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This paper aims to review norms and their relationship with consumer behavior in the tourism sector. The review aims to identify gaps in relation to various norms and their impact on the literature to provide future research recommendations.

A systematic literature review method was used to analyze norms in consumer behavior research within the context of tourism and hospitality. The review focused on the research context, conceptualizations, roles, measurements, theoretical backgrounds and the major findings.

The review reveals that the conceptualizations and dimensionality of norms in the existing studies are inconsistent, and most research in the tourism context only adopted the concept partially without capturing the totality of the concept. The theoretical gaps and measurement of norms were also identified for future research.

This study contributes to a better understanding of the role of norms in shaping tourist behavior and can guide practitioners in developing effective marketing strategies. The findings suggest the need for a more comprehensive understanding of the concept of norms in tourism in relation to theoretical underpinnings, measurement and application. The recommendations provided in this study can guide future research on norms and tourist behavior.

Norms have been extensively discussed in the literature. This paper is the first to systematically review norms and their influence on consumer behavior in the tourism sector.

本文审视规范及其与旅游业消费者行为的关系。此审查旨在确定关于各种规范及其对文献的影响的差距, 并提供未来研究建议。

采用系统文献综述方法, 分析了旅游和酒店消费者行为研究中的规范。审查侧重于研究背景、概念化、角色、测量方法、理论背景和主要发现。

审查发现现有研究中规范的概念化和维度存在不一致性, 而大多数旅游环境下的研究只部分采用了该概念, 未能完整捕捉概念的整体。还确定了未来研究中规范的理论差距和测量问题。

本研究有助于更好地理解规范在塑造游客行为中的作用, 并可以指导从业者制定有效的营销策略。研究结果表明, 需要更全面地理解规范概念在旅游中的理论基础、测量和应用。本研究提供的建议可以指导未来关于规范和游客行为的研究。

规范在文献中已经广泛讨论。本文是第一个系统地审查规范及其对旅游业消费者行为的影响。

Este artículo examina las normas y su relación con el comportamiento del consumidor en el sector turístico. El objetivo de la revisión es identificar brechas con relación a diversas normas y su impacto en la literatura, para proporcionar recomendaciones en futuras investigaciones.

Se empleó un método de revisión sistemática de la literatura para analizar las normas en la investigación del comportamiento del consumidor en el contexto del turismo y hostelería. La revisión se centró en el contexto de investigación, conceptualizaciones, roles, medidas, fundamentos teóricos y los principales hallazgos.

La revisión revela que las conceptualizaciones y la dimensionalidad de las normas en los estudios previos son inconsistentes, y la mayoría de las investigaciones en el contexto del turismo solo adoptaron parcialmente el concepto sin capturar la totalidad de este. También se identificaron lagunas teóricas y medición de las normas para futuras investigaciones.

Este estudio contribuye a una mejor comprensión del papel de las normas en la formación del comportamiento turístico y puede orientar a los profesionales en el desarrollo de estrategias de marketing efectivas. Los resultados sugieren la necesidad de una comprensión más holística del concepto de normas en el turismo en relación con los fundamentos teóricos, la medición y la aplicación. Las recomendaciones proporcionadas en este estudio pueden guiar futuras investigaciones sobre normas y comportamiento turístico.

Las normas han sido ampliamente discutidas en la literatura. Este artículo es el primero en revisar sistemáticamente las normas y su influencia en el comportamiento del consumidor en el sector turístico.

This paper aims to explore the role of frontline employees (FLEs) as mediators in transformative service processes within services targeting vulnerable users.

This paper is based on a case study of the development and implementation of a dementia village, and the data consist of documents, in-depth interviews and field observations.

The analysis identifies FLEs as mediators in six different roles. These roles highlight how FLEs perform as mediators, acting in between and for vulnerable users and thus supporting their well-being. Specifically, the roles explicate the mediating role of FLEs in the design and planning of transformative changes and in daily work practices.

The different mediating roles of FLEs presented here should inform care providers and managers of how employees can become assets for supporting vulnerable users’ well-being during the design and planning stages of transformative change and through daily service work.

This paper offers novel insights into the multifaceted roles of FLEs in transformative services. The findings add to the current debate on mediation in transformative services and contribute to the literature by extending and refining the established conceptual and empirical understandings of the role of transformative service mediators in consumers’ well-being.

This study aimed to the attributes, consequences and personal values that motivate the behavior of consumers of fruits and vegetables (FV) at local markets and how these elements are associated with food safety.

