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In urban planning, sustainability is closely linked to the quality of urban public spaces (UPS). However, some UPS encounter issues of low attractiveness and underutilisation. Vitality serves as a crucial measure in this context. The research perspective on the vitality of UPS centres on the balance between human activities and the built environment. Therefore, this article aims to systematically review critical aspects of UPS vitality evaluation system, including research objects, vitality components and research methods, from the dimensions of crowd activity and the built environment.

A systematic literature review using PRISMA analysed English-language publications from 2008 to 2023 in Scopus and Web of Science (WOS) databases, employing keywords related to UPS and vitality, with defined inclusion and exclusion criteria.

(1) Research objects, including parks, squares, waterfronts, blocks and streets. (2) The factors contributing to crowd activity characteristics originate from five dimensions, namely spatial, temporal, visitor, activity and feedback. Environmental factors, both external (accessibility, surrounding function mix and population density) and internal (service facility mix and water presence), significantly impact vitality. (3) The study primarily relies on quantitative data, including traditional surveys and emerging significant data sources like dynamic location and traffic, social media, geospatial and point of interest (POI) data. Data analysis methods commonly used include correlation analysis and comprehensive evaluation techniques.

The findings contribute to a comprehensive understanding of the vitality evaluation system for UPS from multiple perspectives for urban planners, aiding in identifying key factors and research methods in the vitality evaluation of various types of UPS.

As a smart service, location-based advertising (LBA) integrates advanced technologies to deliver personalized messages based on a user’s real-time geographic location and needs. However, research has shown that privacy concerns threaten the diffusion of LBA. This research investigates how privacy-related factors (i.e. LBA type, privacy self-efficacy (PSE) and consumer generation) impact consumers’ value-in-use and their intention to use LBA.

This study developed and examined an LBA value-in-use framework that integrates the role of LBA type, consumers’ PSE and consumer generation into the technology acceptance model (TAM). Data were collected through two experiments in the field with a total of 374 consumers. The proposed relationships were tested using PROCESS modeling.

The results reveal that pull (vs push) LBA causes higher value-in-use in terms of perceived usefulness and perceived ease of use, leading to greater usage intention. Further, the differences in the mediated relationship between pull- and push-LBA are larger among consumers of low PSE (vs high PSE) and Generation Z (vs other generations). The findings suggest that the consumer value-in-use brought about by LBA diminishes when using push-LBA for low PSE and Generation Z consumers.

This research is the first to integrate the privacy-related interactions of LBA type and consumer characteristics into TAM to develop a TAM-based LBA value-in-use framework. This study contributes to the literature on service value-in-use, smart services and LBA by clarifying the boundary conditions that determine the effectiveness of LBA in enhancing consumers’ value-in-use.

The purpose of this study is to investigate the impact of rapid internationalization by emerging-market multinational enterprises (EMNEs) on their innovation performance. It also seeks to identify any potential moderating factors that could influence this relationship.

By analyzing data from listed Chinese MNEs from 2012 to 2022, this study applies a negative binomial regression model to test the research hypotheses.

This study uncovers an inverted U-shaped relationship between the internationalization speed of EMNEs and their innovation performance. It also suggests that strong absorptive, learning and managerial capacities could play positive moderating roles in the effect of internationalization speed on EMNEs’ innovation performance.

This study highlights rapid global expansion, promoting new knowledge acquisition for EMNEs. However, due to time-compression dilemmas with limited EMNE firm-specific advantages, overly accelerated internationalization hinders learning effectiveness. Additionally, this study reveals the critical importance of three firm-specific capacities in EMNEs – absorptive, learning and managerial capacities – in efficiently assimilating newly acquired knowledge from foreign markets and enhancing their innovation performance through rapid internationalization.

The purpose of this study is to explore how past and future temporal focus of CEOs in the hospitality industry influence their intention to invest in metaverse technology and the underlying mechanism under boundary conditions of perceived competitive pressure.

This multi-informant study collected data over three waves from a sample of 235 CEOs and their subordinates in India’s hospitality industry. A PLS-SEM was applied to the study data. Further, the study also used phenomenological interviews to capture CEOs’ perspectives on the study’s conceptual model.

Findings suggest that the past temporal focus of CEOs decreases technology orientation, and future temporal focus increases the technology orientation of firms, consequently impacting the intention to invest in the metaverse. CEOs’ perceived competitive pressure moderates the mediating relationship, such that the negative impact of past temporal focus on technology orientation is decreased and that of future temporal focus on the CEO is increased.

By exploring the role of a CEO’s past and future temporal focus on influencing technology orientation and, hence, adoption of new technology, the study extends upper-echelon theory to the field of metaverse adoption in the hospitality industry and responds to scholars’ calls to explore the industry’s technology adoption from the lens of the upper echelon.

The study has significant implications for the success of the adoption of metaverse technology in the hospitality industry. Findings imply that the board members should encourage CEOs to have future temporal focus.

The study provides novel insights into the adoption of metaverse technology by the hospitality industry, where CEO attributes such as their temporal focus influence intention to invest in metaverse.

