Adoption Model of Social Customer Relationship Management in the Palestinian Banking Sector
Bibliographic record
Abstract
Social CRM is a new technology that integrates social networking activities within traditional CRM itself. Social media might be the most effective strategy in the context of CRM technology concerning the availability of efforts and time by owners. Therefore, it’s important for financial institutions to take advantage of it upon this opportunity by considering social CRM as part of development and enhancing relationship with their customers. Nevertheless, little empirical studies have focused on adoption of social CRM in banking sector. This research paper aims to investigate the factors that impact banks’ intention to adopt social CRM, based on combining the Technology-Organization-Environment (TOE) with Technology Acceptance Model (TAM) as the theoretical framework. TOE variables such as top management support and relative advantages found to have a direct impact on the two TAM mediating variables (perceived usefulness and perceived ease of use), and an indirect impact on social CRM adoption. Further, results suggested that consumer pressure and competitive pressure have a direct impact on social CRM adoption. The researcher tested the hypothesis using structural equation modeling (SEM). The findings from a survey of 220 employees in banks in Palestine showed that all eight hypotheses were supported as both consumer pressure and competitive pressure in the environmental context have a significant direct impact on social CRM adoption intention, followed by top management support in organizational and technological contexts; relative advantages have the most significant impact on perceived ease of use and perceived usefulness which in turn, have a direct and significant impact on social CRM adoption intention. The contribution of the study, limitations, future studies and conclusion are presented. 
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".