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This study aims to describe the fundamentals of teaching risk management in a classroom setting, with an emphasis on the learning interface between higher education and the workplace environment for business management students.

The study reviews literature that uses spreadsheets to visualize and model risk and uncertainty. Using six distinct case-based activities (CBAs), the study illustrates the practical applications of software like Palisade @RISK in risk management education. It helps to close the gap between theory and practice. The software assists in estimating the likelihood of a risk event and the impact or repercussions it will have if it occurs. This technique of risk analysis makes it possible to identify the risks that need the most active control.

@RISK can be used to create models that produce results to demonstrate every potential scenario outcome. When faced with a choice or analysis that involves uncertainty, @RISK can be utilized to enhance the perspective of what the future might contain.

The insights from this study can be used to develop critical thinking, independent thinking, problem-solving and other important skills in learners. Further, educators can apply Bloom’s taxonomy and the problem-solving taxonomy to help students make informed decisions in risky situations.

The purpose of this study is to examine the rostering practices and work experiences of medical scientists at four health services in the Australian public healthcare sector. There are over 16,000 medical scientists (AIHW, 2019) in Australia responsible for carrying out pathology testing to help save the lives of thousands of patients every day. However, there are systemic shortages of medical scientists largely due to erratic rostering practices and workload issues. The purpose of this paper is to integrate evidence-based human resource management (EBHRM), the LAMP model and HR analytics to enhance line manager decision-making on rostering to support the wellbeing of medical scientists.

Using a qualitative methodological approach, the authors conducted 21 semi-structured interviews with managers/directors and nine focus groups with 53 medical scientists, making a total 74 participants from four large public hospitals in Australia.

Across four health services, manual systems of rostering and management decisions do not meet the requirements of the enterprise agreement (EA) and impact negatively on the wellbeing of medical scientists in pathology services. The authors found no evidence of the systematic approach of the organisations and line managers to implement the LAMP model to understand the root causes of rostering challenges and negative impact on employees. Moreover, there was no evidence of sophisticated use of HR analytics or EBHRM to support line managers' decision-making regarding mitigation of rostering related challenges such as absenteeism and employee turnover.

The authors contribute to HRM theory by integrating EBHRM, the LAMP model (Boudreau and Ramstad, 2007) and HR analytics to inform line management decision-making. The authors advance understandings of how EBHRM incorporating the LAMP model and HR analytics can provide a systematic and robust process for line managers to make informed decisions underpinned by data.

The purpose of this paper is to describe a state mandated merger of two institutional repositories from two separate campuses of a university into one new institutional repository. Due to a State Legislature mandate, the University of South Florida was required to merge institutional repositories from two campus into one new institutional repository.

USF Libraries formed a committee, planned for the migration and executed of the migration.

The authors discovered many unforeseen issues during the process of the migration such as difficulties with site redirects and hidden collections.

This project was a large-scale migration of institutional repositories, under a tight deadline due to a legislative mandate, that has not been discussed in detail in the literature.

Although Public Research Institutions (PRIs) are large technology producers, they lack automated information tools that follow technical and scientific criteria for assessing and valuing patents. The assessment and valuation processes are stages of technology transfer (TT) that make it possible to obtain productive arrangements and guide the efforts of those involved in the development, maintenance and negotiation. This study aims to analyze the hybrid model of assessment and valuation of technologies by Soares (2018), applying the ‘Valorativo' software. In addition to patent value and indicator scores, the methods allow an understanding of the technology portfolio and its management.

This research is quali-quantitative, following an approach of applied nature and descriptive objectives. The research has bibliographical, documental and case study features based on the software development methodologies described in the study and the theoretical framework.

The Valorativo software assisted in the analysis of ten patents on PRIs. With the data collection and patent analysis, PAT1 scored highest among engineering patents, PAT3 scored highest among pharmaceutical patents and PAT10 scored highest among biotechnology patents. Five of the assessed patents resulted in a surplus of net present value (NPV), final net present value (NPVF) and royalties; revenue expectations outpaced investments.

The authors based the developed software on Soares’s (2018) methodology, with additional calculations and graphs. The Web software and the spreadsheet with Visual Basic for Application (VBA) were developed to deal with the patents assessment and valuation, helping in the analysis of their Legal Value, Technological Value and Market Conditions in the assessment process, and the Discounted Cash Flow and NPV in the valuation process.

