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This study systematically assesses and empirically examines the research question: How do social skills influence resource acquisition and social performance? Specifically, this study applies RBV theory from strategy to link social skills, resource conditions and the performance of social enterprises.

For this, we surveyed social enterprises in Korea to collect data and used SPSS 18.0 for hierarchical regression analysis.

In the Korean context, first, the results show that all social skills of social entrepreneurs are positively related to social performance. Second, among independent variables, self-promotion is positively associated with financial support and expressiveness is positively associated with marketing support. However, the rest of the independent variables have no significance. Finally, obtaining financial support from their partner mediates the relationship between self-promotion and social ventures' social performance, and obtaining marketing support from their partner mediates the relationship between expressiveness and social ventures' social performance.

This study provides two contributions. First, this is the first study to apply and test the RBV systematically and empirically in the context of social enterprises. Second, the results suggest that social skills and support types are important to social value creation.

Public-private partnership (PPP) power projects are associated with varying risk factors. This paper aims to develop a fuzzy quantitative risk allocation model (QRAM) to guide decision-making on risk allocation in PPP power projects in Ghana.

A total of 67 risk factors and 9 risk allocation criteria were established from literature and ranked in a two-round Delphi survey using questionnaires. The fuzzy synthetic evaluation method was used in developing the risk allocation model.

The model’s output variable is the risk allocation proportions between the public body and private body based on their capability to manage the risk factors. Out of the 37 critical risk factors, the public sector was allocated 12 risk factors with proportions = 50%, while the private sector was allocated 25 risk factors with proportions = 50%.

To the best of the authors’ knowledge, this research presents the first attempt in Ghana at endeavouring to develop a QRAM for PPP power projects. There is confidence in the model to efficiently allocate risks emanating from PPP power projects.

This study aims to examine the association between community engagement, community commitment and sustainability of public–private partnership (PPP) projects in Uganda.

This study adopted a cross-sectional and quantitative approach. Data were collected using a questionnaire from 42 PPP projects in Uganda.

The study found that community engagement and commitment are all positively and significantly associated with the sustainability of PPP projects in Uganda. Results also show that community commitment mediates community engagement and project sustainability.

The study results imply that for sustainability to be achieved, communities must be engaged in project activities such as planning, design and implementation to boost their commitment to project sustainability.

The sustainability of PPP projects is an emerging phenomenon. This paper contributes to scanty literature on ensuring the sustainability of PPP projects from a developing country’s perspective.

Public–Private Partnerships (PPPs) are crucial to the procurement of global infrastructure projects. Moreover, a price mode based on a cluster of core concessionary items is key to the delivery of value-for-money and successful project outcomes. However, existing research has yet to fully identify PPP concessionary items, nor yet described the range of practical price modes. This study provides taxonomy of core concessionary items impacting PPP projects, systematically classifies price modes, and assesses the applicability and risk impacts of those price modes on PPP projects.

This study adopts a comparative case study method in analyzing core concessionary items and alternative price modes. China is taken as the context, as it is one of the world’s largest PPP markets. In ensuring research validity and reliability, diverse data sources are utilized, with a graphic content analysis tool developed to capture the structure of price modes.

Eight PPP price modes are identified. These are: (1) UP (Unit Price) mode, (2) ALS (Annual Lump Sum) mode, (3) IRR (Internal Rate of Return) mode, (4) RP (Return for Investing Capital (RIC) - Profit Rate of O&M (PROM)) mode, (5) RFP (RIC - Financing Interest Rate (FR) - PROM) mode, (6) RFPL (RIC - FR - PROM - Lower Limit of User Charge (LLoUC)) mode, (7) RFL (RIC - FR - Lump Sum/Fixed Unit Price O&M Contract (LSOM/FUP)) mode, and (8) RFLL (RIC - FR - LSOM/FUP - LLoUC) mode. Other main findings are as follows: (1) Five risk allocation configurations can be achieved via these price modes. Yet while different price modes enable the allocation of specific risks, these do not always align with contracting parties’ original intentions. (2) IRR and RP modes may be less applicable in general because of their vulnerability in allocating critical risks and capacity for spurring opportunistic behavior.

