Article
Business
Hsiao-Ting Tseng, Niloofar Aghaali, Nick Hajli
Summary: New product development is a complex process in marketing, and the success of new products is crucial for firms. This study explores how big data analytics can aid firms in tracking the success of new products. The findings suggest that effective use of data interpretation and data analysis tools are key factors in achieving customer agility and ensuring new product success.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2022)
Article
Business
Morteza Zihayat, Anteneh Ayanso, Heidar Davoudi, Mehdi Kargar, Nigussie Mengesha
Summary: This study introduces a novel framework for modeling customer satisfaction, which predicts customer satisfaction at specific times using data-driven attributes and a time-aware model. The framework also utilizes a learn-to-rank model to enhance the accuracy of the satisfaction model.
JOURNAL OF BUSINESS RESEARCH
(2021)
Article
Mathematics, Interdisciplinary Applications
Weihua Huang
Summary: This article discusses the fairness and efficiency of multiuser sharing of multi-dimensional learning resources in shared clusters, emphasizing the importance of optimizing resource allocation in dynamic scenarios. Through research and analysis of big data processing technology and systems, the paper explores the application of multidimensional analysis and performance optimization technology.
Article
Psychology, Multidisciplinary
Shasha Teng, Kok Wei Khong
Summary: While previous studies on mobile payment mainly focused on consumer adoptions and barriers, little attention was paid to ecosystem factors. This study utilized big data analytics to examine actual usage of e-wallets, revealing factors attracting users, successful business model measures, competition dynamics, and low rates of merchant adoption. The findings highlight the importance of understanding user behavior and addressing ecosystem challenges for sustainable mobile payment development.
COMPUTERS IN HUMAN BEHAVIOR
(2021)
Article
Computer Science, Artificial Intelligence
Lisa Schetgen, Matthias Bogaert, Dirk Van den Poel
Summary: This study demonstrates the value of Facebook data in predicting first-time donation behavior and acquiring new donors for nonprofit organizations. The combination of singular value decomposition and logistic regression outperformed other analytical methodologies, with Facebook pages and categories being the most important data types. Factors related to age, education, residence, and other dimensions played a significant role in predicting donation behavior.
DECISION SUPPORT SYSTEMS
(2021)
Article
Information Science & Library Science
Dimitrios Buhalis, Katerina Volchek
Summary: The integration of technology in business strategy complicates marketing communications and necessitates advanced marketing performance analysis; the paper proposes a novel taxonomy and examines the capabilities of marketing attribution methods for improving value attribution accuracy.
INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT
(2021)
Article
Business
Amit Kumar Kushwaha, Prashant Kumar, Arpan Kumar Kar
Summary: This study investigates the influencing factors of AI-based chatbots in B2B firms from the perspective of CX theories, proposing an organizational model for CX using various theories. The research utilizes social media data for validation, revealing that CX in B2B enterprises using chatbots is influenced by overall system design, customers' ability to use technology, and customer trust towards the brand and system.
INDUSTRIAL MARKETING MANAGEMENT
(2021)
Article
Business
Anastasia Griva
Summary: This study mines customer satisfaction segments using data from a CS survey in 140 e-commerce stores. It presents examples of how one store utilized the segments for automated marketing actions. The findings contribute to decision making and industry benchmarking.
JOURNAL OF RETAILING AND CONSUMER SERVICES
(2022)
Article
Computer Science, Information Systems
Yuan Gao, Liquan Chen, Ge Wu, Qianmu Li, Tong Fu
Summary: With the rapid development of IoT, the focus of research has turned to big data analytics. However, most research has neglected the wishes and profits of participants in BDA. This paper aims to provide a theoretical model for the practical application of BDA in IoT and proves the feasibility of participants voluntarily participating in BDA-IoT for the first time. A non-cooperative game theory model with incentive and payment mechanisms is constructed, and the multi-party interaction process in BDA-IoT is simulated. The results show the feasibility of the model in improving the benefits of all stakeholders in a non-cooperative game.
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
(2023)
Article
Computer Science, Information Systems
Yuxing Chen, Peter Goetsch, Mohammad A. Hoque, Jiaheng Lu, Sasu Tarkoma
Summary: This paper presents a performance prediction framework called d-Simplexed to address the challenge of understanding the relationship between different parameter configurations in Spark. By constructing a mesh using computational geometry and using adaptive sampling techniques, execution time can be predicted with high accuracy.
IEEE TRANSACTIONS ON BIG DATA
(2022)
Article
Computer Science, Artificial Intelligence
Abdolreza Mosaddegh, Amir Albadvi, Mohammad Mehdi Sepehri, Babak Teimourpour
Summary: The study examined the dynamics of bank customer value segments using big data analytics, identifying six major categories such as Local Leaders and Market Trend Initiators which can be predictors of future market dynamics. This approach uses current customer dynamics to predict CLV and adapt to changing market conditions, offering insights into future market trends.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Interdisciplinary Applications
Mohammad Soltani Delgosha, Nastaran Hajiheydari, Sayed Mahmood Fahimi
Summary: This study aims to understand and prioritize the strategic applications, main drivers, and key challenges of implementing big data analytics in banks. The findings reveal that the most important applications of big data in banks are fraud detection and credit risk analysis, with decision-making enhancement and new product/service development being the main drivers for initiating big data initiatives. The main challenge threatening these efforts and expected outputs is information silos and unintegrated data.
JOURNAL OF ENTERPRISE INFORMATION MANAGEMENT
(2021)
Article
Business
Hsiao-Ting Tseng
Summary: In recent years, data-driven strategy formulation has become a popular trend in business. This study aims to explore how big data can be effectively used to understand customers quantitatively. The findings suggest that using big data analysis tools can enhance customer sensing and response capabilities, ultimately leading to new product success. The implications of this study are discussed from both theoretical and practical perspectives.
JOURNAL OF BUSINESS RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Wu He, Jui-Long Hung, Lixin Liu
Summary: This paper presents a case study in the banking industry to explain how to help enterprises leverage big data analytics for changes. The study identifies both non-technical and technical factors that influence the progress of big data implementation.
JOURNAL OF ENTERPRISE INFORMATION MANAGEMENT
(2023)
Review
Computer Science, Interdisciplinary Applications
Fangyu Li, Yuanjun Laili, Xuqiang Chen, Yihuai Lou, Chen Wang, Hongyan Yang, Xuejin Gao, Honggui Han
Summary: The construction industry is undergoing an intelligent revolution enabled by technologies like IoT, cloud computing, and robotics. Utilizing diverse big data from multiple sources can enhance efficiency, reduce waste and expenses, improve planning and decision-making processes, lower errors, and enhance safety at construction sites. This article provides a comprehensive review of the advantages and current state of big data in the construction industry, addressing unresolved difficulties and offering thoughts on its potential future.
JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION
(2023)