Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.8
3.9
Journals
Sustainability
Special Issues
E-commerce and Sustainability
sustainability-logo
Submit to Sustainability Review for Sustainability Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

E-commerce and Sustainability

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: closed (15 March 2022) | Viewed by 34907

Special Issue Editors

Dr. Muhammad Fazal Ijaz

E-Mail Website
Guest Editor
Department of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, Korea
Interests: IoT; big data analytics; e-commerce; sustainability; digital health; data science; artificial intelligence; sensors
Special Issues, Collections and Topics in MDPI journals
Dr. Abu ul Hassan Sarwar Rana

E-Mail Website
Guest Editor
Department of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, Korea
Interests: advanced manufacturing; machine learning; renewable energy; materials science; electrical machines and robotics; project management; industrial management; sustainability
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, the development of e-commerce has gradually increased throughout the world. Analysis has shown that the e-commerce platform is more convenient and has more product selection choices. However, this e-commerce advancement does not mean that all e-commerce companies are making profits. There are many challenges to e-commerce, such as the absence of online identify verification, delivering worse customer experience, failing to analyze competitors, being stuck in the old ways of selling products, shopping cart abandonment, difficulties in customer loyalty management, struggles to compete on price and shipping, and data security problems. These problems occur due to the lack of business, product, and service information. To solve the above challenges, artificial intelligence (AI) and big data techniques are utilized to maximize e-commerce.

Big data consists of the variety and volume of data, including business process details, product information, customer interest, and request-related details. The data are collected according to user surveys, competitor choices, sales criteria, and reviews, which help identify customers' exact requirements. The collected details are processed by applying AI techniques to overcome the e-commerce above challenges. AI techniques can effectively predict future market trends, purchasing criteria, and competitor opinions. Moreover, big data and AI techniques analyze the e-commerce data using an effective learning process affordably and flexibly. Recent advancements of AI have been transforming the electronic e-commerce industry. By using AI capabilities such as self-learning algorithms and natural language processing (NLP), they are enhancing the impact of AI in e-commerce. Furthermore, AI personalization in e-commerce marketing can also enable e-commerce firms to analyze customers' behavior and make precise recommendations.

Therefore, many researchers are interested in investigating e-commerce data to provide guidelines for improving the overall business process. Consequently, this Special Issue focuses on big-data and AI-based e-commerce that will offer an effective platform to develop a better solution for new e-commerce consumers.

The topics of interest for the Special Issue include, but are not limited to, the following:

  • Artificial intelligence in e-commerce and supply chains;
  • AI-based financial technology
  • AI for risk control and management in e-commerce
  • Localization based service in e-commerce
  • Cross-cultural issues in e-commerce
  • Big data analytics for prediction and applications in e-commerce
  • Application of Blockchain technology in e-commerce
  • Logistic management process in e-commerce using optimized machine learning techniques
  • Novel business models and automations in the digital economy;
  • Social impact and interactions in digital economy;
  • Environmental impact and interactions in digital economy;
  • Smart logistics and Sustainable supply chain;
  • Modeling and simulation of business processes;
  • Sustainable e-business;
  • Sustainable business practices;
  • Sustainable e-business model;
  • E-business modeling;
  • Green marketing;
  • Sustainable strategy;
  • Incorporating business ethics into strategy;
  • Sustainable business awards;
  • The social dimension of sustainability in retail marketing;
  • Sustainability communication in retail marketing;
  • In-store and web communication for sustainability.

Dr. Muhammad Fazal Ijaz
Dr. Abu Rana
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sustainability
  • sustainable marketing
  • digital economy
  • supply chain
  • sustainable e-business

