مقاله انگلیسی رایگان در مورد پیش بینی مسیر تبدیل موفقیت آمیز – الزویر 2019

 

مشخصات مقاله
ترجمه عنوان مقاله آیا شما هنوز آنلاین یا سیار هستید؟ – پیش بینی مسیر تبدیل موفقیت آمیز در دستگاههای مختلف
عنوان انگلیسی مقاله Are you still online or are you already mobile? – Predicting the path to successful conversions across different devices
انتشار مقاله سال 2019
تعداد صفحات مقاله انگلیسی 12 صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه الزویر
نوع نگارش مقاله
مقاله پژوهشی (Research Article)
مقاله بیس این مقاله بیس میباشد
نمایه (index) Scopus – Master Journals List – JCR
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF)
4.218 در سال 2018
شاخص H_index 65 در سال 2019
شاخص SJR 1.211 در سال 2018
شناسه ISSN 0969-6989
شاخص Quartile (چارک) Q1 در سال 2018
مدل مفهومی دارد
پرسشنامه ندارد
متغیر دارد
رفرنس دارد
رشته های مرتبط مدیریت
گرایش های مرتبط بازاریابی
نوع ارائه مقاله
ژورنال
مجله / کنفرانس مجله خرده فروشی و خدمات مصرف کننده – Journal of Retailing and Consumer Services
دانشگاه  University of Rostock, Ulmenstraße 69, 18057, Rostock, Germany
کلمات کلیدی مدلسازی نسبی، زنجیره های مارکوف، تجربه مشتری
کلمات کلیدی انگلیسی Attribution modeling، Markov chains، Customer experience
شناسه دیجیتال – doi
https://doi.org/10.1016/j.jretconser.2019.04.005
کد محصول  E13438
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
دانلود رایگان مقاله دانلود رایگان مقاله انگلیسی
سفارش ترجمه این مقاله سفارش ترجمه این مقاله

 

فهرست مطالب مقاله:
Abstract
1. Introduction
2. Conceptual framework
3. Data collection
4. Results and discussion
5. Conclusion
References

 

بخشی از متن مقاله:
Abstract

As digitalization increases, retail firms must invest in online and mobile commerce to attract customers to their website or mobile store. Since the type of device used to access marketing channels influences conversions, this research examines the different impacts of different devices such as desktop computers, tablets, and smartphones on the success of various marketing channels. We find customer experience (CX) to be important in improving attribution outcomes (e.g., conversion rates) by combining clickstream and survey data to understand consumers’ decision processes. Therefore, this paper also conceptualizes and measures perceptions of CX of clickstream-data participants. We identify the central implications of using each device.

Introduction

Due to rapid evolutions in technology, interactions between customers and retail firms have fundamentally changed (Grewal et al., 2017). Customer nowadays have evolving expectations of retailers because of reduced information asymmetries, past experiences, higher levels of customer orientation, or the multiplication of media outlets (e.g., Kumar, 2018). Retailers are interested in how customer behavior is changing as a result of the adoption of different devices for shopping purposes in both the online and mobile contexts (Kannan and Li, 2017; Souiden et al., 2018). Whereas the online context is mainly represented by desktop computers, customers increasingly use smartphones and tablets as primary devices for shopping in the mobile context (Criteo, 2018). Thus, retail firms are challenged by high levels of diversity and complexity in customer journey configurations across different devices used by customers (Harris et al., 2018). As a consequence, both scholars and practitioners are shifting their primary focus to the allocation of investments to attract customers to online or mobile stores, respectively (e.g., Marketing Science Institute, 2016; 2018). Since the effect of marketing channels (e.g., display advertising) on conversions is expected to differ across different devices, research has been encouraged to include tablets and smartphones in attribution modeling (Kannan and Li, 2017; Lemon and Verhoef, 2016; Souiden et al., 2018). Thus, the first objective of this research is to understand the effectiveness of various marketing channels across desktop, tablet, and smartphone devices in enhancing retailers’ performance of marketing channel budget allocation. Against this background, user-specific clickstream data was collected from a retailer that runs both an online and a mobile store. The paper implements an existing attribution model (Anderl et al., 2016) that tracks customer behavior at device level.

دیدگاهتان را بنویسید

نشانی ایمیل شما منتشر نخواهد شد. بخش‌های موردنیاز علامت‌گذاری شده‌اند *

دکمه بازگشت به بالا