The software helps with patent analysis and can generate indicators for traders, technology holders and researchers. Thus, it was necessary to understand and develop a theoretical-applied framework to outline and replicate the methodology clearly and easily.

Sustainability has become an integral part of the real estate industry, alongside advancing globalization and demographic development. Due to real estate's influence on greenhouse gas emissions throughout its life cycle, both the regulatory and legal requirements concerning the sustainability of real estate are growing and, as a result of social responsibility, the interest of tenants and investors in sustainable real estate. However, criteria for measuring the ecological sustainability of a real estate investment in the purchase process in order to reduce the risk of including “stranded assets” in the portfolio are missing. This paper aims to address the need to integrate the issue of carbon stranding into existing sustainability rating tools.

Existing tools are examined based on defined criteria to determine whether they are suitable for purchasing a property before suitable tools for purchase are compared. Strengths and weaknesses are identified, which are to be remedied with the scoring tool. Taxonomy regulation is integrated into the existing valuation basis as a legal regulation.

The result is a scoring tool that enables real estate companies to measure and evaluate the ecological sustainability performance of a property during the acquisition process, taking into account the three aspects of sustainability and considering them when determining an appropriate purchase price in line with market conditions. Moreover, the developed tool helps to minimize the risk of acquiring a stranding asset.

The environmental, social and governance (ESG) framework employed in this study does not incorporate governance considerations. While the analysis extensively evaluates the building's environmental and social aspects, it does not extend to examining the governance practices of the companies involved. Thus, the assessment is confined solely to the physical attributes of the property without accounting for broader corporate governance factors.

The developed scoring tool represents a valuable tool for the real estate industry, offering insights into sustainability performance during property acquisitions and providing a structured framework for decision-making. By addressing both certification and taxonomy regulation requirements, the tool contributes to the industry's evolution toward more sustainable and environmentally responsible real estate practices.

In response to the growing importance of sustainability in the real estate industry, this paper introduces a novel scoring tool for evaluating the sustainability of real estate investments during the acquisition process.

Ready-mix concrete delivery problem (RMCDP), a specific version of the vehicle routing problem (VRP), is a relevant supply-chain engineering task for construction management with various formulations and solving methods. This problem can range from a simple scenario involving one source, one material and one destination to a more challenging and complex case involving multiple sources, multiple materials and multiple destinations. This paper presents an Internet of Things (IoT)-supported active building information modeling (BIM) system for optimized multi-project ready-mix concrete (RMC) delivery.

The presented system is BIM-based, IoT supported, dynamic and automatic input/output exchange to provide an optimal delivery program for multi-project ready-mix-concrete problem. The input parameters are extracted as real-time map-supported IoT data and transferred to the system via an application programming interface (API) into a mixed-integer linear programming (MILP) optimization model developed to perform the optimization. The obtained optimization results are further integrated into BIM by conventional project management tools. To demonstrate the features of the suggested system, an RMCDP example was applied to solve that included four building sites, seven eligible concrete plants and three necessary RMC mixtures.

The system provides the optimum delivery schedule for multiple RMCs to multiple construction sites, as well as the optimum RMC quantities to be delivered, the quantities from each concrete plant that must be supplied, the best delivery routes, the optimum execution times for each construction site, and the total minimal costs, while also assuring the dynamic transfer of the optimized results back into the portfolio of multiple BIM projects. The system can generate as many solutions as needed by updating the real-time input parameters in terms of change of the routes, unit prices and availability of concrete plants.

The suggested system allows dynamic adjustments during the optimization process, andis adaptable to changes in input data also considering the real-time input data. The system is based on spreadsheets, which are widely used and common tool that most stakeholders already utilize daily, while also providing the possibility to apply a more specialized tool. Based on this, the RMCDP can be solved using both conventional and advanced optimization software, enabling the system to handle even large-scale tasks as necessary.

Information infrastructures can enable or constrain how companies pursue their visions of sustainability reporting and help address the urgent need to understand how corporate activity affects sustainability outcomes and how socio-ecological challenges affect corporate activity. The paper examines the relationship between sustainability reporting information infrastructures and sustainability reporting practice.

The paper mobilises a socio-technical perspective and the conception of infrastructure, the socio-technical arrangement of technical artifacts and social routines, to engage with a qualitative dataset comprised of interview and documentary evidence on the development and construction of sustainability reporting information.

