The distinctive research culture at MIT Sloan permeates the PhD Program. World-renowned faculty engage in research that impacts management theory and practice around the globe — often with PhD students by their sides.
Project: Enacting New Ways of Working in Internet-enabled Organizations
MIT Sloan Team: Professors Wanda Orlikowski and JoAnne Yates, and Kate Kellogg, fourth-year MIT Sloan PhD student
This research is focused on how use of the Internet is transforming the ways that companies organize and operate, and on the impact that these changes have on organizational design and performance over time. It is part of a large NSF-funded project examining the social and economic implications of Internet technologies within firms (http://SeeIT.mit.edu).
The team is interested in how, as companies migrate their business processes to the Internet, they experiment with a range of new ways of organizing work. The project's focus is on how virtual work, geographically-dispersed teams, and electronic collaboration alter where, when, how, and with whom work is carried out.
The MIT Sloan team is conducting research on these new ways of organizing at Adweb (a pseudonym), which is an end-to-end interactive marketing company founded as a dotcom in 1995.
Adweb develops interactive websites for a range of organizational clients. Its product development work is carried out in interdependent, multi-specialty teams with fluid authority relations and an emphasis on learning and speed. All Adweb teams use new media and information technologies extensively, both to create their clients' websites and to coordinate with one another during their product development work.
In this field study, a variety of data is collected using multiple techniques, such as interviews, observations, and document review (on paper and the global Adweb intranet). In their analysis of these data, the team used inductive, qualitative techniques to study the new ways of working at Adweb. The team is currently in the process of finalizing a paper based on these findings about new ways of organizing work, which they plan to submit to a journal.
MIT Sloan PhD student Kate Kellogg presented this paper at the Academy of Management conference in the summer of 2002, and it won an award for one of the best papers in its division.
Project: Fast Polyhedral Adaptive Conjoint Analysis
MIT Sloan team: Professors Duncan Simester and John Hauser, and Olivier Toubia, second-year MIT Sloan PhD student
With the advent of new communication and information technologies, the opportunity to provide rapid and iterative feedback on customer preferences is changing rapidly. Web-based customer panels offer the potential to get information from customers rapidly and iteratively, while Web-based multimedia capabilities provide the means to show customers virtual product prototypes with rich, visual, interactive features.
However, Web-based respondents are impatient and have other uses for their time. Questionnaires must be much shorter than those used for traditional central-facility respondents. On the Web, respondents appear to wear out more quickly when asked profile-evaluation or paired-comparison questions.
In this research the team proposes and tests new adaptive conjoint analysis methods that attempt to reduce respondent burden, while simultaneously improving accuracy. Because the methods make full use of high-speed computations and adaptive, customized local Web pages, they are ideally suited for Internet panels and for supporting product development processes.
Specifically the team interprets the problem of selecting questions and estimating parameters as a mathematical program and estimates the solution to the program using recent developments in interior-point methods. This technique can provide accurate estimates of partial utilities from far fewer questions than existing methods.
Recent work in the mathematical programming literature has led to extremely fast algorithms for approximating the interior of polyhedra. These algorithms have been developed to solve large-scale optimization problems in a variety of theoretical and applied contexts.
Although to date none of the applications have addressed marketing issues, the techniques appear to have tremendous potential to contribute to a wide range of marketing problems. The team hopes that the application of these techniques to conjoint analysis will serve to highlight this potential.