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The search for luxurious hospitality experiences increasingly coincides with the imperative to mitigate negative impacts in the pursuit of greater sustainability. This is a task often understood as being complex particularly in the context of luxury hospitality which often resonates with conspicuous consumption. This chapter uses a case study approach to analyze the complex relationship between luxury tourism and sustainability. The study focuses on the development of “luxury” from a materialistic perspective toward an experience economy and relates this to the concept of sustainability and agreements relevant to the tourism industry. The environmental impact of luxury hospitality is then discussed. The case study on properties in Costa Rica, South Africa, the Maldives, Vietnam, and French Polynesia focuses on philosophy, facilities, energy and waste consumption, food and beverage, conservational and educational activities, and alignment to the United Nations Sustainable Development Goals (UN SDGs). The focus is on the properties and shows limitations in that it is not applicable to the whole tourist journey and experience. All properties understand luxury as based on experiences and involvement in nature. Measures to mitigate environmental impact and foster conservational and educational activities are mainstream practices. Comparing the cases with academic literature on luxury, sustainability, ecotourism, and environmental policies underline that sustainability-driven luxury hospitality shows valuable steps toward a more sustainable product but is ultimately faced with the dilemma of taking into consideration and ultimately mitigating the impacts of the entire travel value chain.

This chapter provides an empirical assessment of the effects of infrastructure provision on structural change and aggregate productivity using industrylevel data for a set of developed and developing countries over 1995–2010. A distinctive feature of the empirical strategy followed is that it allows the measurement of the resource reallocation directly attributable to infrastructure provision. To achieve this, a two-level top-down decomposition of aggregate productivity that combines and extends several strands of the literature is proposed. The empirical application reveals significant production losses attributable to misallocation of inputs across firms, especially among African countries. Also, the results show that infrastructure provision has stimulated aggregate total factor productivity growth through both within and between industry productivity gains.

Communities representing groups of agents with similar interests or functions are one of the essential features of complex networks. Finding communities in real-world networks is critical for analyzing complex systems in various areas ranging from collaborative information to political systems. Given the different characteristics of networks and the capability of community detection in handling a plethora of societal problems, community detection methods represent an emerging area of research. Contributing to this field, the authors propose a new community detection algorithm based on the hybridization of node and link granulation.

The proposed algorithm utilizes a rough set-theoretic concept called closure on networks. Initial sets are constructed by using neighborhood topology around the nodes as well as links and represented as two different categories of granules. Subsequently, the authors iteratively obtain the constrained closure of these sets. The authors use node mutuality and link mutuality as merging criteria for node and link granules, respectively, during the iterations. Finally, the constrained closure subsets of nodes and links are combined and refined using the Jaccard similarity coefficient and a local density function to obtain communities in a binary network.

Extensive experiments conducted on twelve real-world networks followed by a comparison with state-of-the-art methods demonstrate the viability and effectiveness of the proposed algorithm.

The study also contributes to the ongoing effort related to the application of soft computing techniques to model complex systems. The extant literature has integrated a rough set-theoretic approach with a fuzzy granular model (Kundu and Pal, 2015) and spectral clustering (Huang and Xiao, 2012) for node-centric community detection in complex networks. In contributing to this stream of work, the proposed algorithm leverages the unexplored synergy between rough set theory, node granulation and link granulation in the context of complex networks. Combined with experiments of network datasets from various domains, the results indicate that the proposed algorithm can effectively reveal co-occurring disjoint, overlapping and nested communities without necessarily assigning each node to a community.

This study carries important practical implications for complex adaptive systems in business and management sciences, in which entities are increasingly getting organized into communities (Jacucci et al., 2006). The proposed community detection method can be used for network-based fraud detection by enabling experts to understand the formation and development of fraudulent setups with an active exchange of information and resources between the firms (Van Vlasselaer et al., 2017). Products and services are getting connected and mapped in every walk of life due to the emergence of a variety of interconnected devices, social networks and software applications.

