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This research aims to forecast the ABI as a leading indicator of U.S. construction activities, applying multivariate machine learning predictive models over different horizons and utilizing the nonlinear and long-term dependencies between the ABI and macroeconomic and construction market variables. To assess the applicability of the machine learning models, six multivariate machine learning predictive models were developed considering the relationships between the ABI and other construction market and macroeconomic variables. The forecasting performances of the developed predictive models were evaluated in different forecasting scenarios, such as short-term, medium-term, and long-term horizons comparable to the actual timelines of construction projects.

The architecture billings index (ABI) as a macroeconomic indicator is published monthly by the American Institute of Architects (AIA) to evaluate business conditions and track construction market movements. The current research developed multivariate machine learning models to forecast ABI data for different time horizons. Different macroeconomic and construction market variables, including Gross Domestic Product (GDP), Total Nonresidential Construction Spending, Project Inquiries, and Design Contracts data were considered for predicting future ABI values. The forecasting accuracies of the machine learning models were validated and compared using the short-term (one-year-ahead), medium-term (three-year-ahead), and long-term (five-year-ahead) ABI testing datasets.

The experimental results show that Long Short Term Memory (LSTM) provides the highest accuracy among the machine learning and traditional time-series forecasting models such as Vector Error Correction Model (VECM) or seasonal ARIMA in forecasting the ABIs over all the forecasting horizons. This is because of the strengths of LSTM for forecasting temporal time series by solving vanishing or exploding gradient problems and learning long-term dependencies in sequential ABI time series. The findings of this research highlight the applicability of machine learning predictive models for forecasting the ABI as a leading indicator of construction activities, business conditions, and market movements.

The architecture, engineering, and construction (AEC) industry practitioners, investment groups, media outlets, and business leaders refer to ABI as a macroeconomic indicator to evaluate business conditions and track construction market movements. It is crucial to forecast the ABI accurately for strategic planning and preemptive risk management in fluctuating AEC business cycles. For example, cost estimators and engineers who forecast the ABI to predict future demand for architectural services and construction activities can prepare and price their bids more strategically to avoid a bid loss or profit loss.

The ABI data have been forecasted and modeled using linear time series models. However, linear time series models often fail to capture nonlinear patterns, interactions, and dependencies among variables, which can be handled by machine learning models in a more flexible manner. Despite the strength of machine learning models to capture nonlinear patterns and relationships between variables, the applicability and forecasting performance of multivariate machine learning models have not been investigated for ABI forecasting problems. This research first attempted to forecast ABI data for different time horizons using multivariate machine learning predictive models using different macroeconomic and construction market variables.

People with intellectual disabilities are at a significantly higher risk than the general population for experiencing a wide range of adverse and potentially traumatic events. This paper aims to explore the incidence of experiences of lifetime trauma across this population in one Forensic Intellectual Disability Service. Risk management recommendations and psychological risk formulations were also examined for their consideration of traumatic experiences.

Risk assessment reports (n = 39) were reviewed for evidence of traumatic experiences and the consideration of trauma in patient risk formulations and risk management treatment recommendations.

Trauma was rated as present or partially present in 84.6% (n = 33) of risk assessment reports reviewed. None of the patients had received a post-traumatic stress disorder (PTSD) diagnosis. Recommendations regarding trauma were identified in 39.4% (n = 13) of the risk assessment reports where trauma was rated either “present” or “partially present”.

Findings suggest a need for diagnostic tools to be used to measure trauma symptoms and potential cases of PTSD to best support needs of patients. Trauma-focused interventions should also be considered. Further investigation is needed to clarify the disparity between the consideration of trauma in formulations and treatment recommendations.

This study highlights the different traumatic experiences that forensic patients across three settings have been exposed to during their lifetimes.

This review identifies low self-concept clarity (SCC) as a source of consumer vulnerabilities and explains how the uncertainty associated with low SCC leads to processes that result in materialistic behaviors and overspending, product dissatisfaction, and potential self-harm. Processes include uncertainty reduction efforts through symbolic self-completion and social comparison, responses to everyday self-concept threats that result in feelings of deficiency and reduced consumption constraints, and susceptibility to interpersonal and marketer influences. In addition, the negative association between SCC and materialism is explained, risk factors for low SCC are described, and the need for research to help low SCC consumers deal with their vulnerabilities is explored.

