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Articles 1 - 20 of 20
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Understanding The Impact Of Trade Policy Effect Uncertainty On Firm-Level Innovation Investment: A Deep Learning Approach, Daniel Chang, Nan Hu, Peng Liang, Morgan Swink
Understanding The Impact Of Trade Policy Effect Uncertainty On Firm-Level Innovation Investment: A Deep Learning Approach, Daniel Chang, Nan Hu, Peng Liang, Morgan Swink
Research Collection School Of Computing and Information Systems
Integrating the real options perspective and resource dependence theory, this study examines how firms adjust their innovation investments to trade policy effect uncertainty (TPEU), a less studied type of firm specific, perceived environmental uncertainty in which managers have difficulty predicting how potential policy changes will affect business operations. To develop a text-based, context-dependent, time-varying measure of firm-level perceived TPEU, we apply Bidirectional Encoder Representations from Transformers (BERT), a state-of-the-art deep learning approach. We apply BERT to analyze the texts of mandatory Management Discussion and Analysis (MD&A) sections of annual reports for a sample of 22,669 firm-year observations from 3,181 unique …
Human-Centred Artificial Intelligence In The Banking Sector, Krishnaraj Arul Obuchettiar, Alan @ Ali Madjelisi Megargel
Human-Centred Artificial Intelligence In The Banking Sector, Krishnaraj Arul Obuchettiar, Alan @ Ali Madjelisi Megargel
Research Collection School Of Computing and Information Systems
Changes in technology have shaped how corporate and retail businesses have evolved, alongside the customers’ preferences. The advent of smart digital devices and social media has shaped how consumers interact and transact with their financial institutions over the past two decades. With the rapid evolution of new technologies and customers' growing preference for digital engagement with financial institutions, organizations need to adopt and align with emerging technologies that support speed, accuracy, efficiency, and security in a user-friendly manner. Today, consumers want hyper-personalized interactions that are more frequent and proactive. Moreover, financial institutions have a growing need to cater to consumers' …
The Important Role Of System Dynamics Investigation On Business Model, Industry And Performance Management, Lina Gozali, Teuku Yuri M. Zagloel, Togar Mangihut Simatupang, Wahyudi Sutopo, Aldy Gunawan, Yun-Chia Liang, Bernardo Nugroho Yahya, Jose Arturo Garza-Reyes, Agustinus Purna Irawan, Yuliani Suseno
The Important Role Of System Dynamics Investigation On Business Model, Industry And Performance Management, Lina Gozali, Teuku Yuri M. Zagloel, Togar Mangihut Simatupang, Wahyudi Sutopo, Aldy Gunawan, Yun-Chia Liang, Bernardo Nugroho Yahya, Jose Arturo Garza-Reyes, Agustinus Purna Irawan, Yuliani Suseno
Research Collection School Of Computing and Information Systems
Purpose: This research studies the development of the evolving dynamic system model and explores the important elements or factors and what detailed attributes are the main influences model in achieving the success of a business, industry and management. It also identifies the real and major differences between static and dynamic business management models and the detailed factors that influence them. Later, this research investigates the benefits/advantages and limitations/disadvantages of some research studies. The studies conducted in this research put more emphasis on the capabilities of system dynamics (SD) in modeling and the ability to measure, analyse and capture problems in …
Augmenting Fake Content Detection In Online Platforms: A Domain Adaptive Transfer Learning Via Adversarial Training Approach, Ka Chung Ng, Ping Fan Ke, Mike K. P. So, Kar Yan Tam
Augmenting Fake Content Detection In Online Platforms: A Domain Adaptive Transfer Learning Via Adversarial Training Approach, Ka Chung Ng, Ping Fan Ke, Mike K. P. So, Kar Yan Tam
Research Collection School Of Computing and Information Systems
Online platforms are experimenting with interventions such as content screening to moderate the effects of fake, biased, and incensing content. Yet, online platforms face an operational challenge in implementing machine learning algorithms for managing online content due to the labeling problem, where labeled data used for model training are limited and costly to obtain. To address this issue, we propose a domain adaptive transfer learning via adversarial training approach to augment fake content detection with collective human intelligence. We first start with a source domain dataset containing deceptive and trustworthy general news constructed from a large collection of labeled news …
