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Digital enabled agility reflects the transformative outset of an organisation to first upgrade its business processes digitally towards facilitating real-time information processing/capabilities. Second, tapping from real-time capabilities, digital enabled agility maximises an agile response's efficacy in enhancing the sophistication of rapidity, flexibility, and sensing involved. In this backdrop, driven by newer IT infrastructure and disruptive technology, this research accentuates on Industry 4.0 digitalisation to understand how a manufacturer can gain digital enabled agility. An empirical survey of manufacturers within the premise of Industry 4.0 is conducted. Drawn from the findings, the capabilities of traceability and visibility can be facilitated by Industry 4.0 that would improve information sharing and information quality in real-time. These capabilities are key propellants to unlock the digital extent of agility. This research however details further how this scope of agility is an extension to that of the scope of typical agility in terms of its ability to handle expansive information processing needs and dynamic coordination/resource orchestration. Insights are weaved under the purviews of (a) organisational information processing view and (b) the manufacturer who is coordinating contemporary dynamic production and allied value chain requirements. [ABSTRACT FROM AUTHOR]

This study investigates the effects of the organization of industrial Research & Development on industrial researchers' knowledge acquisition behavior. Specifically, we test a model about how the fit of individuals with their research tasks affects whether industrial researchers acquire knowledge from outside their assigned projects. Empirical analyses from the R&D laboratory of a global pharmaceutical company show that person-task-fit has a non-linear effect on the knowledge content exchanged through interpersonal interactions. Implications for the management and organization of R&D activities are discussed. [ABSTRACT FROM AUTHOR]

We consider a manufacturer and an e-platform where the manufacturer sells products through offline and e-platform channels under the cap-and-trade scheme. The interaction between the two channels produces the cross-channel effect (CCE). This manufacturer cooperates with the e-platform in the agency or reseller mode. In addition, the platform shares its observed data with the manufacturer and the blockchain can achieve traceability and high transparency of these data. We formulate a Stackelberg game to derive the following results: In the agency mode, the optimal service level is independent of (decreases with) CCE without (with) blockchain. CCE positively affects the optimal service level in the reseller mode and the optimal service level has no impact on (increases with) the cap in the agency (reseller) mode. Second, when the platform-enabled power is high (low), the platform is (not) willing to adopt blockchain. Third, coordination of the manufacturer and platform only can be achieved in the agency mode when CCE is low with blockchain. The reseller mode can (cannot) achieve coordination of the two firms with (without) blockchain. We also consider the cases where the manufacturer serves as the leader and the omni-channel strategy is adopted to check the robustness of the coordination results. [ABSTRACT FROM AUTHOR]

Sire is a Python/C++ library that is used both to prototype new algorithms and as an interoperability engine for exchanging information between molecular simulation programs. It provides a collection of file parsers and information converters that together make it easier to combine and leverage the functionality of many other programs and libraries. This empowers researchers to use sire to write a single script that can, for example, load a molecule from a PDBx/mmCIF file via Gemmi, perform SMARTS searches via RDKit, parameterize molecules using BioSimSpace, run GPU-accelerated molecular dynamics via OpenMM, and then display the resulting dynamics trajectory in a NGLView Jupyter notebook 3D molecular viewer. This functionality is built on by BioSimSpace, which uses sire's molecular information engine to interconvert with programs such as GROMACS, NAMD, Amber, and AmberTools for automated molecular parameterization and the running of molecular dynamics, metadynamics, and alchemical free energy workflows. Sire comes complete with a powerful molecular information search engine, plus trajectory loading and editing, analysis, and energy evaluation engines. This, when combined with an in-built computer algebra system, gives substantial flexibility to researchers to load, search for, edit, and combine molecular information from multiple sources and use that to drive novel algorithms by combining functionality from other programs. Sire is open source (GPL3) and is available via conda and at a free Jupyter notebook server at https://try.openbiosim.org. Sire is supported by the not-for-profit OpenBioSim community interest company. [ABSTRACT FROM AUTHOR]

