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The study aims to develop a model that supports the application of data science techniques for real estate professionals in the fourth industrial revolution (4IR) era. The present 4IR era gave birth to big data sets and is beyond real estate professionals' analysis techniques. This has led to a situation where most real estate professionals rely on their intuition while neglecting a rigorous analysis for real estate investment appraisals. The heavy reliance on their intuition has been responsible for the under-performance of real estate investment, especially in Africa.

This study utilised a survey questionnaire to randomly source data from real estate professionals. The questionnaire was analysed using a combination of Statistical package for social science (SPSS) V24 and Analysis of a Moment Structures (AMOS) graphics V27 software. Exploratory factor analysis was employed to break down the variables (drivers) into meaningful dimensions helpful in developing the conceptual framework. The framework was validated using covariance-based structural equation modelling. The model was validated using fit indices like discriminant validity, standardised root mean square (SRMR), comparative fit index (CFI), Normed Fit Index (NFI), etc.

The model revealed that an inclusive educational system, decentralised real estate market and data management system are the major drivers for applying data science techniques to real estate professionals. Also, real estate professionals' application of the drivers will guarantee an effective data analysis of real estate investments.

Numerous studies have clamoured for adopting data science techniques for real estate professionals. There is a lack of studies on the drivers that will guarantee the successful adoption of data science techniques. A modern form of data analysis for real estate professionals was also proposed in the study.

This study aims to explore the connection between demographic traits and the choice of attraction patterns among international repeat tourists.

The study employed a questionnaire survey to collect data from 1550 international repeat tourists who visited Tanzania between November 2022 and July 2023. Convenient sampling was employed as tourists were selected from the three international airports of Tanzania, namely Kilimanjaro International Airport, Julius Nyerere International Airport, and Abeid Aman Karume International Airport. A multinomial logistic regression model was used to examine the impact of socio-demographic characteristics on the selection of attraction patterns among international repeat tourists.

The study revealed that demographic factors, including age, marital status, income level, occupation, and education level, exhibit statistically significant correlations with preferences for distinct attraction patterns. This significance was established through a p-value of less than 0.05 for all the aforementioned variables.

This study is primarily focused on international repeat tourists, thereby limiting insights into the preferences of domestic tourists. To better inform strategies aimed at attracting a larger domestic tourist base, future research may prioritize the investigation of choice of attractions patterns among domestic tourists in relation to their demographic characteristics.

This study contributes to the nuanced understanding of international tourist behavior by unraveling the extent to which demographic traits impact tourists’ choices of attraction patterns, thereby providing insights crucial for effective marketing strategies, improved visitor experiences, and sustainable tourism development strategies.

This study investigates the relationship between feelings of loneliness in the workplace, life satisfaction, affect, hope and expressivity among hotel employees.

The research model was tested via structural equation modeling based on the empirical data collected from hotel employees in Antalya, Turkey.

The research findings suggest that emotional deprivation and social companionship have a significant impact on life satisfaction, that life satisfaction has a significant impact on positive and negative emotions, and that positive and negative emotions have the same impact on pathways and agencies.

The research findings should assist researchers and practitioners to understand the behaviors of hotel employees in continuous interaction and relationship with individuals to motivate them while providing more effective services.

The aim of this paper is to improve the understanding of strategies for how established companies can respond to disruptive innovation, handle increasing complexity, facilitate entrepreneurial culture and processes and successfully manage organizational ambidexterity.

A qualitative multiple-case study was conducted to explore successful practices of innovation ambidexterity (IA) and their organizational design, entrepreneurial culture and mindset, processes and leadership. Two internationally established firms that have launched and established IA programs provided deep insight, revealing their strategy and learning on the path toward effective IA.

