{"title":"Recent Developments in PLS","authors":"Jöerg Evermann, Mikko Rönkkö","doi":"10.17705/1cais.05229","DOIUrl":"https://doi.org/10.17705/1cais.05229","url":null,"abstract":"","PeriodicalId":47724,"journal":{"name":"Communications of the Association for Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135686452","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}
Climate change is now affecting every known society. Small-scale farmers in low-income countries are especially vulnerable to climate change because they depend heavily on rain, seasonality patterns, and known temperature ranges. Prioritizing the efforts of building climate change resilience and adaptive capacity for small-scale farmers is essential in achieving Sustainable Development Goals 13, 1, and 2. An important first step towards those efforts is to assess the climate change vulnerability among the population. We propose a Climate Change Vulnerability Assessment Framework Design Framework (CCVA-DF) to guide the design of innovative digital CCVA solutions to enhance the adaptive capacity and climate change resilience of small-scale farmers. The framework outlines modern methods for vulnerability data collection and processing through Remote Sensing and GIS, advanced spatial analysis and modeling for measuring vulnerabilities, and visual analytics to support decision-making in the planning and implementation of suitable interventions. The framework is instantiated into a web application that is used by a real-world organization for transforming household resilience in Western Honduras. The CCVA-DF showcases novel measures of vulnerability using geospatial technology. It provides guidelines to design digital vulnerability assessment tools that can be used by researchers and practitioners worldwide to tackle climate change challenges.
{"title":"A Climate Change Vulnerability Assessment Design Framework: The Case of Small-scale Farmers in Western Honduras","authors":"Yan Li, Claudia Caceres, Ali Mohammed Bazarah","doi":"10.17705/1cais.05304","DOIUrl":"https://doi.org/10.17705/1cais.05304","url":null,"abstract":"Climate change is now affecting every known society. Small-scale farmers in low-income countries are especially vulnerable to climate change because they depend heavily on rain, seasonality patterns, and known temperature ranges. Prioritizing the efforts of building climate change resilience and adaptive capacity for small-scale farmers is essential in achieving Sustainable Development Goals 13, 1, and 2. An important first step towards those efforts is to assess the climate change vulnerability among the population. We propose a Climate Change Vulnerability Assessment Framework Design Framework (CCVA-DF) to guide the design of innovative digital CCVA solutions to enhance the adaptive capacity and climate change resilience of small-scale farmers. The framework outlines modern methods for vulnerability data collection and processing through Remote Sensing and GIS, advanced spatial analysis and modeling for measuring vulnerabilities, and visual analytics to support decision-making in the planning and implementation of suitable interventions. The framework is instantiated into a web application that is used by a real-world organization for transforming household resilience in Western Honduras. The CCVA-DF showcases novel measures of vulnerability using geospatial technology. It provides guidelines to design digital vulnerability assessment tools that can be used by researchers and practitioners worldwide to tackle climate change challenges.","PeriodicalId":47724,"journal":{"name":"Communications of the Association for Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135956734","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}
Many companies use the UN Sustainable Development Goals as a point of reference for their sustainability initiatives and actions. Reporting on these goals requires collecting, processing, and interpreting substantial amounts of data (e.g., on emissions or recycled materials) that were previously neither captured nor analyzed. Although prior studies have occasionally highlighted the issues of data availability, data access, and data quality, a research void prevails on the data perspective in the sustainability context. This article aims at developing this perspective by shedding light on data sourcing practices for the reliable reporting of sustainability initiatives and goals. We make a two-fold contribution to sustainability and Green IS research: First, as a theoretical contribution, we propose a framework based on institutional theory to explain how companies develop their data sourcing practices in response to regulatory, normative, and cultural-cognitive pressures. Second, our empirical contributions include insights into five case studies that represent key initiatives in the field of environmental sustainability that touch on, first, understanding the ecological footprint, and, second, obtaining labels or complying with regulations, both on product and packaging levels. Based on five case studies, we identify three data sourcing practices: sense-making, data collection, and data reconciliation. Thereby, our research lays the foundation for an academic conceptualization of data sourcing in the context of sustainability.
