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The purpose of this paper is to manage knowledge pertaining to micro, small and medium enterprise (MSME) actors in the business, agriculture and industry sectors. This study uses text mining techniques, specifically Latent Dirichlet Allocation Mallet, to analyze the data obtained from the in-depth interviews. This analysis helps us identify and understand the issues faced by these actors.

In this study, the authors use big data and business analytics to recalculate the MSME business vulnerability index in 503 districts and 34 provinces across Indonesia. Subsequently, the authors conduct in-depth interviews with MSME actors in Medan, Central Java, Yogyakarta, Bali and Manokwari, West Papua. Through these interviews, the authors explore their strategies for surviving the COVID-19 pandemic and the extent of their digital literacy, and the application of technology to maximize sales and business outcomes.

The findings reveal that, for the sustainable growth of MSMEs during and after the pandemic, collaboration across the Penta-Helix framework is essential. This collaboration enables the development of practical solutions for the challenges posed by COVID-19, particularly in the context of the “new normal.” In addition, the authors’ survey of MSMEs involved in agriculture, trade and processing sectors demonstrates that 58.33% experienced a decrease in income during the pandemic and 12.66% reported an increase in revenue. In contrast, 25% experienced no change in income before and during the pandemic.

This research contributes significantly by offering comprehensive insights obtained from in-depth surveys conducted with MSMEs across multiple sectors. The findings underscore the importance of addressing the challenges MSMEs face and highlight the need for collaboration within the Penta-Helix framework to foster their resilience and success amidst the COVID-19 pandemic.

Despite the practice of credit card services by Islamic financial institutions (IFIs) is debatable, Islamic banks (IBs) have been offering this product. Both Muslim and non-Muslim customers have subscribed to the products. Thus, it is critical to analyse the strategy of IBs’ moral messages in reminding their Muslim and non-Muslim customers to repay their credit card debts. This paper aims to investigate this issue in Indonesia using data mining via machine learning.

This study examines the IBs’ customers across the 32 provinces of Indonesia regarding their moral status in credit card debt repayment. This work considers 6,979 observations of the variables that affect the moral status of the IBs’ customers in repaying their debt. The five types of data mining via machine learning (i.e. Boruta, logistic regression, Bayesian regression, random forest, XGBoost and spatial cluster) are used. Boruta, random forest and XGBoost are used to select the important features to investigate the moral aspects. Bayesian regression is used to get the odds and opportunity for the transition of each variable and spatially formed based on the information from the logistical intercepts. The best method is selected based on the highest accuracy value to deliver the information on the relationship between moral status categories in the selected 32 provinces in Indonesia.

A different variable on moral status in each province is found. The XGBoost finds an accuracy value of 93.42%, which the three provincial groups have the same information based on the importance of the variables. The strategy of IBs’ moral messages by sending the verse of al-Qur’an and al-Hadith (traditions or sayings of the Prophet Muhammad PBUH) and simple messages reminders do not impact the customers’ repaying their debts. Both Muslim and non-Muslim groups are primarily found in the non-moral group.

This study does not consider socio-economic demographics and culture. This limitation calls future works to consider such factors when conducting a similar topic.

The industry professionals can take benefit from this study to understand the Indonesian customers’ moral status in repaying credit card debt. In addition, future works may advance the recent findings by considering socio-cultural factors to investigate the moral status approach to Islamic credit warnings that is not covered by this study.

This work finds that religious text of credit card repayment reminders sent to Muslims in several provinces of Indonesia does not affect their decision to repay their debts. To some extent, this finding draws a social issue that the local IBs need to consider when implementing the strategy of credit card repayment reminders.

This study credits a novelty in the discourse of data science for Islamic finance practices. Specifically, this study pioneers an example of using data mining to investigate Islamic-moral incentives in credit card debt repayment.

Over time, the concept of word of mouth (WOM) has spread beyond marketing into other disciplines. This is because WOM is important in decision-making at both the individual and organisational levels. Also, people are more likely to trust recommendations from their peers than those from companies. Therefore, the purpose of this study is to investigate the perceived usefulness of WOM messages for small and medium-sized enterprise (SME) suppliers in participating in Tanzanian public procurement opportunities.

The study collected cross-sectional data from 214 SME suppliers who supply common use items to public procuring organisations in Dodoma City, Tanzania. Structural equation modelling was used to test the direct relationships between study variables, and Hayes' PROCESS macro was used to test for the indirect effect of WOM message delivery on WOM attributes and the perceived usefulness of WOM.

WOM attributes that include expertise differential, perceptual homophily, and trustworthiness are related to the perceived usefulness of WOM. Also, WOM message delivery mediates the relationship between the WOM attributes and the perceived usefulness of WOM in enhancing public procurement participation. Therefore, the study's findings revealed that WOM is applicable in the public procurement context, under which public buyers act as senders and suppliers act as receivers. The latter finds out about public procurement opportunities and responds to them, while the former gives suppliers whatever information they need to respond to public procurement tenders that have been advertised.

Because the study was cross-sectional, it was difficult to determine whether the opinions gathered over time remained consistent. Furthermore, only suppliers who are parties to framework contracts under Government Procurement Services Agency were included in the study. Therefore, the sample was limited to only suppliers supplying common use items to various public organisations in Dodoma City, Tanzania.

This paper integrates the concept of WOM from the marketing discipline and public procurement. As a result, the study adds to the understanding of the use of information transmission in terms of the contribution of WOM messages from public buyers to suppliers to enhance small and medium enterprises' participation in public procurement opportunities.