A Systematic Review of Blockchain-based Loyalty Programs

2023 | HICSS | Citations: 0

Authors: Abooleet, Saeed; Kinnett, Seth

Abstract: Customer loyalty programs, the incentive structures designed to reward and retai ... Expand

Abstract: Customer loyalty programs, the incentive structures designed to reward and retain customers for purchases and other activities, have struggled to maximize their intended goals. Academics and industry practitioners have advocated for the use of blockchain technology as a vehicle to revolutionize loyalty programs. Despite this hype, we have yet to see an examination of existing blockchain-based loyalty solutions. This paper identifies, reviews, and classifies tokenized loyalty solutions. Using a web-scraping method, we systematically retrieved 9,642 tokens listed on the coinmarketcap.com website. Multiple applications of inclusion/exclusion criteria resulted in 21 active loyalty programs based on blockchain, which we evaluated in depth. Our findings confirm that the domain is nascent yet more actualized than previous research has suggested. This analysis fills a much-needed role in the blockchain-loyalty literature by providing an industry lens into the realities of blockchain as a loyalty solution. Collapse

Topics: blockchain cryptoasset crypto exchange customer loyalty website

Methods: descriptive statistic structured literature research

Ambivalence as a Predictor of Online Review Helpfulness

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Akgul, Mehmet; MONTAZEMI, Ali Reza

Abstract: Online platforms, such as Yelp and TripAdvisor, have facilitated ubiquitous and ... Expand

Abstract: Online platforms, such as Yelp and TripAdvisor, have facilitated ubiquitous and convenient access to a large number of online reviews about almost any product/service. However, they impose an information load on the consumers due to their large number of reviews. The review star rating is practiced to ameliorate consumers' information load. A review star rating shows the reviewer's overall evaluation of a product/service. Nonetheless, the extant research findings about the relationship between star rating and review helpfulness are mixed. Star rating, being a unidimensional bipolar measure, is unable to correctly capture the underlying evaluations of the review content. Our contention in this research is that the use of review ambivalence is a better predictor of review helpfulness than the traditional star rating. To that end, we provide the theoretical foundation and pertinent methodology to assess our research question. KeywordsOnline review helpfulness, ambivalence, electronic word of mouth, eWoM Collapse

Topics: online word of mouth word of mouth

Methods: natural language processing sentiment analysis

Self-Building Artificial Intelligence and Machine Learning to Empower Big Data Analytics in Smart Cities

2023 | Information Systems Frontiers | Citations: 0

Authors: Alahakoon, Damminda; Nawaratne, Rashmika; Xu, Yan; De Silva, Daswin; Sivarajah, Uthayasankar; Gupta, Bhumika

Abstract: The emerging information revolution makes it necessary to manage vast amounts of ... Expand

Abstract: The emerging information revolution makes it necessary to manage vast amounts of unstructured data rapidly. As the world is increasingly populated by IoT devices and sensors that can sense their surroundings and communicate with each other, a digital environment has been created with vast volumes of volatile and diverse data. Traditional AI and machine learning techniques designed for deterministic situations are not suitable for such environments. With a large number of parameters required by each device in this digital environment, it is desirable that the AI is able to be adaptive and self-build (i.e. self-structure, self-configure, self-learn), rather than be structurally and parameter-wise pre-defined. This study explores the benefits of self-building AI and machine learning with unsupervised learning for empowering big data analytics for smart city environments. By using the growing self-organizing map, a new suite of self-building AI is proposed. The self-building AI overcomes the limitations of traditional AI and enables data processing in dynamic smart city environments. With cloud computing platforms, the self-building AI can integrate the data analytics applications that currently work in silos. The new paradigm of the self-building AI and its value are demonstrated using the IoT, video surveillance, and action recognition applications. Collapse

Topics: artificial intelligence smart city big data cloud computing distributed system

Methods: computational algorithm experiment unsupervised learning machine learning longitudinal research

Impact of Anxiety on Information Processing Among Young Adults: An Exploratory Eye-tracking Study

2023 | HICSS | Citations: 0

Authors: Alrefaei, Doaa; Sankar, Gaayathri; Norouzi Nia, Javad; Djamasbi, Soussan; Liu, Shichao; Strauss, Sarah; Gbetonmasse, Somasse

Abstract: Anxiety, one of the most common mental illnesses among American adults, is often ... Expand

