How the digital environment moderates disruptive technology and digital entrepreneurship relationship in emerging markets
Bibliographic record
Abstract
Purpose About 50% of innovations achieve commercial success in advanced countries. The number is much lower in emerging markets. Examining the impact of the digital environment on product success is crucial. The purpose of the study is to investigate the direct effects of disruptive technology (quality, efficiency and congruity) on digital entrepreneurship (new product development, cost-effectiveness and internationalization) and indirect moderating effects of the digital environment (data security, customer privacy and search engine optimization [SEO] algorithm) between disruptive technology and digital entrepreneurship. Design/methodology/approach This is a qualitative study by design. It uses the literature review method and the theory of disruption and competitive advantage to construct the six hypotheses linking the variables – disruptive technology, digital environment and digital entrepreneurship. Findings The study’s conceptual model proposes that disruptive technology leads to digital entrepreneurship; however, the digital environment moderates the relationship between disruptive technology and digital entrepreneurship in emerging markets. Research limitations/implications The conceptual study has research implications for scholars. It constructs a conceptual framework and develops six hypotheses contextualized in emerging markets. The framework can be empirically tested across countries to validate the hypotheses and develop a competing model to explain more variance in digital entrepreneurship. This study also presents the possibility of analytical generalization. Practical implications This study has practical implications for digital entrepreneurs in emerging markets or those wishing to enter emerging markets. The main implication is that disruptive technology leads to digital entrepreneurship; however, the digital environment moderates it. Thus, digital entrepreneurs need to consider digital environmental effects such as data security, customer privacy and SEO. Given that two-thirds of the world is classified as an emerging market, the impact of the study is noticeable for practitioners as well. Social implications Disruptive technology fosters digital entrepreneurship, which creates opportunities for innovative solutions for society worldwide. It breaks down the barriers to entry and promotes inclusivity by providing products and services that were unavailable before. Digital products are also economical and environmentally friendly, making them more suitable for people in emerging markets. Originality/value This study makes three new contributions. First, it proposes that disruptive technology leads to digital entrepreneurship and that the digital environment moderates the relationship between disruptive technology and digital entrepreneurship. Second, from a theoretical viewpoint, it develops a theoretical testable framework, links the variables and proposes the six hypotheses. Finally, the most significant contribution of the study is the identification of the digital environment variable and its dimensions – security, privacy and SEO algorithm – and its comparison between advanced countries and emerging markets.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".