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This study explores the influence of the following factors on consumer adoption of blockchain food traceability (BFT): innovation-adoption characteristics, segmentation, expertise in food traceability, expertise in blockchain technology, food categorical preferences and perceived important features of BFT.

The data was collected via an online questionnaire with 1,401 participants in New Zealand. Exploratory factor analysis, structural equation modelling and segmentation analysis were undertaken.

Consumer adoption of blockchain food traceability was significantly influenced by two innovation-adoption characteristics – perceived incentives and perceived complexity, as well as their expertise in food traceability. Two consumer segments were identified: Conservatives (48%) and Pioneers (52%). Significant differences were found between these two segments in terms of gender, age, education, occupation, residential area and ethnicity. Consumers are more willing to use BFT for purchasing fresh, imported, staple and normal foods than for processed, domestic and upscale foods. Their perceived important specific features of BFT are product origin, food safety information, quality control, food safety information, hygienic condition and scarcity management.

This study contributes knowledge to address the current knowledge gap regarding consumer adoption of blockchain food traceability by using a large sample set. It is also the first study to recognise consumer segments for BFT; to provide information about consumers' important socio-demographic characteristics, food categorical preferences and perceived important features towards BFT; and to explore the influences of consumers' innovation-adoption characteristics, expertise in food traceability and expertise in blockchain technology on their adoption of blockchain food traceability.

This study is carried out to evaluate how well legal knowledge can be demonstrated by a built environment professional via the scenario-based approach to the learning of law modules.

A Delphi analysis of the advice provided by an MSC quantity surveying student, on a scenario-based legal problem arising due to a property contract, is carried out. The tendered legal advice was submitted as part of the assessment requirements for an MSc law module, following the university criteria, after the teaching of a law module. The student report, which attained an A-grade, and the assessment criteria used for marking/grading by the university were subsequently sent to 18 practicing lawyers, who were selected to constitute an expert panel, to independently judge the extent of legal knowledge demonstrated in the student report.

The Delphi analysis outcome showed that the expert panel holds a similar consensus view to the university on the level of legal knowledge demonstrated and by extension the effectiveness of the law module in imparting legal knowledge to a non-lawyer. The study outcome shows how well legal knowledge can be acquired and applied by a non-lawyer, within the context of the built environment, via scenario-based teaching of a law module.

This study serves as a preliminary step necessary to arouse further research toward empirically profiling the current outlook of a wider range of graduating students receiving scenario-based legal education in the built environment.

This study aims to investigate the relationship between corporate governance characteristics and the financial performance of both Islamic and conventional banks in the context of an emerging market, i.e. Malaysia.

This study includes 300 bank-year observations from Islamic and conventional banks over the period 2010–2021. The dynamic panel model (generalized method of moments [GMM]) was considered the primary estimation model that solves simultaneity, endogeneity and omitted variable problems as most governance variables are endogenous by nature. Hence, static models are considered biased after conducting the DWH test of endogeneity, and considering dynamic panel GMM is valid proven by Sargan and Hensen and first-order (ARI) and second-order (ARII) tests.

Based on the regression results, the authors discovered that board size, female participation in the board and director remuneration have a significant positive impact on bank performance, whereas board meetings have a significant negative impact. Furthermore, the board governance structure of commercial banks is found to be more passive than that of Islamic banks.

The study’s findings added a new dimension to governance research, which could be a valuable source of knowledge for policymakers, investors and regulators looking to improve existing governance mechanisms for better performance of conventional and Islamic banks.

The goal of this study is to add to the existing literature by focusing on the impact of female board participation and other board governance mechanisms in both conventional and Islamic banks on bank performance.

Despite the current progress in realizing how Big Data Analytics can considerably enhance the Sustainable Manufacturing Supply Chain (SMSC), there is a major gap in the storyline relating factors of Big Data operations in managing information and trust among several operations of SMSC. This study attempts to fill this gap by studying the key enablers of using Big Data in SMSC operations obtained from the internet of Things (IoT) devices, group behavior parameters, social networks and ecosystem framework.

Adaptive Prospects (Improving SC performance, combating counterfeits, Productivity, Transparency, Security and Safety, Asset Management and Communication) are the constructs that this research first conceptualizes, defines and then evaluates in studying Big Data Analytics based operations in SMSC considering best worst method (BWM) technique.

To begin, two situations are explored one with Big Data Analytics and the other without are addressed using empirical studies. Second, Big Data deployment in addressing MSC barriers and synergistic role in achieving the goals of SMSC is analyzed. The study identifies lesser encounters of barriers and higher benefits of big data analytics in the SMSC scenario.

The research outcome revealed that to handle operations efficiently a 360-degree view of suppliers, distributors and logistics providers' information and trust is essential.

In the Post-COVID scenario, the supply chain practitioners may use the supply chain partner's data to develop resiliency and achieve sustainability.

The unique value that this study adds to the research is, it links the data, trust and sustainability aspects of the Manufacturing Supply Chain (MSC).