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This papers aims to study lattice structures in terms of geometric variables, manufacturing variables and material-based variants and their correlation with compressive behaviour for their application in a methodology for the design and development of personalized elastic therapeutic products.

Lattice samples were designed and manufactured using extrusion-based additive manufacturing technologies. Mechanical tests were carried out on lattice samples for elasticity characterization purposes. The relationships between sample stiffness and key geometric and manufacturing variables were subsequently used in the case study on the design of a pressure cushion model for validation purposes. Differentiated areas were established according to patient’s pressure map to subsequently make a correlation between the patient’s pressure needs and lattice samples stiffness.

A substantial and wide variation in lattice compressive behaviour was found depending on the key study variables. The proposed methodology made it possible to efficiently identify and adjust the pressure of the different areas of the product to adapt them to the elastic needs of the patient. In this sense, the characterization lattice samples turned out to provide an effective and flexible response to the pressure requirements.

This study provides a generalized foundation of lattice structural design and adjustable stiffness in application of pressure cushions, which can be equally applied to other designs with similar purposes. The relevance and contribution of this work lie in the proposed methodology for the design of personalized therapeutic products based on the use of individual lattice structures that function as independent customizable cells.

Amidst unpredictable and turbulent periods, such as the COVID-19 pandemic, service organization’s responses are required to be innovative, adaptable and resilient. The purpose of this study is to explore the utilization of both reconfiguration and transformational strategies as instruments for cultivating resilience and advancing sustainability in service organizations.

The study examines a proposed resilience model using fuzzy logic. The research also used a semantic differential scale to capture nuanced and intricate attitudes. Finally, to augment the validity of the resilience model, a measurement scale was formulated using business mathematics and expert opinions.

Although investing in resilience training can help organizations gain control and maintain their operations in times of crisis, it may not directly help service organizations understand the external turmoil, seek available resources or create adaptive remedies. Conversely, high levels of reconfiguration and transformation management vigour empower a service organization’s revolutionary, malleable vision, organizational structure and decision-making processes, welcoming talented and innovative employees to enhance capabilities during crises.

The resilience model bestows a comprehensive understanding of the pertinence of building resilience for service organizations identifying the antecedents that influence the adoption of these strategies and introduces a range of theoretical perspectives that empowers service organizations to conceptualize and plan for building resilience. The research guides service organizations to become more resilient to external shocks and adapt to changing circumstances by diversifying their offerings, optimizing their resources and adopting flexible work arrangements. The study elaborates on the enhancement of resilience, increasing innovation, improving efficiency and enhancing customer satisfaction for service organizations to remain competitive and contribute to positive social and economic outcomes through the adoption of both reconfiguration and transformational strategies.

The study also guides the service organizations to become more resilient to external shocks and adapt to changing circumstances by diversifying their offerings, optimizing their resources and adopting flexible work arrangements. Rapid innovation and business model innovation are essential components, enabling service organizations to foster a culture of innovation and remain competitive. In addition, the adoption can lead to improved financial performance, job creation and economic growth, contributing to positive social and economic impacts.

The resilience model bestows a comprehensive understanding of the pertinence of building resilience for service organizations. It identifies the antecedents that influence the adoption of these strategies and introduces a range of theoretical perspectives that empowers service organizations to conceptualize and plan for building resilience. The research also provides a foundation for further investigation into the effectiveness of these strategies and their impact on organizational performance and sustainability. By better preparing service organizations for disruptions and uncertainties, this research triggers ameliorated organizational performance and sustainability.

Within the realm of the service industry, the present investigation has undertaken the development, quantification and scrutiny of both resilience and tenacity. In addition, it has delved into the intricate dynamics surrounding the influencing factors and antecedents that bear upon resilience, elucidating their consequential impact on the operational performance and outlook of service-oriented organizations. The findings derived from this research furnish valuable insights germane to enhancing operational efficacy and surmounting impediments within the sector.

