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Prior research has emphasised the importance of the early phases of construction projects, as well as the difficulties of procuring engineering services – especially due to the uncertainties. Despite that, studies on the public procurement of engineering services are scarce. Although scholars have shown that uncertainty may affect the choice of control modes, the level of uncertainty that characterises services is not addressed by the two task characteristics: knowledge of the transformation process and output measurability. The purpose is to investigate organisational control in public procurement of engineering services.

The existing control model was adjusted in this study by conceptually adding uncertainty as a third aspect to the two task characteristics. A single case study of the Swedish Transport Administration was used. The empirical data, comprising 14 interviews with managers from the client and engineering consulting companies, were analysed using flexible pattern matching and visual mapping approaches and then illustrated using the model.

The public client did not base its choice of control modes on uncertainty, but rather on the other two task characteristics. Consequently, the service providers argued that the chosen control modes reduced their creativity, increased their financial risks and caused unclear responsibilities. This study therefore shows that uncertainty is an important factor to consider in the choice of control modes, both from a theoretical perspective and from the service providers' point of view. The developed model may therefore be useful for researchers as well as practitioners.

This study is the first attempt to add uncertainty as a task characteristic when choosing control modes. The results contribute to the scarce control literature regarding the procurement of engineering services for construction projects and the procurement of other services with high uncertainty.

The paper aims at addressing the following research questions: does institutional quality improve countries' environmental efficiency? And which pillars of institutional quality improve countries' environmental efficiency?

By specifying a directional distance function in the context of stochastic frontier method where GHG emissions are considered as the bad output and the GDP is referred as the desirable one, the work computes the environmental efficiency into the appraisal of a production function for the European countries over three decades.

According to the countries' performance, the findings confirm that high and upper middle-income countries have higher environmental efficiency compared to low middle-income countries. In this environmental context, the role of institutional quality turns out to be really important in improving the environmental efficiency for high income countries.

This article attempts to analyze the role of different dimensions of institutional quality in different European countries' performance – in terms of mitigating GHGs (undesirable output) – while trying to raise their economic performance through their GDP (desirable output).

1. The paper aims at addressing the following research question: does institutional quality improve countries' environmental efficiency?

2. We adopt a directional distance function in the context of stochastic frontier method, considering 40 European economies over a 30-year time interval.

3. The findings confirm that high and upper middle-income countries have higher environmental efficiency compared to low middle-income countries.

4. The role of institutional quality turns out to be really important in improving the environmental efficiency for high income countries, while the performance decreases for the low middle-income countries.

The paper aims at addressing the following research question: does institutional quality improve countries' environmental efficiency?

We adopt a directional distance function in the context of stochastic frontier method, considering 40 European economies over a 30-year time interval.

The findings confirm that high and upper middle-income countries have higher environmental efficiency compared to low middle-income countries.

The role of institutional quality turns out to be really important in improving the environmental efficiency for high income countries, while the performance decreases for the low middle-income countries.

The study evaluates the accident-adjusted dynamic efficiency of public bus operators providing bus transportation services in eight major metropolitan cities of India.

The slack-based measure (SBM)–undesirable window analysis approach is used to gauge the dynamic efficiency levels and identify the sources of inefficiency in bus transportation services. This innovative approach integrates the SBM model developed by Tone (2001, 2004) and the window analysis approach of Charnes et al. (1985). The main advantage of this approach is that one can explicitly incorporate the number of accidents in the production technology specification as an undesirable (bad) output and potently handle the issue of the “curse of dimensionality” in a small sample like ours.

The key empirical findings suggest wide variations in average efficiency levels across sample bus operators in metropolitan cities. The Chennai Transport Corporation is observed as the most efficient and consistent bus operator due to its most stable efficiency performance. The results additionally unveil that the role of managerial inefficiency was diminutive, and the scale-related issues were the real cause of sub-optimal or supra-optimal behaviour of sample bus operators in the resource-utilisation process.

There is an urgent requirement for effective policy intercessions to mitigate the sizeable observed inefficiency in the production process and resolve scale-related issues of public bus operators offering transit services in major metropolitan cities of India.

This paper is maybe the first to assess the dynamic efficiency of public bus transit systems in India's major metropolitan cities after treating accidents.

The purpose of this paper is to measure technical efficiency and examine its determinants while disentangling unobserved time-invariant heterogeneity from actual inefficiency using comprehensive household-level panel data.

