Enterprise social media to foster digital maturity: a value-creation perspective
Bibliographic record
Abstract
Purpose In response to the growing need for organizations to enhance their digital capabilities and the widespread adoption of enterprise social media (ESM) in the workplace, researchers have extensively studied the effects of ESM on various organizational outcomes. Nonetheless, a notable theoretical gap exists regarding the influence of ESM on the development of organizational digital maturity. This paper aims to bridge this gap by conducting a comprehensive literature review to investigate how the utilization of ESM can facilitate the transformation of organizational value-creation processes, thereby contributing to the overall enhancement of digital maturity. Design/methodology/approach Using the information technology (IT) value-creation framework developed by Mooneyet al.(1996) and applying a template analysis methodology as outlined by King (2012), the authors conducted a systematic literature review (Okoli and Schabram, 2010), to investigate the influence of ESM on value creation within the digital business environment. Findings The study’s outcomes are structured around a theoretical framework that combines the contingency theory and the sociotechnical perspective to provide a comprehensive understanding of digital maturity. This paper also delves into how ESM facilitates the transformation of organizational value-creation processes, ultimately contributing to the overall progress of their digital maturity. Research limitations/implications This study adapts existing theoretical models to fit the context of ESM and integrates multiple perspectives to provide a comprehensive understanding of its impact. It identifies a convergence in the definition of ESM and offers insights into its various dimensions and effects on value creation. Hence, scholars can use the identified theoretical frameworks and conceptual convergence to guide future investigations into the impact of ESM on value creation, fostering theoretical development and empirical research. Practitioners can benefit from the insights to develop effective strategies for implementing ESM within their organizations, aligning with broader organizational objectives to enhance performance, streamline operations and drive structural changes. Furthermore, both scholars and practitioners can use the identified limitations of the study to identify areas for further improvement and exploration, thus contributing to the advancement of knowledge and practice in ESM and value creation. Limitations of this research include the exclusion of gray literature, a relatively small sample size of analyzed articles, and the restriction to specific databases as per systematic review guidelines, potentially overlooking valuable contributions from alternative sources. Practical implications This paper provides a comprehensive exploration of how ESM can support value-creation processes within organizations. It offers valuable insights to help managers incorporate ESM into their digital strategies and to understand its value-creation effects. Originality/value Adopting a value-creation perspective and integrating the contingency theory and the sociotechnical perspective to build a comprehensive framework, this research introduces an original approach by showcasing how ESM can facilitate shifts in value-creation processes of organizations, paving the way to contribute to the development of their digital maturity.
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How this classification was reachedexpand
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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".