The results detail how sustainability reporting information infrastructures are used by companies and depict the difficulties faced in generating reliable sustainability data. The findings illustrate the challenges and measures undertaken by entities to embed automation and integration, and to enhance sustainability data quality. The findings provide insight into how infrastructures constrain and support sustainability reporting practices.

The paper explains how infrastructures shape sustainability reporting practices, and how infrastructures are shaped by regulatory demands and costs. Companies have developed “uneven” infrastructures supporting legislative requirements, whilst infrastructures supporting non-legislative sustainability reporting remain underdeveloped. Consequently, infrastructures supporting specific legislation have developed along unitary pathways and are often poorly integrated with infrastructures supporting other sustainability reporting areas. Infrastructures developed around legislative requirements are not necessarily constrained by financial reporting norms and do not preclude specific sustainability reporting visions. On the contrary, due to regulation, infrastructure supporting disclosures that offer an “inside out” perspective on sustainability reporting is often comparatively well developed.

One of the most emerging areas of audit knowledge is sustainable quality, which can comprehensively cover the development of audit reports inclusiveness for stakeholders. The purpose of this study is to present the sustainable audit quality (SAQ) framework based on the UK Financial Reporting Council.

The paper discusses the main concepts in both spreadsheets and process mining. Using a concrete data set as a running example, the different types of process mining are explained. Where spreadsheets work with numbers, process mining starts from event data with the aim to analyze processes.

The results of the study showed that the SAQ is more effective based on the two criteria of going concern and disclosure of key audit items. It was also determined that, based on total interpretive structural modeling, the two themes of debt covenants disclosure and assessment of firms’ leverage ratio have a higher priority for SAQ in the Tehran Stock Exchange.

This paper contributes to the discussion on the use of data mining for microarray databases and specifically for studying the present SAQ framework based on the UK Financial Reporting Council. An area that has not been paid attention to by prior research studies, and to the best of the authors’ knowledge, this study is the first research that attempts to provide the SAQ framework.

This research aims to argue that manual geometric modeling is blocking the building information modeling (BIM) promotion to small-size companies. Therefore, it is necessary to study a manner of automated modeling to reduce the dependence of BIM implementation on manpower. This paper aims to make a study into such a system to propose both its theory and prototype.

This research took a prototyping as the methodology, which consists of three steps: (1) proposing a theoretical framework supporting automated geometric modeling process; (2) developing a prototype system based on the framework; (3) conducting a testing for the prototype system on its performance.

Previous researches into automated geometric modeling only respectively focused on a specific procedure for a particular engineering domain. No general model was abstracted to support generic geometric modeling. This paper, taking higher level of abstraction, proposed such a model that can describe general geometric modeling process to serve generic automated geometric modeling systems.

This paper focused on only geometric modeling, skipping non-geometric information of BIM. A complete BIM model consists of geometric and non-geometric data. Therefore, the method of combination of them is on the research agenda.

The model proposed by this paper provide a mechanism to translate engineering geometric objects into textual representations, being able to act as the kernel of generic automated geometric modeling systems, which are expected to boost BIM promotion in industry.

Many cities across the world are actively investing in ways to excel in the innovation economy through the development of innovation districts as one of the most popular policy options. While innovation districts are among the leading drivers of innovation activities in cities, they are also high-cost and high-risk investments. Besides, holistic approaches for assessing these districts’ multifaceted performances are scarce. Bridging this knowledge gap is critical, hence, this paper aims to explore how innovation district performance can be assessed through a classification framework.

The paper introduces a multidimensional innovation district classification framework and applies it into Australian innovation districts with divergent features, functions, spatial and contextual characteristics. The study places 30 innovation districts from South East Queensland under the microscope of the framework to assess the multifaceted nature of innovation district performance. It uses qualitative analysis method to analyse both the primary and secondary data, and descriptive analysis with basic excel spreadsheet calculations to analyse the validity of the data.

The data analysis clusters 30 innovation districts from South East Queensland under three performance levels – i.e. desired, acceptable and unsavoury – concerning their form, feature and function characteristics.

The results disclose that the framework is a practical tool for informing planners, developers and managers on innovation district performances, and it has the capability to provide guidance for policymakers on their policy and investment decisions regarding the most suitable innovation district types and characteristics to consider.