“Something More”: The Meanings of Marriage for Religious Couples in America

This study focused on how couples’ beliefs about marriage and religion shape the meanings they find in their marriage. Interviews about connections between religion and marriage were conducted with 57 Christian, Jewish, and Muslim couples in New England and northern California. Qualitative analyses found the major theme, common across faith traditions, was that marriage is a sacred union that is “something more": more than the self, more than the couple, and more than the family unit. To these couples marriage is divine and institutional and a vital support for their relationship. Our findings raise an interesting counterpoint to the current scholarly discourse about the deinstitutionalization and individualization of contemporary marriage. Institutionalized features of marriage may retain their strength in contemporary society as many religious couples, and perhaps many other couples as well, believe marriage is something more than the deinstitutionalized, private relationship that many scholars now see.     

Piecewise proportional hazards models with interval-censored data

We consider the piecewise proportional hazards (PWPH) model with interval-censored (IC) relapse times under the distribution-free set-up. The partial likelihood approach is not applicable for IC data, and the generalized likelihood approach has not been studied in the literature. It turns out that under the PWPH model with IC data, the semi-parametric MLE (SMLE) of the covariate effect under the standard generalized likelihood may not be unique and may not be consistent. In fact, the parameter under the PWPH model with IC data is not identifiable unless the identifiability assumption is imposed. We propose a modification to the likelihood function so that its SMLE is unique. Under the identifiability assumption, our simulation study suggests that the SMLE is consistent. We apply the method to our cancer relapse time data and conclude that the bone marrow micrometastasis does not have a significant prognostic factor.     

The Relationship Between Corporate Volunteering and Employee Civic Engagement Outside the Workplace in Russia

This paper discusses the relationship between corporate volunteering and civic engagement outside the workplace in Russia, proceeding from a mixed-method approach. The quantitative findings are based on a comparison between employees in 37 Russian companies who participated in corporate volunteering (N = 399) and those who did not (N = 402). Using binary logistic regression analysis, we demonstrate that employee participation in corporate volunteering is positively related to four forms of civic engagement outside the workplace: informal volunteering, formal volunteering, formal monetary donation, and informal monetary donation. In addition, we draw on information obtained from interviews with 10 corporate volunteers, as well as with all 37 company corporate volunteering managers, to develop a general explanation for why corporate volunteering might lead to civic engagement. We identify three primary explanations. First, trust in companies can be converted into increased trust in social institutions. Second, corporate volunteering can expose employees to other realities, thereby leading them to rethink their priorities. Third, corporate volunteering socializes employees to volunteering, thus making them more likely to incorporate volunteering into their personal repertoires of activities. Corporate volunteering appears to be an effective mechanism for stimulating civic engagement and volunteering infrastructure in post-communist countries.     

A new two-party bargaining mechanism

If resources and facilities from different partners need to be engaged for a large-scale project with a huge number of tasks, any of which is indivisible, decision on the number of tasks assigned to any collaborating partner often requires a certain amount of coordination and bargaining among these partners so that the ultimate task allocation can be accepted by any partner in a business union for the project. In the current global financial crisis, such cases may appear frequently. In this paper, we first investigate the behavior of such a discrete bargaining model often faced by service-based organizations. In particular, we address the general situation of two partners, where the finite Pareto efficient (profit allocation) set does not possess any convenient assumption for deriving a bargaining solution, namely a final profit allocation (corresponding to a task assignment) acceptable to both partners. We show that it is not appropriate for our discrete bargaining model to offer the union only one profit allocation. Modifying the original optimization problem used to derive the Nash Bargaining Solution (NBS), we develop a bargaining mechanism and define a related bargaining solution set to fulfil one type of needs on balance between profit-earning efficiency and profit-earning fairness. We then show that our mechanism can also suit both Nash’s original concave bargaining model and its continuous extension without the concavity of Pareto efficient frontier on profit allocation.     

Ensuring units invariant slack selection in radial data envelopment analysis models,and incorporating slacks into an overall efficiency score

This paper introduces a new methodology ensuring units invariant slack selection in radial DEA models and incorporating the slacks into an overall efficiency score. The CCR and BCC models are units invariant in their radial component, but not in their slack component, thus changing the units of measurement of one or more variables can change the models' solution. The proposed Full Proportional Slack (FPS) methodology improves the slack selections of the CCR and BCC models by producing slack selections that (a) are units invariant, thus producing fully units invariant models, (b) maximize the relative improvements represented by the slacks, and not their values, and (c) measure the full slacks that need to be removed from their corresponding variables. The FPS methodology is a fully oriented methodology first maximizing the improvements in the variables on the side of the orientation of the model. The Proportional Slack Adjusted (PSA) methodology incorporates the FPS slacks into an overall efficiency score, making it easier to interpret and use the results. The FPS and PSA methodologies are illustrated using an input oriented VRS Loan Quality DEA model with data from the retail branch network of one of Canada's largest banks.     

