Enhancing Trust, Efficiency, and Empowerment in Sports: Developing a Blockchain-Based Fan Token Framework

2023 | European Conference On Information Systems | Citations: 0

Authors: Ante, Lennart; Schellinger, Benjamin; Wazinski, Friedrich-Philipp

Abstract: Blockchain-based fan tokens provide token holders with certain rights, incentiv ... Expand

Abstract: Blockchain-based fan tokens provide token holders with certain rights, incentivizing fan engagement and decision-making within sports organizations. Despite the recent surge in interest, acceptance and technical advancement, a profound understanding of the technical, functional, and conceptual foundations of fan tokens is still lacking, necessitating further research and practical insights. Drawing on customer and fan engagement theory and utilizing a single case study approach, we analyzed the market-leading platform Socios for the issuance and operation of fan tokens. Our analysis yields a generic blockchain-based fan token framework that includes the constructs: 1) Trust and efficiency layer, 2) utility and 3) financialization features. The latter two constructs promote fan token holder empowerment. In addition, we extend the current definition of fan tokens to the context of blockchain. Our findings indicate that fan tokens are still in a nascent stage, requiring continued research and development. Collapse

Topics: blockchain tokenomics website web application mobile application

Methods: case study single case study survey cluster analysis multidimensional modeling

Theories: job engagement theory

Big Data Guided Resources Businesses – Leveraging Location Analytics and Managing Geospatial-temporal Knowledge

2023 | HICSS | Citations: 0

Authors: Nimmagadda, Shastri; Ochan, Andrew; Reiners, Torsten; Mani, Neel

Abstract: Location data rapidly grow with fast-changing logistics and business rules. Due ... Expand

Abstract: Location data rapidly grow with fast-changing logistics and business rules. Due to fast-growing business ventures and their diverse operations locally and globally, location-based information systems are in demand in resource industries. Data sources in these industries are spatial-temporal, with petabytes in size. Managing volumes and various data in periodic and geographic dimensions using the existing modelling methods is challenging. The current relational database models have implementation challenges, including the interpretation of data views. Multidimensional models are articulated to integrate resource databases with spatial-temporal attribute dimensions. Location and periodic attribute dimensions are incorporated into various schemas to minimise ambiguity during database operations, ensuring resource data's uniqueness and monotonic characteristics. We develop an integrated framework compatible with the multidimensional repository and implement its metadata in resource industries. The resources’ metadata with spatial-temporal attributes enables business research analysts a scope for data views’ interpretation in new geospatial knowledge domains for financial decision support. Collapse

Topics: big data data warehouse database system

Methods: multidimensional modeling design science conceptual modelling data modeling entity relationship modeling

Designing Core-Selecting Payment Rules: A Computational Search Approach

2022 | Information Systems Research | Citations: 0

Authors: Bünz, Benedikt; Lubin, Benjamin; Seuken, Sven

Abstract: We study the design of core-selecting payment rules for combinatorial auctions, ... Expand

Abstract: We study the design of core-selecting payment rules for combinatorial auctions, a challenging setting where no strategyproof rules exist. We show that the rule most commonly used in practice, the Quadratic rule, can be improved on in terms of efficiency, incentives, and revenue. We present a new computational search framework for finding good mechanisms, and we apply it toward a search for good core-selecting rules. Within our framework, we use an algorithmic Bayes–Nash equilibrium solver to evaluate 366 rules across 31 settings to identify rules that outperform the Quadratic rule. Our main finding is that our best-performing rules are large-style rules—that is, they provide bidders with large values with better incentives than does the Quadratic rule. Finally, we identify two particularly well-performing rules and suggest that they may be considered for practical implementation in place of the Quadratic rule. History: This paper has been accepted for the Information Systems Research Special Section on Market Design and Analytics. Ravi Bapna, Martin Bichler, Bob Day, Wolfgang Ketter, Senior Editors; Sasa Pekec, Associate Editor. Supplemental Material: The online supplement is available at https://doi.org/10.1287/isre.2022.1108. Funding: Part of this research was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme [Grant Agreement 805542]. This material is based upon work supported by the National Science Foundation [Grant CMMI-1761163]. Collapse

Topics: shapley additive explanation economic surplus IS economics open source

Methods: computational algorithm experiment design framework multidimensional modeling descriptive statistic

Enhancing Cubes with Models to Describe Multidimensional Data

2022 | Information Systems Frontiers | Citations: 0

Authors: Francia, Matteo; Marcel, Patrick; Peralta, Verónika; Rizzi, Stefano

Abstract: The Intentional Analytics Model (IAM) has been recently envisioned as a new para ... Expand

