With the growing awareness that operations can affect the environment, regulators increasingly use facility inspections to assess a firm's environmental performance: whether its operations comply with or violate environmental regulations. When operations violate regulations, firms can face regulatory sanctions for non-compliance and pressure from stakeholders to improve environmental performance. Consequently, firms need to develop organizational knowledge to ensure that their operations conform to regulations. Learning from past inspection experience is critical for the development of such knowledge. Using data on 13,606 unconventional wells developed in Pennsylvania from 2004 to 2014, we investigate how firms can learn from their inspection experience and from such experience of other firms. We find that an unconventional well learns from the inspection experience of other units both within the organization and outside the organization, only when inspections detect violations but not when they confirm compliance. Further, penalties imposed for violations have a divergent effect they support learning from the inspection experience with violations when it is gained at other units within the organization, but not from such experience gained at units outside the organization. Our results provide insights on how the outcomes of environmental inspections and penalties facilitate the development of organizational knowledge.
- Prof. Suresh Muthulingam, Pennsylvania State University
For a great variety of large-scale optimization problems arising in Operations Research applications, it has become practical to rely on "off-the-shelf" software, without any special programming of algorithms. As a result the use of optimization within business systems has grown dramatically in the past decade.
One key factor in this success has been the adoption of model-based optimization. Using this approach, an optimization problem is conceived as a particular minimization or maximization of some function of decision variables, subject to varied equations, inequalities, and other constraints on the variables. A range of computer modeling languages have evolved to allow these optimization models to be described in a concise and readable way, separately from the data that determines the size and shape of the resulting problem that may have thousands (or even millions) of variables and constraints.
After an optimization problem is instantiated from the model and data, it is automatically put into a standard mathematical form and solved by sophisticated general-purpose algorithmic software packages. Numerous heuristic routines embedded within these packages enable them to adapt to many problem structures without any special effort from the model builder.
The evolution and current state of both modeling and solving software for optimization will be presented in the main part of this talk. The presentation will then conclude with a consideration of current trends and likely future directions.
- Dr. Robert Fourer, President, AMPL Optimization Inc., Professor Emeritus, Northwestern University
We estimate a panel model where the relationship between inequality and GDP per capita growth depends on countries' initial incomes. Estimates of the model show that the relationship between inequality and GDP per capita growth is significantly decreasing in countries' initial incomes. Results from instrumental variables regressions show that in Low Income Countries transitional growth is boosted by greater income inequality. In High Income Countries inequality has a significant negative effect on transitional growth. For the median country in the world, with a year 2015 PPP GDP per capita of around 10000USD, IV estimates predict that a 1 percentage point increase in the Gini coefficient decreases GDP per capita growth over a 5-year period by over 1 percentage point; the long-run effect on the level of GDP per capita is around -5 percent.
- Prof. Markus Brueckner, Australian National University
The CMHS seminar held at Wing - 11 Committee Room, IIMA on December 14, 2017 by Dr. Aravind Srinivasan, CMO, Aravind Eye Hospital, Chennai on Building a Compassionate Organization
- Dr. Aravind Srinivasan, CMO, Aravind Eye Hospital, Chennai