Single-machine batch delivery scheduling with an assignable common due window

This paper addresses a batch delivery single-machine scheduling problem in which jobs have an assignable common due window. Each job will incur an early (tardy) penalty if it is early (tardy) with respect to the common due window under a given schedule. There is no capacity limit on each delivery batch, and the cost per batch delivery is fixed and independent of the number of jobs in the batch. The objective is to find the optimal size and location of the window, the optimal dispatch date for each job, as well as an optimal job sequence to minimize a cost function based on earliness, tardiness, holding time, window location, window size, and batch delivery. We show that the problem can be optimally solved in O(n⁸)$O(n^8)$ time by a dynamic programming algorithm under a reasonable assumption on the relationships among the cost parameters. A computational experiment is also conducted to evaluate the performance of the proposed algorithm. We also show that some special cases of the problem can be optimally solved by lower order algorithms.     

Impact of product proliferation on the reverse supply chain

Product variety is one of the most important advantages in highly competitive markets. However, excessive product proliferation's reducing the profit margin has caused increased focus on developing a management method for maximal profit. In a closed-loop supply chain, product proliferation affects the reverse supply chain as well as the forward supply chain. Although increasing the number of product types can better satisfy diverse customer needs, complexity in the product recycling, remanufacturing, and resale processes may erode a firm's overall profits. In this study, we develop a mathematical model for analyzing a capacitated reverse supply chain consisting of a single manufacturer and multiple retailers. We reveal closed-form solutions for the optimal batch size and maximal profit, and discuss managerial insights into how the number of products and other factors can affect both batch size and profit. Finally, we investigate the relationship between product proliferation and the choice of logistics strategy.     

RFID‐Enabled Visibility and Retail Inventory Record Inaccuracy: Experiments in the Field

Accurate inventory records are key to effective store execution, affecting forecasting, ordering, and replenishment. Prior empirical research, however, shows that retailer inventory records are inherently inaccurate. Radio Frequency Identification (RFID) enables visibility into the movement of inventories in the supply chain. Using two different field experiments, the current research investigates the effectiveness of this visibility in reducing retail store inventory record inaccuracy (IRI). Study 1 used an interrupted time‐series design and involved daily physical counts of all products in one category in 13 stores (8 treatments and 5 controls) of a major global retailer over 23 weeks. Results indicate a significant decrease in IRI of approximately 26% due to RFID‐enabled visibility. Using an untreated control group design with pre‐test and post‐test, Study 2 expands the number of categories to five and the number of stores to 62 (31 treatment and 31 control stores). Results show that the effectiveness of RFID in reducing IRI varies by category (ranging from no statistically significant improvement to 81%). Results also suggest that RFID ameliorates the effects of known determinants of IRI and provide the key insight that the technology is most effective for product categories characterized by these determinants.     

Optimal Inattention to the Stock Market With Information Costs and Transactions Costs

Information costs, which comprise costs of gathering and processing information about stock values and costs of deciding how to respond to this information, induce a consumer to remain inattentive to the stock market for finite intervals of time. Whether, and how much, a consumer transfers assets between accounts depends on the costs of undertaking such transactions. In general, optimal behavior by a consumer facing both information costs and transactions costs is state‐dependent, with the timing of observations and the timing and size of transactions depending on the state. Surprisingly, if the fixed component of the transactions cost is sufficiently small, then eventually, with probability 1, a time‐dependent rule emerges: the interval between observations is constant and on each observation date, the consumer converts enough assets to liquid assets to finance consumption until the next observation. If the fixed component of transactions costs is large, the optimal rule remains state‐dependent indefinitely.     

The derivation of a brief Student Nurse Stress Index

The lack of an adequate measure of perceived sources of stress for student nurses led to the construction of the Student Nurse Stress Index (SNSI). Responses from 235 first-year student nurses to 35 items from the Beck and Srivastava Stress Inventory (Beck, and Srivastava, 1991), and 15 new items, were subjected to exploratory factor analysis using principal components analysis and oblimin rotation. A reliable 22-variable solution with a simple oblique structure including Academic load, Clinical sources, Interface worries, and Personal problems factors was obtained in this initial sample, and confirmed at an exploratory level in a further independent validation sample of 188 first-year students. Confirmatory factor analysis established the four-factor model in the first sample, but required that three variables load onto more than one factor. This more complex four-factor model was confirmed using independent data from the validation sample, and the total invariance of factor loadings and factor covariances of this more complex four-factor model was established in both data sets simultaneously using multi-sample techniques. The SNSI shows cross-sample factor congruence, good internal reliabilities, and concurrent and discriminant validity across a range of reporting conditions.