Ethics I: Authors and their research

Abstract

The ethical values of researchers and the ethical expectations of academic publishers are a permanent feature of our scholarly debates. Meet-the-editor sessions at conferences often touch on a variety of ethical issues, while premier journals publish both special issues and opinion pieces on ethics-related topics. For instance, in a recent issue of the ISJ, Davison et al. (2022) wrote about some of the ethical issues facing action researchers. Indeed, readers with excellent memories may recall that, 20 years ago, a series of articles were published in the Communications of the AIS that later led to the development of a code of research conduct for the AIS.1

The current editorial is the first of several planned in which we examine specific aspects of ethics in IS research. Our writing of the editorial was stimulated by our encounters with ethical issues as experienced in our editorial roles at the ISJ and other journals. The focus of this editorial is ‘ethics and the researcher’. We do not intend to rehash the entire oeuvre of the topic, as this is extensive: the AIS e-Library indicates 516 items published in Communications of the AIS alone. Indeed, the AIS Code of Research Conduct is quite comprehensive in its coverage. Instead, we explore a few less well-appreciated areas of ethics that we suggest researchers should be aware of. These issues include obtaining human ethics research approval prior to empirical data collection, claiming research outcomes as a panacea, and being transparent in research reporting.

It is widely accepted that human research ethics approval should be obtained before data is collected from living people. Usually, such approvals are handled at the institutional level, though it is fair to point out that not all institutions require such approvals. Authors cannot be faulted for failing to secure human research ethics approval if their institution does not require it and if local legislation does not protect the privacy of human subjects. However, in these circumstances authors are required to provide details documenting their ethical conduct while collecting data from human subjects. For instance, they should provide details about whether they were transparent in disclosing research goals and risks with participants, along with explaining how they ensured anonymity, when applicable.

In addition, there may be misunderstandings about the types of data that are subject to these approvals. For instance, should publicly accessible data be subject to such reviews, where the data subjects cannot be reasonably contacted so as to obtain their consent to have that data included in the research? A key issue is whether the data can lead to positive identification (or reidentification) of an individual, and if identification was achieved, what harm or consequence might befall the individual? Research on online communities or relying on crowdsourced data, for example, those gathered from Amazon Mechanical Turk (MTurk), are also problematic. Even if such crowdsourced data subjects cannot be identified, we can ask if they are fairly remunerated for their time.

In many studies, notably case studies and action research but also surveys that are conducted inside an organisation, human research ethics approval is often obtained from a senior manager on behalf of subordinates. This is not necessarily ideal, and indeed the subordinates may essentially be compelled to participate. Thus, a response rate of close to 100% should flag reviewers' attention. Action research studies are particularly complex, since the organisation is itself a client that expects to benefit from the research. It might be that employees' informed consent is achieved, that is, they are informed that their data will be collected, but the more stringent standard of affirmative consent, where each employee freely and positively affirms a personal willingness to participate in the research, is often never sought, let alone achieved. Regardless of whether we talk about small or big data, if data is generated by human subjects, researchers need to ask themselves whether manipulating that data and publishing inferences derived from the data can hurt people.

Academic journals are starting to pay attention to these issues, recognising that research ethics approvals may be fabricated (or not obtained at all). Journals are increasingly expecting that authors will be transparent with regard to their protection of the data privacy rights of research subjects irrespective of the jurisdiction that applied to the collection of research data. At a minimum, we expect that reviewers should probe into whether ethical issues were given due attention in research designs and question if there are inconsistencies in the way ethical issues are reported, or indeed if the research practices are clear and ethically defensible.

A second ethical issue that pertains to authors concerns what we call technological solutionism, that is, research that deterministically offers solutions (to real or imagined problems) without any critical reflection or attempt to test if the solutions actually work in practice. For instance, such ‘solutions’ may benefit a corporate stakeholder yet seriously disadvantage employees. Marginalised and minority groups can also suffer from technologically deterministic solutions. As Díaz Andrade and Techatassanasoontorn (2021) noted, e-banking technology is great for those who like to use it, but when a bank closes rural branches and forces adoption of the technology, those who are digitally challenged or who just do not want to go online to do their banking are left in a difficult situation.

