Powerlessness Also Corrupts: Lower Power Increases Self-Promotional Lying

2023 | Organization Science | Citations: 0

Authors: Li, Huisi (Jessica); Chen, Ya-Ru; Hildreth, John Angus D.

Abstract: The popular maxim holds that power corrupts, and research to date supports the v ... Expand

Abstract: The popular maxim holds that power corrupts, and research to date supports the view that power increases self-interested unethical behavior. However, we predict the opposite effect when unethical behavior, specifically lying, helps an individual self-promote: lower rather than higher power increases self-promotional lying. Drawing from compensatory consumption theory, we propose that this effect occurs because lower power people feel less esteemed in their organizations than do higher power people. To compensate for this need to view themselves as esteemed members of their organizations, lower power individuals are more likely to inflate their accomplishments. Evidence from four studies supports our predictions: compared with those with higher power, executives with lower power in their organizations were more likely to lie about their work achievements (Study 1, n = 230); graduate students with lower power in their Ph.D. studies were more likely to lie about their publication records (Study 2, n = 164); and employees with lower power were more likely to lie about having signed a business contract (Studies 3 and 4). Mediation analyses suggest that lower power increased lying because lower power individuals feel lower esteem in their organizations (Study 3, n = 562). Further supporting this mechanism, a self-affirmation intervention reduced the effect of lower power on self-promotional lying (Study 4, n = 536). These converging findings show that, when lies are self-promotional, lower power can be more corruptive than higher power. Collapse

Topics: anonymity consumer behavior missing data electronic mail website

Methods: survey mediation analysis parametric test chi squared test survey design

Theories: self construal theory

Driving risk prevention in usage-based insurance services based on interpretable machine learning and telematics data

2023 | Decision Support Systems | Citations: 0

Authors: Li, Hong-Jie; Luo, Xing-Gang; Zhang, Zhong-Liang; Jiang, Wei; Huang, Shen-Wei

Abstract: Usage-based insurance (UBI) adjusts premiums based on an individual policyholder ... Expand

Abstract: Usage-based insurance (UBI) adjusts premiums based on an individual policyholder’s dynamic risk evaluation, incentivizing policyholders to maintain safe driving behavior in pursuit of a lower insurance premium. Although post-trip interventions can improve driving behavior significantly, most interventions do not provide risk mitigation strategies tailored to long-term driving behavior. This study proposes a novel approach for driving risk prevention in UBI services, providing risk analysis services and tailoring driving suggestions for policyholders. Advanced prediction models and model interpretation methods were adopted to assess and analyze personal driving risks, respectively. A multi-objective counterfactual model was developed to generate risk mitigation strategies for policyholders. The significance of driving behavior in risk mitigation and its actionability were assessed to provide realistic and actionable suggestions for policyholders. The case study, based on a real dataset from an insurance company in China, showed that the proposed approach can be directly embedded in the existing UBI service framework to provide personalized feedback and services to policyholders. Collapse

Topics: shapley additive explanation decision support system Python decision making logistics management

Methods: experiment computational algorithm machine learning XGBoost factor analysis

A novel label-based multimodal topic model for social media analysis

2023 | Decision Support Systems | Citations: 0

Authors: Li, Hao; Qian, Yang; Jiang, Yuanchun; Liu, Yezheng; Zhou, Fan

Abstract: Extracting useful knowledge from multimodal data is the core of many multimedia ... Expand

Abstract: Extracting useful knowledge from multimodal data is the core of many multimedia applications, such as recommendation systems, and cross-modal retrieval. In this paper, we propose a label-based multimodal topic (LB-MMT) model to jointly model text and image data tagged with multiple labels. Specifically, we use the labels as supervised information to generate the text and image data. In the LB-MMT model, we assume that the textual words and visual words related to each text and image are drawn from a mixture of latent topics, where each topic is represented as a group of textual words and visual words. Moreover, we introduce multiple topics for each label, to build the top-down relationship from label to text and image. To investigate the effectiveness of the proposed approach, we conduct extensive experiments on a real-world multimodal dataset with labels. The re­ sults show the proposed approach obtains superior performances on topic coherence and label prediction compared with previous competitors. In addition, we show that our model yields interesting insights about multimodal topics. The proposed model provides important practical implications, e.g., designing more attrac­ tive multimodal contents for marketers. Collapse

Topics: Java social media Linux electronic commerce search engine

Methods: topic model word embedding Gibbs sampling BERT computational algorithm

Theories: technology acceptance model

Meta-Organizational Learning Through Digital Consensus

2023 | International Conference on Information Systems | Citations: 0

Authors: Li, Junyi; Hahn, Jungpil; Tayi, Giri

Abstract: Blockchain technology has enabled the emergence of decentralized autonomous org ... Expand