The purpose of this study is to reveal the dynamics of house prices and sales in spatial and temporal dimensions across British regions.

This paper incorporates two empirical approaches to describe the behaviour of property prices across British regions. The models are applied to two different data sets. The first empirical approach is to apply the price diffusion model proposed by Holly et al. (2011) to the UK house price index data set. The second empirical approach is to apply a bivariate global vector autoregression model without a time trend to house prices and transaction volumes retrieved from the nationwide building society.

Identifying shocks to London house prices in the GVAR model, based on the generalized impulse response functions framework, I find some heterogeneity in responses to house price changes; for example, South East England responds stronger than the remaining provincial regions. The main pattern detected in responses and characteristic for each region is the fairly rapid fading of the shock. The spatial-temporal diffusion model demonstrates the presence of a ripple effect: a shock emanating from London is dispersed contemporaneously and spatially to other regions, affecting prices in nondominant regions with a delay.

The main contribution of this work is the betterment in understanding how house price changes move across regions and time within a UK context.

The purpose of this study is to identify potential differences in experiences and their causes from a gender-based perspective.

We use secondary data, and we conduct a thematic analysis, to identify whether and how women and men negotiate differently.

Despite remote work being considered as creating a level-playing field for both genders, women are still vulnerable to work and life demands, and pre-existing stereotypes become exacerbated. In addition, we show how technology might be used to manage physical and temporal boundaries, through integration or segmentation tactics.

There is a growing body of literature that focuses on work-life conflict among teleworkers. Yet, there is limited research that explores such conflicts from a gender perspective, specifically whether and how different genders manage boundaries between work and life differently.

How does the interaction between time and knowledge affect the evolution of organizations? Past research in organizational evolution has mostly investigated time and knowledge as two separate variables. In contrast, theoretical perspectives integrating these variables are still seemingly scant. The authors believe that filling this literature gap needs attention. Thus, this study aims to contribute by developing a conceptual framework.

This is a conceptual study. The framework is centred on the concept of “co-evolutionary time”, which the authors explain through a business example from the tourism industry. Supported by a narrative-based style, from a methodological point of view the framework is featured by the attempt to synthesize specific, extant literature into new theoretical development.

As its main theoretical contribution, the co-evolutionary time suggests how firms can adapt in a way that, from an evolutionary perspective, proves fitting both in terms of contents and methods, thus opening possibilities for new long-term social construction and reconstruction. As its main practical contribution, co-evolutionary time can constitute not only a temporary source of organizational success and competitive advantage but also an agent of enduring change and long-term business survival.

As its main novelty, the framework is developed through merging two literature streams. In particular, the authors first consider the literature about time, with a focus on its objective and subjective dimensions. The authors then consider the literature about organizational evolution, with a focus on the co-evolutionary nature of the firm/environment relationship.

The purpose of this paper is to address the challenging issue of developing a quantitative approach for the representation of cultural significance data in heritage information systems (HIS). The authors propose to provide experts in the field with a dedicated framework to structure and integrate targeted data about historical objects' significance in such environments.

This research seeks the identification of key indicators which allow to better inform decision-makers about cultural significance. Identified concepts are formalized in a data structure through conceptual data modeling, taking advantage on unified modeling language (HIS). The design science research (DSR) method is implemented to facilitate the development of the data model.

This paper proposes a practical solution for the formalization of data related to the significance of objects in HIS. The authors end up with a data model which enables multiple knowledge representations through data analysis and information retrieval.

The framework proposed in this article supports a more sustainable vision of heritage preservation as the framework enhances the involvement of all stakeholders in the conservation and management of historical sites. The data model supports explicit communications of the significance of historical objects and strengthens the synergy between the stakeholders involved in different phases of the conservation process.

In the COVID-19 era, sign language (SL) translation has gained attention in online learning, which evaluates the physical gestures of each student and bridges the communication gap between dysphonia and hearing people. The purpose of this paper is to devote the alignment between SL sequence and nature language sequence with high translation performance.

SL can be characterized as joint/bone location information in two-dimensional space over time, forming skeleton sequences. To encode joint, bone and their motion information, we propose a multistream hierarchy network (MHN) along with a vocab prediction network (VPN) and a joint network (JN) with the recurrent neural network transducer. The JN is used to concatenate the sequences encoded by the MHN and VPN and learn their sequence alignments.

We verify the effectiveness of the proposed approach and provide experimental results on three large-scale datasets, which show that translation accuracy is 94.96, 54.52, and 92.88 per cent, and the inference time is 18 and 1.7 times faster than listen-attend-spell network (LAS) and visual hierarchy to lexical sequence network (H2SNet) , respectively.

In this paper, we propose a novel framework that can fuse multimodal input (i.e. joint, bone and their motion stream) and align input streams with nature language. Moreover, the provided framework is improved by the different properties of MHN, VPN and JN. Experimental results on the three datasets demonstrate that our approaches outperform the state-of-the-art methods in terms of translation accuracy and speed.