Gratitude with Expectations: Exploring the Role of Restaurant Delivery and Food Availability on Online Customer Reviews During the COVID-19 Pandemic

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Avery, Atiya; Xu, Pei

Abstract: Online reviews have become a popular tool for understanding consumers' percepti ... Expand

Abstract: Online reviews have become a popular tool for understanding consumers' perceptions of service and product quality. The COVID-19 pandemic has significantly impacted the restaurant industry, including negative impacts on profitability. This study utilizes gratitude theory and expectation confirmation theory to investigate how food delivery and food desert status moderated the impact of the pandemic on consumers' perceptions of restaurant quality. We find that consumers still held expectations for restaurants despite the COVID-19 pandemic crisis and their lack of food availability. Our findings also highlight the importance of food accessibility and availability, particularly in underprivileged communities during a crisis. This study has broader implications for businesses operating during crisis events providing insights into how they can improve their service and product quality to meet the needs of their consumers. Collapse

Topics: pandemic service quality online review website geographic information system

Methods: product review robustness check

Theories: expectation confirmation theory

Digital development: Stories of hope from health and social development By Sundeep Sahay, Arunima Mukherjee, Geoff Walsham, Thomas Hylland Eriksen, Warwickshire: Practical Action Publishing. 2022, 164 pp., paperback £23.95. ISBN 978-1-78853-206-8

2023 | Information Systems Journal | Citations: 0

Authors: Avgerou, Chrisanthi

Abstract: Geoff Walsham, a leading academic in the field of information technology for de ... Expand

Abstract: Geoff Walsham, a leading academic in the field of information technology for development, has repeatedly prompted information systems (IS) researchers to question whether they are making a better world with IT. And, as he argued, the world cannot be considered better if life conditions of vulnerable and disadvantaged populations in low-and middle-income countries (LMICs) do not improve. This book has a cautiously positive message. It contains stories of digital technologies used for social good in LMICs. So, where is hope to be found? Four of the case studies are about health information systems in India and Sri Lanka; the other four are about smartphones and IT systems helping various vulnerable and disadvantaged social groups, specifically: refugees on the move towards safe places; un-banked populations of poor communities; victims of ethnic violence in Kenya; and women victims of violence in Guatemala. Three authors of the book, Sundeep Sahay, Arunima Mukherjee and Geoff Walsham, are information systems scholars; the fourth, Thomas Hylland Eriksen, is an anthropologist. The writing is erudite but approachable-a pleasure to read. Several case studies draw from the extensive experience of Sundeep Sahay and Arunima Mukherjee as participants in the development of the underlying technology of these cases, the DHIS2 open-source software. They have facilitated the use of the DHIS2 platform for a variety of purposes in many countries. They have also been involved in a long-standing education programme at the University of Oslo that supports the implementation and use of DHIS2 in LMICs by developing local skills.Taking a socio-technical perspective, the case studies of IT systems are narratives of design, implementation, and management of technology in local initiatives to provide essential services and address social problems. The case studies of smartphone use by refugees on the move and by poor people making micropayments and receiving remittances are stories of affordances of mobile phones in the life conditions of vulnerable social groups. The analytical framework used throughout the book calls attention to the means mobilised to address a challenging situation, the process followed, and the achieved ends. In addition to digital technologies with social change affordances, the means include available infrastructures and human capacity, such as local skills to customise generic open-source software to the local conditions. The process that leads to the desired outcomes is as multifaceted as the means and includes technology building, data gathering, local capability building as well as fostering effective management structures and alleviating institutional obstacles. Collapse

Topics: open source

Methods: case study

Sensing the Future: A Design Framework for Context-Aware Predictive Systems

2023 | Journal of the Association for Information Systems | Citations: 0

Authors: Avital, Michel; Chatterjee, Samir; Furtak, Szymon

Abstract: Sensors embedded in smart objects, smart machines, and smart buildings produce ... Expand

Abstract: Sensors embedded in smart objects, smart machines, and smart buildings produce ever-growing streams of contextual data that convey information of interest about their operating environment. Although an increasing number of industries have embraced the utilization of sensors in routine operations, no clear framework is available to guide designers who aim to leverage contextual data collected from these sensors to develop predictive systems. In this paper, we applied design science research methodology to develop and evaluate a general framework that can help designers build predictive systems utilizing sensor data. Specifically, we developed a framework for designing context-aware predictive systems (CAPS). We then evaluated the framework through its application in MAN Diesel & Turbo, which served as a case company. The framework can be generalized into a class of demand-forecasting problems that rely on sensor-generated contextual data. The CAPS framework is unique and can help practitioners make better-informed decisions when designing context-aware predictive systems. Collapse

Topics: data quality evaluation criteria knowledge base systems design systems development

Methods: machine learning design science design artifact data transformation design process

The social fabric framework: steps to eliciting the social making of organisations in the digital age