Core enterprises are entering into close collaborations with multi-level manufacturing service providers to create and share value. However, credible data sharing in collaborative manufacturing supply chains is rare, which can lead to uncontrollable production distortions and delayed operational adjustments. Driven by blockchain technology, this study proposes a systematic framework for credible manufacturing data sharing for a cross-enterprise collaborative manufacturing supply chain (CMSC). To develop the needed method, a blockchain network system with blockchain nodes, distributed ledger, and Raft-based distributed node ordering service system was first modelled. Then, two automatic data upload algorithms were studied to ensure the reliability of off-chain manufacturing data sources from core enterprises, suppliers, and customers. Then, two types of smart contracts were designed to ensure the standardisation and co-validation of manufacturing data storage and query processes in the blockchain network. A demonstrative case was studied to validate the proposed blockchain-based credible manufacturing data sharing method. The results show that our work is effective for credible data sharing in CMSC, which makes it easier for core enterprises to better operate the CMSC and further stimulate enterprises to create a credible social community. [ABSTRACT FROM AUTHOR]

Cybersecurity presents non-negligible challenges for firm collaboration and supply chain viability, as information exchange among nodes introduces potential interdependent risks. How to make appropriate decisions on security investments and information exchange modes is a significant issue for supply chain members. Considering two information exchange modes: system interconnection and system independence, this study develops two game models to investigate the cybersecurity investments in a vertical supply chain composed of a retailer and n suppliers. Initial analysis shows that although firms learn investment decisions mutually in the face of a changing cybersecurity environment, suppliers always take a free ride on the efforts of retailer in two cases and the increased interdependent risks will damp nodes enthusiasm for security investments. Next, to compare the two cases, we introduce information exchange efficiency as the mediate parameter to link degree of system interconnection and proportion of information shared. We found that under the system independence mode, firms with high information-exchanging demand in the large-scale supply chain are more motivated to invest in cybersecurity. Furthermore, we extend our models to a centralised decision-making scenario. We find that security investment efficiency is greatly improved, and the free-riding behaviour of supplier is significantly reduced when systems are interconnected. [ABSTRACT FROM AUTHOR]

Interorganizational partnerships can spur innovation, but their value may be diminished by friction in knowledge flows between firms. We consider how a partner's organizational structure may influence the knowledge that is accessible via partnerships. We focus on how a partner's structure trades off localized autonomy for its managers, which facilitates timelier decision making, and unified control, which facilitates integration. By shaping this balance, centralization of decision rights within the partner organization shapes access to its knowledge. Centralized structures generate wide-ranging internal knowledge pathways that enable access to a broader array of a partner's knowledge. However, the reduced managerial autonomy afforded by centralization makes decision making more cumbersome, which constricts the rate of access to a partner's knowledge. We find evidence of this tradeoff in the context of corporate venture capital relationships between incumbents and startups in the pharmaceutical industry. An increase in the incumbent's diversity of knowledge or in the knowledge required by the startup enhances the value of a greater breadth of access, whereas the degree to which the startup can leverage social ties (affinity) or hierarchical fiat (authority) alleviates the costs of a reduced access rate. Each of these features makes an incumbent organization's centralization more valuable to the startup. By highlighting this tension related to centralization, our findings suggest that new firms striving to maximize their partnership benefits may need to carefully consider their partners' internal structures. [ABSTRACT FROM AUTHOR]

Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The historiography of the American effort in World War I describes an American unwillingness to learn from the Allies. However true that may be for the combat arms, it was untrue for the Army Medical Department (AMEDD). The AMEDD sought a wide range of information from the beginning of the war, and through multiple channels that expand substantially and systematically once the U.S. entered the war. The information was also disseminated through multiple channels and made significant impacts on medical care in the American Expeditionary Force (AEF) during the Great War. Historians should be more cautious about assuming that all parts of the AEF were resistant to foreign information. [ABSTRACT FROM AUTHOR]

