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This study aims to explore the relationship between elderly users' trust in public digital cultural services (PDCS) and their intention to use PDCS, and reveal the factors affecting their intentions from the perspective of trust to make recommendations that will increase their intention to use PDCS.

Combined with the trust building model and social exchange theory, this study constructed a conceptual model of elderly users' intention to use PDCS. Data collected from Chinese elderly users who have reached the age of 60 through questionnaire surveys were tested using the structural equation model with partial least squares. Finally, the authors proposed a model of elderly users' intention to use PDCS.

This study finds that elderly users' trust positively affects their intention to use PDCS from two aspects: service features and user features of PDCS. Concerning the service features, system quality directly affects elderly users' trust in PDCS most significantly, followed by information quality and service reputation. Concerning the user features, perceived value has a higher impact on elderly users' trust than that of service features, and information literacy and information quality directly affect perceived value.

This study adds new knowledge to the users' behavior of PDCS and enriches the prior description of PDCS. The recommendations made in this study provide a series of strategies for practitioners and researchers to improve the elderly users' intention to use PDCS and bridge the silver digital divide, which offers new ideas for improving the efficiency of PDCS.

This paper considers carbon abatement in a competitive supply chain that is composed of a manufacturer and two retailers under vertical shareholding. The authors emphasize the equilibrium decision problem of stakeholders under vertical shareholding and different power structures.

A game-theoretic approach was used to probe the influence of power structure and retailer competition on manufacturers' carbon abatement under vertical shareholding. The carbon abatement decisions, environmental imp4cacts (EIs) and social welfare (SW) of different scenarios under vertical shareholding are obtained.

The findings show that manufacturers are preferable to carbon abatement and capture optimal profits when shareholding is above a threshold under the retailer power equilibrium, but they may exert a worse negative impact on the environment. The dominant position of the held retailer is not always favorable to capturing the optimal SW and mitigating EIs. In addition, under the combined effect of competition level and shareholding, retailer power equilibrium scenarios are more favorable to improving SW and reducing EIs.

This paper inspects the combined influence of retailer competition and power structure on manufacturers' carbon abatement. Distinguishing from previous literature, the authors also consider the impact of vertical shareholding and consumer preferences. In addition, the authors analyze the SW and EIs in different scenarios.

Integrating artificial intelligence and quantitative investment has given birth to various agricultural futures price prediction models suitable for nonlinear and non-stationary data. However, traditional models have limitations in testing the spatial transmission relationship in time series, and the actual prediction effect is restricted by the inability to obtain the prices of other variable factors in the future.

To explore the impact of spatiotemporal factors on agricultural prices and achieve the best prediction effect, the authors innovatively propose a price prediction method for China's soybean and palm oil futures prices. First, an improved Granger Causality Test was adopted to explore the spatial transmission relationship in the data; second, the Seasonal and Trend decomposition using Loess model (STL) was employed to decompose the price; then, the Apriori algorithm was applied to test the time spillover effect between data, and CRITIC was used to extract essential features; finally, the N-Beats model was selected as the prediction model for futures prices.

Using the Apriori and STL algorithms, the authors found a spillover effect in agricultural prices, and past trends and seasonal data will impact future prices. Using the improved Granger causality test method to analyze the unidirectional causality relationship between the prices, the authors obtained a spatial effect among the agricultural product prices. By comparison, the N-Beats model based on the spatiotemporal factors shows excellent prediction effects on different prices.

This paper addressed the problem that traditional models can only predict the current prices of different agricultural products on the same date, and traditional spatial models cannot test the characteristics of time series. This result is beneficial to the sustainable development of agriculture and provides necessary numerical and technical support to ensure national agricultural security.

Blockchain technology (BCT), since its emergence touted to be disruptive, is gaining momentum, especially in the agri-food system owing to its multiple benefits.

The authors attempted to conduct a systematic bibliometric visualization analysis of the BCT in the agri-food system. The analysis investigated the list of countries and institutions that conducted research on BCT in agriculture, growth trend analysis in research publications, bibliographic coupling of journals using the VOSviewer tool, and the countries and institutions researching BCT.

