A Modular Social Sensing System for Personalized Orienteering in the COVID-19 Era

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

Authors: Pilato, Giovanni; Persia, Fabio; Ge, Mouzhi; Chondrogiannis, Theodoros; D’Auria, Daniela

Abstract: Orienteering or itinerary planning algorithms in tourism are used to optimize tr ... Expand

Abstract: Orienteering or itinerary planning algorithms in tourism are used to optimize travel routes by considering user preference and other constraints, such as time budget or traffic conditions. For these algorithms, it is essential to explore the user preference to predict potential points of interest (POIs) or tourist routes. However, nowadays, user preference has been significantly affected by COVID-19, since health concern plays a key tradeoff role. For example, people may try to avoid crowdedness, even if there is a strong desire for social interaction. Thus, the orienteering or itinerary planning algorithms should optimize routes beyond user preference. Therefore, this article proposes a social sensing system that considers the tradeoff between user preference and various factors, such as crowdedness, personality, knowledge of COVID-19, POI features, and desire for socialization. The experiments are conducted on profiling user interests with a properly trained fastText neural network and a set of specialized Naïve Bayesian Classifiers based on the “Yelp!” dataset. Also, we demonstrate how to approach and integrate COVID-related factors via conversational agents. Furthermore, the proposed system is in a modular design and evaluated in a user study; thus, it can be efficiently adapted to different algorithms for COVID-19-aware itinerary planning. Collapse

Topics: user satisfaction social network personality conversational agent Twitter

Methods: computational algorithm fastText machine learning experiment descriptive statistic

CSR Communication on Twitter -A Scoping Review on Social Media Mining and Analytic Methods

2023 | HICSS | Citations: 0

Authors: Pilgrim, K.; Koss, J.; Bohnet-Joschko, S.

Abstract: Adopting corporate social responsibility (CSR) is becoming increasingly mandato ... Expand

Abstract: Adopting corporate social responsibility (CSR) is becoming increasingly mandatory as international legislation puts pressure on companies to implement and report on appropriate CSR measures. As of 2024, a significant number of companies will need to report on CSR topics for the first time. To identify relevant topics that resonate best in the industry or even with one's own stakeholder groups and should therefore be picked up, addressed and reported on preferentially, social media mining (SMM) can be an efficient approach for companies. By reviewing applied SMM and analytic methods of Twitter data, we identified four methodological approaches that use algorithms to identify relevant CSR topics for companies to engage with. This scoping review thus provides a systematized overview of SMM pipelines for use, being equally relevant for academics and practitioners aiming at computational analysis of Twitter content regarding CSR activities and communication. Research aim and questionAs scoping reviews have become an increasingly popular approach for synthesizing research evidence by mapping the existing literature in the field of interest in terms of the volume, nature, and characteristics of the primary research (Pham et al., 2014), we aim to identify existing SMM and analytic approaches for research on CSR on Twitter employing a scoping (methods) review. Collapse

Topics: Twitter application programming interface database system social media open access

Methods: structured literature research computational algorithm machine learning network analysis topic model

Improving scale adaptation practices in information systems research: Development and validation of a cognitive validity assessment method

2023 | Information Systems Journal | Citations: 1

Authors: Pillet, Jean-Charles; Carillo, Kevin D.; Vitari, Claudio; Pigni, Federico

Abstract: Scale adaptation, where authors alter the wording of an already published scale, ... Expand

Abstract: Scale adaptation, where authors alter the wording of an already published scale, is a deeply rooted social practice in IS research. This paper argues that the time is ripe to question this activity as well as the beliefs that have progressively formed around it. We identify and challenge five fallacious scale adaptation beliefs that hinder the development of more robust measure development norms. Contributing to this area of research, this paper offers a conceptual definition of the cognitive validity concept, defined as the extent to which a scale is free of problematic item characteristics (PICs) that bias the survey response process and subsequent empirical results. Building on this conceptualization effort, a new methodological process for assessing the cognitive validity of adapted IS measures is introduced. Through a series of three programmatic studies, we find converging evidence that the method can benefit the IS field by making the scale adaptation process more robust, transparent, and consistent. Along with the method, we introduce a new index that IS scholars can use to benchmark the cognitive quality of their scales against venerable IS measures. We discuss the implications of our work for IS research (including detailed implementation guidelines) and provide directions for future research on measurement in IS. Collapse

Topics: crowdsourcing privacy website evaluation criteria decision making

Methods: survey F-test parametric test literature study statistical hypothesis test

AI Literacy -Towards Measuring Human Competency in Artificial Intelligence

2023 | HICSS | Citations: 0

Authors: Pinski, M.; Benlian, A.

