Label‐ and Level‐Invariant Graphical Log‐Linear Models

We introduce two types of graphical log‐linear models: label‐ and level‐invariant models for triangle‐free graphs. These models generalise symmetry concepts in graphical log‐linear models and provide a tool with which to model symmetry in the discrete case. A label‐invariant model is category‐invariant and is preserved after permuting some of the vertices according to transformations that maintain the graph, whereas a level‐invariant model equates expected frequencies according to a given set of permutations. These new models can both be seen as instances of a new type of graphical log‐linear model termed the restricted graphical log‐linear model, or RGLL, in which equality restrictions on subsets of main effects and first‐order interactions are imposed. Their likelihood equations and graphical representation can be obtained from those derived for the RGLL models.     

Coopetitive Buyer–Supplier Relationship: An Investigation of Bargaining Power,Relational Context,and Investment Strategies

This study proposes an analytical approach combined with a behavioral experiment for a joint examination of the competitive and cooperative (i.e., coopetitive) relationship between a buyer and a supplier. Specifically, the article considers the scenario in which the buyer and the supplier invest in strategic capabilities to increase their relative bargaining power. The article examines how dynamic investments in strategic assets are influenced by the locus of bargaining power and by the underlying context (synergistic vs. adversarial) of the interfirm relationship. The dynamic evolution of bargaining power is also examined. A dynamic game model is considered to examine the evolution of investment strategies in critical resources and to investigate the issues of bargaining power in a buyer–supplier dyad. Equilibrium expressions for the investment strategies of the buyer and the supplier are presented and their implications for buyer–supplier relationships are examined. The behavioral experiment complements the analytical model and examines the correspondence between optimal behavior suggested by the analytical model and the boundedly rational behavior of decision makers in an experimental context. The results from the model and behavioral experiments suggest that the strategies are a function of the risk‐adjusted returns obtained from investments. The experiment shows that, in a synergistic relational context when the buyer maintains bargaining power, the investment shifts of the buyer and the supplier accord well with theoretical predictions. In an adversarial relational context, the results of the experimental study do not correspond well with that predicted by the theoretical model. The implications of the results are discussed and directions for future research are presented.     

Uncovering the Management Process: An Ethnographic Approach1

The continuing controversy over the extent to which labour management has been transformed in recent years has sustained considerable interest in the basic issue of how management regulates the employment relationship. However, two curious features of these burgeoning discussions are the neglect of small firms and the rarity of intensive fieldwork methods of investigation. This paper examines particular methodological issues arising from an ethnographic study of the small firm-dominated West Midlands clothing sector (Ram, 1994). The ethnographic approach was crucial to the unravelling of the complexities and tensions inherent in the management process. Insights generated by the method allow prevailing views of managerial practices in such settings to be questioned; and more generally, highlight the potential of ethnography as a means of management research.     

Models and Methods to Support a New Type of Inventory Performance Measure: The ESWSO

When analyzing a reorder point, order quantity (r, Q) inventory systems, one important question that often gets very little, if any, attention is: When a stockout occurs, how large is it? This paper is directed at researchers and practicing inventory planners with two objectives. First, we provide several models and algorithms to compute the Expected Shortages When a Stockout Occurs (ESWSO) for a variety of stochastic environments. We show that when ESWSO, is used in conjunction with the traditional fill rate measures it greatly enhances a planners ability to plan for shortages. Second, we develop two cost‐minimizing inventory models—one addressing the backorder and the other the shortage scenario—to show how the ESWSO can be seamlessly integrated into an inventory‐cost framework to specify lot sizes and safety stocks.     

The Impact of Imperfect Processes on Production Run Times

This paper investigates the interaction between the economics of production and imperfections in the production process. Specifically, this paper is the first to devise a model in an attempt to provide managers with guidelines to choose the appropriate production run times to buffer against both the production of defective items and stoppages occurring due to machine breakdowns. In addition to providing several structural properties of the model, we show that a manager will always incur a cost penalty when (s)he uses the results of two oft‐cited models‐the EMQ (Economic Order/Manufacturing Quantity) and the NR‐E (No‐Resumption, Exponential machine breakdown)‐to determine production run times.     

