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This study aimed to explore the spatial accessibility dynamics of urban parks and their driving forces from 1901 to 2010 in terms of the dynamic relationships between spatial morphology and road networks, taking Nanjing City as an example.

This study mapped and examined the spatiotemporal distribution of urban parks and road networks in four time points at Nanjing: the 1910s, 1930s, 1960s and 2010s, using the analysis methodology of spatial design network analysis, kernel density estimation and buffer analysis. Two approaches of spatial overlaying and data analysis were adopted to investigate the accessibility dynamics. The spatial overlaying compared the parks' layout and the road networks' core, subcore and noncore accessible areas; the data analysis clarified the average data on the city-wide and local scales of the road networks within the park buffer zone.

The analysis of the changing relationships between urban parks and the spatial morphology of road networks showed that the accessibility of urban parks has generally improved. This was influenced by six main factors: planning implementation, political policies, natural resources, historical heritage and cultural and economic levels.

The results provide a reference for achieving spatial equity, improving urban park accessibility and supporting sustainable urban park planning.

An increasing number of studies have explored the spatial accessibility of urban parks through the relationships between their spatial distribution and road networks. However, few studies have investigated the dynamic changes in accessibility over time. Discussing parks' accessibility over relatively long-time scales has practical, innovative and theoretical values; because it can reveal correlational laws and internal influences not apparent in short term and provide reference and implications for parks' spatial equity.

Blockchain technology has been recognized as a potential solution to the challenges in managing healthcare information. Its adoption in the healthcare industry has garnered the attention of healthcare institutions and governments. Given the significant role of subsidies in promoting technology adoption, this study applies evolutionary game theory to examine the impact of government subsidies on the adoption of blockchain technology by healthcare institutions.

First, the authors analyze the interests of government administration departments and healthcare institutions separately in regards to blockchain adoption. Subsequently, the authors develop the payoff matrix of both participants and construct the evolutionary game model. And then, the authors calculate the replication dynamic equations and analyze the decision evolution of both participants through the replication dynamic equations and numerical experiments.

The numerical experiments demonstrate that government subsidies are effective in encouraging healthcare institutions to adopt blockchain technology. The study also reveals the necessary amount of subsidy required to guide healthcare institutions towards adoption. Additionally, the validity of the evolutionary game model in analyzing the interaction between governments and healthcare institutions is confirmed by the results.

Blockchain adoption in the healthcare industry differs from other emerging technologies, as there is the potential for it to reduce revenue for healthcare institutions. This study contributes to the analysis of theoretical models for promoting blockchain in the healthcare industry through subsidies. Additionally, it demonstrates the potential of evolutionary game theory in analyzing the adoption of blockchain technology, and the interaction between governments and healthcare institutions.

Industry 4.0 has put forward a smart perspective on managing supply chain networks and their operations. The current manufacturing system is primarily data-driven. Industries are deploying new emerging technologies in their operations to build a competitive edge in the business environment; however, the true potential of smart manufacturing has not yet been fully unveiled. This research aims to extensively analyse emerging technologies and their interconnection with smart manufacturing in developing smarter supply chains.

This research endeavours to establish a conceptual framework for a smart supply chain. A real case study on a smart factory is conducted to demonstrate the validity of this framework for building smarter supply chains. A comparative analysis is carried out between conventional and smart supply chains to ascertain the advantages of smart supply chains. In addition, a thorough investigation of the several factors needed to transition from smart to smarter supply chains is undertaken.

The integration of smart technology exemplifies the ability to improve the efficiency of supply chain operations. Research findings indicate that transitioning to a smart factory radically enhances productivity, quality assurance, data privacy and labour efficiency. The outcomes of this research will help academic and industrial sectors critically comprehend technological breakthroughs and their applications in smart supply chains.

This study highlights the implications of incorporating smart technologies into supply chain operations, specifically in smart purchasing, smart factory operations, smart warehousing and smart customer performance. A paradigm transition from conventional, smart to smarter supply chains offers a comprehensive perspective on the evolving dynamics in automation, optimisation and manufacturing technology domains, ultimately leading to the emergence of Industry 5.0.

The purpose of this paper is to identify and prioritise supply chain finance (SCF) adoption enablers and develop a novel comprehensive framework to select supplier firms based on their SCF adoption capability.

The study deploys a three-phase method to identify and prioritise SCF adoption enablers, followed by developing a model to select suppliers according to their SCF adoption capability. An extensive literature review, followed by a Delphi approach-based expert interview, has been used to finalise the enablers. Using the Best Worst Method and the VIsekriterijumsko KOmpromisno Rangiranje technique, a supplier selection model has been developed in the context of a case company.