By depicting the paths by which concessionary items in price modes affect cash flow, a systematic analysis of price modes was conducted exposing structural characteristics, along with risk allocation choice implications. The study is unique in: (1) Providing a systematic classification of PPP price modes used in PPP projects, (2) Presenting a comprehensive identification and streamlining of concessionary items in PPP practice, and (3) Analyzing the risk effects of different price modes. Together, these outcomes offer a hitherto unavailable perspective on PPP project risk management. The value of the study lies in the following: (1) Existing studies employ diverse concessionary items, but their applicability varies. This study offers an overarching framework facilitating decision-making in selecting appropriate PPP price modes and in determining concessionary items. (2) This study adds to the understanding of PPP price modes in significant ways that will aid local governments and potential sponsors in crafting and administrating more workable contract designs.

Pre-construction of a project comprises stages that are pivotal for the procurement performance. It is defined as the duration from the project's initiation to construction. However, Private Public Partnerships (PPPs) have been subjected to a long pre-construction, thereby leading to an inefficient development process. Therefore, the purpose of this paper is to pay attention to the influencing factors elongating the pre-construction duration.

Based on data of 5,677 PPP projects between 2009 and 2021 in China, the authors adopt the Accelerated Failure Time (AFT) model in duration analysis to empirically analyze the following underlying dynamics determining the duration of PPP pre-construction stages: (1) policy uncertainty; (2) corruption; and (3) procurement method selection. To observe the influencing paths more specifically, the authors divided the pre-construction duration into the pre-tendering period and tendering period and regressed them separately.

The results indicate that the pre-construction duration is significantly prolonged with increased policy uncertainty and corruption degree as well as the use of tendering methods. Meanwhile, the above factors have a greater impact on the pre-tendering period than the tendering period.

The contribution of this study is twofold: (1) theoretically, this paper provides new evidence on the impact of PPP policy uncertainty, corruption and procurement method selection on the pre-construction duration. It complements empirical studies on the factors elongating the time efficiency of PPPs projects. (2) In practice, it provides a specific path for the government to improve the time efficiency of PPPs.

This paper delves into the ex ante rates of return demanded by the private sector in Indonesian public–private partnership (PPP) infrastructure projects and the manifold factors emanating from project attributes that can influence these rates.

This paper analyzes feasibility studies of 37 PPP projects across different sectors. The studies were carefully selected based on relevance, completeness and validity of data. The analysis uses statistical techniques, including Levene’s tests, t-tests, ANOVA tests, Cohen’s effect size and Pearson correlations, to explore differences in cost of capital and excess returns across various attributes.

Based on the statistical analysis, no significant difference exists between the excess return of 200 basis points (bps) and the equity excess return of 0 bps. This suggests that the eligibility criteria for PPP projects require an internal rate of return (IRR) equal to the weighted average cost of capital plus 200 bps or an equity IRR equal to the cost of equity. The variations in the tested variables among diverse project attributes do not exhibit statistically significant disparities, even though specific attributes display moderate to high effect sizes.

This paper represents one of the first attempts to examine the rates of return demanded by the private sector in the context of Indonesian PPP projects. It comprehensively explores the factors that influence these rates, drawing on insights derived from feasibility studies.

Demand for private investment in infrastructure, notably in the power sector remains high, and this is anticipated to expand with the passage of time. Very little research currently exists on the power sector and specifically the private sector influencing factors (PSIFs) for entering into public–private partnerships (PPPs). The purpose of this study is to explore influencing factors for private sector participation in PPP power projects in Ghana.

Using purposive and snowball sampling techniques, questionnaires were used to gather responses from experts in the PPP power sector domain in a two-round Delphi survey. Reliability analysis was conducted using Cronbach’s alpha coefficient and level of agreement tested using Kendall’s concordance. Mean score ranking, analysis of variance (ANOVA) and Chi-square test were the main analysis conducted on the influencing factors.

The most significant PSIFs were: obtaining of investment support; improvement in private sector’s international image; synergy with public sector; sharing of risks; and gaining of profits. From ANOVA results, all the influencing factors had no significant different perception between the number of years in PPP practice and the motivations for the private sector entering into PPP power projects. Using Chi-square, the association between the variables indicated they were statistically significant.

The findings in this study are significant for multinational power generation firms that seek to enter the Ghanaian energy sector to help fill the generation gap and deficit.

The output of this research contributes to the checklist of influencing factors for private sector participation in PPP power projects and enhances the development of PPP practice.