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Recycling and reuse of the electric vehicle (EV) batteries are ways to extend their limited lives. If batteries can be traced from production to recycling, it is beneficial for battery recycling and reuse. Using blockchain technology to build a smart EV battery reverse supply chain can solve the difficulties of lack of trust and data. The purpose of this study is to discuss the behavioural evolution of a smart EV battery reverse supply chain under government supervision.

This study adopts evolutionary game theory to examine the decision-making behaviours of the government, EV manufacturers with recycled used batteries and third-party EV battery recyclers lacking professional recycling qualification.

On the smart reverse supply chain integrated by blockchain technology, a cooperative recycling strategy of the third-party EV battery recycler is the optimal choice when the government tends to actively regulate. The probability of the EV manufacturer choosing the blockchain adoption strategy exceeds (below) the threshold, and the government prefers negative (positive) supervision. According to numerical analysis, in the mature stage in the EV battery recycling industry, when the investment cost of applying blockchain is high, EV manufacturers' willingness to apply blockchain slows down, the government accelerates adopting a negative supervision strategy and third-party EV battery recyclers prefer cooperative recycling.

The results of this study provide opinions on the strength of government supervision and the conditions under which EV manufacturers and third-party EV battery recyclers should apply blockchain and cooperate. On the other hand, this study provides theoretical analysis for promoting the application of blockchain technology in smart reverse supply chain.

Compared with previous research, this study reveals the relevance of government supervision, blockchain application and cooperation strategy in smart EV battery reverse supply chain. In the initial stage, even if the subsidy (subsidy reduction rate) and penalty are high and the penalty reduction rate is low, the EV manufacturer should rather give up the application of blockchain technology. In the middle stage in the EV battery recycling industry, the government can set a lower subsidy (subsidy reduction rate) combined with a penalty or a higher penalty (penalty reduction rate) combined with a subsidy to supervise it. The third-party EV battery recycler is advised to cooperate with the EV manufacturer when the subsidy is low or the penalty is high.

The coronavirus disease 2019 pandemic changed the lives of people around the world. In a post pandemic era, leaders have a role to enable the changes needed to make workplaces smart and happier. The aim of this study is to look at human resource management (HRM) from new perspectives: being smart and happy in the workplace. Some research questions are proposed: What do we know about smart human resources (smart HR)? What do we know about human resource analytics (HRA)? and how can future research on smart and happy HRM be oriented?

A bibliometric technique is used to identify the main topics studied in smart HR and HRA. A logical reasoning is applied to propose future research models.

For smart HR, the roadmap considers the approaches, practices and purposes. For HRA, the roadmap shows what are the perspectives HR processes, tools and its usefulness. Considering the context of Industry 5.0 and post pandemic era, a future research line for studying smart HRA for happy management is proposed.

This study has developed a proposed model to guide future research on the application of HRA to manage smart and happy workers.

Production-related industrial zones, super structures and infrastructures are constructed by the construction industry. Nearly all industries and their environmental emissions are influenced by the construction industry including its sub-industries, companies and their supply chains. Furthermore, cities play an important role in economic growth. Cities are hubs for productivity, production, supply and demand, and innovation with the help of their human capital and built environment (e.g. offices, factories, industrial zones, infrastructures, etc.).

Industrial growth fosters urbanisation which is vital for the supply side in the economy to reach to the human resources. Urbanisation which supports industrial growth obstacles industries’ efficiency due to urbanisation problems (e.g. traffic, air and water pollution, health problems).

Construction industry and its sub-industries affect total factor productivity growth in nearly all industries. Construction industry can be a facilitator industry for economic growth and industrial growth considering total factor productivity growth and environment aspects. All industries’ green and sustainable total factor productivity growth can be supported by rethinking construction industry, its sub-industries and their outputs (e.g. construction materials, built environment, cities) as well as construction project management processes.

This chapter aims to introduce carbon capturing smart construction industry model to foster green and sustainable total factor productivity growth of industries. This chapter emphasises current and potential roles of construction industry, its sub-industries and their outputs in fostering other industries’ growth through green and sustainable total factor productivity growth. It focusses on carbon capturing technologies and design at different levels. Furthermore, this chapter emphasises cities’ role in green and sustainable total factor productivity growth. This chapter provides recommendations for construction industry policies and carbon capturing cities/built environment model to solve urbanisation problems and to foster industrial growth and green and sustainable total factor productivity growth. This chapter is expected to be useful to all stakeholders of the construction industry, policy makers, and researchers in the relevant field.