The Internet's widespread adoption and recent technological developments have provided researchers with the opportunity to capture new data types (e.g., images, passively collected data), which offer several advantages over conventional survey data. Nevertheless, the limited participation rate in projects requiring to share such data may limit their benefits, and even their feasibility. To estimate the willingness to participate in such projects in advance, researchers frequently rely on surveys. However, the way researchers describe what data should be shared and how, and the phrasing of questions asked to participants to obtain their agreement may result in different estimates. This study presents the results of a conjoint experiment that estimates the hypothetical willingness of participants to engage in two research activities that require sharing geolocation data. Three different descriptions of the activities were presented to participants: a neutral one, one emphasizing the necessity to commit to participate, and one emphasizing safe handling of shared data. The three descriptions elicited different levels of willingness, with a maximum effect of 7.0 percentage points (statistically significant). Additionally, the importance given by participants to the attributes of the activities (e.g., project duration or incentives) differed depending on the description. Notably, the description that emphasized data safety produced lower levels of willingness compared to the neutral one. This suggests that researchers should avoid overly emphasizing safety assurances when requesting the sharing of sensitive data, beyond the necessary information required for obtaining informed consent from participants. [ABSTRACT FROM AUTHOR]

Knowledge sharing is considered an important promotor of new product development (NPD) performance. However, studies have shown that making experts share knowledge in new product development (NPD) projects is often a challenging task. Consequently, this topic has attracted substantial attention in academic research. However, although studies have produced valuable insights, more detailed accounts of the mechanisms shaping knowledge sharing processes in NPD projects are sparse. To add to the knowledge on this topic, this study conducts a series of interviews with NPD professionals at manufacturers of high-tech industrial products to identify 'factors influencing knowledge sharing' (FIKS). The identified FIKS are explained through the socio-physiological theory, the 'reasoned action approach' (RAA). This involves several contributions. First, the study provides a detailed explanation of the role of FIKS by describing how they affect the behaviour of knowledge providers and receivers in NPD processes. Second, by identifying 161 FIKS in NPD processes, organised under 18 categories, the study offers the so far most extensive account of FIKS in NPD processes. Third, the findings suggest a special characteristic of knowledge sharing in NPD contexts concerning the relatively high importance of knowledge receiver behaviour. [ABSTRACT FROM AUTHOR]

We study the observability of investors' information-acquisition activities in financial markets. Improving observability leads to two strategic effects on information acquisition: (1) the pricing effect, which arises from interactions between investors and the market maker and can encourage or discourage information acquisition, and (2) the competition effect, which concerns interactions among investors and always encourages information acquisition. We apply our theory to study voluntary and mandatory disclosures of corporate site visits. When the competition effect dominates, investors voluntarily disclose their visits. When the pricing effect dominates, mandatory disclosure is effective. Our analysis sheds novel light on Regulation Fair Disclosure. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online. [ABSTRACT FROM AUTHOR]

Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Leaders may be seen by their followers as miscalibrating the quantity of their communication—sharing too much or too little. We propose that leaders are more likely to be seen as under-communicating than over-communicating, even though under-communication is more heavily penalized. In Study 1a, we examine 2,717 qualitative comments from archived leadership assessments and find that leaders are nearly 10 times as likely to be criticized for under-communicating than for over-communicating. In Study 1b, we obtain further evidence of this bias using a representative sample of U.S. adults. In Study 2, we manipulate communication (mis)calibration, showing that leaders who under-communicate are viewed as less qualified for a leadership role because they are viewed as less empathic. In Study 3, we use separate measures of employee perceptions of their manager's communication as well as their preferences. When there is a lack of congruence between perceived and preferred communication, employees judge their leaders as lacking empathy and, in turn, leadership ability. [ABSTRACT FROM AUTHOR]