Abstract: Anxiety, one of the most common mental illnesses among American adults, is often assessed via self-reported measures. While self-reported measures provide an efficient step in capturing health symptoms from patients’ point of view, by their mere nature self-reported measures provide only a narrow interpretation of health symptoms. Capturing eye movements unobtrusively during self-reports, when patients summarize their experience of anxiety by choosing a single option among a set of alternatives, can provide invaluable insight about patients’ information processing and decision behavior. Because anxiety impacts how we attended to information that we use to select options, the objective moment-to-moment eye-movement data can substantially enrich the information that is typically provided by patients as single scores representing their anxiety levels. Supporting this point of view, our results indicate that eye movements may serve as valuable objective information complementing the subjective self-reported anxiety measures to enable more effective assessment and treatment of anxiety. Collapse

Topics: decision making innovation management

Methods: oculometry self reported survey regression analysis method survey experiment

Measuring the Actual Office Workspace Utilization in a Desk Sharing Environment Based on IoT Sensors

2023 | DESRIST | Citations: 0

Authors: Arz von Straussenburg, Arnold F.; Blazevic, Mevludin; Riehle, Dennis M.

Abstract: Businesses that follow the trend of flexible work arrangements with home offices ... Expand

Abstract: Businesses that follow the trend of flexible work arrangements with home offices and hybrid work models are increasingly utilizing desk sharing to allocate available desks in the office efficiently. In this work, we investigate the utilization of flexible work arrangements, specifically the implementation of desk sharing in hybrid work models. To optimize the occupancy rate of shared desks and simultaneously meet demand and save costs, it is crucial to have real-time knowledge of their availability which can be obtained by recording occupancy over time. We utilize the Design Science Research (DSR) methodology to develop a prototype solution for real-time monitoring of shared desks occupancy in hybrid work models. The proposed prototype is a low-cost solution utilizing Internet of Things (IoT) technology consisting of a motion sensor and accelerometer that collect occupancy data and transmit it via Long Range Wide Area Network (LoRaWAN). Signal processing utilizing cloud computing is employed to enhance the quality and accuracy of the data, which is subsequently made available through a web dashboard. The prototype’s effectiveness is evaluated through a small-scale pilot deployment in a real-world environment over a two-week period, with reference values obtained during periods of non-use serving as a benchmark for the evaluation. Collapse

Topics: mobile system internet of things digital dashboard application programming interface smart wearable device

Methods: design artifact wearables based research design science experiment descriptive statistic

The impact of enterprise architecture management on information systems architecture complexity

2023 | European Journal of Information Systems | Citations: 0

Authors: Beese, Jannis; Aier, Stephan; Haki, Kazem; Winter, Robert

Abstract: Significant investments in information systems (IS) over the past decades have l ... Expand

Abstract: Significant investments in information systems (IS) over the past decades have led to increasingly complex IS architectures in organisations, which are difficult to understand, operate, and maintain. We investigate this development and associated challenges through a conceptual model that distinguishes four constituent elements of IS architecture complexity by differentiating technological from organisational aspects and structural from dynamic aspects. Building on this conceptualisation, we hypothesise relations between these four IS architecture complexity constructs and investigate their impact on architectural outcomes (i.e., efficiency, flexibility, transparency, and predictability). Using survey data from 249 IS managers, we test our model through a partial least squares (PLS) approach to structural equation modelling (SEM). We find that organisational complexity drives technological complexity and that structural complexity drives dynamic complexity. We also demonstrate that increasing IS architecture complexity has a significant negative impact on efficiency, flexibility, transparency, and predictability. Finally, we show that enterprise architecture management (EAM) helps to offset these negative effects by acting as a moderator in the relation between organisational and technological IS architecture complexity. Thus, organisations without adequate EAM are likely to face large increases in technological complexity due to increasing organisational complexity, whereas organisations with adequate EAM exhibit no such relation. Collapse

Topics: enterprise architecture IT manager IT development project missing data organization structure

Methods: survey focus group survey design structural equation modeling partial least squares path modeling

INNOVATION ON THE VENDOR SIDE - ANALYZING THE EFFECTS OF INNOVATION INITIATIVES ON OUTSOURCING PROVIDERS' PERFORMANCE

2023 | European Conference On Information Systems | Citations: 0

Authors: Beimborn, Daniel; Mildenberger, Andreas

Abstract: Innovation through outsourcing' describes a firm's strategy to receive innovati ... Expand

Abstract: Innovation through outsourcing' describes a firm's strategy to receive innovation by outsourcing IT or IT-intensive processes to more competent and innovative service providers who, in turn, do not only operate those activities but also improve and innovate for or on behalf of their clients. This strategy has gathered some attention from recent research, though it has mainly examined the client perspective, yet. We contribute to this sub-field of outsourcing research by analyzing vendors' strategies to improve their innovation capability and thus to be more innovative for their clients. Based on a longitudinal dataset of 136 outsourcing vendors, we analyze which innovationenabling initiatives are related to superior firm performance (in terms of revenue growth). We find that particularly employee-involving initiatives are promising: outsourcing vendors that have implemented, e.g., idea/innovation platforms that support employee-driven innovation, receive above-average revenue growth. Collapse

Topics: innovation management outsourcing organizational productivity financial performance absorptive capacity

Methods: regression analysis method statistical hypothesis test longitudinal research Student's t-test linear regression analysis

Theories: dynamic capabilities theory

Towards a thematic dimensional framework of online fraud: An exploration of fraudulent email attack tactics and intentions

2023 | Decision Support Systems | Citations: 1

Authors: Bera, Debalina; Ogbanufe, Obi; Kim, Dan J.