The financial health and technological advancement variables received the top priority, followed by collaborative efficiency, whereas the human resources and organisational variables received the slightest significance. A supplier selection framework has also been developed by using the adoption capability of these factors by the supplier partners. In this study’s model, Supplier 4 exhibited better SCF adoption capability and received the top priority.

Manufacturing supply chains in a developing country are the scope of the current study. Extensive future studies are required to derive a global consensus.

The proposed framework of this study can be used to select supplier firms based on their SCF adoption capability. Policymakers can emphasise the most critical enablers of SCF adoption to assist small supplier firms to be a part of the advanced global supply chains.

The current study established a novel comprehensive framework for supplier selection based on the Supply Chain Finance adoption capability of MSME supplier firms.

Knowledge adoption is the key to effective knowledge exchange in virtual question-and-answer (Q&A) communities. Although previous studies have examined the effects of knowledge content, knowledge source credibility and the personal characteristics of knowledge seekers on knowledge adoption in virtual Q&A communities from a static perspective, the impact of answer deviation on knowledge adoption has rarely been explored from a context-based perspective. The purpose of this study is to explore the impact of two-way deviation on knowledge adoption in virtual Q&A communities, with the aim of expanding the understanding of knowledge exchange and community management.

The same question and the same answerer often yield multiple answers. Knowledge seekers usually read multiple answers to make adoption decisions. The impact of deviations among answers on knowledge seekers' knowledge adoption is critical. From a context-based perspective, a research model of the impact of the deviation of horizontal and vertical answers on knowledge adoption is established based on the heuristic-systematic model (HSM) and empirically examined with 88,287 Q&A data points and answerer data collected from Zhihu. Additionally, the moderation effects of static factors such as answerer reputation and answer length are examined.

The negative binomial regression results show that the content and emotion deviation of horizontal answers negatively affect knowledge seekers' knowledge adoption. The content deviation of vertical answers is negatively associated with knowledge adoption, while the emotion deviation of vertical answers is positively related to knowledge adoption. Moreover, answerer reputation positively moderates the negative effect of the emotion deviation of horizontal answers on knowledge adoption. Answer length weakens the negative correlation between the content deviation of horizontal and vertical answers and knowledge adoption.

This study extends previous research on knowledge adoption from a static perspective to a context-based perspective. Moreover, information deviation is expanded from a one-way variable to a two-way variable. The combined effects of static and contextual factors on knowledge adoption are further uncovered. This study can not only help knowledge seekers identify the best answers but also help virtual Q&A community managers optimize community design and operation to reduce the cost of knowledge search and improve the efficiency of knowledge exchange.

The purpose of this study is to explore the impact of online reviews on answer adoption in virtual Q&A communities, with an eye toward extending knowledge exchange and community management.

Online reviews contain rich cognitive and emotional information about community members regarding the provided answers. As feedback information on answers, it is crucial to explore how online reviews affect answer adoption. Based on signaling theory, a research model reflecting the influence of online reviews on answer adoption is established and empirically examined by using secondary data with 69,597 Q&A data and user data collected from Zhihu. Meanwhile, the moderating effects of the informational and emotional consistency of reviews and answers are examined.

The negative binomial regression results show that both answer-related signals (informational support and emotional support) and answerers-related signals (answerers’ reputations and expertise) positively impact answer adoption. The informational consistency of reviews and answers negatively moderates the relationships among information support, emotional support and answer adoption but positively moderates the effect of answerers’ expertise on answer adoption. Furthermore, the emotional consistency of reviews and answers positively moderates the effect of information support and answerers’ reputations on answer adoption.

Although previous studies have investigated the impacts of answer content, answer source credibility and personal characteristics of knowledge seekers on answer adoption in virtual Q&A communities, few have examined the impact of online reviews on answer adoption. This study explores the impacts of informational and emotional feedback in online reviews on answer adoption from a signaling theory perspective. The results not only provide unique ideas for community managers to optimize community design and operation but also inspire community users to provide or utilize knowledge, thereby reducing knowledge search costs and improving knowledge exchange efficiency.

During COVID-19 restrictions, people spent more time in cyberspace and consuming health-related information. An increase was also observed in mediated caring messages or health-relevant information sent to one another. This study aims to explore how the information and interactions around COVID-19 can provide a good learning opportunity for public health, specifically related to eHealth literacy and eHealth promotion.

While mainstream literature has concentrated on experimental designs and a priming effect, this study inspects psychological distance related to a health threat under real-life circumstances. The article adopted a survey approach and utilized PLS-SEM techniques to examine the proposed hypotheses.

