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The purpose of this paper is to systematically analyze the literature around regulatory compliance and market manipulation in capital markets through the use of bibliometrics and propose future research directions. Under the domain of capital markets, this theme is a niche area of research where greater academic investigations are required. Most of the research is fragmented and limited to a few conventional aspects only. To address this gap, this study engages in a large-scale systematic literature review approach to collect and analyze the research corpus in the post-2000 era.

The big data corpus comprising research articles has been extracted from the scientific Scopus database and analyzed using the VoSviewer application. The literature around the subject has been presented using bibliometrics to give useful insights on the most popular research work and articles, top contributing journals, authors, institutions and countries leading to identification of gaps and potential research areas.

Based on the review, this study concludes that, even in an era of global market integration and disruptive technological advancements, many important aspects of this subject remain significantly underexplored. Over the past two decades, research has lagged behind the evolution of capital market crime and market regulations. Finally, based on the findings, the study suggests important future research directions as well as a few research questions. This includes market manipulation, market regulations and new-age technologies, all of which could be very useful to researchers in this field and generate key inputs for stock market regulators.

The limitation of this research is that it is based on Scopus database so the possibility of omission of some literature cannot be completely ruled out. More advanced machine learning techniques could be applied to decode the finer aspects of the studies undertaken so far.

Increased integration among global markets, fast-paced technological disruptions and complexity of financial crimes in stock markets have put immense pressure on market regulators. As economies and equity markets evolve, good research investigations can aid in a better understanding of market manipulation and regulatory compliance. The proposed research directions will be very useful to researchers in this field as well as generate key inputs for stock market regulators to deal with market misbehavior.

This study has adopted a period-wise broad-based scientific approach to identify some of the most pertinent gaps in the subject and has proposed practical areas of study to strengthen the literature in the said field.

Given the scarcity of studies regarding religious food as a destination attraction and limited research on tourist halal food experience, this study aims to explore and compare halal food experience perceived by Muslim and non-Muslim tourists in a non-Islamic destination.

This study was carried out in a halal food street in Yuanjia Village, China. It used a qualitative approach and interviewed 16 Muslim tourists and 20 non-Muslim tourists.

Six themes and 18 attributes of halal food experience were identified. The findings revealed that Muslim tourists saw the reassuring options and religious value of halal food as important experiences. By contrast, the experiences of abundant choices, value for money, sensory pleasure and unique charm were frequently mentioned by non-Muslim tourists. The nature of halal food, the context of China (i.e. Chinese halal food culture) and the feature of research site (i.e. food operation of Yuanjia Village) work together to create such experiences.

To the best of the authors’ knowledge, this is one of the first studies to explore and compare halal food experiences of Muslim and non-Muslim tourists in a non-Islamic country (China). This study suggests that halal food could be an appealing destination attraction, even in non-Islamic destinations. Thus, this study contributes to a better understanding of the halal food experiences and assists destination marketers in promoting halal food.

This study concentrates on assessing the research productivity in the domain of social media security in the past decades. The purpose of this study is to conduct a comprehensive bibliometric review on social media using various bibliometric indicators.

A total of 8,121 scientific publications were retrieved from Scopus database from period 1998 to 2021 using associated keyword search. This study also used VOSviewer^© tool to evaluate the network visualisation.

The result of this study revealed that there is a steady growth of annual publications except for the years 2015 and 2016. A total of 8,121 scientific publications and 80,454 total citations were found with 11.2 average citations per publication. The USA, China and India were top productive countries in terms of publishing research in the field; Chinese Academy of Sciences secured top position with 126 publications in highly productive organisation in the domain. The lecture notes in computer science from Springer Nature received a highly produced title with 553 publications and 4,453 total citations. For co-occurrence of author’s keywords, network visualisation analysis revealed that “Social Media”, “Social Network”, “Security”, “Privacy” and “Trust” found maximum occurrence in the domain of social media security.

This study provides comprehensive research status of social media security by performing a bibliometric analysis. The findings of this study will help relevant researchers to understand the research trend, pursue scientific collaborators and enhance research topic preferences.

The rareness of this study, detailed bibliometric analysis on the domain of social media security, is proven using numerous bibliometric indicators and application of VOSviewer in the domain.

Every day, small and big incidents happen all over the world, and given the human, financial and spiritual damage they cause, proper planning should be sought to deal with them so they can be appropriately managed in times of crisis. This study aims to examine humanitarian supply chain models.

A new model is developed to pursue the necessary relations in an optimal way that will minimize human, financial and moral losses. In this developed model, in order to optimize the problem and minimize the amount of human and financial losses, the following subjects have been applied: magnitude of the areas in which an accident may occur as obtained by multiple attribute decision-making methods, the distances between relief centers, the number of available rescuers, the number of rescuers required and the risk level of each patient which is determined using previous data and machine learning (ML) algorithms.

For this purpose, a case study in the east of Tehran has been conducted. According to the results obtained from the algorithms, problem modeling and case study, the accuracy of the proposed model is evaluated very well.

Obtaining each injured person's priority using ML techniques and each area's importance or risk level, besides developing a bi-objective mathematical model and using multiple attribute decision-making methods, make this study unique among very few studies that concern ML in the humanitarian supply chain. Moreover, the findings validate the results and the model's functionality very well.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

This study investigates the influence of corporate income tax on two corporate financial decisions — dividend and capital structure policies, particularly for Shariah compliant companies in Malaysia.

