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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.

Gender disparity is a global phenomenon where females outnumber male participants. It has been observed that males are the early leaver from higher education, thus reflecting a severe concern about social instability. Malaysia is a prominent example where females outnumber males in higher education. In this context, this paper aims to examine the effect of individual, social and financial factors on the higher education self-efficacy of male and female students. It develops a comprehensive understanding of gender-based decision factors in pursuing higher education.

The hypothesis was formed based on a comprehensive literature review following the hypothetico-deductive positivist approach. These hypotheses were tested based on a sample of 250 respondents. A multiple regression analysis was deployed to test the relationship between the dependent variable and its predictors.

The results suggest that male and female students’ self-efficacy depends on five determinants, i.e. family influence, peer influence, career expectancy outcome, gender roles and institutional factors. Male students tend to be influenced more by these five determinants than females. Additionally, male students with better financial backgrounds are more likely to have higher self-efficacy, whereas gender roles negatively affect male and female students’ self-efficacy for higher education.

The breakout of COVID-19 resulted in the selection of limited students in Malaysia. Due to restricted movement orders, it was impossible to reach out to the students for data collection. Future research could include a broader area to include multiple other regions of Malaysia. For a broader aspect, the study could be conducted in other areas/countries where the problem of less male participation exists.

The relationship between higher education self-efficacy is assessed with social, financial and institutional factors for male and female students. It will enable the stakeholders and policymakers to make better decisions in increasing the self-efficacy of students to attain equity in higher education institutions.

The finding of this paper will assist in increasing male participation in higher education institutions to avoid any social instability.

This paper contributes to the literature in understanding the causes of gender gap reversal, focusing on Malaysian higher education institutions. It also provides empirical evidence to look at potential factors that affect the higher education self-efficacy of male and female students.

The planning of massive vaccination campaigns often falls to nongovernmental organizations that have to face the critical challenge of vaccinating the largest number of people in the shortest time. This study aims to provide an easy tool for minimizing the duration of mass vaccination campaigns in rural and remote areas of developing countries.

This paper presents a linear mathematical model that combines location, scheduling and routing decisions that allows determining where to locate the vaccination centers, as well as the schedule/route that each medical team must follow to meet the target demand in the shortest time possible. In addition, the paper proposes an heuristic approach that can be integrated in a spreadsheet.

As the numerical experiments show, the proposed heuristic provides good solutions in a short time. Due to its simplicity and flexibility, the proposed approach allows decision-makers to analyze and evaluate several possible scenarios for decision-making by simply playing with input parameters.

The integration of the heuristic approach in a spreadsheet provides a simple and efficient tool to help decision-makers while avoiding the need for large investments in information systems infrastructure by user organizations.

Motivated by a real-life problem and different from previous studies, the objective of the planning is to reduce the length of the vaccination campaigns with the available resources and ensure a target coverage instead of planning for minimizing costs or maximizing coverage. Furthermore, for helping implementation to practitioners, the heuristic can be solved in a spreadsheet.

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.

This study aims to explore the role of successfully implemented enterprise resource planning (ERP) systems by investigating changes in management accounting (MA) and the influence of the context of small and medium-sized enterprises (SMEs) on the adoption and implementation process in an emerging market economy, namely, Saudi Arabia.

A case-study approach was used to review and compare the ERP adoption and implementation process in two Saudi SMEs from different industries for the descriptive analysis and assessment of changes in MA following the adoption of the system and influence of context. Secondary data were analyzed, and semi-structured interviews were conducted to collect data.

The results indicate that successful ERP implementations support and unify the core business processes and functions and improve analysis, decision-making, reporting and the overall quality of data. Furthermore, the results show that a management accountant's role is widened and shifted from a mere information provider to a business advisor and analyst, enhancing management accounting techniques. The results confirm that ERP implementation is related to the SMEs' technological, organizational and environmental contexts, which must be fully understood to achieve the desired improvements in the management accounting system.

