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China’s foreign aid efforts in Africa remain contentious. Chinese foreign aid tends to be different from “traditional” development assistance in that it frequently involves firms as the implementing agents of projects. Firms bring unique resources to public–private partnerships (PPPs) formed with government agencies, but their possible self-interested nature also gives rise to concerns over their development impact. Yet, on a larger scale, little is known about the characteristics of Chinese PPPs in foreign aid. Using project-level data available for 1,308 Chinese aid projects in 50 countries across Africa, the author characterizes the projects undertaken by firms and government agencies in a PPP and contrasts them to those executed by Chinese government agencies without firm involvement. This exploratory data analysis suggests that important differences apply, as Chinese PPPs tend to target different sustainable development goals (SDGs), work on the basis of distinct aid conditions, and implement projects that tend to be larger than those that are solely run by government agencies. Such observations raise important questions of an ethical, theoretical, and international nature, and warrant further research. The author develops a research agenda that aims at issues particularly important for business ethics scholars, organization theorists, and international business scholarship.

This study illustrates the economic and financial dynamics of the sector, analysing the evolution of the main ratios of profitability and financial structure of 1,559 Italian real estate companies divided into the three macro-regions: North, Centre and South, in the period 2011–2020. In this way, it is also possible to verify the responsiveness to the 2020 pandemic crisis.

The analysis uses descriptive statistics tools and the ANOVA method of analysis of variance, supplemented by the Tukey–Kramer test, to identify significant differences between the three Italian macro-regions.

The study shows the increase in profitability after the 2008 crisis, despite its reverberation in the years 2012–2013. The financial structure of companies improved almost everywhere. The pandemic had modest effects on performance.

In the future, other indices should be considered to gain a more comprehensive view. This is a quantitative study based on financial statements data that neglects other important economic and social factors.

Public policies could use this study for better interventions to support the sector. In addition, internal management can compare their company's performance with the industry average to identify possible improvements.

The research analyses an economic field that employs a large number of people, especially when considering the construction and real estate services covered by this analysis.

The study contributes to the literature by providing a quantitative analysis of industry dynamics, with comparative information that can be deduced from financial statements over the years.

Over a long period, even low inflation has an impact on portfolio value and households’ purchasing power. In such a context, inflation hedging should remain an important issue for investors. In particular, long-term investors, who are concerned with the protection of their wealth, seek to hold effective hedging assets. This study aims to demonstrate that residential assets in “Grand Paris” are a hedge against inflation and particularly against its unexpected component.

In this study, the physical residential markets in 127 communes in Paris and the Parisian first-ring suburbs are considered as potential asset classes. We simplified the analysis by clustering the 127 communes into five homogenous groups using ascending hierarchical classification (AHC). Then, we test the hedging ability of these groups within a mixed asset portfolios using both correlation and regression analysis.

This paper presents an analysis of the “Grand Paris” housing market and its inflation hedging ability with comparison to other financial asset classes. Results show that the five housing groups act as a highly positive hedge against unexpected inflation. Furthermore, cash and bonds seem to provide, respectively, a partial and an over hedge against unexpected inflation. Stocks act as a perverse hedge against unexpected inflation and provide no significant hedge against expected inflation. Also, indirect listed real estate demonstrates little correlation with inflation, which makes us reject its hedging ability contrary to physical residential real estate.

The inflation topic: although several researches exist that question the hedging property of real estate, very few concentrate on physical residential assets and to the best of the authors’ knowledge, this study is the only one that targets the “Grand Paris” area. Residential assets of the “Grand Paris” communes are confirmed to be a hedge against inflation and particularly against its unexpected component thanks to its capital appreciation rather than income one. Also, we show that the listed real estate in France (Sociétés d’Investissement Immobilier Cotée) does not provide the same hedging properties contrary to the US real estate investment trusts (REITs) who demonstrate this ability. Listed real estate could thus not be used interchangeably with housing to protect from inflation in the French market.

