Green Marketing: A Challenge or an Opportunity in the Global Environment
Bibliographic record
Abstract
The earlier perception of industry towards green marketing was that the pressure for making business environment green and behaving in a more responsible manner especially comes from Government and its legislations. Now that old perception is changing throughout the globe as studies performed on consumers reflect that in most countries consumers are becoming more aware and willing to act on environmental concerns. There is a radical change in consumer preferences and life styles. They prefer environment friendly products over the others and many times are ready to pay a little extra price for such green products. Due to this shift from traditional marketing to green marketing, companies these days are facing many new challenges. This can also be viewed as a source of new opportunities to grow in today’s highly competitive global environment. A 2008 survey by the National Geographic Society and GlobScan on consumer choice and the environment reported on current behavior in fourteen countries (including Canada, China, France, Germany, India, Mexico, Russia, the UK and the US). The study found signs that consumer in all countries “feel empowered when it comes to the environment and are taking some action in their daily lives to reduce consumption and waste.” A global Synovate survey conducted in 2007 in association with Aegis, and repeated in 2008 in association with BBC World, also found that consumers in most countries are becoming more aware and willing to act on environmental concerns. Most of such studies on green philosophy and green marketing are done in developed countries but such studies however, remain conspicuously missing in the context of developing economies like India. The present study discusses the concept of green marketing and its interface with consumers in India. A field survey of consumers was conducted to understand their perception towards green marketing and preference for green products. The data collected was analyzed by using the T-test and One Way ANOVA. The results of the study are highly relevant in this challenging era of liberalization and globalization and can be used by industries for exploring and exploiting new opportunities. This study also provides future direction to researchers in the field of green marketing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.020 |
| Scholarly communication | 0.018 | 0.024 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 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".