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In most developing countries, indigenous emerging construction contractors (ECCs) face severe problems of not adopting a project management framework (PMF) in their business activities. It has increased their business risk and threatened their sustainability. Studies showed that government policy support (GPS) helps mitigate business risks. Thus, there is a paucity of literature concerning GPS on emerging Nigerian construction contractors' business sustainability. Therefore, the paper aims to investigate the moderating effect of GPS on the relationship between PMF and ECCs in Nigeria.

SmartPLS was used to analyse the collected data from the useable 310 questionnaires retrieved from respondents in Abuja and Lagos, Nigeria. Systems Theory was used to support the developed framework.

Findings show that government policy support significantly moderates the relationships between PMF and ECCs in the Nigerian construction sector. It implies that the study's results offer more understanding regarding issues affecting construction entrepreneurs' sustainable business cycle via applying PMF to mitigate business sustainable associated risks.

The study will stir Nigeria's ECCs and policymakers to promote construction business sustainability for a new entrepreneur, emphasising business risk management via PMF and GPS to enhance the sustainable business cycle.

The research (PMF and GPS) is strategies to enhance ECCs business sustainability in the Nigerian construction sector and other developing countries with similar political and economic attributes. Besides the study guiding old and intending ECCs and policymakers in the developing countries industries, it would contribute to bridge the theoretical gap regarding PMF and ECC, especially ECCs in developing countries with similar business sustainability issues.

In this article, the authors draw-upon an extended unified theory of acceptance and use of technology (UTAUT) and propose a research model involving performance expectancy (PE), effort expectancy (EE), facilitating conditions (FC) and competitive pressure (CP) as potential salient factors explaining the adoption of digitalization in European SMEs. The authors also postulate that there may be cross-cultural differences, thereby leading us to include the country as a moderator in the model.

The authors validate this model with a cross-cultural sample involving 188 owner-managers from the Czech Republic and Slovakia and through the partial least square structural equation modeling (PLS-SEM) techniques as well as multi-group analysis.

The results using the study’s global dataset indicate that PE, FC and CP significantly affect owner-managers intentions toward digitalization in SMEs. The authors’ application of the multi-group analysis also suggests that although the two countries differ in digitalization adoption intention, the differences are statistically insignificant. In the conclusion, the authors highlight several implications these findings have for theory and practice.

The authors recommend that the providers of emerging digital technologies should improve on the performance features of those technologies and ensure they are relevant to the SMEs. By doing so, the adoption of digitalization will grow, because owner-managers of SMEs will have the confidence that adopting such technologies will improve their operations. Second, SMEs are required to provide adequate organizational and technical infrastructure to support digitalization adoption.

Aside from being among the few attempts to extend the explanatory power of UTAUT with PE, EE, FC and CP in investigating digitalization adoption in SMEs context, this study also validates its model with rigorous methodological approach as well as three datasets (global, Czech Republic and Slovakia) thereby strengthening the validity of the results.

Technologies have had a positive impact on the construction industry. Technologies such as BIM, automation, augmented and virtual reality, Internet of Things and robotics have been adopted by construction firms to enhance productivity. However, not much research has been done on the awareness and adoption of wearable technologies for health and safety (H&S) management. This paper investigates the level of awareness and adoption of wearable technologies for H&S management in the Nigerian construction industry.

A quantitative research method was adopted for the study. An electronic questionnaire format was used as an instrument to collect the data. Both descriptive (mean score) and inferential statistics (Kruskal–Wallis test) were used to analyse the data.

The results indicate that organisations rarely use H&S wearable devices for H&S management although professionals within the construction industry are somewhat aware of the common H&S wearable devices. The findings further indicate that all 11 variables were perceived as “rarely adopted”, whereas 2 variables were perceived as “aware”, 3 variables as “slightly aware” and the remaining 6 variables as “somewhat aware”.

Data were collected from only construction professionals working in government agencies, consultancy firms and grade D contracting firms in Lagos and Abuja. For a broader perspective, a study that expands the number of states and categories of construction firms is recommended.

The construction industry in Nigeria can use the recommendations to improve H&S management on site. Moreover, the recommendations can contribute to the development of policies to promote the adoption of wearable technologies in construction sites.

Research on wearable technologies, particularly in the Nigerian construction industry, is at the developing stage. With this article, the authors contribute to the body of knowledge in this area of research.

