SLEEP TRACKING AS A STRESSOR: EXPERIENCES FROM SMART RING USERS

2023 | European Conference On Information Systems | Citations: 0

Authors: Feng, Shan; Mäntymäki, Matti; Salmela, Hannu

Abstract: This study explores the stress that users attribute to sleep tracking with a sm ... Expand

Abstract: This study explores the stress that users attribute to sleep tracking with a smart ring. Prior research has discussed the challenges and barriers related to sleep-tracking technologies, but specific research on the stress caused by these technologies is scarce. This study explores the potential stressors that users attribute to sleep tracking executed via a smart ring. We conducted 38 semi-structured interviews and used thematic analysis to identify eight potential stressors from sleep tracking: complexity, invasion, inaccuracy, unreliability, data-perception discrepancy, pursuit of perfect data, vague guidance and interpretations, and overload with multiple self-tracking technologies. We further theorize these potential stressors using the person-technology fit model. The paper contributes to the nascent Information Systems research on technostress in the context of sleep tracking. Collapse

Topics: technostress website smart wearable device smart watch smartphone

Methods: qualitative interview qualitative content analysis theory development personal interview wearables based research

Fair Play for Fair Pay: Fighting Digital Piracy through Revenue Sharing

2023 | International Conference on Information Systems | Citations: 0

Authors: Fereidouni, Meysam; Vijairaghavan, Vaarun

Abstract: ... Expand

Abstract: Collapse

Topics: digital piracy IS economics participatory design consumer surplus producer surplus

Methods: design methodology

Theories: game theory

Causal Matching for Startups: Methods for Controlling Confounding

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Fernandes Marinho Ferreira, Vitor; Kuruzovich, Jason

Abstract: Causal inference is a critical methodology that allows researchers to empirical ... Expand

Abstract: Causal inference is a critical methodology that allows researchers to empirically test hypotheses and build theories. Ideally, the design method for establishing this causality would be through randomized controlled trials. However, studying the impact of different practices (hereinafter treatments) on initial outcomes when treatments are not applied exogenously is a challenge. Matching methods are an appropriate way to provide these study groups. The objective of this work is to provide an algorithmbased solution to match startups in a way that can mimic a human match. To do this, we use the human matching effort by Yu (2020) as a ground truth to evaluate various natural language processes and compare the performance of each with human raters. By comparing automated approaches with matching, we provide guidance for researchers interested in the causal analysis of startups using textual data and other covariates. Collapse

Topics: entrepreneurship business model strategic management

Methods: causality analysis natural language processing computational algorithm term frequency–inverse document frequency GloVe

Cross-cultural and Institutional Perspectives on Information Technology Governance

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Fernandes, Pedro; Pereira, Ruben; Wiedenhoft, Guilherme

Abstract: Nowadays, over 20% of organizations' worldwide capital expenditure goes toward ... Expand

Abstract: Nowadays, over 20% of organizations' worldwide capital expenditure goes toward Information Technology (IT). Hence IT Governance (ITG) is essential to establish a mutually beneficial connection between IT and the business. To deploy ITG, some factors, such as Organizational Culture (OC), should be considered. This study focuses on how the different cultures in the OCAI model affect employees' perception of ITG institutionalization. A survey was conducted on 513 workers from over 150 companies worldwide. Our model was validated using the Kruskal-Wallis H test. Although the results were not as anticipated, the general hypothesis was validated, demonstrating that individuals' perceptions of ITG institutionalization are influenced by their predominant OC type. Market and Hierarchy cultures show higher levels of individual perception of ITG. Organizations will learn how various cultures affect employees' perceptions of ITG, which will help them create a more ITG-oriented culture, greater alignment between business and IT, and more IT-enabled value. Collapse

Topics: organizational culture missing data national culture anonymity

Methods: survey Kruskal Wallis test nonparametric test factor analysis data transformation

Theories: institutional theory

Evolution of Referrals over Customers’ Life Cycle: Evidence from a Ride-Sharing Platform

