Customer Value Creation for the Emerging Market Middle Class: Perspectives from Case Studies in India
Bibliographic record
Abstract
This paper examines the customer value creation framework and discusses the design of the key elements for product development in emerging markets. A scientometric/bibliometric scoping literature review identifies a clear gap in the current research in studying prerequisites for customer value creation in emerging market contexts. Observing experiences of Daikin and Renault in the context of India, the purpose of this paper is to identify value creation strategic choices following which comprehensive customer value offerings in products and services can be successfully created by firms across the four facets of the framework in emerging markets. Value creation strategies include having a nuanced understanding of the latent contextual needs to offer localized high-quality products that embody distinct functional attributes that provide a functional value and being responsive to specific emotional needs and epistemic experiences of the target customers in product and service offerings to deliver a greater experiential value. Furthermore, the products should adopt a localized operational excellence strategy throughout the value chain to reduce costs for competitive price offerings in order to deliver superior cost value and develop brand image and equity strategy, thereby allowing for the provision of a greater symbolic value. Experiences of successful firms demonstrate the need for extensive local research into the emerging market followed by localization of production and development of a distribution network to be able to offer customized products at competitive prices whilst maintaining the brand value. We thus extend the customer value creation framework by introducing localization as a necessary condition for successful organizational performance in emerging markets.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 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".