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The purpose of the research is to analyze the factors that determine the intention of small- and medium-sized enterprises (SMEs) to adopt the Metaverse. For this purpose, the analysis of the effort expectancy and performance expectancy of the constructs in relation to business satisfaction is proposed.

The analysis was performed on a sample of 182 Spanish SMEs in the technology sector, using a PLS-SEM approach for development. For the confirmation of the model and its results, an analysis with PLSpredict was performed, obtaining a high predictive capacity of the model.

After the analysis of the model proposed in this research, it is recorded that the valuation of the effort to be made and the possible performance expected by the companies does not directly determine the intention to use immersive technology in their strategic behavior. Instead, the results obtained indicate that business satisfaction will involve obtaining information, reducing uncertainty and analyzing the competition necessary for approaching this new virtual environment.

The study represents one of the first approaches to the intention of business behavior in the development of performance strategies within Metaverse systems. So far, the literature has approached immersive systems from perspectives close to consumer behavior, but the study of strategic business behavior has been left aside due to the high degree of experimentalism of this field of study and its scientific approach. The present study aims to contribute to the knowledge of the factors involved in the intention to use the Metaverse by SMEs interested in this field.

This paper aims to identify the effect of environmental management systems (EMSs), commitment to stakeholders and gender diversity on corporate environmental performance (CEP) and the extent to which an economic crisis moderates these relationships.

A regression analysis was conducted on a sample of 14,217 observations from 1,933 firms from 26 countries from 2002 to 2010. The estimator used is ordinary least squares with heteroscedastic panel-corrected standard errors (PCSEs), which allows us to obtain consistent results in the presence of heteroscedasticity and autocorrelation.

The results show that EMSs and stakeholder engagement are mechanisms that drive CEP but lose their effectiveness in times of crisis. However, the presence of women on boards has a positive effect on CEP that is not affected by an economic crisis.

The study has some limitations that could be addressed in the future. We present board gender diversity as a governance mechanism because its role is strongly related to non-financial performance. Future studies could focus on other corporate governance mechanisms, such as the presence of institutional or long-term investors. In addition, other mechanisms could be found that can counteract poor environmental performance in times of crisis. Finally, it might be useful to contrast these results with the crisis generated by the coronavirus pandemic.

The results obtained have important practical implications at the corporate and institutional levels. At the corporate level, they highlight, as essential contributions, that environmental management systems and stakeholder orientation are not effective in times of economic crisis, except for with the presence of women on the board.

Following the crisis, the European Commission has promoted gender diversity on boards as a mechanism to improve the governance of entities – improving, among other aspects, sustainability. In this sense, another one of the practical implications of the study is support for the policies that the European Union has implemented over the last two decades.

The paper analyses how a crisis affects the moral and cultural institutional mechanisms that promote CEP. Gender diversity on the board of directors not only promotes environmental performance but also appears to be a governance mechanism that ensures this performance in times of crisis when the other mechanisms lose their effectiveness. The study proposes specific policies that help maintain environmental performance in an economic crisis.

This study aims to examine the process of value co-creation (VCC) on digital ecotourism platforms and the role of perceived platform usefulness and user participation behavior in that process. The study also seeks to determine the extent to which the typology of the ecotourist moderates VCC.

A total of 420 users of a digital ecotourism platform participated in a study analyzing the factors that influence VCC. A mediation, moderation and conditional process analysis was used to test the proposed hypotheses. A K-means cluster analysis was also used to classify the ecotourists into four groups.

The results show that perceived platform usefulness has a strong influence on the generation of VCC and also on user participation behavior. In turn, user participation behavior is an important driver of VCC. This study also highlights the moderating role of the ecotourist typology in the formation of VCC on these digital platforms.

This study offers managers of digital ecotourism platforms a means to identify and motivate those ecotourists with the necessary skills and characteristics to become true co-creators of value.

This study contributes to the existing knowledge on how value is co-created on digital ecotourism platforms, confirming the important antecedent role of perceived platform usefulness and user participation behavior, as well as the moderating role of ecotourist typology.

El propósito de este estudio es examinar el proceso de co-creación de valor (VCC) en las plataformas digitales de ecoturismo y el papel de la utilidad percibida de la plataforma y el comportamiento de participación de los usuarios. El estudio también pretende determinar en qué medida la tipología del ecoturista modera la VCC.

420 usuarios de una plataforma digital de ecoturismo participaron en un estudio que analizaba los factores que influyen en la co-creación de valor. Se utilizó un análisis de mediación, moderación y proceso condicional para probar las hipótesis propuestas. También se utilizó un análisis de conglomerados K-means para clasificar a los ecoturistas en 4 grupos.

Los resultados muestran que la utilidad percibida de la plataforma tiene una fuerte influencia en la generación de VCC y también en el comportamiento de participación del usuario. A su vez, el comportamiento de participación del usuario es un importante impulsor de la VCC. El estudio también destaca el papel moderador de la tipología ecoturística en la formación de VCC en estas plataformas digitales.

El estudio ofrece a los gestores de plataformas digitales de ecoturismo un medio para identificar y motivar a aquellos ecoturistas con las habilidades y características necesarias para convertirse en verdaderos co-creadores de valor.

Este estudio contribuye al conocimiento existente sobre cómo se co-crea valor en las plataformas digitales de ecoturismo, confirmando el importante papel antecedente de la utilidad percibida de la plataforma y el comportamiento de participación de los usuarios, así como el papel moderador de la tipología del ecoturista.