This study contributes to understanding how ERP systems impact MA and management accountants, particularly in SMEs from developing countries, namely, Saudi Arabia. Specifically, to the best of the author’s knowledge, this study is one of the first to use the technology–organization–environment framework and contingency theory to investigate post-ERP implementation changes in SMEs MA in an emerging market economy.

Data analytics (DA) is an emerging topic in management science at large organizations; however, accountants in small and medium-sized enterprises (SMEs) are believed to be lagging far behind in the usage of DA. This study aims to provide a deep understanding of the actual DA activities undertaken by management accountants (MA) and to draw on SMEs’ characteristics to take advantage of DA applications.

This study used a qualitative approach by conducting in-depth interviews with 31 accounting and finance practitioners at senior levels of SMEs, following the use of the MAXQDA 2022 application for data analysis.

Findings in this study suggest variance and trend analysis as the two most popular tasks of DA, and advanced tasks such as contingency analysis, financial modeling, sentiment analysis and regression analysis are unfully performed in SMEs. The outcomes revealed that DA is not anticipated to affect the responsibilities but to expand the role and scope of management accounting.

This study simultaneously builds a theoretical framework about the antecedents, in terms of the external and internal drives and the characteristics of SMEs’ owner-managers, that are most common in all types of SMEs that encourage MA to use a specific technology, data analysis in a more advanced way instead of searching for determinants that affect the adoption of technology in general, as previous studies have conducted.

Although there are studies on DA usage, little has approached the mutual interconnections between how DA is applied by MA in SMEs and what changes in management accounting responsibilities by DA affect. Therefore, the point of this study was to look into how SMEs use DA and what activities MA actually do with DA to discover what traits SMEs need to use DA applications effectively as DA applications become more advanced.

In this paper, a systematic review of 284 articles published between 2015 and 2022 and a full-text thematic analysis of 70 selected articles was conducted to catalog and synthesize factors in a framework. Thematic analysis subsequently revealed 18 selective codes under three groups of drivers, barriers, and outcomes. These three groups were explained by four key aspects including organization, stakeholders, infrastructure, and business environment that set a framework for the digitalization of construction. The study finally concluded digitalization strategies with a focus on support mechanisms, government incentives, regulations, the transition from manual labor to technicians, organizational technology culture, methodology development, and innovation processes. Such strategies provide insight into prioritizing resources towards smooth digital transformation in construction businesses.

A two-stage methodology is adopted by undertaking a systematic literature review followed by thematic content analysis. This work concludes with an analysis of remaining research gaps and suggestions for potential future research.

In this paper, a systematic review of 284 articles published between 2015 and 2022 and a full-text thematic analysis of 70 selected articles was conducted to catalog and synthesize variables in a framework. Thematic analysis subsequently revealed a set of variables and factors describing construction digitalization under three groups of success factors, barriers, and outcomes. A critical content analysis of the representative studies was conducted to identify five future research trends as well as associated research gaps and directions on the topic.

This study contributes to practice by providing directions concerning the key strategies and priorities associated with the digitalization of construction businesses.

This ground-breaking research brings to light a classified set of factors that are important for the digitalization of construction businesses. The elicited framework contributes to the current body of knowledge by offering a unique conceptualization of both driving and adverse aspects for the seamless digital transformation of construction.

This paper aims to discuss the effect of Canada’s regulatory framework on the strategies of entrepreneurial businesses during the first phase of legalization of the recreational cannabis industry. Decriminalization of cannabis required a host of regulatory changes at the federal, provincial and municipal levels. Each province developed legal markets independently, differentially impacting entrepreneurial strategies. This paper describes the value chain that emerged in the first phase of the nascent industry, focusing on the actions of the businesses.

The authors develop a qualitative narrative analysis using government publications, press articles (especially from the business press) and personal communications of industry insiders speaking in public settings. The paper includes four short case studies to illustrate the emerging value chain of the nascent industry.

