How the digital environment moderates disruptive technology and digital entrepreneurship relationship in emerging markets
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,016 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,000 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».