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Communications of the Association for Information Systems

Forthcoming Papers

Forthcoming papers have been accepted for publication at the Communications of the Association for Information Systems and are listed below in order of acceptance date. Copies of unedited manuscripts can either be obtained by clicking the manuscript title or contacting the corresponding authors listed below.

Note that the decision to provide a copy rests with the authors, not with the Communications of the Association for Information Systems.

The manuscripts listed here will undergo copyediting, typesetting, and review of the resulting proofs before they are published in their final form. During the production process errors may be discovered, which could affect the content. All legal disclaimers that apply to the Communications of the Association for Information Systems pertain. For a definitive version of the works listed here, please check for their appearance online at http://aisel.aisnet.org/cais/.



Actions Lead to Results: How the Behaviors of Information Systems Professionals Influence the Success of Information Systems Departments

Karimikia, Hadi (hadi.karimikia@mu.ie)

Abstract

The growing complexity of systems, the increasing intensity of their use, and the greater prominence of technology in supporting organizational activities has meant that information systems (IS) professionals in organizations have to go beyond offering routine task-related support when working with their non-IS colleagues. To be seen as being effective, IS professionals have to carry out empathic behaviors such as sharing their IT knowledge with their non-IS colleagues and taking the initiative to minimize inconveniences during IS projects. Drawing from the concept of organizational citizenship behavior, we develop a multilevel research model to examine how behaviors performed by IS professionals influence the effectiveness of IS departments. Using data from more than 1,000 respondents working in the global finance industry, the results of both cross-level and unit-level analyses support our arguments. The results deepen our understanding of the role of IS professionals as being intimately involved in supporting post-adoption IS use and digitally empowering business units, while also performing their traditional roles.



When to Use Machine Learning: A Course Project

Kayhan, Varol (vkayhan@usf.edu)

Abstract

The number of institutions offering machine learning courses is on the rise. Supplementary materials that help teach these courses fail to address one of the most important steps of the machine learning process, namely identifying a problem, and determining whether it is appropriate for machine learning. We address this problem by first reviewing frameworks in extant work, then proposing a decision flow to help students determine whether an input-output relationship is appropriate for machine learning. Following the discussion of the steps in the decision flow, we present a course assignment that reinforces the concepts in the decision flow. We conclude by discussing the lessons learned after using this assignment in a graduate class.



Partial least squares is an estimator for structural equation models: A comment on Evermann and Rönkkö (2021)

Schuberth, Florian (f.schuberth@utwente.nl)

Abstract

In 2012 and 2013, several critical publications questioned many alleged PLS properties. As a consequence, PLS benefited from a boost of developments. It is, therefore, a good time to review these developments. Evermann and R¨onkk¨o devote their paper to this task and formulate guidelines in the form of 14 recommendations. Yet, while they identified the major developments, they overlook a fundamental change, maybe because it is so subtle: The view on PLS. As mentioned by Evermann and R¨onkk¨o (2021, p. 1), “[PLS] is a statistical method used to estimate linear structural equation models” and consequently should not be regarded as a standalone SEM technique following its own assessment criteria. Against this background, we explain which models can be estimated by PLS and PLSc. Moreover, we present the Henseler-Ogasawara specification to estimate composite models by common SEM estimators. Additionally, we review Evermann and R¨onkk¨o’s 14 recommendations one by one and suggest updates and improvements where necessary. Further, we address Evermann and R¨onkk¨o’s comments about the latest advancement in composite models and show that PLS is a viable estimator for confirmatory composite analysis. Finally, we conclude that there is little value in distinguishing between covariance-based and variance-based SEM – there is only SEM.