Planned Lead Times in Multistage Systems

This study investigates the impact of planned lead times on performance in multistage manufacturing where material requirements planning is used in a make-to-stock environment. We simulate a variety of different operating environments and find: (1) planned lead times are important to customer service levels under all operating environments examined, but have a smaller impact on inventory investment; (2) tight due dates introduced by short planned lead times hurt customer service without saving much inventory; (3) small increases to tight planned lead times improve customer service substantially with small inventory increases; (4) co-component inventories change with planned lead times, and disparity between such inventories is a sign of poor timing coordination; (5) the fixed order quantity rule performs better than the periodic order quantity rule; and (6) tall product structure and large lot sizes require particular attention to planned lead times. The findings also extend the current understanding of planned lead times by including uncertainties such as forecast error, yield loss, and equipment reliability. The study concludes with a way to diagnose and improve poorly set planned lead times.     

Detecting multiple change points in piecewise constant hazard functions

The National Cancer Institute (NCI) suggests a sudden reduction in prostate cancer mortality rates, likely due to highly successful treatments and screening methods for early diagnosis. We are interested in understanding the impact of medical breakthroughs, treatments, or interventions, on the survival experience for a population. For this purpose, estimating the underlying hazard function, with possible time change points, would be of substantial interest, as it will provide a general picture of the survival trend and when this trend is disrupted. Increasing attention has been given to testing the assumption of a constant failure rate against a failure rate that changes at a single point in time. We expand the set of alternatives to allow for the consideration of multiple change-points, and propose a model selection algorithm using sequential testing for the piecewise constant hazard model. These methods are data driven and allow us to estimate not only the number of change points in the hazard function but where those changes occur. Such an analysis allows for better understanding of how changing medical practice affects the survival experience for a patient population. We test for change points in prostate cancer mortality rates using the NCI Surveillance, Epidemiology, and End Results dataset.     

Welfare gains of the poor: An endogenous Bayesian approach with spatial random effects

We introduce a Bayesian instrumental variable procedure with spatial random effects that handles endogeneity, and spatial dependence with unobserved heterogeneity. We find through a limited Monte Carlo experiment that our proposal works well in terms of point estimates and prediction. We apply our method to analyze the welfare effects generated by a process of electricity tariff unification on the poorest households. In particular, we deduce an Equivalent Variation measure where there is a budget constraint for a two-tiered pricing scheme, and find that 10% of the poorest municipalities attained welfare gains above 2% of their initial income.     

Blurring the Lines Between Civil Society,Volunteering and Social Movements. A Reflection on Redrawing Boundaries Inspired by the Spanish Case

Citizen participation is manifested through various concepts, such as activism, social movements, volunteering or civil society. The different ways of understanding popular engagement are often separated by delimitations that define them, particularly volunteering and civic action, as two highly differentiated forms of participation in the distinct academic disciplines: political science, volunteering studies, social movement studies or civil society theory. This article considers whether this basic theoretical differentiation can be problematised in the Spanish political context by exploring four paradigmatic cases of popular engagement, using qualitative case study methodology, specifically, a historic case from the 1990s and three more recent cases. It is hoped that the results of the study—which differentiates between organisational hybridity and fuzziness—will encourage reflection on the traditional boundaries between different forms of popular engagement.     

Episodic Volunteering at a Religious Megaevent

In preparation for Pope Francis's visit to Philadelphia and the 2015 World Meeting of Families, organizers looked for thousands of volunteers to help carry out these events. This is common for many one‐time and episodic events, such as large sporting events (from marathons to Special Olympics), arts and cultural events (such as festivals and concerts), and fundraising events. After the pope's visit, volunteers were asked to respond to a questionnaire about their experiences and the volunteer management of the event; 2,408 responded (34.4 percent). Data on motivation, who volunteered, recruitment, training, assignment, supervision, communication, satisfaction, and suggestions for improvement were elicited. We focused on episodic volunteering at a religious event and on a broad spectrum of issues pertaining to management of episodic volunteers. Our findings add to the knowledge regarding volunteer management and also add to conceptual understanding of the distinction between ongoing and episodic volunteers.