2023 | Information Systems Research | Citations: 0

Authors: Fernández-Loría, Carlos; Cohen, Maxime C.; Ghose, Anindya

Abstract: Online platforms often ask their users to refer friends in exchange for a reward ... Expand

Abstract: Online platforms often ask their users to refer friends in exchange for a reward. This paper addresses how referral generation and referral value evolve throughout the customer’s life cycle as a function of service usage, experience level, and past referral behavior. Our analysis is based on a longitudinal data set that comprises the transactions and referral actions of 400,000 users in a ride-sharing platform over a year. The richness of our data set allows us to address two shortcomings from previous studies: modeling dynamic behavior (i.e., the relationship between past and future referrals) and accounting for unobserved heterogeneity across users. Our results show that users make more referrals when they have used the service recently and intensively. For example, users become 9% less likely to make referrals for each week they have not used the service. Furthermore, users make more high-value referrals as they become more experienced with the service. The referral generation and referral value of the top 10% most experienced users are more than 18% higher relative to when they first used the service. Finally, as users make more referrals, they become more likely to run out of friends to whom they can refer the service, leading to less referrals in the future. After users make their first referral, the probability of making additional referrals decreases by more than 78% and the value of subsequent referrals reduces by 19% on average. The results imply that platforms should consider tailoring their referral programs according to how referral generation and referral value evolve over time.History: Xiaoquan (Michael) Zhang, Senior Editor; Khim Yong Goh, Associate Editor. Collapse

Topics: ride sharing platform mobile application logistics management accounting marketing management

Methods: longitudinal research robustness check instrumental variables estimation regression analysis method Poisson regression

Theories: social contagion theory

A Comparison of Methods for Treatment Assignment with an Application to Playlist Generation

2023 | Information Systems Research | Citations: 0

Authors: Fernández-Loría, Carlos; Provost, Foster; Anderton, Jesse; Carterette, Benjamin; Chandar, Praveen

Abstract: This study presents a systematic comparison of methods for individual treatment ... Expand

Abstract: This study presents a systematic comparison of methods for individual treatment assignment, a general problem that arises in many applications and that has received significant attention from economists, computer scientists, and social scientists. We group the various methods proposed in the literature into three general classes of algorithms (or metalearners): learning models to predict outcomes (the O-learner), learning models to predict causal effects (the E-learner), and learning models to predict optimal treatment assignments (the A-learner). We compare the metalearners in terms of (1) their level of generality and (2) the objective function they use to learn models from data; we then discuss the implications that these characteristics have for modeling and decision making. Notably, we demonstrate analytically and empirically that optimizing for the prediction of outcomes or causal effects is not the same as optimizing for treatment assignments, suggesting that, in general, the A-learner should lead to better treatment assignments than the other metalearners. We demonstrate the practical implications of our findings in the context of choosing, for each user, the best algorithm for playlist generation in order to optimize engagement. This is the first comparison of the three different metalearners on a real-world application at scale (based on more than half a billion individual treatment assignments). In addition to supporting our analytical findings, the results show how large A/B tests can provide substantial value for learning treatment-assignment policies, rather than simply for choosing the variant that performs best on average.History: Olivia Liu Sheng, Senior Editor; Gautam Pant, Associate Editor.Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1149. Collapse

Topics: decision making digital service music streaming service Spotify marketing management

Methods: meta learning computational algorithm machine learning experiment decision tree classification

Disruption and Legitimacy: Big Data in Society

2023 | Information Systems Frontiers | Citations: 1

Authors: Ferreira, Carlos; Merendino, Alessandro; Meadows, Maureen

Abstract: The growing availability of data and the emergence of business analytics ecosyst ... Expand

Abstract: The growing availability of data and the emergence of business analytics ecosystems offer possibilities for companies developing innovative business models. However, the disruptive impact of these business models on society is not always judged favourably. This paper explores the growing tensions in the relationship between disruptive Big Data companies and society through the lens of legitimacy – a judgement about the fit and propriety of an entity, such as a company, to society. The study is based on four instrumental cases where Big Data organisations were faced with challenges to their legitimacy. The findings elaborate how digital transformations require companies to understand and manage how much to disrupt and how much to conform to social norms and values. Big Data businesses face a dynamic and paradoxical tension between the potential costs and benefits of their disruptive business models. The topic of legitimacy management is also addressed, drawing out implications for practice. Collapse