The proposed algorithm could be extended for community detection on customer trajectory patterns and design recommendation systems for online products and services (Ghose et al., 2019; Liu and Wang, 2017). In line with prior research, the proposed algorithm can aid companies in investigating the characteristics of implicit communities of bloggers or social media users for their services and products so as to identify peer influencers and conduct targeted marketing (Chau and Xu, 2012; De Matos et al., 2014; Zhang et al., 2016). The proposed algorithm can be used to understand the behavior of each group and the appropriate communication strategy for that group. For instance, a group using a specific language or following a specific account might benefit more from a particular piece of content than another group. The proposed algorithm can thus help in exploring the factors defining communities and confronting many real-life challenges.

This work is based on a theoretical argument that communities in networks are not only based on compatibility among nodes but also on the compatibility among links. Building up on the aforementioned argument, the authors propose a community detection method that considers the relationship among both the entities in a network (nodes and links) as opposed to traditional methods, which are predominantly based on relationships among nodes only.

The authors examine how the major board reforms recently implemented by countries around the world affect firms' choice of debt.

Using a quasi-experimental setting of major board reforms around the world that aim to improve board-related governance practices in various areas, this study investigates the impact of effective board monitoring on corporate debt choice. The authors employ difference-in-differences-type quasi-natural experiment method and path analysis for hypotheses testing.

The authors find that the implementation of board reforms is positively associated with firms' preference for public debt financing over bank debt. However, this effect tends to weaken after the fourth year following the implementation of board reforms. In additional analyses, the authors find that “rule-based” reforms have a more pronounced effect on firms' choice of debt than do “comply-or-explain” reforms. Both (1) strengthened firm-level internal governance practices that address concerns about the agency cost of debt and (2) reduced information asymmetries play important roles in facilitating firms' debt choice, but the evidence suggests that the former is the economic mechanism through which country-level reforms affect corporate debt choice.

The study extends the literature examining the heterogeneity of corporate debt choices in a global setting and the literature on the consequences of corporate governance reforms.

The findings demonstrate the effectiveness of the corporate board reforms implemented in countries around the world, addressing concerns from critics about their potential harm or ineffectiveness.

The results indicate that country-level board reforms reduce the extent to which shareholder–creditor conflicts harm shareholders.

In this chapter, the author critically examines the deeply entrenched practices and theories within counselor education, revealing their roots in historically dominant, Eurocentric, and often racially oppressive assumptions. This study brings to light the pervasive impact of these traditional approaches, illuminating their role in perpetuating racial oppression and disparities in mental health care. The author presents a compelling argument for adopting Critical Race Theory (CRT) as an effective pedagogical and clinical practice framework in the counseling profession, a step toward its much-needed liberation. CRT's tenets are examined as a robust alternative, promoting socially just outcomes in counseling and psychotherapy. The article highlights CRT's capacity to address the well-established relationship between racism, white supremacy, and minority mental health. It proposes a groundbreaking model for praxis, predicated on CRT, which holds potential not only to challenge and disrupt oppressive structures but also to pave the way for the liberation of both the oppressed and the oppressor. This seminal work prompts a re-envisioning of counselor education, asserting a call for a transformative shift toward a liberation-based, social justice pedagogy.

This study systematically reviewed existing literature on the impact of economic uncertainty on property performance to highlight focus areas and spur future research amid unprecedented global uncertainty levels. Conceptually, uncertainty levels and environmental dynamism are related to investors' risk judgement and decision-making.

Peer-reviewed journal articles published from 2007 to 2022 were assembled and arranged through the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) protocol. The initial search produced 2,028 results from the Web of Science and Scopus databases, which were rigorously purified for a final dataset of 70 articles. These records were subsequently assessed through content analysis, bibliographic modelling, topic modelling and thematic analysis. Recurring themes were visualised using the VOSviewer software.