Results indicated that whereas closer social support correlates with closer psychological distance and less usage of the social media approach, more substantial COVID-19 impacts were associated with closer psychological distance but greater use of social media. Since both closer psychological distance and social media approach contribute to eHealth literacy, social support from closer and virtual social networks should be embraced but utilized through different routes and for different purposes. The timing of messages but not psychological distance affects people's social media approach, indicating that morning messages should be employed. Moreover, eHealth literacy mediates timing preferences and leads to a preference for eHealth communication earlier in the day. Overall, morning messages create a virtuous circle during a health crisis.

This paper establishes a mechanism of virtuous cycles for eHealth communication during a health threat. Additionally, it bridges existing research gaps by expanding chronopsychology and CLT in the health domain using an empirical approach, a real-life case and an extension of performance regarding information-seeking and utilization.

The environment in which users acquire medical and health information has changed dramatically, with online health communities (OHCs) emerging as an essential means for accessing health information. It is imperative to comprehend the factors that shape the users' compliance willingness (UCW) to health information in OHCs.

This study adopted the information adoption model (IAM) and theory of planned behavior (TPB) to investigate the influence of argument quality (AQ), source credibility (SC) and subjective norms (SN) on UCW while considering the two types of online health information – mature and emerging treatments. The authors conducted an explanatory-predictive study based on a 2 (treatment types: mature vs. emerging) * 2 (AQ: high vs. low) * 2 (SC: high vs. low) scenario-based experiment, using the partial least squares structural equation modeling (PLS-SEM).

SC positively influences AQ. AQ, SC and SN contribute to information usefulness (IU). These factors positively affect UCW through the mediation of IU. SN were found to improve UCW directly. Moreover, the moderating effect of SC on AQ and IU was more substantial for emerging treatments.

The research model integrates IAM and TPB, considering information types as an additional variable. The approach and findings provide a valuable explanation for UCW to health information in OHCs.

This paper aims to investigate why followers have low perceptions of leader openness and thus feel reluctant to communicate novel ideas by examining leader–follower relationship conflict (i.e. interpersonal incompatibility) and a follower’s power distance orientation (i.e. an acceptance of uneven power distribution in organizations) as antecedents.

The research administrators conducted a three-wave work behavior survey in Study 1, a laboratory experiment in Study 2, and an online experiment in Study 3.

The results demonstrated that leader–follower relationship conflict reduced followers’ perceptions of leader openness. However, the negative impact of relationship conflict became non-significant when followers have high power distance orientations (i.e. an acceptance of uneven power distribution in organizations). The findings also showed an indirect interaction effect of leader–follower relationship conflict and followers’ power distance orientation on the followers’ communication of novel ideas through the followers’ perceptions of leader openness.

The research suggests that followers with higher power distance orientations are more likely to communicate novel ideas consistently because their relationship conflicts with their leaders do not negatively influence their perceptions of leader openness. Although researchers traditionally view cultures with a high level of power distance value as an obstacle to employee creativity, the present study reveals the benefits of an individual-level power distance orientation.

Digital transformation is a foundational change in how firms operate and deliver value to customers by using digital technologies to create new business opportunities. The purpose of this study is to offer a conceptual framework by reorganizing the elements of digital transformation, including resources, technology, capabilities and performance, into a workable process and investigating how firms integrate these resources, build new capabilities and transform them into enhanced performance.

This framework builds three blocks: resource integration, organizational capabilities and outcomes, exploring the impact of resource integration on outcomes through organizational capabilities. For resource integration, this study adopts a resource-based view (RBV) and service-dominant logic (SDL) to integrate organizational resources, including information technology (IT)-based resources, which play a role in moderating the effect of resource integration. Moreover, the author argues that firms’ capabilities have two levels: higher-order capabilities and lower-order capabilities, which will convert these resources through the capabilities into organizational performance.

This framework is built to understand the process of digital transformation and its antecedents for firms’ performance in business environments. Drawing on RBV, it provides a more holistic perspective that has been linked to resource integration, organizational capabilities and outcomes at the firm level. In this way, the theoretical basis for diminishing implicitness associated with the current perspective of digital transformation can be strengthened.

This paper offers a coherent discussion of digital transformation and explains the process of digital transformation, thus advancing prior work. The major contribution is connecting the process of digital transformation through which firms integrate resources, i.e. digital technologies and valuable, rare, inimitable and nonsubstitutable (VRIN) and nonVRIN resources as well, to build organizational dynamic capabilities based on RBV and SDL.