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This study aims to address the need for robust conceptual foundations in the digital nomadism discourse through a systematic literature review (SLR). It delves into digital nomadism within sustainable tourism, providing valuable insights to foster community development.

This study uses a rigorous eight-step process that combines an SLR and a system dynamics approach. In the SLR phase, the authors use the theory, context, characteristics and methodology framework to identify key variables for a dynamic model of sustainable tourism through digital nomadism, following detailed search and selection criteria based on PRISMA guidelines. The second phase uses causal loop diagrams (CLDs) from the literature review to visualize relationships and inform future research directions. The CLD model is validated through literature-based and stakeholder interaction processes, focusing on the social, economic and environmental dimensions, resulting in the development of a robust conceptual model.

This study identified 28 theories, including agency–structure theory, travel career ladder theory, stakeholder theory and grounded theory, among others. Semi-structured interviews were the primary research method. Major themes explored encompass community interactions, work lifestyles, cultural aspects, financial considerations, infrastructure and policy. The proposed conceptual model aims to scrutinize relationships across economic, environmental and social dimensions, providing a foundation for investigating and promoting sustainable tourism.

Policy implications involve refining taxation policies to maintain tax bases, promoting collaborative economic models and enforcing environmental regulations. Additionally, integrating community planning infrastructure and implementing demographic strategies to manage potential population shifts are crucial. Policies supporting education, skill transfer, health and well-being initiatives contribute significantly to fostering sustainable tourism practices and enhancing community vitality.

To the best of authors’ knowledge, this study is the first in the digital nomadism space to propose a conceptual model for sustainable tourism adoption.

本研究通过系统的文献综述解决了数字游牧话语中对坚实概念基础的需求。它深入研究了可持续旅游业中的数字游牧主义, 为促进社区发展提供了宝贵的见解。

本研究采用严格的八步流程, 结合了系统文献综述（SLR）和系统动力学方法。在 SLR 阶段, 我们利用 TCCM 框架, 遵循基于 PRISMA 指南的详细搜索和选择标准, 通过数字游牧主义确定可持续旅游业动态模型的关键变量。第二阶段利用文献综述中的因果循环图（CLD）来可视化关系并为未来的研究方向提供信息。 CLD 模型通过基于文献和利益相关者互动过程进行验证, 重点关注社会、经济和环境维度, 从而开发出稳健的概念模型。

本研究确定了 28 种理论, 包括代理结构理论、旅游职业阶梯理论、利益相关者理论和扎根理论等。半结构化访谈是主要的研究方法。探讨的主要主题包括社区互动、工作生活方式、文化方面、财务考虑、基础设施和政策。提出的概念模型旨在审查经济、环境和社会维度之间的关系, 为调查和促进可持续旅游业提供基础。

政策影响包括完善税收政策以维持税基、促进协作经济模式以及执行环境法规。此外, 整合社区规划基础设施和实施人口战略以管理潜在的人口变化也至关重要。支持教育、技能转让、健康和福祉举措的政策对促进可持续旅游实践和增强社区活力做出了重大贡献。

据作者所知, 这项研究是数字游牧领域第一个提出可持续旅游业概念模型的研究。

Este estudio aborda la necesidad de fundamentos conceptuales sólidos en el discurso del nomadismo digital, mediante una revisión sistemática de la literatura. Profundiza en el nomadismo digital dentro del turismo sostenible, proporcionando un conocimiento valioso para fomentar el desarrollo comunitario.

Este estudio emplea un riguroso proceso de ocho pasos que combina una revisión sistemática de la literatura (SLR) y un enfoque de dinámica de sistemas. En la fase SLR, utilizamos el marco Teoría-Contexto-Características-Metodología (TCCM) para identificar variables clave para un modelo dinámico de turismo sostenible a través del nomadismo digital, siguiendo criterios detallados de búsqueda y selección basados en las directrices del método de elementos de notificación preferidos para revisiones sistemáticas y metaanálisis (PRISMA). La segunda fase utiliza diagramas de bucles causales (CLD) a partir de la revisión de la literatura para visualizar las relaciones e informar sobre futuras direcciones de investigación. El modelo CLD se valida mediante procesos basados en la literatura y en la interacción con las partes interesadas, centrándose en las dimensiones social, económica y medioambiental, lo que da como resultado el desarrollo de un modelo conceptual sólido.

Este estudio identificó 28 teorías, entre ellas la teoría de la estructura de agencia, la teoría de la carrera profesional en los viajes, la teoría de las partes interesadas y la teoría fundamentada. Las entrevistas semiestructuradas fueron el método de investigación primordial. Los principales temas explorados abarcan las interacciones comunitarias, los estilos de vida laborales, los aspectos culturales, las consideraciones financieras, la infraestructura y la política. El modelo conceptual propuesto tiene como objetivo examinar las relaciones entre las dimensiones económica, medioambiental y social, proporcionando una base para investigar y promover el turismo sostenible.