The authors discovered that China, the USA and India were the highly active countries in BCT research and publication. However, India has only limited research collaboration with other countries as compared to China and the USA. The keyword analysis indicates the role of BCT in order to maintain the transparency of the supply chain by means of protecting the privacy of the personal data of the stakeholders.

More research related to the implementation of BCT in livestock, fishery and agro-forestry sector is recommended.

The case examined is of particular interest as it is concerned with efficient supply chain management.

This study adds value and evidence to the scope and benefits of BCT by providing a comprehensive literature review, with a special focus on the opportunities and challenges concerned with implementation of BCT in the Indian agri-food system.

1. Blockchain technology (BCT) – a promising tool to resolve issues in agriculture supply chain.

2. BCT ensures transparency and protection of information along the supply chain transactions.

3. China, the USA and India are the highly active countries in BCT research and publication.

4. Multiple potential benefits to stakeholders are attributed to the BCT in the agri-food system.

5. The key challenge is to bridge the digital gap between developed and developing nations.

6. Future research on BCT should aim at easing and undistorted competition among stakeholders.

Blockchain technology (BCT) – a promising tool to resolve issues in agriculture supply chain.

BCT ensures transparency and protection of information along the supply chain transactions.

China, the USA and India are the highly active countries in BCT research and publication.

Multiple potential benefits to stakeholders are attributed to the BCT in the agri-food system.

The key challenge is to bridge the digital gap between developed and developing nations.

Future research on BCT should aim at easing and undistorted competition among stakeholders.

Corona Virus Disease (Covid-19) is a global pandemic that emerged at the end of 2019 and caused disruptions in global supply chains, particularly in the food supply chains that exposed the vulnerability of today’s food supply chain in a major disruption which provided a unique research opportunity. This review explores the current research direction for food supply chain resilience and identifies gaps for future research in preparing for future major global pandemics.

This article presents a review of food supply chain resilience followed a systematic literature review of the business and management-based studies related to the food supply chain in Covid-19 published between December 2019 and December 2021 to identify the immediate issues and responses that need to be addressed in the event of future disruptions in food supply chains due to new global health threats.

The study revealed the need for more literature on food supply chain resilience, particularly resilience to a major global pandemic. The study also uncovered the sequence of events in a major pandemic and identified some strategies for building resilience to potential future risks of such an event.

The limitations of this study are apparent. Firstly, the selection of databases is not comprehensive. Due to time limitations, authoritative publishers such as Springer, Emerald, Wiley and Taylor & Francis were not selected. Secondly, a single author completed the literature quality testing and text analysis, possibly reducing the credibility of the results due to subjective bias. Thirdly, the selected literature are the studies published during the immediate event of Covid-19, and before January 2022, other research studies may have been completed but were still in the state of auditing at this time.

This paper is the first study that provides a detailed classification of the immediate challenges to the food supply chain faced in both upstream and downstream nodes during a major global disruption. For researchers, this clearly shows the immediate difficulties faced at each node of the food supply chain, which provides research topics for future studies.

In tourism live streaming (TLS), streamers strive to capture viewers’ attention by responding quickly to viewers’ requests and providing tourism-related knowledge. However, the effectiveness of such practices in the TLS context remains unclear. Accordingly, based on flow theory, this study aims to uncover the effects of responsiveness and knowledge spillover on viewers’ travelling intentions.

The authors collected 319 valid questionnaires to examine the proposed model. Followingly, the authors used a partial least squares structural equation modelling approach using SmartPLS 4 to analyse the survey data.

The authors found that responsiveness could enhance viewers’ flow experience and destination attachment, fostering travelling intentions. The authors further found that knowledge spillover strengthened the relationship between responsiveness and travelling intentions and responsiveness and flow experience.

This study broadens the scope of extant tourism research by juxtaposing the effects of responsiveness and knowledge spillover on viewers’ travelling intentions in the TLS context. Practically, the findings provide valuable insights for streamers to conduct appropriate viewer–streamer interaction strategies by providing instant responses and tourism-related knowledge to viewers.

