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INSEAD Course/Program Name
Application closes on
National :15 Dec
International :15 Dec

PhD Technology and Operations Management

 Course Level
PhD
 Type
Full Time

 Duration
5 Years
 Start month
July

 Tuition fee

International
60000 EUR
National
60000 EUR

Application fee

International 50 EUR
National 50 EUR
Department
Technology and Operations Management Area
Scores accepted
IELTS (min)7.5
TOEFL-IBT (min)105
TOEFL-PBT (min)620
GRE (avg)325
GMAT (avg)702
1

World B-School Ranking

About this course

The field of Operations Management has been changing dramatically due to the emergence of a truly global economy, significant advances in information and process technology, and the continued growth of services. The Technology and Operations Management Area (TOM) focuses on value creation on a global scale through innovative product and process design, project management as well as on value capture through effective supply chain management.

 

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Eligibility Criteria

Selection Criteria

  • Proven academic record - irrespective of subject background.
  • Creativity and Independent thought - necessary to become a great researcher.
  • Motivation, Determination and Drive - to follow through with goals.
  • Ability to work in English - as English is the sole medium of instruction at INSEAD

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Course Modules

Advanced Courses

Discrete Stochastic Processes

Stochastic processes are methods of quantifying the dynamic relationships of sequences of random events. Many applications of stochastic processes occur in operations, finance, marketing, economics, etc. This course provides the concepts that are needed to study these processes from a non-measure theoretic perspective. We will focus on model building, probabilistic intuition, and the ability to analyze stochastic processes formally.
The objective of this course is to provide the student with tools that are frequently used in the formal studies of management. The course builds upon the concepts already seen in Probability and Statistics I (A) and (B). It is divided into self-contained modules, each covering a specific topic and ending with a set of exercises.
Specific topics of the course include probabilistic reasoning, with emphasis on tools that are useful for gaining insight from stochastic process models, Poisson processes, renewal/reward processes, discrete-time Markov chains, and an introduction to continuous time models such as Brownian motion and continuous time Markov chains.

Foundations of Operations (A) and (B)

This course covers fundamental concepts of production and operations management, with an emphasis on analytical models.
The purpose of the course is threefold:

  • Introduce the students to the classical foundations of the field;
  • Introduce the students to some of the the fundamental issues and phenomena that are relevant to the management of operations;
  • Introduce the students to a broad sample of modelling tools.

Modeling Workshop

Formal modeling has always been at the heart of many disciplines in the study of Management. As an example, most scholars in Operations Management are engaged in building formal models.
This course addresses the question of why formal models support the academic knowledge creation process, what kinds of models exist, what are characteristic features of good models and what are good practices in creating and solving models. The course is not geared towards any specific discipline and is designed to be accessible to students from all areas.
Since building models is not algorithmic, but a weighing of different factors, students who want to engage in building models need to understand these factors and at the same time build some practical experience in weighing these factors. Therefore some part of the course (the larger one) will consist of reading individual papers that illustrate some important aspects of modeling while some other part will be about having students build models and having a group discussion about their merits.

Optimization

Linear programming is a fundamental technique both for its theory and its power in applications. Theoretically it is widely used in Economics, Operations Research and Management, Computer Science and Marketing. Industrial applications are prominent in Finance, Operations, Logistics and Marketing.
This is an introductory class about linear and (linear) integer programming. There are no formal prerequisites but students are expected to know some linear algebra. (We will review the required linear algebra material in the first class.) The class will be technical in nature, intended to give students an insight as well as the necessary background to use linear programming. 

Research Topics in TOM

Uncertainty is a feature of all business decisions. The objective of this course is to provide theory and applications of state-of-the art methods for Bayesian and classical statistical inference methods that quantify uncertainty.
The underlying probability and stochastic process background for a number of techniques in point estimation and uncertainty analysis will be presented. These include normal and non-normal approximations of likelihood functions, the expectation-maximization (EM) algorithm, data augmentation, and Markov Chain Monte Carlo (MCMC) methods that have recently opened the door to a variety of applications.
These techniques will be applied to specific practical problems in operations, portfolio management, health care, and other business applications. Computer programs, such as BUGS, will help tie theory with practice.