Recommender systems on online platforms are often accused of polarizing user attention and consumption. The authors examine this phenomenon using a quasi-experiment conducted by Zhihu, the largest online knowledge-sharing platform (or Q&A community) in China. Zhihu originally used a content-based filtering algorithm, which recommends content to users on the basis of the topics to which each user has subscribed. After more than a year, Zhihu moved to a social filtering algorithm, which recommends content with which users' social connections are already engaged. The authors find that this algorithm change increased the creation of social ties by approximately 15% but decreased question subscriptions by 20% and answer contributions by 23%. The authors show that users' increased social interests mainly involved following popular users, leading to a greater concentration of social interests on the platform. However, users' topical interests became less concentrated, as popular topics received significantly fewer subscribers than unpopular topics. The authors explain these findings by exploring the underlying mechanism. They show that compared with content-based filtering algorithms, social filtering algorithms are more likely to expose general users to content consumed by their followees, who are more interested in niche topics than general users are. [ABSTRACT FROM AUTHOR]

The digital capabilities driven by Internet of Things and affiliated techniques have enabled the prevailing service-oriented business models, among which servitization has been well recognised as one of the most competitive strategies for manufacturing companies. However, manufacturing companies usually show a lack of knowledge regarding the service offering associated to their manufactured products. Acquiring external knowledge from service providers is one effective way to tackle this problem, but due to the information asymmetry, the process of knowledge sharing between the two is often faced with a prisoner's dilemma game. Meanwhile, the company's game strategy will change with the evolution of the knowledge sharing network structure. We therefore consider the influence of group spatial structure on individual game strategy, marry a canonical evolutionary game model on the decision-making mechanism of individuals to the complex network theory on the interaction behaviour among individuals in the groups. By analysing the model, we reveal the influence of various factors under the dimensions of ability and benefit on the willingness of companies to share knowledge. We also demonstrate the divergence in the influence of various factors on different types of companies. [ABSTRACT FROM AUTHOR]

Whenever consumers interact with technological devices connected to the internet, they disclose information about themselves. The rapid diffusion of voice technology is shifting the way consumers interact with technological devices from typing or clicking to speaking. This article offers a comprehensive analysis of how this shift from manual to oral communication with technology affects information disclosure. The authors first consider verbal disclosure and provide a conceptual framework that explicates how voice technology can influence consumers' propensity to reveal information about themselves through semantic content disclosed voluntarily. They then consider nonverbal disclosure and provide an analysis of how voice technology enables the collection of information revealed unintentionally through vocal paralanguage and ambient sound. The article offers testable propositions and poses open research questions that can serve as impetus for future research. In addition, it provides insights to marketers regarding how to navigate voice technology as a source of consumer information and to policy makers regarding how to better protect consumer privacy in interactions with voice technology. [ABSTRACT FROM AUTHOR]

Sharing positive events with others is a phenomenon referred to as "capitalization." Extant theory on capitalization considers the process of disclosing positive events as socioemotional in nature. However, individuals capitalize in the context of workplace relationships that serve instrumental functions, pointing to the possibility that the process of capitalization may at times be instrumental as well. In this paper, we integrate theory on capitalization with the social-functionalist model of emotions to develop a model that explains how workplace interpersonal capitalization serves the instrumental function of spurring knowledge sharing. We identify pride as a linking mechanism between workplace interpersonal capitalization and knowledge sharing, and we argue that experiencing pride is contingent on employees disclosing positive events that they attribute to their own efforts. We also identify perceived coworker responsiveness as a boundary condition qualifying the association between pride and knowledge sharing. A source- and time-separated field study and an experience sampling field experiment with a daily intervention provide support for our hypothesized model. Overall, our work broadens the concept of capitalization and contributes to the social-functionalist model of emotions. [ABSTRACT FROM AUTHOR]

