Facilitating interorganizational trust in strategic alliances by leveraging blockchain-based systems: Case studies of two eastern banks

2023 | International Journal of Information Management | Citations: 0

Authors: Chen, Renee Rui; Chen, Kun; Ou, Carol X.J.

Abstract: Strategic alliances require mutual trust and collaboration between organizations ... Expand

Abstract: Strategic alliances require mutual trust and collaboration between organizations. To increase alliance perfor­ mance, organizations in a strategic alliance are more likely to interpret each other’s equivocal behaviors in a positive way to sustain the stability of the relationship. Different from traditional mechanisms to build inter­ organizational trust, blockchain facilitates trust among alliance partners via its technology advantages, for example, public ledger and distributed consensus. The decentralized and distributed nature of a blockchainbased system assures that no single organization can add information to the chain without an approval from the alliance, nor can it make unilateral changes in the system. Drawing from the Affordance Theory, we propose an exploratory research design to understand the structure of a blockchain-based system, as well as how this blockchain-based system influences interorganizational trust in a strategic alliance and how blockchain-enabled interorganizational trust influences alliance performance. The case studies of two eastern banks indicate that the technical features of blockchain can help reduce equivocal behaviors and improve interorganizational trust. We discuss the findings and conclude the paper with implications. Collapse

Topics: blockchain affordance user experience usability smart contract

Methods: qualitative interview case study design artifact conceptual modelling computational algorithm

Theories: theory of affordance

The Core Industry Manufacturing Process of Electronics Assembly Based on Smart Manufacturing

2023 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Chen, Rongli; Chen, Xiaozhong; Wang, Lei; Li, Jianxin

Abstract: This research takes a case study approach to show the development of a diverse a ... Expand

Abstract: This research takes a case study approach to show the development of a diverse adoption and product strategy distinct from the core manufacturing industry process. It explains the development status in all aspects of smart manufacturing, via the example of ceramic circuit board manufacturing and electronic assembly, and outlines future smart manufacturing plans and processes. The research proposed two experiments using artificial intelligence and deep learning to demonstrate the problems and solutions regarding methods in manufacturing and factory facilities, respectively. In the first experiment, a Bayesian network inference is used to find the cause of the problem of metal residues between electronic circuits through key process and quality correlations. In the second experiment, a convolutional neural network is used to identify false defects that were overinspected during automatic optical inspection. This improves the manufacturing process by enhancing the yield rate and reducing cost. The contributions of the study built in circuit board production. Smart manufacturing, with the application of a Bayesian network to an Internet of Things setup, has addressed the problem of residue and redundant conductors on the edge of the ceramic circuit board pattern, and has improved and prevented leakage and high-frequency interference. The convolutional neural network and deep learning were used to improve the accuracy of the automatic optical inspection system, reduce the current manual review ratio, save labor costs, and provide defect classification as a reference for preprocess improvement. Collapse

Topics: artificial intelligence smart manufacturing production management Python internet of things

Methods: experiment deep learning case study convolutional neural network Bayesian network

The Relationship Between Twitter Sentiment and Stock Performance: A Decision Tree Approach

2023 | HICSS | Citations: 0

Authors: Chen, Rongjuan; Dong, Ruoxi

Abstract: Social media has become a communication tool, but also a valuable database for r ... Expand

Abstract: Social media has become a communication tool, but also a valuable database for researchers and practitioners to gather information, share knowledge, as well as express opinions about stock performance. The sentiment embedded in social media content can be analyzed to predict stock performance. Although numerous past studies have attempted to predict stock price movement using social media sentiment, some emerging analytical tools, like existing lexicons, may require further testing and validation in a financial decision making context. In this study, we develop and test predictive models for stock price and trend forecasting. By using a large-scale sample of tweets collected from Twitter, related to four companies, Apple, Google, Microsoft, and Netflix, we propose a novel decision tree approach to stock performance prediction. Based on our findings, we then provide theoretical and practical implications and discuss the directions for future work. Collapse

Topics: Twitter social media decision making digital service Netflix

Methods: sentiment analysis decision tree classification regression analysis method multiple linear regression NLP tool

