Thorsten Schoormann, Gero Strobel, Frederik Möller, Dimitri Petrik, Patrick Zschech
The booming adoption of Artificial Intelligence (AI) likewise poses benefits and challenges. In this paper, we particularly focus on the bright side of AI and its promising potential to face our society’s grand challenges. Given this potential, different studies have already conducted valuable work by conceptualizing specific facets of AI and sustainability, including reviews on AI and Information Systems (IS) research or AI and business values. Nonetheless, there is still little holistic knowledge at the intersection of IS, AI, and sustainability. This is problematic because the IS discipline, with its socio-technical nature, has the ability to integrate perspectives beyond the currently dominant technological one as well as can advance both theory and the development of purposeful artifacts. To bridge this gap, we disclose how IS research currently makes use of AI to boost sustainable development. Based on a systematically collected corpus of 95 articles, we examine sustainability goals, data inputs, technologies and algorithms, and evaluation approaches that define the current state of the art within the IS discipline. This comprehensive overview enables us to make more informed investments (e.g., policy and practice) as well as to discuss blind spots and possible directions for future research.
{"title":"Artificial Intelligence for Sustainability—A Systematic Review of Information Systems Literature","authors":"Thorsten Schoormann, Gero Strobel, Frederik Möller, Dimitri Petrik, Patrick Zschech","doi":"10.17705/1cais.05209","DOIUrl":"https://doi.org/10.17705/1cais.05209","url":null,"abstract":"The booming adoption of Artificial Intelligence (AI) likewise poses benefits and challenges. In this paper, we particularly focus on the bright side of AI and its promising potential to face our society’s grand challenges. Given this potential, different studies have already conducted valuable work by conceptualizing specific facets of AI and sustainability, including reviews on AI and Information Systems (IS) research or AI and business values. Nonetheless, there is still little holistic knowledge at the intersection of IS, AI, and sustainability. This is problematic because the IS discipline, with its socio-technical nature, has the ability to integrate perspectives beyond the currently dominant technological one as well as can advance both theory and the development of purposeful artifacts. To bridge this gap, we disclose how IS research currently makes use of AI to boost sustainable development. Based on a systematically collected corpus of 95 articles, we examine sustainability goals, data inputs, technologies and algorithms, and evaluation approaches that define the current state of the art within the IS discipline. This comprehensive overview enables us to make more informed investments (e.g., policy and practice) as well as to discuss blind spots and possible directions for future research.","PeriodicalId":47724,"journal":{"name":"Communications of the Association for Information Systems","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135534334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pratyush N. Sharma, Benjamin D. Liengaard, Marko Sarstedt, Joseph F. Hair, Christian M. Ringle
{"title":"Extraordinary Claims Require Extraordinary Evidence: A Comment on “Recent Developments in PLS”","authors":"Pratyush N. Sharma, Benjamin D. Liengaard, Marko Sarstedt, Joseph F. Hair, Christian M. Ringle","doi":"10.17705/1cais.05234","DOIUrl":"https://doi.org/10.17705/1cais.05234","url":null,"abstract":"","PeriodicalId":47724,"journal":{"name":"Communications of the Association for Information Systems","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136297680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Judith Gebauer, Minoo Modaresnezhad, Christopher Sibona, Kevin Matthews
Stakeholder analysis is a methodology that can provide valuable insights about a phenomenon. Information systems and information technology researchers have utilized stakeholder analysis to understand and learn from successes, failures, and other aspects of IS/IT initiatives. In this tutorial, we provide guidelines for conducting a stakeholder analysis currently missing in the IS/IT discipline despite being repeatedly called for. We reviewed studies on stakeholder analysis within IS/IT first, but found that there was not sufficient coverage. Then we went outside the discipline and found relevant studies in the areas of organizational and strategic management and public policy. Our analysis, then, consists of a review and a combination of the findings of studies from within the IS/IT discipline and studies in organizational and strategic management and public policy. Our guidelines start with determining who the stakeholders are related to a phenomenon and what key concerns these stakeholders have about the phenomenon. In the next step, we relate stakeholders to one another and across the key concerns and point out how to identify possible coalitions. Last, we describe how to apply these findings to determine strategies for managing stakeholders or building theory around a phenomenon and its concerns. These final steps can be used to make policy recommendations, provide guidance for IS/IT-related initiatives, or present constructs and relationships that can be tested by future researchers. We demonstrate the applicability of our guidelines with a case study about broadband availability in rural North Carolina.
