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Environmental knowledge management (EKM) has been studied mainly owing to the increasing awareness of environmental issues. Such issues have generated a warning in the tourism industry that has stimulated a new wave of research on EKM. EKM forges landscape characteristics and so destination image. In turn, EKM sounds affecting tourism destination which calls for destination personality which shows a research context less explored. From a knowledge management perspective, The present research aims to investigate on EKM to understand how it leverages tourists' and destination personality.

With the intent of exploring EKM, the research uses a quantitative analysis on a sample of 2,222 young Chinese tourists. In this context, EKM is linked with destination’s personality and tourists’ personalities, their satisfaction with the destination and their behavioral intentions.

By SPSS regression model, EKM and destination personality are positively linked. This positive relationship is also reflected on destination personality and destination satisfaction, behavioral intention.

The authors’ original contribution to the knowledge management literature extends the new wave of research on EKM. The research also proves the need to make a close collaboration between tourists, the local community and marketers. Marketers need to pay more attention to what tourists want to do and see in the place visited. In a nutshell, there is the need of enforcing and promoting EKM.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

This study aims to propose an innovative model that integrates variables and examines the influence of internet usage expertise, perceived risk and attitude toward information control on privacy concerns (PC) and, consequently, in consumers’ willingness to disclose personal information online. The authors also propose to test the mediation role of trust between PCs and willingness to disclose information. Trust is not a predictor of PC but a causal mechanism – considering that the focus is to understand consumers’ attitudes and behavior regarding the virtual environment (not context-specific) (Martin, 2018).

The authors developed a survey questionnaire based on the constructs that compose the proposed model to collect data from 864 respondents. The survey questionnaire included the following scales: internet usage expertise from Ohanian (1990); perceived risk, attitude toward information control, trust and willingness to disclose personal information online from Malhotra et al. (2004); and PC from Castañeda and Montoro (2007). All items were measured on a Likert seven-point scale (1 = totally disagree; 7 = totally agree). To obtain Westin’s attitudinal categories toward privacy, respondents answered Westin’s three-item privacy index. For data analysis, the authors applied covariance-based structural equation modeling.

First, the proposed model explains the drivers of consumers’ disposition to provide personal information at a level that surpasses specific contexts (Martin, 2018), bringing the analysis to consumers’ level and considering their general perceptions toward data privacy. Second, the findings provide inputs to propose a better definition of Westin’s attitudinal categories toward privacy, which used to be defined only by individuals’ information privacy perception. Consumers’ perceptions about their abilities in using the internet, the risks, their beliefs toward information control and trust also help to delimitate and distinguish the fundamentalists, the pragmatics and the unconcerned.

Some limitations weigh the theoretical and practical implications of this study. The sample size of pragmatic and unconcerned respondents was substantially smaller than that of fundamentalists. It might be explained by applying Westin’s self-report index to classify the groups according to their score regarding PCs. Most individuals affirm having a great concern for their data privacy but still provide online information for the benefit of personalization – known as the privacy paradox (Zeng et al., 2021). It leads to another limitation of this research, given the lack of measures that classify respondents by considering their actual behavior toward privacy.

PC emerges as an important predictor of consumer trust and willingness to disclose their data online, and trust also influences this disposition. Managers need to implement actions that effectively reduce consumers’ concerns about privacy and increase their trust in the company – e.g. adopting a clear and transparent policy on how the data collected is stored, treated, protected and used to benefit the consumer. Regarding the perception of risk, if managers convince consumers that the data collected on the internet is protected, they tend to be less concerned about privacy.

The results suggest different aspects influencing the willingness to disclose personal information online, including different responses considering consumers’ PCs. Through their policies and legislation, the authors understand that governments must be attentive to this aspect, establishing regulations that protect consumers’ data in the virtual environment. In addition to regulatory policies, education campaigns can be carried out for both consumers and managers to raise the discussion about privacy and the availability of information in the online environment, demonstrating the importance of protecting personal data to benefit the government, consumers and organizations.

