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Land is the basis for economic development as well as tourism development. There is a close relationship between tourism development and the land market. However, research on the effect of tourism development on land prices is insufficient. This paper aims to investigate the effect and mechanism of tourism development on land prices.

The econometric paradigm is the main research method. Fixed effect models, instrumental variable models and mediating effect models are introduced to examine the impact of tourism development on land prices. The data include three types: land transaction data, city-level data and scenic spot data. More than 360,000 samples of land transactions for 284 prefecture-level cities in China from 2007 to 2021 are applied.

Tourism development can significantly increase land prices. This conclusion holds after using instrumental variables to address endogeneity and testing for robustness. Meanwhile, tourism development’s effect on land price is influenced by land type, city type, city tier and city location. The land price increase effect of tourism is more significant for tourism land, tourist cities, central cities and Western cities. The paper also reveals the mechanisms of the public service enhancement effect, infrastructure upgrading effect and environmental optimization effect in tourism development’s effect on land price.

The study contributes to the literature on the relationship between tourism development and land market. The generality and specificity of tourism development’s effect on land price are revealed from the micro and macrolevel research level. The findings enrich the literature on tourism price effects, point to rational ways to optimize and regulate land prices and provide new ideas for land-market development.

Psychological ownership has been a topic of intense debate for several decades, especially in the digital era. In addition, as part of the digital public domain, virtual communities shape our digital lives. Unfortunately, few studies have examined the communication process in virtual communities from the perspective of psychological ownership. Moreover, information and organization are key aspects of virtual communities. This research aimed to explore the impact of psychological ownership on communication satisfaction from these two perspectives.

I collected 471 responses using a questionnaire. In terms of empirical methods, I developed a structural equation model (SEM) to examine the relationship between psychological ownership and communication satisfaction as well as the mechanism underlying this relationship – namely, information behavior. Specifically, I first examined the relationship between psychological ownership and information behavior. I then developed a comprehensive framework for the double-edged impact of psychological ownership in virtual communities on communication satisfaction.

I found that psychological ownership has a double-edged effect on communication satisfaction based on two types of information behavior in virtual communities. Specifically, organization-based psychological ownership (OPO) positively influences communication satisfaction through information exchange. In contrast, information-based psychological ownership (IPO) negatively impacts communication satisfaction through information-hiding.

The findings of this research demonstrate that psychological ownership has a double-edged effect on communication satisfaction. First, the findings of this study reveal the downsides of psychological ownership, which are not consistent with its beneficial role. Second, the negative effect of psychological ownership with regard to communication in virtual communities also helps explain communication failure in virtual communities. Finally, despite the downsides of psychological ownership in the context of a virtual community revealed by this study, this factor has an overall beneficial effect.

This study aimed to investigate the relationship between supply chain resilience and organizational performance with innovation as a mediator and information sharing as a moderator.

The study thoroughly explored how supply chain resilience, organizational performance, innovation and information sharing are connected. It used an exploratory approach and quantitative methods. Data were collected from large manufacturing firms through online questionnaire surveys using Google Forms, emails and WhatsApp.

The findings demonstrated that supply chain resilience positively impacts sustainability efforts. Furthermore, leveraging innovation and effective information sharing mediated and moderated the relationship, playing pivotal roles in enhancing sustainability within the supply chain.

The study provided actionable insights for businesses to strengthen their sustainability efforts. Managers could utilize these findings to implement strategies that enhance supply chain resilience, drive innovation and promote effective information sharing, ultimately leading to a more sustainable supply chain.

This study contributed to the existing body of knowledge by examining the complex relationships between supply chain resilience, organizational performance, innovation and information sharing in the context of achieving sustainability. The exploration of these components in a holistic manner added originality to the research and shed light on effective strategies for sustainable supply chain management.

In today's fast developing era, the volume of data is increasing day by day. The traditional methods are lagging for efficiently managing the huge amount of data. The adoption of machine learning techniques helps in efficient management of data and draws relevant patterns from that data. The main aim of this research paper is to provide brief information about the proposed adoption of machine learning techniques in different sectors of manufacturing supply chain.

This research paper has done rigorous systematic literature review of adoption of machine learning techniques in manufacturing supply chain from year 2015 to 2023. Out of 511 papers, 74 papers are shortlisted for detailed analysis.

The papers are subcategorised into 8 sections which helps in scrutinizing the work done in manufacturing supply chain. This paper helps in finding out the contribution of application of machine learning techniques in manufacturing field mostly in automotive sector.

The research is limited to papers published from year 2015 to year 2023. The limitation of the current research that book chapters, unpublished work, white papers and conference papers are not considered for study. Only English language articles and review papers are studied in brief. This study helps in adoption of machine learning techniques in manufacturing supply chain.

This study is one of the few studies which investigate machine learning techniques in manufacturing sector and supply chain through systematic literature survey.

