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This paper aims to examine if Malaysian public listed companies have expressed any specific sentiment(s) when publishing their financial performance during the COVID-19 pandemic.

The disclosed sentiments contained in the management discussion and analysis section of the companies’ annual reports were extracted by means of computer-automated textual analysis through the linguistic inquiry and word counts and the Loughran–McDonald Financial Sentiment Dictionary. Next, a correlation analysis was conducted. Finally, a qualitative content analysis (QCA) was conducted to confirm these sentiments.

The analysis shows that companies adopted various tones of sentiments when communicating with their stakeholders. Most companies used negative sentiments to voice their concerns about how the COVID-19 pandemic has impacted upon their business operations. Only a few companies reflected positive sentiments, whilst those that experienced operating losses also expressed uncertainty.

This study may assist either the regulators or accounting bodies to introduce a reporting framework that public companies can adopt during natural hazards. It also provides useful insights to (potential) investors to enable them to better understand the business landscape. For future research, the same study could be conducted on more countries so that their experiences can be used to better understand the business phenomenon from a global perspective.

This study is one of few studies to adopt automated textual analysis and QCA to examine the exhibited sentiments when public companies reported their financial performance during the COVID-19 pandemic.

Building defects are becoming recurrent phenomena in most high-rise buildings. However, little research exists on the analysis of defects in high-rise buildings based on data from real-life projects. This study aims to develop dashboards and models for revealing the most common locations of defects, understanding associations among defects and predicting the rectification periods.

In total, 15,484 defect reports comprising qualitative and quantitative data were obtained from a company that provides consulting services for the construction industry in Victoria, Australia. Data mining methods were applied using a wide range of Python libraries including NumPy, Pandas, Natural Language Toolkit, SpaCy and Regular Expression, alongside association rule mining (ARM) and simulations.

Findings reveal that defects in multi-storey buildings often occur on lower levels, rather than on higher levels. Joinery defects were found to be the most recurrent problem on ground floors. The ARM outcomes show that the occurrence of one type of defect can be taken as an indication for the existence of other types of defects. For instance, in laundry, the chance of occurrence of plumbing and joinery defects, where paint defects are observed, is 88%. The stochastic model built for door defects showed that there is a 60% chance that defects on doors can be rectified within 60 days.

The dashboards provide original insight and novel ideas regarding the frequency of defects in various positions in multi-storey buildings. The stochastic models can provide a reliable point of reference for property managers, occupants and sub-contractors for taking measures to avoid reoccurring defects; so too, findings provide estimations of possible rectification periods for various types of defects.

This study aims to investigate the tendency that Malaysian consumers will choose the recombinant collagen-like protein (RCLP) from bacteria as an alternative source of collagen in their consumption and the determinants of the consumer acceptance.

Quantitative approach is adopted in the study. Descriptive analysis and logistic regression are used to analyze primary data collected from a survey.

The likelihood of consumers choosing RCLP as an alternative source of collagen is higher among elderly and females. The choice is significantly influenced by the idea that the collagen should support maqasid al-syariah, approved by national Islamic body, should clear on the ingredients used and could boost local economic activities in the future.

An ethical halal policy should be outlined as the guiding principles to the potential producers of RCLP.

An alternative source of collagen using bacteria as proposed is not yet being introduced in Malaysian industry, and the analysis on probability that consumers will accept this new sourced collagen product is using primary data from survey.

This study aimed to investigate the impact of job embeddedness (JE) on the turnover intention (TI) of the public sector with the mediating effect of the individual factor (i.e. life satisfaction [LS]) and the moderating effect of the leadership style (i.e. ethical leadership [EL]).

This study adopted a quantitative design to collect data from 236 employees working in the public sector in Vietnam through field research using structured questionnaires. Data were analysed using partial least squares structural equation modelling (PLS-SEM) to test the hypotheses.

The results show that JE negatively affects the TI of public sector employees through the mediation effect of LS. Additionally, this study indicates that EL moderates the relationship between JE and TI.

This study implies that public sector stakeholders should consider both individual and contextual factors to manage and retain employees. In addition to addressing employees' embeddedness with the organisation and community and their LS, public organisations need to focus on hiring, training and promoting ethical leaders.

This study highlights the role of embeddedness within both the organisation and the community, along with the role of EL in the LS and TI of public sector employees.

This study aims to investigate the growth of Indonesian Islamic banks and explores organisational growth determinants from different perspectives, namely, organisational climate, intellectual capital (IC) and organisational service orientation. The study also attempts to develop a model to measure the growth of Islamic banks and uncovers the root causes of the stagnancy in Indonesian Islamic banking.

The study used survey questionnaires distributed to Islamic bank managers, who were considered representative experts in the field of Islamic banking. The data collected were analysed using the Statistical Package for Social Sciences (SPSS Version 21.0), and two analyses were performed with different strategies to build the regression model, namely, multiple linear regression and automatic linear regression.

The study found that IC significantly affected Islamic banks’ growth in Indonesia; however, organisational climate and service orientation did not predict such growth. Concerning service orientation as a mediating model, climate or IC had no indirect effect on growth.

This study’s results contribute to fill the gap by analysing the growth of Islamic banks. Hence, the study results will be especially practical and helpful for Islamic bank managers and policymakers to help develop mechanisms for Islamic banks in Indonesia.

By combining the aspects of organisational climate, IC and service orientation from earlier studies and categorising them by organisational growth, together with a comprehensive literature review, the study proposes a model specific to Islamic banks. It also offers new insight and discussion for determining organisational growth in Indonesian Islamic banks.