Researchers need to be mindful of the broader implications and consequences of their research, recognising the limitations of technological narratives that give rise to false hope or that discriminate against some sections of society. It is important that researchers do not overreach while discussing the scholarly and practical implications of their work. Indeed, authors have a duty to inform readers if they feel that there could be negative appropriation/interpretation of their work and whether there could be an ethical issue if that were the case. Making such cautionary notes explicit would be helpful for future researchers and practitioners as they build upon the authors' published study.

The authors should realise that transparency is of utmost importance in scholarly creativity. Authors should never attempt to ‘hide’ any inconvenient or unwanted facts in an attempt to make a favourable case for publication of the research. In fact, such attempts to hide information would undermine the sanctity of the research project. All steps taken in research design and data analysis should be clearly documented. For example, in a quantitative study it is quite common that authors engage in what is euphemistically called ‘data cleaning’. If authors had a set of items measuring a construct and they dropped a couple due to poor factor loadings, it would be a good idea to document this process in the article with an explanation. Again, if there were certain respondents whose data were discarded, such actions should be documented and justified in the article. If some hypotheses that were originally in the model were not supported, it is preferable not to change the research model just so as to ensure that all hypotheses are supported; instead, discussions about all the originally hypothesised links should be included. Authors should understand that non-significant relationships also support the cause of knowledge advancement and failing to report them can be interpreted as an unethical behaviour. Of course, the reviewers and editors (and readers, if the study is published) will never likely know the ‘original’ model that the authors had in mind. Therefore, the onus is solely on the authors' integrity and their commitment to knowledge advancement in a righteous manner.

Similar arguments can be made for a qualitative study. In a qualitative study, the authors should be mindful about reporting conclusions that are faithful to the genre of the qualitative research they are conducting. For example, the authors should not attempt to theorise ‘forcefully’ if they are conducting a primarily inductive study (nor should reviewers require them to do so!); instead, their theoretical arguments must be reasonably consistent with (and emerge from) the data that they have obtained. They certainly cannot fabricate interview data in order to plug a hole in their evidence base.

What is important is to understand that improving clarity of their empirical efforts (in the article) is an ethical duty of the authors. A clear documentation of all empirical steps taken helps the editors and reviewers ascertain the value and rigour of the work, and its possible impact on future research and practice.

In this issue of the ISJ, we present eight articles and two book reviews.

In the first article, Wu et al. (2024) investigate the effect of task descriptions on solvers' participation by focusing on informational and affective linguistic signals. They validate a model by analysing 13,929 descriptions posted in single-winner tasks on epwk.com, a Chinese competitive crowdsourcing platform. For informational linguistic signals, the results reveal that there are inverted U-shaped relationships between both concreteness and specificity and solver participation, whereas linguistic accuracy has a positive effect on solver participation. For affective linguistic signals, positive emotional words have a positive relationship with solver participation, whereas negative emotional words have the opposite effect. Theoretical and practical implications are discussed.

In the second article, Lee et al. (2024) delve into the dynamics of building digital resilience to manage crises. Through an empirical investigation of Taiwan's response to the COVID-19 pandemic, they unpacked four digital orchestration approaches that together constitute an effective strategy for tackling multidimensional and unforeseen crisis-related events and concerns. They also demonstrate how a variety of digital resources can be deployed and utilised. Their conceptual model on digital resilience in the making goes beyond the traditional capability-based theorisation of digital resilience and instead moves toward a process-oriented approach in addressing multiple tensions and challenges arising from crisis conditions.

In the third article, Karanasios et al. (2024) explore the consequences of using social media in various ways in the context of emergencies in multiple organisations under differing logics. This situation is particularly critical in fields like emergency management where fragmented and inconsistent information is problematic. They undertook a comprehensive qualitative study with 27 organisations including emergency, government, non-government, private, and community entities. The findings enhance understanding of the coevolution of logics and digital technology enactment within an organisational field. The authors present a theoretical model that highlights mutual influence between organisational logics and social media usage. They present a framework capturing the breadth of information flow across an organisational field. These contributions advance theoretical insight into institutional dynamics and improve our understanding of the role of social media in organisational fields. The authors also discuss the practical implications of their findings.