Poor quality in building projects is high and increasing. Poor quality can increase the cost of a building by up to more than 50% and can delay a project by up to 50%. This research investigated the poor quality of building elements/components.

The site operatives were requested to rate the frequency of poor quality in 25 building elements/components. The frequencies of the poor quality were scored on a five-point Likert scale, ranging from least often to extremely often. The survey forms were administered to construction site operatives by hand delivery.

The data revealed that poor quality occurred in more than 80% of the building projects completed. Approximately 40% of the cost of a building project is attributed to poor quality. In total, 70% of the respondents measured the poor quality of building elements as being high and frequent. The size and frequency of poor quality are higher in concrete, plaster, brick, foundations and roof trusses.

The research findings would help to reduce claims, disputes, maintenance costs and waste on sites.

This research provides fresh information on poor quality in building projects and provides a systemic process for anticipating poor quality in building projects. The findings also provide an option to increase maintenance span and a means to reduce claims and disputes in the construction sector.

The efficiency of each of an organization’s individual workers determines its effectiveness. The study aims to explore the relationship between human resource management (HRM) practices and organizational effectiveness with employee performance as a mediating variable.

Data were collected from 800 police officers in the Greater Accra and Tema regions. The data were supported by the hypothesized relationship. Construct reliability and validity was established through confirmatory factor analysis. The proposed model and hypotheses were evaluated using structural equation modeling.

The results show that career planning and employee performance were significantly related. Self-managed teams and employee performance were shown to be nonsignificantly related. Similarly, performance management and employee performance were shown to be nonsignificantly related. Employee performance significantly influenced organizational effectiveness. The results further indicate that employee performance mediates the relationship between HRM practices and organizational effectiveness.

The generalizability of the findings will be constrained due to the research’s police service focus and cross-sectional data.

The study’s findings will serve as valuable pointers for the police administration in the adoption, design and implementation of well-articulated and proactive HRM practices to improve the abilities, skills, knowledge and motivation of officer’s to inordinately enhance the effectiveness of the service.

By evidencing empirically that employee performance mediates the relationship between HRM practice and organizational effectiveness, the study extends the literature.

The purpose of the study is to investigate the correlation between credit supply to government and credit supply to the private sector to determine whether there is a crowding-out or crowding-in effect of credit supply to government on credit supply to the private sector.

The study used data from 43 countries during the 1980–2019 period. The study employed the Pearson correlation methodology to analyze the data.

There is a significant positive correlation between credit supply to government and credit supply to the private sector. There is also a significant positive relationship between credit supply to government and credit supply to the private sector, implying a crowding-in effect of government borrowing on private sector borrowing. The positive correlation between credit supply to government and credit supply to the private sector by banks is stronger and highly significant in the period before the Great Recession, while the positive correlation is weaker and less significant during the Great Recession, and the correlation further weakens after the Great Recession. The regional analyses show that the positive correlation between credit supply to government and credit supply to the private sector by banks is stronger and highly significant in the African region than in the Asian region and the region of the Americas.

There is no evidence on the correlation between credit supply to government and credit supply to the private sector during the Great Recession.

Despite the contributions of both the oil and gas and construction industries to the gross domestic product (GDP) of the country, both industries are still marred by incessant accidents. Therefore, the aim of this study is to compare the health and safety practises of the construction and oil and gas industries in Nigeria in order to suggest the best approach to health and safety practices.

A survey questionnaire was developed and administered to professionals working in the construction and oil and gas industries. Data were analysed using the relative importance index (RII). An independent sample t-test was also conducted to determine whether there was a significant difference in the construction and oil and gas industries.

The study revealed that the rate at which health and safety are practised in the oil and gas industry is comparatively high compared to how they are practised in the construction industry. Proper site layout and planning, provision of a safe working environment, proper health and safety risk assessment were more predominantly practised in the oil and gas industry, while proper site layout and planning, disallowing unauthorised entry into site and the provision of a safe working environment were predominantly practised in the construction industry.

This study is the first to compare the health and safety practises of the construction and oil and gas industries in Nigeria. This study was significant because it would provide insight into construction and oil and gas managers, as well as other decision-makers in both industries, on how to improve health and safety practices.

Psychological and entrepreneurial traits have been widely studied as explicative variables of encouraging entrepreneurial behavior, while their impact on innovative activity is less explored. This study examines whether, how and why psycho-entrepreneurial traits and social networks effect innovativeness among women firm owners.