Abstract: Despite anti-phishing filters, social engineering-based cyber-attacks still resu ... Expand

Abstract: Despite anti-phishing filters, social engineering-based cyber-attacks still result in billions of dollars lost annually, significant personal identity theft, loss of corporate secrets, and espionage. We review the phishing literature on psychological attacks and design tactics employed for deception by attackers. The result reveals the need to continuously identify tactics embedded in fraudulent email content to understand why users still fall prey to phishing attacks. Using the literature as a backdrop, we identify and conceptualize a thematic dimensional framework of fraudulent phishing attacks. This study uses benchmark datasets of fraudulent email to empirically validate the proposed dimensional framework. Specifically, a combination of machine learning-based content analysis and topic modeling found a majority of the discovered topics were labeled against the proposed di­ mensions. Statistical analysis was employed to provide empirical evidence of the thematic dimensions of fraudulent email attacks. This study thus, not only extends the cybersecurity literature by identifying and vali­ dating eight dimensions that enrich our understanding of phishing and attack identification but stimulates cu­ mulative research endeavors to develop yet more comprehensive dimensional frameworks of phishing email attacks. Collapse

Topics: phishing email phishing electronic mail email spam personalization

Methods: term frequency–inverse document frequency natural language processing topic model discriminant analysis literature study

Microfoundations of Adaptive Search in Complex Tasks: The Role of Cognitive Abilities and Styles

2023 | Organization Science | Citations: 1

Authors: Bergenholtz, Carsten; Vuculescu, Oana; Amidi, Ali

Abstract: Problem-solving in complex environments requires a cognitively demanding search ... Expand

Abstract: Problem-solving in complex environments requires a cognitively demanding search for task solutions. Managing this search process presents a major challenge in organizations. We contribute to the literature on this topic by providing new evidence on the cognitive antecedents that shape how individuals search when engaged in complex problem-solving tasks. We present results from three laboratory studies, wherein 335 individuals solved a complex task. In doing so, they generated behavioral data coupled with survey-based measurements of the individuals’ cognitive styles and performance-based tests of their cognitive abilities. Our data analysis contributes to the current literature by documenting systematic heterogeneity in the persistence and distance of search that can be explained by the participants’ level of creativity, attention to detail, and executive functions. We extend the research on the microfoundations of adaptive search by linking cognitive antecedents with a complex search task, widening our insight into what search behavior certain cognitive microfoundations lead to, and showing how managers can more effectively shape organizational search.History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory.Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2023.1654. Collapse

Topics: decision making logistics management problem solving anonymity competitive advantage

Methods: laboratory experiment survey qualitative interview experimental task generalized linear model

Theories: ambidexterity theory

AI-Enhanced Hybrid Decision Management

2023 | Business & Information Systems Engineering | Citations: 0

Authors: Bork, Dominik; Ali, Syed Juned; Dinev, Georgi Milenov

Abstract: The Decision Model and Notation (DMN) modeling language allows the precise speci ... Expand

Abstract: The Decision Model and Notation (DMN) modeling language allows the precise specification of business decisions and business rules. DMN is readily understandable by business users involved in decision management. However, as the models get complex, the cognitive abilities of humans threaten manual maintainability and comprehensibility. Proper design of the decision logic thus requires comprehensive automated analysis of e.g., all possible cases the decision shall cover; correlations between inputs and outputs; and the importance of inputs for deriving the output. In the paper, the authors explore the mutual benefits of combining human-driven DMN decision modeling with the computational power of Artificial Intelligence for DMN model analysis and improved comprehension. The authors propose a model-driven approach that uses DMN models to generate Machine Learning (ML) training data and show, how the trained ML models can inform human decision modelers by means of superimposing the feature importance within the original DMN models. An evaluation with multiple real DMN models from an insurance company evaluates the feasibility and the utility of the approach. Collapse

Topics: artificial intelligence explainable artificial intelligence perceived usefulness price management extensible markup language

Methods: computational algorithm decision tree classification experiment conceptual modelling simulation