This is a qualitative research that used the laddering in-depth interview technique for data collection. Fifty interviews were conducted with consumers from Minas Gerais, Brazil. From the codification of the interview content, a hierarchical value map was constructed, showing the relationships between the attributes, consequences and values involved in the consumers’ purchasing decision.

Consumers value characteristics related to the origin of the product and the way it is produced and marketed. They seek particular benefits – such as satisfaction with the purchase, care for their health/well-being and safety when consuming food – and social benefits, such as the possibility of contributing to the local economy. Issues related to hygiene, organization, exposure and handling of products were some of the concerns reported by respondents with regard to food safety.

It is worth highlighting the application of the laddering technique itself. Analyzing the predictive validity of the method, there is a propensity for biases linked to possible interference by the researcher, especially in the coding stage of the elements.

This study can be used by producers, marketing professionals and public policymakers to promote FV sold at local markets and to encourage the improvement of food safety practices.

The research points to five consumer segments according to the different motivations that guide their purchase behavior for local FV. In addition, a focus is given to food safety, revealing its importance in the investigated context.

Emotional labour (EL) is a complex phenomenon that has received increasing attention in recent years due to its impact on employee’s well-being and job satisfaction. For a comprehensive understanding of the evolving field of EL, it is important to extract different research trends, new developments and research directions in this domain. The study aims to reveal 13 prominent research topics based on the topic modelling analysis.

Using latent Dirichlet allocation (LDA) method, topic modelling is done on 1,462 journal research papers published between 1999 and 2023, extracted from the Scopus database using the keyword “EL”.

The analysis identifies several emerging trends in EL research, including emotional regulation training and job redesign. Similarly, the topics like EL strategies, cultural differences and EL, EL in hospitality, organizational support and EL, EL and gender and psychological well-being of nursing workers are popular research topics in this domain.

The findings provide valuable insights into the current state of EL research and can provide a direction for future research as well as assist organizations to design practices aimed at improving working conditions for employees in various industries.

Topic modelling on emotional labor is done. The paper identifies specific topics or clusters related to emotional labor, quantifies these topics using topic modeling, adds empirical rigor, and allows for comparisons across different contexts.

The data economy, emerging from the current hyper-technological landscape, is a global digital ecosystem where data is gathered, organized and exchanged to create economic value. This paper aims to shed light on the interplay of the different topics involved in the data economy, as found in the literature. The study research provides a comprehensive understanding of the opportunities, challenges and implications of the data economy for businesses, governments, individuals and society at large, while investigating its impact on business value creation, knowledge and digital business transformation.

The authors conducted a literature review that generated a conceptual map of the data economy by analyzing a corpus of research papers through a combination of machine learning algorithms, text mining techniques and a qualitative research approach.

The study findings revealed eight topics that collectively represent the essential features of data economy in the current literature, namely (1) Data Security, (2) Technology Enablers, (3) Business Implications, (4) Social Implications, (5) Political Framework, (6) Legal Enablers, (7) Privacy Concerns and (8) Data Marketplace. The study resulting model may help researchers and practitioners to develop the concept of data economy in a structured way and provide a subset of specific areas that require further research exploration.

Practically, this paper offers managers and marketers valuable insights to comprehend how to manage the opportunities deriving from a constantly changing competitive arena whose value is today also generated by the data economy.

Socially, the authors also reveal insights explaining how the data economy features may be exploited to build a better society.

This is the first paper exploring the data economy opportunity for business value creation from a critical perspective.

Due to the unknown location, size and timing of disasters, the rapid response required by humanitarian operations (HO) faces high uncertainty and limited time to raise funds. These harsh realities make HO challenging. This study aims to systematically capture the complex dynamic relationships between operations in humanitarian settings.

To achieve this goal, the authors undertook a systematic review of the extant academic literature linking HO to system dynamics (SD) simulation.

The research reviews 88 papers to propose a taxonomy of different topics covered in the literature; a framework represented through a causal loop diagram (CLD) to summarise the taxonomy, offering a view of operational activities and their linkages before and after disasters; and a research agenda for future research avenues.

As the authors provide an adequate representation of reality, the findings can help decision makers understand the problems faced in HO and make more effective decisions.

While other reviews on the application of SD in HO have focused on specific subjects, the current research presents a broad view, summarising the main results of a comprehensive CLD.

Using bibliometrics, this study aims to explore the intellectual structure of social segregation research, key contributors, thematic areas and hotspot topics.

