The challenges and crises that face organisations are frequently the result of unintended, unanticipated or unforeseen consequences of well‑intended decisions. In this paper the role of research ethics is analysed in as far as it contributes to or militat

Data fabrication and falsification are clear breaches of research ethics, but have been shown to be insidious factors in various research disciplines. It would be naïve to believe that data fabrication and falsification do not affect the validity and reliability of business research. It behoves all users of such research to militate against these unethical practices and ensure that they do not go undetected. This paper briefly reviews the motivations for researchers, interviewers or surveyors to falsify or fabricate research data. This is followed by a discussion of techniques in the literature for detecting such unethical and fraudulent practices. Typically, these rely on the premise that falsification or fabrication of data results in anomalies in the dataset that cannot be attributed to sampling or methodology. A number of business case studies are discussed involving subtle data anomalies that could be attributable to fabrication or falsification or data. It is demonstrated that tried and tested parametric or non‑parametric statistical tests are often more than sufficient to identify these anomalies that characterise bogus data. However, data fabrication and falsification are not necessarily self‑evident and it may therefore require an unconventional and innovative approach to determine the appropriate variables of analysis. Analysis of the phenomenon leads to the conclusion that data fabrication and falsification are most easily detected by carrying out analyses on apparently extraneous variables, as these would tend to be neglected by the errant interviewer or surveyor. This leads to proposing a generic approach to detecting bogus data and a corresponding protocol to militate against it. A protocol is proposed that separates the essential research functions by adopting the trias politica principle, or separation of powers, analogous to the three branches of government: the legislature, the executive and the judiciary. The protocol requires the three functions of research design plus substantive analysis, data collection, and data verification to be separated. Suggestions for presenting data analyses and research findings that will ensure greater transparency, militate against data fabrication and falsification, improve reliability, and promote research integrity are included. The paper concludes with a specific recommendation to academics, consultants, reviewers, examiners, and other users of business research to hold researchers more accountable for their validity and reliability of their research outputs.

Academic research and scientific publication are being influenced irreversibly by what is referred to as the fourth industrial revolution. The exponential growth in the number of research publications continues, information and communication technology (including artificial intelligence) is making available research data and tools with unprecedented capabilities, and online open access to publications has enabled greater and more rapid access by other researchers. Changes of research practice and the behaviour of researchers and authors as a result of these developments are evident, and are challenging the criteria, norms and standards by which the quality and integrity of research has historically been judged. The manner in which prior research is being accessed, reproduced, applied and acknowledged is an example of such changes. In academia, the presentation of the ideas or writings of another without them being explicitly attributed to the original source has always been regarded as plagiarism and considered serious misconduct. Yet when such ideas and writings are freely available and in the public domain, they arguably fulfil the criteria for being considered common knowledge which don’t necessarily need to be referenced. This article presents examples of acceptable replication and reuse of the work of others, and examples of how plagiarism is manifesting differently because of information and communication technologies, including plagiarism software. It is argued that while paraphrasing previous authors result from understanding and applying their prior research, paraphrasing may simply be a grammatical or mechanistic process that does not attest understanding and application. It is provocatively suggested that current norms and standards of academic writing, including referencing, may no longer be appropriate. Relatively modest amendments to academic conventions and assumptions are proposed that could lead to a new paradigm of more efficient research and scientific publications, acknowledging that this would place greater burden of responsibility on the users, reviewers, editors and examiners of research to be familiar with extant knowledge.