本研究的主要目的是考察数字生态旅游平台上的价值共同创造（VCC）过程, 以及感知平台有用性和用户参与行为在该过程中的作用。该研究还试图确定生态旅游者的类型在多大程度上调节了VCC。

一个数字生态旅游平台的420名用户参与了一项研究, 分析影响价值共同创造的因素。使用调解、调节和条件过程分析来检验所提出的假设。还使用了K-均值聚类分析, 将生态旅游者分为4组。

结果显示, 感知的平台有用性对VCC的产生有很大影响, 也对用户的参与行为有很大影响。反过来, 用户参与行为也是VCC的一个重要驱动因素。该研究还强调了生态旅游者类型学在这些数字平台上形成VCC的调节作用。

该研究为数字生态旅游平台的管理者提供了一种识别和激励那些具有必要技能和特征的生态旅游者成为真正的价值共同创造者的手段。

本研究对数字生态旅游平台上如何共同创造价值的现有知识做出了贡献, 证实了感知平台有用性和用户参与行为的重要前因作用, 以及生态旅游者类型学的调节作用。

This study aims to analyze the impact of Artificial Intelligence (AI) and Machine Learning (ML) on heritage conservation and preservation, and to identify relevant future research trends, by applying scientometrics.

A total of 1,646 articles, published between 1985 and 2021, concerning research on the application of ML and AI in cultural heritage were collected from the Scopus database and analyzed using bibliometric methodologies.

The findings of this study have shown that although there is a very important increase in academic literature in relation to AI and ML, publications that specifically deal with these issues in relation to cultural heritage and its conservation and preservation are significantly limited.

This study enriches the academic outline by highlighting the limited literature in this context and therefore the need to advance the study of AI and ML as key elements that support heritage researchers and practitioners in conservation and preservation work.

Few studies have explained how and when consumers are willing to engage in online brand-related activities (COBRAs). This study examines the role of brand love in a consumer’s decision to engage in online brand-related activities, considering the mediating effect of attitudinal brand engagement and the moderating effect of brand value on this relationship.

The study analysed data from 404 Spanish consumers using structural equation modelling and the PROCESS package in SPSS to test hypotheses, including mediation and moderation effects.

The study expands on previous research by revealing the mediating role of brand attitudinal engagement in the relationship between brand love and COBRAs and the moderating role of brand value in the relationship between brand engagement and COBRAs. The results show that online consumers who feel brand love from an online store are likelier to be engaged with the brand. This predisposes them to comment on, share, and create content related to the company or brand. Furthermore, consumers who attribute a high value to the brand are likelier to engage in brand-related online activities.

This study offers valuable insights into mechanisms to encourage consumers to generate content, known as user-generated content, to the extent that the tools for developing this content are the same.

至今, 很少研究嘗試去探討消費者為何或於何時會樂意去參與與品牌相關的在線活動。本研究擬探討品牌摯愛對消費者會否決定參與與品牌相關的在線活動所扮演的角色; 研究方法是透過分析態度品牌參與的中介效應和品牌價值在上述品牌摯愛與參與在線活動之間的關聯上所起的調節效果,以求達至研究目的。

研究人員收集來自404名西班牙消費者的數據,並以結構方程模型和SPSS裏的模組PROCESS,去檢測有關的假設,包括就中介效應和調節效果的假設。

研究揭示了態度品牌參與在品牌摯愛與COBRAs 之間的關聯上所扮演的中介角色,研究亦揭示了品牌價值在品牌參與與COBRAs之間的關聯上所扮演的調節角色; 就此而言, 本研究拓展了從前學者探討有關的領域。再者,研究結果顯示,如果消費者從網上商店產生品牌愛慕的話,他們會投入這個品牌; 這使他們更有可能去評價有關的公司和品牌,以及去分享和創建關於公司和品牌的內容; 而且,若消費者視品牌本身擁有高度價值的話,他們會更易於參與與品牌相關的在線活動。

本研究提供了寶貴的啟示,使我們更了解驅使消費者去創造內容 (即用戶生成內容) 的機制,以至生成這些內容的工具均儘相同的地步。

This study analyzes the impact of the COVID-19 pandemic on the consumption of locally produced food. In particular, it examines an extended model of the theory of planned behavior, with the addition of the perceived risk of becoming infected with the disease, locavorism and internal locus of control.

The study employs data collected from an online panel of consumers from the five largest cities in Spain (n = 1,000). It uses partial least squares structural equation modeling (PLS-SEM) to test and validate the proposed theoretical model.

The results indicate that the perceived risk of COVID-19 drives consumers to embrace locavorism more and, although locavorism is a strong predictor of attitude, internal locus of control also has a strong impact on attitude and switching intentions. Subjective norm and attitude are strong predictors of switching intentions and purchase intentions, and switching intentions also have a powerful impact on purchase intentions.

This study extends previous research on locally produced food consumption in that it has proposed and tested a new conceptual model with the inclusion of the perceived risk of COVID-19, locavorism, internal locus of control and switching intentions, which were found to have an influence on purchasing behavior.

Organizations in many domains generate a considerable amount of heterogeneous data every day. Such data can be processed to enhance these organizations’ decisions in real time. However, storing and processing large and varied datasets (known as big data) is challenging to do in real time. In machine learning, streaming feature selection has always been considered a superior technique for selecting the relevant subset features from highly dimensional data and thus reducing learning complexity. In the relevant literature, streaming feature selection refers to the features that arrive consecutively over time; despite a lack of exact figure on the number of features, numbers of instances are well-established. Many scholars in the field have proposed streaming-feature-selection algorithms in attempts to find the proper solution to this problem. This paper presents an exhaustive and methodological introduction of these techniques. This study provides a review of the traditional feature-selection algorithms and then scrutinizes the current algorithms that use streaming feature selection to determine their strengths and weaknesses. The survey also sheds light on the ongoing challenges in big-data research.