A bibliometric analysis was performed for more than 15,000 research papers listed in one of the famous, rich and widely used scientific databases: Web of Science (WoS). This review approach was used to identify social research hotspots on segregation, intellectual structure, borders and development trends. VOSviewer and Gephi software were employed for mapping and analysis.

The study indicates a marked increase in segregation research, particularly from a spatial/urban perspective. The study reveals the interrelationship between segregation and many other social concepts, such as social equality, cohesion, integration and inclusion. In conclusion, addressing the ramifications resulting from the multiple forms of segregation will help in implementing social policies and evaluating their impact on achieving inclusive social development in general and the 2030 agenda of Sustainable Development Goals (SDGs) in specific.

This study remains limited to the precision and thoroughness of the bibliographic data gained from WoS.

This study is valuable for readers to gain rich insights into the state of research on social segregation. It also provides ideas for future research that prospective authors and interested research and academic institutions can investigate.

This research aims to propose a model for the complex decision-making involved in the ecological restoration of mega-infrastructure (e.g. railway engineering). This model is based on multi-source heterogeneous data and will enable stakeholders to solve practical problems in decision-making processes and prevent delayed responses to the demand for ecological restoration.

Based on the principle of complexity degradation, this research collects and brings together multi-source heterogeneous data, including meteorological station data, remote sensing image data, railway engineering ecological risk text data and ecological restoration text data. Further, this research establishes an ecological restoration plan library to form input feature vectors. Random forest is used for classification decisions. The ecological restoration technologies and restoration plant species suitable for different regions are generated.

This research can effectively assist managers of mega-infrastructure projects in making ecological restoration decisions. The accuracy of the model reaches 0.83. Based on the natural environment and construction disturbances in different regions, this model can determine suitable types of trees, shrubs and herbs for planting, as well as the corresponding ecological restoration technologies needed.

Managers should pay attention to the multiple types of data generated in different stages of megaproject and identify the internal relationships between these multi-source heterogeneous data, which provides a decision-making basis for complex management decisions. The coupling between ecological restoration technologies and restoration plant species is also an important factor in improving the efficiency of ecological compensation.

Unlike previous studies, which have selected a typical section of a railway for specialized analysis, the complex decision-making model for ecological restoration proposed in this research has wider geographical applicability and can better meet the diverse ecological restoration needs of railway projects that span large regions.

The purpose of this paper is to demonstrate how critical realism can be mobilised as a meta-theory, or philosophical under-labourer, for research on space accounting and how this may further inquiries into the known as well as the unknown implications of space exploration and commercialisation.

This is a conceptual paper that applies critical realism to the field of space accounting using cost management in space contracts as an illustrative example.

Adopting a naturalised version of critical realism that recognises the complex interplay between natural and social realities, the author nuances the distinction between intransitive and transitive objects of knowledge and advances a framework that may be used as a starting point for a transfactual mode of reasoning. The author then applies this mode of reasoning to the topic of cost management in the space sector and illustrates how it may enhance our insights into what causes cost overruns in space contracts.

By adopting a naturalised version of critical realism, the author establishes a philosophical framework that can support the broadly based, inter-disciplinary research agenda that has been envisaged for research on space accounting and possibly inform policy development.

This paper is the first to apply a critical realist perspective to space accounting and lays a philosophical foundation for future research on the topic.

There is a growing need for methodological plurality in advancing operations management (OM), especially with the emergence of machine learning (ML) techniques for analysing extensive textual data. To bridge this knowledge gap, this paper introduces a new methodology that combines ML techniques with traditional qualitative approaches, aiming to reconstruct knowledge from existing publications.

In this pragmatist-rooted abductive method where human-machine interactions analyse big data, the authors employ topic modelling (TM), an ML technique, to enable constructivist grounded theory (CGT). A four-step coding process (Raw coding, expert coding, focused coding and theory building) is deployed to strive for procedural and interpretive rigour. To demonstrate the approach, the authors collected data from an open-source professional project management (PM) website and illustrated their research design and data analysis leading to theory development.

The results show that TM significantly improves the ability of researchers to systematically investigate and interpret codes generated from large textual data, thus contributing to theory building.

This paper presents a novel approach that integrates an ML-based technique with human hermeneutic methods for empirical studies in OM. Using grounded theory, this method reconstructs latent knowledge from massive textual data and uncovers management phenomena hidden from published data, offering a new way for academics to develop potential theories for business and management studies.