Contributing to the success of PLS in SEM: An action research perspective

Kock, Ned (nedkock@tamiu.edu)

Abstract

We share with Evermann & Rönkkö (2021) the belief that classic composite-based partial least squares path modeling (PLS-PM) presents shortcomings when used to conduct structural equation modeling (SEM) analyses. The shortcomings can be traced back to one fundamental problem, which is that latent variables (LVs) are approximated in PLS-PM as exact linear combinations of their corresponding indicators. In SEM, each LV is in fact a factor; i.e., a linear combination of the indicators and a measurement residual. Our approach to addressing the shortcomings of PLS-PM is rather unique among researchers concerned with quantitative methods. We have employed an action research approach, helping investigators employ SEM in their empirical studies. This has led to our development of a widely used software tool for SEM analyses. We illustrate our action research orientation by discussing three recent methodological developments with which we have been closely involved.



Don’t Throw the Baby Out With the Bathwater: Comments on “Recent Developments in PLS”

Russo, Daniel (daniel.russo@cs.aau.dk)

Abstract

Evermann and Rönkkö aim to present an overview of recent advances in PLS, and while some advances are described with several useful recommendations, we argue that their article does not fully deliver on its promise. In this response, we argue that their position presents an unbalanced view, ignores several methodological advances by IS scholars. We note that several recommendations are so stringent that implementing that there are philosophical and practical differences that are insufficiently taken into account. Further, several studies that highlight the shortcomings of PLS seem to be based on specially designed cases that are not necessarily representative of typical use of PLS. In our response, we call for a more balanced debate that takes into consideration different perspectives and that studies of the performance of PLS are conducted fairly. While we do not disagree with E&R’s recommendations, the implementation of those is challenged by a lack of tool support, and we observe that besides scholars using PLS, editors and reviewers also have a responsibility to be cognizant of methodological advances. We commend E&R for their efforts in studying the limitations of PLS which have spurred several methodological advances, but also caution that we should not ‘throw the baby out with the bathwater,” by discarding PLS for its known limitations.



Needed Developments in the Understanding of Quasi-Factor Methods

Rigdon, Edward (erigdon@gsu.edu)

Abstract

This response to Evermann and Rönkkö (this issue) acknowledges areas of agreement regarding application of partial least squares (PLS) path modeling, but cites substantial disagreements. Researchers are encouraged to also consider generalized structured component analysis and regression component analysis as procedures built around weighted composites rather than common factors. All of these methods are best regarded as quasi-factor methods, which avoid the uncertainty of factor indeterminacy though they still rely on covariance structures similar to those in factor analysis. They remain useful tools for the researcher.



Extraordinary claims require extraordinary evidence: A comment on “recent developments in PLS”

Sarstedt, Marko (sarstedt@lmu.de)

Abstract

Evermann and Rönkkö (2021) review recent developments in partial least squares (PLS) with the aim of providing guidance to researchers. Indeed, the explosion of methodological advances in PLS in the last decade necessitates such overview articles. In so far as the goal is to provide an objective assessment of the technique, such articles are most welcome. Unfortunately, the authors’ extraordinary and questionable claims paint a misleading picture of PLS. Our goal in this short commentary is to address selected claims made by ER using simulations and latest research. Our objective is to bring a positive perspective to this debate and highlight the recent developments in PLS that make it an increasingly valuable technique in IS and management research in general.



Comments on Evermann and Rönkkö (2021): Recent Developments in PLS

Thompson, Ron (thompsrl@wfu.edu)

Abstract

Evermann and Rönkkö (2022) have provided an excellent overview of recent findings relating to the use of Partial Least Squares (PLS). Their overall message is that if researchers decide to use PLS, they need to ensure that they follow best practices to reduce the possibility of obtaining misleading or erroneous results. We generally agree with their assessment, but go further to recommend against the use of PLS. We demonstrate exactly how PLS introduces biases, arguing that the algorithm violates accepted norms for statistical inference. Our final recommendation is for the Editors-in-Chief of top IS research journals to convene a task force to assess the advisability of continuing to accept articles where PLS is used for publication in IS journals.



