The traditional view of cost behavior assumes a simple mechanistic relation between cost drivers and costs. In contrast, contemporary cost management research recognizes that costs are caused by managers' operating decisions subject to various constraints, incentives, and psychological biases. This conceptual innovation opens up the "black box" of cost behavior and gives researchers a powerful new way to use observed cost behavior as a lens to study the determinants and the consequences of managers' operating decisions. In 2014, Banker and Byzalov presented an overview of the economic theory of cost behavior and major estimation issues. The research literature on cost management has grown rapidly in the past few years and enhanced the understanding of how managerial decisions influence observed costs. In this study, we provide a comprehensive review of recent findings and insights, with a particular emphasis on the implications of cost management for understanding issues in cost, managerial, and financial accounting, and challenges and opportunities for future research.
- Prof. Rajiv D. Banker, Fox School of Business, Temple University
In this talk, I will present a sampling of studies that investigate factors and processes that shape health persuasion. We will examine whether and why people are averse to health persuasion and how these barriers can be overcome. In particular, we will look at three main influences and their interactions on heath message processing: (a) motivational sources such as goals, reactance, and moral identity, (b) affective sources such as specific emotions arising from or unrelated to the health message, and (c) social forces such as stigma and norms that can aid or impede the effectiveness of health messages. Understanding these influences will expand our knowledge of consumer psychology and help us design better health messages.
- Prof. Nidhi Agarwal, Foster School of Business, University of Washington
The demand for various socio-economic, transportation, and health statistics for small geographical areas is steadily increasing at a time when survey agencies are desperately looking for ways to reduce costs to meet fixed budgetary requirements. In the current survey environment, the application of standard sample survey methods for small areas, which require a large sample, is generally not feasible when considering the costs. One of the key factors that lead to the success of small area estimation (SAE) methodology is the availability of strong auxiliary variables. The accessibility of big data from different sources is now bringing new opportunities for statisticians to develop innovative SAE methods. In this talk, I will provide an outline of how SAE methods can be adapted to incorporate big data in improving local area statistics. Then I will discuss my recent collaboration with my UMD colleagues --- Professor Cinzia Cirillo of Department of Civil and Environmental Engineering, and Professor Joseph JaJa of Department of Electrical and Computer Engineering, and the University of Maryland Institute for Advanced Computer Studies (UMIACS). Finally, as an example from our different collaborative research projects, I will explain how SAE can help solve a seemingly different problem of predicting in real-time traffic by exploiting rich vehicle probe big data.
- Prof. Partha Lahiri, University of Maryland, College Park
Large family owners monitor managers, which attenuates principal-agent conflicts and improves firm performance. However, these owners can also appropriate resources, which creates principal-principal conflicts and harms firm performance. Although the two performance effects occur simultaneously, research does not explain when positive effects outweigh the negative. We theorize that family members must be involved to minimize principal-agent problems, but too much involvement creates principal-principal problems. Consistent with our theory, evidence from a panel of 667 publicly listed French firms from 2003 to 2007 shows an inverted U-shaped relationship between firm performance and the amount of family involvement relative to the family's ownership stake. Our theory and findings help explain the heterogeneity of performance effects among family firms.
- Prof. Klaus Uhlenbruck, University of Montana