{"title":"Introducing a Data Perspective to Sustainability: How Companies Develop Data Sourcing Practices for Sustainability Initiatives","authors":"Pavel Krasikov, Christine Legner","doi":"10.17705/1cais.05307","DOIUrl":"https://doi.org/10.17705/1cais.05307","url":null,"abstract":"Many companies use the UN Sustainable Development Goals as a point of reference for their sustainability initiatives and actions. Reporting on these goals requires collecting, processing, and interpreting substantial amounts of data (e.g., on emissions or recycled materials) that were previously neither captured nor analyzed. Although prior studies have occasionally highlighted the issues of data availability, data access, and data quality, a research void prevails on the data perspective in the sustainability context. This article aims at developing this perspective by shedding light on data sourcing practices for the reliable reporting of sustainability initiatives and goals. We make a two-fold contribution to sustainability and Green IS research: First, as a theoretical contribution, we propose a framework based on institutional theory to explain how companies develop their data sourcing practices in response to regulatory, normative, and cultural-cognitive pressures. Second, our empirical contributions include insights into five case studies that represent key initiatives in the field of environmental sustainability that touch on, first, understanding the ecological footprint, and, second, obtaining labels or complying with regulations, both on product and packaging levels. Based on five case studies, we identify three data sourcing practices: sense-making, data collection, and data reconciliation. Thereby, our research lays the foundation for an academic conceptualization of data sourcing in the context of sustainability.","PeriodicalId":47724,"journal":{"name":"Communications of the Association for Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136208060","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 2022, we launched a call for papers for a special section on digital innovation for social development and environmental action. The call was motivated by the need for the information systems discipline to move beyond talking about sustainability to taking actions to address important challenges facing society and the planet. Many authors responded to the call and we are pleased to present the fruits of their labors. In this introduction to the special section, we discuss the motivations for the special section, explain how the special section came together, highlight key points of interest in the eight papers that make up the special section, and reflect on future directions for information systems research.
{"title":"Introduction to the Special Section: Digital Innovation for Social Development and Environmental Action","authors":"Jacqueline Corbett, Denis Dennehy, Lemuria Carter","doi":"10.17705/1cais.05302","DOIUrl":"https://doi.org/10.17705/1cais.05302","url":null,"abstract":"In 2022, we launched a call for papers for a special section on digital innovation for social development and environmental action. The call was motivated by the need for the information systems discipline to move beyond talking about sustainability to taking actions to address important challenges facing society and the planet. Many authors responded to the call and we are pleased to present the fruits of their labors. In this introduction to the special section, we discuss the motivations for the special section, explain how the special section came together, highlight key points of interest in the eight papers that make up the special section, and reflect on future directions for information systems research.","PeriodicalId":47724,"journal":{"name":"Communications of the Association for Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135913643","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 historical perspective, I share my thoughts and experiences working with companies to engage and support academic research. I show the process from finding the right topic to deciding when it is time to move on to something new. As I go through my experiences, I will introduce 10 lessons learned to help in your research efforts. I also introduce three example professors who operate in different academic environments, have different academic and personal goals, and take different paths in working with the business community. I close by exploring the four evolutionary stages of academic IS research. The latest stage, big data/machine learning/artificial intelligence, offers new opportunities for engaging the business community, as well as impacting what academic IS research is and how it is conducted.
{"title":"Reflections on Engaging the Business Community to Support Academic Research","authors":"Hugh J. Watson","doi":"10.17705/1cais.05318","DOIUrl":"https://doi.org/10.17705/1cais.05318","url":null,"abstract":"In this historical perspective, I share my thoughts and experiences working with companies to engage and support academic research. I show the process from finding the right topic to deciding when it is time to move on to something new. As I go through my experiences, I will introduce 10 lessons learned to help in your research efforts. I also introduce three example professors who operate in different academic environments, have different academic and personal goals, and take different paths in working with the business community. I close by exploring the four evolutionary stages of academic IS research. The latest stage, big data/machine learning/artificial intelligence, offers new opportunities for engaging the business community, as well as impacting what academic IS research is and how it is conducted.","PeriodicalId":47724,"journal":{"name":"Communications of the Association for Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135213120","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}
Rosetta Romano, Blooma John, Dale MacKrell, Sumaira Qureshi, Wayne Applebee, Peter Copeman
In the context of an institution-wide initiative of the University of Canberra (UC), Australia, to mandate the Indigenization of the curriculum in all its courses, this descriptive case study reports on a pilot project to redesign the syllabus of an Information Technology (IT) unit that is a mandatory capstone for all students undertaking IT degrees. The capstone previously included no Indigenous-related content or pedagogical approaches. Indigenizing of the unit was achieved by embedding and interconnecting Tyson Yunkaporta’s (2009) 8 Ways of Indigenous Learning with the unit's content, teaching methods, and assessments, along with the Indigenous collaborative learning method Yarning Circles, in a design that could be expressed and unified in the teaching delivery to inform continuous adjustment and improvement of the unit’s curriculum, and also potentially inform the Indigenization of other UC IT units over time. A Design Science Research (DSR) methodology was put into action to evaluate the previous curriculum (as expressed in the offering of the unit), to design its Indigenized replacement, to implement it with student cohorts over two semesters, to collect data on the experience, and to reflect on the successes and challenges that arise. This methodology can also be applied reflexively in future iterative cycles of continuous adjustment and improvement of the unit’s curriculum by its conveners and colleagues to inform Indigenized designs for other units that currently have no Indigenous-related content. The extensibility of DSR is proffered as a methodological contribution to the project.
