Social Media for Product Life Cycle Management of SMEs: Multiple Case Studies
Bibliographic record
Abstract
SMEs evolve in a highly competitive environment, where firms' survival depends on their ability to differentiate themselves from competitors and provide greater value for customers. This study focuses on how social media tools can enable SMEs to collaborate with external parties, such as customers, partners, and suppliers, to generate value throughout their products' life cycles. Social media tools can be very beneficial for SMEs, as they are familiar tools to customers, they allow firms to reach an increased amount of current and potential customers, and are inexpensive. This research uses a multiple case studies design, in order to understand how SMEs currently use social media to collaborate with these external actors, and aims at identifying where improvement is necessary. Six cases have been used from diversified industries of tangible products, intangible products, and services. Results illustrate that SMEs do not actively use social media tools to collaborate for innovation purposes during the initial phases of the product life cycle. Rather, they use them for marketing, customer service support, and business development activities in the later phases of the product life cycle. Findings suggest a need for further guidelines as to how social media can be integrated to support innovation activities.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".