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Despite the well-recognized importance of recycled water, the study of industry-peer pressure on recycled water is relatively new. This study investigates how organizations experience and react to industry-peer pressure to set recycled water targets. Additionally, this study investigates the role of board chairs involved in sustainability committees in contributing to responses to industry-peer pressure.

Using Eviews 12, this study employed a pooled logistic regression model to analyze data from 1,346 firms on Taiwan and Taipei exchanges (2017–2020).

The findings revealed that frequency-based imitation drives recycled water target-setting diffusion. However, there is no direct relationship between outcome-based imitation and recycled water target-setting. Notably, outcome-based imitation drives the adoption of recycled water target-setting of firms with board-chair membership in sustainability committees.

This study faces certain data limitations. First, this study primarily focuses on water recycling. Future research could explore other ways to reduce water usage, such as using water-efficient equipment. Second, this study gathered information solely on the presence or absence of a board chairperson on the sustainability committee. Future researchers could explore the impact of the composition of sustainability committee on recycled water target-setting. Lastly, the sample used in this study is restricted to Taiwan's corporations that existed during 2017–2020. Future researchers may consider adopting a longitudinal design in other economies to address this limitation.

The findings of this study offer several guidelines and implications for recycled water target-setting and the composition of sustainability committees. It responds to an urgent call for solutions to water shortages when pressure from governments and nongovernmental organizations is relatively absent. The number of industry peers that have already set recycled water targets is indispensable for motivating firms to set their own recycled water targets. In terms of insufficient water-related regulatory pressure and normative pressure, this study found evidence suggesting that the direct motivation for setting recycled water targets stems from mimetic pressures via frequency-based imitation. The evidence in this study suggests that policymakers should require companies to disclose their peers’ recycled water target information, as doing so serves as an alternative means to achieving SDG 6.3.

Recycled water target-setting might be challenging. Water recycling practices may face strong resistance and require substantial additional resources (Zhang and Tang, 2019; Gao et al., 2019; Gu et al., 2023). Therefore, this study suggests that firms should ensure the mindfulness of board members in promoting the welfare of the natural environment when making recycled water target-setting decisions. To reap the second-mover advantage, firms must consider the conditions in which board members can more effectively play their role. Corporations may help their chairpersons in setting recycled water targets by recruiting them as members of sustainability committees. Meanwhile, chairpersons tend to activate accurate mental models when the water conservation performance of pioneering industry peers is strong enough to indicate the potential benefits of adopting recycled water target-setting. Investors’ and stakeholders’ understanding of how the composition of sustainability committees is related to recycled water target-setting may help to identify the potential drivers of firms’ water responsibility. Investors and stakeholders should distinguish firms in terms of the board chair’s membership of their sustainability committee and focus on water-use reduction outcomes in the industry. This study provides insights into circumstances whereby chairpersons help to restore the water ecosystem.

This study explains how frequency-based and outcome-based imitation are two prominent mechanisms underlying the industry-peer pressure concerning recycled water target-setting. Moreover, this study fills literature gaps related to the moderating roles of board-chair membership in sustainability committees concerning industry-peer pressure on recycled water target-setting.

Marine seaweeds, characterised by high-valued bioactive compounds, are used worldwide for several applications, including human food, animal feed, pharmaceutics and cosmetics, bioplastics, agricultural fertilisers, biofuels, and others. Seaweed production can be carried out through different approaches, from on-land or sea-based cultivation to the harvesting of wild stocks. The latter can be of particular importance in the case of seasonal algal over-proliferations, often caused by eutrophic conditions associated with intensive human industrial activities, and which wreak havoc with ecosystem functioning and hinder economic activities. In Europe, Italy experiences seaweed blooms in several coastal basins, such as the Lagoon of Venice and the Lagoon of Orbetello (Tuscany). Here, the proliferating seaweed represents a disturbance to the natural ecosystem and to local business and touristic activities. These biomasses hold no economic value in the country and are systemically removed and disposed of. Re-purposing the biomass to produce seaweed-derived commercial goods would provide benefits for the environment and local economic activities while promoting a sustainable business within a Circular Economy framework and contribute to the UN Sustainable Development Goals number 12 (‘Responsible consumption and production’), and number 14 (‘Life under water’), among others.

The purpose of this study is to elucidate the risks and changes in consumer awareness associated with gender-based pricing, particularly women’s exclusive discounts, in Japan. By examining the case of Gyu-Kaku’s half-price campaign exclusively for women implemented in 2024, the study investigates the legal and reputational risks faced by companies and the rising awareness of consumer diversity and fairness.

A mixed research method combining qualitative and quantitative analysis was adopted. Social trends and expert opinions were grasped through news articles and professional insights, and users’ reactions on X (formerly Twitter) were statistically analyzed from the perspective of sentiment analysis.