The findings show that accepting and managing the inherent complexity increases within an ambidextrous organization strategy is a decisive factor in achieving effective IA. As a result, segmenting small organizational units and granting them extensive autonomy is proposed for managing the complexity of an organization while increasing its effectiveness. Furthermore, it is shown that this helps foster entrepreneurial culture, mindsets and processes as additional mediators for achieving effective IA. Coaching, empowerment and trust were identified as key factors of ambidextrous leadership values that encourage entrepreneurial behavior and decision-making.

To the best of the authors knowledge the first study connecting the research fields of complexity management, organizational ambidexterity theory and entrepreneurial culture while applying the fundamentals of systems theory to propose a practical management framework for successfully responding to disruptive innovation.

This is a general review study aiming to specify the key customer-based factors and technologies that influence the value co-creation (VCC) process through artificial intelligence (AI) and automation in the hospitality and tourism industry.

The study uses a theory-based general literature review approach to explore key customer-based factors and technologies influencing VCC in the tourism industry. By reviewing the relevant literature, the authors conclude a theoretical framework postulating the determinants of VCC in the AI-driven tourism industry.

This paper identifies customers' perceptions, attitudes, trust, social influence, hedonic motivations, anthropomorphism and prior experience as customer-based factors to VCC through the use of AI. Service robots, AI-enabled self-service kiosks, chatbots, metaversal tourism and new reality, machine learning (ML) and natural language processing (NLP) are technologies that influence VCC.

The results of this research inform a theoretical framework articulating the human and AI elements for future research set to expand the models predicting VCC in the tourism industry.

Few studies have examined consumer-related factors that influence their participation in the VCC process through automation and AI.

The climate crisis presents a global threat. Research shows the necessity of joint communication efforts across different arenas—media, politics, business, academia and protest—to address this threat. However, communication about social change in response to the climate crisis comes with challenges. These challenges manifest, among others, in public accusations of inconsistency in terms of hypocrisy and incapability against self-declared change agents in different arenas. This increasingly turns public climate communication into a “blame game”.

Strategic communication scholarship has started to engage in this debate, thereby acknowledging climate communication as an arena-spanning, necessarily contested issue. Still, a systematic overview of specific inconsistency accusations in different public arenas is lacking. This conceptual article provides an overview based on a macro-focused public arena approach and decoupling scholarship.

Drawing on a systematic literature review of climate-related strategic communication scholarship and key debates from climate communication research in neighboring domains, the authors develop a framework mapping how inconsistency accusations of hypocrisy and incapacity, that is, policy–practice and means–ends decoupling, manifest in different climate communication arenas.

This framework creates awareness for the shared challenge of decoupling accusations across different climate communication arenas, underscoring the necessity of an arena-spanning strategic communication agenda. This agenda requires a communicative shift from downplaying to embracing decoupling accusations, from mutual blaming to approval of accountable ways of working through accusations and from confrontation to cooperation of agents across arenas.

This paper aims to provide an overview of the application of blockchain to agri-food supply chains, including key issues and trends. It examines the state of the art and conceptual structure of the field and proposes an agenda to guide future research.

This article performs a bibliometric analysis using VOSviewer software on a sample of 205 articles from the WoS database to identify research trend topics.

The number of publications in this area has increased since 2020, which shows a growing research interest. The research hotspots are related to the integration of blockchain technology in the agri-food supply chain for traceability, coordination between all actors involved, transparency of operations and improvement of food safety. Furthermore, this is linked to sustainability and the achievement of the sustainable development gtoals (SDGs), while addressing key challenges in the implementation of blockchain-based technologies in the agri-food supply chain.

The application of blockchain in the agri-food supply chain may consider four key aspects. Firstly, the implementation of blockchain can improve the traceability of food products. Secondly, this technology supports sustainability issues and could avoid disruptions in the agri-food supply chain. Third, blockchain improves food quality and safety control throughout the supply chain. Fourthly, the findings show that regulation is needed to improve trust between stakeholders.

The paper provides a comprehensive overview of the blockchain phenomenon in the agri-food supply chain by optimising the search criteria. Moreover, it serves to bridge to future research by identifying gaps in the field.