Las implicaciones políticas conllevan el perfeccionamiento de las políticas fiscales para mantener las bases impositivas, el fomento de modelos económicos colaborativos y el cumplimiento de la normativa medioambiental. Además, es fundamental integrar la infraestructura de planificación comunitaria y aplicar estrategias demográficas para gestionar los posibles cambios en la población. Las políticas de apoyo a las iniciativas de educación, transferencia de habilidades, salud y bienestar contribuyen significativamente a fomentar prácticas de turismo sostenible y a mejorar la vitalidad de la comunidad.

Hasta donde el autor sabe, este estudio es el primero en el espacio del nomadismo digital que propone un modelo conceptual para la adopción del turismo sostenible.

This study aims to explore tourist perceptions and behaviors toward electric vehicles (EVs) in the Delhi National Capital Region using the technology continuance theory.

An online survey involving 226 respondents uses structural equation modeling to analyze correlations among factors, including perceived enjoyment, facilitating conditions, ease of use, satisfaction, cost, image and performance.

This study reveals that enhancing perceived enjoyment and facilitating conditions can improve the user-friendliness of EVs. Additionally, reducing perceived cost, enhancing image and improving perceived performance can increase the perceived usefulness of EVs. Perceived ease of use strongly influences user satisfaction, while perceived usefulness and satisfaction positively impact users’ attitudes and intentions to use EVs. Although factors such as experience, environmental consciousness, age and gender influence perceptions, focusing on enjoyment, facilitating conditions, cost, image and performance can significantly enhance user satisfaction and intention to use EVs.

The findings underscore several actionable recommendations for businesses and policymakers to boost EV adoption at tourist destinations. The potential benefits of EV adoption, such as improved environmental sustainability, enhanced technological image and increased tourist satisfaction, can serve as a source of inspiration and motivation. Enhancing user experience by prioritizing comfort and convenience in EV design is crucial. Addressing cost concerns through incentives and cost-effective pricing strategies can make EVs more appealing. Marketing campaigns highlighting environmental benefits and technological advancements can improve EV image and performance perception. Prioritizing tourists’ satisfaction and support services is essential, along with educational campaigns to increase awareness. Infrastructure development, including expanding charging networks, and supportive policies like tax incentives, can further encourage EVs adoption, accelerating the transition to sustainable transportation.

This research contributes to understanding tourist perspectives on EV adoption within the context of sustainable tourism and technology adoption.

Electric vehicle adoption (EVA) drives sustainability by significantly reducing carbon emissions and reliance on fossil fuels. Despite EVA’s notable advantages from existing literature and its evolving nature, a gap persists in evaluating EVA research. This research presents a systematic literature review, offering insights into the current state of EVA advancements.

This study amalgamates various factors influencing EVA and elucidates their associations, fostering sustainable transportation. To evaluate progress in this domain, we adopt the Theory-Context-Characteristics-Methodology (TCCM) framework, systematically assessing the theories, contextual factors, characteristics and methodologies employed in EVA research to support efficient decision-making.

The study reveals 18 theories, prominently including the theory of planned behavior, innovation diffusion theory, technology acceptance model and UTAUT. The study identifies diverse factors such as perceived risk, effort expectancy, social norms, performance expectancy, government policy, personal norms, attitude, perceived behavioral control, subjective norms, demographics and ecological knowledge as pivotal in shaping attitudes and intentions toward electric vehicle adoption. Furthermore, structured equation modeling emerges as the predominant methodology, while including alternative approaches enriches the methodological landscape, contributing to a more comprehensive understanding of the factors driving EV adoption.

The insights gained from this research can inform policymakers, manufacturers and researchers, ultimately contributing to the global transition towards more sustainable transportation solutions.

This research’s cardinal contribution lies in developing an integrated theoretical framework, a novel approach that offers a structured and holistic perspective on the multifaceted determinants of EVA. This framework not only illuminates the intricate relationships among these variables but also opens up exciting avenues for future research.

Grounded in the stakeholder theory and signaling theory, this study aims to broaden the research agenda on environmental, social and governance (ESG) investing by uncovering public sentiments and key themes using Twitter data spanning from 2009 to 2022.

Using various machine learning models for text tonality analysis and topic modeling, this research scrutinizes 1,842,985 Twitter texts to extract prevalent ESG investing trends and gauge their sentiment.

Gibbs Sampling Dirichlet Multinomial Mixture emerges as the optimal topic modeling method, unveiling significant topics such as “Physical risk of climate change,” “Employee Health, Safety and well-being” and “Water management and Scarcity.” RoBERTa, an attention-based model, outperforms other machine learning models in sentiment analysis, revealing a predominantly positive shift in public sentiment toward ESG investing over the past five years.

This study establishes a framework for sentiment analysis and topic modeling on alternative data, offering a foundation for future research. Prospective studies can enhance insights by incorporating data from additional social media platforms like LinkedIn and Facebook.

