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Tourism and hospitality employment have long faced widely recognised challenges with regard to employment, its workforce and the workplace environment, issues that have been addressed by generations of policymakers and practitioners without evident success or solution. These wicked problems are frequently characterised by inherent paradoxes and, therefore, accepting the tenets of paradox theory provides the basis for recognising the need to accept contradictions as a reality which a search for solutions will not resolve. This chapter presents six examples of wicked problems in tourism and hospitality employment, which are underpinned by paradoxes as proxies for the much wider range of intractable problems that beset policy-making and practice in this vital area of tourism and hospitality. The chapter concludes by suggesting ways in which wicked problems can be accommodated, and stakeholders can learn to understand and live with paradoxes.

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.

Antagonistic relationship among the participants of construction projects has significantly improved, and further improving cooperation quality are committed. In this context, expanding new ways to improve cooperation quality has become a new topic in cooperation research. This study is dedicated to exploring the mechanism of cross-organizational private relationships on cooperative behaviors, which is rarely addressed in current research on construction projects, and provides reference for the rational use of cross-organizational private relationships.

Based on analysis of studies related to relational governance theory, institutional theory and project complexity, this study constructs the theoretical model. This study uses survey data from 395 construction professionals in China to test the theoretical model by using structural equation modeling (SEM) and explains the direct and indirect mechanism of cross-organizational private relationships on cooperation behavior.

(1) Cross-organizational private relationships have direct and indirect facilitating effect on cooperation behavior. (2) Relational norms as mediating variables contribute to the expansion of the positive effects of cross-organizational private relationships on cooperation behavior. (3) Institutional environment and project complexity have the moderating effect between cross-organizational private relationships and cooperation behavior.

This research investigates the impact mechanisms and boundary conditions of cross-organizational private relationships at the micro level on the cooperative behaviors in construction projects and conducts empirical research. It is a topic that has not been adequately researched in the field of project management. The research results expand the scope of research on relational governance and deepen the research on the antecedents of relational norms. It provides the base for the proposed contingency theory of relational governance.

This paper aims to deepen the current knowledge of seasonality by investigating visitors’ intentional and behavioural patterns during peak and off-peak seasons. It compares the variation in several key behavioural factors, namely, duration of stay, party size, revisit intention, spending and breakdown of spending in different sectors in hospitality and tourism including entertainment, restaurant, accommodation and transportation. Moreover, this research expands the understanding by examining the effectiveness of two innovative strategies of offering a digital app and organising a unique event to tackle seasonal imbalances through stimulating visitors’ intention to change their timing of visit from peak to off-peak periods.

The author initially used a Delphi approach to gather experts’ opinion on the two scenario settings: event organisation and a trip planner app. The scenarios aimed to potentially encourage visitors to change their visit time to off-peak seasons. Then, using a quantitative survey, the travel habits and spending behaviours of 310 participants were captured. Furthermore, the survey assessed their intention to travel during off-peak seasons in response to the implementation of the two innovative strategies.

The results revealed that although the number of visitors who travel in off-peak seasons may be lower, their daily spending is higher than peak season visitors. In addition to total spending per day, the duration of stay, part size, quality of accommodation and re-visit intention of visitors indicated significant variation between peak and off-peak seasons. According to the statistical analysis’ results, organising events (including festivals) proves more effective in encouraging visitors to travel during off-peak seasons compared to digital innovation (i.e. a trip planner app). This finding is in line with the tenets of the Jobs-to-be-Done Theory of innovation.

This study contributes by conceptualising the mechanism of seasonality and its impacts on subsectors of tourism and hospitality. To the best of the author’s knowledge, this is one of the few empirical research that compares the behavioural patterns of visitors including their average spending per day between peak and off-peak seasons. Previous studies focused on specific regions or sectors, whereas this research investigates visitors’ behaviour on a broader scale to provide more comprehensive view. Furthermore, this study is novel due to practising an outside-in approach through investigating the effectiveness of the two innovative strategies aimed at addressing seasonality in the hospitality and tourism industry from visitors’ point of view.

Technological innovations provide huge opportunities to expand and revolutionize the scope of products and services offered. This is particularly true for tourism, which is undergoing significant changes due to the development of new technologies. The level of technology diffusion depends on several factors like the exchange of information among peers, and the attitude and shared perception among the contributors. The aim of the study is to explore the diffusion of technology in tourism with a specific focus on the social media discourse around new technologies. Thus, the paper investigates the level of interest in these new technologies analysing the information exchange occurring between individuals on Twitter in order to explore the influence of reciprocal networking.

To capture the attitudes expressed in the industry, the study analyses the ongoing discourse on Twitter as a proxy for the participants “interest in new technologies. Through a social network analysis of the tweets and retweets conducted over a period of nine months, the research maps the level of information exchange about the diffusion of new technologies. Moreover, the sentiment analysis provides an interesting overview of the individuals” attitudes towards the awareness or the adoption of new technologies.

