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This study aims to quantify the associations among employee’s communication skills (language ability, body language and personal appearance), restaurant image and tourist behaviour.

A survey instrument is used to examine the relationships in the proposed model by using structural equation modelling (SEM) technique. The collected primary data (n = 153) are analysed to test the relationship between exogenous and endogenous constructs expressed in the proposed structural model.

The results revealed that language ability, body language and personal appearance impacted restaurant image, which, in turn, affected tourist behaviour.

This study will contribute a better understanding towards employee’s communication skills in Aqaba city resorts and restaurants.

This study is considered the first in the region that links the tourist image of a restaurant with its employee’s skills and its impact on tourists’ behaviour.

This study aims to investigate the impact of artificial intelligence (AI) on customer loyalty in the luxury fashion market. It explores how AI-driven tools influence customer trust, satisfaction, commitment and engagement, which in turn affect loyalty. By examining these relationships, the study provides insights into the acceptance and effectiveness of AI technologies in enhancing customer loyalty within the luxury fashion sector.

This study employs structural equation modelling (SEM) to analyse data collected from 406 luxury consumers in Iran. The data was gathered using a targeted sampling procedure, leveraging DigiKala’s e-commerce platform. A comprehensive literature review informed the measurement items, and a seven-point Likert scale was used. The methodology includes confirmatory factor analysis (CFA) to assess the reliability and validity of the constructs, followed by hypothesis testing through SEM.

The study reveals that AI significantly enhances customer loyalty in the luxury fashion market by positively influencing trust, satisfaction, commitment and engagement. Satisfaction and engagement were found to be key mediators between AI and loyalty, while trust had no direct impact on loyalty. The results underscore the importance of AI-driven personalized experiences in fostering stronger customer relationships and loyalty.

This study is one of the first to explore the impact of AI on customer loyalty in the luxury fashion market, using a comprehensive model that includes trust, satisfaction, commitment and engagement as mediators. It extends the stimulus-organism-response (SOR) and technology acceptance model (TAM) frameworks, offering valuable insights for luxury brands on how AI can be leveraged to enhance customer relationships and loyalty.

The unpredictable distribution of globalization has directed the world economy and revealed the need to establish cooperation in all business processes. This global structure also highlights the necessity of designing an agile supply chain that is capable of continuous information sharing during end-to-end transportation for the purpose of creating sustainable connections. In this process, various strategies enhanced with contemporary information and communication technologies have been developed to create a fast and accurate data-sharing network between logistics service providers and supply chain parties. However, unlike the short-term interruptions experienced in the past, COVID-19 has caused unprecedented problems in the dynamics of most economies. In eliminating these problems, it has been seen that information communication technologies, which provide the advantage of digital visibility in normal operations, need to be redesigned with the technology of the autonomous age. To meet this requirement, Industry 4.0, a revolutionary conceptual trend that started roughly a decade ago but that has become considerably more widespread during COVID-19, has been integrated into business models as a key concept that governs intelligent transformation in the chain. This process, which is today considered a compulsory intelligent transformation rather than an alternative method, has however led to some conflicts, especially in adaptation, expertise, and security subjects. This chapter of the book evaluates, within the scope of cybersecurity and workforce in logistics services, the conflicts created by the digital solution methods that have been integrated into business models to reduce the negative effects of COVID-19.

COVID-19 pandemic has impacted global human lives, killing millions and attacking the real economy to its core. United Nations has called for global solidarity to overcome this unprecedented disaster. Having said that, zakat has been utilized to respond to this ongoing suffering in Muslim countries. This chapter explore zakat utilization for COVID-19 under the shariah perspective and discuss the role of zakat to respond to the pandemic in Muslim countries. A qualitative methodology including conceptual and content analysis is applied to conduct this study. The findings show that most sharia scholars agreed to utilize zakat for the COVID-19 pandemic and endorse advance zakat payment. Moreover, zakat has been disbursed mainly to fulfil basic needs, support emergency health services, sustain education activities, recover economic impact and maintain dakwah programme. The global zakat institutions have also started up the international initiative to respond to this pandemic. This study contributes to the academia on showing how zakat is a conceivable and reliable instrument to give immediate response to this pandemic in Muslim countries. The best practices found in this study are worthy for zakat institutions to continue their programme under this pandemic and be resilient for the next global scale of disasters.

This study aims to propose Islamic solutions to the Covid-19 health and economic crises, specifically using Islamic social finance (ISF) instruments, including zakat, infaq and waqf.

This study applies the qualitative content analysis method, guided by a model of composite approaches of poverty alleviation in Islam, integrated Islamic commercial and social finance (IICSF) and crisis management of Umar bin Khattab, to construct various programs and/or policy actions toward economic recovery in Indonesia.

The results show that ISF with its instruments, especially zakat, infaq and waqf could help the government and the economy to recover from the crisis. The proposed solutions include: save lives, including medical assistance using zakat-infaq and health-care waqf using waqf; save households, by creating a social safety net and graduation program using zakat-infaq; save businesses, especially micro-small enterprises (MSEs), through financial and business assistance (especially digital marketing) leveraging zakat-infaq-waqf and save financial institutions, especially micro-small financial institutions, by the development of cash waqf and the adoption of fintech and IICSF, especially in Islamic financial institutions targeting MSEs.