Leveraging unstructured data on ESG from platforms like Twitter provides a novel avenue to capture company-related information, supplementing traditional self-reported sustainability disclosures. This approach opens new possibilities for understanding a company’s ESG standing.

By shedding light on public perceptions of ESG investing, this research uncovers influential factors that often elude traditional corporate reporting. The findings empower both investors and the general public, aiding managers in refining ESG and management strategies.

This study marks a groundbreaking contribution to scholarly exploration, to the best of the authors’ knowledge, by being the first to analyze unstructured Twitter data in the context of ESG investing, offering unique insights and advancing the understanding of this emerging field.

Amidst the turbulent tides of geopolitical uncertainty and pandemic-induced economic disruptions, the information technology industry grapples with alarming attrition and aggravating talent gaps, spurring a surge in demand for specialized digital proficiencies. Leveraging this imperative, firms seek to attract and retain top-tier talent through generous compensation packages. This study introduces a holistic, integrated theoretical framework integrating machine learning models to develop a compensation model, interrogating the multifaceted factors that shape pay determination.

Drawing upon a stratified sample of 2488 observations, this study determines whether compensation can be accurately predicted via constructs derived from the integrated theoretical framework, employing various cutting-edge machine learning models. This study culminates in discovering a random forest model, exhibiting 99.6% accuracy and 0.08° mean absolute error, following a series of comprehensive robustness checks.

The empirical findings of this study have revealed critical determinants of compensation, including but not limited to experience level, educational background, and specialized skill-set. The research also elucidates that gender does not play a role in pay disparity, while company size and type hold no consequential sway over individual compensation determination.

The research underscores the importance of equitable compensation to foster technological innovation and encourage the retention of top talent, emphasizing the significance of human capital. Furthermore, the model presented in this study empowers individuals to negotiate their compensation more effectively and supports enterprises in crafting targeted compensation strategies, thereby facilitating sustainable economic growth and helping to attain various Sustainable Development Goals.

The cardinal contribution of this research lies in the inception of an inclusive theoretical framework that persuasively explicates the intricacies of a machine learning-driven remuneration model, ennobled by the synthesis of diverse management theories to capture the complexity of compensation determination. However, the generalizability of the findings to other sectors is constrained as this study is exclusively limited to the IT sector.

The purpose of the study was to develop a powder shampoo with antioxidant attributes.

Dry shampoo compositions were formulated containing alpha olefin sulfonate (AOS), sodium cocoyl isethionate (SCI), microcrystalline cellulose, mannitol, carboxymethyl cellulose, maltodextrin and sodium benzoate with or without extract of Cinnamomum zeylanicum bark. Cinnamon extract was chosen for this study owing to its ubiquitously known antioxidant attributes. The formulations were tested for detergency action and antioxidant potential in vitro.

Cinnamomum zeylanicum extract exhibited noticeable antioxidant activity in vitro. The authors observed that addition of the bark extract to the shampoo formulation was associated with remarkable increase in total phenolic content, total antioxidant activity and radical scavenging activity without any effect on detergency action.

This preliminary study provides a powder shampoo formulation which exhibits antioxidant attributes as a result of incorporation of cinnamon bark extract. Clinical efficacy of the formulation remains to be tested.

Owing to the powder format of the shampoo, the formulation can be manufactured with ease and economically. Functionalizing the formulation with enhancement of antioxidant activity by incorporation of cinnamon bark extract may be associated with beneficial clinical outcomes, which remains to be tested.

The proposed formulation may be stored and sold in eco-friendly packing material, thus could pave the way for reducing the burden of plastic consumption by the shampoo industry.

The present work demonstrates that incorporation of cinnamon bark extract to a powder shampoo formulation, containing AOS and SCI as principle surfactants, significantly enhances its antioxidant attributes.

This paper aims to explore the nature and degree to which marketing affects consumption behavior of bottom of the pyramid (BOP) population. The objective of the study is to examine, identify and explain aspects of consumption behavior that evidences the influence of marketing practices on the BOP consumers.

The study uses a long interview-based approach for an in-depth qualitative investigation of consumption behaviors of BOP consumers.

Key findings that emerged from the research are: widespread usage of international brands and expenditure on products outside of the core bundle of consumption, susceptibility to sales promotions, need to look and feel good and use “fairness” creams, susceptibility to advertising and celebrity endorsements and influence of store personnel.

For managers, this research suggests a careful examination of the likely consequences of their marketing actions. A set of guidelines are provided to them for doing business in a responsible manner at the BOP markets.

Recommendations for public policymakers are offered that stress on the need for ethical marketing exchanges to address the concern over possible exploitation of this vulnerable population.

Extant literature on BOP has largely been conceptual in nature, relying on various case studies. This study empirically examines the nature and influence of marketing in the purchase behavior of BOP consumers. This is perhaps the first study providing empirical support to the argument that the poor consumers divert their scarce financial resources from fulfilling basic needs to purchasing non-essential discretionary products under the influence of BOP marketing.