The Business of Soul-Mates \nA Social Network Approach to Assessing a Customer-Company Relationship: The Customer-Company Network Strength Structural Equation Model
Bibliographic record
Abstract
This thesis develops and tests a Measurement Model and a Structural Equation Model (SEM) to assess the strength of a customer-company network using an interdisciplinary approach. The research integrates recent principles from Social Network Theory, Service-Dominant Logic and Customer Engagement Theory. The model investigates the impact of three real companies interactions with customers. The overall customer-company relationship is viewed from an interpersonal perspective. Relationship strength is defined by social network characteristics of tie directionality, tie reciprocity norms and network’s actors’ centrality. This framework looks at how the company’s value proposition is directed towards a customer and how this perceived directionality impacts the relationship. Moreover, the model integrates the effect of reciprocal behaviour from both the customer and the company perspective. While company initiated reciprocity is viewed as directed towards both the customer and society as a whole, the customer reciprocity is assessed in terms of their expressed attitudinal loyalty and commitment to the relationship. The model also incorporates the impact of the company centrality in the customer’s private networks (e.g. friends) and of the customer perceived connection to the company’s customer group(s). From a theoretical perspective, the interactions under investigation do not take into consideration the economic exchange and satisfaction derived from service/product usage. As a result this study breaks away all together from the traditional view of marketing and relationships. Additionally, the inclusion of non-customers in this research also shows that the relationship exists prior to an economic exchange. From a methodological perspective, we develop and assess a scale to capture the customer-company network interactions before evaluating a SEM that measures the impact of all the constructs on the customer Reciprocity towards the Company. The latter is viewed as reflective of the customer-company network strength. We find that Directionality has no direct impact on the customer willingness to reciprocate while Overall Centrality, Reciprocity towards Society and Reciprocity towards the Customer significantly and directly impact the customer-company network strength. The findings will allow companies to identify the network dimensions that matter to each customer or customer group(s). Companies can then dedicate resources to enhance the interactions that matter most.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".