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This paper aims to examine the link between the corporate social responsibility (CSR) communication efforts of companies and their ability to obtain public procurement contracts.

The authors are exploiting a database with the number of public procurement contracts won by SBF 120 companies in France and a constructed CSR index over the period of 2007–2015. The authors provide estimates of the amount of public contracts won by those companies.

The results suggest a striking influence of CSR communication on the ability of firms to win contracts.

This study focused on the case of the SBF 120 companies under the French regulatory system and European directives, which are different from the obligations in North American countries. Second, our constructed CSR index may be too simplistic in nature, and its application is limited only to the French context. Third, we do not have any evidence about the efficiency of well-ranked firms in our study. CSR reporting is still considered to be a form of communication, even if formal, that can contain information that does not especially reflect reality, as the scandals of several companies have shown in recent years (e.g. Volkswagen, Eiffage, Enron).

Companies should consider Business-to-Government (B-to-G) market when investing in CSR actions.

This is one of the first empirical studies measuring the impact of CSR on the ability of companies to win public contracts.

The purpose of this chapter is to determine the optimal path of development of social entrepreneurship in Russia and Central Asian countries by performing a scenario analysis of the development of social entrepreneurship and analyzing the opinions of interested parties regarding the outcome of social entrepreneurship in Russia and Central Asian states. The authors’ recommendations for the practical implementation of the optimal path of social entrepreneurship development are described.

The scenario analysis of statistical data showed that the existing practice of standardization of social companies’ activities hinders their executing their functions on raising the quality of life. With the expansion of freedom of social entrepreneurship, the population’s quality of life grows; on the contrary, the increase of state regulation leads to its reduction. The findings show that social entrepreneurship in Russia and Central Asian countries is interested in private investments and social companies’ employees. That is why the representatives of these categories of concerned parties support de-regulation. Consumers of social goods and services are interested in obtaining them freely and thus prefer standardization.

This chapter presents a new direction of social entrepreneurship analysis – by determining the correlation between economic freedom and quality of life. This opens an opportunity for thorough social entrepreneurship research based on authentic and objective quantitative (statistical) data. The obtained conclusions and offered recommendations allow using the mechanism of public–private entrepreneurship for turning social entrepreneurship into something more valuable and useful – a tool for increasing the quality of the population’s life.

In this conceptual chapter we examine the impact of the institutional role of public social policy as opposed to the individual role of private social entrepreneurship on the process of social change and value creation.

We review the above fields in order to identify their common and distinctive characteristics. We also examine how each contributes to social value creation and in which way these two sources of social value creation can interact in order to maximize their positive impact.

The value of our work relies on the development analysis reveals that the intersection between social policy and social entrepreneurship constitutes one of the possible responses to the growing uncertainty in the global economy and society. In a conceptual level, the findings of our theoretical inquiry allow us to provide a framework for better understanding the nature and the possible implications of social entrepreneurial/policy activities that allows the appropriate selection of the proper actions to be made for theorists, practitioners, and policy-makers alike.

Our work contributes to existing literature by providing views on understanding how the different forms of organizational actions (public policy vs. social entrepreneurship) act toward social value creation; and by contributing to the understanding of their similarities and differences and the distinctive frameworks within which they unfold.

The purpose of this article is to determine the future proportion and variants of usage of human intellect and artificial intelligence (AI) in entrepreneurship of industry 4.0 that fits social entrepreneurship the most. It could be convergence (simultaneous utilization during the same entrepreneurial processes with the emphasis on unique features by the terms of the competition) or divergence (usage during different business processes by the terms of labor division).

The authors determine the influence of usage of human capital and AI on the efficiency of social entrepreneurship. The authors identify the perspective directions of usage of AI in social entrepreneurship and evaluate the readiness and interest in the implementation of these directions of concerned parties. The authors also model the optimal proportions and the variant of usage of human intellect and AI in social entrepreneurship in the conditions of Industry 4.0 in the future (until 2030).

It is found that social entrepreneurship will use the opportunities of Industry 4.0 for optimization of its activities until 2030, but will refuse from full automatization, using human intellect and AI at the same time.