Analysis of data collected from 304 Saudi women entrepreneurs accompanied by business accelerators provides a wide support with some notable exceptions. We use Structural Equation Modeling technique to estimate how different constructs interact with each other and jointly affect directly or indirectly women's innovativeness behavior in Saudi Arabia.

Findings point out that innovativeness is positively and significantly affected by emotional intelligence, internal locus of control, entrepreneurial alertness and entrepreneurial self-efficacy. The construct of entrepreneurial self-efficacy mediates the relationship between both business and personal networks and innovativeness. However, professional forums and mentors have no significant effect on innovativeness.

The sample selection is limited to two entrepreneurial support structures especially business accelerator and business incubator. Expanding the context to other support structures can reinforce the implications and provide more valuable results.

The findings are likely to be of applicability for improving women entrepreneurship by entrepreneurial support structures.

This research is original in the sense that it investigated useful insights of innovativeness among Saudi female entrepreneurs.

This study aims to predict overnight stays in Italy at tourist accommodation facilities through a nonlinear, single factor, stochastic model called CIR#. The contribution of this study is twofold: in terms of forecast accuracy and in terms of parsimony (both from the perspective of the data and the complexity of the modeling), especially when a regular pattern in the time series is disrupted. This study shows that the CIR# not only performs better than the considered baseline models but also has a much lower error than other additional models or approaches reported in the literature.

Typically, tourism demand tends to follow regular trends, such as low and high seasons on a quarterly/monthly level and weekends and holidays on a daily level. The data set consists of nights spent in Italy at tourist accommodation establishments as collected on a monthly basis by Eurostat before and during the COVID-19 pandemic breaking regular patterns.

Traditional tourism demand forecasting models may face challenges when massive amounts of search intensity indices are adopted as tourism demand indicators. In addition, given the importance of accurate forecasts, many studies have proposed novel hybrid models or used various combinations of methods. Thus, although there are clear benefits in adopting more complex approaches, the risk is that of dealing with unwieldy models. To demonstrate how this approach can be fruitfully extended to tourism, the accuracy of the CIR# is tested by using standard metrics such as root mean squared errors, mean absolute errors, mean absolute percentage error or average relative mean squared error.

The CIR# model is notably simpler than other models found in literature and does not rely on black box techniques such as those used in neural network (NN) or data science-based models. The carried analysis suggests that the CIR# model outperforms other reference predictions in terms of statistical significance of the error.

The proposed model stands out for being a viable option to the Holt–Winters (HW) model, particularly when dealing with irregular data.

The proposed model has demonstrated superiority even when compared to other models in the literature, and it can be especially useful for tourism stakeholders when making decisions in the presence of disruptions in data patterns.

The novelty lies in the fact that the proposed model is a valid alternative to the HW, especially when the data are not regular. In addition, compared to many existing models in the literature, the CIR# model is notably simpler and more transparent, avoiding the “black box” nature of NN and data science-based models.

一般来说, 旅游需求往往遵循规律的趋势, 例如季度/月的淡季和旺季, 以及日常的周末和假期。该数据集包括欧盟统计局在打破常规模式的2019冠状病毒病大流行之前和期间每月收集的在意大利旅游住宿设施度过的夜晚。

本研究旨在通过一个名为cir#的非线性单因素随机模型来预测意大利游客住宿设施的过夜住宿情况。这项研究的贡献是双重的:在预测准确性方面和在简洁方面(从数据和建模复杂性的角度来看), 特别是当时间序列中的规则模式被打乱时。我们表明, cir#不仅比考虑的基线模型表现更好, 而且比文献中报告的其他模型或方法具有更低的误差。

当大量搜索强度指标被作为旅游需求指标时, 传统的旅游需求预测模型将面临挑战。此外, 鉴于准确预测的重要性, 许多研究提出了新的混合模型或使用各种方法的组合。因此, 尽管采用更复杂的方法有明显的好处, 但风险在于处理难使用的模型。为了证明这种方法能有效地扩展到旅游业, 使用RMSE、MAE、MAPE或AvgReIMSE等标准指标来测试cir#的准确性。

cir#模型明显比文献中发现的其他模型简单, 并且不依赖于黑盒技术, 例如在神经网络或基于数据科学的模型中使用的技术。所进行的分析表明, cir#模型在误差的统计显著性方面优于其他参考预测。