{"title":"A Guide for Stakeholder Analysis in IS/IT Management and Research: The Case of Broadband Availability in Rural North Carolina","authors":"Judith Gebauer, Minoo Modaresnezhad, Christopher Sibona, Kevin Matthews","doi":"10.17705/1cais.05326","DOIUrl":"https://doi.org/10.17705/1cais.05326","url":null,"abstract":"Stakeholder analysis is a methodology that can provide valuable insights about a phenomenon. Information systems and information technology researchers have utilized stakeholder analysis to understand and learn from successes, failures, and other aspects of IS/IT initiatives. In this tutorial, we provide guidelines for conducting a stakeholder analysis currently missing in the IS/IT discipline despite being repeatedly called for. We reviewed studies on stakeholder analysis within IS/IT first, but found that there was not sufficient coverage. Then we went outside the discipline and found relevant studies in the areas of organizational and strategic management and public policy. Our analysis, then, consists of a review and a combination of the findings of studies from within the IS/IT discipline and studies in organizational and strategic management and public policy. Our guidelines start with determining who the stakeholders are related to a phenomenon and what key concerns these stakeholders have about the phenomenon. In the next step, we relate stakeholders to one another and across the key concerns and point out how to identify possible coalitions. Last, we describe how to apply these findings to determine strategies for managing stakeholders or building theory around a phenomenon and its concerns. These final steps can be used to make policy recommendations, provide guidance for IS/IT-related initiatives, or present constructs and relationships that can be tested by future researchers. We demonstrate the applicability of our guidelines with a case study about broadband availability in rural North Carolina.","PeriodicalId":47724,"journal":{"name":"Communications of the Association for Information Systems","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135562145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Information Systems (IS) among other Information Technology (IT) disciplines has been concerned with student recruitment while students in secondary education have little knowledge of the field and few end up choosing it as their career. We piloted an IS-oriented entrepreneurship course in a Finnish secondary school (aged 16-19) to examine how we can change student understanding of the IS/IT field. We gathered data through observation, questionnaires, essays, and teacher interviews, and returned two years later for a follow-up inquiry on how the course lived on in the school. In this article, we examine what kind of value was created for the stakeholders and study the negotiation of meanings around the image of IS/IT by the students and the teacher. We contribute insights on the collaboration that serves as a form of marketing of IS education and point to factors that can affect the continued existence of this kind of course.
{"title":"Increasing Secondary Education Students’ Understanding of the Information Systems Field","authors":"Fanny Vainionpää, Netta Iivari, Marianne Kinnula, Heidi Hartikainen, Joni Rajala","doi":"10.17705/1cais.05323","DOIUrl":"https://doi.org/10.17705/1cais.05323","url":null,"abstract":"Information Systems (IS) among other Information Technology (IT) disciplines has been concerned with student recruitment while students in secondary education have little knowledge of the field and few end up choosing it as their career. We piloted an IS-oriented entrepreneurship course in a Finnish secondary school (aged 16-19) to examine how we can change student understanding of the IS/IT field. We gathered data through observation, questionnaires, essays, and teacher interviews, and returned two years later for a follow-up inquiry on how the course lived on in the school. In this article, we examine what kind of value was created for the stakeholders and study the negotiation of meanings around the image of IS/IT by the students and the teacher. We contribute insights on the collaboration that serves as a form of marketing of IS education and point to factors that can affect the continued existence of this kind of course.","PeriodicalId":47724,"journal":{"name":"Communications of the Association for Information Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135502495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AgriMitr was a tech-savvy start-up situated in Bengaluru, the Silicon Valley of India. It was a subsidiary of KnowThyData (KTD), a Data Science and Analytics firm, a leading data science firm providing myriad solutions to many clients. AgriMitr was established by the founder and CEO of KTD, Dr. Jishu Bose, to develop products using satellite imagery and data science. AgriMitr developed a mobile and web application that helped farmers and other key stakeholders understand crop health, soil fertility and other critical factors related to agriculture by machine learning algorithms using satellite images. The app was a major leap of innovation in the Indian Agri-Tech space. The app was to be used majorly by farmers based in rural India, and thus the major challenge lay in spreading awareness, adoption, and usage of the app. The app, if appropriately deployed, would be an imminent milestone in sustainable food production and consumption and can aid in taking a step forward in solving the world hunger problem, an SDG of the UN. Dr. Bose was planning the strategy for AgriMitr’s mass adoption and implementation with the help of Mr. Madhav A. Ram. The much-awaited meeting with investors and key stakeholders was just one week away. Madhav, under the guidance of Dr. Bose, had to prepare a roadmap and his game plan for the next year to bring this wave of change and large-scale digital adoption among the farmers of India.