Abstract: The Intentional Analytics Model (IAM) has been recently envisioned as a new paradigm to couple OLAP and analytics. It relies on two basic ideas: (i) letting the user explore data by expressing her analysis intentions rather than the data she needs, and (ii) returning enhanced cubes, i.e., multidimensional data annotated with knowledge insights in the form of interesting model components (e.g., clusters). In this paper we contribute to give a proof-of-concept for the IAM vision by delivering an end-to-end implementation of describe, one of the five intention operators introduced by IAM. Among the research challenges left open in IAM, those we address are (i) automatically tuning the size of models (e.g., the number of clusters), (ii) devising a measure to estimate the interestingness of model components, (iii) selecting the most effective chart or graph for visualizing each enhanced cube depending on its features, and (iv) devising a visual metaphor to display enhanced cubes and interact with them. We assess the validity of our approach in terms of user effort for formulating intentions, effectiveness, efficiency, and scalability. Collapse

Topics: Python online analytical processing structured query language covid 19 JavaScript

Methods: cluster analysis design artifact experiment multidimensional modeling design science

Contextual drivers of employees' phishing susceptibility: Insights from a field study

2022 | Decision Support Systems | Citations: 0

Authors: Frank, Muriel; Jaeger, Lennart; Ranft, Lukas Manuel

Abstract: Phishing attacks rate as one of the most prevalent security threats to contempor ... Expand

Abstract: Phishing attacks rate as one of the most prevalent security threats to contemporary organizations. Hence, managers strive heavily to apply security measures that keep their employees safe from these risks, thereby relying on insights from security researchers who have predominantly focused on recipient characteristics, message attributes, and interventions to explicate the phishing susceptibility of individuals. A theoretical lens yet to be explored is the discrete context in which individuals encounter phishing attacks. This paper presents a multi-dimensional model – comprising the three contextual components social, task, and physical – that explains why an employee is likely to fall for phishing emails or not. To empirically validate our model, we conducted a field study among 2302 employees of an internationally operating pharmaceutical company in the United States. By combining employees' behavioral responses to a phishing email, training data, and contextual data, like help desk reliance, job status or workspace, we find that context is key to a more thorough understanding of phishing susceptibility. Moreover, our study provides practical insights on how organizations can identify and support employees prone to phishing as well as tailor training programs to prevent their workforce from falling prey to cybercriminals. Collapse

Topics: phishing service desk email phishing IT security training social network

Methods: logistic regression multidimensional modeling company material field study ANOVA

Effects of Personality on Trading Performance in Social Trading Platforms

2022 | Americas Conference on Information Systems | Citations: 0

Authors: Liu, Quanchen; Xiong, Bingqing; Lim, Eric; Zhu, Jiantao

Abstract: Social trading platforms offer opportunities for amateur investors to copy prof ... Expand

Abstract: Social trading platforms offer opportunities for amateur investors to copy professional traders' behavior. However, past studies on behavioral finance have largely neglected the role of personality in shaping traders' behavior. To this end, we aim to scrutinize the effects of leader traders' personality on their trading behaviors and subsequent performance on social trading platforms. Particularly, we employ the Myers-Briggs Type Indicator (MBTI) personality classification scheme to delineate leader traders' personality into the four dimensions of Extraversion-Introversion (E-I), Sensing-Intuition (S-N), Thinking-Feeling (T-F), and Judging-Perceiving (J-P). Next, we draw on machine learning techniques to advance a novel text-based approach for extracting the personality dimensions of leader traders automatically. Analytical results attest to the impact of personality dimensions on trading behavior and that of trading behavior on performance. Findings from this study yield insights for both social trading platforms and followers by identifying profitable leader traders based on their personality. Collapse

Topics: personality social trading platform

Methods: machine learning descriptive statistic statistical hypothesis test multidimensional modeling partial least squares regression

Theories: Myers–Briggs type indicator big five model behavioral economics

A Multi-Dimensional Theory of Transparency, Trust, and Risk in Technology Adoption

2022 | International Conference on Information Systems | Citations: 0

Authors: Märtins, Julian; Kehl, Robin; Westmattelmann, Daniel; Schewe, Gerhard

Abstract: With regard to the complexity of emerging technologies, technology acceptance r ... Expand