Protection of investors against inflation and in particular in the face of its return to France in 2022. Reassuring promoters and investors of the interest of residential investment projects in “Greater Paris” and of the potential that this holds.

Inflation takes a chunk out of the purchasing power of money and thereby erodes the real value of people’s finance. Investors and households who seek protection from inflation erosion should invest in direct housing, and in particular within areas that are experiencing an effective metropolization process.

The originality of the study is precisely relative to the geographical area studied. The latter has experienced favorable economic conditions for several years and offers interesting fundamentals to explore and exploit in investment strategies that prove capable of protecting against imminent inflation. The database is specific to this project and has been built through the compilation of several sources and with the support of BNP Paribas Real Estate.

This analysis examines the relationship between corruption and firm productivity in Vietnam.

The authors apply the system generalized method of moments estimation approach on a panel dataset constructed from comprehensive enterprise surveys covering all the sectors over the 2011–2020 period.

The results confirm a non-linear relationship between corruption and firm productivity. Where corruption is severe, leaving corruption alone tends to benefit firm productivity because efforts to control corruption are likely to cause greater delays. In less corrupt provinces, corruption appears to harm firm productivity while efforts to control corruption provide significant productivity gains. This U-shaped relationship is confirmed for small firms and those in the private sector sub-samples. Intriguingly, this study reveals that the U-shaped relationship does not apply to micro, medium, large firms, state-owned firms and foreign-invested firms because corruption is found to have no significant impact on productivity among these sub-samples. Changes in regulations after 2014 toward promoting a transparent business environment are shown to foster the positive impact of lowering corruption on firm productivity.

This study suggests that lowering corruption is beneficial for firm productivity at the micro level. However, where corruption is severe, monitoring corruption alone is likely to cause adverse effects on productivity due to increased bureaucratic delays. Institutional reforms might play an important role in leveraging the effects of lowering corruption on productivity in highly corrupt areas.

This paper sheds new light on the relationship between corruption and firm productivity in the broad existing literature and especially in the limited number of studies for Vietnam.

The present study assesses the commercial bank profit efficiency and its relationship to banking sector competition in a rapidly growing emerging economy, India from 2009 to 2019 using stochastic frontier analysis (SFA).

Lerner indices, conventional and efficiency-adjusted, quantify competition. Two SFA models are employed to calculate alternative profit efficiency (inefficiency) scores: the two-step time-decay approach proposed by Battese and Coelli (1992) and the recently developed single-step pairwise difference estimator (PDE) by Belotti and Ilardi (2018). In the first step of the BC92 framework, profit inefficiency is calculated, and in the second step, Tobit and Fractional Regression Model (FRM) are utilized to evaluate profit inefficiency correlates. PDE concurrently solves the frontier and inefficiency equations using the maximum likelihood process.

The results suggest that foreign banks are less profit efficient than domestic equivalents, supporting the “home-field advantage” hypothesis in India. Further, increasing competition drives bank managers to make riskier lending and investment choices, decreasing bank profit efficiency. However, this effect varies depending on bank ownership and size.

Literature on the competition bank efficiency link is conspicuously scant, with a focus on technical and cost efficiency. Less is known regarding the influence of competition on bank profit efficiency. The article is one of the first to examine commercial bank profit efficiency and its relationship to banking sector competition. Additionally, the study work represents one of the first applications of the FRM presented by Papke and Wooldridge (1996) and the PDE provided by Belotti and Ilardi (2018).

The purpose of this study is to examine the corruption prevalent in the distribution of COVID-19 palliatives during the lockdown and movement restrictions in the country. This study seeks to analyse the current state of corruption in the distribution of COVID-19 palliatives and public health facilities in Nigeria while also providing a legal insight and strategic blueprint to combat corruption. To this end, this study will address the current legal framework for combating corruption and build upon this to formulate a working strategy for tackling corruption in the future.

