Global Market Investigation for a New Product in Video Post-Production : Case Company: Loupedeck Ltd
Notice bibliographique
Résumé
This study is a research-orientated thesis which is focused on creating a knowledge basis of the video post-production industry for the company Loupedeck and its new product development project. The company offers an innovative and advanced control panel to improve and facilitate the professional photo editing workflow in Adobe Lightroom.\nLoupedeck is growing and opening new market opportunities, therefore, they are aiming to design and manufacture more hardware devices for post processing solutions in the future. The objective of the thesis is to conduct a market study and customer needs investigation for the start of the new product development process. The research questions are designed to investigate the current market of video editing hardware and software, industry trends, target audience and their needs and preferences for the new product.\n\nThe literature review consists of the product development concept and detailed description of its stages, market study and its elements, such as market segmentation, target audience, competition analysis and market trends. Additionally, several strategies of customer interaction in the development process are reviewed and the process of customer needs data collecting and analyzing is investigated.\n\nThe study includes primary and secondary data. The selected methodology for the primary data collection is qualitative research through in-depth semi-structured interviews. The secondary data is gathered through the desk research approach.\n\nThe findings chapter presents the summary of the video post-production industry and the most commonly used video editing software on the market. It was defined that Adobe Premiere Pro and Final Cut Pro have the largest share of the video post processing soft-ware market. The chapter shows the estimated number of business users of these two applications and gives statistical data of the video editors amount in US and UK markets. It was defined that the first five leading markets of both software are: US, UK, Canada, Australia and France. I determined that the UK video post-production industry annual growth increased by 4.3% and the US market increased by 2.7%. On the global level, market analysists predicted that the post-production market will grow at a Compound Annual Growth Rate of almost 6% by 2021.The study findings also include the overview of the existing hardware products. I defined seven potential competitors on the global market. Moreover, the research provides the description of potential customers profiles and analysis of the customer needs regarding the video post-production workflow.\n\nIn conclusion, I discuss the study results and the research in terms of validity, reliability and limitations, answers research questions and provide recommendations for future research. The personal learning outcomes are precisely described in the last chapter of the thesis.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,002 |
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 source (Gemma direct ou Codex distillé), 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 ».