2023 | European Journal of Information Systems | Citations: 0

Authors: Avital, Michel; Jensen, Tina Blegind; Dyrby, Signe

Abstract: The proliferation of enterprise social media generates an ever-growing record of ... Expand

Abstract: The proliferation of enterprise social media generates an ever-growing record of digital traces that provides ample opportunities to study the social making of organisations. Subsequently, we present the social fabric framework, which comprises a structured five-step approach for eliciting, interpreting, and representing the situated social idiosyncrasies and underlying patterns of the social making of organisations. The paper focuses on the application of the social fabric framework as a research method. However, the framework also lends itself to practice as a diagnostic tool that can detect emergent changes in the social fabric of an organisation as well as support organisational development and change. Moreover, by providing a vocabulary for articulating the social making of organisations, the framework can help organisation members reify their dispositions, make sense of the social dynamics, and enable a constructive discussion at the grassroots level about any controversy or aspiration. Collapse

Topics: social media information exchange accounting enterprise social media

Methods: longitudinal research cluster analysis qualitative coding cross sectional research time series analysis

TRADING GREEN BONDS USING DISTRIBUTED LEDGER TECHNOLOGY

2023 | European Conference On Information Systems | Citations: 0

Authors: Axelsen, Henrik; Rasmussen, Ulrik; Jensen, Johannes; Ross, Omri; Henglein, Fritz

Abstract: The promising markets for voluntary carbon credits are faced with crippling cha ... Expand

Abstract: The promising markets for voluntary carbon credits are faced with crippling challenges to the certification of carbon sequestration and the lack of scalable market infrastructure in which companies and institutions can invest in carbon offsetting. This amounts to a funding problem for green transition projects, such as in the agricultural sector, since farmers need access to the liquidity needed to fund the transition to sustainable practices. We explore the feasibility of mitigating infrastructural challenges based on a DLT Trading and Settlement System for green bonds. The artefact employs a multi-sharded architecture in which the nodes retain carefully orchestrated responsibilities in the functioning of the network. We evaluate the artefact in a supranational context with an EU-based regulator as part of a regulatory sandbox program targeting the new EU DLT Pilot regime. By conducting design-driven research with stakeholders from industrial and governmental bodies, we contribute to the IS literature on the practical implications of DLT. Collapse

Topics: distributed ledger technology network effect blockchain domain-specific language

Methods: design science qualitative interview design artifact testing design artifact

The Consequences of Rating Inflation on Platforms: Evidence from a Quasi-Experiment

2023 | Information Systems Research | Citations: 0

Authors: Aziz, Arslan; Li, Hui; Telang, Rahul

Abstract: Informative online ratings enable digital platforms to reduce the search cost fo ... Expand

Abstract: Informative online ratings enable digital platforms to reduce the search cost for buyers to find good sellers. However, rating inflation, a phenomenon in which average rating increases and rating variance across listings decreases, threatens the informativeness of ratings. We empirically identify the consequences of rating inflation by conducting a quasi-experiment with a digital platform that exogenously changed its rating display rule in a treated neighborhood, which resulted in rating inflation. Using a differences-in-differences approach, we find that platforms benefit from one aspect of rating inflation: user purchases and seller sales increase because of the increased average rating. However, they also face negative consequences: rating inflation causes a decrease in user trial and a greater concentration of sales among popular restaurants. Overall, our results illustrate the potential consequences of rating inflation that platforms need to consider when designing and managing their rating system.History: Xiaoquan (Michael) Zhang, Senior Editor; Gordon Burtch, Associate Editor.Supplemental Material: The online appendices are available at https://doi.org/10.1287/isre.2022.1134. Collapse

Topics: digital platform mobile application word of mouth ease of use consumer behavior

Methods: experiment pilot experiment experimental group robustness check quasi experiment

Rumor Classification through a Multimodal Fusion Framework and Ensemble Learning

2023 | Information Systems Frontiers | Citations: 0

Authors: Azri, Abderrazek; Favre, Cécile; Harbi, Nouria; Darmont, Jérôme; Noûs, Camille

Abstract: The proliferation of rumors on social media has become a major concern due to it ... Expand

Abstract: The proliferation of rumors on social media has become a major concern due to its ability to create a devastating impact. Manually assessing the veracity of social media messages is a very time-consuming task that can be much helped by machine learning. Most message veracity verification methods only exploit textual contents and metadata. Very few take both textual and visual contents, and more particularly images, into account. Moreover, prior works have used many classical machine learning models to detect rumors. However, although recent studies have proven the effectiveness of ensemble machine learning approaches, such models have seldom been applied. Thus, in this paper, we propose a set of advanced image features that are inspired from the field of image quality assessment, and introduce the Multimodal fusiON framework to assess message veracIty in social neTwORks (MONITOR), which exploits all message features by exploring various machine learning models. Moreover, we demonstrate the effectiveness of ensemble learning algorithms for rumor detection by using five metalearning models. Eventually, we conduct extensive experiments on two real-world datasets. Results show that MONITOR outperforms state-of-the-art machine learning baselines and that ensemble models significantly increase MONITOR’s performance. Collapse