Although environmental pressures have been covered in great detail in prior literature as the drivers of eco-innovation, there remains inconsistency in the empirical results concerning the effects of these pressures on eco-innovation behaviour. Hence, this paper aims to investigate the impact of environmental pressures, namely, regulatory pressure, green demand and competitive pressure, on eco-innovation among manufacturing SMEs. Moreover, it examined the mediating role of environmental capabilities on the environmental pressure–eco-innovation relationship.

Quantitative data were collected using an online self-reported questionnaire survey to test the hypothesised model. A total of 183 valid questionnaires were collected from managers and owners of manufacturing SMEs in Egypt.

The results of the data analysis using the Smart-PLS software package revealed that among environmental pressures, only green demand had a direct effect on eco-innovation. In addition, environmental capabilities only mediated the effect of competitive pressure on eco-innovation.

This study has been one of the few addressing the issue of how the drivers of eco-innovation interact. It has also provided the managers and owners of SMEs and policymakers with practical implications.

The case study’s learning objectives, structured according to Bloom’s taxonomy, engage students in higher-order thinking for critical analysis and strategic decision-making. After completion of the case study, students will be able to analyze sustainability practices and evaluate the family’s distribution model for alignment with sustainability and potential expansion strategies; explore adaptive strategies to identify adaptive solutions to challenges such as climate change and economic fluctuations; apply theoretical frameworks to balance exclusivity and growth in the olive oil industry; and assess strategic decisions considering financial viability, environmental responsibility, community engagement and sustainability.

The case study centers on the Abi Raad olive farm, a multigenerational family-owned business deeply rooted in olive cultivation traditions in Selfaya village, within Mount Lebanon’s Aley district. Led by Richard Abi Raad, the family specializes in olive cultivation, olive oil production and handmade soap manufacturing within the agriculture sector. In 2023, the organization faces significant challenges such as rising labor costs and the exploration of sustainable labor sources for future growth. Abi Raad, the primary protagonist, grapples with critical decisions regarding maintaining traditional distribution methods versus expanding into broader markets. His choices must balance the preservation of cultural heritage with the need to uphold brand integrity and competitiveness. The case study traces the family’s historical journey in olive farming and explores their contemporary strategic dilemmas, offering insights into sustainable agriculture, entrepreneurship and navigating modern challenges while honoring tradition. Through the narrative of the Abi Raad family-owned business, the case study provides profound lessons in strategic decision-making and ensuring long-term sustainability.

This case study is suitable for students studying master’s in business.

Teaching notes are available for educators only.

CSS 11: Strategy.

This review aims to present the state of the art regarding the impact of financial technology (FinTech) on financial inclusion and its implications for consumers and institutions in terms of accessibility, usage and quality. An integrated framework is developed to illustrate the primary thematic areas for future research.

We performed a systematic literature review (SLR) to summarize and synthesize existing research published in peer-reviewed academic journals. Forty-two eligible studies were identified from the Web of Science database and a cross-reference search.

The results suggest that FinTech promotes financial inclusion for consumers and businesses by increasing the accessibility, usage and quality of financial products. We present a multidisciplinary integrative framework that links the three dimensions of financial inclusion (i.e. access, usage and quality) to financial technology. Finally, we propose several avenues for future research.

To the best of the author’s knowledge, this is the first SLR on how FinTech is associated with the accessibility, usage and quality of financial products. We provide an integrative framework for understanding the topic with implications in different fields.

This study aims to deepen the understanding of the challenges and implications entailed by deploying mobile clinics in conflict zones to reach populations affected by violence and cut off from health-care services.

This research combines an integrated literature review and an instrumental case study. The literature review comprises two targeted reviews to provide insights: one on conflict zones and one on mobile clinics. The case study describes the process and challenges faced throughout a mobile clinic deployment during and after the Iraq War. The data was gathered using mixed methods over a two-year period (2017–2018).

Armed conflicts directly impact the populations’ health and access to health care. Mobile clinic deployments are often used and recommended to provide health-care access to vulnerable populations cut off from health-care services. However, there is a dearth of peer-reviewed literature documenting decision support tools for mobile clinic deployments.

This study highlights the gaps in the literature and provides direction for future research to support the development of valuable insights and decision support tools for practitioners.

This study aims to facilitate access to vascular disease screening for low-income individuals living in remote and conflict areas based on the results of a pilot trial in Colombia. Also, to increase the amount of diagnosis training of vascular surgery (VS) in civilians.

The operation method includes five stages: strategy development and adjustment; translation of the strategy into a real-world setting; operation logistics planning; strategy analysis and adoption. The operation plan worked efficiently in this study’s sample. It demonstrated high sensibility, efficiency and safety in a real-world setting.