Abstract: Artificial intelligence (AI) has gained significant traction in information sys ... Expand

Abstract: Artificial intelligence (AI) has gained significant traction in information systems (IS) research in recent years. While past studies have identified many effects of AI technology on human-AI collaborations, there is a paucity in IS literature on the competencies of humans that affect this relationship. In this study, we set out to develop a measurement instrument (scale) for general AI literacy, that is humans' socio-technical competencies regarding AI. We conducted a systematic literature review followed by five expert interviews to define and conceptualize the construct of general AI literacy and to generate an initial set of items. Furthermore, we performed two rounds of card sorting with six and five judges and a pre-test study with 50 participants to evaluate the developed scale. The validated measurement instrument contains five dimensions and 13 items. We provide empirical support for the measurement model and conclude with future research directions. Collapse

Topics: artificial intelligence IT skill implicit knowledge information system use digital literacy

Methods: survey design qualitative interview card sorting literature study cognitive walkthrough

AiLingo – A Design Science Approach to Advancing Non-Expert Adults’ AI Literacy

2023 | International Conference on Information Systems | Citations: 0

Authors: Pinski, Marc; Haas, Miguel; Franz, Anjuli

Abstract: Non-experts struggle in human-AI collaboration due to AI's differences from mor ... Expand

Abstract: Non-experts struggle in human-AI collaboration due to AI's differences from more traditional technologies, such as inscrutability. Meanwhile, information systems research on AI education primarily focuses on students in formal learning settings and neglects non-expert adults. Applying a design science research approach, we develop a learning application ("AiLingo") as an informal learning experience to advance nonexpert adults' AI literacy. Based on self-determination theory, we deduct design principles and features tailored to non-expert adults. Through experimental evaluation (n = 101), we find that a learning experience with our design features present (vs. absent) leads to greater AI literacy advancement. Additionally, we find downstream effects of AI literacy, as it increases AI usage continuance intention and leads to a more positive attitude toward AI. Our study contributes to AI literacy and educational literature with a perspective on non-expert adults, novel design knowledge for AI education, and the discovery of crucial AI literacy consequences. Collapse

Topics: artificial intelligence mobile application online learning system robotic user experience

Methods: design artifact design science experimental group experiment regression analysis method

Theories: self determination theory

Executive AI Literacy: A Text-Mining Approach to Understand Existing and Demanded AI Skills of Leaders in Unicorn Firms

2023 | International Conference on Business Informatics | Citations: 0

Authors: Pinski, Marc; Hofmann, Thomas; Benlian, Alexander

Abstract: Despite the growing relevance of artificial intelligence (AI) for businesses, t ... Expand

Abstract: Despite the growing relevance of artificial intelligence (AI) for businesses, there is a lack of research on how top-level executives must be skilled in AI. Drawing on upper echelons theory, this paper explores executive AI literacy, defined as the combined AI skills of top-level executives, and its relevance for different executive roles. We conducted a text-mining analysis of 1,625 executives' online profiles and 1,033 executive job postings from unicorn firms retrieved via web-scraping from an online professional social network. We find that AI skills are mostly required in product-related executive roles (vs. administrative roles). Thus, we provide an AI-specific perspective complementing prior information systems research on executives, which asserts that (non-AI) IT is driven by administrative executive roles. Our paper contributes to AI literacy literature by shedding light on the substance of executive AI literacy within firms. Lastly, we provide implications for AI-related information systems strategy. Collapse

Topics: artificial intelligence marketing management social network IT skill IT job

Methods: natural language processing latent semantic analysis factor analysis term frequency–inverse document frequency topic model

Theories: upper echelons theory

Effects of gender congruity in human-robot service interactions: The moderating role of masculinity

2023 | International Journal of Information Management | Citations: 0

Authors: Pitardi, Valentina; Bartikowski, Boris; Osburg, Victoria-Sophie; Yoganathan, Vignesh

Abstract: Despite humanoid service robots having attracted considerable research attention ... Expand

Abstract: Despite humanoid service robots having attracted considerable research attention, it remains unclear how consumers respond to some specific human characteristics of robots. Drawing from theories on social catego­ rization and identification, we study the role of consumer perceived control as a psychological mechanism to explain how human-robot gender congruity alters consumers’ affective reactions (feelings of comfort in the service encounter and service brand attitudes). We also consider that such gender congruity effects may be contingent on the individual cultural value of masculinity. We demonstrate experimentally that human-robot gender congruity (vs. incongruity) elicits more positive affect, while masculinity moderates some of these ef­ fects. Moreover, perceived control mediates effects of gender congruity on affective reactions only for consumers high on masculinity. We offer three major theoretical contributions as we 1) focus on social identity theory to shed light on how human-robot gender congruity affects consumer behavior in service encounters, 2) demon­ strate the role of perceptions of control as a psychological process variable to explain these effects, and 3) provide insights into the role of the cultural value of masculinity as a factor that shapes human-robot gender congruity effects. Collapse