Topics: big data business model Airbnb Facebook disruptive innovation

Methods: case study literature sample qualitative content analysis archival research triangulation

The Big Five Under Pressure in E-Commerce: Exploring the Role of Coping Strategy and Technostress

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Feste, Jasmin Maria; Baumann, Carolin; Peters, Leonore

Abstract: Although e-commerce has taken over consumers' lives, the effects of technostres ... Expand

Abstract: Although e-commerce has taken over consumers' lives, the effects of technostress on the purchasing intention depending on personality dimensions still lacks coverage in the scientific field. We build on previous literature by focusing on the effect of the Big Five inventory under consideration of technostress and coping strategy on purchasing intention. The aim is to extend the current state of research by analyzing the effects of all Big Five dimensions on purchase intention, mediated by coping strategies and moderated by technostress. Our findings, based on an online survey with 479 participants, show that three personality dimensions have an effect on the chosen coping strategy moderated by technostress. Further, a proactive coping strategy has a positive effect on the purchasing intention of consumers while a reactive coping strategy affects purchase intention negatively. Thereby, we contribute to technostress and consumer psychology research and provide insights for managerial practice (i.e. retailers). Collapse

Topics: technostress personality electronic commerce

Methods: experiment experimental design mediation analysis data transformation confirmatory factor analysis

Theories: big five model

Fighting Fire with Fire: Use of Technology and Emerging Technostress during the Covid-19 Pandemic in an Academic Context

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Feste, Jasmin Maria; Peters, Leonore; Henkel, Dominik

Abstract: In response to the Covid-19 pandemic, German government introduced a "stay-at-h ... Expand

Abstract: In response to the Covid-19 pandemic, German government introduced a "stay-at-home" policy to slow the spread of the virus. This, in turn, resulted in universities introducing online teaching, which thereby fostered technology-related stress perception for students. Based on social presence theory and current technostress research, we analyze the effects of loneliness on perceptions of technostress in online teaching and the moderating effect of social network services. Using a sample size of 327, our findings show that loneliness has a negative impact on technostress perception and that the use of social network services diminishes technostress perception even more. These findings are an important contribution to current technostress research, as the effects of digital technologies can no longer be considered in isolation, but should rather be understood as the interplay of different digital communication tools from various perspectives and contextual settings. Collapse

Topics: technostress pandemic online learning system information system use social presence

Methods: survey mediation analysis business process modeling regression analysis method cross sectional research

Theories: social presence theory

Do Social Media Marketing Activities Improve Brand Loyalty? An Empirical Study on Luxury Fashion Brands

2023 | Information Systems Frontiers | Citations: 0

Authors: Fetais, Abdulla H.; Algharabat, Raed S.; Aljafari, Abdullah; Rana, Nripendra P.

Abstract: This research aims to investigate the impact of social media marketing activitie ... Expand

Abstract: This research aims to investigate the impact of social media marketing activities (SMMa) on brand loyalty directly and through mediating variables community engagement and lovemark. To propose a research model, we used the theories including lovemark theory, engagement theory and brand equity theory. As a result, this research investigates the impact of SMMa, community engagement, and lovemark on brand loyalty. Using an online survey, we collected data from 464 female participants who are following luxury fashion brands on major social networking sites including Facebook, Instagram, Snapchat, and Twitter. Results using PLS revealed that SMMa positively influences community engagement and lovemark. Moreover, we find positive relationships between community engagement, lovemark and brand loyalty. However, we find that SMMa has no direct influence on brand loyalty. Collapse

Topics: customer loyalty social media word of mouth online word of mouth marketing management

Methods: survey partial least squares regression partial least squares path modeling statistical hypothesis test data transformation

Theories: equity theory job engagement theory service-dominant logic theory of logic