Abstract: Blockchain technology has enabled the emergence of decentralized autonomous organizations (DAOs) with consensus-based governance. Staking governs DAOs instead of centralized authorities. As a new organizing form, DAOs require careful theoretical consideration. We conceptualize the vehicle of consensusbased governance as digital consensus. Using an agent-based simulation model, this paper aims to extend meta-organization theory to incorporate an organizational learning perspective. We benchmark the DAOs using two well-established organizing forms, namely autonomous and hierarchical organizations. We find that hierarchies outperform DAOs in static environments, whereas DAOs outperform hierarchies in turbulent environments, with autonomies only excelling with intensive experimentation. Our analyses allow us to characterize DAOs as evolving through a staggered process of polarization and homogenization, as opposed to autonomies' continuous polarization and hierarchies' continuous homogenization. Such a staggered process can be affected by several factors (e.g., voting thresholds, token asymmetry, and contributor incentives). Collapse

Topics: organization learning information system use armed conflict unintended consequence organization structure

Methods: experiment theory development simulation sensitivity analysis agent based simulation

Theories: organizational theory organizational learning theory

It Depends On When You Search

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Li, Jun; Liu, Xianwei; Ye, Qiang; Zhao, Feng; Zhao, Xiaofei

Abstract: Existing studies have found that online search is a revealed measure for invest ... Expand

Abstract: Existing studies have found that online search is a revealed measure for investor attention and a useful predictor of stock returns. We study the heterogeneity in retail investor attention by comparing search conducted on weekdays vs. weekends and investigate the price pressure channel and information processing channel for stock return predictability. According to the information processing channel, weekends afford retail investors more time for the intensive cognitive analysis necessary to make better predictions. Alternatively, weekend search might better capture the price pressure from retail investors' trading activities. We provide empirical results that support the information processing channel. We first show that weekend search, rather than weekday search, predicts large-cap stock returns in both the cross-section and time series. Additionally, our findings on retail trading activity contradict the price pressure channel in that weekday search, rather than weekend search, leads to a subsequent retail order imbalance. Overall, our study contributes to the literature on the predictive power of online search on stock returns, which has mainly focused on the price pressure channel, which yields significant results for small-cap stocks only. Collapse

Topics: Google+ database system internet technology search engine electronic finance

Methods: cross sectional research longitudinal research time series analysis autocorrelation analysis descriptive statistic

Order matters: Breaking cognitive lock-in through occasional preferential use of a rival app

2023 | Information & Management | Citations: 0

Authors: Li, Jia; Lu, Ying; Peng, Zeyu; Ma, Ling; Liu, Xuan

Abstract: Although growing attention has been paid to the use of competing technologies, l ... Expand

Abstract: Although growing attention has been paid to the use of competing technologies, little is known about how oc­ casional preferential use of the rival system (OPUR) affects individuals’ adoption of the dominant system. In this study, we investigate how OPUR breaks the cognitive lock-in of the dominant system in the app context. The results demonstrate that supplementing OPUR reduces (increases) user access to the dominant (rival) app. In addition, the OPUR effect is more salient for high-demand and female users. Our results demonstrate that OPUR provides a great opportunity for catching-up apps to offset the first-mover advantage of dominant apps. Collapse

Topics: mobile application information system use marketing management WeChat Tencent QQ

Methods: propensity score matching experimental group propensity score method literature study usage data

Theories: unified theory of acceptance and use of technology

How should companies deploy their digital supply chain platforms to gain competitive advantages? An asset orchestration perspective

2023 | Information & Management | Citations: 0

Authors: Li, Lixu; Xu, Su Xiu; Ning, Yu; Liu, Yaoqi; Yang, Shuili

Abstract: Although many companies have deployed digital supply chain platforms (DSCP), not ... Expand

Abstract: Although many companies have deployed digital supply chain platforms (DSCP), not all obtain the anticipated benefits. This study explores how different deployment strategies of DSCP affect competitive advantages. The empirical results show that DSCP deployment breadth positively relates to exploitative and exploratory in­ novations for both manufacturing companies and service companies. DSCP deployment depth positively affects exploitative and exploratory innovations for manufacturing companies but exploratory innovation for service companies. Although exploitative and exploratory innovations both incur competitive advantages, exploitative innovation is more important for service companies. These findings provide theoretical and practical implica­ tions by unraveling the puzzle of the DSCP-performance association. Collapse