Although there is increasing research on consumers’ privacy, studies have not considered their attitudinal classifications – high, moderate and low concern – as moderators of willingness to disclose information online. Researchers have also increased attention to the antecedents of PCs and disclosure of information but overlooked possible mechanisms that explain the relationship between them.

Racism occurs in many ways and varies across countries, evolving and adapting to sociocultural history, as well as contemporary economic, political and technological changes. This chapter discusses the multilevel dimensions of racism and its diverse manifestations across multiracial societies. It examines how different aspects of racism are mediated interpersonally, and embedded in institutions, social structures and processes, that produce and sustain racial inequities in power, resources and lived experiences. Furthermore, this chapter explores the direct and indirect ways racism is expressed in online and offline platforms and details its impacts on various groups based on their intersecting social and cultural identities. Targets of racism are those who primarily bear the adverse effects. However, racism also affects its perpetrators in many ways, including by limiting their social relations and attachments, and by imposing social and economic costs. This chapter thus analyses the many aspects of racism both from targets and perpetrators' perspectives.

The paper aims to explore the relationship between customer mindsets and customer citizenship behavior. This study used the cognitive-affective-behavioral model to examine how customer mindsets relate to customer citizenship behavior. In addition, it investigated the mediating effect of customer brand engagement and moderating role of brand trust.

The study used a self-administered online survey from 412 respondents using cellular mobile operating brands. Partial least square structural equation modeling was used to analyze the collected data.

The results revealed that growth-mindset customers directly and significantly influence customer citizenship behavior. The impact of a fixed mindset on customer citizenship behavior is indirect through customer brand engagement. The moderating findings revealed that the effect of brand trust on the relationship between customer brand engagement and customer citizenship behavior is higher than that between the fixed mindset and customer brand engagement.

The findings provide valuable insights for marketing and brand managers to design marketing campaigns considering different mindsets to generate customer citizenship behavior among customers.

This study provides new avenues in consumer psychology and behavior by unfolding the underlying mechanism through which mindsets lead to customer citizenship behavior, contributing to existing knowledge by extending the cognitive-affective-behavioral model.

In a complex, ever-changing, and turbulent business world, encouraging employees to express their improvement-oriented novel ideas through voice behavior is crucial for organizations to survive and thrive. Understanding how to foster employee promotive voice at work is a significant issue for both researchers and managers. This study explores how to foster employee promotive voice through specific HRM practices and positive employee attitudes. It also examines the effect of employee promotive voice on perceived organizational performance.

This study employed a time-lagged multisource survey design. Data were collected from 215 executives, 790 supervisors, and 1,004 employees in 113 firms, and analyzed utilizing a multilevel moderated serial mediation model.

The findings of this study revealed that promotive voice was significantly related to perceived organizational performance. Innovation-enhancing HRM was positively associated with employee promotive voice. The HRM-voice relationship was partially mediated by employee job satisfaction. Power distance orientation was found to significantly moderate the relationship between innovation-enhancing HRM and employee job satisfaction at the firm level. Our findings showed that innovation-enhancing HRM policies may fail to foster promotive voice if they do not enhance employee job satisfaction.

This study challenges some taken-for-granted assumptions in the literature such as any high performance HRM bundles (e.g. HPWS) can foster employee promotive voice, and the effects of HRM are direct and even unconditional on organizational outcomes. It emphasizes the need to avoid potential unintended effects of HRM on employee voice and the importance of contextualizing voice research.

Recent research has proposed a specific female phenotype within autism spectrum disorder (ASD). It suggests females exhibit differences in social communication styles with higher levels of camouflaging and compensatory strategies, as well as variance in restrictive repetitive behaviours (RRBs); however, many existing studies have been based on either small, disproportionate or child and adolescent samples, leaving questions about the specific phenotype. This study aims to explore the sex difference and phenotype in a clinic sample of individuals diagnosed with autism.

A service evaluation of sex/ gender differences on 150 historical ASD assessment reports (75 males, 75 females) using a 103-item questionnaire developed from a quantitative review of existing literature was undertaken.

Females camouflaged more significantly than males in five different areas (thinking how to act next, preparing conversation in advance, making lists of prompts/social responses, wearing a mask/acting, less monotone voice); however, these were not maintained in post-analysis correction.