AgriMitr是一家技术娴熟的初创公司，位于印度硅谷班加罗尔。它是KnowThyData (KTD)的子公司，KnowThyData是一家数据科学和分析公司，是一家领先的数据科学公司，为许多客户提供无数解决方案。AgriMitr由KTD的创始人兼首席执行官Jishu Bose博士成立，旨在开发使用卫星图像和数据科学的产品。AgriMitr开发了一个移动和网络应用程序，通过使用卫星图像的机器学习算法，帮助农民和其他关键利益相关者了解作物健康、土壤肥力和其他与农业相关的关键因素。这款应用是印度农业科技领域创新的一次重大飞跃。这款应用程序的主要用户是印度农村的农民，因此主要的挑战在于传播这款应用程序的意识、采用和使用。如果应用程序得到适当部署，它将成为可持续粮食生产和消费的一个即将到来的里程碑，并有助于在解决世界饥饿问题方面向前迈进一步，这是联合国的可持续发展目标。Bose博士在Madhav A. Ram先生的帮助下为AgriMitr的大规模采用和实施制定了战略。与投资者和主要利益相关者期待已久的会议只有一周的时间了。在Bose博士的指导下，Madhav必须为下一年准备一个路线图和他的游戏计划，以便在印度农民中带来这一波变革和大规模的数字应用。
{"title":"AgriMitr: Digitalizing the Agricultural Landscape with Satellite Imaging","authors":"Amol S. Dhaigude, Riju Ghosh","doi":"10.17705/1cais.05251","DOIUrl":"https://doi.org/10.17705/1cais.05251","url":null,"abstract":"AgriMitr was a tech-savvy start-up situated in Bengaluru, the Silicon Valley of India. It was a subsidiary of KnowThyData (KTD), a Data Science and Analytics firm, a leading data science firm providing myriad solutions to many clients. AgriMitr was established by the founder and CEO of KTD, Dr. Jishu Bose, to develop products using satellite imagery and data science. AgriMitr developed a mobile and web application that helped farmers and other key stakeholders understand crop health, soil fertility and other critical factors related to agriculture by machine learning algorithms using satellite images. The app was a major leap of innovation in the Indian Agri-Tech space. The app was to be used majorly by farmers based in rural India, and thus the major challenge lay in spreading awareness, adoption, and usage of the app. The app, if appropriately deployed, would be an imminent milestone in sustainable food production and consumption and can aid in taking a step forward in solving the world hunger problem, an SDG of the UN. Dr. Bose was planning the strategy for AgriMitr’s mass adoption and implementation with the help of Mr. Madhav A. Ram. The much-awaited meeting with investors and key stakeholders was just one week away. Madhav, under the guidance of Dr. Bose, had to prepare a roadmap and his game plan for the next year to bring this wave of change and large-scale digital adoption among the farmers of India.","PeriodicalId":47724,"journal":{"name":"Communications of the Association for Information Systems","volume":"259 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136138024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anne Kristin S. Ajer, Eli Hustad, Dag H. Olsen, Polyxeni Vassilakopoulou
Enterprise architecture (EA) is a systematic approach used for designing and implementing changes in technological systems and processes to improve organizational performance and align technology with business. This paper unpacks the process through which EA moves from strategic-level endorsement to diffusion across organizations. The insights provided are based on a longitudinal case study within the Norwegian hospital sector. An institutional work lens is adopted to analyze the purposeful activities carried out to introduce EA in Norwegian hospitals providing a granular view on diffusion. The paper provides a rich description of the institutional work employed by the key actors involved mapping them to different turns in EA’s trajectory. Drawing from this analysis, we contribute to Information Systems literature with a conceptual model that illustrates how institutional work can mitigate the challenges of moving from the strategic-level endorsement of novelty to its diffusion and institutionalization smoothing downturns along the way. The findings indicate ways to facilitate the introduction of EA within complex organizations, providing insights for practitioners involved in EA initiatives, and advancing extant EA research through an institutional perspective.