The most perspective directions of application of AI at social companies are a collection of social goods and services, marketing studies and promotion of social goods and services. Neither convergence nor divergence of human and artificial intellectual capital does not fully conform to the interests of concerned parties. The most preferable (optimal) variant of usage of human intellect and AI in social entrepreneurship in the Industry 4.0 is human intelligent decision support.

This paper aims to determine the trends and prospects of the development of social entrepreneurship in Russia and Asian countries.

The methodology includes trend, regression, and correlation analysis and scenario (imitation) modeling and elaborates on perspectives and recommendations for further development of social entrepreneurship in Russia and Asia.

Despite the active development of social entrepreneurship in Russia and Asian countries (its share in the structure of GDP of these countries constituted 2.6% on average in 2018), it accounts for a small contribution to domestic development of socio-economic systems. These countries of Asia in 2018 were peculiar for low level of social freedoms (70th position in the world), low level of healthcare (51st position), moderate level of ecological effectiveness (61.33 points out of 100), moderate level of education (0.767 points out of 1) and low level of development of infrastructure (39 points out of 100). In the provision of social freedoms and healthcare, social entrepreneurship is least developed and is peculiar for a tendency for a decrease. The difference between demand and offer of social entrepreneurship causes an imbalance of the market of social (non-profit, volunteer and charity) services in these countries. This imbalance is to be overcome with the recent tendency of digitization of social entrepreneurship in Russia and Asian countries.

Digitization occupies the last position among the factors of the development of social entrepreneurship. Tax stimulation of social entrepreneurship is preferable, so it is recommended to pay primary attention to it until 2022, for the provision of the balance of the market of social services.

The purpose of this study is to investigate the interplay between economic governance and privatization, and how these two instruments affect the entry mode choice of the foreign firm and the social welfare of the host country.

This study constructs a mixed duopoly model wherein one domestic public firm competes with a foreign firm and investigates the influence of economic governance investment on the domestic government’s optimal degree of privatization choice and the foreign firm’s entry mode choice.

This study shows that (1) better economic governance enhances the effect of privatization on output, thus resulting in a lower degree of privatization; (2) the optimal privatization policy of the domestic government is partial privatization irrespective of the foreign firm’s entry mode choice; (3) with optimal investment by the domestic government on economic governance, the optimal degree of privatization is higher under FDI than export, and the host-country welfare is also higher under FDI. In particular, this study demonstrates that better economic governance decreases the threshold of the degree of privatization when the foreign firm switches from export to FDI, implying that better economic governance stimulates the foreign firm to undertake FDI in the host country.

The findings shed some light on both the mixed ownership reform of the SOEs in China and attracting foreign capital inflow to improve the host country’s social welfare.

To the best of the authors’ knowledge, this study constitutes the first attempt to build a theoretical framework to explore how the interactions between economic governance and privatization influence the entry mode choice of the foreign firm.

The purpose of this paper is to examine the requirement that non-profit organizations recognize unconditional promises to give as assets and revenues in the year promises are received as mandated by Statement of Financial Accounting Standards (SFAS) No. 116.

Using the adoption of SFAS No. 116 and financial information reported on Internal Revenue Service Form 990, the study examines the requirement that non-profit organizations recognize unconditional promises to give as assets and revenues in the year promises are received. Combining insights derived from a model developed by Dechow, Kothari and Watts (1998) with the rationale applied by the Financial Accounting Standards Board (FASB) in mandating recognition treatment, it adopts the view that information about promises to give is relevant if it useful in assessing probable future cash inflows. The study also employs relative tests of predictive ability to assess competing specifications.

The study finds that recognizing unconditional promises to give as assets and as revenues in the year received improves predictions of next period’s cash inflows. It also finds that accrual-based contribution revenue consistently provides information content that is incremental to cash-based contribution revenue.