{"title":"Indigenizing the IT Curriculum by Design","authors":"Rosetta Romano, Blooma John, Dale MacKrell, Sumaira Qureshi, Wayne Applebee, Peter Copeman","doi":"10.17705/1cais.05315","DOIUrl":"https://doi.org/10.17705/1cais.05315","url":null,"abstract":"In the context of an institution-wide initiative of the University of Canberra (UC), Australia, to mandate the Indigenization of the curriculum in all its courses, this descriptive case study reports on a pilot project to redesign the syllabus of an Information Technology (IT) unit that is a mandatory capstone for all students undertaking IT degrees. The capstone previously included no Indigenous-related content or pedagogical approaches. Indigenizing of the unit was achieved by embedding and interconnecting Tyson Yunkaporta’s (2009) 8 Ways of Indigenous Learning with the unit's content, teaching methods, and assessments, along with the Indigenous collaborative learning method Yarning Circles, in a design that could be expressed and unified in the teaching delivery to inform continuous adjustment and improvement of the unit’s curriculum, and also potentially inform the Indigenization of other UC IT units over time. A Design Science Research (DSR) methodology was put into action to evaluate the previous curriculum (as expressed in the offering of the unit), to design its Indigenized replacement, to implement it with student cohorts over two semesters, to collect data on the experience, and to reflect on the successes and challenges that arise. This methodology can also be applied reflexively in future iterative cycles of continuous adjustment and improvement of the unit’s curriculum by its conveners and colleagues to inform Indigenized designs for other units that currently have no Indigenous-related content. The extensibility of DSR is proffered as a methodological contribution to the project.","PeriodicalId":47724,"journal":{"name":"Communications of the Association for Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135105715","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":"Don’t Throw the Baby Out With the Bathwater: Comments on “Recent Developments in PLS”","authors":"Daniel Russo, Klaas-Jan Stol","doi":"10.17705/1cais.05231","DOIUrl":"https://doi.org/10.17705/1cais.05231","url":null,"abstract":"","PeriodicalId":47724,"journal":{"name":"Communications of the Association for Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135182918","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}
The world is confronted with the grand challenge of food insecurity amidst growing populations and the climate crisis. Artificial intelligence (AI) deployed in agricultural decision support systems (AgriDSS) raises both hopes and concerns for increasing agricultural productivity in sustainable ways. In this paper, we conduct a scoping review to uncover the roadblocks to the use of AI-supported AgriDSS in sustainable agriculture. Based on the corpus of 121 articles, we find that the effective use of AI-supported AgriDSS is hindered at technical, social, ethical, and ecological levels. Then, drawing on the experiential learning perspective, we propose how conjoint experiential learning (CEL) can enhance sustainable agricultural practices by enhancing both AI and human learning and overcoming roadblocks in using AgriDSS. Based on this conceptual framework, we build a research agenda that suggests blind spots and possible directions for future research.
{"title":"Using AI to Improve Sustainable Agricultural Practices: A Literature Review and Research Agenda","authors":"Vijaya Lakshmi, Jacqueline Corbett","doi":"10.17705/1cais.05305","DOIUrl":"https://doi.org/10.17705/1cais.05305","url":null,"abstract":"The world is confronted with the grand challenge of food insecurity amidst growing populations and the climate crisis. Artificial intelligence (AI) deployed in agricultural decision support systems (AgriDSS) raises both hopes and concerns for increasing agricultural productivity in sustainable ways. In this paper, we conduct a scoping review to uncover the roadblocks to the use of AI-supported AgriDSS in sustainable agriculture. Based on the corpus of 121 articles, we find that the effective use of AI-supported AgriDSS is hindered at technical, social, ethical, and ecological levels. Then, drawing on the experiential learning perspective, we propose how conjoint experiential learning (CEL) can enhance sustainable agricultural practices by enhancing both AI and human learning and overcoming roadblocks in using AgriDSS. Based on this conceptual framework, we build a research agenda that suggests blind spots and possible directions for future research.","PeriodicalId":47724,"journal":{"name":"Communications of the Association for Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135956732","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}
Green information systems (green IS) have evolved and expanded over the years, now having a broad scope in organizations. Green IS in these organizations function to help to address climate change challenges. The growing complexity of green IS in organizations needs a conceptual framework that can articulate its different impacts at various levels while taking into consideration a holistic and integrated perspective. This research focuses on how to enhance and ensure green IS-driven green performance in organizations from an operant resources hierarchy perspective. A conceptual model is proposed to examine the role of management support for green initiatives and the role of information assurance in addressing IS misuse and process automation in relationship to green IS capability and green performance. The current study tests the effects of management support as composite operant resources and information assurance as interconnected operant resources for green IS capability in enhancing and ensuring organizations’ green performance using a matched dataset of 73 organizations. We illustrate the application of the proposed conceptual model in two real-world scenarios. This study contributes theoretically by illustrating the application of the operant resources hierarchy perspective in green IS research and provides practical action suggestions for organizations adopting sustainable practices to achieve Sustainable Development Goal (SDG) 13.