It was suggested that gender-based pricing, while pursuing short-term profits, may significantly harm a company’s brand image and long-term profits by ignoring consumer diversity and fairness. In particular, the study indicates a possible link between increased criticism of women’s exclusive discounts and the rising dissatisfaction among young men, who perceive selective application of gender equality amidst a heightened awareness of equality. Additionally, there was a significant increase in negative posts about Gyu-Kaku on X, and even after the total number of mentions decreased, the proportion of negative posts remained high.

This study is an initial attempt to comparatively examine the extent to which gender-based pricing is accepted by consumers in Japan. In a field with few prior studies, it presents new perspectives and hypotheses, proposing directions for future discussions.

This chapter seeks to answer the question of how food tourists will be in the future based on technology and digitalisation. Therefore, two future food tourist scenarios are proposed: realistic and utopian. More specifically, considering the developing technology, from a realistic perspective, future food tourists are evaluated according to their experiences (virtual food experiences, personalised and hyper-personalised food experiences, interactive tech-based food experiences, and sensory food experiences), information sources and communication, tendencies (seeking transparency and traceability in the food supply chain and sustainability-oriented), and payments. However, a utopian future food tourist was also provided as the second future food tourist scenario. In this scenario, the dimensions of future food tourists include instantaneous food travel thanks to teleportation, brain–computer interface-based food experiences, lab-grown food experiences, and intergalactic food tourism. Since this is the first study providing future food tourist scenarios, it plays a guidance role for service providers and launches a scholarly debate in food tourism literature.

Conventional approaches such as Data Envelopment Analysis (DEA) and Fuzzy Data Envelopment Analysis (FDEA) cannot effectively account for uncertainty, which can lead to imprecise decision-making. Furthermore, these methods frequently rely on precise numbers, ignoring the inherent uncertainty of real-world data. To address this gap, the research question arises: How can we develop a methodology that combines Z-number theory and FDEA to provide a comprehensive assessment of residency preferences in European countries while accounting for uncertainty in information reliability? The proposed methodology aims to fill this gap by incorporating Z-number theory and FDEA.

The proposed study assesses residency preferences across 39 European countries, focusing on key factors like environment, sustainability, technology, education, and development, which significantly influence individuals' residency choices. Unlike conventional DEA and FDEA approaches, the proposed method introduces a novel consideration: dependability. This inclusion aims to refine decision-making precision by accounting for uncertainties related to data reliability. The proposed methodology utilizes an interval approach, specifically employing the a-cut approach with interval values in the second step. Unlike using crisp values, this interval programming resolves formulations to determine the efficiencies of decision-making units (DMUs).

The comprehensive findings provide valuable insights into the distinctive factors of European nations, aiding informed decision-making for residency choices. Malta (75.6%-76.1%-75.8%), Austria (78.2%-78%-76.1%), and the United Kingdom (79.3%-78.4%-77%) stand out with distinct characteristics at levels of a = 0-a = 0.5-a = 1, assuming the independence of variables of the overall evaluation. Individual consideration of each factor reveals various countries as prominent contenders, except for the environmental factor, which remains consistent across countries.

Traditional DEA models encounter challenges when dealing with uncertainties and inaccuracies, particularly in the evaluation of large systems. To overcome these limitations, we propose integrating Z-numbers—a powerful mathematical tool for modeling uncertainty—into the conventional DEA process. Our methodology not only assesses the effectiveness of countries across various socio-economic and environmental metrics but also explicitly addresses the inherent uncertainties associated with the data. By doing so, it aims to enhance the precision of decision-making and provide valuable insights for policymakers and stakeholders.

Many researchers and analysts are interested in evaluating the performance of a system with a network structure as a decision-making unit. In this regard, fuzzy network data envelopment analysis (FNDEA) is a noticeable and worthy method for evaluating the efficiency of a system with fuzzy data. Based on the structure of a fuzzy network system, which consists of at least two serial stages, an intermediate factor has an output nature for the first stage and an input nature for the second stage. Hence, it is inappropriate to allocate the same weight for each stage using this factor. Unfortunately, contrary to real-world conditions, all previous conventional FNDEA studies have considered the same role for intermediate factors to linearize or simplify models. For the first time, this study attempts to determine the upper and lower bounds of the overall efficiencies of a fuzzy two-stage series system and its subprocesses with unequal intermediate product weights.

The proposed model remains in its original nature as a complex combinatorial problem in the nonlinear programming category of NP-hard problems. A genetic algorithm (GA) is utilized as a metaheuristic algorithm, and a novel hybrid GA-FNDEA algorithm is presented to solve the problem.

The findings of the study outlined several theoretical contributions and practical implications, including as compensatory property of DEA, determining upper and lower bounds, improving efficiency in nonlinear systems, reducing computational burden, enhancing evolutionary algorithms and retaining real-world conditions.

Contrary to real-world conditions, all previous conventional FNDEA studies have considered the same role for intermediate factors to linearize or simplify models. For the first time, this study attempts to determine the upper and lower bounds of the overall efficiencies of a fuzzy two-stage series system and its subprocesses with unequal intermediate product weights.