这个模型作为Holt-Winters模型的一个拟议模型, 特别是在处理不规则数据时。

即使与文献中的其他模型相比, 所提出的模型也显示出优越性, 并且在数据模式中断时对旅游利益相关者做出决策特别有用。

创新之处在于所提出的模型是Holt-Winters模型的有效替代方案, 特别是当数据不规律时。此外, 与文献中的许多现有模型相比, cir#模型明显更简单、更透明, 避免了神经网络和基于数据科学的模型的“黑箱”性质。

Normalmente, la demanda turística tiende a seguir tendencias regulares, como temporadas altas y bajas a nivel trimestral/mensual y fines de semana y festivos a nivel diario. El conjunto de datos consiste en las pernoctaciones en Italia en establecimientos de alojamiento turístico recogidas mensualmente por Eurostat antes y durante la pandemia de COVID-19, rompiendo los patrones regulares.

El presente estudio pretende predecir las pernoctaciones en Italia en establecimientos de alojamiento turístico mediante un modelo estocástico no lineal de un solo factor denominado CIR#. La contribución de este estudio es doble: en términos de precisión de la predicción y en términos de parsimonia (tanto desde la perspectiva de los datos como de la complejidad de la modelización), especialmente cuando un patrón regular en la serie temporal se ve interrumpido. Demostramos que el CIR# no sólo aplica mejor que los modelos de referencia considerados, sino que también tiene un error mucho menor que otros modelos o enfoques adicionales de los que se informa en la literatura.

Los modelos tradicionales de previsión de la demanda turística pueden enfrentarse a desafíos cuando se adoptan cantidades masivas de índices de intensidad de búsqueda como indicadores de la demanda turística. Además, dada la importancia de unas previsiones precisas, muchos estudios han propuesto modelos híbridos novedosos o han utilizado diversas combinaciones de métodos. Así pues, aunque la adopción de enfoques más complejos presenta ventajas evidentes, el riesgo es el de enfrentarse a modelos poco manejables. Para demostrar cómo este enfoque puede extenderse de forma fructífera al turismo, se comprueba la precisión del CIR# utilizando métricas estándar como RMSE, MAE, MAPE o AvgReIMSE.

El modelo CIR# es notablemente más sencillo que otros modelos encontrados en la literatura y no se basa en técnicas de caja negra como las utilizadas en los modelos basados en redes neuronales o en la ciencia de datos. El análisis realizado sugiere que el modelo CIR# supera a otras predicciones de referencia en términos de significación estadística del error.

El modelo propuesto destaca por ser una opción viable al modelo Holt-Winters, sobre todo cuando se trata de datos irregulares.

El modelo propuesto ha demostrado su superioridad incluso cuando se compara con otros modelos de la bibliografía, y puede ser especialmente útil para los agentes del sector turístico a la hora de tomar decisiones cuando se producen alteraciones en los patrones de datos.

La novedad radica en que el modelo propuesto es una alternativa válida al Holt-Winters especialmente cuando los datos no son regulares. Además, en comparación con muchos modelos existentes en la literatura, el modelo CIR# es notablemente más sencillo y transparente, evitando la naturaleza de “caja negra” de los modelos basados en redes neuronales y en ciencia de datos.

Housing provision and the neighbourhood's safety are significant social sustainability concerns. If structural issues are not well checked, housing provision and the neighbourhood's safety may become threatened, especially in Lagos State, Nigeria. Thus, this study aims to investigate the perceived root cause of collapsed buildings at the construction stage using two case studies, its effect on social sustainability aspects and suggested measures to mitigate future happening and enhance achieving social sustainability aspects goals.

The researchers collected data from Nigeria's built environment experts and eyewitnesses/employees of selected cases of collapsed buildings. The study adopted a phenomenology type of qualitative research design and analysed collated data via thematic analysis and achieved saturation. The analysed data created three themes.

Results reveal that inadequate heavy equipment and personnel incapacitated relevant government agencies are responsible for handling emergency and rescue during building projects collapse. Preliminary findings show developers' greed and systematic failures as the root cause of Nigeria's building project collapse (BPC). It categorised the root causes into three groups (developer's related-cause, design team related-cause and government entities related-cause). The study suggested measures to mitigate future happening. The emerged measures were grouped into a penalty, regulatory, byelaw act, technical and safety measures.

This study contributes to curbing the threat to social sustainability of housing provision in cities. It reveals the underlying perceived root cause of collapsed buildings in Nigeria's building industry. Also, it suggested feasible measures to mitigate BPC. These measures may be modified and adopted by other developing countries facing similar challenges.