1. A comprehensive understanding of Machine Learning techniques is presented.

2. The state of art of adoption of Machine Learning techniques are investigated.

3. The methodology of (SLR) is proposed.

4. An innovative study of Machine Learning techniques in manufacturing supply chain.

A comprehensive understanding of Machine Learning techniques is presented.

The state of art of adoption of Machine Learning techniques are investigated.

The methodology of (SLR) is proposed.

An innovative study of Machine Learning techniques in manufacturing supply chain.

This paper explores emerging technologies in higher education libraries indexed in the Web of Science core collection and Scopus for the periods between 1994 and 2024 (January 18, 2024).

Data from Web of Science (WoS) and Scopus databases were collected and combined using RStudio software. Once this was completed using RStudio, the combined Scopus and Web of Science Excel file was uploaded into Biblioshiny, an interactive web interface. The data was then categorized to illustrate contributions from authors, journals, countries and academic institutions across the globe.

Results and findings related to publication growth trends, annual growth, core journals, impact and productivity of authors, most cited documents, collaborations, network mapping and country contributions on emerging technologies and higher education libraries are presented.

This topic requires further exploration as academic librarians are fast becoming integrated into the teaching and learning agenda of institutions globally.

Higher education libraries and library schools to promote the teaching identity of academic librarians by helping them improve their pedagogical and digital skills for online teaching.

Library and information science schools need to fast track the integration of emerging technologies into the curriculum. Higher education libraries should consider the training of staff in order to keep abreast of emerging technologies. Library management must frame their policies and strategies in order to promote the use of emerging technologies in higher education libraries.

The current study is novel in that it explores emerging technologies and higher education libraries using combined data from Scopus and Web of Science. The topic of emerging technologies and higher education libraries is still developing and therefore is in its infancy. The research is useful for researchers, library management and library schools in the higher education sector globally.

This paper aims to map the evolution of hydrogen-based technologies (HBTs) by examining the patenting activity associated to these technlogies from 1930 to 2020. In doing so, the study provides a novel perspective on the development of HBTs and offers implications for managers and policymakers.

We collected patent data at the level of patent families (PFs). Our sample includes 317,089 PFs related to hydrogen production and 62,496 PFs to hydrogen storage. We examined PF data to delineate the state of the art and major technical advancements of HBTs.

Our analysis provides evidence of an increasing patenting activity in the area of HBTs, hence suggesting relatively high levels of expectations on the economic potential of these technologies. US and Japan hold the largest proportion of PFs related to HBTs (about 60%), while European applicants hold the highest proportion of highly cited PFs (about 60%). While firms represent the applicant with the highest share of PFs, our analysis reveals that firms holding HBT PFs are primarily from the chemical sector.

While our analysis is limited to examining patent data which capture some aspects of the innovation activity around HBTs (namelly, patented inventions), our study enriches existing literature by performinng a patent analysis on a much larger sample of data when compared to previous studies.

Two main implications emerge from our study. Firstly, there seems to be an urgent need to support the emergence of a dominant design so as to facilitate the consolidation and diffusion of the HBTs, hence the transition to a more sustainable energy production. Secondly, the majority of HBT PFs are held by a small number of countries. This, in turn, suggests opportunities to develop cross-country cooperation (e.g. international agreements, research and technology offices) to support the development and adoption of HBTs globally.

Considering the results obtained in this study, from a social point of view, the attention that organizations have paid to hydrogen related technologies is evident. This suggests that the development HBTs can function as a social enabler for a sustianable energy transition.

Extant research has focused on the individual components of the hydrogen chain. As a result, we lack a comprehensive understanding of the progress made in the area of HBTs. To address this gap, this study examined HBTs by focusing on both production and storage technologies since their initial developments, hence adopting an observation period of about 70 years.

The purpose of this study is to examine the influence of perceived risk (perceived susceptibility and perceived severity), self-efficacy and individual differences (personal innovativeness and mobile payment knowledge) on consumers’ intention to use contactless mobile payment services (MPS). Additionally, it also empirically tested the moderating effect of hygiene consciousness in the proposed conceptual model.

The present research developed a conceptual model based on the health belief model (HBM) and diffusion of innovation theory (DOI) to empirically assess whether and how perceived risk, self-efficacy and individual differences influence consumer intention to use contactless MPS. The data was collected using the survey method from 251 smartphone users and analyzed with structural equation modeling. The moderating role of hygiene consciousness was studied in the relationship that self-efficacy and personal innovativeness shares with consumers’ intention toward contactless MPS.

The results of this study disclose that among all precursors of consumers’ intention toward contactless MPS, only perceived severity, self-efficacy, personal innovativeness and mobile payment knowledge positively affect consumers’ intention to use contactless MPS. However, the effect of perceived susceptibility on consumers’ intention toward contactless MPS was found to be non-significant. The results further depict that hygiene consciousness acts as a moderator in driving consumers’ intention toward contactless mobile payment services.

The HBM model and DOI, which incorporate perceived risk, self-efficacy, individual differences and hygiene consciousness, give light on the factors influencing consumer intention to use contactless MPS in a pandemic situation such as COVID-19. The study will provide useful insights to marketers on how to frame their strategies in the aftermath of pandemics, as the contactless mobile payment method may be perceived as a defensive behavior during and after pandemics.

