A multi-method bibliometric review of value co-creation research
Bibliographic record
Abstract
Purpose This paper aims to examine the origins of value co-creation (VCC) knowledge streams, vis-a-vis their progression over the past 18 years. The study explores how knowledge of this discipline emerged across the tripartite strategic paradigms of business transformation. Design/methodology/approach Co-citation analysis (CCA) and co-word analysis (CWA) are used as bibliometric techniques, for which, a group of articles is retrieved using Scopus’s usual keyword-based search. The initial collection consists of 3,431 research articles published in business and management publications. By explaining the article clusters generated through CCA and keyword connections generated through CWA, the findings outline the origins and development of VCC research. A CWA-based chronological study adds further insights to the development of VCC research themes. Findings The results depict that VCC research has grown multifold in the past 18 years, whereby it has shifted its attention from a dyadic interaction approach to a multistakeholder ecosystem-based approach detailing the phenomenological instances of resource integration and institutional processes. Notably, extant research in this field has grown at a much faster rate since 2008. In fact, a stronger concentration of research emerged in the experience domain, particularly in terms of hedonic services. Development of engagement platforms has been driven by research into technologies such as IoT and artificial intelligence. Research limitations/implications The theoretical framework of the VCC paradigm is used to describe the aggregation of co-creation research around the three strategic pillars. This framework is useful for business strategy and to track VCC research over time. Practical implications This work identifies the practices and strategies of VCC at three different levels: capacity, platform and experience. The study offers insights into a variety of co-creation practices at their respective levels, incorporating micro-level dyadic interactions and macro-level processes in a service ecosystem. Originality/value This study uses different bibliometric methodologies to investigate the development of this scientific field over time. “Document co-citation” analysis, a more preferred bibliometric technique under CCA, is used to construct the cluster of theoretical cores of this area. The results are classified under the strategic framework of the co-creation paradigm (Ramaswamy and Ozcan, 2014).
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| gpt | Bibliometrics Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | high |
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.043 | 0.167 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.243 | 0.188 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".