在旅游直播中, 主播常常通过快速响应观众并提供目的地知识, 以吸引观众注意。然而这种策略是否有效地提升了观众的旅游意愿仍需进一步验证。因此, 本研究基于心流理论验证了响应性及知识溢出效应对观众旅游意愿的影响。

我们通过评估319份有效问卷来检验所提出的模型, 采用了SmartPLS软件构建偏最小二乘结构方程模型（PLS-SEM）分析问卷数据。

我们发现, 响应性将增强观众的心流体验和目的地依恋感, 从而促进旅游意愿。此外, 知识溢出效应强化了响应性和旅游意愿及响应性和心流体验之间的关系。

本研究同时关注响应性及知识溢出在旅游直播情境下对观众旅游意愿的影响机制。从实践层面, 本研究为旅游主播提供了高效互动及目的地推广的策略。

En las retransmisiones turísticas en directo (TLS), los organizadores se esfuerzan por captar la atención de los espectadores respondiendo de forma rápida a sus peticiones y aportando conocimientos relacionados con el turismo. Sin embargo, la eficacia de estas prácticas en el contexto de la retransmisión turística en directo sigue sin estar clara. Por consiguiente, este estudio, basado en la teoría del flujo, trata de descubrir los efectos de la capacidad de respuesta y la difusión de conocimientos en la intención de viajar de los espectadores.

Se recogieron 319 cuestionarios válidos para examinar el modelo propuesto. Seguidamente, se aplicó la técnica de ecuaciones estructurales con mínimos cuadrados parciales (PLS-SEM) mediante el software SmartPLS para analizar los datos de la encuesta.

Se concluye que la capacidad de respuesta mejoraría la experiencia de flujo de los espectadores y el apego al destino, fomentando su intención de viajar. Además, se comprueba que la difusión de conocimientos fortalece la relación entre (1) la capacidad de respuesta y la intención de viajar y (2) la capacidad de respuesta y la experiencia de flujo.

La presente investigación amplía el enfoque de los estudios existentes en la investigación turística al aproximar los efectos de la capacidad de respuesta y la difusión de conocimientos sobre la intención de viajar de los espectadores en el contexto de retransmisiones turísticas en directo. Desde el punto de vista práctico, los resultados aportan ideas para que los streamers empleen estrategias de interacción apropiadas con los espectadores, proporcionándoles respuestas instantáneas y transmitiéndoles conocimientos relacionados con el turismo.

Perceived benefits of building information modelling (BIM) have been discussed for some time, but cost–benefit benchmarking has been inconsistent. The purpose of this paper is to investigate BIM feasibility and evaluate investment worth to elucidate and develop the current understanding of BIM merit. The aim of the study is to propose a research agenda towards a more holistic perspective of BIM use incorporating quantifying investment return.

An in-depth examination of research patterns has been conducted to identify challenges in the assessment of the investment value and return on investment (ROI) for BIM in the construction industry. A total of 75 research articles were considered for the final literature review. An evaluation of the literature is conducted using a combination of bibliometric analysis and systematic reviews.

This study, which analysed 75 articles, unveils key findings in quantifying BIM benefits, primarily through ROI calculation. Two major research gaps are identified: the absence of a standardized BIM ROI method and insufficient exploration of intangible benefits. Research focus varies across phases, emphasizing design and construction integration and exploring post-construction phases. The study categorizes quantifiable factors, including productivity, changes and rework reduction, requests for information reduction, schedule efficiency, safety, environmental sustainability and operations and facility management. These findings offer vital insights for researchers and practitioners, enhancing understanding of ’BIM’s financial benefits and signalling areas for further exploration in construction.

The ’study’s outcomes offer the latest insights for researchers and practitioners to create effective approaches for quantifying ’BIM’s financial benefits. Additionally, the proposed research agenda aims to improve the current limited understanding of BIM feasibility and investment worth evaluation. Results of the study could assist practitioners in overcoming limitations associated with BIM investment and economic evaluations in the construction industry.

This study aims to examine the antecedents of purchase intention toward energy efficient air conditioners by incorporating the theory of planned behavior (TPB) with two additional constructs, i.e. environmental concern and personal norms. TPB is one of the most widely used theoretical framework to study consumer behavior.

