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This study builds on the extant research of the authors on illegal rural enterprise (IRE). However, instead of taking a single or micro case approach within specific sections of the farming and food industries we examine the concept holistically from a macro case perspective. Many IRE crimes simply could not be committed without insider knowledge and complicity, making it essential to appreciate this when researching or investigating such crimes.

Using data from published studies, we introduce the theoretical concept of “Shadow infrastructure” to analyse and explain the prevalence and endurance of such criminal enterprises. Using a multiple case approach, we examine data across the cases to provide an analysis of several industry wide crimes—the illicit halal meat trade; the theft of sheep; the theft of tractors and plant; and the supply of illicit veterinary medicines.

We examine IRE crimes across various sectors to identify commonalities in practice and in relation to business models drawing from a multidisciplinary literature spanning business and criminology. Such enterprises can be are inter-linked. We also provide suggestions on investigating such structures.

We identify academic and practical implications in relation to the investigation of IRE crime and from an academic perspective in relation to researching the phenomenon.

This study combines data from numerous individual studies from a macro perspective to provide practical solutions to a multifaceted problem.

This paper aims to examine the determinants that influence acceptance towards e-wallet apps by extending the technology acceptance model (TAM) among (asnaf), a term used for charity or gift receivers from alms tax distribution institutions also known as donee.

The review of literature and structural equation modelling approach using judgemental sampling on extended TAM and determinants of e-wallet apps’ acceptance related to asnaf (donee) were conducted in a bid to contribute to the factors that are instrumental in determining acceptance of e-wallet services among asnaf.

The findings indicate that the e-wallet app’s service acceptance is determined not only by perceived usefulness, consumer maqasid index and consumer innovativeness but also by subjective norms. On the contrary, consumer maqasid index and perceived ease of use do not lend themselves to be the factor of asnafs’ e-wallet acceptance. The authors extend the TAM model to determine the factors that may be influential in predicting the e-wallet app acceptance by asnaf.

In assessing future outcomes when different sampling techniques are opted for and geographic coverage is expanded, this study should be considered in terms of the limited scope.

This study is intended to serve as a reference for making a significant contribution related to user acceptance factors related to alms tax-based e-wallet apps in asnafs’ context in Malaysia in terms of both theory and practice.

TAM is extended in the context of e-wallet app acceptance among asnafs’. A variable, namely, consumer innovativeness, is tested using the extended TAM model. To the best of the authors’ knowledge, consumer innovativeness in the context of asnafs’ acceptance of e-wallet apps is yet to be tested. Therefore, this paper will be a useful reference for policymakers, technologists, academicians and future researchers.

Tourists with different cultural backgrounds think and behave differently. Accurately capturing and correctly understanding cultural differences will help tourist destinations in product/service planning, marketing communication and attracting and retaining tourists. This research employs Hofstede's cultural dimensions theory to analyse the variations in destination image perceptions of Chinese-speaking and English-speaking tourists to Xiamen, a prominent tourist attraction in China.

The evaluation utilizes a two-stage approach, incorporating LDA and BERT-BILSTM models. By leveraging text mining, sentiment analysis and t-tests, this research investigates the variations in tourists' perceptions of Xiamen across different cultures.

The results reveal that cultural disparities significantly impact tourists' perceived image of Xiamen, particularly regarding their preferences for renowned tourist destinations and the factors influencing their travel experience.

This research pioneers applying natural language processing methods and machine learning techniques to affirm the substantial differences in the perceptions of tourist destinations among Chinese-speaking and English-speaking tourists based on Hofstede's cultural theory. The findings furnish theoretical insights for destination marketing organizations to target diverse cultural tourists through precise marketing strategies and illuminate the practical application of Hofstede's cultural theory in tourism and hospitality.