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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.

Aboriginal and Torres Strait Islander (Aboriginal) people are overrepresented in Australian prisons, where they experience complex health needs. A model of care was designed to respond to the broad needs of the Aboriginal prisoner population within the nine adult prisons across South Australia. The purpose of this paper is to describe the methods and findings of the Model of Care for Aboriginal and Torres Strait Islander Prisoner Health and Wellbeing for South Australia.

The project used a qualitative mixed-method approach, including a rapid review of relevant literature, stakeholder consultations and key stakeholder workshop. The project was overseen by a Stakeholder Reference Group, which met monthly to ensure that the specific needs of project partners, stakeholders and Aboriginal communities were appropriately incorporated into the planning and management of the project and to facilitate access to relevant information and key informants.

The model of care for Aboriginal prisoner health and wellbeing is designed to be holistic, person-centred and underpinned by the provision of culturally appropriate care. It recognises that Aboriginal prisoners are members of communities both inside and outside of prison. It notes the unique needs of remanded and sentenced prisoners and differing needs by gender.

Supporting the health and wellbeing of Indigenous prison populations can improve health outcomes, community health and reduce recidivism.

Only one other model of care for Aboriginal prisoner health exists in Australia, an Aboriginal Community Controlled Health Organisation-initiated in-reach model of care in one prison in one jurisdiction. The South Australian model of care presents principles that are applicable across all jurisdictions and provides a framework that could be adapted to support Indigenous peoples in diverse prison settings.

This study aims to provide a systemic and integrated view of how Industry 4.0 and its enabling technologies affect companies' internal and external environments. It offers a comprehensive view of the contribution about ten years after the start of the Fourth Industrial Revolution.

The study performs a systematic literature review based on Industry 4.0 management literature. Analyzing the results of the 308 final papers in the sample made it possible to build a theoretical model to explain the contribution of Industry 4.0 to the internal and external environment of the company.

The results highlight the contribution of Industry 4.0 to the processes and environment of the company by providing a systemic and integrated view, highlighting the most applied enabling technologies and their internal, external, and combined usefulness in business processes.

Finally, the paper provides a broad view of the Industry 4.0 topic ten years after its origin through an extensive literature analysis that allows us to highlight the significant studies and the areas still under-researched by researchers and opens the debate on the Industry 5.0 scenario.

The model makes it possible to appreciate the role of Industry 4.0 and its enabling technologies in companies in a broad and systemic view and to understand, from a managerial point of view, the interactions, synergies, and possibilities within processes and the reflection on the external environment.

Supervisor incivility and organizational gossip are two examples of dark organizational behaviors. Norm of reciprocity theory suggests that employees may develop revenge intentions after exposure to such behaviors while attributing blame to others. This study aims to empirically investigate the mediating effect of blaming others on the impact of supervisor incivility and negative organizational gossip on revenge intention.

Confirmatory factor analysis (CFA) was performed to test the measurement model. Structural equation model was used to test the research hypotheses based on data gathered in Turkey from restaurant employees in Mersin Marina selected by convenience sampling. Data set that consists of 239 questionnaires was subjected to CFA.

The findings show that negative organizational gossip and supervisor incivility increase to employees’ revenge intentions, and blaming others mediates the impact of supervisor incivility and negative organizational gossip no employees’ revenge intentions. In addition, blaming others mediates the impact of supervisor incivility and negative organizational gossip on employees’ revenge intentions.

Empirical study has not been encountered related to dark behaviors of (especially gossip, incivility, blame and revenge intention) restaurant managers and employees as a holistic model. Therefore, this paper contributes to organizational behavior literature. Moreover, this paper suggests to restaurant managers for supply to organizational peace.

The world of work is constantly changing. The COVID-19 pandemic has reinforced working from home, and there is an increasing demand for flexibility regarding the workplace. There is little empirical evidence on the mechanisms and factors that influence employee outcomes, such as productivity and turnover intention, at the workplace and at home. In addition, it is unclear whether the workplace characteristics that influence employee outcomes vary between different nations due to country-specific circumstances. The paper aims to address these two issues.

The research model applied in this study is based on the job demands-resources (JD-R) and environmental demands-resources models using German (n = 429) and USA (n = 507) survey samples. Partial least squares structural equation modelling is used to analyse the influence of workplace characteristics (isolation, family–work interference, equipment/facilities and skill variety) on employee outcomes (satisfaction, burnout, productivity and turnover intention). Additionally, a multi-group analysis is used to explore group differences in the factors influencing satisfaction, burnout, productivity and turnover intention between employees in Germany and the USA.

The results reveal that significant determinants of productivity and turnover intention include isolation, family–work interference, equipment/facilities and skill variety. Isolation and equipment/facilities are identified as the most important demands and resources of the home workplace. Some significant differences are found between Germany and the USA. The positive effect of isolation on burnout is significantly stronger in the USA than in Germany, whereas the positive effect of family–work inference on burnout is stronger in Germany than in the USA. The negative effects visible for the relations between burnout and satisfaction, and satisfaction and turnover intention are stronger in Germany than in the USA. The positive effect of burnout on turnover intention is stronger in the USA compared to Germany.

The study adds empirical evidence to the JD-R theory by analysing the influence of the home workplace characteristics on employee outcomes in different countries for the first time using a multi-group analysis. In addition, the study reveals new insights into the differences between the knowledge workforces in Germany and the USA by uncovering how key factors influence employee outcomes such as productivity and turnover intention, partially carried by varying length of experience in work from home between both of these countries. Insights from this study can support corporate real estate managers to make better decisions on the design of employees’ home workplaces and the integration of work from home into the company’s workspace concept.