Topics: Twitter social network Python microblog logistics management

Methods: computational algorithm machine learning experiment meta learning ensemble learning

DataOps as a Prerequisite for the Next Level of Self-Service Analytics – Balancing User Agency and Central Control

2023 | International Conference on Business Informatics | Citations: 0

Authors: Baars, Henning

Abstract: The area of Business Intelligence and Analytics (BIA) has repeatedly oscillated ... Expand

Abstract: The area of Business Intelligence and Analytics (BIA) has repeatedly oscillated between more central, efficiency-oriented, professionalized approaches and decentral, agility-oriented, user-driven ones. This paper investigates whether and how to alleviate that tradeoff by combining an agility-oriented self-service analytics approach with the professionalization-driven DataOps concept: DataOps aims at transferring ideas from DevOps to the realm of analytics, namely a mutual integration of Development and Operations and a high degree of professionalization and automation. A case study with a series of interviews and a workshop led to insights into the viability of such a combination. These inspire a theoretical concept for capturing the economics behind the approaches that is considering the (opportunity) costs of the components "user agency" and "central control". The concept has been evaluated with representatives from the case study. Based on the results, I argue that the discussed combination can push BIA solutions towards fine-tuned federated environments. Collapse

Topics: devops artificial intelligence mlops data management data integration

Methods: qualitative interview case study literature study machine learning survey

The Effects of Digitally Delivered Nudges in a Corporate Wellness Program

2023 | Journal of the Association for Information Systems | Citations: 1

Authors: Babar, Yash; Curley, Shawn; Ke, Zhihong; Liu, De; Sheffler, Zachary

Abstract: We investigate how two digitally delivered nudges, namely light social support ... Expand

Abstract: We investigate how two digitally delivered nudges, namely light social support (nonverbal cues such as kudos or likes) and motivational messaging, affect employees' self-reported physical activity in an online, corporate wellness program. Within this unique field setting, using data from several years, we found evidence that both types of nudges provide benefits beyond the effect of cash incentives. However, the effects vary by individual, depending on whether the employee is actively engaging in physical activity, and by time, depending on how long the employee has been in the wellness program. We found light social support to be less effective over time, while motivational messages were found to be more effective with the duration in the program and generally more effective for physically inactive users. Our findings have implications for the design of wellness systems, suggesting different approaches depending on an employee's current activity level and tenure in the program.De Liu is a Xian Dong Eric Jing Professor of Information and Decision Sciences at the Carlson School of Management, University of Minnesota. He received his PhD from the University of Texas at Austin, and his master's and bachelor's degrees from Tsinghua University. His recent research interests include gamification, AI /augmented reality, internetbased auctions and market mechanisms, online reviews, and crowdfunding. His research has appeared in leading journals such as MIS Quarterly, Management Science, Information Systems Research, Journal of Marketing, Journal of Market Research, and Production and Operations Management. He has served as an associate editor for Information Systems Research and Journal of Organizational Computing and Electronic Commerce. He is also the academic director of the Business Analytics programs at the Carlson School of Management.Yash Babar is an assistant professor in the Department of Operations and Information Management at the University of Wisconsin-Madison. He received his PhD from the University of Minnesota in information and decision sciences and his bachelor's degree from BITS Pilani Goa. He researches the socioeconomic impacts of information systems exploring online-offline interactions in digital platforms like the gig economy, online communities, social media, and mobile fitness applications. His work has appeared in Information Systems Research and MIS Quarterly and at several international IS conferences. Collapse

Topics: mobile phone web forum intrinsic motivation user behavior

Methods: longitudinal research difference in differences Poisson regression propensity score matching robustness check

Theories: self determination theory

Introduction to the Minitrack on Data Analytics, Data Mining, and Machine Learning for Social Media

2023 | HICSS | Citations: 0

Authors: Babb, J.; Mentzer, K.; Yates, D.

Abstract: Thank you for your interest in the Data Analytics, Data Mining, and Machine Le ... Expand

Abstract: Thank you for your interest in the Data Analytics, Data Mining, and Machine Learning for Social Media Minitrack. This year's paper contributions vary in scope and focus and thus provide a rich spectral view of developing insights and understanding from social media. According to Monique Thomas of Later, social media is experiencing a significant evolution: "We've said goodbye to simple status updates (we miss you!) and hello to social selling and growing digital communities." However, our digital communities continue to struggle with the challenge of being free and open, allowing anyone to express their thoughts and ideas, while at the same time working to combat misinformation and deep fakes. We are grateful to social media scholars who continue on various paths of sensemaking to better understand social media's impact on our society. This year's papers provide many new insights into this vital area of research. Collapse

Topics: social media misinformation privacy online community Twitter

Methods: structured literature research cluster analysis sentiment analysis case study