This study is exploratory in nature, which needs further investigations using more sophisticated qualitative and/or quantitative methods.

If the above programs using ISF instruments are implemented, the economic surplus would be re-established and the acceleration of economic recovery can be realized.

The successful adoption of ISF could at the same time reduce poverty, accelerate MSEs development and improve equitable well-being.

The Covid-19 pandemic has caused health, economic and social problems, which must be solved holistically, including ISF within IICSF.

Showrooming presents a complex and evolving challenge to retail managers, as it signifies the emergence of new forms of exchange rules. The purpose of this research is to investigate how factors responsible for information search and evaluation affect showrooming and also consider the consumer mindset as a moderator.

This research undertakes three experimental designs to investigate how the push (i.e. assortment size), pull (i.e. price discount), and mooring (i.e. sunk cost) factors influence consumers' showrooming intention. Specifically, consumers' maximizing tendency plays the role of moderator.

The results reveal that push, pull, and mooring factors are significantly related to consumers' showrooming intention. Furthermore, the findings show that maximizers have higher showrooming intention than satisficers in the context of the push, pull, and mooring factors.

By integrating the push-pull-mooring framework and the maximizing mindset theory, this research proposes a novel research model and the empirical testing results support six hypotheses. The findings add to the body of knowledge in showrooming behavior by taking consumer mindset into account. The results also provide implications for practitioners to develop their retail strategies.

Fractional Fokker-Planck equation (FFPE) and time fractional coupled Boussinesq-Burger equations (TFCBBEs) play important roles in the fields of solute transport, fluid dynamics, respectively. Although there are many methods for solving the approximate solution, simple and effective methods are more preferred. This paper aims to utilize Laplace Adomian decomposition method (LADM) to construct approximate solutions for these two types of equations and gives some examples of numerical calculations, which can prove the validity of LADM by comparing the error between the calculated results and the exact solution.

This paper analyzes and investigates the time-space fractional partial differential equations based on the LADM method in the sense of Caputo fractional derivative, which is a combination of the Laplace transform and the Adomian decomposition method. LADM method was first proposed by Khuri in 2001. Many partial differential equations which can describe the physical phenomena are solved by applying LADM and it has been used extensively to solve approximate solutions of partial differential and fractional partial differential equations.

This paper obtained an approximate solution to the FFPE and TFCBBEs by using the LADM. A number of numerical examples and graphs are used to compare the errors between the results and the exact solutions. The results show that LADM is a simple and effective mathematical technique to construct the approximate solutions of nonlinear time-space fractional equations in this work.

This paper verifies the effectiveness of this method by using the LADM to solve the FFPE and TFCBBEs. In addition, these two equations are very meaningful, and this paper will be helpful in the study of atmospheric diffusion, shallow water waves and other areas. And this paper also generalizes the drift and diffusion terms of the FFPE equation to the general form, which provides a great convenience for our future studies.

The paper aims to analyze the potential of artificial intelligence (AI) in enhancing marketing capabilities for Indian fast-moving consumer goods (FMCG) firms, with appropriate emphasis on dynamic capabilities (DC). By integrating AI into their operations, companies can enhance diverse marketing practices, leading to improved efficiency and effectiveness. In addition, the study offers valuable insights and guidance for effectively implementing AI in marketing strategies.

In-depth interviews of 26 seasoned professionals from various positions in the Indian FMCG sector were conducted for the study. A systematic approach of coding that includes open, axial and selective coding was made to recognize the themes that represent AI-enabled marketing practices. This approach ensured that the themes were precisely identified and comprehensively analyzed. Interviews followed by a rigorous coding process provide valuable insights into the practical implementation of AI-enabled marketing practices for the Indian FMCG industry.

The study’s results underscore the importance of AI in enhancing marketing practices for FMCG firms, particularly in four critical areas: personalization, consumer engagement, marketing automation and strategic goals. By adopting AI in these areas, Indian FMCG firms can significantly enhance their marketing capabilities, increasing efficiency, effectiveness and gaining a competitive advantage.

The study uses qualitative data analysis to explain how DC through AI technologies can enhance digital marketing practices for Indian FMCG organizations. Furthermore, the study provides valuable insights into how AI technologies can improve marketing capabilities and emphasizes the importance of DC. The study also proposes a framework for AI-enabled Marketing 4.0 that can guide FMCG firms seeking to leverage AI technologies to enhance their marketing practices.

This study outlines the potential for enhancing marketing practices by adapting AI in the Marketing 4.0 environment for Indian FMCG companies, highlighting the importance of DC in achieving this goal.

The paper aims to conceptually exhibit modern marketing theory from an Islamic perspective.

The paper is conceptual and qualitative in nature. It originated from two mainstream publications. The first belongs to the ones which discuss Islamic economics and Islamic banking and finance. The second source comes from those which discuss Islamic business ethics. Both sources are essential in developing the conceptual theory of Islamic marketing.

Religious teachings, at least Islam, could be applied in the realm of modern marketing theory. Though not all of its elements could be applied in Islamic society, modern marketing theory will provide some elements which could be utilised in developing Islamic marketing theory.

The lack of papers on Islamic marketing makes the depth of discussion rather limited.

Although several papers already exist in discussing Islamic business ethics with some elements of the marketing mix, it could be argued that this paper is the first of its kind which specifically discusses the concept of modern marketing from an Islamic perspective.