Purpose <p>This study aims to classify various start-ups based on their experiences with digital marketing adoption. It examines the characteristics of these start-ups and how they interact to influence the adoption process.</p> Design/methodology/approach <p>A quantitative research approach was adopted, utilizing questionnaires administered to 205 founders and managers of Egyptian start-ups. Data were collected on the usage of digital marketing tools, level of utilization, duration of adoption, resource allocation, and budget. A nonparametric decision tree algorithm, visualized using R, was employed for data analysis.</p> Findings <p>The study identifies key characteristics of start-ups that influence their classification in terms of digital marketing adoption. Factors such as digital marketing experience, time and budget allocation, and utilization levels significantly impact this classification. Furthermore, website usage emerged as a crucial criterion distinguishing basic from moderate digital marketing adopters among Egyptian start-ups.</p> Originality <p>This research enhances the understanding of digital marketing adoption among Egyptian start-ups. By classifying start-ups based on demographics and digital marketing practices using a decision tree algorithm, it offers a novel perspective on the topic.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Classification of start-ups’ digital marketing adoption experiences: an investigation of characteristics and interactions

  • Dina El-Shihy,
  • Noha Hassan

摘要

Purpose

This study aims to classify various start-ups based on their experiences with digital marketing adoption. It examines the characteristics of these start-ups and how they interact to influence the adoption process.

Design/methodology/approach

A quantitative research approach was adopted, utilizing questionnaires administered to 205 founders and managers of Egyptian start-ups. Data were collected on the usage of digital marketing tools, level of utilization, duration of adoption, resource allocation, and budget. A nonparametric decision tree algorithm, visualized using R, was employed for data analysis.

Findings

The study identifies key characteristics of start-ups that influence their classification in terms of digital marketing adoption. Factors such as digital marketing experience, time and budget allocation, and utilization levels significantly impact this classification. Furthermore, website usage emerged as a crucial criterion distinguishing basic from moderate digital marketing adopters among Egyptian start-ups.

Originality

This research enhances the understanding of digital marketing adoption among Egyptian start-ups. By classifying start-ups based on demographics and digital marketing practices using a decision tree algorithm, it offers a novel perspective on the topic.