Thinking Fast and Thinking Slow: Digital Devices' Effects on Cognitive Reflection

2023 | Journal of Management Information Systems | Citations: 0

Authors: Figl, Kathrin; Remus, Ulrich

Abstract: Informed by theoretical perspectives on working memory demands and devices' pote ... Expand

Abstract: Informed by theoretical perspectives on working memory demands and devices' potential to "prime" different types of cognitive processing, this paper investigates whether we tend to think "faster" and more intuitively, with less reflection when we use a smartphone instead of a personal computer (PC) or notebook. Three complementary experimental studies with a total of 823 participants reveal that the results of using such devices surface only when participants can select the smartphone as their preferred device. Controlling for potential confounding variables reveals no evidence of general differences between devices. Our findings caution against overemphasizing the importance of the type of device in thinking slow or fast and establish self-selection bias as an important factor in explaining such differences. This study contributes to clarifying the psychology of smartphone screens and how humans make choices when they are using these devices. Collapse

Topics: smartphone electronic mail social media decision making laptop computer

Methods: survey within subject experiment longitudinal research experiment hierarchical linear modeling

Theories: dual-system theory cognitive theory

DIGITAL NUDGING TO PROMOTE SUSTAINABLE CONSUMER BEHAVIOR? AN EXPERIMENTAL ANALYSIS IN ONLINE FASHION RETAIL

2023 | European Conference On Information Systems | Citations: 0

Authors: Schürmann, Christina; Helinski, Cindy; Koch, Julia; Westmattelmann, Daniel; Schewe, Gerhard

Abstract: Online fashion retail is gaining importance and faces challenges in addressing ... Expand

Abstract: Online fashion retail is gaining importance and faces challenges in addressing its environmental impact. Targeting sustainable product choices presents an opportunity to contribute to the sustainable development of online retail. This can be accomplished through digital nudging, a technique influencing consumer behavior. Based on nudging theory, an online experiment is conducted employing simplification and social norm nudges to examine their impact on sustainable product choice in online retail. A dataset of 461 participants is analyzed using contingency analysis and logistic regression. The results reveal that the simplification nudge increases sustainable product choice. Contrarily, the social norm nudge positively affects the non-nudged sustainable product choice. Further, the simplification nudge negatively affects subsequent sustainable behavior, while the social norm nudge shows insignificant effects, indicating negative spillover effects of the simplification nudge. Finally, theoretical implications and recommendations for introducing digital nudging tools to promote sustainable choices in online retail are derived. Collapse

Topics: social norm consumer behavior logistics management decision making intrinsic motivation

Methods: regression analysis method experiment logistic regression experimental group survey

Theories: consumer behaviour theory

Factors Affecting Customer Analytics: Evidence from Three Retail Cases

2022 | Information Systems Frontiers | Citations: 0

Authors: Griva, Anastasia; Bardaki, Cleopatra; Pramatari, Katerina; Doukidis, Georgios

Abstract: The abundance of customer behavioral data alters the design and application of c ... Expand

Abstract: The abundance of customer behavioral data alters the design and application of customer analytics systems and approaches. Segmentation is a common customer analytics practice, but researchers highlight that traditional segmentation approaches are not enough. We coin the term “visit segmentation” and devise a visit segmentation approach. When designing or applying a new information system or approach, it is important to consider factors related to the input data, the application context, the users, and all the relevant requirements. Considering the literature, this paper identifies such factors that affect customer analytics approaches and systems. We explore how these factors affect segmentation through applying our segmentation approach to three heterogeneous retailers, e.g., the products’ variety a shopper purchases in each visit seems to be crucial to the segmentation. The more attention data analysts and designers pay to these factors, the more reliable segmentation results they will get and, thus, improved retail decisions are expected. Collapse

Topics: electronic commerce marketing management analytical information system decision making structured query language

Methods: cluster analysis design science descriptive statistic computational algorithm k-means clustering

Space Norms for Constructing Quality Reviews on Online Consumer Review Sites

2022 | Information Systems Research | Citations: 0

Authors: Hou, Jinghui (Jove); Ma, Xiao

Abstract: High-quality online consumer reviews are valuable to e-commerce stakeholders. Ex ... Expand

