Capabilities Enabling Product Orientation and Service Orientation: A Study of Canadian Software Firms
Notice bibliographique
Résumé
This thesis identifies the unique capabilities that characterise product-oriented vs. \nservice-oriented firms in the software industry. Firms in the software industry have very \ndifferent business models from other industries. Some firms rely entirely on earning \nrevenue from services provided on an hourly basis, while others build and sell software \nonce and earn revenue from it for years to come. There are even successful firms in the \nindustry with a variety of revenue sources and models resulting from planned or \nunplanned transitions across orientations. The unique characteristics of this industry offer \nan opportunity to study the development of organisational capabilities that support \ncontrasting strategic orientations. \nThere is substantial literature on strategic orientations (e.g., Roberts 1990; Lynn et \nal. 2000; Pelham 2000; Voss and Voss 2000). There is also substantial literature on \norganisational capabilities (e.g., Nelson and Winter 1982; Leonard-Barton 1992; Day \n1994; Teece et al. 1997; Winter 2003; Ethiraj et al. 2005). However, few studies \nempirically identify organisational capabilities that are developed to support an \norientation. This study identifies the capabilities that enable product orientations and \nservice orientations in the software industry. Moreover, the research tests the hypothesis \nthat product orientations and services orientations are distinguished by different \norganisational capabilities. \nThe study tests this hypothesis by eliciting capabilities and measuring the \nmaturity of these capabilities in different firms. The findings of this study make unique \ncontributions to the literature pertaining to strategic orientations and capabilities through \nfurther definition of both constructs. This research also utilises a previously untested \napproach for identifying capabilities. The method approaches the research problem using \na two-step approach. The first phase focuses on eliciting the capabilities that characterise \nboth service and product orientations. Interviews with key informants support the \nelicitation of capabilities. The second phase of the research study involved the collection \nof data using a survey to validate the existence of and identify the maturity of the \ncapabilities from the first phase. \nThe findings indicate that there are significant differences between productoriented \nand service-oriented firms, the capabilities that distinguish them and their \nperspectives on transition between orientations. The key result of the research is the \nidentification of the capabilities that distinguish between software firms of three different \norientations: product orientation, service orientation and a hybrid orientation. \nThis research study contributes to advancement in the literature pertaining to \nstrategic orientations and capabilities (e.g., Morgan and Strong 2003; Venkatraman 1989; \nDuhan et al. 2005; Winter 2000; Teece 2007). The results of the study further define what \nit means for software firms to have product, service and hybrid orientations, resulting in \nadvancement of these constructs. The approach used to elicit and capture capabilities is \nnovel and contributes to advancement in the literature pertaining to capabilities by \napplying a previously untested methodology. The results of this research are of particular \ninterest to software firms that aspire to build or strengthen a product, service or hybrid \norientation.
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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 | 0,000 | 0,000 |
| 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 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 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 ».