AIS4C - AIS Candid Conversation on Community Conduct: Panel Report from ICIS 2020

Zinner Henriksen, Helle (hzh.digi@cbs.dk)

Abstract

This report reflects the discussion that took place at a virtual panel at the ICIS 2020 conference. It focuses on a candid conversation on code of conduct (AIS4C) among AIS community members. As our AIS community has evolved, we have grown in size, diversity, and in the scope of member needs, it is important for all stakeholders to understand what is expected as members of this academic community. The panel included those currently serving in AIS committees related to member and research conduct. The objective of the panel was to start a dialogue about what we – as members of the AIS – each hope to gain from our academic interactions, how AIS can help members achieve these goals and help each other achieve desired outcomes. Maintaining good standing in the AIS community protects individuals’ professional reputations and the reputation of the IS discipline as a whole. Understanding what AIS offers its members to accomplish these objectives, allows individuals to leverage fully AIS member services to become more successful researchers and teachers. By situating the panel within the current COVID-disrupted world, the descriptions of desirable behavior among members and the outlining of member services, this panel report is intended to benefit current and future members of AIS.



Artificial Intelligence and Machine Learning in Cybersecurity: Applications, Challenges, and Opportunities for MIS Academics

Sen, Ravi (ravisen@tamu.edu)

Abstract

Availability of massive amounts of data, fast computers, and superior machine learning (ML) algorithms has spurred interest in artificial intelligence (AI). It is no surprise, then, that we observe an increase in the application of AI in cybersecurity. Our survey of AI applications in cybersecurity shows most of the present applications are in the areas of malware identification and classification, intrusion detection, and cybercrime prevention. We should, however, be aware that AI-enabled cybersecurity is not without its drawbacks. Challenges to AI solutions include a shortage of good quality data to train machine learning models, the potential for exploits via adversarial AI/ML, and limited human expertise about AI. However, the rewards in terms of increased accuracy of cyberattack predictions, faster response to cyberattacks, and improved cybersecurity make it worthwhile to overcome these challenges. We present a summary of current research on the application of AI and ML to improve cybersecurity, challenges that need to be overcome, and research opportunities for academics in management information systems.



Contextualizing self-disclosure to the online environment: An assessment of the literature

Nabity-Grover, Teagen (teagennabitygrov@boisestate.edu)

Abstract

Online self-disclosure – any message about the self that one person communicates to another – has been studied for nearly two decades. Self-disclosure research started with the study of face-to-face interactions within the communications and psychology disciplines and expanded to study communicative behaviors online in many disciplines, including Information Systems. This paper develops a framework to evaluate how effectively self-disclosure measures are contextualized to the online environment. To do so, we review the multidisciplinary literature of online self-disclosure, analyze online self-disclosure measures, and evaluate their degree of contextualization to online interactions. We find inconsistent measurement of online self-disclosure and reported results across studies. Based on our analysis, we provide recommendations for improving the contextualization and measurement of self-disclosure in online environments, including reconceptualizing the dimension of intent, improving the quality of existing instruments, and identifying context-specific dimensions to address the unique features of online communication.



Recent Developments in PLS

Evermann, Joerg (jevermann@mun.ca)

Abstract

Partial Least Squares path modeling (PLS) is a method for estimating linear structural equation models. Widely used in the information systems (IS) discipline, there has been considerable argument over its relative merits compared to simple summed scores or to covariance-based estimation of structural equation models. This paper comments on recent developments in PLS to ensure that IS researchers have up-to-date methodological knowledge and best practices if they decide to use PLS. The paper briefly reviews the mechanisms of PLS, its well-known properties of PLS, and its usage history in IS research. We briefly revisit a high-impact critique and debate a few years ago to identify the critical arguments around current practices and use of PLS. That critique proved the driver for many advances in the field, which are discussed extensively and used to make 14 recommendations for how and when to use PLS or alternatives.