{"title":"The Hierarchy of Green Information Systems Capability in Organizations to Enhance and Ensure Green Performance: An Operant Resources Perspective","authors":"Xue Ning, Jiban Khuntia","doi":"10.17705/1cais.05309","DOIUrl":"https://doi.org/10.17705/1cais.05309","url":null,"abstract":"Green information systems (green IS) have evolved and expanded over the years, now having a broad scope in organizations. Green IS in these organizations function to help to address climate change challenges. The growing complexity of green IS in organizations needs a conceptual framework that can articulate its different impacts at various levels while taking into consideration a holistic and integrated perspective. This research focuses on how to enhance and ensure green IS-driven green performance in organizations from an operant resources hierarchy perspective. A conceptual model is proposed to examine the role of management support for green initiatives and the role of information assurance in addressing IS misuse and process automation in relationship to green IS capability and green performance. The current study tests the effects of management support as composite operant resources and information assurance as interconnected operant resources for green IS capability in enhancing and ensuring organizations’ green performance using a matched dataset of 73 organizations. We illustrate the application of the proposed conceptual model in two real-world scenarios. This study contributes theoretically by illustrating the application of the operant resources hierarchy perspective in green IS research and provides practical action suggestions for organizations adopting sustainable practices to achieve Sustainable Development Goal (SDG) 13.","PeriodicalId":47724,"journal":{"name":"Communications of the Association for Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136258244","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}
Gero Strobel, Thorsten Schoormann, Leonardo Banh, Frederik Möller
Although our digitalized society is able to foster social inclusion and integration, there are still numerous communities suffering from inequality. This is also the case with deaf people. About 750,000 deaf people in the European Union and over 4 million deaf people in the United States face daily challenges in terms of communication and participation. This occurs not only in leisure activities but also, and more importantly, in emergency situations. To provide equal environments and allow people with hearing handicaps to communicate in their native language, this paper presents an AI-based sign language translator. We adopted a transformer neural network capable of analyzing over 500 data points from a person’s gestures and face to translate sign language into text. We have designed a machine learning pipeline that enables the translator to evolve, build new datasets, and train sign language recognition models. As proof of concept, we instantiated a sign language interpreter for an emergency call with over 200 phrases. The overall goal is to support people with hearing inabilities by enabling them to participate in economic, social, political, and cultural life.
{"title":"Artificial Intelligence for Sign Language Translation – A Design Science Research Study","authors":"Gero Strobel, Thorsten Schoormann, Leonardo Banh, Frederik Möller","doi":"10.17705/1cais.05303","DOIUrl":"https://doi.org/10.17705/1cais.05303","url":null,"abstract":"Although our digitalized society is able to foster social inclusion and integration, there are still numerous communities suffering from inequality. This is also the case with deaf people. About 750,000 deaf people in the European Union and over 4 million deaf people in the United States face daily challenges in terms of communication and participation. This occurs not only in leisure activities but also, and more importantly, in emergency situations. To provide equal environments and allow people with hearing handicaps to communicate in their native language, this paper presents an AI-based sign language translator. We adopted a transformer neural network capable of analyzing over 500 data points from a person’s gestures and face to translate sign language into text. We have designed a machine learning pipeline that enables the translator to evolve, build new datasets, and train sign language recognition models. As proof of concept, we instantiated a sign language interpreter for an emergency call with over 200 phrases. The overall goal is to support people with hearing inabilities by enabling them to participate in economic, social, political, and cultural life.","PeriodicalId":47724,"journal":{"name":"Communications of the Association for Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135914651","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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