{"title":"Institutional Work for Enterprise Architecture","authors":"Anne Kristin S. Ajer, Eli Hustad, Dag H. Olsen, Polyxeni Vassilakopoulou","doi":"10.17705/1cais.05311","DOIUrl":"https://doi.org/10.17705/1cais.05311","url":null,"abstract":"Enterprise architecture (EA) is a systematic approach used for designing and implementing changes in technological systems and processes to improve organizational performance and align technology with business. This paper unpacks the process through which EA moves from strategic-level endorsement to diffusion across organizations. The insights provided are based on a longitudinal case study within the Norwegian hospital sector. An institutional work lens is adopted to analyze the purposeful activities carried out to introduce EA in Norwegian hospitals providing a granular view on diffusion. The paper provides a rich description of the institutional work employed by the key actors involved mapping them to different turns in EA’s trajectory. Drawing from this analysis, we contribute to Information Systems literature with a conceptual model that illustrates how institutional work can mitigate the challenges of moving from the strategic-level endorsement of novelty to its diffusion and institutionalization smoothing downturns along the way. The findings indicate ways to facilitate the introduction of EA within complex organizations, providing insights for practitioners involved in EA initiatives, and advancing extant EA research through an institutional perspective.","PeriodicalId":47724,"journal":{"name":"Communications of the Association for Information Systems","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136373271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"MaCuDE IS Task Force Phase II Report: Views of Industry Leaders on Big Data Analytics and AI","authors":"K. Lyytinen, H. Topi, Jing Tang","doi":"10.17705/1cais.05217","DOIUrl":"https://doi.org/10.17705/1cais.05217","url":null,"abstract":"","PeriodicalId":47724,"journal":{"name":"Communications of the Association for Information Systems","volume":"144 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74247897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Classroom teaching has been undergoing a digital transformation in the last decade and is now being amplified by Educational Key Opinion Leaders (Edu-KOLs). This research aims to investigate the relationship between learners’ perceived outcomes, motivation, and the selection preferences of Edu-KOLs. This paper presents insights gained from a two-phase study. We conducted research in the first phase through an online questionnaire completed by 186 parents in China whose children are studying or have recently studied online. In the second phase, we interviewed parents to deep dive into their thinking process behind their choices of Edu-KOLs. By utilizing the PLS-SEM method, this research has proposed and verified six hypotheses asserting that e-learning platforms, student engagement scores, and perceived outcomes strongly correlate with the perception of Edu-KOLs. However, parents’ educational level or occupation has less impact on the choices of Edu-KOLs. There are also positive relationships among Edu-KOLs, customer advocacy, and future purchase intention.
{"title":"Children’s E-Learning Interactions and Perceived Outcomes with Educational Key Opinion Leaders in China","authors":"Susan Zhang, Jun Shen, Jun Yan","doi":"10.17705/1cais.05317","DOIUrl":"https://doi.org/10.17705/1cais.05317","url":null,"abstract":"Classroom teaching has been undergoing a digital transformation in the last decade and is now being amplified by Educational Key Opinion Leaders (Edu-KOLs). This research aims to investigate the relationship between learners’ perceived outcomes, motivation, and the selection preferences of Edu-KOLs. This paper presents insights gained from a two-phase study. We conducted research in the first phase through an online questionnaire completed by 186 parents in China whose children are studying or have recently studied online. In the second phase, we interviewed parents to deep dive into their thinking process behind their choices of Edu-KOLs. By utilizing the PLS-SEM method, this research has proposed and verified six hypotheses asserting that e-learning platforms, student engagement scores, and perceived outcomes strongly correlate with the perception of Edu-KOLs. However, parents’ educational level or occupation has less impact on the choices of Edu-KOLs. There are also positive relationships among Edu-KOLs, customer advocacy, and future purchase intention.","PeriodicalId":47724,"journal":{"name":"Communications of the Association for Information Systems","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135105714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this tutorial, the issue of compatibility between a big data storage technology and an analytic workload is explored using a fictitious streaming company as an example. The tutorial offers an interactive approach to help students understand the importance of considering workload compatibility when adopting new technologies. We provide instructors with the following: two Jupyter Notebooks that analyze compatibility, a detailed instructor guide on how to execute these notebooks, lessons learned, and appendices containing solutions and explanations. This tutorial provides a valuable resource for instructors teaching courses in database systems, big data, and analytic concepts, helping students develop practical skills to navigate effectively the complexities of big data technologies.