Topics: innovation management competitive advantage supply chain management digital innovation organizational productivity

Methods: survey chi squared test data transformation confirmatory factor analysis SEM tool

The puzzle of experience vs. memory: Peak-end theory and strategic gamification design in M-commerce

2023 | Information & Management | Citations: 0

Authors: Li, Manning; Jiang, Zhenhui (Jack); Ma, Guanghui

Abstract: As businesses increasingly use gamified mobile marketing campaign (GMMC) systems ... Expand

Abstract: As businesses increasingly use gamified mobile marketing campaign (GMMC) systems to engage mobile shop­ pers, gamification in m-commerce systems warrants more attention in both IS research and design practices. Inspired by peak-end theory, this study focused on the puzzling differences between user experience vs. memory and empirically examined the impact of different experience orders of cognitive load on user perceptions and behavioral intentions. Overall, the outcomes of this research suggest that appropriate applications of the peakend effect, moderated via users’ regulatory focus styles, can alleviate the negative mental utility imagery of users, reducing their perceived uncertainties and opt-out intentions from the GMMC. Important implications for research and practice are then discussed. Collapse

Topics: electronic data interchange marketing management user experience gamification systems design

Methods: experiment electroencephalography survey multivariate analysis of variance survey design

Theories: technology acceptance model flow theory self determination theory theory of planned behavior

AI Affordance Actualisation: Empirical Evidence from Mobility Ecosystem Organisations

2023 | International Conference on Information Systems | Citations: 0

Authors: Li, Mingye; Molla, Alemayehu; Duan, Sophia

Abstract: One of the UN Sustainable Development Goals (SDGs) is to transform urban mobil ... Expand

Abstract: One of the UN Sustainable Development Goals (SDGs) is to transform urban mobility to be more accessible, efficient, safe, and sustainable. Artificial Intelligence (AI) can be applied to address some critical urban mobility issues and facilitate the achievement of SDGs. However, there is a need to understand how mobility ecosystem organisations use AI in alignment with their organisational goals to contribute to SDGs. To address this puzzle, this study draws on the affordance theory and preliminary interviews with ten key informants from mobility organisations in Australia. The preliminary findings show that mobility organisations' exploitation of AI systems and technologies leads to the emergence of decarbonising, optimising, conditioning asset management, and provisioning customer-centric services. To do so, they develop AI literacy, business-IT collaboration, change management, and technology and data foundation. The paper contributes a tentative framework linking AI affordances with mobility-related SDGs, serving as a guide for future research and practice. Collapse

Topics: artificial intelligence affordance user experience usability digital ecosystem

Methods: qualitative interview exploratory data analysis deep learning constant comparative analysis qualitative coding

Theories: theory of affordance socio technical theory

Analysis of Security Threats in the Supply Chain of ICT Products Based on Evolutionary Game Theory

2023 | Group Decision and Negotiation | Citations: 0

Authors: Li, Qing; Li, Yan; Yuan, Tianlongyi; Chen, Dawei

Abstract: The network information security regulation of information and communication tec ... Expand

Abstract: The network information security regulation of information and communication technology (ICT) product supply chain is an important issue for governments globally. The whole life cycle of ICT supply chain is a complex process, comprising the design and development stage, outsourcing integration stage and service operation and maintenance stage. Each of these stages may be maliciously attacked, leading to network information security crisis. Therefore, a tripartite evolutionary game model comprising ICT product suppliers, demand customers (such as system integrators, operation and maintenance suppliers and service providers) and government regulatory authorities was constructed from the perspective of security threats and government regulation in the supply chain of ICT products based on bound rationality. The effects of each element on the tripartite strategy selection were evaluated by determining the evolutionary stability of upstream and downstream supply chains. The evolution path was simulated using Matlab2016a software and external variables were included for simulation analysis. The results showed that: (1) the costs of design development and production of high-quality ICT products directly affect the strategy choice of the producers, and determine the stable strategy time of the demanding customers, implying that excessive R&D costs negatively affect healthy development of the supply chain; (2) increase in incentives by the government within a reasonable range promotes the development of products with high security performance and ensures standardization of the implementation standards of information security acceptance of products by customers. However, the increase in incentives leads to a decrease in government supervision; (3) the initial probability of selection of product manufacturers plays an important role in the convergence rate of demand customers. The participating enterprises and government’s operational decision were explored using the tripartite evolutionary game of the ICT product supply chain to formulate recommendations to enhance the construction of information security. Collapse

Topics: data security supply chain management IT security decision making IT investment

Methods: simulation