Published Papers (7 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

15 pages, 5052 KiB  
Article
K-Means Clustering Approach for Intelligent Customer Segmentation Using Customer Purchase Behavior Data
by Kayalvily Tabianan, Shubashini Velu and Vinayakumar Ravi
Sustainability 2022, 14(12), 7243; https://0-doi-org.brum.beds.ac.uk/10.3390/su14127243 - 13 Jun 2022
Cited by 31 | Viewed by 10355
Abstract
E-commerce system has become more popular and implemented in almost all business areas. E-commerce system is a platform for marketing and promoting the products to customer through online. Customer segmentation is known as a process of dividing the customers into groups which shares [...] Read more.
E-commerce system has become more popular and implemented in almost all business areas. E-commerce system is a platform for marketing and promoting the products to customer through online. Customer segmentation is known as a process of dividing the customers into groups which shares similar characteristics. The purpose of customer segmentation is to determine how to deal with customers in each category in order to increase the profit of each customer to the business. Segmenting the customers assist business to identify their profitable customer to satisfy their needs by optimizing the services and products. Therefore, customer segmentation helps E-commerce system to promote the right product to the right customer with the intention to increase profits. There are few types of customer segmentation factors which are demographic psychographic, behavioral, and geographic. In this study, customer behavioral factor has been focused. Therefore users will be analyzed using clustering algorithm in determining the purchase behavior of E-commerce system. The aim of clustering is to optimize the experimental similarity within the cluster and to maximize the dissimilarity in between clusters. In this study there are relationship between three clusters: event type, products, and categories. In this research, the proposed approach analyzed the groups that share similar criteria to help vendors to identify and focus on the high profitable segment to the least profitable segment. This type of analysis can play important role in improving the business. Grouping their customer according to their similar behavioral factor to sustain their customer for long-term and increase their business profit. It also enables high exposure of the e-offer to gain attention of potential customers. In order to process the collected data and segment the customers, an learning algorithm is used which is known as K-Means clustering. K-Means clustering is implemented to solve the clustering problems. Full article
(This article belongs to the Special Issue E-commerce and Sustainability)
►▼ Show Figures

Figure 1

23 pages, 1263 KiB  
Article
Inclusive Digital Innovation in South Africa: Perspectives from Disadvantaged and Marginalized Communities
by Willard Munyoka
Sustainability 2022, 14(9), 5372; https://0-doi-org.brum.beds.ac.uk/10.3390/su14095372 - 29 Apr 2022
Cited by 1 | Viewed by 2640
Abstract
Inclusive digital innovation (IDI) entails rolling out policies and digital innovations to ensure equal access to services and new goods by previously excluded and marginalized societies. Digital commerce (d-commerce) has the potential to foster an inclusive community through IDI empowerment in emerging economies; [...] Read more.
Inclusive digital innovation (IDI) entails rolling out policies and digital innovations to ensure equal access to services and new goods by previously excluded and marginalized societies. Digital commerce (d-commerce) has the potential to foster an inclusive community through IDI empowerment in emerging economies; however, the literature on inclusive digital innovation and citizen empowerment is limited on the effect of e-strategy policies and empowerment on d-commerce adoption, use, and recommendation propensity. Underpinned by three theories: the Extended Unified Theory of Acceptance and Use of Technology, the citizen empowerment theory, and the affective decision-making theory of optimism bias and risk, this study proposes a model to establish the determinants of use intention, use behavior, and propensity to recommend d-commerce in disadvantaged and marginalized communities in South Africa. Using survey data from 983 disadvantaged d-commerce users to test the proposed model and hypotheses using IBM Amos for Windows and structural equation modeling (SEM), this paper provides a unique narrative to the empowerment discourse of marginalized people. Results show that privacy, security, trust, and citizen empowerment positively influence use intention and optimism bias, use behavior, and citizen empowerment mediate the propensity to recommend. Factors that promote or hinder citizens’ choices to use and recommend d-commerce are pertinent to scholars, government agencies, and regulators seeking better policy implementations to eradicate socio-economic inequalities, sustainable societies, and the empowerment of disadvantaged and marginalized people. Full article
(This article belongs to the Special Issue E-commerce and Sustainability)
►▼ Show Figures

