Pathways to social value and social change: An integrative review of the social entrepreneurship literature

Social entrepreneurship has emerged as an important means of addressing grand challenges. Although research on the topic has accelerated, scholars have yet to articulate an overarching framework that links the different pathways taken by social entrepreneurs with the positive effects of these efforts. To address this shortcoming, we conducted a systematic literature review which enabled us to conceptually differentiate between social value and social change as distinct outcomes of social entrepreneurship and identify seven pathways for achieving these outcomes. Building on our analysis, we outline a research agenda for questions pertaining to: the dynamics between social value and social change; how contextual factors and social entrepreneurs influence various pathways; design principles of business models and innovations that facilitate social value and social change; and defining, measuring, and ensuring accountability for social value and social change.     

Bootstrap Methods for Markov Processes

The block bootstrap is the best known bootstrap method for time‐series data when the analyst does not have a parametric model that reduces the data generation process to simple random sampling. However, the errors made by the block bootstrap converge to zero only slightly faster than those made by first‐order asymptotic approximations. This paper describes a bootstrap procedure for data that are generated by a Markov process or a process that can be approximated by a Markov process with sufficient accuracy. The procedure is based on estimating the Markov transition density nonparametrically. Bootstrap samples are obtained by sampling the process implied by the estimated transition density. Conditions are given under which the errors made by the Markov bootstrap converge to zero more rapidly than those made by the block bootstrap.