Our analysis has provided several insights: (1) the information network on blockchain in tourism consists of participants who change very quickly over time (high turnover of accounts); (2) some contributors have an extremely important role in influencing the flow of information in the system (information centralization), they can have a generalist (discussing several topics) or a specialist (focusing on a specific topic) behaviour and this strategic choice influences their network's structure; (3) these central nodes also have an impact on the definition of positive and negative sentiment towards a topic (sentiment influencer).

The paper contributes to the literature on technology diffusion, by focusing on one of the preconditions of diffusion that is the shared positive attitude towards technological innovation. More specifically, we adopt a network-based approach, which is useful to explain the level of information exchange and the public discourse that can impact the shared perception and attitude towards technological innovation. The study also highlights the role of knowledge brokers in influencing this public discourse. Future studies can deepen the association between positive perception, higher levels of information exchange and increasing usage of specific technologies. Our results also suggest further exploring the opportunity to combine social media data and other sources of information to shed more light on the technological innovation diffusion processes.

This paper shows how practitioners can benefit from the analysis of information exchange about new technologies in tourism adopting a network perspective with the aim of understanding the level of influence among contributors. Moreover, the increasing interest in blockchain technology and the potential combination between social media data and other sources of information can offer promising insights.

The present study explores the level of technology diffusion through the analysis of information exchange on social media (Twitter). Furthermore, the dynamics of individual user behaviour offers a better understanding about media effects.

While previous research is focused on the users' perception towards the development of new technologies in tourism, the aim of this study is to investigate the dynamics behind the level of diffusion of information and awareness about these new technologies, which still represents an unexplored area of research.

Given the scientific and practical difficulties inherent in measuring and comparing socioeconomic deprivation (SED), and the further complexity added in cross national measurements, the main aim of this paper was to check the validity of SED measures used in PISA 2018 dataset. The SED measure used in PISA 2018 was the PISA index of economic, social and cultural status abbreviated as the ESCS index. This assessment was important as PISA analysis is based on variables derived from this instrument and the ESCS index and these reports influence and reflect international and comparative education policies and practice.

This study critically evaluates the socioeconomic status measures in the PISA 2018 dataset, focusing on their convergent validity and cross-national comparability. Using responses from over 600,000 students in 73 countries, it examines the validity of SES indicators and their comparability across countries. The study employs principal component analysis to construct local SES measures and compares them with the existing Economic, Social, and Cultural Status (ESCS) index. It explores the relationship between these SES measures and academic achievement in reading, science, and mathematics, aiming to understand their predictive validity in diverse educational settings. Statistical analyses were conducted using the IEA’s IDB Analyser and SPSS, ensuring robustness and generalisability across the diverse participant countries.

Our research findings challenge the assumed superiority of local measures over broader constructs like the Economic, Social, and Cultural Status (ESCS). It suggests that standardised measures like ESCS may provide more reliable predictions of academic achievement across various educational contexts, underscoring the complex relationship between SES measures and academic performance.

Our novel analysis shows that local and cross-national SED measures are poorly correlated. Our findings raise questions about the measures' validity while acknowledging the methodological challenges. We provide empirical evidence to support ongoing debates on the topic.

The purpose of this paper is to develop a conceptual framework that examines the impacts of changing seasons on tourism.

The paper presents a conceptual process model of the impact of seasons on all aspects of in-destination tourist behaviour. The model is developed from the literature and is then tested using Cairns, Australia as a case study.

Seasons influence the actual and perceived range of products/experiences available, which dictate the pull features of a destination, that in turn, influence who comes and why they come. Combined the activity sets and visitor profile define in-destination behaviour and, ultimately, satisfaction.

The study fills a needed research gap in two ways. Firstly, it explains conceptually and then tests empirically how changes in seasons affect the delivery of tourism products and experiences. Secondly, it adds significantly to our understanding of the factors that influence in-destination behaviour.

Managerial implications for destination management organisations are identified.

This paper presents a new conceptual process model for a previously unexamined issue.

本文提出了一个季节影响目的地游客行为的过程的理论模型。该模型基于文献开发而成, 然后以澳大利亚凯恩斯作为案例进行测试。

本文的目的是开发一个研究季节变化影响旅游的理论框架。

研究发现季节会影响实际和感知的产品或体验的范围, 从而决定一个目的地的吸引力特征。他们反过来可以影响谁来旅游以及他们来旅游的原因。 结合活动和旅游者画像来定义其目的地行为。

这项研究从两个方面填补了理论空白。 首先, 它从概念上解释, 然后实证检验了季节的变化如何影响旅游产品和体验的供应。 其次, 它极大地增强了我们对影响目的地行为的因素的理解。

本文指出了对目的地管理的实践意义。

本文针对先前未经考察的问题提出了一种新的理论过程模型。

El artículo presenta un modelo de proceso conceptual del impacto de las estaciones en todos los aspectos del comportamiento en en destino turístico. El modelo se desarrolla a partir de la literatura y luego se pone a prueba usando Cairns, Australia como estudio de caso.

El propósito de este artículo es desarrollar un marco conceptual que examine los impactos de los cambios de estación en el turismo.