Figure 1

39 pages, 3383 KiB  
Article
Fashion E-Tail and the Impact of Returns: Mapping Processes and the Consumer Journey towards More Sustainable Practices
by Carolina Bozzi, Marco Neves and Claudia Mont’Alvão
Sustainability 2022, 14(9), 5328; https://0-doi-org.brum.beds.ac.uk/10.3390/su14095328 - 28 Apr 2022
Cited by 4 | Viewed by 3847
Abstract
The purpose of this study is to trace the processes behind the elaboration of the product page and map the shopping journey to identify ways to reduce returns. This is a qualitative study conducted in three stages: exploratory interviews with users, semi-structured interviews [...] Read more.
The purpose of this study is to trace the processes behind the elaboration of the product page and map the shopping journey to identify ways to reduce returns. This is a qualitative study conducted in three stages: exploratory interviews with users, semi-structured interviews with e-commerce and logistics specialists, and directed storytelling sessions with users. Our findings indicate that the e-commerce specialists are not fully aware of the impacts caused by the high return rates, and product presentation pages are therefore not elaborated to provide users with all the information necessary to make accurate purchases. Sellers should improve product presentation pages to increase product knowledge by providing tools to enhance quality mental imagery. Additionally, sellers should inform consumers of the impact of their shipping options and returning habits. There are ways to optimize logistics processes to reduce the environmental impact. Prior research has addressed these issues separately. Besides, have addressed mental imagery to increase sales. This study brings a holistic approach and brings mental imagery as a tool to provide users with more information about a product. Full article
(This article belongs to the Special Issue E-commerce and Sustainability)
►▼ Show Figures

Figure 1

18 pages, 2473 KiB  
Article
How Web Content Types Improve Consumer Engagement through Scarcity and Interactivity of Mobile Commerce?
by Ming Wang and Jaewon Choi
Sustainability 2022, 14(9), 4898; https://0-doi-org.brum.beds.ac.uk/10.3390/su14094898 - 19 Apr 2022
Cited by 3 | Viewed by 2102
Abstract
The emergence of various web contents gives customers influence according to characteristics. The characteristics of the content can distinguish the three types of commerce: branded content-type commerce, review content-type commerce, and home shopping content-type commerce. The purpose of this study is to identify [...] Read more.
The emergence of various web contents gives customers influence according to characteristics. The characteristics of the content can distinguish the three types of commerce: branded content-type commerce, review content-type commerce, and home shopping content-type commerce. The purpose of this study is to identify the difference between customer engagement and reuse intention according to the three types of content characteristics. To identify the research questions, we conducted experiment and survey for three different commerce types. Randomized participants were exposed to different three web contents. Analysis of variance (ANOVA) was applied to compare three groups on average to analyze the differences between those groups. After testing the manipulation of experiment, structural equation modeling for various antecedents was performed. Interaction had a positive effect on engagement, as we prove within the paper. Content information had a positive impact on engagement, as you can see within the research. The effect of attention on engagement was confirmed as positive. Results of analysis proved our hypotheses; thus, scarcity of time had a positive effect on engagement and scarcity of quantity had a positive effect on engagement, as we prove within the paper. Ubiquity has a positive effect on engagement. System quality positively affects engagement. Ease of use has a positive effect on engagement. Consumer engagement had a positive effect on reuse intention. Finally, there are differences among the three kinds of mobile commerce as a conclusion within the findings. Full article
(This article belongs to the Special Issue E-commerce and Sustainability)
►▼ Show Figures

Figure 1

13 pages, 755 KiB  
Article
Drivers of Consumer Participation in Online Second-Hand Transactions
by Pedro Hinojo, David Suárez and Begoña García-Mariñoso
Sustainability 2022, 14(7), 4318; https://0-doi-org.brum.beds.ac.uk/10.3390/su14074318 - 05 Apr 2022
Cited by 4 | Viewed by 4624
Abstract
Consumer participation in second-hand transactions is increasing, facilitated by digital platforms in the form of apps or websites. This study sheds light on the factors behind consumers’ decisions to demand used goods via online platforms. Applying a logit model to a sample of [...] Read more.
Consumer participation in second-hand transactions is increasing, facilitated by digital platforms in the form of apps or websites. This study sheds light on the factors behind consumers’ decisions to demand used goods via online platforms. Applying a logit model to a sample of 6705 internet users in Spain, we explore the role of economic variables, situational factors and individual characteristics. Our original findings indicate that the use of online platforms to buy or rent second-hand goods is more likely when being male, relatively young, with children, a frequent internet user, with employment and living in a household with some price-consciousness and environmental awareness. The scarcity of brick-and-mortar stores in the area and car ownership can also increase demand for used goods through online platforms. Full article
(This article belongs to the Special Issue E-commerce and Sustainability)
►▼ Show Figures

