This chapter seeks to understand what motivates an investment in a social entrepreneurial initiative (SEI), in order to easy the fit between investors goals and the SEI proposals. It provides a benchmark for investors and a guide for entrepreneurs through the identification of the most valued investment criteria. Data were collected online between March and May 2019 from Schawb foundation, Skoll foundation, Ashoka and Yunus Social Business. It was analyzed by content analysis. The results obtained corroborate previous literature review as well as highlighted different perspectives, suggesting further research for a better understanding where theory can improve practice. This study contributes to a theoretical consolidation of social entrepreneurship research field by means of the identification of common points among the practice of global organizations and the theory. Exploring social entrepreneurship is important because it is a new way of doing business and delivering social value and maybe the better bet to achieving a more sustainable society.
PurposeSocial initiatives must disclose their results to access support. However, there is no theoretical consensus about how to do it. It is still necessary to understand the value creation in social initiatives because they may or not have economic goals. However, these goals serve to make the social ones feasible. This study aims to cut this Gordian knot by providing measures aligned to the value theory but developed by the social lens. It offers a non-economic-focused approach to dealing with assessment complexity and with multiple stakeholders’ needs for information.Design/methodology/approachA consolidation research path is suggested by three composed measures built upon tested and reliable scales. These value measures are discussed through narratives from Portuguese investors and social entrepreneurs in a mixed-methods design. Content analysis and online survey provided data for descriptive statistics, exploratory factor analysis and Cronbach's alpha test.FindingsThe analyses supported the value measures. Thus, they allow an effective way to assess and report the social value created. It also highlighted a potential use in preventive and corrective approaches helpful for several organizations that pursue social goals.Research limitations/implicationsThe measures were tested based on social entrepreneurs' opinions. Future studies can include beneficiaries' opinions, allowing comparisons that can help to set more realistic goals and better investment criteria.Originality/valueThe relationship between investors and initiatives can improve, boosting their impact on society. The measures can highlight prioritization choices that influence the way value is created. Hence, they serve as a sensemaking from a holistic standpoint.
Designing circular economy (CE) implies the adoption of a set of circular principles that support a society for the future. Understanding how CE principles influence attitudes to consume green products is a key factor aligned with consumer trends. This chapter aims to study how CE principles influence attitudes to consume green products in a particular case of fashion industry. Very few empirical studies on the perceptions of the fashion “users” exist. This chapter aims to bring some inputs to this topic. The methodology uses a path analysis study based on a sample of 110 respondents collected in a higher education institution in Portugal. The estimated model allows to test the relation between a set of variables, and the study reveals that: CE principles have a direct effect on the attitudes on the green products consumption in fashion industry in the sample considered.
In the last decades, the concern over natural resources, sustainability, and the current linear economic model based on continuous growth is one of the great challenges of our time. The assumption that there is an unlimited supply of natural resources and that the environment has an unlimited capacity to absorb waste and pollution is no longer a current trend, and growing attention has been paid to it worldwide. This chapter represents a contribution to the continuous conceptual development of circular economy and sustainability, and it also reviews how these two concepts have evolved over the past decades. An extensive literature review was conducted, employing bibliometric analysis to scrutinise the state of the art, the perspectives, the agreements and disagreements among these concepts and their correlation.
Social entrepreneurial initiatives (SEI) answer problems and needs that otherwise would remain unattended. Therefore, they provide high collective interest social value achieved by a stable, reliable, and sustainable operation. Because the economic goal is a means to accomplish the social aim, it is hard to overcome resource constraints. SEIs must prove innovation and efficiency to access funding. However, the investment criteria are usually circumstantial or abstract. Additionally, the theory lacks the recommendation to enlighten how to increase the chances to be funded. The literature does not offer consensual, consistent, empirically tested criteria to compare business models. To help address these issues, this paper provides a Delphi analysis of a social business model taxonomy. The following criteria selected interviews from a broad study: 1) have qualitative and quantitative data recorded; 2) represent different SEIs’ types in the taxonomy. Then, four invited scholars blindly reviewed the data. They are experts in social innovation, entrepreneurship, sustainability, and social psychology. Online meetings helped to solve doubts and build synthesis. All Delphi participants described their opinion about the taxonomy fit by e-mail. Results were also compared by previous statistical classification. The Delphi process happened from December 2020 to June 2021. The similarity between statistical and analytical results indicated that the taxonomy is an efficient tool to identify and compare elements of the social business model. The study made the taxonomy easier and more replicable, providing an analytical framework. Evidence can help social agents and investors to frame information and achieve better decision-making.
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