The existing literature suggests that economic uncertainty negatively impacts investment volumes, returns and performance. Research has also increased since 2018, with a strong emphasis on the housing sector and developed property markets. Commercial property and emerging markets account for only 10 and 8% of previous research, respectively.

These findings highlight the negative impact of economic uncertainties on property performance and investment volumes, which necessitate careful risk assessment. Given the high susceptibility of emerging and commercial property markets to uncertainty, these markets warrant further research amid ongoing uncertainty concerns across the globe.

Given current unprecedented levels of global uncertainty, the effects of economic uncertainty have received renewed interest. This study synthesised the current understanding of how different property markets respond to increased uncertainty and outlined future research directions to enhance understanding. Themes and relationships were also integrated into a conceptual map summarising the reported effects of economic uncertainty on housing, commercial property, investment and behaviour in the property market.

This paper explores how the blockchain food traceability system (BFTS) affects consumers' affective brand commitment and subsequent willingness to pay premium prices.

From February 11 to May 23, 2023, this study collected data from 236 Chinese customers, who had purchased blockchain-traced food in Jingdong Mall within the past three months. Structural equation modelling was used to analyse the data.

The main findings were as follows: (1) BFTS information transparency, information immutability and product diagnosticity are significant predictors of consumer-perceived trustworthiness; BFTS information transparency, product diagnosticity and product safety are significant predictors of consumer-perceived informativeness, (2) Perceived trustworthiness and perceived informativeness build consumers' affective brand commitment, (3) Affective brand commitment affects willingness to pay premiums and (4) Health consciousness positively moderates the relationship between consumers' affective brand commitment and willingness to pay premiums.

This paper complements the research on consumer behaviour in the BFTS, and the research results provide important enlightenment for guiding food enterprises to formulate reasonable and perfect marketing strategies of blockchain-traced food.

Understanding consumer brand relationships from the perspective of the consumer has been a research topic for years. Despite this, there are still various ways in which the construct is interpreted. This paper aims to identify the most typical interpretation of brand relationships by consumers.

A four-study prototype analysis was conducted, in which a bottom-up approach was applied to identify lay people’s conceptualization of consumer brand relationships.

The prototype analysis generates a comprehensive list of features of consumer brand relationships that provide a nuanced understanding of the concept. The most typical characteristics of a brand relationship according to consumers are quality, bond, value and joy. Comparing this relationship prototype with existing literature shows that there may be a gap between theory and practice regarding the concept of brand relationship.

The prototypical conceptualization of brand relationships shows which aspects play a role in consumers' most common interpretation of the construct. This provides an opportunity to assess the validity of existing conceptualizations of brand relationships. Knowing which aspects are most relevant for consumers’ brand relationships allows brands to make adjustments as needed and improve at establishing and maintaining relationships with consumers.

Companies must no longer just report on corporate sustainability (CS) performance but also demonstrate that they are aligning their strategies with sustainability. However, suitable management control systems (MCS) are required to implement a sustainability strategy. Thereby, sustainability reporting (SR) can also be employed for control purposes. On the other hand, existing MCS can be used to develop SR that goes beyond accountability. Accordingly, this paper explores how this interplay can be designed.

For the study, 20 semi-structured interviews were conducted with persons from ATX and DAX companies. Since the interplay should be examined from a holistic control perspective, the authors used the MCS package of Malmi and Brown as an analysis framework.

Nowadays, merely focusing on reporting is too narrow a view. It is therefore not surprising that the investigation was able to reveal various possible linkages between MCS and SR that span the full range of the MCS package of Malmi and Brown.

Future research should also consider non-listed companies to investigate potential differences and take a closer look at the proposed reciprocal nature of the interplay.

The findings expand the knowledge of how companies can use SR for control purposes and how existing MCS can help develop a reporting that goes beyond accountability.

The study contributes by highlighting the potential of SR to control CS performance from a holistic MCS perspective and likewise the impact of existing MCS on reporting. In addition, different theoretical perspectives are used to explain why the interplay can be designed differently in practice.