This study examines the impact of blockchain technology on platform supply chains from the perspectives of information transparency and transaction cost. We build a hybrid-format supply chain in which one supplier adopts an agency selling format and sells a product through the platform by paying a commission fee, while the other supplier adopts a reselling format. A game theory model is adopted to solve the key question: What is the best blockchain strategy for each supply chain member? Our research shows that blockchain technology can be a powerful weapon for platforms to adjust prices and control the market. As for the two suppliers in our supply chain, they will become better off with blockchain technology due to the elimination of information asymmetry and transaction costs. Moreover, the optimal strategies for platforms strongly depend on transaction cost, commission rate, and blockchain's operation cost. Furthermore, we also provide a side-payment contract to help different players achieve Pareto improvement, thus reaching a win-win-win outcome. Our findings not only provide guidance for the adoption of blockchains in the platform economy but also complement the gap in research on information sharing. [ABSTRACT FROM AUTHOR]

Introduction: The emergence of collective behavior often depends on the adequate interaction of individuals through self-organization and the exchange of local information. When facing external threats, communication among individuals requires both rapid and effective information exchange to characterize sudden events. In this paper, we introduce the mechanism of emotions into the modeling of dynamics to study collective avoidance behavior in response to threats. Methods: A scenario involving a hidden dynamic threat is constructed to test the avoidance and survival capabilities of the collective when faced with a lack of effective information. By employing the activation and spread of emotion in modeling, the collective may self-organized and adeptly mitigate risks and enhance their own benefits. Results: Through adjustments to the intensity of emotional activation, spread, and decay, rich behaviors emerge. Relying on the regulation of emotion, the collective exhibits different response strategies and action patterns when facing threats, in which the optimal performance from the macroscopic level is expectable. Discussion: By analyzing these phenomena, it can enhance our understanding of the emotional states of collective in response to threats and the methods of controlling in intelligent collective motion. [ABSTRACT FROM AUTHOR]

Background: In Norway, as in other countries, national eHealth systems, such as the Summary Care Record (SCR), have been implemented to improve the collaboration around patients by sharing patient information between health professionals across healthcare institutions and administrative levels. Although widely implemented across the health and care services in Norway, evaluations of the SCR indicate less use than expected. There is a need for analysis that lays out the visions and expectations of the SCR and contrasts these with detailed observations of use in everyday health professional work. This study adds to the eHealth research field by exploring this reality. Method: This paper has a qualitative design with an ethnographic approach, including participant observation, qualitative interviews, and a document review. Qualitative individual interviews with 22 health professionals and six weeks of participant observation were conducted, and eight documents were reviewed. The field notes and the interview-transcriptions were analyzed following a stepwise-deductive induction analysis. Results: The document review identified the expectations and visions of the SCR, including an underlying assumption of trust in shared patient information. However, this assumption is implicit and not recognized as a crucial element for success in the documents. In our observation and interview data, we found that health professionals do not necessarily trust information in the SCR. In fact, several procedures and routines to assess the trustworthiness of SCR information were identified that complicate and disturb the expected use. In our analysis, two main themes characterize the health professionals' handling of the SCR: adapting to workflow and dealing with uncertainty. Conclusion: Our study illustrates that unconditional trust in shared patient information is an implicit assumption in SCR policy documents, but in their everyday work health professionals do not necessarily unconditionally trust shared patient information. Rather, sharing patient information through technology, such as the SCR, requires of health professionals to critically assess the digital information. The information in the SCR, as all sources of information presented to health professionals, becomes an item for their constant trust-work. Our study is of value to policymakers, health information systems developers, and the field of practice both nationally and internationally. [ABSTRACT FROM AUTHOR]