Mixed-Methods in Information Systems Research: Status Quo, Core Concepts, and Future Research Implicationss

Reis, Lea (lea.reis@uni-bamberg.de)

Abstract

Mixed-methods studies are on the rise in information systems (IS) research, as they deliver robust and insightful inferences combining qualitative and quantitative research. However, there is much divergence in conducting such studies and reporting their findings. Therefore, we aim (1) to evaluate how mixed-methods studies have developed in information systems (IS) research under the existence of heavily used guidelines presented by Venkatesh et al. (2013) and (2) to reflect on those observations in terms of potentials for future research. During our review, we identified 52 mixed-methods papers and quantitatively elaborated the adherence to the three core concepts of mixed-methods in terms of purpose, meta-inferences, and validation. Findings discover that only eight adhere to all three of them. We discuss the significance of our results for current and upcoming mixed-methods research and derive specific suggestions for authors. With our study, we contribute to mixed-methods research by showing how to leverage the insights from existing guidelines to strengthen future research and by contributing to the discussion of the legislation associated with research guidelines, in general, presenting the status quo in current literature.



Ethics and AI in Information Systems Research

Mirbabaie, Milad (milad.mirbabaie@uni-paderborn.de)

Abstract

The ethical dimensions of Artificial Intelligence (AI) constitute a salient topic in information systems (IS) research and beyond. There is an increasing number of journal and conference articles on how AI should be designed and used. For this, IS research offers and curates knowledge not only on the ethical dimensions of information technologies but also on their acceptance and impact. However, the current discourse on the ethical dimensions of AI is highly unstructured and seeks clarity. As conventional systematic literature research has been criticized for lacking in performance, we applied an adapted discourse approach to identify the most relevant articles within the debate. As the fundamental manuscripts within the discourse were not obvious, we used a weighted citation-based technique to identify fundamental manuscripts and their relationships within the field of AI ethics across disciplines. Starting from an initial sample of 175 papers, we extracted and further analyzed 12 fundamental manuscripts and their citations. Although we found many similarities between traditionally curated ethical principles and the identified ethical dimensions of AI, no IS paper could be classified as fundamental to the discourse. Therefore, we derived our own ethical dimensions on AI and provided guidance for future IS research.



Trends in FinTech Research and Practice: Examining the Intersection with the Information Systems Field

Marrone, Mauricio (mauricio.marrone@mq.edu.au)

Abstract

This paper offers a systematic review of academic and practitioner-oriented literature on FinTech to determine the literature's existing scope and examine the intersection with work in the Information Systems (IS) field. Findings from our review show that the practitioner-oriented literature foreshadowed the rise of FinTech by extensively reporting on algorithm-based and electronic trading (2009 onwards), followed by reporting on FinTech start-ups and funding successes (2014 onwards). The practitioner literature subsequently reported on alternative finance models, the introduction of cryptocurrencies, and risks and regulatory issues. Academic literature on FinTech began to rise from 2014 onwards, focusing initially on the development of FinTech in the aftermath of the 2007-2008 global financial crisis. Research attention subsequently shifted to FinTech innovations (alternative finance, cryptocurrency and blockchain, machine-based methods for financial analysis and forecasting, including artificial intelligence), as well as risk and regulatory issues. IS work on FinTech started to emerge from 2015 onwards, initially focusing on mobile payment systems and peer-to-peer lending. However, the body of work at the intersection of FinTech and IS is still small. Our review sheds light on several opportunities for future research, including financial inclusion, the impacts arising from COVID-19, and the emergence of new business models, such as Banking as a Service (BaaS).



Becoming a most digitalized country: A history of digital organizational resilience in Denmark

Fleron, Benedicte (bff@ruc.dk)

Abstract

The purpose of this paper is to demonstrate how digital organizational resilience was a key to digital transformation success in the public sector of Denmark. Using a historical research method, we analyze the IS history from 1998-2019 at all three levels of the public sector in Denmark. This study finds historical events about barriers and hindrances and shows how resilience enabled a continuity in the transformation. From significant events in the history of Denmark becoming a digitalized nation, we find a pattern of what constitutes digital organizational resilience in e-government: first, new ways to strategize digitalization, second, collaborative strategy execution across the public sector that envelopes the ability to learn from overcoming barriers and hindrances, and third, an organizational resilience path that iterates action, collaboration, and learning. Digital resilience has previously been studied in the context of individual learning and cyber security. The pattern found in the historical account is a promising basis for understanding and achieving resilience in a transformative digitalization strategy in the public sector.