Abstract: High-quality online consumer reviews are valuable to e-commerce stakeholders. Extant research mainly focuses on what drives consumers to submit reviews, whereas little has been done to specifically theorize why review writers construct high-quality reviews versus post poor review content. To advance current theorizing on the behavior of writing quality reviews, we propose the concept of space norms, a distinct instantiation of social norms inferred from locally observing how others write reviews on the local digital space (i.e., the review site). Specifically, we theorize that the focal behavior is largely directed by space norms; space norms beget a sense of how one should do and induce conformity in the given social space. We tested the theory of space norms in a series of empirical studies, and the findings provide converging evidence. Study 1 used experimental methods and demonstrates—with large effect sizes—that review writers tend to act in accordance with the space norm of the local site. Post hoc text analyses rule out an alternative explanation and corroborate the findings. Study 2 used field data collected from two e-commerce websites to further triangulate the space norms proposition. Another post hoc study confirms the robustness of the results. This paper contributes to information systems research by developing and empirically validating a theory of space norms that pinpoints the role of local digital spaces in constructing the focal normative phenomenon. It also lends insights to digital platforms and the information technology practitioners. Managers looking to elicit quality reviewing behavior should devise the local digital space to nurture the space norms for the desired behavior. Collapse

Topics: social presence online review social norm website electronic commerce

Methods: theory development natural language processing computational algorithm statistical hypothesis test design artifact

Visual Communication and Fashion Popularity Contagion in Social Networks

2022 | International Conference on Information Systems | Citations: 0

Authors: Li, Xiang; Wang, Yunhui; Junming, Liu; Xiong, Hui

Abstract: Fast fashion has emerged as a prevalent retail strategy shaping fashion popular ... Expand

Abstract: Fast fashion has emerged as a prevalent retail strategy shaping fashion popularity. However, due to the lack of historical records and the dynamics of fashion trends, existing demand prediction methods do not apply to new-season fast fashion sales forecasting. We draw on the Social Contagion Theory to conceptualize a sales prediction framework for fast fashion new releases. We posit that fashion popularity contagion comes from Source Contagion and Media Contagion, which refer to the inherent infectiousness of fashion posts and the popularity diffusion in social networks, respectively. We consider fashion posts as the contagion source that visually attracts social media users with images of fashion products. Graph Convolutional Network is developed to model the dynamic fashion contagion process in the topology structure of social networks. This theory-based deep learning method can incorporate the latest social media activities to offset the deficiency of historical fashion data in new seasons. Collapse

Topics: social media social network electronic commerce

Methods: convolutional neural network image processing theory development deep learning longitudinal research

Theories: social contagion theory

Gamified Live-streaming: Is Avatar Better than Human Being?

2022 | International Conference on Information Systems | Citations: 0

Authors: Liu, Yahui; Wang, Lei; Yang, Shuai; Wang, Yanwen

Abstract: Live-streaming has emerged as a popular direct selling channel to foster synchr ... Expand

Abstract: Live-streaming has emerged as a popular direct selling channel to foster synchronous interaction between streamers and consumers, with the avatar streamer largely underexplored. Using the data from a fashion retailer, we adopt the Generalized Synthetic Control (GSC) method to examine the effect of gamified and human livestreaming on product sales and return rate. We find that (1) the gamified live-streaming reduces product sales and the return rate simultaneously; (2) human live-streaming boosts product sales but increases the return rate, and (3) the dual-type live-streaming can increase product sales and decrease return rates. Furthermore, we proposed that the reason for the differentiated effects between gamified and human live-streaming could be driven by the impulse-buying behavior of viewers only in human live-streaming. Our findings contribute to the growing literature on the business value of AI technology and gamification in live-streaming and shed light on practical decisions made by online retailers. Collapse

Topics: electronic commerce live streaming platform video streaming service artificial intelligence gamification

Methods: synthetic control method robustness check experimental group qualitative content analysis convolutional neural network

Retargeting Ads for Shopping Cart Recovery: Online Field Experiments

2022 | International Conference on Information Systems | Citations: 0

Authors: Moriguchi, Takeshi; Xiong, Guiyang; Luo, Xueming

Abstract: Retargeting ads (RA) aim to convert customers who previously browsed the websit ... Expand