Figure 1

16 pages, 2701 KiB  
Article
Return Rate Prediction in Blockchain Financial Products Using Deep Learning
by Noura Metawa, Mohamemd I. Alghamdi, Ibrahim M. El-Hasnony and Mohamed Elhoseny
Sustainability 2021, 13(21), 11901; https://0-doi-org.brum.beds.ac.uk/10.3390/su132111901 - 28 Oct 2021
Cited by 10 | Viewed by 2388
Abstract
Recently, bitcoin-based blockchain technologies have received significant interest among investors. They have concentrated on the prediction of return and risk rates of the financial product. So, an automated tool to predict the return rate of bitcoin is needed for financial products. The recently [...] Read more.
Recently, bitcoin-based blockchain technologies have received significant interest among investors. They have concentrated on the prediction of return and risk rates of the financial product. So, an automated tool to predict the return rate of bitcoin is needed for financial products. The recently designed machine learning and deep learning models pave the way for the return rate prediction process. In this aspect, this study develops an intelligent return rate predictive approach using deep learning for blockchain financial products (RRP-DLBFP). The proposed RRP-DLBFP technique involves designing a long short-term memory (LSTM) model for the predictive analysis of return rate. In addition, Adam optimizer is applied to optimally adjust the LSTM model’s hyperparameters, consequently increasing the predictive performance. The learning rate of the LSTM model is adjusted using the oppositional glowworm swarm optimization (OGSO) algorithm. The design of the OGSO algorithm to optimize the LSTM hyperparameters for bitcoin return rate prediction shows the novelty of the work. To ensure the supreme performance of the RRP-DLBFP technique, the Ethereum (ETH) return rate is chosen as the target, and the simulation results are investigated in different measures. The simulation outcomes highlighted the supremacy of the RRP-DLBFP technique over the current state of art techniques in terms of diverse evaluation parameters. For the MSE, the proposed RRP-DLBFP has 0.0435 and 0.0655 compared to an average of 0.6139 and 0.723 for compared methods in training and testing, respectively. Full article
(This article belongs to the Special Issue E-commerce and Sustainability)
►▼ Show Figures

Figure 1

27 pages, 592 KiB  
Article
Adoption and Usage of E-Grocery Shopping: A Context-Specific UTAUT2 Model
by Ellen Van Droogenbroeck and Leo Van Hove
Sustainability 2021, 13(8), 4144; https://0-doi-org.brum.beds.ac.uk/10.3390/su13084144 - 08 Apr 2021
Cited by 32 | Viewed by 7481
Abstract
In order to determine how sustainable online grocery shopping is as a practice, it is crucial to have an in-depth understanding of its drivers. This paper therefore validates the Unified Theory of Acceptance and Use of Technology (UTAUT2) in the context of e-grocery [...] Read more.
In order to determine how sustainable online grocery shopping is as a practice, it is crucial to have an in-depth understanding of its drivers. This paper therefore validates the Unified Theory of Acceptance and Use of Technology (UTAUT2) in the context of e-grocery and enriches it with five constructs. We exploit a self-administered survey among 560 customers of two Belgian supermarkets and test the model by means of hierarchical multiple regression analysis. We do so not only for the full sample, but also for users and non-users separately. For the full sample, four of the five proposed context-specific constructs—namely, perceived risk, perceived time pressure, perceived in-store shopping enjoyment, and innovativeness—help better explain the intention to adopt or continue to use e-grocery services. In the subsamples, only perceived time pressure and innovativeness add explanatory power, and this only for non-users. In other words, the additional constructs primarily help discriminate between users and non-users. In addition, while the extended model outperforms the original UTAUT2 model for all three samples, the added value of the extended model does not so much lie in a higher explained variance, but rather in a more correct identification of the drivers of BI. Full article
(This article belongs to the Special Issue E-commerce and Sustainability)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-7
Back to TopTop