Förbättrad operationell tid genom tjänster : En studie av kundvärdet och kundupplevelsen för tillgänglighetstjänster i lastbilsindustrin
Notice bibliographique
Résumé
The trucking industry is undergoing a significant transformation of business models, which is driven by technological advancements and increasing demands for operational efficiency. A central piece of this transition is the growth of availability services, which are service offerings that aim to maximize uptime and minimize unplanned stops for the customer. These services represent a shift to a more service-based business model through servitization and demand that truck manufacturers reconfigure how they create and capture value during the customer journey. As product and relationship quality become increasingly commodified, the customer experience of these services becomes the main differentiating component in value creation. Therefore, the purpose of this study is to develop a framework for how OEMs in the trucking industry can create and capture the value of availability services throughout the customer journey. The study was designed as a qualitative single case study, where the case company is a large European truck manufacturer. The data collection took place through semistructured interviews with case company employees and customers. Interviews were conducted with 17 customers from varying industries and with five respondents from the case company. Thematic data analysis was utilised with inspiration from the Gioia methodology. The findings of the study include a total of 16 value driving factors distributed into four dimensions of value in business markets. Namely, table stakes, functional value, ease of doing business value and individual value. Additionally, 16 activities that influence the customer experience of availability services were found and categorised into five groups. These groups are activities related to the purchase phase, daily interactions during the usage phase, moments of truth, background activities performed by the supplier and external activities performed by the customer. Lastly, a framework was created for how OEMs in the trucking industry can create and capture value of availability services throughout the customer journey by combining the identified value driving factors and activities. The conclusions showed that the different activities maintain different roles in creating and capturing value throughout the customer journey. Activities related to the purchase phase showcase the expected value for the customer and act as a door opener by selling a win-win solution that the customer accepts as economically beneficial. Phase spanning activities from the customer and the supplier ensure that the economical and individual value-in-use for the service offering is increased over time by creating a more coherent and contextually adapted experience. Daily interactions during the usage phase facilitate that the customer experience differentiates the supplier from its competitors. This is achieved by enabling and simplifying daily tasks within administration. Moments of truth are when the customer experience becomes accentuated. By utilising a quick and adaptive service organisation that uses transparent and factual communication, suppliers ensure that these instances take the customer experience to the next level.
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 | 0,009 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,003 |
| Communication savante | 0,011 | 0,008 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».