Country-Of-Origin (COO) Impact and Product Categories’ Evaluations: The Case of an Emerging Market

This study assesses the impact of culture on the perception of COO and consumer decision-making processes in Morocco, as an emerging market and a non-Western and North African nation. In general, the findings confirm that product categories from more developed countries receive more favorable evaluations than products from developing nations. The results from this exploratory study confirm other researchers' conclusions that economically developed nations and economies have the highest perceived quality image and that there is a bias against products from less advanced countries and markets. Managerial implications are also discussed

The Role of Individual Variables, Organizational Variables and Moral Intensity Dimensions in Libyan Management Accountants’ Ethical Decision Making

This study investigates the association of a broad set of variables with the ethical decision making of management accountants in Libya. Adopting a cross-sectional methodology, a questionnaire including four different ethical scenarios was used to gather data from 229 participants. For each scenario, ethical decision making was examined in terms of the recognition, judgment and intention stages of Rest’s model. A significant relationship was found between ethical recognition and ethical judgment and also between ethical judgment and ethical intention, but ethical recognition did not significantly predict ethical intention—thus providing support for Rest’s model. Organizational variables, age and educational level yielded few significant results. The lack of significance for codes of ethics might reflect their relative lack of development in Libya, in which case Libyan companies should pay attention to their content and how they are supported, especially in the light of the under-development of the accounting profession in Libya. Few significant results were also found for gender, but where they were found, males showed more ethical characteristics than females. This unusual result reinforces the dangers of gender stereotyping in business. Personal moral philosophy and moral intensity dimensions were generally found to be significant predictors of the three stages of ethical decision making studied. One implication of this is to give more attention to ethics in accounting education, making the connections between accounting practice and (in Libya) Islam. Overall, this study not only adds to the available empirical evidence on factors affecting ethical decision making, notably examining three stages of Rest’s model, but also offers rare insights into the ethical views of practising management accountants and provides a benchmark for future studies of ethical decision making in Muslim majority countries and other parts of the developing world

OMG-Net: A Deep Learning Framework Deploying Segment Anything to Detect Pan-Cancer Mitotic Figures from Haematoxylin and Eosin-Stained Slides

Mitotic activity is an important feature for grading several cancer types. Counting mitotic figures (MFs) is a time-consuming, laborious task prone to inter-observer variation. Inaccurate recognition of MFs can lead to incorrect grading and hence potential suboptimal treatment. In this study, we propose an artificial intelligence (AI)-aided approach to detect MFs in digitised haematoxylin and eosin-stained whole slide images (WSIs). Advances in this area are hampered by the limited number and types of cancer datasets of MFs. Here we establish the largest pan-cancer dataset of mitotic figures by combining an in-house dataset of soft tissue tumours (STMF) with five open-source mitotic datasets comprising multiple human cancers and canine specimens (ICPR, TUPAC, CCMCT, CMC and MIDOG++). This new dataset identifies 74,620 MFs and 105,538 mitotic-like figures. We then employed a two-stage framework (the Optimised Mitoses Generator Network (OMG-Net) to classify MFs. The framework first deploys the Segment Anything Model (SAM) to automate the contouring of MFs and surrounding objects. An adapted ResNet18 is subsequently trained to classify MFs. OMG-Net reaches an F1-score of 0.84 on pan-cancer MF detection (breast carcinoma, neuroendocrine tumour and melanoma), largely outperforming the previous state-of-the-art MIDOG++ benchmark model on its hold-out testing set (e.g. +16% F1-score on breast cancer detection, p<0.001) thereby providing superior accuracy in detecting MFs on various types of tumours obtained with different scanners

Qur’anic Ethics for Environmental Responsibility: Implications for Business Practice

Despite the growing interest in examining the role of religious beliefs as a guide towards environmental conscious actions, there is still a lack of research informed by an analysis of divine messages. This deficiency includes the extent to which ethics for environmental responsibility are promoted within textual divine messages; types of environmental themes promoted within the text of divine messages; and implications of such religious environmental ethics for business practice. The present study attempts to fill this gap by conducting a thorough content analysis of environmental themes within the divine message of Muslims (the Qur’an) focusing on their related ethical aspects and business implications. The analysis has revealed 675 verses in 84 chapters throughout all 30 parts of the Qur’an, with environmental content relating to the core components of the natural world, i.e. human beings, water, air, land, plants, animals, and other natural resources. This environmental content and its related ethics are grounded on the belief that humans are vicegerents of God on the earth and their behaviours and actions are motivated by earthly and heavenly rewards. Implications of these findings for different sectors/businesses are also highlighted