This paper estimates technical efficiency based on the true random-effects stochastic production frontier estimator with a Mundlak adjustment. By utilising comprehensive panel data with 4,694 observations from 39 districts of four major maize-producing regions in Ethiopia, the author measures technical efficiency and examine its determinants while disentangling unobserved time-invariant heterogeneity from technical inefficiency. By using competing stochastic production frontier estimators, the author provides insights into the influence of farm heterogeneity on measuring farm efficiency and the subsequent impact on the ranking of farmers based on their efficiency scores.

The study results indicate that ignoring unobservable farmer heterogeneity leads to a downwards bias of technical efficiency estimates with a consequent effect on the ranking of farmers based on their efficiency scores. The mean technical efficiency score implied that about a 34% increase in maize productivity can be achieved with the current input use and technology in Ethiopia. The key determinants of the technical inefficiency of maize farmers are the age, gender and formal education level of the household head, household size, income, livestock ownership, and participation in off-farm activities.

While the findings of this study are critical for informing policy on improving agricultural production and productivity, a few important things are worth considering in terms of the generalisability of the findings. First, the study relied on secondary data, so only a snapshot of environmental factors was accounted for in the empirical estimations. Second, there could be other sources of unmeasured potential sources of heterogeneity caused by persistent technical inefficiency and endogeneity of inputs. Third, the study is limited to one country. Therefore, future research should extend the analysis to ensure the generalisability of the empirical findings regarding the extent to which unmeasured potential sources of heterogeneity caused by persistent technical inefficiency, endogeneity of inputs and other unobservable country-specific features – such as geographical differences.

This paper contributes to the literature on agricultural productivity and efficiency by providing new evidence on the influence of unobservable heterogeneity in a farm efficiency analysis. While agricultural production is characterised by heterogeneous production conditions, the influence of unobservable farm heterogeneity has generally been ignored in technical efficiency estimations, particularly in the context of smallholder farming. The value of this paper comes from disentailing producer-specific random heterogeneity from the actual inefficiency.

The amount of expenditure required to scale up smart infrastructure projects is often enormous. Public–private partnership (PPP) is one of the proposed and viable solutions for addressing the financial issues of smart infrastructure projects. However, the most important criterion in choosing PPP over other procurement methods is that the project under the PPP method should deliver the best value for money (VFM) while also including defined economic and social objectives, rather than relying exclusively on efficiency factors. While PPP provides a variety of advantages for developing infrastructure, significant challenges may arise as a result of smart infrastructure initiatives. Diverse PPP approaches have been used to build smart infrastructure around the world, with varying degrees of success. The purpose of this study is to identify the VFM factors that are suitable for smart infrastructure projects and to examine the impact of their interrelationships.

The methodology for this study consisted of three stages: identifying VFM factors in PPP for smart cities based on an extensive literature review, analyzing data from a sample of 90 PPP practitioners using a Likert scale questionnaire and estimating interrelationships among VFM factors using structural equation modeling (SEM).

After performing a SEM analysis on the gathered data, the best fitted measurement model consisted of 11 VFM factors acting as indicators of three latent variables for smart infrastructure projects (clear output specification for measuring performance, efficient dispute resolutions, optimized risk allocation and business models, improved and integrated community services, economic sustainability, appropriate capital structure and collaterals, smart asset management, diffusion of smart technologies, technical innovation, Ince) and three clusters of their interrelations (economic sustainability, integration drive, optimization and smart technology).

This research has resulted in a useful and readily applicable list of factors and clusters of value for money criteria for the implementation of PPP in smart infrastructure projects, assisting public sector management by providing a measure of pre-conditions that can be used as an assessment tool when determining whether a PPP should be used instead of conventional methods.

In addition to the theoretical and methodological contributions, this study produced a usable and readily adaptable list and clusters of value for money factors for the implementation of PPP in smart infrastructure projects.

This paper analyses the direct relationship between budget deficits and economic growth, the channels through which budget deficits inhibit growth and finally, the Granger causality between budget deficit and economic growth in South Africa over the period 1975 to 2020.

In a bid to control for endogeneity that is common in economic growth regressions, the author employed the dynamic ordinary least squares (DOLS) approach.

Towards analysing the direct relationship between budget deficit and economic growth, results show that a 10-percentage rise in the budget deficit slows economic growth by 0.2 percentage points. Results show that the growth inhibiting consequences of the budget deficit in South Africa are principally driven by negatively affecting private and public physical capital accumulation growth, as well as a drop in gross national savings. However, results show no evidence of a deficit reduction effect through long term-real interest rate. The findings reveal a one-way Granger causality running from budget deficits to economic growth.

Based on the findings in this article, expanding the fiscal deficit to support growth is not a viable policy option for the South African economy.