Theories: behavioral economics

Understanding Emojis for Financial Sentiment Analysis

2023 | International Conference on Information Systems | Citations: 0

Authors: Chen, Siyi; Xing, Frank

Abstract: ... Expand

Abstract: Collapse

Topics: application programming interface social media website cryptocurrency Python

Methods: sentiment analysis machine learning BERT deep learning experiment

A Review and Meta-analysis of Mobile Government Adoption

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Chen, Ting; Sun, Ting; Duan, Yaoqing; Ahmad, Farhan

Abstract: With the explosive growth of mobile phone users, individuals are getting used t ... Expand

Abstract: With the explosive growth of mobile phone users, individuals are getting used to using mobile phones to get various services. Mobile government, as one of important channels to provide official government services, has been paid increasingly attention recently. In order to discover the critical influence factors of individual attitude and behavioral intention, a meta-analysis method was used to construct a comprehensive framework for individual mobile government adoption and find out the moderating role of economic development level, based on 38 related empirical research publications. We would like to figure out the results from meta-analysis and moderator analysis. Both theoretical and practical implications are going to yield through these findings. Collapse

Topics: behavioral intention user acceptance social influence service quality technology adoption

Methods: meta analysis correlation analysis survival analysis descriptive statistic literature sample

Theories: theory of economic development technology acceptance model unified theory of acceptance and use of technology technology acceptance theory extended unified theory of acceptance and use of technology

The bright side of emotional extremity: Evidence from tipping in live streaming platform

2023 | Information & Management | Citations: 0

Authors: Chen, Xingyu; Ji, Li; Jiang, Ling; Huang, Justin T.

Abstract: Live streaming has enabled viewers to interact with broadcasters and peer viewer ... Expand

Abstract: Live streaming has enabled viewers to interact with broadcasters and peer viewers, as well as tip the broadcaster based on their emotional state. While most tips are small, a minority of viewers tip extremely large. To uncover such unique tipping patterns, we draw on the emotion literature and competitive arousal theory to examine how viewers’ emotional extremity affects tipping behavior and how broadcaster’s emotional response moderates the baseline effect. This study contributes to the emerging live streaming literature by revealing the differential effects of emotional extremity on tipping amount and frequency and provides practical implications for broad­ casters and platforms to steer tipping behavior. Collapse

Topics: live streaming platform marketing management accounting digital platform artificial intelligence

Methods: statistical hypothesis test computational algorithm psychometrics machine learning longitudinal research

The Opportunity in Difficulty: A Dynamic Privacy Budget Allocation Mechanism for Privacy-Preserving Multi-dimensional Data Collection

2023 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Chen, Xue; Wang, Cheng; Yang, Qing; Hu, Teng; Jiang, Changjun

Abstract: Data collection under local differential privacy (LDP) has been gradually on the ... Expand

Abstract: Data collection under local differential privacy (LDP) has been gradually on the stage. Compared with the implementation of LDP on the single attribute data collection, that on multi-dimensional data faces great challenges as follows: (1) Communication cost. Multivariate data collection needs to retain the correlations between attributes, which means that more complex privatization mechanisms will result in more communication costs. (2) Noise scale. More attributes have to share the privacy budget limited by data utility and privacy-preserving level, which means that less privacy budget can be allocated to each of them, resulting in more noise added to the data. In this work, we innovatively reverse the complex multi-dimensional attributes, i.e., the major negative factor that leads to the above difficulties, to act as a beneficial factor to improve the efficiency of privacy budget allocation, so as to realize a multi-dimensional data collection under LDP with high comprehensive performance. Specifically, we first present a Multivariate k-ary Randomized Response (kRR) mechanism, called Multi-kRR. It applies the RR directly to each attribute to reduce the communication cost. To deal with the impact of a large amount of noise, we propose a Markov-based dynamic privacy budget allocation mechanism Markov-kRR, which determines the present privacy budget (flipping probability) of an attribute related to the state of the previous attributes. Then, we fix the threshold of flipping times in Markov-kRR and propose an improved mechanism called MarkFixed-kRR, which can obtain more optimized utility by choosing the suitable threshold. Finally, extensive experiments demonstrate the efficiency and effectiveness of our proposed methods. Collapse

Topics: privacy marketing management differential privacy data quality local differential privacy

Methods: computational algorithm experiment lasso regression archival research survey

