Persons at MENDELU


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Ing. Vladimír Hajko, Ph.D.
Identification number: 54007
University e-mail: vladimir.hajko [at] mendelu.cz
 
Assistant Professor - Department of Business Economics (FBE)
Researcher - Department of Marketing and Trade (FBE)

Contacts     Lesson     Publications     Supervised theses     Conferences     

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University e-mail box last checked on 09/22/2017 20:15.
 
Office phone number:+420 545 132 636
Office address: DMT FBE, Zemědělská 1, 61300 Brno,
DBE FBE, Zemědělská 1, 61300 Brno
Office number:BA39N6008 (Q6.08)
Contact:Pro anonymní vzkazy, připomínky, podněty atp. použijte následující odkaz (You can send anonymous messages, comments, suggestions and alike using the following link): https://goo.gl/forms/TeDe2vWDxgDVs6xV2
Consulting hours:Úterý: 13:00-14:00, kancelář Q06.08 (vždy se předem nahlašte e-mailem). Tuesday: 13:00-14:00, room Q06.08 (please arrange an appointment by e-mail).
Note:Available thesis topics:
  1. Meta-analysis models
    1. Meta-analysis of energy efficiency intervention studies
    2. Meta-analysis of oil price transmission studies (rockets & feathers)
  2. Applied Index Decomposition models
    1. Perfect decomposition in the shift-share analysis
    2. Index decomposition analysis using firm-level data
  3. Efficiency of energy conservation investments
  4. Profit elasticity, price-cost margins and competition
    1. of a selected industry / relevant market
    2. of Czech District-heating sector (regulated industry)
  5. Energy demand management in relation to smart-cities
  6. Use of contingent valuation to estimate the wilingness to pay and willingness to accept
    1. with a particular focus on large-scale waste producers
    2. with a particular focus on large-scale producers of atmospheric emissions
  7. Differences between stated and revealed preferences regarding communal waste generation
  8. Systematic review of intervention studies
    1. focused on energy conservation
    2. focused on pro-environmental behavior
  9. Scoring/bankruptcy models (using firm-level data)
  10. Empirical financial data analysis performance - ordinary approach vs. automated evolutionary algorithms

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