The originality of this paper lies in establishing the Granger causality between budget deficit and economic growth, thus adding to the scant literature, as well as establishing the channels through which budget deficit retards economic growth for the South African economy.

The demand for retirement villages globally has been increasing due to the rapid growth in the ageing population in recent years. To address the rising challenges in the retirement market, the public–private partnership (PPP) has become a feasible method to develop retirement villages. This paper aims to survey and examine the key success criteria (SC) for using the PPP approach in the retirement village sector.

An empirical questionnaire survey was conducted with experts experienced in international PPP and retirement village. The analysis was conducted using one-way analysis of variance, mean score analysis, Kendall’s coefficient of concordance and factor analysis.

Results indicate that out of the 16 recognized SC, the most significant ones are SC1: “Affordability”, SC11: “Reduced social isolation of residents” and SC14: “Improvement of emotional wellbeing of residents”. Furthermore, results from the factor analysis technique indicate that the 16 SC can be classified into five major factor groupings, and these include SCG1 – “Financial performance of project”; SCG2 – “Adherence to design and technical specifications”; SCG3 – “Adherence to local council/authority’s environmental health and socio-economic requirements”; SCG4 – “Social inclusion and risk management”; and SCG5 – “Advancement in emotional wellbeing and physical health of residents”.

The study will sufficiently assist retirement village stakeholders, retirement village project participants and related government authorities of the best measures to put in place to maintain the sustainable development of the global retirement village market.

Despite the widespread study and application of public-private partnerships (PPPs) since the 1980s, the field lacks a universally accepted definition that captures the concept's complexity. This study aims to offer a definition and foster a more substantive and comprehensive discourse on PPPs to improve communication and understanding between academics and practitioners from diverse disciplines and legislative backgrounds.

Grounded in the family-resemblance concept proposed by German philosopher Ludwig Wittgenstein, this study conducts a comprehensive literature review to identify core and non-core elements frequently cited in PPP descriptions. The authors used these findings to develop the PPP sunflower model as a structured framework for defining PPPs.

The analysis elucidates six core elements consistently present in PPP descriptions: clarity of roles and responsibilities, appropriate risk allocation and sharing, injection of expertise and resources, cooperation and teamwork, a bundle of services, and long-term contracts. Coupled with identified non-core elements, these core components comprise the PPP sunflower model, a structured framework for defining PPPs that accommodates their multi-faceted nature.

The PPP sunflower model distinguishes itself as a unique contribution to the PPP literature. It offers a rigorous theoretical framework that can elucidate the complexity of PPPs for various stakeholders. The model serves as a practical tool for evaluating the authenticity and viability of PPP projects. The study's novelty lies in its adoption of the family-resemblance concept, thereby providing a comprehensive, multi-dimensional framework that enhances the understanding of PPPs across different disciplines and legislative contexts.

Task complexity is one of the significant factors that influences and is used for forecasting employee performance and determining labor cost. However, the complexity level of tasks is unstructured, dynamic and complicated to perform. This paper develops a new method for evaluating the complexity level of tasks in the production process to support production managers to control their manufacturing systems in terms of flexibility, reliability to production planning and labor cost.

The complexity level of tasks will be analyzed based on the structuralist concept. Using the structure of task, the factors that significantly affect the task complexity in an assembly line will be defined, and the complexity level of the task will be evaluated by measuring the number of task components. Using the proportional 2-tuples linguistic values, the difference between the complexity levels of tasks can be compared and described clearly.

Based on the structure of the task, three contributory factors including input factors, process-operation factors and output factors that significantly affect the task complexity in an assembly line are identified in the present study. The complexity level of the task is quantified through analyzing the details of the three factors according to two criteria and six sub-criteria within the textile case study.

The proposed approach provides a new insight about the factors that have an effect on the complexity of tasks in production and remedies some of limitations of previous methods. The combination of experts' experience and scientific knowledge will improve the accuracy in determining the complexity level of tasks.

The purpose of this paper is to find a closed relation for the phase noise of LC oscillators.

The governing equation of oscillators is generally a stochastic nonlinear differential equation. In this paper, a closed relation for the phase noise of LC oscillators was obtained by approximating the I–V characteristic of the oscillator with third-degree polynomials and analyzing its differential equation.

This relation expresses phase noise directly in terms of circuit parameters, including the sizes of the transistors and the bias. Next, for evaluation, the phase noise of the cross-coupled oscillator without tail current was calculated with the proposed model. In this approach, the obtained equations are expressed independently of technology by combining the obtained phase noise relation and g_m/I_D method.

A technology-independent method using the g_m/I_D method and the closed relationship is provided to calculate phase noise.