Abstract: With regard to the complexity of emerging technologies, technology acceptance research examines the role of transparency, trusting beliefs, and perceived risks in individuals' technology adoption process. However, IS research lacks an established theoretical explanation of the interrelationship of those multi-dimensional constructs. Referring to organizational science, an integrative model considering transparency, trusting beliefs, and perceived risks is developed. To obtain generalizable results, we collected quantitative survey data for two different technologies: A banking app and a foodsharing app. The proposed research model was then tested using structural equation modeling and multigroup analysis. The results indicate that transparency should be understood as an antecedent of trusting beliefs. This relationship is technologyindependent, whereas the relationship between trusting beliefs and individuals' intention to use depends on the technology in question. The study also suggests that perceived risks are context-specific and should not generally be considered as moderators. Collapse

Topics: mobile application usage intention technology adoption privacy information exchange

Methods: survey structural equation modeling survey design partial least squares regression PLS tool

Investigating Impulse Buying Behavior in Live Streaming Commerce: The Role of Social Presence

2022 | HICSS | Citations: 0

Authors: Zhang, Xiaoping; Cheng, Xusen; Huang, Xiaowen; Li, Haolin

Abstract: Live streaming is changing the paradigm of people’s entertainment and consumptio ... Expand

Abstract: Live streaming is changing the paradigm of people’s entertainment and consumption. It has been adopted by many small individual sellers to improve their market performance, leading to the emergence of live streaming commerce. Although existing literature has paid attention to consumer purchase behavior in live streaming commerce, little knowledge on impulse buying can be available. Drawing on social presence theory and cognitive-affective framework, this paper attempts to develop a theoretical model to investigate how social presence affects consumers’ urge to buy impulsively through the mediating mechanism of cognitive state (i.e., product risk) and affective state (i.e., affective intensity). This paper is expected to advance knowledge on consumers’ impulse buying in live streaming commerce. Collapse

Topics: social presence live streaming platform smart city social commerce

Methods: theory development survey multidimensional modeling theoretical contribution literature study

Theories: social presence theory

Peak cubes in service operations: Bringing multidimensionality into decision support systems

2021 | Decision Support Systems | Citations: 0

Authors: Barfar, Arash; Padmanabhan, Balaji; Hevner, Alan

Abstract: Companies like Ritz Carlton, Disney and Verizon are among many who have invested ... Expand

Abstract: Companies like Ritz Carlton, Disney and Verizon are among many who have invested in analytics to improve their customers’ service experiences with the firms. Extensive data are collected on all aspects of how customers interact or experience the products or services. Research has shown the importance of the “peak-end” rule in service design; that is, providing a customer with good “peak” service levels and “ending” the service experience with high quality can enhance customer satisfaction and build loyalty. However, previous studies have examined this phenomenon only in contexts with unidimensional service levels. We introduce peak cubes, which enable service designers and scholars to pinpoint prominent service levels in multidimensional service experience pro­ files—thereby extending current research on behavioral economics and service design to more general settings. Results indicate the potential of multidimensional peak-end models to better predict customer satisfaction in various service scenarios. Using Shapley values in coalitional game theory, the resulting models can also inform service designers about the quality dimensions that are critical from the perspective of multidimensional peakend heuristic and customer satisfaction. Our research contributions and proposed methodology will enhance decision support systems with multidimensional capabilities and have applications to fields as diverse as service operations and healthcare. Collapse

Topics: service quality shapley additive explanation logistics management customer satisfaction database system

Methods: simulation computational algorithm time series analysis longitudinal research LightGBM

Theories: behavioral economics theory of bounded rationality game theory cooperative game theory

Applying data driven decision making to rank vocational and educational training programs with TOPSIS

2021 | Decision Support Systems | Citations: 2

Authors: Conejero, J.M.; Preciado, J.C.; Prieto, A.E.; Bas, M.C.; Bolós, V.J.

Abstract: In this paper we present a multi-criteria classification of Vocational and Educa ... Expand

Abstract: In this paper we present a multi-criteria classification of Vocational and Educational Programs in Extremadura (Spain) during the period 2009–2016. This ranking has been carried out through the integration into a complete database of the detailed information of individuals finishing such studies together with their labor data. The multicriteria method used is TOPSIS together with a new decision support method for assessing the influence of each criterion and its dependence on the weights assigned to them. This new method is based on a worst-best case scenario analysis and it is compared to a well known global sensitivity analysis technique based on the Pearson’s correlation ratio. Collapse

Topics: database system decision support decision making

Methods: trade-off analysis method TOPSIS multiple criteria decision making sensitivity analysis expert panel