The authors developed and implemented a flow model operating plan for screening vascular pathologies in low-income patients pro bono without proper access to vascular health care. A total of 140 patients from rural areas in Colombia were recruited to a controlled screening session where they underwent serial noninvasive ultrasound assessments conducted by health professionals of different training stages in VS.

The plan was designed to be implemented in remote, conflict areas with limited access to VS care. Vascular injuries are critically important and common among civilians and military forces in regions with active armed conflicts. As this strategy can be modified and adapted to different medical specialties and geographic areas, the authors recommend checking the related legislation and legal aspects of the intended areas where we will implement this tool.

Different sub-specialties can implement the described method to be translated into significant areas of medicine, as the authors can adjust the deployment and execution for the assessment in peripheral areas, conflict zones and other public health crises that require a faster response. This is necessary, as the amount of training to which VS trainees are exposed is low. A simulated exercise offers a novel opportunity to enhance their current diagnostic skills using ultrasound in a controlled environment.

Evaluating and assessing patients with limited access to vascular medicine and other specialties can decrease the burden of vascular disease and related complications and increase the number of treatments available for remote communities.

It is essential to assess the most significant number of patients and treat them according to their triage designation. This management is similar to assessment in remote areas without access to a proper VS consult. The authors were able to determine, classify and redirect to therapeutic interventions the patients with positive findings in remote areas with a fast deployment methodology in VS.

Access to health care is limited due to multiple barriers and the assessment and response, especially in peripheral areas that require a highly skilled team of medical professionals and related equipment. The authors tested a novel mobile assessment tool for remote and conflict areas in a rural zone of Colombia.

This paper aims to provide a systematic review of the academic literature on the determinants, processes and impacts of indigenous entrepreneurship (IE), highlights its contribution to current knowledge and identifies research gaps to guide future research.

Databases used in this study included Scopus, ABI, Business Source Complete, ProQuest and Emerald Insight. In total, 84 articles were included in the review.

The findings revealed that 33 studies were qualitative, 12 used a survey-based approach, 25 were conceptual and 14 used mixed approaches. The focus on theory-building research underlines the fact that more theory-testing research is needed in the future. In total, 38 studies were conducted in developed countries and 43 in developing countries. The findings indicated that IE was driven by many determinants such as family and clan ties, patriarchy and social stratification, government support and conducive entrepreneurial ecosystems. Processes related to policies, IE development programs, partnerships, expenditure mechanisms, equitable distribution of benefits and resource mobilization. The outcomes of IE included economic development, sustainability, increased indigenous economic participation, enhanced quality of life, self-determination and preserving cultural heritage.

The current paper has some limitations. Firstly, it focuses only on academic journals and excludes conferences, books and working papers. Secondly, it includes only English language academic articles. However, while the current systematic literature review (SLR) has these limitations, it presents a thorough view of the determinants, processes and impacts of IE. Future studies may consider other sources beyond academic journals and also include non-English publications, and this approach may identify interesting areas for future research.

Existing reviews of IE take a narrow perspective and fail to present a comprehensive view of the IE phenomenon. The current study aims to fill this gap in the literature and provides a SLR pertaining to IE’s determinants, processes and impacts. The review is both timely and relevant because it identifies gaps and serves as a springboard to guide future research.

Takaful is a social security approach that guarantees business risks in light of shari’ah, thus playing a crucial role in human life and the economy. The purpose of this study is to examine the factors that influence the behavioural intention of micro, small and medium-sized enterprises (MSMEs) entrepreneurs to participate in takaful in Sri Lanka.

This study is designed quantitatively with deductive approach using the theory of planned behaviour. A total of 432 MSMEs in Sri Lanka were surveyed using convenience sampling to measure the intention to participate in takaful as a risk mitigation. The collected data were analysed through partial least square-structural equational modelling.

Attitude, subjective norm and perceived behavioural control variables positively influenced the intention, with t-values of 3.216, 3.813 and 3.859, respectively. The influence of these variables exhibits not much difference.

This study only focuses on MSMEs and a general takaful scheme. Future researchers may consider family takaful involvement among Sri Lankan business entrepreneurs.

Takaful practitioners should gain from the entrepreneurs’ intention to participate in takaful. Findings from this study could help marketing managers to revamp their strategies to further attract the entrepreneurs and make them to understand risk they are facing and, subsequently, participate in the takaful scheme.

This paper focuses on the context of Muslim minority among pluralism, where there is no regulation for Islamic financial products and services, and under the Islamic financial market crisis. This unleashes how business owners feel about takaful system on different dimensions.