This study points the evidence towards a different phenotype of Autism that is more common in women than men rather than a unique female phenotype.

A switching depth controller based on a variable buoyancy system (VBS) is proposed to improve the performance of small autonomous underwater vehicles (AUVs). First, the requirements of VBS for small AUVs are analyzed. Second, a modular VBS with high extensibility and easy integration is proposed based on the concepts of generality and interchangeability. Subsequently, a depth-switching controller is proposed based on the modular VBS, which combines the best features of the linear active disturbance rejection controller and the nonlinear active disturbance rejection controller.

The controller design and endurance of tiny AUVs are challenging because of their low environmental adaptation, limited energy resources and nonlinear dynamics. Traditional and single linear controllers cannot solve these problems efficiently. Although the VBS can improve the endurance of AUVs, the current VBS is not extensible for small AUVs in terms of the differences in individuals and operating environments.

The switching controller’s performance was examined using simulation with water flow and external disturbances, and the controller’s performance was compared in pool experiments. The results show that switching controllers have greater effectiveness, disturbance rejection capability and robustness even in the face of various disturbances.

A high degree of standardization and integration of VBS significantly enhances the performance of small AUVs. This will help expand the market for small AUV applications.

This solution improves the extensibility of the VBS, making it easier to integrate into different models of small AUVs. The device enhances the endurance and maneuverability of the small AUVs by adjusting buoyancy and center of gravity for low-power hovering and pitch angle control.

This study aims to delve into the transformative potential of metaverse-driven sustainable tourism (MDST) to envision a sustainable and inclusive future for the tourism industry.

The author uses a forward-looking approach by drawing insights from existing literature, visionary articles and an analysis of technological developments to project the MDST trajectory to 2050, aligning with sustainable development goals (SDGs).

The study highlights the profound potential of MDST as a crucial force in sustainable tourism, identifying key components – immersive experiences, artificial intelligence integration, blockchain and collaborative platforms – that will drive MDST’s evolution. The alignment with SDGs demonstrates MDST’s capacity to facilitate global collaboration, cultural exchange and community engagement, especially in uncertain situations (e.g. pandemic).

While presenting an exploration of MDST, there is a need for empirical evidence in response to the dynamic tourism environment.

Tourism policymakers, businesses and technology developers can leverage MDST to drive sustainable practices, enhance user experiences and contribute to economic growth. The findings offer actionable insights for the practical implementation of MDST initiatives, aligning with the importance of SDGs.

The value of this study lies in its forward-looking perspective, envisioning the role of MDST in the year 2050. The author proposes ten foci for MDST development, contributing to the discourse on sustainable tourism.

The use of over-the-top (OTT) platforms grew substantially after the declaration of the COVID-19 pandemic in 2020. With the pandemic receding, there is a concern that users may not continue with their subscriptions. To counter this, OTT service providers must strategize proactively to retain and acquire new users once the pandemic abates. Positing that understanding the consumption values that users ascribe to OTT platform usage can provide useful customer retention insights, the purpose of this paper is to use the theory of consumption value (TCV) to study the values that users derived from their use of OTT following the onset of the pandemic.

The mixed-method approach is used to collect qualitative and quantitative data. Analysis of qualitative responses collected through interviews of 12 current OTT platform users helped identify two categories of OTT platform-specific values: attribute-level and benefit-based. Next, the study examined the association of values thus identified with one another, as well as with continued intentions to use OTT platforms, by analyzing data collected from 371 existing users.

The findings indicated that functional value quality and social value, representing the attribute-level values, were positively associated with two benefit-based values – functional value price and emotional value (EMV). Next, EMV was not only associated with intentions but also partially mediated the association of attribute-level values with intentions. Premium subscription purchased and increased viewing time were confirmed to have moderating effects on the association between attribute-level and benefit-based values.

The study is amongst the foremost research initiatives to examine consumption values derived from OTT platform usage after the onset of the pandemic. Its novelty also comes from its identifying OTT platform-specific consumption values for the first time and adding a new dimension to the TCV by examining the interplay of these values in the OTT platform context.