Purpose — Fare validation data from transit smart card automatic fare collection (AFC) systems have properties that align with the direction of large-scale mobility surveys and the evermore demanding data needs of the transit industry. In addition to applications in transit planning and service monitoring, travel patterns and behaviour can effectively be studied by exploiting the continuous stream of observations from the same card. The paper proposes a methodology to enrich fare validation data in order to generate information that is hard to obtain with traditional travel surveys.

Methodology/approach — The methodology aims to synthesize individual-level attributes by summarizing multi-day validation records from each card. These new dimensions are then transposed to various levels of aggregation and studied simultaneously in multivariate analysis. The methodology can also be applied to synthesize other multi-day attributes and is transferable to other modes and other travel behaviour studies.

Findings — Results show that validation data can effectively be used to measure the distribution of travel patterns in time and space as well as the variation of those phenomena over time. The paper provides several examples based on millions of validation records from the metro sub-network of Montréal, along with interpretations and some practical implications.

Research limitations/implications — Limitations and bias regarding the data and the methodology as well as the strategies to handle them are discussed within the context of passive travel survey and travel behaviour studies.

Practical implications — Practitioners in transit planning, operations, marketing and modelling can benefit from studying the increasingly accessible and massive smart card datasets through a deeper understanding of multi-day travel patterns and behaviour of transit users.

Originality/value — This paper outlines a data modelling approach and simple-to-implement methodology which exploit the multi-day property of fare validation data from a smart card AFC. The concept of multi-day attributes is introduced. The analyses show that the approach is effective for extracting information on travel behaviour and its variation which would otherwise be hard to obtain through traditional travel surveys, opening up another dimension of this data source for practitioners and transport modellers alike.

Purpose: The purpose of this chapter is to review and critically evaluate robots, artificial intelligence and service automation (RAISA) applications in the restaurant industry to educate professors, graduate students, and industry professionals.

Design/methodology/approach: This chapter is a survey of applications of RAISA in restaurants. The chapter is based on the review of professional and peer-reviewed academic literature, and the industry insight section was prepared based on a 50-minute interview with Mr. Juan Higueros, Chief Operations Officer of Bear Robotics.

Findings: Various case studies presented in this chapter illustrate numerous possibilities for automation: from automating a specific function to complete automation of the front of the house (e.g., Eatsa) or back of the house (e.g., Spyce robotic kitchen). The restaurant industry has already adopted chatbots; voice-activated and biometric technologies; robots as hosts, food runners, chefs, and bartenders; tableside ordering; conveyors; and robotic food delivery.

Practical implications: The chapter presents professors and students with a detailed overview of RAISA in the restaurant industry that will be useful for educational and research purposes. Restaurant owners and managers may also benefit from reading this chapter as they will learn about the current state of technology and opportunities for RAISA implementation.

Originality/value: To the best of the authors’ knowledge, this chapter presents the first systematic and in-depth review of RAISA technologies in the restaurant industry.

This research aims to answer two major research questions related to the COVID-19 crisis from a longitudinal approach: What is the revenue management (RM) role during the different periods subject to analysis? What are the RM strategies and measures implemented during this crisis in contrast with a non-crisis context? It also aims to propose an RM implementation model that provides a contingency plan to face future crises.

This qualitative study, following a longitudinal approach, analyses three round-table discussions with 11 internationally renowned experts during three key scenarios of the COVID-19 crisis: the lockdown period (from March to June 2020) and the following two summer seasons (the post-lockdown period): Post-lockdown I (the summer campaign, 2020) and Post-lockdown II (the summer campaign, 2021). Based on a deductive approach, thematic analysis is conducted using NVivo.

Further professionalisation of revenue managers, which has enabled the correct application of strategies and measures, highlighting the importance of not lowering prices, the flexibility of booking conditions, the development of other sources of income and the increase in the value of services, amongst others, are key factors in managing this crisis. The longitudinal analysis carried out in three different periods of this crisis shows how these measures have evolved and the contrast with RM application in a non-crisis context. The revenue manager's leadership and proactivity, the holistic organisation of RM marketing, commercial and sales departments and the quick adaptation of RM systems (RMSs) by modifying their algorithms are essential to reducing the impact of COVID-19 on the hospitality industry. This crisis has led the industry to rethink processes and strategies and to increase digitalisation. The proposed model, which considers the various RM strategies and measures implemented during COVID-19 in contrast to a non-crisis context, is the cornerstone for developing a graded contingency plan to face future crises. This research sheds light on the widely discussed role of RM during this crisis.