Using a doctrinal legal research methodology, this study draws upon existing literature, tertiary data sources and information from the Nigeria Centre for Disease Control. The collected data is analysed and compared with current literature to identify key findings. Rent-seeking and utilitarian theories of the law were examined to guide this study. This study offers useful insights into combating corruption. The use of this method is justified, as it enhances the credibility of the findings on the importance of strategies for future emergencies. This legal research approach is consistent with the law and can be easily verified. The empirical aspect of this study involved a survey of multidimensional health-care and economic data set of 36 states in Nigeria plus the Federal Capital Territory on COVID-19 in Nigeria. A survey linearised regression model was estimated to determine the influence of government revenue and public health-care facilities in the control of the virus spread in Nigeria.

This study reveals the need for emphasis on the imperative of combating corruption in the distribution of COVID-19 palliatives and establishing economic resilience through transparent and accountable practices, supported by legal frameworks.

Rent-seeking and utilitarian theories of law are evaluated because of their impacts on combating corruption. The limitation of this study is the intricacy of gathering data on COVID-19 palliatives corruption in Nigeria because of secrecy and the absence of reliable data on the subject.

Estimating the exact number of stolen palliatives and their fiscal impact on Nigeria's economy proves to be a formidable task because of the covert nature of corruption. This study equips policymakers in Nigeria with a better understanding of the legal challenges posed by corruption in the health care sector and provides an effective strategy to combat it.

The lack of reliable data on the extent of palliative theft hinders the ability of lawmakers to enact effective legislation and strategies for combating corruption in the distribution of COVID-19 palliatives and addressing future emergencies in Nigeria. The policy implications of this study can assist policymakers in Nigeria and other countries in formulating measures to combat corruption in the distribution of COVID-19 palliatives and other future emergencies. Furthermore, it recommends the overhaul of anti-corruption laws and mechanisms in Nigeria to ensure effective measures against corruption.

In conclusion, this study contributes to knowledge by proposing a legal model centred on people's participation to enhance transparency and accountability in future palliative distribution processes. This study recommends legal strategies that can effectively address corruption in future emergencies or shocks. This study proposes a strategic blueprint to tackle corruption in the future. This blueprint includes an analysis of existing laws and regulations, as well as potential policy changes and legislative reform. This study also includes recommendations for improved enforcement and oversight mechanisms and for improved public awareness and education. As part of this, this study considers the potential for public–private partnerships to increase transparency and accountability in public health and health-care services.

The main purpose of this paper is to examine the status of poverty and its reduction by following the inclusive development approach. This study is designed to examine the benefits obtained from development programs, assess the government’s commitment to alleviating social inequality, and its impacts on the redistribution of wealth and poverty reduction.

To evaluate the implementation of the various development schemes and enhance grass-roots participation, a survey was carried out on 540 households, selected through multistage stratified sampling techniques in three different states of Punjab. The study employed an exploratory factor analysis on 21 independent variables to identify the key factors influencing poverty reduction subsequently followed by the binary logistic regression to access the sectoral impact of inclusiveness on poverty reduction in Punjab.

Exploratory Factor analysis extracted six key factors from the selected 21 variables, also called statements: “'Housing Development Resources”; “Human Capital Variables”; “Livelihood Essentials”, “Medical and Family Welfare Benefits”; “Receiving Educational Benefits”; and Social Security Benefits’. Binary logistic regression revealed that Housing Development Resources, Human Capital Variables, and Receiving Educational Facilities, significantly predict the likelihood of poverty reduction with inclusive growth in Punjab.

To provide basic amenities to rural people, increased people’s participation, decentralized planning, extended irrigation facilities, improved equipped facilities, and improved cultivation techniques are pivotal. The Indian Government has implemented several programs and projects to develop and support rural households. However, these schemes have faced many challenges such as rigidity, non-adaptability to local conditions, late disbursements of funds, reallocation of funds to unrelated expenditures by some states, embezzlement, and bribery demands. Hence, the findings indicate the presence of pseudo-inclusivity in Punjab’s growth.

The study’s uniqueness lies in its focus on selected districts of Punjab and also its application of exploratory factor analysis and binary logistic regression to construct a statistical model from the selected variables.