Trust and deception with high stakes: Evidence from the friend or foe dataset

2023 | Decision Support Systems | Citations: 0

Authors: Chen, Xunyu; Wang, Xinran; Spitzley, Lee; Nunamaker, Jay

Abstract: Many social interactions rely on the premise of mutual trust, but deception viol ... Expand

Abstract: Many social interactions rely on the premise of mutual trust, but deception violates trust and poses risk. Empirically examining trust and deception, particularly in high-stakes situations, is challenging but essential for improving the research realism and generalizability. To address this difficulty, we study trusting and deceptive behaviors in a high-stakes situation by using a novel dataset created from an American game show, Friend or Foe (FoF). In the show, a contestant's reward was determined through a trust game modified from the prisoner's dilemma. We explore how numerous human behaviors including facial expressions, gaze, head pose, body motion, language, and socio-demographic attributes, were related to a contestant's trusting or deceptive decision. Using a data-driven approach, we find that the deceivers' (contestants who chose Foe) behavior featured a neutralized face, negative facial emotions, enhanced upper body motion, and language with a lower sense of immediacy and agreeableness. The contestants who chose to trust (chose Friend) exhibited opposite behavioral patterns. Socio-demographic factors such as age, height, and facial attractiveness were also associated with a contestant's choice. Combining multimodal information, machine learning classifiers could predict the contes­ tant's choice with an accuracy about 25% greater than earlier reported human accuracy. We contribute to both trust and deception literature by examining the generalizability of trusting and deceptive behaviors to a new high-stakes scenario. We also add to the decision support literature by showing the superior predictive perfor­ mances of combining behavioral and socio-demographic features. Furthermore, we contribute to the academic community by introducing the FoF dataset. Collapse

Topics: decision support website YouTube Python decision making

Methods: meta analysis support vector machine correlation analysis descriptive statistic random forest classification

Prototyping AI-Powered Social Innovation in an Undergraduate MIS course

2023 | International Conference on Information Systems | Citations: 0

Authors: Chen, Yu; Albert, Leslie; Macias, Heather

Abstract: While implementing with caution, Artificial Intelligence (AI) holds potential t ... Expand

Abstract: While implementing with caution, Artificial Intelligence (AI) holds potential to help nations address pressing social issues, such as homelessness, climate change, and healthcare accessibility. With the existing and potential economic and social benefits of AI, it is crucial to integrate AI learning in undergraduate education. This paper presents the preliminary findings of a course project that engages students to learn AI by prototyping solutions to address important social issues in their communities among 120 undergraduate MIS students. Students worked in groups and developed chatbots that addressed a variety of community issues during . A survey study shows students' enhanced understanding and mastery of AI concepts and applications, empowerment of contributing to their communities through AI innovation, and an emerging awareness of diversity, equity, and ethical issues in the community and AI technologies. We conclude with implications of learning AI, innovation, and ethics through the lens of AI for social good. Collapse

Topics: artificial intelligence design thinking societal evaluation criteria innovation management responsible artificial intelligence

Methods: design methodology survey chatbot personal interview design artifact

How Does (In)consistent Performance Feedback Affect Business Model Digitalization？

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Chen, Yao; Chen, Meng; Liu, Hefu; Tang, Xinlin

Abstract: Despite the merits of business model (BM) digitalization to sustain organizatio ... Expand

Abstract: Despite the merits of business model (BM) digitalization to sustain organizational competitive advantages, many firms are cautious to digitalize their BMs due to the efforts needed and the high risks accompanying them. To date, the existing understanding of the antecedents of BM digitalization is still underdeveloped. We draw on the behavioral theory of the firm to develop a comprehensive understanding of what motivates firms to promote BM digitalization. In so doing, this study explores how (in)consistency between historical and social performance feedback affects BM digitalization. Moreover, we theorize that board experience with BM digitalization from interlock firms is an important contingency that influences these relationships. Based on panel data from 2,373 Chinese-listed firms from 2008 to 2019, the results provide general support for our arguments. This study contributes to the BM digitalization literature by disentangling the critical roles of (in)consistent performance feedback and board experience. Collapse

Topics: organizational productivity research and development corporate governance accounting accounting standard

Methods: theory development machine learning descriptive statistic statistical hypothesis test word2vec

Theories: behavioral theory of the firm