Capabilities Enabling Product Orientation and Service Orientation: A Study of Canadian Software Firms
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".