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The Build‐Operate‐Transfer (BOT) model of development of privatized infrastructure projects is implemented through the award of a concession to a private sector consortium which will finance, build and operate the facility. In a competitive BOT tender, the selection of the successful consortium does not depend on the lowest tolls offered by the tenderer. Rather, it is dependent on the ability of the promoter to provide the most competitive package of distinctive winning elements in its proposal during the final negotiations. The promoter must fully understand the government's needs and concerns and be able to address them through the right package of the winning elements. In this paper, these elements are developed from sub‐factors of the critical success factors of technical solution advantage, financial package differentiation and differentiation in guarantees.

Conventional theories of market entry assume choice availability. This investment assumption is subject to challenges in the power generation market of an emerging economy where the host government controls most key resources and market entry choices. With such constraints, entrants become heavily dependent on their host country partners. This study investigates how the resource dependency frameworks explain better in respect of some US power generation firms that manage to operate electricity facilities in China whereas some have to abort. Using cross‐case analysis, patterns emerged illustrate how two groups of entrants manage key resources differently.

Suggests that there are great opportunities for retailers in the mass rail transit (MRT) malls in Singapore due to their strategic location by bus and train station. States that maximum competitive advantage will be gained only if retailers understand consumer’s perception of the malls and how this affects their behaviour. Outlines the results of a survey of 250 shoppers across 5 malls showing that consumers value convenience, variety, cleanliness, and air‐conditioning. Argues that retailers need to advertise and display their merchandise while mall owners need to attract a good mix of tenants, maintain a good environment and provide good facilities. Suggests that communal activities held in the mall would make them more commercially viable.

Negative perceptions of political risk can prevent capital from being committed to support cross‐border investment. Information about risks that impact infra‐structure projects is often vague, imprecise, subjective, or ambiguous. Political risks in developing countries also often lack meaningful historical and numerical data. A novel fuzzy set approach for quantifying qualitative information on risks (QQIR) in structured finance transactions that bridges the gap between qualitative and quantitative risk assessment methods has been developed. The QQIR Method is validated empirically through the results of an international survey to determine the impact of perceived political risk on Asian infrastructure projects. The impact is measured by the effect on financial project criteria. The impact was assessed across 14 Asian countries and 14 infrastructure sectors. The survey findings are validated by triangulation of three data sets and employing non‐parametric statistics. The validation shows that in 77.5% of all observations the QQIR Method produces mean results that are within 0.85 standard deviations of the absolute values, without elimination of any seemingly unusual or unreasonable responses or data. The validation also shows that with increasing perceived risks, the costs of equity investment, debt finance, and insurance also increase. The QQIR Method is thus a valid tool to quantify perceptions on risks. In this case it has been applied to political risks, but the Method is generic and may be applied to any problem set in which perceptions can be structured and assessed with opinions.

As a pillar of integrated digital delivery (IDD), building information modeling demonstrates the tremendous potential to enhance productivity for the architectural, engineering and construction (AEC) industry worldwide. However, the implementation of digital solutions presents numerous challenges related to its adoption and implementation. Distinguishing a comprehensive set of critical factors can facilitate the construction professionals to execute their strategies in a properly planned manner, thus augmenting the possibilities of successfully implementing BIM in their organization. This study aims to identify critical success factors (CSFs) for BIM adoption and implementation in Singapore.

This study adopted structured empirical questionnaire survey. Relevant data were collected from the various stakeholders in Singapore AEC industry through an online survey questionnaire. Furthermore, data analysis was done using SPSS Statistics software in order to identify the key factors (KFs) based on which the CSFs were derived for BIM adoption and implementation during the construction phase.

From a set of 45 influencing factors, 35 KFs were derived after performing ranking analysis, from which a set of 26 CSFs were finally obtained based on the factor analysis methodology.

This study has identified the CSFs of BIM adoption in Singapore, as well as in the builders' perspective on how to enhance the digitalization in construction projects.

The purpose of this study is to identify driving factors and a quantitative model for implementing public-private partnership (PPP) projects in Ethiopia as a case study in emerging economies.

A review of the literature and semi-structured interviews were carried out to identify driving factors affecting the implementation of PPP projects in the Ethiopian context. Data were collected through a questionnaire survey within three months, with 59 validated responses; mean score technique and factor analysis were conducted. The fuzzy synthetic evaluation (FSE) method was applied to develop a driving index (DI) for implementing infrastructure PPP projects. Finally, a comparative analysis of top-five drivers was conducted between four emerging economies.

Mean values show that all driving variables are important. Through factor analysis, 22 identified driving variables were grouped into six factors, namely, benefit for public and private sectors, attention of private sector, social development, cost reduction, management ability of public sector and ability of private sector. The FSE method constructs a DI and shows that benefit for public and private sectors is the most crucial factor for PPP implementation in the context of Ethiopia. Apart from this, most driving forces for adopting PPP projects in these countries related to financial problems.

This study is one of the first integrate driving factors for PPP implementation. The index provides the decision-makers with a comprehensive tool to assess the needs of PPP implementation.

Based on the Chinese government's increased public‐private partnership (PPP) experience in the last decade, they have made a lot of efforts to improve the investment environment. This paper hence aims to conduct a more up‐to‐date evaluation of the potential risks in China's PPP projects.

As part of a comprehensive research looking at implementing PPP, a two‐round Delphi survey was conducted with experienced practitioners to identify the key risks that could be encountered in China's PPP projects. The probability of occurrence and severity of the consequence for the selected risks were derived from the surveys and used to calculate their relative risk significance index score.

The results showed that the top ten risks identified according to their risk significance index score are: government's intervention; poor political decision making; financial risk; government's reliability; market demand change; corruption; subjective evaluation; interest rate change; immature juristic system; and inflation. Further analysis was conducted on these risks so that the possible consequence, the most impacted parties, and the preferred allocation are discussed. Recommendations on commercial principles or contract terms between the Chinese government and private consortium are also provided.

These up‐to‐date findings concerning the probability and consequence of key risks would provide a valuable reference for private investors who are planning to invest in infrastructure projects in China.

Construction projects are well known for their complexity and ambiguity. These projects carry out higher risk than traditional ones because they entail high capital outlays and intricate site conditions. Poor financial management of these projects may lead to bankruptcy; therefore, effective cash flow management is essential. Although the peculiar characteristics of construction projects, the accuracy of cash flow forecasting has been a long lasting problem. The paper aims to discuss these issues.

Many unforeseen factors affect the cash flow forecasting of construction projects. Therefore, the objective of the presented research in this paper is to examine the impact of these factors on contractor's cash flow. A model has been established by integrating analytic hierarchy process and simulation to examine the impact of various factors on cash flow. Data on the selected factors have been collected through questionnaires from various agencies in North America and China.

Results show that the most significant factors are: change of progress payment, payment duration, financial position of the contractor, project delays, and poor planning. It also shows that the effect of cash inflow factors varied approximately from 9.7 to 16.3 percent with a mean value of 12.4 percent.

The implementation of the developed models are limited to few case study projects in testing the models. However, the developed models and framework are sound for future improvement. They are considered as a major step toward a broader cash flow planning.

The developed methodology and models play essential roles in decision-making process.

The developed model is expected to help contractors realistically forecast project cash flow under uncertainty. This may lead to more dependable and professional cash flow management, which might substantially reduce failures in construction business.