What Should Streamers Communicate In Livestream E-Commerce? The Effects Of Social Interactions On Live Streaming Performance, Danyang Song, Xi Chen, Zhiling Guo, Xiao Liu Liu, Ruijin. Jin
What Should Streamers Communicate In Livestream E-Commerce? The Effects Of Social Interactions On Live Streaming Performance, Danyang Song, Xi Chen, Zhiling Guo, Xiao Liu Liu, Ruijin. Jin
Research Collection School Of Computing and Information Systems
Compared with traditional e-commerce, livestreaming e-commerce is characterized by direct and intimate communication between streamers and consumers that stimulates instant social interactions. This study focuses on streamers’ three types of information exchange (i.e., product information, social conversation, and social solicitation) and examines their roles in driving both short-term and long-term livestreaming performance (i.e., sales and customer base growth). We find that the informational role of product information (nonpromotional and promotional) is beneficial not only to sales performance, but also to the growth of the customer base. We also find that social conversation has a relationship-building effect that positively impacts both …
Learning To Ask Critical Questions For Assisting Product Search, Zixuan Li, Lizi Liao, Tat-Seng Chua
Learning To Ask Critical Questions For Assisting Product Search, Zixuan Li, Lizi Liao, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Product search plays an essential role in eCommerce. It was treated as a special type of information retrieval problem. Most existing works make use of historical data to improve the search performance, which do not take the opportunity to ask for user’s current interest directly. Some session-aware methods take the user’s clicks within the session as implicit feedback, but it is still just a guess on user’s preference. To address this problem, recent conversational or question-based search models interact with users directly for understanding the user’s interest explicitly. However, most users do not have a clear picture on what to …
Ampsum: Adaptive Multiple-Product Summarization Towards Improving Recommendation Captions, Quoc Tuan Truong, Hady Wirawan Lauw, Changhe Yuan, Jin Li, Jim Chan, Soo-Min Pantel, Hady W. Lauw
Ampsum: Adaptive Multiple-Product Summarization Towards Improving Recommendation Captions, Quoc Tuan Truong, Hady Wirawan Lauw, Changhe Yuan, Jin Li, Jim Chan, Soo-Min Pantel, Hady W. Lauw
Research Collection School Of Computing and Information Systems
In e-commerce websites, multiple related product recommendations are usually organized into “widgets”, each given a name, as a recommendation caption, to describe the products within. These recommendation captions are usually manually crafted and generic in nature, making it difficult to attach meaningful and informative names at scale. As a result, the captions are inadequate in helping customers to better understand the connection between the multiple recommendations and make faster product discovery.We propose an Adaptive Multiple-Product Summarization framework (AmpSum) that automatically and adaptively generates widget captions based on different recommended products. The multiplicity of products to be summarized in a widget …
Do Sequels Outperform Or Disappoint? Insights From An Analysis Of Amazon Echo Consumer Reviews, Kyong Jin Shim, Siaw Ling Lo, Su Yee Liew
Do Sequels Outperform Or Disappoint? Insights From An Analysis Of Amazon Echo Consumer Reviews, Kyong Jin Shim, Siaw Ling Lo, Su Yee Liew
Research Collection School Of Computing and Information Systems
Rapid technological advances in recent years drastically transformed our world. Amidst modern technological inventions such as smart phones, smart watches and smart home devices, consumers of electronic digital devices experience greatly improved automation, productivity, and efficiency in conducting routine daily tasks, information searching, shopping as well as finding entertainment. In the last few years, the global smart speaker market has undergone significant growth. As technology continues to advance and smart speakers are equipped with innovative features, the adoption of smart speakers will increase and so will consumer expectations. This research paper presents an aspect-specific sentiment analysis of consumer reviews of …
Automated Theme Search In Ico Whitepapers, Chuanjie Fu, Andrew Koh, Paul Griffin