Research on knowledge hiding has largely focused on its antecedents while overlooking its consequences. Drawing on moral cleansing theory, we adopt a "perpetrator-centric view" and posit that employees who engage in playing dumb and evasive hiding–two specific knowledge hiding behaviors that involve deception–will subsequently perform more organizational citizenship behavior directed toward individuals (OCB-I) because they perceive a loss of moral credits following their moral transgression. Further, we propose that the indirect effects are contingent on perpetrators' moral identity internalization. We tested our hypotheses using a time-lagged research design with a sample of 362 respondents from a large pharmaceutical group company. Consistent with our hypotheses, we found that employees who engaged in playing dumb and evasive hiding subsequently exhibited more OCB-I as they perceived a loss of moral credits, whereas employees who engaged in rationalized hiding did not. In addition, the positive relationships between playing dumb and evasive hiding with perceived loss of moral credits were stronger when perpetrators had high moral identity internalization, as were the indirect effects of playing dumb and evasive hiding on OCB-I via perceived loss of moral credits. Our research contributes to the understanding of when and how engaging in knowledge hiding affects perpetrators and their compensatory behaviors toward coworkers. [ABSTRACT FROM AUTHOR]

PURPOSE: In Canada, health data are siloed, slowing bioinnovation and evidence generation for personalized cancer care. Secured data-sharing platforms (SDSPs) can enable data analysis across silos through rapid concatenation across trial and real-world settings and timely researcher access. To motivate patient participation and trust in research, it is critical to ensure that SDSP design and oversight align with patients' values and address their concerns. We sought to qualitatively characterize patient preferences for the design of a pan-Canadian SDSP. METHODS: Between January 2022 and July 2023, we conducted pan-Canadian virtual focus groups with individuals who had a personal history of cancer. Following each focus group, participants were invited to provide feedback on early-phase analysis results via a member-checking survey. Three trained qualitative researchers analyzed data using thematic analysis. RESULTS: Twenty-eight individuals participated across five focus groups. Four focus groups were conducted in English and one in French. Thematic analysis generated two major and five minor themes. Analytic themes spanned personal and population implications of data sharing and willingness to manage perceived risks. Participants were supportive of increasing access to health data for precision oncology research, while voicing concerns about unintended data use, reidentification, and inequitable access to costly therapeutics. To mitigate perceived risks, participants highlighted the value of data access oversight and governance and informational transparency. CONCLUSION: Strategies for secured data sharing should anticipate and mitigate the risks that patients perceive. Participants supported enhancing timely research capability while ensuring safeguards to protect patient autonomy and privacy. Our study informs the development of data-governance and data-sharing frameworks that integrate real-world and trial data, informed by evidence from direct patient input. @CLEONetwork researchers identify patient priorities for enhanced precision oncology data sharing initiatives [ABSTRACT FROM AUTHOR]

Data quality issues can significantly hinder research reproducibility, data sharing, and reuse. At the forefront of addressing data quality issues are research data repositories (RDRs). This study conducted a systematic analysis of data quality assurance (DQA) practices in RDRs, guided by activity theory and data quality literature, resulting in conceptualizing a data quality assurance model (DQAM) for RDRs. DQAM outlines a DQA process comprising evaluation, intervention, and communication activities and categorizes 17 quality dimensions into intrinsic and product‐level data quality. It also details specific improvement actions for data products and identifies the essential roles, skills, standards, and tools for DQA in RDRs. By comparing DQAM with existing DQA models, the study highlights its potential to improve these models by adding a specific DQA activity structure. The theoretical implication of the study is a systematic conceptualization of DQA work in RDRs that is grounded in a comprehensive analysis of the literature and offers a refined conceptualization of DQA integration into broader frameworks of RDR evaluation. In practice, DQAM can inform the design and development of DQA workflows and tools. As a future research direction, the study suggests applying and evaluating DQAM across various domains to validate and refine this model further. [ABSTRACT FROM AUTHOR]

