Causal Discovery in Manufacturing: A Structured Literature Review

Industry 4.0 radically alters manufacturing organization and management, fostering collection and analysis of increasing amounts of data. Advanced data analytics, such as machine learning (ML), are essential for implementing Industry 4.0 and obtaining insights regarding production, better decision support, and enhanced manufacturing quality and sustainability. ML outperforms traditional approaches in many cases, but its complexity leads to unclear bases for decisions. Thus, acceptance of ML and, concomitantly, Industry 4.0, is hindered due to increasing requirements of fairness, accountability, and transparency, especially in sensitive-use cases. ML does not augment organizational knowledge, which is highly desired by manufacturing experts. Causal discovery promises a solution by providing insights on causal relationships that go beyond traditional ML’s statistical dependency. Causal discovery has a theoretical background and been successfully applied in medicine, genetics, and ecology. However, in manufacturing, only experimental and scattered applications are known; no comprehensive overview about how causal discovery can be applied in manufacturing is available. This paper investigates the state and development of research on causal discovery in manufacturing by focusing on motivations for application, common application scenarios and approaches, impacts, and implementation challenges. Based on the structured literature review, four core areas are identified, and a research agenda is proposed.

The Role of Trustworthiness Facets for Developing Social Media Applications: A Structured Literature Review

This work reviews existing research about attributes, which are assessed by individuals to evaluate the trustworthiness of (i) software applications, (ii) organizations (e.g., service providers), and (iii) other individuals. As these parties are part of social media services, previous research has identified the need for users to assess their trustworthiness. Based on the trustworthiness assessment, users decide whether they want to interact with them and whether such interactions appear safe. The literature review encompasses 264 works from which so-called trustworthiness facets of 100 papers could be identified. In addition to an overview of trustworthiness facets, this work further introduces a guideline for software engineers on how to select appropriate trustworthiness facets during the analysis of the problem space for the development of specific social media applications. It is exemplified by the problem of “catfishing” in online dating.

The appearance of agency theory in the publications of Polish authors – the need to expand research in behavioral accounting

Purpose: The aim of the article is to assess the use of agency theory by Polish authors in articles in the field of accounting published by the end of 2020. Methodology/approach: The study was carried out using a structured literature review, which is a recognized method of conducting literature analysis, also in the field of accounting. Findings: The results of the review show little use of agency relations in empirical re-search. Both in theoretical and empirical research, the issues in financial reporting were most often addressed. In most publications, agency theory constitutes the theoretical back-ground for the considerations, while there is a lack of research that focuses on the impact of the agency relationship between the owner and manager or between employees at vari-ous levels on accounting. The empirical studies analyzed only external factors that influ-ence decision-making, while there is a gap in studies that focused on individual human characteristics. Research limitations/implications: The structured literature review covers articles pub-lished between 1993 and 2020 written by Polish authors. Originality/value: The originality of the article arises from the identification of shortcom-ings in the publications of Polish authors in contrast to global achievements, in particular in the fields of management accounting and behavioral accounting. Thus, we indicate the directions of further development of research already carried out by the few Polish authors. The guidelines concern the development of research in the field of behavioral accounting, which will deepen the knowledge about the impact of the principal-agent relationship on the decisions people make in creating reporting and management information. Keywords: agency theory, agency relation, behavioral accounting, SLR, literature review.

Lean accounting: a structured literature review

PurposeThe purpose of the paper is to perform a review and analyze the literature on lean accounting (LA) to develop insights into how LA research is developing, offering a critique of the research to date and underlining future research opportunities.Design/methodology/approachThe research uses a structured literature review (SLR) to categorize and analyze 39 research articles from relevant journals with a publication date from 1996 to 2020 (September) and to answer three research questions.FindingsFindings demonstrated that although LA seems to be the most suitable method for lean companies, it still lacks research in terms of the role of accountants in lean organizations as well as how its concepts are integrated with the generally accepted accounting principles (GAAP).Practical implicationsThe paper provides both academics and practitioners with valuable insights regarding the role of management accounting and accountants in the pursuit of lean transformation, presenting meaningful themes and a complete analysis of the literature along with research gaps for future research.Originality/valueThe paper contributes to lean manufacturing literature by providing a comprehensive SLR of articles regarding LA. Also, the paper serves as a basis for developing future research agendas in management accounting practices for lean organizations.

A structured literature review on Big Data for customer relationship management (CRM): toward a future agenda in international marketing

PurposeThis paper aims to advance the international marketing debate by presenting the results of a structured literature review (SLR) focusing on Big Data implementation in customer relationship management (CRM) strategizing. It outlines past and present literature and frames a future research agenda.Design/methodology/approachThe research analyzes papers published in journals from 2013 to 2020, deriving significant insights about Big Data applications in CRM. A sample of 48 articles indexed at Scopus was preliminarily submitted for bibliometric analysis. Finally, 46 papers were analyzed with content and a bibliometric analysis to identify areas of thematic specializations.FindingsThe paper presents a conceptual multilevel framework demonstrating areas of specialization emerging from the literature. The framework is built around four coordinated sequences of actions relevant to “why,” “what,” “who” and “how” Big Data is implemented in CRM strategies, thus supporting the conception and implementation of an internationalization marketing strategy.Research limitations/implicationsImplications for the development of the future research agenda on international marketing arise from the comprehension of Big Data in CRM strategy.Originality/valueThe paper provides a comprehensive SLR of the articles dealing with models and processes of Big Data for CRM from an international marketing perspective. Despite these issues' relevance and the increasing literature focused on them, research in this area is still fragmented and underexplored, requiring more systematic and holistic studies.