In recent decades, several Multi-Criteria Decision Aid (MCDA) methods have been proposed to help in selecting the best compromise alternatives. In the meantime, the PROMETHEE (Preference Ranking ...Organization Method for Enrichment Evaluations) family of outranking methods and their applications has attracted much attention from academics and practitioners. In this paper, a classification scheme and a comprehensive literature review are presented in order to uncover, classify, and interpret the current research on PROMETHEE methodologies and applications. Based on the scheme, 217 scholarly papers from 100 journals are categorized into application areas and non-application papers. The application areas include the papers on the topics of Environment Management, Hydrology and Water Management, Business and Financial Management, Chemistry, Logistics and Transportation, Manufacturing and Assembly, Energy Management, Social, and Other Topics. The last area covers the papers published in several fields: Medicine, Agriculture, Education, Design, Government and Sports. The scholarly papers are also classified by (1) year of publication, (2) journal of publication, (3) authors’ nationality, (4) PROMETHEE as applied with other MCDA methods, and (5) PROMETHEE as applied with GAIA (Geometrical Analysis for Interactive Aid) plane. It is hoped that the paper can meet the needs of researchers and practitioners for easy references of PROMETHEE methodologies and applications, and hence promote the future of PROMETHEE research.
•This article focuses on prescriptive analytics, which is the less mature area of business analytics in comparison with descriptive and predictive analytics.•Prescriptive analytics are positioned as ...the next step towards increasing data analytics maturity and leading to optimized decision making ahead of time.•The existing literature pertaining to prescriptive analytics is reviewed and prominent methods for its implementation are examined.•The article identifies research challenges and outlines directions for future research in the field of prescriptive analytics.
Business analytics aims to enable organizations to make quicker, better, and more intelligent decisions with the aim to create business value. To date, the major focus in the academic and industrial realms is on descriptive and predictive analytics. Nevertheless, prescriptive analytics, which seeks to find the best course of action for the future, has been increasingly gathering the research interest. Prescriptive analytics is often considered as the next step towards increasing data analytics maturity and leading to optimized decision making ahead of time for business performance improvement. This paper investigates the existing literature pertaining to prescriptive analytics and prominent methods for its implementation, provides clarity on the research field of prescriptive analytics, synthesizes the literature review in order to identify the existing research challenges, and outlines directions for future research.
Knowledge production within the field of business research is accelerating at a tremendous speed while at the same time remaining fragmented and interdisciplinary. This makes it hard to keep up with ...state-of-the-art and to be at the forefront of research, as well as to assess the collective evidence in a particular area of business research. This is why the literature review as a research method is more relevant than ever. Traditional literature reviews often lack thoroughness and rigor and are conducted ad hoc, rather than following a specific methodology. Therefore, questions can be raised about the quality and trustworthiness of these types of reviews. This paper discusses literature review as a methodology for conducting research and offers an overview of different types of reviews, as well as some guidelines to how to both conduct and evaluate a literature review paper. It also discusses common pitfalls and how to get literature reviews published.
Stakeholder engagement has grown into a widely used yet often unclear construct in business and society research. The literature lacks a unified understanding of the essentials of stakeholder ...engagement, and the fragmented use of the stakeholder engagement construct challenges its development and legitimacy. The purpose of this article is to clarify the construct of stakeholder engagement to unfold the full potential of stakeholder engagement research. We conduct a literature review on 90 articles in leading academic journals focusing on stakeholder engagement in the business and society, management and strategy, and environmental management and environmental policy literatures. We present a descriptive analysis of stakeholder engagement research for a 15-year period, and we identify the moral, strategic, and pragmatic components of stakeholder engagement as well as its aims, activities, and impacts. Moreover, we offer an inclusive stakeholder engagement definition and provide a guide to organizing the research. Finally, we complement the current understanding with a largely overlooked dark side of stakeholder engagement. We conclude with future research avenues for stakeholder engagement research.
PurposeInscrutable machine learning (ML) models are part of increasingly many information systems. Understanding how these models behave, and what their output is based on, is a challenge for ...developers let alone non-technical end users.Design/methodology/approachThe authors investigate how AI systems and their decisions ought to be explained for end users through a systematic literature review.FindingsThe authors’ synthesis of the literature suggests that AI system communication for end users has five high-level goals: (1) understandability, (2) trustworthiness, (3) transparency, (4) controllability and (5) fairness. The authors identified several design recommendations, such as offering personalized and on-demand explanations and focusing on the explainability of key functionalities instead of aiming to explain the whole system. There exists multiple trade-offs in AI system explanations, and there is no single best solution that fits all cases.Research limitations/implicationsBased on the synthesis, the authors provide a design framework for explaining AI systems to end users. The study contributes to the work on AI governance by suggesting guidelines on how to make AI systems more understandable, fair, trustworthy, controllable and transparent.Originality/valueThis literature review brings together the literature on AI system communication and explainable AI (XAI) for end users. Building on previous academic literature on the topic, it provides synthesized insights, design recommendations and future research agenda.
Learning analytics can improve learning practice by transforming the ways we support learning processes. This study is based on the analysis of 252 papers on learning analytics in higher education ...published between 2012 and 2018. The main research question is: What is the current scientific knowledge about the application of learning analytics in higher education? The focus is on research approaches, methods and the evidence for learning analytics. The evidence was examined in relation to four earlier validated propositions: whether learning analytics i) improve learning outcomes, ii) support learning and teaching, iii) are deployed widely, and iv) are used ethically. The results demonstrate that overall there is little evidence that shows improvements in students' learning outcomes (9%) as well as learning support and teaching (35%). Similarly, little evidence was found for the third (6%) and the forth (18%) proposition. Despite the fact that the identified potential for improving learner practice is high, we cannot currently see much transfer of the suggested potential into higher educational practice over the years. However, the analysis of the existing evidence for learning analytics indicates that there is a shift towards a deeper understanding of students’ learning experiences for the last years.
•Most learning analytics research undertake a descriptive approach.•Interpretative and experimental studies prevail.•Overall there is little evidence that shows improvements in learner practice.•The identified potential for improving learning support and teaching is high.•There is a shift towards a deeper understanding of students' learning experiences.
Trimethylaminuria, better known as fish odor syndrome, is a psychologically disabling condition in which a patient emits a foul odor, which resembles that of rotting fish. The disorder is most ...commonly caused by an inherited deficiency in flavin monooxygenase 3, the vital enzyme for the metabolism of trimethylamine, which is the compound responsible for the unpleasant odor. The condition is uncommon, but there has been recent research to suggest that the diagnosis may often be overlooked. Moreover, it is important to be cognizant of this condition because there are reliable diagnostic tests and the disorder can be devastating from a psychosocial perspective. While there is no cure, many simple treatment options exist that may drastically improve the quality of life of these patients. This article will review the literature with an emphasis on the psychosocial impact and treatment options.
PDF