Abstract: Retargeting ads (RA) aim to convert customers who previously browsed the websites or abandoned shopping-carts. We exploit several randomized field experiments to test how the effects of RA vary depending on ad-copy content and purchase-funnel stages. Results suggest that compared to hold-out without retargeting, RA in lower funnel based on shopping-cart abandonment history significantly enhances purchase responses. The effects are driven by ad content that highlights product return information rather than product reminder or shipping information. Due to lack of touch/feel/trial of online orders, such ad-copy can nudge customers to try the products by reducing shopping risks and, thus, increase purchase rates. Net revenue for RAs with product return information is 49.7% larger than conventional RAs with product information. Also, lower funnel retargeting is 2.25 times as effective as upper funnel retargeting in lifting purchase rates. These findings indicate how to design RAs to recover abandoned carts and boost sales. Collapse

Topics: electronic commerce website online advertising electronic mail marketing management

Methods: experiment longitudinal research field experiment randomized field experiment ANOVA

Guest Editorial: A special section on digital marketing

2021 | International Journal of Information Management | Citations: 0

Authors: Kizgin, Hatice; Gutierrez, Anabel; Desai, Bhavini; Vazquez, Delia; Rana, Nripendra

Abstract: ... Expand

Abstract: Collapse

Topics: marketing management Google+ artificial intelligence consumer behavior website

Methods: oculometry experiment digital trace data theoretical contribution case study

Theories: semiotic theory

Consent Notices and the Willingness-to-Sell Observational Data: Evidence from User Reactions in the Field

2021 | European Conference On Information Systems | Citations: 0

Authors: Mager, Stefan; Kranz, Johann

Abstract: Privacy regulations like the EU's General Data Protection Regulation (GDPR) req ... Expand

Abstract: Privacy regulations like the EU's General Data Protection Regulation (GDPR) require e-commerce shops to request opt-in consent for usage data collection from EU website visitors. Despite the regulation's intentional strengthening of consumer rights, consent notices are often regarded as burdensome by consumers and shops alike. Thus, ever more consumers turn to consent-automating browser extension tools, which decreases opt-in rates for e-commerce shops. To investigate potential for a win-win solution, we examined in cooperation with a fashion retailer in Germany how consumers react when they are presented a coupon for the website's shop in the moment of cookie consent decision. Using the Becker-DeGroot-Marschak mechanism, we elicited consumers' willingnesses-to-sell (WTS) for cookie consent. Our unique field dataset of 1274 participants allows us to derive the WTS of consumers for any desired consent rate. For instance, 65.05% of consumers are ready to trade their consent to cookies for a 10€-coupon value. Collapse

Topics: website privacy electronic commerce internet technology information privacy law

Methods: quantitative observational study field experiment experimental group digital trace data experiment

Theories: behavioral economics

Forecasting and Anomaly Detection approaches using LSTM and LSTM Autoencoder techniques with the applications in supply chain management

2021 | International Journal of Information Management | Citations: 2

Authors: Nguyen, H.D.; Tran, K.P.; Thomassey, S.; Hamad, M.

Abstract: Making appropriate decisions is indeed a key factor to help companies facing cha ... Expand

Abstract: Making appropriate decisions is indeed a key factor to help companies facing challenges from supply chains nowadays. In this paper, we propose two data-driven approaches that allow making better decisions in supply chain management. In particular, we suggest a Long Short Term Memory (LSTM) network-based method for forecasting multivariate time series data and an LSTM Autoencoder network-based method combined with a oneclass support vector machine algorithm for detecting anomalies in sales. Unlike other approaches, we recom­ mend combining external and internal company data sources for the purpose of enhancing the performance of forecasting algorithms using multivariate LSTM with the optimal hyperparameters. In addition, we also propose a method to optimize hyperparameters for hybrid algorithms for detecting anomalies in time series data. The proposed approaches will be applied to both benchmarking datasets and real data in fashion retail. The obtained results show that the LSTM Autoencoder based method leads to better performance for anomaly detection compared to the LSTM based method suggested in a previous study. The proposed forecasting method for multivariate time series data also performs better than some other methods based on a dataset provided by NASA. Collapse

Topics: supply chain management IT security threat artificial intelligence

Methods: data transformation autoencoder longitudinal research time series analysis computational algorithm