Synergistically Employing User Stories and Use Cases in the Practice and Teaching of Systems Analysis and Design

Spurrier, Gary (gspurrier@cba.ua.edu)

Abstract

Over the past three decades, user stories and use cases have become increasingly dominant requirements techniques. Both support articulating functional requirements for software projects, although they evolved within different software development approaches—user stories from agile development and use cases from traditional software engineering—and differ significantly in the level of requirements detail they can capture. As such, user stories and use cases are neither synonyms nor mutually exclusive alternatives. Rather, they can and should be complementary in the systems requirements process. Unfortunately, this mix of similarities and differences—coupled with a lack of formal standards for either—make understanding and synergistically employing user stories with use cases confusing and challenging for practitioners and students alike. To address this, this paper first provides a descriptive overview of the evolution of user stories, use cases, and their interrelationship. Second, it fills a gap in the literature by providing a prescriptive, detailed approach to employing user stories and use cases together. This prescriptive approach is illustrated via a comprehensive tutorial example, providing practitioners with actionable skills and SA&D teachers and students with a new pedagogical tool.



The Scholarly Impact of Exploitative and Explorative Knowledge in Top IS Journals

Lindberg, Aron (aron.lindberg@stevens.edu)

Abstract

Recently, several scholars have argued that the information system (IS) field needs to reduce its reliance on reference theories and focus on developing “indigenous” theorical knowledge, suggesting that such a shift may help to increase the independence of the IS discipline. While original IS theory is likely to have larger impacts, the uptake of such ideas may also be more uncertain. To investigate such effects, we conduct a scientometric study on 211 research articles published in the two top IS journals, MISQ and ISR. We investigate the uptake of studies that draw on exploitative (i.e., exploiting existing theories from other disciplines) and explorative (i.e., exploration of new theoretical frameworks within the discipline) knowledge, respectively. We find that explorative knowledge receives, on average, a higher quantity of citations. Over time explorative knowledge manifests higher variance in citations received. Further, we find that explorative knowledge is more likely to assume more sophisticated conceptions of the IT artifact compared to exploitative knowledge. Last, exploitative knowledge, due to its platform nature, interacts with reputation effects to a greater degree than explorative knowledge. We conclude by providing guidance to both individual researchers as well as to the IS discipline as a whole.



Psychological Contract Violations on Information Disclosure: A Study of Institutional Arrangements in Social Media Platforms

Hammer, Bryan (bryan.hammer.phd@outlook.com)

Abstract

Previous research investigating information disclosure with online merchants has extended social contract theory using psychological contracts to explain the nature of the relationship between the consumer and merchant. This research extends the role of psychological contracts to social media platforms (SMP) by investigating how institutional psychological contract violations (PCV) influence trust in the SMP through institutional arrangements. Using a sample from MTurk, we presented two hypothetical scenarios manipulating the degree of PCV. Our findings suggest institutional PCVs act differently on institutional arrangements. Institutional PCVs impact attitudes toward institutional arrangements and trust in the SMP.



Online, On Call, On Your Mind? Coping with Extensive Connectivity to Work

mattern, jana (jana.mattern@t-online.de)

Abstract

Connectivity has become the hallmark of modern work and has also shaped the social life of many. Originating from a technical discourse, connectivity to work is reflected in numerous disciplinary discourses. While previous studies have identified negative effects for employees, the specific mechanisms which cause these effects are still poorly understood. The broadening of the term “connectivity” and the profound changes in the technical connectivity infrastructure require an adjusted conceptualization of connectivity, its structural causes and dimensions, how these dimensions interact, and how they explain different outcomes of connectivity. Based on a review of extant literature on connectivity and interviews with consultants, we develop a framework of connectivity that conceptualizes individual connectivity to work (social and technical) and its psychological impact (emotional, cognitive, behavioral). We derive extensive connectivity to work as a cause of strain. We develop two strategies, which allow employees to control extensive connectivity to work and cope with its effects. Preventive detachment aims to control the extent of connectivity and the psychological responses that lead to extensive connectivity if not controlled. Therapeutic detachment aims to reduce the strain resulting from extensive connectivity to work.