Automated Theme Search In Ico Whitepapers, Chuanjie Fu, Andrew Koh, Paul Griffin
Research Collection School Of Computing and Information Systems
The authors explore how topic modeling can be used to automate the categorization of initial coin offerings (ICOs) into different topics (e.g., finance, media, information, professional services, health and social, natural resources) based solely on the content within the whitepapers. This tool has been developed by fitting a latent Dirichlet allocation (LDA) model to the text extracted from the ICO whitepapers. After evaluating the automated categorization of whitepapers using statistical and human judgment methods, it is determined that there is enough evidence to conclude that the LDA model appropriately categorizes the ICO whitepapers. The results from a two-population proportion test …
Inferring User Consumption Preferences From Social Media, Yang Li, Jing Jiang, Ting Liu
Inferring User Consumption Preferences From Social Media, Yang Li, Jing Jiang, Ting Liu
Research Collection School Of Computing and Information Systems
Social Media has already become a new arena of our lives and involved different aspects of our social presence. Users' personal information and activities on social media presumably reveal their personal interests, which offer great opportunities for many e-commerce applications. In this paper, we propose a principled latent variable model to infer user consumption preferences at the category level (e.g. inferring what categories of products a user would like to buy). Our model naturally links users' published content and following relations on microblogs with their consumption behaviors on e-commerce websites. Experimental results show our model outperforms the state-of-the-art methods significantly …
Aspect-Based Helpfulness Prediction For Online Product Reviews, Yinfei Yang, Cen Chen, Forrest Sheng Bao
Aspect-Based Helpfulness Prediction For Online Product Reviews, Yinfei Yang, Cen Chen, Forrest Sheng Bao
Research Collection School Of Computing and Information Systems
Product reviews greatly influence purchase decisions in online shopping. A common burden of online shopping is that consumers have to search for the right answers through massive reviews, especially on popular products. Hence, estimating and predicting the helpfulness of reviews become important tasks to directly improve shopping experience. In this paper, we propose a new approach to helpfulness prediction by leveraging aspect analysis of reviews. Our hypothesis is that a helpful review will cover many aspects of a product at different emphasis levels. The first step to tackle this problem is to extract proper aspects. Because related products share common …
Evaluation And Improvement Of Procurement Process With Data Analytics, Melvin H. C. Tan, Wee Leong Lee
Evaluation And Improvement Of Procurement Process With Data Analytics, Melvin H. C. Tan, Wee Leong Lee
Research Collection School Of Computing and Information Systems
Analytics can be applied in procurement to benefit organizations beyond just prevention and detection of fraud. This study aims to demonstrate how advanced data mining techniques such as text mining and cluster analysis can be used to improve visibility of procurement patterns and provide decision-makers with insight to develop more efficient sourcing strategies, in terms of cost and effort. A case study of an organization’s effort to improve its procurement process is presented in this paper. The findings from this study suggest that opportunities exist for organizations to aggregate common goods and services among the purchases made under and across …
Message From General Chair And Program Co-Chairs [Of Icec '12, 14th Annual International Conference On Electronic Commerce, Held In Singapore, 7-8 August 2012], Robert J. Kauffman, Martin Bichler, Hoong Chuin Lau, Christopher Yang, Yinping Yang
Message From General Chair And Program Co-Chairs [Of Icec '12, 14th Annual International Conference On Electronic Commerce, Held In Singapore, 7-8 August 2012], Robert J. Kauffman, Martin Bichler, Hoong Chuin Lau, Christopher Yang, Yinping Yang
Research Collection School Of Computing and Information Systems
Singapore, a major hub in the Asia Pacific region well known for its multi-racial and multicultural society, is proud to host the 14th International Conference on Electronic Commerce. Singapore Management University (SMU), the School of Information Systems (SIS) and the Living Analytics Research Center (LARC) are also delighted to be able to support the delivery of this event.
