Exploring the role of the Senate Majority Leader's political public relations efforts

Grounded in first- and second-level agenda building, this study explored the role of the U.S. Senate Majority Leader in shaping the salience of issues and issue attributes in news media coverage and policymaking in 2011. A total of 358 public relations messages, 164 newspaper articles, and 83 policymaking documents were analyzed. Significant correlations were found supporting agenda-building linkages at both levels. Different types of information subsidies were explored, including press releases, blog posts, Facebook posts, and Twitter messages.     

Employees’ prosocial behavioral intentions through empowerment in CSR decision-making

This study theorizes and empirically tests a conceptual framework to understand how a company can better motivate its employees to carry out persistent prosocial behavior and develop positive organization-employee relationships through corporate social responsibility (CSR) involvement. A managerial approach, employee participative decision making in CSR, is examined for its impact on the prosocial behavioral outcome among employees and the relational outcome for the organization. Furthermore, a psychological mechanism that emphasizes employees’ perceived need satisfaction is examined as the underlying explanation that drives the effectiveness of the managerial approach. The study results support that empowering employees to co-construct CSR decisions with top management is effective in satisfying employees’ basic psychological needs for autonomy, competence, and relatedness. This in turn increases the employees’ intention to maintain long-lasting involvement in CSR and improves their relationships with the company. This study provides important implications for public relations professionals and organizational leaders on how to improve their internal CSR communication and involvement practice and cultivate desirable organization-employee relationships.     

EXPERIMENTAL RESULTS OF AN APPROACH FOR EVALUATING MULTIATTRIBUTE ALTERNATIVES

In this paper the results of an extensive simulation study are reported to provide empirical evidence on the Evaluation and Bound approach. Some rules for implementing the procedure interactively on a computer are also examined and compared experimentally. The results suggest that the Evaluation and Bound procedure, in conjunction with an appropriate strategy of implementing it, would reduce considerably the information requirement of the decision maker in the choice of a preferred multiattribute alternative.     

Scheduling to minimize stringer utilization for continuous annealing operations

In this paper we present a mathematical program and heuristic algorithms to schedule coils for the production operations in a copper (or steel) coil manufacturing industry. The processing facility uses continuous operations for processing (e.g., galvanizing and annealing) while the handling unit is a discrete coil. The ends of coils are “stitched” or welded together to enable continuous processing, and the joint is later sheared off to obtain the processed coils. Processing constraints impose restrictions on the compatibility between a pair of coils that are overcome by introducing a dummy coil called stringer, which is very expensive to a mill. This paper deals with modeling the sequencing/scheduling problem of coils on parallel non-identical machines to minimize stringer utilization. Both computational and practical experiences show the efficiency and effectiveness of the solution approaches. Implementing these methods in an actual coil annealing facility resulted in 65% reduction in stringer utilization.     

International labor migration and domestic labor supply

Prominent among the variety of issues raised by the immigration of labor are its effects on domestic wage rates and labor supply. In contrast to the existing literature, this paper constructs a dynamic, general equilibrium framework to study the relationship between international labor migration and domestic labor supply. The general equilibrium nature of the model enables us to endogenize the pattern of labor migration. The effect of labor migration on domestic wage rates and labor supply is shown to depend on the pattern of labor migration. If the substitution effect dominates the income effect in labor supply, the domestic supply of labor necessarily decreases in response to an inflow of migrants. This happens even if immigrants, through their savings behavior, cause an increase in the domestic capital-labor ratio and wage rate. Similarly, if the dominant effect is the income effect, the immigration of labor necessarily increases the domestic supply of labor.I wish to thank Oded Galor, Harl Ryder, Kalpana Kochhar and two referees for valuable comments. The opinions expressed in this paper are my own and do not necessarily reflect the views of Joel Popkin and Company.     

Evaluating Time Streams of Income: Discounting What?

For decisions whose consequences accrue over time, there are several possible techniques to compute total utility. One is to discount utilities of future consequences at some appropriate rate. The second is to discount per-period certainty equivalents. And the third is to compute net present values (NPVs) of various possible streams and to then apply the utility function to these net present values. We find that the best approach is to first compute NPVs of various possible income streams and then take the utility of such NPVs. We show the drawbacks of other alternative models of evaluating income streams. The article discusses the advantages of the power and logarithmic forms in the modeling of time preference. These are the only forms for which utility of income and utility of consumption are strategically equivalent. Further, these forms permit the flexibility in the choice of a time period (e.g., monthly or quarterly) without modifying the utility function, thus simplifying analysis.     

The impact of lean practices on operational performance – an empirical investigation of Indian process industries

In deciding to adopt lean manufacturing, it is imperative to investigate where and how lean practices are most needed to influence manufacturing and business performance. Such an investigation becomes indispensable when lean thinking is to be considered in a production arrangement different to the conventional, repetitive, high-volume, stable-demand and discrete-manufacturing environment. This study provides explanations of how performance is improved through the adoption of lean practices in process industries. This is a relatively under-researched area compared to the performance effects associated with the introduction and implementation of lean principles in traditional, discrete manufacturing. Based on a survey of Indian process industries, this study attempts to develop an empirical relationship between lean practices and performance improvement through the use of multivariate statistical analysis. The findings have led to the conclusion that lean practices are positively associated with timely deliveries, productivity, first-pass yield, elimination of waste, reduction in inventory, reduction in costs, reduction in defects and improved demand management. However, within a process-industry context, lean practices related to pull production were found to have a marginal impact on performance improvement. A detailed discussion of the findings along with their theoretical and managerial implications is provided in the paper.     

Admissibility of a test procedure in a conditionally specified random model

Admissibility of a test procedure is a desirable property though not a compelling one; while lack of it often results in discarding a given test procedure. In this paper we have proved necessary conditions for admissibility for a test procedure.     

The Efficacy of Neural Networks in Predicting Returns on Stock and Bond Indices*

This paper uses two recently developed tests to identify neglected nonlinearity in the relationship between excess returns on four asset classes and several economic and financial variables. Having found some evidence of possible nonlinearity, it was then investigated whether the predictive power of these variables could be enhanced by using neural network models instead of linear regression or GARCH models. Some evidence of nonlinearity in the relationships between the explanatory variables and large stocks and corporate bonds was found. It was also found that the GARCH models are conditionally efficient with respect to neural network models, but the neural network models outperform GARCH models if financial performance measures are used. In resonance with the results reported for the tests for neglected nonlinearity, it was found that the neural network forecasts are conditionally efficient with respect to linear regression models for large stocks and corporate bonds, whereas the evidence is not statistically significant for small stocks and intermediate-term government bonds. This difference persists even when financial performance measures for individual asset classes are used for comparison.