Las estaciones influyen en la gama, real y percibida, de productos/experiencias disponibles que condicionan las características de atracción de un destino. Las estaciones, a su vez, influyen en quién viene y por qué viene. Los conjuntos de actividades combinadas y el perfil del visitante definen el comportamiento en el destino.

El estudio llena un vacío de investigación necesario de dos maneras. Primero, explica conceptualmente y luego demuestra empíricamente cómo los cambios en las estaciones afectan la oferta de productos y experiencias turísticas. En segundo lugar, contribuye significativamente a la comprensión de los factores que influyen en el comportamiento en el destino.

Se identifican las implicaciones de gestión para las organizaciones de gestión de destinos.

Este artículo presenta un nuevo modelo de proceso conceptual para un tema no examinado previamente.

This paper aims to optimize the air pressure regulation scheme of the aeroengine pressure test bench.

Based on the requirements of pressure regulation process and the operating mechanism of aeroengine pressure test bench, a grey performance evaluation index system is constructed. The combination of principal component analysis and grey theory is employed to assign weights to grey indexes. The grey target evaluation model is introduced to evaluate the performance of historical regulation processes, and the evaluation results are analyzed to derive optimization mechanism for pressure regulating schemes.

A case study based on monitoring data from nearly 300 regulation processes verifies the feasibility of the proposed method. On the one hand, the improved principal component analysis method can achieve rational weighting for grey indexes. On the other hand, the method comparison intuitively shows that the proposed method performs better.

The pressure test bench is a fundamental technical equipment in the aviation industry, serving the development and testing of aircraft engines. Due to the complex system composition, the pressure and flow adjustment of the test bench heavily rely on manual experience, leading to issues such as slow adjustment speed and insufficient accuracy. This paper proposes a performance evaluation method for the regulation process of pressure test bench, which can draw knowledge from historical regulation processes, provide guidance for the pressure regulation of test benches, and ultimately achieve the goal of reducing equipment operating costs.

China is a large country with different regions due to regional differences and project characteristics, and the selection of prefabricated building technology according to local conditions is the key to its sustainable development in China. The purpose of this paper is to develop the suitability evaluation system of prefabricated building technology from the perspective of the suitability concept and to analyze the selection path of prefabricated building technology and to provide a reference for selecting and developing prefabricated building technology schemes that meet regional endowments.

Based on relevant literature, technical specifications, and standards, this paper constructs an index system for analyzing the technical suitability of prefabricated buildings. It includes 23 indicators, 7 dimensions, and 3 aspects through the semantic clustering method. Following this, the comprehensive weight of each index is determined using the order relation method (G1) and the continuous ordered weighted averaging (COWA). The selection of technical schemes is comprehensively evaluated using Visekriterjumska Optimizacija Ikompromisno Resenje (VIKOR) and Fuzzy Comprehensive Evaluation Method.

 (1) The technical suitability of prefabricated buildings is influenced by 7 core factors, such as adaptability of resources and environment, project planning and design level, and economic benefit; (2) When selecting the appropriate technology for prefabricated buildings, economic suitability should be considered first, followed by regional suitability, and then technical characteristic; (3) The prefabricated building technology suitability evaluation model constructed in this paper has high feasibility in the technical suitability selection of the example project.

The comprehensive evaluation model of prefabricated building technology suitability constructed in this paper provides technical selection support for the promotion and development of prefabricated buildings in different regions. In addition, the model can also be widely used in areas related to prefabricated building consulting and decision-making, and provides theoretical support for subsequent research.

This study provides a new decision support tool for prefabricated building technology suitability selection, which helps decision makers to make more rational technology choices.

This study has a positive impact on the advancement of prefabricated building technology, the improvement of construction industry standards, and the promotion of sustainable development.

The contribution of this study is twofold: (1) Theoretically, this paper provides technical evaluation indicators and guidelines for provincial and regional governments to cultivate model cities, plan industrial bases, etc. (2) In practice, it offers project-level appropriate technology system solutions for the technology application of assemblers in various regions.

In the highly competitive business landscape, manufacturing firms need to adopt an effective manufacturing strategy to attain a successful world-class manufacturing status. Over the past few decades, the lean manufacturing (LM) approach has gained recognition as one of the foremost strategies for enhancing performance. However, the implementation of LM poses significant challenges due to several barriers. The purpose of this paper is to investigate the primary barriers to lean implementation within the apparel industry.

This paper used an exploratory study approach, using a three-part structured questionnaire to assess the level of agreement on different lean barriers. The measurement of these barriers was conducted using a five-point Likert scale. Empirical data were collected from 177 apparel companies located in Bangladesh.

The findings of the research highlight that the primary obstacles to implementing LI include a lack of understanding of the lean manufacturing system (LMS), the manufacturing process, the company culture and resistance from employees.

This paper could potentially limit the generalizability of this research, as it exclusively examines a single manufacturing sector – the apparel industry.

This paper will help practitioners in finding solutions to resolve discrepancies between current manufacturing practices and the LMS.

This paper fulfills an identified need to examine the extent of lean adoption within the apparel industry of Bangladesh.