and lecturers at Pan Africa Christian University in Kenya on learning leadership online versus on-campus. It is debatable whether leaders are born or made; however, post-industrial theories embrace the concept that leadership is teachable. Semi-structured interviews were conducted, recorded, transcribed and thematically analysed, using a top-down approach, from a critical realist perspective. The results show that participants’ leadership ideals synthesised Afrocentric perspectives of communality, with Western ideals of transformational and servant leadership. Furthermore, there are differences between perceptions of East- African students and lecturers on online leadership learning. Students preferred the online avatar experience, whilst lecturers preferred on-campus or blended methods of leadership studies. Face-to-face connection was deemed important by students and lecturers but impeded by the inability to see facial reactions using the current online platform. This exploratory study gives insight into an East-African experience and sends a clear message to Kenyan institutions to invest further in video technology. Future research could include a longitudinal study of destinations and successes of Kenyan University online leadership alumni. The impact of the global coronavirus pandemic, with lockdowns and social distancing, further underlines the importance of ongoing online leadership research and education across the world.

This interview with Adam Bryant and Kevin Sharer, the authors of “The CEO Test: Mastering the Challenges that Make or Break All Leaders,” examines the relationship between the leaders and followers and the key challenges that tend to determine leadership success or failure.

The authors told S&L’s interviewer Brian Leavy: “We focus specifically on leading others - illuminating seven of the most common make-or-break challenges, and then showing how to navigate them effectively.”

The authors' research found that “It’s the leader’s job to capture the essence of what matters and then be able to boil down the strategy to just a handful of memorable ideas so that everyone understands, remembers and knows how to contribute to its success.”

Leaders have to learn that listening is a multidimensional practice that requires commitment and constant attention, and the aim is to get a true sense of the nature of their organization and its dynamics.

Much of the on-going outpouring of leadership literature tends to focus on the personal qualities and characteristics of the individual leader. Less studied are the dynamics of the relationship between the leader and the led, or the nature and content of the role itself and the key tasks associated with it. One exception is "The CEO Test: Mastering the Challenges that Make or Break All Leaders" by Adam Bryant and Kevin Sharer. Their "overarching framework to mastering the inner game of leadership is to embrace it as a series of paradoxes,” is an original perspective.