Value drivers of social businesses: A business model perspective

Hybrid organizational forms that combine commercial and welfare institutional logics play an increasingly important role in addressing the grand societal challenges we face today. Building on the literatures on hybrid organizations and social business models, we explore the characteristics of social businesses from a business model perspective. This study seeks to better understand the particularities and value drivers of hybrid social purpose in contrast to purely commercial business models. We follow a grounded theory approach and our findings are based on interview data from 17 social business firms. Building on social businesses' identified particularities, we propose four value drivers of social business models: 1) responsible efficiency, 2) impact complementarities, 3) shared values, and 4) integration novelties. We link our findings to the literature, contributing new insights into social businesses models and implications for practitioners.     

Political competence and ideological constraint

Converse's definition of ideological contraint is expanded to provide for various respondent identified ideological dimensions rather than an all encompassing liberal-conservative dimension. Using this redefinition a sample of adults is shown to have high levels of ideological constraint. Ideological constraint is shown to vary with the degree of cognitive complexity and the degree of preference evaluability. The latter is a new concept that suggests that some issues will be easier for a respondent to demonstrate constraint on depending upon the availability and applicability of preference criteria. Salience is also shown to have a positive relationship with ideological constraint, but only when preference evaluability is high.     

An Integrated Risk Assessment Model of Township‐Scaled Land Subsidence Based on an Evidential Reasoning Algorithm and Fuzzy Set Theory

Land subsidence risk assessment (LSRA) is a multi‐attribute decision analysis (MADA) problem and is often characterized by both quantitative and qualitative attributes with various types of uncertainty. Therefore, the problem needs to be modeled and analyzed using methods that can handle uncertainty. In this article, we propose an integrated assessment model based on the evidential reasoning (ER) algorithm and fuzzy set theory. The assessment model is structured as a hierarchical framework that regards land subsidence risk as a composite of two key factors: hazard and vulnerability. These factors can be described by a set of basic indicators defined by assessment grades with attributes for transforming both numerical data and subjective judgments into a belief structure. The factor‐level attributes of hazard and vulnerability are combined using the ER algorithm, which is based on the information from a belief structure calculated by the Dempster‐Shafer (D‐S) theory, and a distributed fuzzy belief structure calculated by fuzzy set theory. The results from the combined algorithms yield distributed assessment grade matrices. The application of the model to the Xixi‐Chengnan area, China, illustrates its usefulness and validity for LSRA. The model utilizes a combination of all types of evidence, including all assessment information—quantitative or qualitative, complete or incomplete, and precise or imprecise—to provide assessment grades that define risk assessment on the basis of hazard and vulnerability. The results will enable risk managers to apply different risk prevention measures and mitigation planning based on the calculated risk states.     

Predictive factors of acculturation attitudes and social support among Asian immigrants in the USA

This study examines acculturation attitude and its relation to social support among Asian immigrants. The data were collected from 242 Korean, Indian and Filipino immigrants in the USA using the Acculturation Attitude Scale and the Social Support Index. Findings showed that Koreans had a less positive attitude toward acculturation than did Indian and Filipino participants. Acculturation attitude was positively correlated with educational level and English fluency. This study also found a negative correlation between acculturation attitude and social support. Social support from friends and English fluency were identified as significant predictor variables in determining the level of acculturation attitude. These findings not only contribute to social work education and practice, but also increase cultural sensitivity and awareness in working with these populations.     

Assessing the Concept of the ‘Insecure‐Other’ Category in the Cassidy–Marvin Scheme: Changes Between 4 and 6 Years in the English and Romanian Adoptee Study

We set out to explore the meaning of the attachment categories in the Cassidy/Marvin strange situation procedure, as employed in the home, using data from a longitudinal study of children adopted into UK families up to the age of 42 months from Romanian institutions, and of adopted children without the experience of institutional care––both groups being assessed at 4 and 6 years of age. Inter‐rater reliability was found to be good. Security (meaning the use of the parent as a secure base and no negative behavior on reunion) was the modal categorical rating in both the institution‐reared and comparison groups, but the category of anomalous non‐normative behavior (meaning a lack of any ordered attachment behavior as covered by the standard ratings), previously labeled ‘insecure‐other’, was more common in the institution‐reared children. Because this was unassociated with the usual manifestations of insecurity (such as avoidance or resistance) and because it was largely evident in interactions with the stranger, it is concluded that the adjective ‘insecure’ was not appropriate. Although this ‘insecure‐other’ category was associated with disinhibited attachment as reported by parents (meaning a lack of differentiation among adults, a willingness to go off with strangers and a lack of checking back with parents in anxiety‐provoking situations), it did not prove to be a good index of disinhibited attachment because changes over time in the ‘insecure‐other’ category were not associated with changes in the rate of disinhibited attachment. Also, whereas the rate of ‘insecure‐other’ fell markedly in the institution‐reared group between 4 and 6 years of age, it rose in the comparison group, raising queries over its meaning.     

Voting Technology,Political Responsiveness,and Infant Health: Evidence From Brazil

This paper studies the introduction of electronic voting technology in Brazilian elections. Estimates exploiting a regression discontinuity design indicate that electronic voting reduced residual (error‐ridden and uncounted) votes and promoted a large de facto enfranchisement of mainly less educated citizens. Estimates exploiting the unique pattern of the technology's phase‐in across states over time suggest that, as predicted by political economy models, it shifted government spending toward health care, which is particularly beneficial to the poor. Positive effects on both the utilization of health services (prenatal visits) and newborn health (low‐weight births) are also found for less educated mothers, but not for the more educated.     

Benefits of Hybrid Lateral Transshipments in Multi‐Item Inventory Systems under Periodic Replenishment

Lateral transshipments are a method of responding to shortages of stock in a network of inventory‐holding locations. Conventional reactive approaches only seek to meet immediate shortages. The study proposes hybrid transshipments which exploit economies of scale by moving additional stock between locations to prevent future shortages in addition to meeting immediate ones. The setting considered is motivated by retailers who operate networks of outlets supplying car parts via a system of periodic replenishment. It is novel in allowing non‐stationary stochastic demand and general patterns of dependence between multiple item types. The generality of our work makes it widely applicable. We develop an easy‐to‐compute quasi‐myopic heuristic for determining how hybrid transshipments should be made. We obtain simple characterizations of the heuristic and demonstrate its strong cost performance in both small and large networks in an extensive numerical study.     

Boosting multi-state models

One important goal in multi-state modelling is to explore information about conditional transition-type-specific hazard rate functions by estimating influencing effects of explanatory variables. This may be performed using single transition-type-specific models if these covariate effects are assumed to be different across transition-types. To investigate whether this assumption holds or whether one of the effects is equal across several transition-types (cross-transition-type effect), a combined model has to be applied, for instance with the use of a stratified partial likelihood formulation. Here, prior knowledge about the underlying covariate effect mechanisms is often sparse, especially about ineffectivenesses of transition-type-specific or cross-transition-type effects. As a consequence, data-driven variable selection is an important task: a large number of estimable effects has to be taken into account if joint modelling of all transition-types is performed. A related but subsequent task is model choice: is an effect satisfactory estimated assuming linearity, or is the true underlying nature strongly deviating from linearity? This article introduces component-wise Functional Gradient Descent Boosting (short boosting) for multi-state models, an approach performing unsupervised variable selection and model choice simultaneously within a single estimation run. We demonstrate that features and advantages in the application of boosting introduced and illustrated in classical regression scenarios remain present in the transfer to multi-state models. As a consequence, boosting provides an effective means to answer questions about ineffectiveness and non-linearity of single transition-type-specific or cross-transition-type effects.