Who Receives What? The Influence of the Donation Magnitude and Donation Recipient in Cause-Related Marketing

Cause-related marketing campaign structural elements (CSEs) are individual message components that are selected for campaigns and have the ability to influence consumer intentions and behavior. In this study, the impact of donation magnitude (small; large) and donation recipient (branded and well-known; branded and fictitious; unbranded and well-known) on the dependent variables of consumer attitude toward the offer, attitude toward the alliance, and participation intention is explored by means of a 2?×?3 between-subjects experiment. Despite significant differences in familiarity with and attitude toward the donation recipient, significant differences between groups in terms of the dependent variables were not found. The nature of the sample (Generation Y), their attitude toward helping others and charitable organizations, social exchange theory, and equity theory are explored in an attempt to clarify the lack of significant differences pertaining to the dependent variables.     

Destination Social Business: Exploring an Organization's Journey with Social Media,Collaborative Community and Expressive Individuality

This paper delineates the main characteristics of the evolution of the organization as a social business in response to the socially networked marketplace. We advance the notion that the modern day firm is increasingly organized as a community according to the principle of collaboration. The main message is that the prominence of organizational structure is not redundant but needs to be complemented by collaborative community in response to market demands. In order to fulfill this complementary role, the concept of organization is profoundly changing. Based on recent theorizing, we review the role of collaborative community as a key characteristic of social business, provide an overview of its principles, show how social media can effectively facilitate and support collaborative community, and introduce the concept of expressive individuality. We provide illustrative examples that feature Dell. We conclude by identifying an agenda for further academic inquiry, and by specifying a large number of issues that researchers may address.     

Empirical evidence on the dependence of credit default swaps and equity prices

We investigate the common practice of estimating the dependence structure between credit default swap prices on multi‐name credit instruments from the dependence structure of the equity returns of the underlying firms. We find convincing evidence that the practice is inappropriate for high‐yield instruments and that it may even be flawed for instruments containing only firms within a sector. To do this, we model individual credit ratings by univariate continuous time Markov chains, and their joint dynamics by copulas. The use of copulas allows us to incorporate our knowledge of the modeling of univariate processes, into a multivariate framework. However, our test and results are robust to the choice of copula. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 29:695–712, 2009     

An Examination of Cheating and its Antecedents Among Marketing and Management Majors

This study examines cheating behaviors among 742 marketing and management majors at three public AACSB-accredited business schools. Specifically, we studied the simultaneous influence of demographic and attitudinal characteristics on: (1) reported prior cheating behavior; (2) the tendency to neutralize cheating behaviors; and, (3) likelihood of future cheating. We additionally examined the impact of in-class deterrents on neutralization of cheating behaviors and the likelihood of future cheating. We also directly tested potential mediating effects of neutralization on cheating behavior.We conducted independent assessments of the validity of the Smith et al. (2002) model of cheating behavior and its antecedents using structural equations modeling procedures. Results supported the differentiation of the theoretical constructs within the specified process model. Furthermore, tests of the aforementioned theoretical model indicated that the primary influences on future cheating were prior cheating, and the degree to which one neutralized prior cheating behaviors. Equally noteworthy, in contrast to previous research we found in-class deterrents to have no significant influence in either neutralizing behavior or future cheating proclivities.     

Forecasting temperature to price CME temperature derivatives

This paper seeks to forecast temperatures in US cities in order to price temperature derivatives on the Chicago Mercantile Exchange (CME). The CME defines the average daily temperature underlying its contracts as the average of the maximum and minimum daily temperatures, yet all published work on temperature forecasting for pricing purposes has ignored this peculiar definition of the average and sought to model the average temperature directly. This paper is the first to look at the average temperature forecasting problem as an analysis of extreme values. The theory of extreme values guides model selection for temperature maxima and minima, and a forecast distribution for the CME’s daily average temperature is found through convolution. While univariate time series AR-GARCH and regression models generally yield superior point forecasts of temperatures, our extreme-value-based model consistently outperforms these models in density forecasting, the most important risk management tool.     

Project Success and Executive Sponsor Behaviors: Empirical Life Cycle Stage Investigations

The role of the executive sponsor in achieving project success is important, yet rarely addressed. Recent research identifies behaviors that constitute the role of the executive project sponsor and evaluates how such behavior affects project success during different project stages. This study answers two research questions: (1) Does the relative importance of executive sponsor behavior vary significantly at different project stages? And (2) Does the relative importance of project success dimensions vary significantly within and across the different stages of completion? Results provide knowledge that will help executive sponsors decide how to invest their limited time and resources.     

Binary response panel data models with sample selection and self‐selection

We consider estimating binary response models on an unbalanced panel, where the outcome of the dependent variable may be missing due to nonrandom selection, or there is self‐selection into a treatment. In the present paper, we first consider estimation of sample selection models and treatment effects using a fully parametric approach, where the error distribution is assumed to be normal in both primary and selection equations. Arbitrary time dependence in errors is permitted. Estimation of both coefficients and partial effects, as well as tests for selection bias, are discussed. Furthermore, we consider a semiparametric estimator of binary response panel data models with sample selection that is robust to a variety of error distributions. The estimator employs a control function approach to account for endogenous selection and permits consistent estimation of scaled coefficients and relative effects.     

Redesigning nurse staffing plans for acute care hospitals

Johnson City Medical Center's approach to maximizing staffing in nursing units, particularly in acute care settings, had four primary goals: Identify opportunities to maximize the effectiveness of nurse staffing based on a review of core staffing schedules. Reduce cost duplication and improve workflow. Decrease the use of contract labor (with the goal of eliminating the use of contract labor). Develop financial dashboards for staffing that could be used by nursing managers.