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The exponential rise of digital payments has underscored the critical importance of digital payment security, particularly in payment gateway systems. This chapter delves into the vulnerabilities within these systems and proposes a comprehensive security enhancement framework to address them. Recent security breaches, such as those at SONY and Ontario’s birth registry, have emphasised the urgent need for improved protective measures. The proposed framework integrates advanced technologies like data encryption, next-generation firewalls (NGFWs), unified threat management (UTM), network traffic analysis, and multi-factor authentication (MFA). It aims not only to defend against current cyber threats but also to remain adaptable to future vulnerabilities, ensuring the integrity, confidentiality, and availability of transactional data. Moreover, aligning with regulatory standards such as the Payment Card Industry Data Security Standard (PCI DSS) and the General Data Protection Regulation (GDPR) is crucial for building trust and ensuring security in the digital transaction ecosystem. This chapter also highlights the importance of balancing security measures with user experience and advocates for user education and user-centric security solutions. Emerging technologies like artificial intelligence (AI) and blockchain are proposed for real-time fraud detection and maintaining immutable transaction records, offering innovative solutions to contemporary security challenges. Empirical analysis supports the efficacy of the proposed framework, showing improvements in data loss prevention, user satisfaction, and fraud mitigation. This framework, termed ‘Guardians of Trust’, represents a paradigm shift in payment gateway security, providing a scalable and forward-looking model that balances robust security protocols with user experience and compliance considerations. This chapter contributes significantly to the academic discourse on digital payment security.

In particular, it is worth mentoring new and more efficient solutions that can meet the increasingly specific needs of each company, especially in food management. A business intelligence (BI) solution can help your food company better understand and manage business processes more effectively. Management information is essential for all levels of an organisation to make quick and correct decisions. However, what exactly is BI, and what can it mean for a food company?

The PRISMA stands for (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and content analysis strategy used the SLR (systematic literature review) methodology to examine 151 papers published in peer-reviewed academic journals and industry reports between 2016 and 2023.

The findings show that artificial intelligence and digitalisation are linked to the UN 2030 Agenda. BI management ranks first (66%), followed by crop and land mapping systems (40%), agricultural machinery monitoring tools (39%) and decision support systems (31%). The road to digital transformation remains extended, with the main impediments being more compatibility between enterprise systems and a shortage of expertise.

The section relating to methodological perspective adopts the PRISMA methodology for systematic review. Interoperability is easily managed by assigning qualified teams to projects. The added value of a consulting firm with extensive project management experience in the food industry is closely related to the results achieved.

BI: What exactly is it, and why a data-driven culture is essential in the food and beverage industry?

This study aims to examine the direct and indirect influence of electronic word of mouth (eWOM) on green cosmetics purchase intention of young Vietnamese female consumers through health concern, environmental concern and the theory of planned behavior (TPB) factors.

Data were collected from a survey of Vietnamese young female consumers that were analyzed using a partial least squares structural equation modeling.

The results reveal that eWOM has a direct effect on consumers’ purchase intention of green cosmetics. Among TPB factors, attitude was a greater influential predictor of purchase intention than subjective norms. However, the influence of perceived behavioral control on purchase intention was not supported. There were significant indirect effects of eWOM on purchase intention through the mediation of health concern, environmental concern and attitude.

Therefore, the findings of this study are relevant for marketers and managers as they provide valuable insights into understanding the motivational factors of consumers’ green cosmetics purchase intention. The results highlighted that eWOM could increase young female consumers’ environmental concern and health concern, which, in turn, influence a positive attitude toward green cosmetics. Hence, eWOM is a powerful vehicle for environmental and health messages; also, it can be an important channel of sensitization toward environmental and health issues and motivation of proenvironmental behavior and healthy lifestyle.

The study contributed to the literature by confirming the utility of the TPB model in predicting young women’s green cosmetics purchases in the context of Vietnam, an emerging market, which has largely been overlooked in the literature. The findings show that eWOM has a direct influence on green cosmetics purchase intentions of young Vietnamese female consumers and indirectly eWOM through health concern, environmental concern and two TPB factors (attitude and subjective norms).

The aim of this study is to empirically investigate the impact of marketing analytics capability on business performance from the perspective of RBV theory.

This study used a survey method to gather information from 225 food processing SMEs registered with the Ghana Enterprise Agency (GEA) in Ghana’s eastern region. A structural equation modeling (SEM) path analysis was used to assess the impact of marketing analytics capability (MAC) on the performance of SMEs.

The results of the study show that MAC significantly and positively affect the financial performance (FP), customer performance (CF), internal business process performance (IBPP) and learning and growth performance (LGP) of Ghanaian SMEs. The findings of this study also illustrated the significance of MAC determinants, including marketing analytics skills (MAS), data resource management (DRM) and data processing capabilities (DPC), in achieving SME success in Ghana.

The research’s conclusions give RBV theory strong credence. The results of this study also provide credence to previous research finding that SMEs should view MAC and its determinants (i.e. DRM, DPC, MAS) as a crucial strategic capability to improve their performance (i.e. FP, CF, IBPP, LGP). With regard to its contribution, this study broadens the body of knowledge on MAC and SME performance, particularly in the context of an emerging economy.

This paper aims to assess the economic impacts of the European Union’s Carbon Border Adjustment Mechanism (CBAM) on Vietnam.

We constructed a general equilibrium model to assess the economic impacts of the CBAM on the macroeconomic indicators of Vietnam. We also constructed a generic partial equilibrium model to provide a zoomed-in view of the impact on each group of CBAM-targeted commodities, which is not possible in the general equilibrium model. Both the general equilibrium and the partial equilibrium models were calibrated with publicly available data and a high number of value sets of hyperparameters to estimate the variations of the estimated impacts.

The results suggest that the current form of the EU’s CBAM is unlikely to produce substantial effects on the overall economy of Vietnam, mainly because the commodities affected by it represent a small portion of Vietnam’s exports. However, at the sectoral level, the CBAM can reduce production outputs and export values of steel, aluminium, and cement.

The CBAM by itself may not lead to significant decreases in greenhouse gas emissions, but it could provide a rationale for implementing carbon pricing strategies, which might result in more significant economic effects and help in reducing greenhouse gas emissions. This highlights the necessity of supplementary policies to tackle global climate change.

We constructed economic models to evaluate the impacts of the European Union’s Carbon Border Adjustment Mechanism on Vietnam, both at the macroeconomic level and zooming in on directly impacted groups of commodities.