Building a competitive positioning strategy for Swedish companies in the Ukrainian market of energy saving technologies
Notice bibliographique
Résumé
The purpose of this thesis work is analysis of heat pump market in Ukraine. This market is almost not developed in our country, but we can say that it has a great potential. That is because for our company it is a new and innovative direction of energy saving technologies. In Ukraine, for heating of buildings are used gas and diesel boiler. Heating equipment of buildings are old and very energy-intensive. There are hundreds of cubic meters of gas spent for heating buildings. Instead, heat pumps allow generating energy from environmental sources such as soil, water, air. In addition, the technology of heat pumps is ecologically clean. It does not pollute the environment. International practice of heat pumps usage is very wide. Almost all of Europe, the USA, Canada, use this equipment. Heat pumps production in these countries is high. Foreign companies almost completely captured the market of this industry in Ukraine. This market is underdeveloped at this point. Heat pumps are set almost exclusively in new private buildings. As the price of this equipment is more expensive than a simple gas boiler, so such equipment sets people with high incomes. In developed countries heat pumps in different functional direction use in amount of millions or hundreds of thousands but in Ukraine there are some individual settings that were created, mainly in the element base of refrigeration equipment, imported from Western Europe from specialized producers. Striking gap between Ukraine and the countries that are successfully using heat pump technology can be explained by objective factors - energy development in our country carried out mainly by way of district heating. And there are some subjective factors. There are insufficient attention specific companies and individual persons to save fuel and energy resources. The main causes of concern are the absence of a demonstration place of operating heat pumps of different functions and promotion their benefits. And also there are lack of government support in developing, researching and implementing this type of equipment. So we can conclude that the entrance foreign companies on the Ukrainian market are aimed in perspective.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».