The study will provide useful insights to marketers on how to frame their strategies in the aftermath of pandemics, as the contactless mobile payment method may be perceived as a defensive behavior during and after pandemics.

By uniting perceived risk, self-efficacy and individual differences with consumers’ intention toward contactless MPS in a conceptual model, along with examining the moderating role of hygiene consciousness, this work responds to the calls for upcoming research concerning mobile payment systems as means of future payment. Thus, it offers an understanding of particular consumer motivations that may guide consumers’ intention toward contactless MPS through the theoretical lens of HBM and DOI.

Following the recent rise in generative artificial intelligence (GenAI) tools, fundamental questions about their wider impacts have started to reverberate around various disciplines. This study aims to track the unfolding landscape of general issues surrounding GenAI tools and to elucidate the specific opportunities and limitations of these tools as part of the technology-assisted enhancement of mechanical engineering education and professional practices.

As part of the investigation, the authors conduct and present a brief scientometric analysis of recently published studies to unravel the emerging trend on the subject matter. Furthermore, experimentation was done with selected GenAI tools (Bard, ChatGPT, DALL.E and 3DGPT) for mechanical engineering-related tasks.

The study identified several pedagogical and professional opportunities and guidelines for deploying GenAI tools in mechanical engineering. Besides, the study highlights some pitfalls of GenAI tools for analytical reasoning tasks (e.g., subtle errors in computation involving unit conversions) and sketching/image generation tasks (e.g., poor demonstration of symmetry).

To the best of the authors’ knowledge, this study presents the first thorough assessment of the potential of GenAI from the lens of the mechanical engineering field. Combining scientometric analysis, experimentation and pedagogical insights, the study provides a unique focus on the implications of GenAI tools for material selection/discovery in product design, manufacturing troubleshooting, technical documentation and product positioning, among others.

Blockchain, a groundbreaking technology that recently surfaced, is under thorough scrutiny due to its prospective utility across different sectors. This research aims to delve into and assess the cognitive elements that impact the integration of blockchain technology (BT) within library environments.

Utilizing the Stimulus–Organism–Response (SOR) theory, this research aims to facilitate the implementation of BT within academic institution libraries and provide valuable insights for managerial decision-making. A two-staged deep learning structural equation modelling artificial neural network (ANN) analysis was conducted on 583 computer experts affiliated with academic institutions across various countries to gather relevant information.

The research model can correspondingly expound 71% and 60% of the variance in trust and adoption intention of BT in libraries, where ANN results indicate that perceived possession is the primary predictor, with a technical capability factor that has a normalized significance of 84%. The study successfully identified the relationship of each variable of our conceptual model.

Unlike the SOR theory framework that uses a linear model and theoretically assumes that all relationships are significant, to the best of the authors’ knowledge, it is the first study to validate ANN and SEM in a library context successfully. The results of the two-step PLS–SEM and ANN technique demonstrate that the usage of ANN validates the PLS–SEM analysis. ANN can represent complicated linear and nonlinear connections with higher prediction accuracy than SEM approaches. Also, an importance-performance Map analysis of the PLS–SEM data offers a more detailed insight into each factor's significance and performance.

This study aims to examine the factors driving the adoption of carbon management accounting (CMA) and various considerations that mediate its effectiveness in accounting and disclosure practices.

This study used an exploratory, cross-sectional, quantitative design. Academics, managements/executives, professional accountants, professional auditors and researchers served as the primary units of analysis. This study used a survey method to gather data through a structured online questionnaire. The data were analyzed using descriptive statistics and partial least squares structural equation modeling (PLS-SEM).

The results revealed that the factors driving the adoption of CMA directly influence the effectiveness of CMA practices, with a significant mediating effect of regulatory and ethical aspects. Furthermore, this study revealed the difficulty of accounting, quantifying and reporting carbon emissions and revenue generation from the trading of carbon credits. This highlights the critical role of standard-setters and academics in deciding the concrete methodology to promote uniformity in carbon disclosures.

The major limitations of this study are that it considered only the perception of experts and did not study the actual practices of CMA by considering companies that have already implemented CMA. Further studies should consider this aspect to validate the results of this study. Furthermore, the findings highlight the insignificant effect of economic, environmental and social aspects in enhancing the overall effectiveness of CMA. This is because of the limited number of factors considered in the study of such metrics. To overcome this limitation, future studies should consider wider aspects to validate the outcomes of this study.

The major contribution of this study is that it serves as a base input for business organizations, academics, researchers and regulatory authorities who are working to implement CMA strategies to reduce carbon emissions and promote net-zero business practices.

The outcome of this study is unique and new, as the subject matter of this study is in the nascent stage. The outcome of this study may become a significant valid input for regulators and policymaking companies to gain knowledge about CMA practices and motivate them to integrate CMA practices as part of their sustainability initiatives.