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This study aims to investigate the impact of service quality (SQ), perceived value (PV) and consumer satisfaction on Thai street food, with customer satisfaction (CS) as a mediator for customer loyalty and repurchase intention (RI). It also explores how consumer trust (CT) in Thai street food safety moderates these relationships.

Structural equation modelling (SEM) was utilised to analyse the complex interrelationships between various constructs. Multi-group analyses were conducted to investigate the moderating effects of CT on the structural model, considering two distinct groups based on trust levels: low and high.

The findings revealed that SQ and PV significantly influenced CS and behavioural intention, while the perceived quality of Thai street food had no significant impact on post-COVID-19 consumer satisfaction. The study highlighted the critical role of CT in moderating the relationships between SQ, PV and CS, with distinct effects observed in groups with varying trust levels.

The research emphasises the importance of enhancing SQ and delivering value to customers in the context of Thai street food, which can contribute to increased CS, RI and positive word-of-mouth. Furthermore, the study underscores the critical role of building CT in fostering enduring customer relationships and promoting consumer satisfaction and loyalty.

This research offers valuable insights into consumer behaviour and decision-making processes, particularly within the realm of Thai street food. It underscores the significance of understanding and nurturing CT, especially in the post-COVID-19 landscape, emphasising the need for effective business strategies and consumer engagement.

This study evaluates the relative preference for local foods among foreign tourists. It also assessed how the sociodemographic profiles of tourists influence their local food preferences.

This research utilized a mixed-methods approach. The initial qualitative analysis phase involved semi-structured, in-depth interviews with stakeholders in Fiji’s local food sector, providing feedback on tourists’ preferred dishes. In the second phase, 204 foreign tourists were surveyed through the location intercept approach at various local restaurants, street food joints and eateries across Fiji. The preferences of these foreign tourists for the local food were subsequently analyzed utilizing the analytical hierarchical process (AHP) model and Chi-square statistics.

This research identified 25 local food dishes most preferred by foreign tourists. A pairwise comparison matrix revealed that “Kokoda” was most preferred, while “Tuna Ika Vakalolo” was the least preferred, and the normalized matrix presented the estimated overall priorities of the local foods based on taste and flavor. Among all the factors analyzed for their potential influence on the local food preferences of foreign tourists, “education attainment” and “marital status” were found to have no significant influence.

This study highlights the varied local dishes preferred by tourists, assessed through the AHP model, and provides the sociodemographic factors influencing these preferences. By identifying and presenting local Fijian dishes across regions and examining sociodemographics’ impact on food preference, this research provides invaluable implications for significantly benefiting the local food vending sector.

The authors examine whether the duration of performance shortfall in the firm impacts the real earnings management.

We find the results in the context of India, an emerging market, on a large sample set of 15,011 firm-year observations during 2006–2020.

We find that when managers continue to face short-term performance pressures, they shift their focus away from aspirational levels, prefer not to engage in strategic actions to address performance shortfalls and engage in opaque actions of real earnings management. We discover that this baseline relationship for business group-affiliated firms is stronger; however, the moderation effect is weaker under stronger corporate governance and the involvement of high-quality auditors.

The study suggests that the governing council of firms, such as the board of directors, must pay additional attention to underperforming firms, as a longer duration of performance shortfall may induce firms to engage in earnings management, which is detrimental to the long-term viability of organizations. Government authorities should pay close attention to the choices made by managers, especially when their performance is subpar. Furthermore, the government has the option to implement policies or offer financial assistance, such as special funds, to incentivize companies to refrain from participating in manipulation activities.

This is the first study to examine corporate misconduct through the lens of the “threat rigidity hypothesis,” which has significant implications for the management literature.

We focus on multi-level heterogeneity in board interlocks by accounting for the experience of the “tied-to” firm and the efficacy of the channel for knowledge transfer. Specifically, we study the role of board interlocks of a focal firm with cross-border acquirers and their implications on the entry mode decision (greenfield vs acquisitions). While studying board interlocks, we also consider the type of directors (inside vs independent) that form the interlocks. We situate our research within the context of knowledge-intensive industries in emerging markets. By focusing on heterogeneity in board interlocks, we consider the interplay between experiential and vicarious learning and its implication on a firm’s foreign market entry mode choice.