Where Do Theories Come From? An Inference-to-the-Best-Explanation Theory of Theory Building (IBET)

Seddon, Peter (p.seddon@unimelb.edu.au)

Abstract

This paper presents a theory of theory building and testing, called IBET, that is based primarily on Lipton’s 2004 book “Inference to the Best Explanation”. First, IBET argues that theories are ideas invented (not discovered) by people to explain how some part of the world works. Second, IBET argues that the goal in theory building is to abduce from the available evidence (including data, the literature, and the theory builder’s personal beliefs) an explanation that provides the researcher with their best understanding of why the phenomena of interest occur. Finally, IBET distinguishes between abductive testing of theories, where the information used for theory building is used for testing, and independent-data testing, where independently collected data are used for assessing the validity of a theory. In the last quarter of the paper, IBET is compared to three rival theories of theory building: (a) Grounded Theory, (b) Eisenhardt’s theory building from case studies, and (c) Shepherd and Suddaby’s recent advice on theory building. The conclusion is that IBET seems to provide a more in-depth, broad-scope, explanation of theory building than these rival theories.



Social Media as a Source of Citizens’ Communicative Power: Relating Social Media Diffusion, E-participation, and Corruption

Krishnan, Satish (satishk@iimk.ac.in)

Abstract

The utility of social media as an anti-corruption mechanism, although widely acknowledged, is less investigated, both empirically and theoretically. Accordingly, in this study, through a cross-country panel analysis and grounding our arguments on Habermas's theory of democracy, we explore the relationships among social media diffusion, e-participation, and corruption, in addition to the evolution of these relationships over time. Our results indicate that social media diffusion has a positive relationship with e-participation, which, in turn, has a negative relationship with corruption. Further, results show that the strength of these relationships wanes over time. These findings can help policymakers make informed decisions regarding the strategies for controlling corruption by increasing social media diffusion and e-participation.



A Tutorial on Prototyping Internet of Things Devices and Systems: A Gentle Introduction to Technology that Shapes Our Lives

Chua, Cecil (cchua@mst.edu)

Abstract

The Internet of Things, which has been quietly building and evolving over the past decade, now impacts many aspects of society, including homes, battlefields, and medical communities. Research in information systems, traditionally, has been more concentrated on exploring the impacts of such technology, rather than how to actually create systems using it. Although research in design science could especially contribute to the Internet of Things, this type of research from the Information Systems community has been sparse. The most likely cause is the knowledge barriers to learning and understanding this kind of technology development. Recognizing the importance of the continued evolution of the Internet of Things, this paper provides a basic tutorial on how to construct Internet of Things prototypes. The paper is intended to educate Information Systems scholars on how to build their own Internet of Things so they can conduct technical research in this area and instruct their students on how to do the same.



The ACM/AIS IS2020 Competency Model for Undergraduate Programs in Information Systems - A Joint ACM/AIS Task Force Report

Salmela, Hannu (hannu.salmela@utu.fi)

Abstract

The Association of Computing Machinery (ACM) and the Association of Information Systems (AIS) along with the ISCAP EDSIG, recently released a joint taskforce report IS2020: A Competency Model for Undergraduate Programs in Information Systems. In this paper, the co-chairs of IS2020, the latest Information Systems curriculum guidelines, provide their insight on the problems presented with existing guidelines, illustrate the issue, and share their opinions that led to the release of these latest guidelines.