The study applied a quantitative technique using a survey method by distributing self-administered questionnaires among the Indian households who have purchased energy efficient air conditioners in the past six months or had enquired to do so. The study collected data from three select regions: Delhi and NCR, Punjab and Tri-city. The collected data of 424 respondents have been analyzed using confirmatory factor analysis and structural equation modeling.

The study posits that normative factors such as subjective norms and personal norms have a relatively higher influence on purchase intention. Despite the significant existence of environmental concern, the study did not find environmental concern directly influencing purchase intention.

The sample size of the study is too small and pertains to specific regions. Thus, it could hinder the generalizability of the results. Advertisement appeals should be related with enhancement of self-esteem in terms of making responsible and valuable contribution to environment protection through the purchase of energy efficient air conditioner.

There are a few studies in the Indian context studying consumer’s purchase intention toward energy efficient air conditioners to which this study adds. The study provides an important contribution to marketers in developing strategies for increasing purchase intention toward energy efficient air conditioners in view of their stage in the product life cycle, diffusion of product and influence of normative factors.

In the era of artificial intelligence (AI), algorithms have gained unprecedented importance. Scientific studies have shown that algorithms are frequently mentioned in papers, making mention frequency a classical indicator of their popularity and influence. However, contemporary methods for evaluating influence tend to focus solely on individual algorithms, disregarding the collective impact resulting from the interconnectedness of these algorithms, which can provide a new way to reveal their roles and importance within algorithm clusters. This paper aims to build the co-occurrence network of algorithms in the natural language processing field based on the full-text content of academic papers and analyze the academic influence of algorithms in the group based on the features of the network.

We use deep learning models to extract algorithm entities from articles and construct the whole, cumulative and annual co-occurrence networks. We first analyze the characteristics of algorithm networks and then use various centrality metrics to obtain the score and ranking of group influence for each algorithm in the whole domain and each year. Finally, we analyze the influence evolution of different representative algorithms.

The results indicate that algorithm networks also have the characteristics of complex networks, with tight connections between nodes developing over approximately four decades. For different algorithms, algorithms that are classic, high-performing and appear at the junctions of different eras can possess high popularity, control, central position and balanced influence in the network. As an algorithm gradually diminishes its sway within the group, it typically loses its core position first, followed by a dwindling association with other algorithms.

To the best of the authors’ knowledge, this paper is the first large-scale analysis of algorithm networks. The extensive temporal coverage, spanning over four decades of academic publications, ensures the depth and integrity of the network. Our results serve as a cornerstone for constructing multifaceted networks interlinking algorithms, scholars and tasks, facilitating future exploration of their scientific roles and semantic relations.

The construction industry and its activities harmfully affect the environment. Hence, adopting green building (GRB) practices can be helpful in achieving sustainable development goals. Therefore, this study aims to identify the factors affecting the intention to adopt GRB practices by extending theory of planned behavior (TPB).

Using non-probability purposive sampling technique, data was gathered from consultant and contractor engineers in the construction industry through a questionnaire. The analysis was done using partial least square-structural equation modeling technique on a useful sample of 290.

Findings revealed that the core constructs of TPB [i.e. attitude (AT), subjective norms (SUBN) and perceived behavioral control (PBC)] significantly affect the intention to adopt GRB practices. Moreover, government support and knowledge of green practices (KNGP) were found to be critical influencing factors on AT, SUBNs and PBC. Lastly, the findings confirmed that environmental concerns (ENC) play as a moderating between SUBN and intention to adopt GRB practices, as well as AT and intention to adopt GRB practices.

This study contributes to existing knowledge on GRB, offering evidence base for policy choices regarding climate change adaptation and mitigation in the construction industry.

This study provides insights from the perspective of a developing economy and confirms the applicability of TPB in the adoption of GRB practices. Moreover, this study confirms the moderation role of ENC in between TPB constructs and intention to GRB that is not tested earlier in the context of GRB. This study also confirms that government sustainable support positively affects PBC, and KNGP significantly affects SUBNs.