We conduct our analysis on a propriety dataset of 450 foreign market entries by Indian firms belonging to knowledge-intensive industries during the period 2003 to 2013. We use a binomial logistic regression model to analyze the choice between greenfield ventures and cross-border acquisitions.

We find that firms are more likely to choose cross-border acquisitions over greenfield ventures when connected to other cross-border acquirers through inside and independent director interlocks. However, this effect is more substantial for inside director interlocks. Foreign institutional investors’ shareholding weakens the impact of inside director interlocks but strengthens the effect of independent director interlocks. A firm’s cross-border acquisition experience weakens the impact of independent director interlocks. Still, it enhances the effect of inside director interlocks on the likelihood of choosing cross-border acquisitions over greenfield ventures.

The study highlights heterogeneity in board interlocks and the effectiveness of channels of transfer of learning. It also highlights boundary conditions of board interlocks’ effectiveness in shaping the entry mode decision by elucidating the biases within different actors in the organizational learning process.

Accurate solar photovoltaic models (SPVM) are critical for optimizing solar photovoltaic (PV) capacity to convert sunlight into electricity. The simulation and design of PV systems rely on estimating unknown constraints from solar photovoltaic (SPV) cells. Each parameter plays a crucial task in the output properties of an SPV under actual environmental conditions. Optimizing the unknown constraints of the SPVM is not an easy task due to the nonlinear characteristics of the PV cell. This study aims to develop a novel metaheuristic algorithm, enhanced dynamic inertia particle swarm optimization (EDIPSO) algorithm with velocity clamping, to establish all the seven and five constraints of the two-diode model (TDM) and one-diode model (ODM).

In complex parameter spaces, the conventional particle swarm optimization (PSO) approach typically leads to poor convergence because it fails to balance exploration and exploitation. The proposed approach is an EDIPSO with velocity clamping to minimize the possibility of overshooting possible solutions and improve stability. Velocity clamping is also used to prevent particle velocities from rising over specified limitations. Beginning the process with a large inertia weight to promote exploration and progressively decreasing it to improve exploitation, leading to a thorough analysis of the search space. The algorithm is implemented to investigate the accuracy of estimated constraint values of RTC-France (RTC-F) solar cell, Photo watt-PWP 201 SPV module (PWP 201 SPV), KC 200GT SPV module (KC 200 GT SPV) for ODM and TDM.

The proposed approach is used to extract the seven and five constraints of the TDM and ODM under standard test conditions for three different SPV modules. Thorough simulation and statistical analysis indicate that the EDIPSO with velocity clamping may outperform other cutting-edge optimization algorithms exclusively regarding accuracy, computational time and reliability.

An enhanced dynamic inertia PSO is suggested for determining the parameters of the TDM and ODM in SPV modules. This method specifically accounts for the recombination saturation current within the p–n junction’s depletion region, without overlooking or assuming away any parameters, thereby achieving greater accuracy. When comparing the estimated constraints of TDM and ODM for various SPVs, EDIPSO almost precisely aligns the data from the proposed model with the practical data. Thus, the proposed method for calculating the SPV model parameter may exhibit to be a feasible and efficient solution.

Across the globe, cities have contemplated practical measures to handle sustainable development issues which vary from environmental, social and to economic problems. Despite this, Africa has continued to fall behind in the implementation of smart city development. Yet, one of Africa's most cherished goals is achieving sustainable human settlements to keep up with the present and future urbanisation rates. The backbone to achieving sustainable human settlements is having efficient, well-capacitated, municipal systems and committed public servants. African Governments, however, continue to have failing municipalities with corruption being rife in both small towns and cities, yet there are chances to evolve and become smarter. Blockchain technology is a novel and disruptive innovation that has the potential to empower smart cities by providing a platform for interoperability, coordination and governance among multiple smart city initiatives and actors. However, the adoption of blockchain technology also faces several challenges and barriers to its adoption and implementation in smart cities, especially in Africa, where there is lack of awareness, regulation, infrastructure and access to ICT. This chapter examines the current state, opportunities and challenges in the adoption of blockchain technology in smart city development in Africa, a continent that faces multiple urbanisation issues, such as poverty, inequality, environmental degradation and lack of infrastructure. As such, the study adopts two theories, the diffusion of innovation (DOI) and the technology–organisation–environment (TOE) framework to view the use and opportunities placed by adopting blockchain technology through municipal stakeholders and citizens to enhance smart city development.