This study has various limitations. First, the three round-table discussions were held online due to the health crisis, and the chosen webinar format may have biased the participants' answers due to its public nature. Second, the survey was carried out in Spanish. Despite the strong international profiles of the participants, cultural distortion may appear, suggesting that the research should possibly be extended to other cultural contexts in the future. Third, some of the participants were unable to attend all the round-table discussions due to their professional duties, so people with similar profiles were invited to the rest of the sessions.

The revenue manager's leadership and proactivity, the holistic organisation of RM marketing, commercial and sales departments and the quick adaptation of RMSs by modifying their algorithms are essential to reducing the impact of COVID-19 on the hospitality industry. This crisis has led the industry to rethink processes and strategies and to increase digitalisation. The proposed model, which considers the various RM strategies and measures implemented during COVID-19 in contrast to a non-crisis context, is the cornerstone for developing a graded contingency plan to face future crises. This research sheds light on the widely discussed role of RM during this crisis.

This work contributes to the literature by providing a model that considers the various RM strategies and measures implemented during COVID-19 in contrast to a non-crisis context. The novelty of this research is mainly found in the conducting of a deductive and longitudinal study considering previous research focussed on RM strategies applied during the COVID-19 crisis and supplementing it with new measures by applying qualitative techniques.

Nations are opening their “digital borders” to allow the free movement of business, employment and skills. However, this process of digitalization is fraught with challenges. This study aims to identify these challenges to build a solution-oriented framework for smart nations.

This study conducted a systematic literature review, analyzing 69 peer-reviewed academic papers out of 5,958 identified papers.

The identified challenges for smart nation building were categorized as follows: people and society, technology and innovation, digital infrastructure, politics, governance, economics and business and sustainability. To overcome these challenges, this study highlights the need for a holistic national approach, which includes solutions such as improving education, technology-driven innovations, investments for building smart nation infrastructure, top political leadership involvement, national vision and action plan, national regulatory frameworks, business environment and job creation, stakeholder engagement, renewable energy use and technological integration – all of which are key for sustainable development.

This study provides directions for building a smart nation framework, but the literature review results are confined to articles, conference papers and book chapters. This study could be further enriched if the findings are cross-checked with experts. This limitation will be addressed in future research.

Given the dearth of literature on this nascent concept, the insights from this study can guide policymakers and industry leaders involved in smart nation building and benefit researchers engaged in theoretical development.

The purpose of this paper is to analyse the future of the implementation of artificial intelligence (AI) technologies in services experience provided by cultural institutions (e.g. museums, exhibition halls and cultural centres) from experts’, cultural tourists’ and users’ point of view under the Industry 5.0 approach.

The research was conducted using a qualitative approach, which was based on the analysis of the contents obtained from two roundtable discussions with experts and cultural tourists and users. A thematic analysis using NVivo was done to the data obtained.

From a futuristic Industry 5.0 approach, AI is considered to be more than a tool – it as an integral part of the entire experience. AI aids in connecting cultural institutions with users and is beneficial since it allows the institutions to get to know the users better and provide a more integrated and immersive experience. Furthermore, AI is critical in establishing a community and nurturing it daily.

The most important contribution of this research is the theoretical model focused on the user experience and AI application in services experiences of museums and cultural institutions from an Industry 5.0 approach. This model includes the visitors’ and managers’ points of view through the following dimensions: the pre-experience, experience and post-experience. This model is focused on human–AI coworking (HAIC) in museums and cultural institutions.

The purpose of this treatise is to present an analysis of the importance of positive transformational crisis management. The analysis relates to the difficulty now being faced by Nokia, historically the world's leading manufacturer of technologically advanced mobile phones, of Apple's innovative combination of its iTunes, iPhone, and applications that deliver internet content to the iPhone.

A crisis, typically considered to be a negative issue, can be a positive transformational event in the life of a business firm when that firm recognizes a crisis and makes appropriate changes in its operations to facilitate positive growth and development. However, the initial stage of a crisis must be recognized and appropriately responded to. The crisis management paradigm that is the foundation for this case analysis focuses on four stages of a crisis: the preliminary crisis, acute crisis, chronic crisis, and crisis resolution. The case deals with the innovations of Apple that have enabled the firm to become a direct competitor to Nokia in the smart phone market. The preliminary crisis stage was not appropriately recognized by Nokia, and the firm was thrust into an acute crisis that has now evolved into a chronic crisis. A brief overview is presented of the historical development of both Nokia and Apple, and an analysis of the present crisis situation in which Nokia now finds itself is presented in some detail.

It was concluded that Nokia is now in a very difficult position regarding Apple due to its failure to engage in a timely transformational response to the competitive innovations of Apple.

This is an excellent example of failure in positive transformational crisis management.