|
|
|
Ridzal Hasim
Nowadays due to strong competition in the business environment, only those organizations are successful that they can use the most innovative and successful ways for advertisement to attract their consumers? attention to the products or services that the...
ver más
|
|
|
|
|
|
|
Ângela Leite, Anabela Rodrigues and Sílvia Lopes
Brand experience, brand love, and brand behavior outcomes hold significant importance in management research. Their relevance extends to shaping strategic decision-making, fostering a customer-centric approach, and providing insights into the competitive...
ver más
|
|
|
|
|
|
|
Virgilijus Sakalauskas and Dalia Kriksciuniene
The growing popularity of e-commerce has prompted researchers to take a greater interest in deeper understanding online shopping behavior, consumer interest patterns, and the effectiveness of advertising campaigns. This paper presents a fresh approach fo...
ver más
|
|
|
|
|
|
|
Kexiao Xie, Dongkai Lin, Weihan Zhu, Yongqiang Ma, Jiaxiong Qiu, Youcheng Chen and Zhidan Chen
Tea is a global economic crop. In the traditional sales model, the quality of tea is difficult to judge via external clues, and it basically relies on consumers to taste and experience it firsthand. However, currently, most e-commerce platforms can only ...
ver más
|
|
|
|
|
|
|
Majid Nasirinejad and Srinivas Sampalli
Home appliance manufacturers have been adding Wi-Fi modules and sensors to devices to make them ?smart? since the early 2010s. However, consumers are still largely unaware of what kind of sensors are used in these devices. In fact, they usually do not ev...
ver más
|
|
|
|
|
|
|
Antiopi Panteli and Basilis Boutsinas
Recommender systems aim to forecast users? rank, interests, and preferences in specific products and recommend them to a user for purchase. Collaborative filtering is the most popular approach, where the user?s past purchase behavior consists of the user...
ver más
|
|
|
|
|
|
|
Christie I. Ezeife and Hemni Karlapalepu
E-commerce recommendation systems usually deal with massive customer sequential databases, such as historical purchase or click stream sequences. Recommendation systems? accuracy can be improved if complex sequential patterns of user purchase behavior ar...
ver más
|
|
|
|
|
|
|
Michail Salampasis, Alkiviadis Katsalis, Theodosios Siomos, Marina Delianidi, Dimitrios Tektonidis, Konstantinos Christantonis, Pantelis Kaplanoglou, Ifigeneia Karaveli, Chrysostomos Bourlis and Konstantinos Diamantaras
Research into session-based recommendation systems (SBSR) has attracted a lot of attention, but each study focuses on a specific class of methods. This work examines and evaluates a large range of methods, from simpler statistical co-occurrence methods t...
ver más
|
|
|
|
|
|
|
Pejman Ebrahimi, Marjan Basirat, Ali Yousefi, Md. Nekmahmud, Abbas Gholampour and Maria Fekete-Farkas
The purpose of this paper is to reveal how social network marketing (SNM) can affect consumers? purchase behavior (CPB). We used the combination of structural equation modeling (SEM) and unsupervised machine learning approaches as an innovative method. T...
ver más
|
|
|
|
|
|
|
Pejman Ebrahimi, Aidin Salamzadeh, Maryam Soleimani, Seyed Mohammad Khansari, Hadi Zarea and Maria Fekete-Farkas
This study evaluated the impact of startup technology innovations and customer relationship management (CRM) performance on customer participation, value co-creation, and consumer purchase behavior (CPB). This analytical study empirically tested the prop...
ver más
|
|
|
|