Consumers are increasingly shopping online, and they want reliable and trustworthy information about the quality of goods and all members of the distribution chain. Blockchain and gamification are two technologies that can drive digital transformation across various industries. The current study investigates the application of blockchain and gamification in emerging modern markets. Gamification is a viable method for familiarising individuals with blockchain technology. It is an example of an idea that might be utilised to build a setting as a bargaining strategy. The goal of this research is to investigate how gamification components might be used to engage individuals in blockchain technology and foster a positive attitude towards future use. In this review article, we did a thorough study of the research articles published between 2018 and 2023 on various web search engines for scholarly literature and academic resources. This comprehensive review investigates the incorporation of blockchain technology and gamification in emerging markets. Blockchain, known for its decentralised and secure nature, has the potential to transform a wide range of industries, including marketing. Similarly, gamification has grown in favour as a method of engaging and motivating customers. Marketers may use the benefits of both approaches to build unique and effective marketing campaigns by integrating blockchain and gamification. This review focuses on the digital transformation with focus on major concepts, benefits, problems and real-world applications of using blockchain and gamification into modern marketing techniques in emerging markets.

In a context where the promotion of a more sustainable agriculture is clearly aimed at, the paradoxical combination of sustainable agricultural practices (SAP) with chemical pesticides use instead of biological pest management techniques is recurrent in Sub-Saharan African (SSA) countries like Burkina Faso. Chemical pesticides are harmful to the environment and health. This paper aims to analyze the role of farmer education on the mode of adoption of SAP.

An endogenous treatment effect model is used with survey data on 1,898 rural households in Burkina Faso.

The results show a positive causal effect of farmer education on sustainable and chemical pesticide-free agriculture adoption.

Formal education appears to be general. This research could be extended to consider the role of training or extension services. More detailed results, focusing on spatial effects, could reinforce those of the present research.

Unlike previous studies, this paper addresses for the first time the paradoxical behavior of combining SAP with chemical pesticides use. It shows that farmer education contributes to explain it and is therefore a determining factor for a more sustainable agriculture.

The discourse traverses the intricate landscape of the metaverse, exploring its evolution, intricacies, and the symbiotic integration of artificial intelligence (AI). The metaverse, a virtual realm where individuals interact with digital entities, burgeons from a decades-old concept to a contemporary reality, captivating attention with its immersive potential. The union of AI and the metaverse heralds unprecedented possibilities and challenges. It fuels personalized recommendations, realistic avatars, intelligent Non-Playable Character (NPCs), and predictive analytics. However, concerns loom, spanning addiction, privacy, and security, as users immerse themselves in virtual realms, potentially neglecting real-world responsibilities and sharing sensitive information has been discussed in this chapter. The narrative further delves into the metaverse's anatomy, delineating its infrastructure, hardware, software, content creation, and commerce. The integration of AI into metaverse security epitomizes a confluence of innovation and growth. Balancing the potential benefits and risks, stakeholders embark on a journey toward a secure, immersive digital realm. The discourse advocates for proactive and responsible AI usage, encompassing transparency, accountability, and trustworthiness. Regulatory frameworks and standards emerge as essential guardrails, protecting user privacy and forestalling AI misuse.

Peer-to-peer lending has emerged as a promising alternative investment avenue globally. This study explores the variables influencing investors' intention in peer-to-peer lending. Studying these factors is crucial for inspiring investor motivation, which leads to the growth of peer-to-peer lending platforms in India.

The research utilizes information gathered from 293 investors of the Rang de platform through a questionnaire. It employs ordinal logistic regression to assess how demographic characteristics, investor experience, social projects and investment factors influence the study’s outcomes.

The research indicates that the education qualification and income level of the investors are significant demographic variables in their investment decisions. Moreover, social projects, the experience of the investors and investment factors affect their intent to invest more in peer-to-peer lending projects.

It helps stakeholders and borrowers of crowdfunding platforms think about these aspects when creating plans to bring in and keep investors. This approach also enhances the openness and dependability of lending processes.

This research sheds light on Indian investors' behavior toward peer-to-peer lending platforms and includes new investment factors like project categories and impact partners that other researchers did not identify.