In the fourth article, Srivastava et al. (2024) theorise the mechanisms through which organisational citizenship behaviour (OCB) fosters positive work attitudes among IT professionals. The authors ground their research in self-perception and self-determination theories, hypothesizing the relationships between IT professionals' OCB and their affective attitudes toward their organisation and job, as being mediated by their cognitive evaluations of the ‘meaning of their IT work’. They test the model with data collected through a large-scale two-wave survey design from a multinational IT-services company. The results offer a nuanced understanding of the relationship between OCB and positive work attitudes for IT professionals, which have significant implications for research and practice.

In the fifth article, Recker et al. (2024) examine the context of responsible production and consumption, reporting on Vytal, an innovative “scale up” (a rapidly growing young firm) that has managed to become the world's largest provider of digitalized reusable packaging solutions in the food retail sector. The unique challenge of Vytal was to grow their business both in the online world through a digital platform app that must attract both consumers and food providers such as canteens or restaurants, and in the physical food retail world where food containers move around, get dirty, and need cleaning. Vytal navigated this challenge successfully and this article conceptualises the lessons learnt from their growth in a framework that provides recommendations for other firms operating online-to-offline business models.

In the sixth article, Zhang et al. (2024) remark that online learning platforms provide an opportunity for self-directed learning; however, they often encounter difficulties in maintaining learners' engagement. This study builds upon normative influence theories and explores the impact of peer information on online learning engagement and outcomes, specifically in an online learning setting devoid of external incentives such as rewards or performance evaluations. To investigate this, a field experiment was conducted on an online learning platform. The findings indicate that the mere sharing of information regarding peers' active learning behaviour does not necessarily enhance engagement. However, it does exhibit a positive influence when accompanied by course-related question interventions. This research contributes to our understanding of how peer influence can be utilised to improve engagement and offers practical insights for addressing the challenge of low engagement in online learning settings where learners typically learn in isolation, without external incentives.

In the seventh article, Liao et al. (2024) examine the social networks present in livestreaming contexts. They propose that both centralised and decentralised networks can coexist within multi-level bimodal platforms via various role-based subgroups with different types of decision-makers. Drawing on social impact theory, they examine the role of information from host-audience centralised and host–host decentralised networks in shaping subscription increment and herding effects. Using a panel dataset, they find that bidirectional ties in host–host networks strengthen both the acquisition of fans and the herding effect in the host-audience decentralised network, with hosts of lower social status gaining more fans than those with higher status in bidirectional ties. This study contributes to the understanding of social network structure, herding effect, social impact theory and livestreaming by problematizing core assumptions and offering a contextual explanation of livestreaming. Moreover, their work provides practitioners with valuable insights into leveraging network effects for hosts' success in livestreaming.

In the eighth article, Chamakiotis et al. (2024) use a novel methodology involving video diaries and follow-up interviews to explore ‘contemporary boundary work’, that is, the practices individuals develop to manage their boundaries between ‘work’ and ‘life’. Premised on their critique that existing frameworks fail to accurately explain this, they creatively adopt the lenses of ‘hybridity’ (fusion of boundaries) and ‘liminality’ (a state of suspension/in-betweenness) in combination to unpack how the interplay of the two enables or undermines desired boundary work outcomes. Their findings highlight individuals' creative agency in bringing hybridity and liminality together as part of their everyday boundary work. This study offers an important advancement in the field of digital technologies and boundary work, moving away from narrower understandings of contemporary boundary work and providing new conceptual combinations (i.e., the interplay between hybridity and liminality) that could be used to explain additional phenomena in the IS field and beyond.

Finally, we present two reviews of recently published books: ‘Deep Fakes: Algorithms and Society’ and ‘Digital transformation: Understanding business goals, risks, processes and decisions’.