Supply Chain Management

According to Fisher (1997), supply chains perform two distinct functions: a physical function and a market mediation function.
The physical function includes transformation (manufacturing and assembly), storage, and transportation. The market mediation function, on the other hand, ensures that the products reaching the market place matches what consumers want to buy.
Most OR/OM literature, under the umbrella of production and inventory control, has focused on the physical function of the supply chain. More recently, with the growing popularity of supply chain management, the market mediation function started receiving considerable attention. Moreover, the emphasis has shifted away from centralized control, where issues of competition and coordination do not arise, towards a more decentralized view of the supply chain. A recent body of literature studies the use of incentives and contracts for supply chain management under competition.
The goal of this course is to review the emerging literature in supply chain management and identify future research directions in this rapidly evolving field. The course is aimed at doctoral students in Operations Management, Marketing, and Strategy, who are in their second year of study. The course will adopt the following format: each student will have a primary responsibility for one of the papers assigned for the session. Once the papers are presented by the students, the instructors will lead the discussion in comparing the work and identifying new research directions. The students' performance will be based on the class presentations and the quality of a research proposal.

Technology Management

Effective management of Innovation, Research and Development, and Technology have become key determinants of competitiveness, and therefore are receiving significant attention in business literature. This seminar is designed to give future researchers an overview of important topics within the area of Technology Management.
In the seminar, we will acknowledge the cross-functional nature of this field by studying research papers from different disciplines. We will cover topics related to innovation in three different modules: innovation dynamics and strategy, innovation management in development organisations, and the role of information technology in innovation.
Even though we will study various research paradigms (model based, qualitative, and empirical), special emphasis will be put on manuscripts that use empirical methods. Prior offerings of this seminar have attracted students in Production and Operations Management, Decision Science, Business Strategy, Marketing, and Organisational Behaviour.

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How to Apply

Supporting Documents

All supporting documents should be in electronic format and uploaded through our online application platform. Only selected candidates for admission will be asked to provide original copies to the PhD Office to secure their admission in the programme. Thus, no originals or hard copies of transcripts should be sent to the PhD Office prior to admission to the programme.

1. Photograph (passport sized) in JPEG or GIF format, uploaded to your profile.
2. Application fee (non-refundable) of 50 €, which is paid online by credit card. Your application will not be considered until the correct fee is received. 
3. Electronic copy of CV/Resume
4. Electronic copy of Official Transcripts of Grades and Diploma / Degree Certificates with certified translation in English, where applicable
5. Electronic copy of official GMAT or GRE score report
6. Electronic copy of original TOEFL score report. (Note: We do not accept IELTS score in lieu of the TOEFL; if any of your degree's medium of instruction is in English, the TOEFL requirement is automatically waived. Your transcripts from this degree will suffice as proof of waiver)
7. Supplementary information survey form that is accomplished and submitted online (part of your online application form, found under the Supporting Documents section).

Recommendation Letters

A maximum 3 Letters of Recommendation are required coming from faculty, scholars or individuals who can evaluate the applicant’s academic ability and potential for research and teaching. When requesting recommendations, candidates are asked to use the appropriate online forms. Only 3 electronic recommendation letters are required to complete the application.

On the section of Letters of Recommendation, applicants are requested to enter the details of referees, including the 'official' email address (official email addresses do not include gmail, yahoo, or hotmail email clients). Once done, applicants need to click on the link 'Send an email to your recommenders now'.

Important: Refrain from clicking more than once the 'Send an email to your recommenders now' link, to avoid unnecessary email requests sent to your referees.

Applying Online

All applications to INSEAD are fully electronic and must be submitted online. To successfully access the application, you must download or upgrade your browsers to the following minimum requirements: Internet Explorer 9 and above, Firefox 8 and above, Chrome 10, Safari 5 and above, and Opera 10 and above.

A complete application includes the following: duly accomplished online application form, e-copies (e.g. PDFs) of supporting documents and application fee of 50€. Incomplete applications (missing documents or pages of documents, information or payment) will not be considered by the PhD Admissions Committee.

The application form is comprised of:

1. Your Profile: personal information, test results, academic background, professional background, proficieny in the English language and other languages, international exposure and activities and interests.
2. Statement of Purpose or letter of motivation (1500 essay), stating current goals, career plans, reasons for being interested in the PhD Programme. In as much depth as possible, discuss study plans and intended area of specialisation. 
3. Statement of Integrity (by agreeing to the terms and conditions when submitting the application form)

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