The study’s findings highlight the effect of regulatory frameworks on entrepreneurial strategies. We find that public policies had a significant impact on entrepreneurs and startup strategies. Inter-jurisdictional differences limited expansion into different provinces, with implications for regional economic development. Achieving public policy goals was delayed as a result of regulatory challenges that impacted industry development.

The authors’ findings show enterprises may develop growth strategies that comply with regulations when participating in nascent industries, but they must cope with extra risks, capital costs and uncertainty. The analysis also illustrates the value of engaging in government-industry collaboration to improve emerging regulatory frameworks.

The originality of this research consists of the detailed description of the first phase of Canada’s legalized recreational cannabis industry and the insight gained into the dynamics of nascent industries.

Efforts to implement supplier selection and order allocation (SSOA) approaches in small and medium-sized enterprises (SMEs) are quite restricted due to the lack of affordable and simple-to-use strategies. Although there is a huge amount of literature on SSOA techniques, very few studies have attempted to address the issues faced by SMEs and develop strategies from their point of view. The purpose of this study is to provide an effective, practical, and time-tested integrated SSOA framework for evaluating the performance of suppliers and allocating orders to them that can improve the efficiency and competitiveness of SMEs.

This study was conducted in two stages. First, an integrated supplier selection approach was designed, which consists of the analytic hierarchy process and newly developed measurement alternatives and ranking using compromise solution to evaluate supplier performance and rank them. Second, the Wagner-Whitin algorithm is used to determine optimal order quantities and optimize inventory carrying and ordering costs. The joint impact of quantity discounts is also evaluated at the end.

Insights derived from the case study proved that the proposed approach is capable of assisting purchase managers in the SSOA decision-making process. In addition, this case study resulted in 10.89% total cost savings and fewer stock-out situations.

Criteria selected in this study are based on the advice of the managers in the selected manufacturing organizations. So the methods applied are limited to manufacturing SMEs. There were some aspects of the supplier selection process that this study could not explore. The development of an effective, reliable supplier selection procedure is a continuous process and it is indeed certainly possible that there are other aspects of supplier selection that are more crucial but are not considered in the proposed approach.

Purchase managers working in SMEs will be the primary beneficiaries of the developed approach. The suggested integrated approach can make a strategic difference in the working of SMEs.

A practical SSOA framework is developed for professionals working in SMEs. This approach will help SMEs to manage their operations effectively.

This research aims to create a methodology that integrates optimization techniques into preliminary cost estimates and predicts the impacts of design alternatives of steel pedestrian bridges (SPBs). The cost estimation process uses two main parameters, but the main goal is to create a cost estimation model.

This study explores a flexible model design that uses computing capabilities for decision-making. Using cost optimization techniques, the model can select an optimal pedestrian bridge system based on multiple criteria that may change independently. This research focuses on four types of SPB systems prevalent in Egypt and worldwide. The study also suggests developing a computerized cost and weight optimization model that enables decision-makers to select the optimal system for SPBs in keeping up with the criteria established for that system.

In this paper, the authors developed an optimization model for cost estimates of SPBs. The model considers two main parameters: weight and cost. The main contribution of this study based on a parametric study is to propose an approach that enables structural engineers and designers to select the optimum system for SPBs.

The implications of this research from a practical perspective are that the study outlines a feasible approach to develop a computerized model that utilizes the capabilities of computing for quick cost optimization that enables decision-makers to select the optimal system for four common SPBs based on multiple criteria that may change independently and in concert with cost optimization during the preliminary design stage.

The model can choose an optimal system for SPBs based on multiple criteria that may change independently and in concert with cost optimization. The resulting optimization model can forecast the optimum cost of the SPBs for different structural spans and road spans based on local unit costs of materials cost of steel structures, fabrication, erection and painting works.

The authors developed a computerized model that uses spreadsheet software's capabilities for cost optimization, enabling decision-makers to select the optimal system for SPBs meeting the criteria established for such a system. Based on structural characteristics and material unit costs, this study shows that using the optimization model for estimating the total direct cost of SPB systems, the project cost can be accurately predicted based on the conceptual design status, and positive prediction outcomes are achieved.