What makes hybrid insourcing successful: A new public–private partnership model for social welfare services

Outsourcing has been a key policy tool for delivering a range of social services, and regarded as more effective than insourcing or direct government provision. At the same time, it has also caused many delivery issues such as principal‐agent problems, a lack of policy coordination, and poor‐quality welfare services. While the pendulum continues to swing between insourcing and outsourcing, we aim to propose a new public–private partnership model called the “hybrid insourcing model” and examine which factors influence the performance of the model. In South Korea, around 2010, the local government in Namyangju City was the first to implement the “Hope Care Center model,” a kind of hybrid insourcing model, which has been praised for its innovation and widely emulated by central and local governments. Our analysis utilizes data collected between December 2017 and January 2018 from public sector employees and civilian staff in Namyangju and a comparable city, A. From this, we draw a number of implications, both for theory and for policy. We argue that, for public–private partnerships, active cooperation and equality are the biggest factors in contributing to positive performance. These work alongside leaders with a clear vision and with employees' positive attitude.     

The Infrequency of Family Violence

We examined the frequency of domestic violence and verbal altercations relative to the level of domestic conflict using survey data from the United States and Korea. We found evidence that individuals are generally less likely to use violence during an altercation if the antagonist is a family member than if the antagonist is a stranger. People apparently have stronger inhibitions about hitting family members than about hitting strangers, and, as a result, domestic violence is infrequent relative to the level of domestic conflict. In addition, verbal altercations are more likely to occur in conflicts with partners and children than in conflicts involving strangers, suggesting that the relaxation of rules of politeness contributes to the expression of grievances and ultimately the use of violence in these relationships.     

Immigration cohorts and residential overcrowding in southern California

To what degree do immigrants reduce their high rates of residential overcrowding with increasing length of residence in the United States? This question is addressed through the application of a “double cohort” method that nests birth cohorts within immigration cohorts. This method enables duration of immigration effects to be separated from aging effects as cohorts pass through life course phases, when family sizes may be growing or shrinking. The analysis finds that cohort trends differ sharply from the cross-sectional pattern observed at a single point in time. Cohorts’ growth in income is found to contribute substantially to the decline in overcrowding over time. Cohort trends among Hispanic immigrants, however, diverge from those among others, indicating much less decrease in overcrowding and even increases over certain age spans.     

Two‐sample empirical likelihood ratio tests for medians in application to biomarker evaluations

The median is a commonly used parameter to characterize biomarker data. In particular, with two vastly different underlying distributions, comparing medians provides different information than comparing means; however, very few tests for medians are available. We propose a series of two‐sample median‐specific tests using empirical likelihood methodology and investigate their properties. We present the technical details of incorporating the relevant constraints into the empirical likelihood function for in‐depth median testing. An extensive Monte Carlo study shows that the proposed tests have excellent operating characteristics even under unfavourable occasions such as non‐exchangeability under the null hypothesis. We apply the proposed methods to analyze biomarker data from Western blot analysis to compare normal cells with bronchial epithelial cells from a case–control study. The Canadian Journal of Statistics 39: 671–689; 2011. © 2011 Statistical Society of Canada     

An integrated modelling approach for raw material management in a steel mill

An integrated modelling approach combining optimisation models with simulation is proposed for coordinated raw material management at steel works throughout the whole supply chain management process. The integrated model is composed of three components: ship scheduling, yard operation simulation and material blending models. The ship scheduling model determines which brands, how much and when they should be arrived, and the problem is modelled as mixed integer linear programming. The simulation model is used to simulate the whole processes from ships’ arrivals to the retrieval of the materials through the berthing and unloading the raw materials. Finally, the raw material blending model is developed for determining the brand and quantity of raw materials to be used. The proposed integrated modelling approach for raw material management has been successfully implemented and applied at steelwork to provide shipping schedules and predict future inventory levels at stock yards. By coordinating all the activities throughout the entire raw material supply chain management process, this article proposes an integrated approach to the problem and suggests a guideline by the appropriate simplification. The quantitative nature of the optimisation model and simulation facilitates an assessment of the risk factors in the supply chain, leading to an evaluation of a wide variety of scenarios and the development of multiple contingency plans. Further research is expected to supplement the ship scheduling models with heuristics for the idiosyncratic constraints of maritime transportation.     

Corporate Environmental Behaviors in Voluntary Programs: Does Timing Matter?*

Objective. Why do some firms participate in voluntary programs earlier than others? What conditions dictate whether firms participate in voluntary programs earlier rather than later? Current research on voluntary programs has not considered discrete processes in which corporate actors could have different motives and objectives in different time dimensions, that is, early versus late. Methods. We adopt a diffusion theory to disaggregate corporate voluntary participation behavior in the Environmental Protection Agency (EPA) sponsored Green Lights (GL) voluntary program. We focus on the GL participants during two periods—the early joiners in 1993–1994, and the late joiners in 1995–1996. Results. At the early diffusion stage, firms are more likely driven by the market motive that garners a “green” reputation, an important strategic asset to promote market competitiveness; at the late diffusion stage, firms are more driven by the institutional motive to improve their relationships with regulatory agencies and subsequently relieve regulatory pressures from them. Conclusion. We find that firms have different motives for GL participation at different diffusion stages. We suggest that policymakers who want to induce firms to join voluntary programs should pay more attention to program designs and implementation schemes that accommodate different corporate interests and objectives in different time orders of firms' participations in voluntary programs.     

Cluster analysis using different correlation coefficients

Partitioning objects into closely related groups that have different states allows to understand the underlying structure in the data set treated. Different kinds of similarity measure with clustering algorithms are commonly used to find an optimal clustering or closely akin to original clustering. Using shrinkage-based and rank-based correlation coefficients, which are known to be robust, the recovery level of six chosen clustering algorithms is evaluated using Rand’s C values. The recovery levels using weighted likelihood estimate of correlation coefficient are obtained and compared to the results from using those correlation coefficients in applying agglomerative clustering algorithms. This work was supported by RIC(R) grants from Traditional and Bio-Medical Research Center, Daejeon University (RRC04713, 2005) by ITEP in Republic of Korea.     

Intrinsic Priors for Model Selection Using an Encompassing Model with Applications to Censored Failure Time Data

In Bayesian model selection or testingproblems one cannot utilize standard or default noninformativepriors, since these priors are typically improper and are definedonly up to arbitrary constants. Therefore, Bayes factors andposterior probabilities are not well defined under these noninformativepriors, making Bayesian model selection and testing problemsimpossible. We derive the intrinsic Bayes factor (IBF) of Bergerand Pericchi (1996a, 1996b) for the commonly used models in reliabilityand survival analysis using an encompassing model. We also deriveproper intrinsic priors for these models, whose Bayes factors are asymptoticallyequivalent to the respective IBFs. We demonstrate our resultsin three examples.     

A genetic algorithm approach to developing the multi-echelon reverse logistics network for product returns

Traditionally, product returns have been viewed as an unavoidable cost of doing business, forfeiting any chance of cost savings. As cost pressures continue to mount in this era of economic downturns, a growing number of firms have begun to explore the possibility of managing product returns in a more cost-efficient manner. However, few studies have addressed the problem of determining the number and location of centralized return centers (i.e., reverse consolidation points) where returned products from retailers or end-customers were collected, sorted, and consolidated into a large shipment destined for manufacturers’ or distributors’ repair facilities. To fill the void in such a line of research, this paper proposes a nonlinear mixed-integer programming model and a genetic algorithm that can solve the reverse logistics problem involving product returns. The usefulness of the proposed model and algorithm was validated by its application to an illustrative example dealing with products returned from online sales.