The extreme nature of fire makes structural fire engineering unique in that the load actions dictating design are intense and neither geographically nor seasonally bound. Simply, fire can break out anywhere, at any time and for any number of reasons. Despite the apparent need, the fire design of structures still relies on expensive fire tests, complex finite element simulations and outdated procedures with little room for innovation. This paper aims to discuss the aforementioned issues.

This primer highlights the latest state of the art in this area with regard to performance-based design in fire structural engineering. In addition, this short review also presents a series of examples of successful implementation of performance-based fire design of structures from around the world.

A comparison between global efforts clearly shows the advances put forth by European and Oceanian efforts as opposed to the rest of the world. In addition, it can be clearly seen that most performance-based fire designs are related to steel and composite structures.

In one study, this paper presents a concise and global view to performance-based fire design of structures from success stories from around the world.

This survey explores the application of real options theory to the field of health economics. The integration of options theory offers a valuable framework to address these challenges, providing insights into healthcare investments, policy analysis and patient care pathways.

This research employs the real options theory, a financial concept, to delve into health economics challenges. Through a systematic approach, three distinct models rooted in this theory are crafted and analyzed. Firstly, the study examines the value of investing in emerging health technology, factoring in future advantages, associated costs and unpredictability. The second model is patient-centric, evaluating the choice between immediate treatment switch and waiting for more clarity, while also weighing the associated risks. Lastly, the research assesses pandemic-related government policies, emphasizing the importance of delaying decisions in the face of uncertainties, thereby promoting data-driven policymaking.

Three different real options models are presented in this study to illustrate their applicability and value in aiding decision-makers. (1) The first evaluates investments in new technology, analyzing future benefits, discount rates and benefit volatility to determine investment value. (2) In the second model, a patient has the option of switching treatments now or waiting for more information before optimally switching treatments. However, waiting has its risks, such as disease progression. By modeling the potential benefits and risks of both options, and factoring in the time value, this model aids doctors and patients in making informed decisions based on a quantified assessment of potential outcomes. (3) The third model concerns pandemic policy: governments can end or prolong lockdowns. While awaiting more data on the virus might lead to economic and societal strain, the model emphasizes the economic value of deferring decisions under uncertainty.

This research provides a quantified perspective on various decisions in healthcare, from investments in new technology to treatment choices for patients to government decisions regarding pandemics. By applying real options theory, stakeholders can make more evidence-driven decisions.

Decisions about patient care pathways and pandemic policies have direct societal implications. For instance, choices regarding the prolongation or ending of lockdowns can lead to economic and societal strain.

The originality of this study lies in its application of real options theory, a concept from finance, to the realm of health economics, offering novel insights and analytical tools for decision-makers in the healthcare sector.

The South African construction industry appears to be lagging behind other industries in the country in terms of implementation and adoption of innovative technologies. Moreover, sufficient empirical data on the adoption of innovative technologies, especially, in developing countries are not readily available. The aim of this study is therefore to assess the adoption and implementation of innovative technologies in the South African construction industry with a view to improving the industry's performance.

A survey was undertaken using a questionnaire, administered to construction professionals primarily in project management, quantity surveying and architectural firms.

The key findings show that there are some innovative technologies such as building information modelling, 3-dimensional mapping, drones, 3-dimensional printing and virtual reality that have been deployed. However, limited adoption of innovative technologies within the industry and low levels of knowledge of its benefits among the respondents were reported. This low implementation of innovative technologies was due to critical barriers such as high cost, limited knowledge, time requirement, fear of change, lack of interest, nature of construction processes and lack of team dynamics. Key drivers of innovation were found to include globalization and competition.

The current level of implementation of innovative technologies indicated that they are not yet optimized in the South African construction industry and suggests implications for change, adaptation and growth. The study recommends that firms should consider investing in research and development in order to exploit the potential of innovation for organizations and the industry at large.

The drivers and barriers indicated will help to prioritize the direction of adoption and growth which could help to improve the industry.

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?

