The Far-Reaching Consequences of Job Insecurity: A Review on Family-Related Outcomes

Job insecurity (JI) appears a fairly stable job stressor in working life today and likely to impair employee well-being. This review article presents the key findings of studies examining the effects of perceived JI on family well-being (e.g., marital/parental role quality, work–family conflict). The results, based on 25 published peer-reviewed studies, suggest an association between JI and impaired family well-being. Thus, JI spills over into family life as proposed in the spillover theory of work–family interface. Furthermore, studies have found some evidence of crossover effects of JI from parents to children: parents’ JI relates to negative outcomes in children. These results support the view that JI is very likely a severe stressor not only for employees’ well-being and health but also for their families’ well-being. Limitations, future directions, and implications are also discussed.     

The Reorganization of the US Citizenship and Immigration Services (USCIS) and Its Effects

Public Organization Review - Few studies have assessed the consequences of reorganization on the perceptions of employees. The article examines the effects of the reorganization of the US...     

Predictors of Nursing Home Admission: A Social Work Perspective

Abstract

Institutionalisation of geriatric patients is a growing trend in ageing societies, such as Singapore. Earlier studies focused on the sociodemographic profile and attributes of nursing home residents and applications, but neglected to address the predictors of nursing home admission from a social work perspective. The present retrospective study identifies independent risk factors that predispose a patient to a nursing home discharge from a general rehabilitation ward in a community hospital in Singapore, with a multidisciplinary emphasis on clinical intervention. Factor analysis results reinforced findings that functional impairment and dementia are consistent predictors of nursing home admission. Multivariate logistic regression analysis showed that positive predictors of nursing home admission include older age, length of hospital stay, low socioeconomic status, dementia, and functional disability. Social work interventions include early referrals to the medical social worker, so that options for social and family support can be explored prior to deciding to place patients in a nursing home. Other interventions include suitable family therapy and counselling for patients and their families.     

Municipal Groundwater Management: Optimal Allocation and Control of a Renewable Natural Resource

We study a municipal groundwater management problem to determine optimal allocation and control policies in the presence of water transfer opportunities. We establish and characterize threshold polices governing export or import decisions of a given municipality. In the spirit of the Triple Bottom Line (3BL), we ascertain that exporting (importing) water through a water market defined by an exogenous export/import price is detrimental (beneficial) to both society and the environment within the municipality. In contrast, fixed quantity trading between two municipalities defined by an endogenously negotiated export/import price can have positive as well as negative impacts from a global 3BL perspective. In particular, typical trading scenarios that occur between municipalities can be detrimental to the environment. We also study the implications of privatization, and find that a privatized municipality would be more (less) likely to export (import) water as compared to its non‐privatized counterpart, resulting in negative implications for society within the municipality. However, if exports are banned, privatization can benefit the environment by mitigating the damage caused by the extraction differential, a phenomenon analogous to the green paradox. Moreover, careful and restricted privatization of municipalities can lead to positive global 3BL impacts from fixed quantity trading.     

Grocery Perishables Management

In this article, we study the joint pricing and inventory control problem for perishables when a retailer does not sell new and old inventory at the same time. At the beginning of a period, the retailer makes replenishment and pricing decisions, and at the end of a period, the retailer decides whether to dispose of ending inventory or carry it forward to the next period. The objective of the retailer is to maximize the long‐run average profit. Assuming zero lead time, we propose an efficient solution approach to the problem, which is also generalized to solve three extensions to the basic model. A feature of the present study is that we consider explicitly the influence of perishability on the demand. Among the insights gathered from the numerical analysis, we find that dynamic pricing aids extending shelf life and when disposal incurs a lower cost, or even a positive salvage value, the retailer is induced to dispose earlier since the benefit of selling new inventory offsets the loss due to disposal. We also observe that the faster the perceived rate of deterioration, the lower the threshold of the ending inventory for disposal. Perhaps a bit counter‐intuitive, maximizing profits does not mean eliminating disposals or expirations.     

Comparisons of computational methods for clustered binary data

Clustered binary data are common in medical research and can be fitted to the logistic regression model with random effects which belongs to a wider class of models called the generalized linear mixed model. The likelihood-based estimation of model parameters often has to handle intractable integration which leads to several estimation methods to overcome such difficulty. The penalized quasi-likelihood (PQL) method is the one that is very popular and computationally efficient in most cases. The expectation–maximization (EM) algorithm allows to estimate maximum-likelihood estimates, but requires to compute possibly intractable integration in the E-step. The variants of the EM algorithm to evaluate the E-step are introduced. The Monte Carlo EM (MCEM) method computes the E-step by approximating the expectation using Monte Carlo samples, while the Modified EM (MEM) method computes the E-step by approximating the expectation using the Laplace's method. All these methods involve several steps of approximation so that corresponding estimates of model parameters contain inevitable errors (large or small) induced by approximation. Understanding and quantifying discrepancy theoretically is difficult due to the complexity of approximations in each method, even though the focus is on clustered binary data. As an alternative competing computational method, we consider a non-parametric maximum-likelihood (NPML) method as well. We review and compare the PQL, MCEM, MEM and NPML methods for clustered binary data via simulation study, which will be useful for researchers when choosing an estimation method for their analysis.     

Extending Financial Portfolio Theory for Product Management*

This paper attempts to modify financial portfolio theory for application in product portfolio decisions. The proposed multiperiod portfolio framework should help marketers in allocating scarce corporate resources to various competing products as well as contribute to developing a body of theory to solve an important problem in marketing management. Managerial and theoretical implications are discussed.