This paper has implications for several other lines of research as well. First, an ancillary concern expressed by many organizations in the non-profit sector was that the recognition of multi-year promises to give would adversely affect trends in long-term giving. In this regard, another promising line of inquiry would be to empirically test the Standard’s impact on the time-series properties of contributions and short- and long-term giving trends. Second, future research might consider conducting tests after partitioning by NTEE/NAICS classification, as well as substituting or supplementing the SOI data with financial statement data. Third, future research might consider applying the approach used in this study to other industries or groups for which market prices are not readily ascertainable. Data constraints, including the calculation of cash flow information indirectly from the balance sheet, impose limitations on this study.

This study documents that by recognizing unconditional promises to give as assets and revenues in the period received, donors, creditors and other users gain useful information about probable future cash inflows – a fundamental element of the accrual process and one of several important factors used to evaluate an organization’s ability to sustain future operations. This information is valuable to stakeholders and practitioners who rely on this information to make informed decisions. It is also helpful to standard setters in establishing guidelines that improve the usefulness of financial reporting for non-profits.

The paper contributes to existing literature by operationalizing, in a non-profit setting, a model that describes the relationship among revenues, accruals and cash flows. It fills a gap in the accrual literature regarding the relevance of non-profit revenue accruals. The study is the first to employ a relative information content approach to assess non-profit standards, which provides useful input to policy makers and end users. It affirms that many of the key conventions and elements embodied in the FASB Concepts Statements apply to non-profits as well, which heretofore has not been studied extensively. The results are also consistent with Accounting Standards Update 958, Not-for-Profit Entities, which requires that non-profits provide users with information about liquidity, including how they manage liquid resources needed to meet cash requirements for general expenditures within one year of the date of the statement of financial position.

The purpose of the research is to determine the perspective directions of state regulation of competition between human and artificial intellectual capital in Industry 4.0 and to develop scientific and methodological recommendations for their implementation. For this, the directions of state regulation of competition between human and artificial intellectual capital are described, monitoring of competition between human and artificial intellectual capital by the example of modern Russia (2019) is performed and scientific and practical recommendations for state regulation of competition between human and artificial intellectual capital are developed, with their approbation by the example of modern Russia (2019).

A method of expert evaluation is used for collection of the information and empirical data. The method of comparative analysis is used for comparing the successfulness of implementing the distinguished directions of state regulation of competition between human and artificial intellectual capital (4.1) according to the official statistics to their current evaluation according to the interested parties. Also, future evaluation (forecasts) according to the interested parties (until 2045) is determined.

It is substantiated that during evaluation of state regulation of competition between human and artificial intellectual capital in Industry 4.0, one cannot use only the official statistics, as these data are fragmentary and indirect. Fuller and more precise data are provided by assessment according to the interested parties. They allow determining the current and the future state of affairs and, based on it, compiling a forecast and developing a long-term strategy of state regulation of competition between human and artificial intellectual capital in Industry 4.0.

The perspective directions of state regulation of competition between human and artificial intellectual capital in Industry 4.0 are as follows: stimulation of competition in the market of intellectual capital, social risk management of the market of intellectual capital, managing international competition in the market of intellectual capital and ecological risk management of the intellectual capital market. As the experience of modern Russia shows, even at the initial stage of transition to Industry 4.0, the measures of state regulation of competition between human and artificial intellectual capital are not enough, but their deficit is moderate. In the course of development of Industry 4.0, the necessity for the measures of regulation will grow, and their deficit will increase. That's why there's a need for strategic approach to their implementation, which envisages their systemic reconsideration and supplementing. An author's algorithm is offered for this.

In this chapter, we estimate the allocative efficiency of Spanish airports in the pre-privatization period from 2009 until 2014. The estimation of an input-oriented distance system of equations allows us to calculate different allocative efficiency measures using two approaches. The results show that allocative inefficiencies exist for Spanish airports during this period. Moreover, in breaking down allocative efficiency changes by periods coinciding with different government strategies of privatization, we find important differences. In the initial period, when the government encouraged decentralized management of airports and privatization of the largest airports, allocative efficiency improved (from 2009 to 2012). In the second period, however, when the government focused on centralized airport management and privatization of the system as a whole (from 2012 to 2014), inefficiencies slightly increased again.