Leadership is an essential contributor to employee creative self-efficacy, and past research suggests a positive relationship between servant leadership and creative self-efficacy. However, the relationship is complex and contingent upon moderating variables, and this research examines the moderating effect of role clarity by drawing on social exchange theory and social cognitive theory.

Data collected from a survey among 116 emergency room employees is used to test the research model using moderated ordinary least squares regression.

The results confirm a positive relationship between servant leadership and creative self-efficacy and suggest a U-shaped relationship between role clarity and creative self-efficacy. Furthermore, role clarity positively moderates the relationship between servant leadership and creative self-efficacy.

The sample used for this research mainly consisted of highly educated employees within a specific setting. Future research is needed to study if the relationships found in this research can be generalized to other organizational settings.

This research suggests that leaders can support employees' creative self-efficacy through servant leadership, particularly when coupled with high role clarity.

Rapidly changing work environments are characterized by decreased role clarity, so attention is needed to its moderating role on the relationship between servant leadership and creative self-efficacy.

The purpose of this research is to explore how one unsanctioned community sport organization (CSO), AM Hockey, sought to acquire legitimacy in a highly institutionalized minor hockey marketplace at various points in its organizational life cycle.

This study was guided by instrumental case study methodology. Twenty (20) AM Hockey stakeholders from a variety of roles (e.g. executives, program directors and coaches) were interviewed. Document analysis was also utilized to supplement the interviewees. Internal and public documents reflective of the CSO's creation and growth were obtained.

Findings revealed that the CSO had to navigate distinct phases of evolution including the Building, Growth, Competition and Stabilization phases. Although the four life cycle phases identified in this study share similarities with the phases identified by Lester et al. (2003), findings indicated that institutional work mechanisms must be understood in their context as they can vary over the life cycle of an organization. Therefore, start-up sports organizations must approach the pursuit of legitimacy as a continual process rather than something acquired and defended through maintenance work.

Developing legitimacy remains a central challenge for CSOs that seek to deliver alternative sport programming, yet it continues to be understudied. Ultimately, the long-term viability of an unsanctioned CSO in a federated sports system relies, in part, on its ability to continually determine the actions needed to achieve legitimacy within its environment.

This study relied on the job demands and resource model to understand employees’ turnover intentions. Recent studies have consistently lent support for the significant association between role ambiguity and turnover intentions; however, only a handful of studies focused on examining the potential mediators in this association. The authors argued that role ambiguity positively influences turnover intentions through affective mechanisms: job involvement and satisfaction.

To test the model, a large sample of working adults participated (N = 505).

Structural equation modeling results showed that role ambiguity, job involvement and job satisfaction were significantly associated with turnover intentions. Moreover, a serial mediation was found among the variables: employees with low levels of role ambiguity tended to report higher job involvement, which further increased their satisfaction with the job and subsequently decreased their turnover intentions.

The cross-sectional design is a limitation.

Practical suggestions regarding how organizations can reduce employee turnover are discussed.

The findings provide support for theory-driven interventions to address developing the intention to stay at work among working adults.

This research aims to develop an automated and optimization algorithms (OAs)-integrated 4D building information modeling (BIM) approach and a prototype and enable construction managers and practitioners to estimate the time of compound elements in building projects using the resource specification technique.

A 4D BIM estimation process was first developed by applying the resource specification and geometric information from the BIM model. A suite of OA including particle swarm optimization, ant colony, differential evolution and genetic algorithm were developed and compared in order to facilitate and automate the estimation process. The developed processes and porotypes were linked and integrated.

The OA-based automated 4D BIM estimation prototype was developed and validated through a real-life construction project. Different OAs were applied and compared, and the genetic algorithm was found as the best performing one. The prototype was successfully linked with BIM timeliner application. By using this approach, the start and finish dates of all object-based activities are developed, and the project completion time is automatically estimated.

Unlike conventional construction estimation methods which need various tools and are error prone and time-consuming, the developed method bypasses the existing time estimation tools and provides the integrated and automated process with BIM and machine learning algorithms. Furthermore, this approach integrates 4D BIM applications into construction design procedures, connected with OA automation.