Manipulation Of Online Reviews: An Analysis Of Ratings, Readability, And Sentiments, Nan Hu, Indranil Bose, Noi Sian Koh, Ling Liu
Manipulation Of Online Reviews: An Analysis Of Ratings, Readability, And Sentiments, Nan Hu, Indranil Bose, Noi Sian Koh, Ling Liu
Research Collection School Of Computing and Information Systems
As consumers become increasingly reliant on online reviews to make purchase decisions, the sales of the product becomes dependent on the word of mouth (WOM) that it generates. As a result, there can be attempts by firms to manipulate online reviews of products to increase their sales. Despite the suspicion on the existence of such manipulation, the amount of such manipulation is unknown, and deciding which reviews to believe in is largely based on the reader's discretion and intuition. Therefore, the success of the manipulation of reviews by firms in generating sales of products is unknown. In this paper, we …
A Fuzzy Logic Multi-Criteria Decision Framework For Selecting It Service Providers, Amir Karami, Zhiling Guo
A Fuzzy Logic Multi-Criteria Decision Framework For Selecting It Service Providers, Amir Karami, Zhiling Guo
Research Collection School Of Computing and Information Systems
Selecting IT service providers in information systems outsourcing involves both qualitative and quantitative evaluations. This paper proposes an integrated multi-criteria decision-making (MCDM) framework to effectively handle uncertainty and subjectivity in the vendor selection process. The proposed methods apply fuzzy logic approach to integrate qualitative survey data into traditional multi-criteria decision models such as data envelope analysis (DEA), analytical hierarchy process (AHP) methods, and TOPSIS. Based on case studies from Iranian banking industry, we empirically test the proposed framework and show it is superior to existing methods. We demonstrate that the fuzzy logic approach provides a robust analysis for vendor selection …
Consumer-Driven Innovation Management, Arcot Desai Narasimhalu, Shekhar Mitra
Consumer-Driven Innovation Management, Arcot Desai Narasimhalu, Shekhar Mitra
Research Collection School Of Computing and Information Systems
The evolution of human society leads to increased affluence and prosperity of certain populations, sometimes at the expense of well-established markets. Market leaders in products and services tend to be so focused on their current customer base that they are caught off guard with the changes in markets created by the evolution. These changes often go unnoticed until it is too late. The change in customer base often requires the repositioning of products and services through innovations, which address new and emerging markets. Some of these changes could potentially result in tectonic market shifts that force innovation managers to involve …
Hybrid Time-Frequency Domain Analysis For Inverter-Fed Induction Motor Fault Detection, T. W. Chua, W. W. Tan, Zhaoxia Wang, C. S. Chang
Hybrid Time-Frequency Domain Analysis For Inverter-Fed Induction Motor Fault Detection, T. W. Chua, W. W. Tan, Zhaoxia Wang, C. S. Chang
Research Collection School Of Computing and Information Systems
The detection of faults in an induction motor is important as a part of preventive maintenance. Stator current is one of the most popular signals used for utility-supplied induction motor fault detection as a current sensor can be installed nonintrusively. In variable speeds operation, the use of an inverter to drive the induction motor introduces noise into the stator current so stator current based fault detection techniques become less reliable. This paper presents a hybrid algorithm, which combines time and frequency domain analysis, for broken rotor bar and bearing fault detection. Cluster information obtained by using Independent Component Analysis (ICA) …
Ontology-Based Business Process Customization For Composite Web Services, Qianhui (Althea) Liang, Xindong Wu, E. K. Park, T. Khoshgoftaar, C. Chi
Ontology-Based Business Process Customization For Composite Web Services, Qianhui (Althea) Liang, Xindong Wu, E. K. Park, T. Khoshgoftaar, C. Chi
Research Collection School Of Computing and Information Systems
A key goal of the Semantic Web is to shift social interaction patterns from a producer-centric paradigm to a consumer-centric one. Treating customers as the most valuable assets and making the business models work better for them are at the core of building successful consumer-centric business models. It follows that customizing business processes constitutes a major concern in the realm of a knowledge-pull-based human semantic Web. This paper conceptualizes the customization of service-based business processes leveraging the existing knowledge of Web services and business processes. We represent this conceptualization as a new Extensible Markup Language (XML) markup language Web Ontology …
Chaos And Uncertainty, M. Thulasidas
Chaos And Uncertainty, M. Thulasidas
Research Collection School Of Computing and Information Systems
The end of 2008 in the finance industry can be summarized in two words – chaos and uncertainty. The subprime crisis, where everybody lost; the dizzying commodity price movements; the pink slip syndrome; the spectacular bank busts; and the gargantuan bail-outs all vouch for it.
How Friendly Is Too Friendly?, M. Thulasidas
How Friendly Is Too Friendly?, M. Thulasidas
Research Collection School Of Computing and Information Systems
Being a boss is tough and being a good boss is a tricky balancing act. One issue many bosses face is: How friendly can they become with their team?