{"title":"Navigating Workload Compatibility Between a Recommender System and a NoSQL Database: An Interactive Tutorial","authors":"Varol O. Kayhan, Donald J. Berndt","doi":"10.17705/1cais.05327","DOIUrl":"https://doi.org/10.17705/1cais.05327","url":null,"abstract":"In this tutorial, the issue of compatibility between a big data storage technology and an analytic workload is explored using a fictitious streaming company as an example. The tutorial offers an interactive approach to help students understand the importance of considering workload compatibility when adopting new technologies. We provide instructors with the following: two Jupyter Notebooks that analyze compatibility, a detailed instructor guide on how to execute these notebooks, lessons learned, and appendices containing solutions and explanations. This tutorial provides a valuable resource for instructors teaching courses in database systems, big data, and analytic concepts, helping students develop practical skills to navigate effectively the complexities of big data technologies.","PeriodicalId":47724,"journal":{"name":"Communications of the Association for Information Systems","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135610727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bastin Tony Roy Savarimuthu, Jacqueline Corbett, Muhammad Yasir, Vijaya Lakshmi
Big data are key building blocks for creating information value. However, information systems are increasingly plagued with useless, waste data that can impede their effective use and threaten sustainability objectives. Using a constructive design science approach, this work first, defines digital data waste. Then, it develops an ensemble artifact comprising two components. The first component comprises 13 machine learning models for detecting data waste. Applying these to 35,576 online reviews in two domains reveals data waste of 1.9% for restaurant reviews compared to 35.8% for app reviews. Machine learning can accurately identify 83% to 99.8% of data waste; deep learning models are particularly promising, with accuracy ranging from 96.4% to 99.8%. The second component comprises a sustainability cost calculator to quantify the social, economic, and environmental benefits of reducing data waste. Eliminating 5948 useless reviews in the sample would result in saving 6.9 person hours, $2.93 in server, middleware and client costs, and 9.52 kg of carbon emissions. Extrapolating these results to reviews on the internet shows substantially greater savings. This work contributes to design knowledge relating to sustainable information systems by highlighting the new class of problem of data waste and by designing approaches for addressing this problem.
{"title":"Improving Information Systems Sustainability by Applying Machine Learning to Detect and Reduce Data Waste","authors":"Bastin Tony Roy Savarimuthu, Jacqueline Corbett, Muhammad Yasir, Vijaya Lakshmi","doi":"10.17705/1cais.05308","DOIUrl":"https://doi.org/10.17705/1cais.05308","url":null,"abstract":"Big data are key building blocks for creating information value. However, information systems are increasingly plagued with useless, waste data that can impede their effective use and threaten sustainability objectives. Using a constructive design science approach, this work first, defines digital data waste. Then, it develops an ensemble artifact comprising two components. The first component comprises 13 machine learning models for detecting data waste. Applying these to 35,576 online reviews in two domains reveals data waste of 1.9% for restaurant reviews compared to 35.8% for app reviews. Machine learning can accurately identify 83% to 99.8% of data waste; deep learning models are particularly promising, with accuracy ranging from 96.4% to 99.8%. The second component comprises a sustainability cost calculator to quantify the social, economic, and environmental benefits of reducing data waste. Eliminating 5948 useless reviews in the sample would result in saving 6.9 person hours, $2.93 in server, middleware and client costs, and 9.52 kg of carbon emissions. Extrapolating these results to reviews on the internet shows substantially greater savings. This work contributes to design knowledge relating to sustainable information systems by highlighting the new class of problem of data waste and by designing approaches for addressing this problem.","PeriodicalId":47724,"journal":{"name":"Communications of the Association for Information Systems","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136207039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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