The study considered data from a sample of 529 Malaysian listed companies from four industrial sectors from 2007–2021 (6,746 company-year observations, before eliminating outliers). Panel models such as Fixed Effect and Random effect models were used. The study specifically tested the effect of corporate income tax on dividend and capital structure policies for Shariah compliant companies (3,148 observations) and controlled for industrial sectors.

(1) Firms are mostly Shariah-compliant, less liquid, less profitable and smaller in size, (2) Broadly when analysed together, tax has no impact on debt-equity ratio while it has an impact on dividend per share, (3) However, when tested separately for Shariah compliant companies, the influence of effective tax on capital structure is very evident but not for dividend and (4) influence of industrial sector on the relationship between corporate tax and capital structure and dividend policy is significant. Results indicate that Shariah firms might be raising debt to gain tax advantage. Companies in general pay dividends to avoid reputational damage.

This study assumes that leverage and dividend policy decisions are the main outcomes of the changing tax policies, while it seems that there could be other important outcomes that can be tested in future research. The study also shows the changing tax regimes of different ASEAN countries but they have not been tested to see the differences between countries. It will be indeed interesting for future researchers to focus on this aspect.

The findings contribute to the literature on tax planning of the Shariah-compliant firms, a high growth business segment in the Asian context. The study discussed potential tax-based Islamic market product development.

COVID-19 has made businesses increasingly dependent on technology to be competitive and efficient. Small and medium enterprises (SME) digitalisation and innovation research are widespread. SME digital transformation and innovation require government policies, initiatives and assistance. How the government can help SMEs achieve these goals is unclear. So, this paper aims to investigate how government policy may assist Vietnamese SMEs to boost innovation performance and digital transformation.

The study will take a quantitative approach, with questionnaires distributed to 659 respondents from SMEs in Vietnam through snowball and convenience sampling procedures. The structural equational modelling method is used for data analysis.

The study indicated that government policies supported Vietnamese SMEs’ innovation and information technology (IT) capabilities. Government policy assistance also boosted IT capabilities and innovation. Furthermore, mediation effects show that digital transformation fully mediates the relationship between innovativeness and firm performance, whereas IT capabilities partially mediate this relationship.

Further research that replicates the findings and analyses contextual heterogeneities between nations is advised because Vietnam’s pandemic setting was both similar and dissimilar.

The study demonstrated government-company interactions through supportive policy. It investigated whether SMEs seeking digital transformation and innovativeness might gain competitive benefits by implementing effective knowledge management and enhancing their IT capabilities.

A resource-based theoretical framework is extended to study how innovation, public policy and digital transformation for SMEs interact. The study confirms government policy strongly influences enterprises’ digital development. Specifically, the new mediating effects of IT capabilities and digital transformation are explored and provide new insights into the existing literature.

This study aims to understand how organizations in the service industry can encourage the use of enterprise social networks (ESNs) for knowledge sharing, focusing on the concepts of intra-organizational trust and governance.

The authors gathered data through an online survey of 104 participants from the financial services industry. Data were analyzed using structural equation modelling to test the proposed model and evaluate the constructs’ reliability and validity.

The findings of the survey data indicate that intra-organizational trust and governance are related to the use of ESN for knowledge sharing to enhance service innovation. Further, the findings suggest that, although trust directly affects service innovation, using ESN for knowledge sharing partially mediates the relationship between trust and service innovation. The findings also reveal that governance significantly moderates the relationship between ESN for knowledge sharing and innovation.

This paper provides insights into the relationship between trust, knowledge sharing and innovation. The novelty of this study demonstrates that governance strengthens the relationship between ESN for knowledge sharing and innovation. Further, the study suggests that firms using or intending to use ESNs could keep track of the evolving nature of ESNs, develop an open culture and create a trusted environment in their organizations.

We form portfolios based on return and liquidity and examine the effects of liquidity and other risk factors on asset pricing in the Chinese stock market. Our results show that the past loser-and-illiquid stock portfolios tend to outperform the past winner-and-liquid stock portfolios in the 1–12 months holding period. The excess return is significantly associated with the market-wide liquidity factor even when we control the three Fama-French and momentum factors. Cross-sectionally, the liquidity beta significantly affects the excess return even with control of other risk betas and other traditional liquidity proxies.

The purpose of this paper is to explore a new approach to solve the problem of positive and negative offset in the calculation process of integral elements, then propose a series of new grey relational degree model for cross sequences.

The definitions of cross sequences and area elements have been proposed at first. Then the concept of difference degree between sequences has been put forward. Based on the definition of difference degree between sequences, various modified grey relational degree models for cross sequences have been proposed to solve the measurement problem of cross sequence correlation relationships.

(1) The new definition of cross sequences; (2) The area element; (3) Various modified grey relational degree models for cross sequences based on the definition of difference degree between sequences.

The grey relational analysis model of cross sequences is a difficult problem in grey relational analysis. The new model proposed in this article can effectively avoid the calculation deviation of grey relational analysis model for cross sequences, and reasonably measure the correlation between cross sequences. The new model was used to analyse the food consumer price index in Shaanxi Province, clarifying the relationship between different types of food consumer price indices, some interesting results that are not completely consistent with general economic theory were obtained.

The new definition of cross sequences, the area element and various modified grey relational degree models for cross sequences were proposed.