Effective customer journey design (ECJD) is considered a key variable in customer experience management and an essential source of brand meaning and pro-brand behavior. Although previous research has confirmed its importance for driving brand attitudes and loyalty, the role of consumer-brand identification as a social identity-based influence in this relationship has not yet been discussed. Drawing on construal level and social identity theories, this paper aims to investigate whether effective journeys and the resulting overall journey experience are equally powerful in driving brand loyalty among customers with different levels of consumer-brand identification.

The present article develops and tests a research model using data from the European and US service sectors (N = 1,454) to investigate how and when ECJD affects service brand loyalty.

Across two cultural contexts, four service industries and 33 service brands, the results reveal that ECJD is a crucial driver of service brand loyalty for customers with low consumer-brand identification. Moreover, the findings show that different aspects of journey effectiveness positively impact the valence of customers’ experience related to those journeys – a process that is ultimately decisive for their brand loyalty.

This study is unique because it generates theoretical and practical knowledge by combining the literature streams of customer journey design, customer experience and branding. Furthermore, this work demonstrates that consumer-brand identification is a critical boundary condition to be considered in the relationship between ECJD and brand loyalty in services.

Considering food waste as a global problem resulting from the wastage of valuable resources that could fulfil the requirements of malnourished people, the current research focusses on understanding consumerism’s impact on this phenomenon. Additionally, the circular economy (CE) approach can be critical in reducing food waste and promoting sustainability.

A systematic literature review was conducted using bibliometrics and network analysis. The study reviewed 326 articles within 10 years, from 2013 to 2023.

The findings reveal four prominent factors – behavioural, environmental, socioeconomic and technological – in managing food waste (FW). Reducing FW at a holistic level can benefit individuals and the environment in several ways.

Consumers are encouraged to be more responsible for their food consumption by reducing food waste, as it affects societies and businesses both economically and environmentally. This can help promote a responsible consumption culture that values quality over quantity and encourages people to make more informed choices about what they eat and how they dispose of it post-consumption. All stakeholders, including firms, the government and consumers, must examine the motives behind inculcating pro-environmental behaviour.

Addressing consumerism and the ability to decrease FW behaviour are complex issues that require a multidimensional approach. This study seeks to fill the gap in understanding consumerism and the capacity to reduce FW using the CE approach and understand the research gaps and future research trends.

Drawing on the cognitive–affective–conative framework, this study aims to develop a model of service robot acceptance in the hospitality sector by incorporating both cognitive evaluations and affective responses.

A mixed-method approach combining qualitative and quantitative methods was used to develop measurement and test research hypotheses.

The results show that five cognitive evaluations (i.e. cuteness, coolness, courtesy, utility and autonomy) significantly influence consumers’ positive affect, leading to customer acceptance intention. Four cognitive evaluations (cuteness, interactivity, courtesy and utility) significantly influence consumers’ negative affect, which in turn positively affects consumer acceptance intention.

This study provides significant implications for the design and implementation of service robots in the hospitality and tourism sector.

Different from traditional technology acceptance models, this study proposed a model based on the hierarchical relationships of cognition, affect and conation to enhance knowledge about human–robot interactions.

Scholars and practitioners acknowledge that digital leadership can help organizations gain a competitive advantage. This article focuses on the characteristics, styles and skills needed for effective digital leadership. It looks at the role of digital leaders in innovating business models and introducing organizational change required for a successful digital transformation.

This paper is based on a comprehensive literature review of digital transformation, digital leadership, business model innovation, and organizational culture. It draws on institutional theory (INT) the neo-institutional theory (NIT). It draws from Science Direct, Web of Science and Google Scholar publications. A proposition and a conceptual framework are developed based on evaluating and synthesizing the literature.

We find that specific leader characteristics (agility, participative, innovativeness and openness), styles (democratic and transformational) and skills (cognitive, social, technological and digital) enable successful business model innovation and organizational change, all of which allow successful digital transformation of firms.

The literature on digital transformation has not been well integrated with the leadership literature. This is particularly true in terms of the role digital leaders play in the successful digital transformation of firms. The conceptual framework and a way forward proposed in this paper introduce future research directions on the topic.

The paper aims to explore the roles and impact of design in incubating and accelerating social enterprises. It aims to understand design’s influence on social enterprise ecosystems and in improving outcomes for social enterprises.

The study used an exploratory, qualitative approach, using case studies and interviews. The comparative case-study methodology was applied to evaluate the influence of design on the development of social enterprises in the UK and South Korea and identify critical issues in their utilisation of design. Empirical data included: in-depth case studies of design utilisation practices (UK = 6; South Korea = 15) and design applications (UK = 2; South Korea = 2) for the growth of social enterprise and its ecosystem; 27 social enterprise/design experts (UK = 17; South Korea = 10); and 22 social enterprises (UK = 12; South Korea = 10). Content and thematic analysis were used to synthesise the findings.

Findings demonstrate the differing influences of design on social enterprise, from improving products/services and business models to enhancing social enterprise ecosystem support and networks. Future directions are suggested for applying design for social enterprise growth, business stage development and systematising interactions between the social enterprise and design sectors.

The research is based on case studies from only two countries. Further, the adoption of working definitions of social enterprise in the countries may result in the research underestimating the heterogeneity of social enterprise.

The findings contribute to optimising efficient ecosystem development to improve social enterprise competitiveness and innovation.

This paper establishes a research foundation on design for social enterprise, offering theoretical and practical insights into its impact on growth.