Topics: robotic consumer behavior social norm human computer interaction artificial intelligence

Methods: experiment survey ANOVA parametric test statistical hypothesis test

Theories: social identity theory

Effects of Social Information on Risk Taking and Performance: Understanding Others’ Decisions vs. Comparing Oneself with Others in Short-Term Performance

2023 | Organization Science | Citations: 0

Authors: Pittnauer, Sabine; Hohnisch, Martin; Ostermaier, Andreas; Pfingsten, Andreas

Abstract: When a problem leaves decision makers uncertain as to how to approach it, observ ... Expand

Abstract: When a problem leaves decision makers uncertain as to how to approach it, observing others’ decisions can improve one’s own decisions by promoting more accurate judgments and a better insight into the problem. However, observing others’ decisions may also activate motives that prevent this potential from being realized, for instance, ego concerns that prompt excessive risk taking. Our experimental study investigates how two features of the social environment influence the effect of observing others’ decisions on individual risk taking and performance. We manipulated (1) the psychological distance to others whose decisions could be observed (and thereby the tendency to seek self-enhancing social comparison) and (2) the opportunity for interaction (and thereby for a cumulative effect of any such tendency on decisions over time and for an effect on social information itself). Because the two features covary in real-world settings, we designed two treatments corresponding to the two natural combinations. Both treatments provided participants with two other participants’ period decisions in a multiperiod problem under uncertainty. No new objective information about the problem could be inferred from these decisions. We predicted that participants who observed the decisions of distant others (who had solved the same problem earlier) would perform better than participants in a control sample without any information about others’ decisions and that participants who observed the decisions of proximal others (with whom interaction could arise) would take more risk and perform worse than those who observed distant others’ decisions. The data corroborate our predictions. We discuss implications for organizational learning.History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory.Funding: The research was made possible by funding from the Nordrhein-Westfälische Akademie der Wissenschaften und der Künste through the Akademienprogramm of the German Academies of Sciences and Humanities (2006–2015). Hohnisch and Pittnauer gratefully acknowledge funding from the Stiftung der Freunde und Förderer der NRW-Akademie der Wissenschaften und der Künste (2016).Supplemental Material: The supplemental material is available at https://doi.org/10.1287/orsc.2021.1507. Collapse

Topics: decision making organization learning problem solving

Methods: experiment hierarchical linear modeling descriptive statistic statistical power analysis cluster analysis

Theories: construal level theory

Emotional Rollercoaster: The Inverted U-Shaped Relationship between CEO Emotions and Innovation Outcomes

2023 | International Conference on Information Systems | Citations: 0

Authors: Platz, Marika; Schaeper, Thomas; Foege, Johann Nils

Abstract: While the literature suggests that CEOs' emotions can affect organizational dec ... Expand

Abstract: While the literature suggests that CEOs' emotions can affect organizational decisionmaking, leadership, and employee engagement, we know little about how they influence firms' culture and outcomes of innovation. Acknowledging that innovation is a critical element for long-term success, we investigate the relationship between CEO emotions and firm innovation. The results of our analysis of 1,903 firm-year observations supports our theorizing of an inverted U-shaped relationship between CEO emotions and innovation outcomes. The findings show that moderate levels of emotions lead to the highest innovation outcomes, while extremely high or low levels decrease innovation. This study contributes to the literature by applying the Yerkes-Dodson law within upper echelon theory, demonstrating a non-linear relationship between CEO emotions and innovation, and utilizing a novel algorithm to measure CEO emotions more objectively. Collapse

Topics: innovation management research and development database system advertising management decision making

Methods: computational algorithm Compustat natural language processing regression analysis method theory development

Theories: upper echelons theory

Data Valuation Methods - A Literature Review

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Pohl, Matthias; Haertel, Christian; Staegemann, Daniel; Turowski, Klaus

Abstract: Data has become an important asset for businesses, and it is crucial to underst ... Expand

Abstract: Data has become an important asset for businesses, and it is crucial to understand its value. The valuation of data is an important step in leveraging the potential of data as an asset. It helps companies to use data effectively and adapt their strategies accordingly. A distinction must be made between valuation and pricing. Valuation refers to the process of determining the objective value of an asset based on factors, such as comparable transactions, future cash flows or market trends. Pricing, in contrast, refers to the process of setting a price for a product offered in the market. The research paper at hand aims at an investigation of factors and methods for data valuation. Thus, a structured literature review is conducted to identify a framework to classify data valuation methods and influencing factors on the value of data. Collapse

Topics: database system

Methods: literature study structured literature research synthesis