The primary purpose of this study is to explore the relationship between the unsolicited proposal (USP) and the performance of private participation infrastructure (PPI) projects in developing countries.

The main data set for this study was collected from the World Bank database consisting of 8,951 PPI projects that occurred in developing countries from 1996 to 2020. Hierarchical logistic regression was applied for investigating the effects of USPs on project success. Three moderators, namely, control of corruption, presence of local sponsor and project size were also included in the model to test the impact of their interactions with the USP on the performance of PPI projects. Further, to assess the impact of the effect of USPs, the average marginal effect was calculated. The framework used in this study consists of 18 control variables, three moderators and one noncontrolled independent variable (the USP).

The results of hierarchical logistic regression indicate that USPs have a significant and negative effect on the success of PPI projects occurring in developing countries. The negative effect of a USP weakens with the presence of local sponsors and stronger control of corruption in the host country. However, contrary to the authors’ expectations, the results show that project size does not significantly affect the association between USPs and the success of PPI projects. Moreover, the results of average marginal effects show that the negative impact of USP on the success of PPI projects ranges between 2.4% and 3.8%.

This study quantifies the negative impact of USP on the success of PPI projects in developing countries, which will be helpful for the practitioners to understand the associated risk with USP projects. Furthermore, it also identifies the moderating roles of control of corruption and the presence of local sponsors on the relationship between USP and the success of PPI projects.

The main purpose of this paper is to explore whether the nature of innovation is accumulative or radical and to what extent past year accumulation of technology stock can predict future innovation. More importantly, the authors are concerned with whether a change of policy regime or a variance in the quality of technology will moderate the nature of innovation.

The authors examined a dataset of 3.6 million Chinese patents during 1985–2015 and constructed more than 5 million citation pairs across 8 sections and 128 classes to track knowledge spillover across technology fields. The authors used this citation dataset to calculate the technology innovation network. The authors constructed a measure of upstream invention, interacting the pre-existing technology innovation network with historical patent growth in each technology field, and estimated measure's impact on future innovation since 2005. The authors also constructed three sets of metrics – technology dependence, centrality and scientific value – to identify innovation quality and a policy dummy to consider the impact of policy on innovation.

Innovation growth is built upon past year accumulation and technology spillover. Innovation grows faster for technologies that are more central and grows more slowly for more valuable technologies. A pro-innovation and pro-intellectual property right (IPR) policy plays a positive and significant role in driving technical progress. The authors also found that for technologies that have faster access to new information or larger power to control knowledge flow, the upstream and downstream innovation linkage is stronger. However, this linkage is weaker for technologies that are more novel or general. On most occasions, the nature of innovation was less responsive to policy shock.

This paper contributes to the debate on the nature of innovation by determining whether upstream innovation has strong predictive power on future innovation. The authors develop the assumption used in the technology spillover literature by considering a time-variant, directional and asymmetric matrix to model technology diffusion. For the first time, the authors answer how the nature of innovation will vary depending on the technology network configurations and policy environment. In addition to contributing to the academic debate, the authors' study has important implications for economic growth and industrial or innovation management policies.

The study examines the effect of natural resources (NRs) and the control of corruption, voice and accountability and regulatory quality on carbon emissions in Africa. Aside from their individual effects, the moderation effect of institutional quality is assessed.

Data from 32 African countries from 2002 to 2021 and the fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) regression methods were used for the investigation.

In the long term, the NRs effect is sensitive to the estimation technique employed. However, quality regulatory framework, robust corruption control and voice and accountability abate any positive effect of NRs on carbon emissions. Institutional quality can be argued to moderate the CO2-emitting potentials of resource extraction in the selected African countries.

Enhancing regulation quality, enforcing corruption control and empowering citizens towards greater participation in governance and demanding accountability are essential catalyst to effectively mitigate CO2 emissions resulting from NRs.

The moderation effect of control of corruption, voice and accountability and regulatory quality on the NR–carbon emission nexus is examined.