| مشخصات مقاله | |
| ترجمه عنوان مقاله | مدلسازی شبکه عصبی رضایت مصرف کننده در تجارت موبایلی: یک تحلیل تجربی |
| عنوان انگلیسی مقاله | Neural network modeling of consumer satisfaction in mobile commerce: An empirical analysis |
| انتشار | مقاله سال 2021 |
| تعداد صفحات مقاله انگلیسی | 16 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 | |
| ایمپکت فاکتور(IF) |
6.954 درسال 2020 |
| شاخص H_index | 207 درسال 2020 |
| شاخص SJR | 1.368 درسال 2020 |
| شناسه ISSN | 0957-4174 |
| شاخص Quartile (چارک) | Q1 درسال 2020 |
| فرضیه | دارد |
| مدل مفهومی | دارد تصویر 1 صفحه 3 |
| پرسشنامه | ندارد |
| متغیر | دارد بخش 3.2 در صفحه 5 |
| رفرنس | دارد |
| رشته های مرتبط | مدیریت، فناوری اطلاعات |
| گرایش های مرتبط | بازاریابی، مدیریت فناوری اطلاعات، تجارت الکترونیکی |
| نوع ارائه مقاله |
ژورنال |
| مجله | سیستم های خبره با کاربردها – Expert Systems With Applications |
| کلمات کلیدی | تجارت موبایلی، رضایت مصرف کننده، شبکه عصبی مصنوعی، تحرک، اعتماد |
| کلمات کلیدی انگلیسی | Mobile commerce, Consumer satisfaction, Artificial neural network, Mobility, Trust |
| شناسه دیجیتال – doi |
https://doi.org/10.1016/j.eswa.2021.114803 |
| کد محصول | E15582 |
| 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 Graphical abstract Keywords Introduction Literature review and research model Research methodology Empirical findings ANNs The selection of ANN parameters Sensitivity analysis Discussion and implications Conclusion, limitations and avenues for future research CRediT authorship contribution statement Declaration of Competing Interest Acknowledgements References |
| بخشی از متن مقاله: |
| ABSTRACT The mobile commerce (m-commerce) industry has rapidly grown in value in recent years, as has the number of m-commerce service providers and interest in it from consumers and academia alike. In order to ensure customer loyalty, providers must determine which factors influence consumer satisfaction in m-commerce. Therefore, the objective of this study is to determine and rank the significant predictors of satisfaction in m-commerce. The paper also develops a procedure for artificial neural network model design and parameter setting in technology acceptance studies. Data was collected from 224 users of m-commerce services. The results presented are based on a combination of structural equation modeling (SEM) and artificial neural network (ANN) analyses. A multilayer perceptron was used for ANN modeling. The results show that the optimal ANN model has one hidden layerand a sigmoid as an activation function in both layers, while the number of hidden nodes should be determined using a recommended rule-of-thumb. In addition, mobility and trust were found to be the most significant determinants of consumer satisfaction in m-commerce. The results of the study are significant as they have important implications for both academia and companies, due to the fact that some of the factors investigated in the study, such as mobility, have rarely been explored in previous consumer satisfaction studies, but were proved to be very significant. Another important result of the study is the proposal of a detailed procedure of ANN model design and the recommendations made for the selection of ANN model architecture and parameter settings. Introduction Mobile phones are nowadays the most popular devices used forcommunication among people (eMarketer, 2016), not only for conversation but also e-mail, text messaging and video calls. Increasingly mobile devices – particularly smartphones and tablets – are being used for many other activities, including purchases and payments. |