Biodiversity research is essential for addressing the global biodiversity crisis, necessitating diverse participation and perspectives of researchers from a wide range of backgrounds. However, conservation faces a significant inclusivity problem because local expertise from biodiversity‐rich but economically disadvantaged regions is often underrepresented. This underrepresentation is driven by linguistic bias, undervalued contributions, parachute science practices, and capacity constraints. Although fragmented solutions exist, a unified multistakeholder approach is needed to address the interconnected and systemic conservation issues. We devised a holistic framework of collective responsibility across all research participants and tailored strategies that embrace diversity and dismantle systemic barriers to equitable collaboration. This framework delineates the diverse actors and practices required for promoting inclusivity in biodiversity research, assigning clear responsibilities to researchers, publishers, institutions, and funding bodies. Strategies for researchers include cultivating self‐awareness, expanding literature searches, fostering partnerships with local experts, and promoting knowledge exchange. For institutions, we recommend establishing specialized liaison roles, implementing equitable policies, allocating resources for diversity initiatives, and enhancing support for international researchers. Publishers can facilitate multilingual dissemination, remove financial barriers, establish inclusivity standards, and ensure equitable representation in peer review. Funders must remove systemic barriers, strengthen research networks, and prioritize equitable resource allocation. Implementing these stakeholder‐specific strategies can help dismantle deep‐rooted biases and structural inequities in biodiversity research, catalyzing a shift toward a more inclusive and representative model that amplifies diverse perspectives and maximizes collective knowledge for effective global conservation. [ABSTRACT FROM AUTHOR]

In response to the replication crisis in psychology, the scientific community has advocated open science practices to promote transparency and reproducibility. Although existing reviews indicate inconsistent and generally low adoption of open science in psychology, a current-day, detailed analysis is lacking. Recognising the significant impact of false memory research in legal contexts, we conducted a preregistered systematic review to assess the integration of open science practices within this field, analysing 388 publications from 2015 to 2023 (including 15 replications and 3 meta-analyses). Our findings indicated a significant yet varied adoption of open science practices. Most studies (86.86%) adhered to at least one measure, with publication accessibility being the most consistently adopted practice at 73.97%. While data sharing demonstrated the most substantial growth, reaching about 75% by 2023, preregistration and analysis script sharing lagged, with 20–25% adoption in 2023. This review highlights a promising trend towards enhanced research quality, transparency, and reproducibility in false memory research. However, the inconsistent implementation of open science practices may still challenge the verification, replication, and interpretation of research findings. Our study underscores the need for a comprehensive adoption of open science to improve research reliability and validity substantially, fostering trust and credibility in psychology. [ABSTRACT FROM AUTHOR]

Green technology innovation is a critical factor in ensuring the long-term stable development of renewable energy enterprises. Based on the super network theory, this paper constructs a network model of green technology innovation influencing factors of renewable energy enterprises, which includes the knowledge sub-network of green technology innovation of renewable energy enterprises, the research and development member sub-network of green technology innovation team of renewable energy enterprises and the policy sub-network of green technology innovation of renewable energy enterprises. It explores the mechanism of its influence on innovation in the preparation stage. Simulation analysis by Netlogo software concludes that innovation knowledge sharing, R&D membership, and innovation policy all have a significant positive impact on green technology innovation in renewable energy companies. [ABSTRACT FROM AUTHOR]

This article explores the dynamic interplay between human and non-human entities, focusing on how embodied data representation is distributed. It examines how predictive coding, which utilizes preconceived knowledge, interacts with tangible experiences to shape our understanding of the world. Emphasizing this, I propose the concept of co-Ability as a deep underlying explanatory framework for understanding adaptive behaviors within a networked world. A nonverbal dialog between humans and a data-saturated environment is analyzed through an action-oriented perspective and the predictive coding framework in cognition, utilizing digital craft and rapid prototyping. This transformative approach augments human interaction with digital landscapes through tangible prototypes, bridging physical experience with abstract information, and identifying potential ways to conceptualize data materially. The article discusses the various aspects of connectivity among network agents and the evolving nature of these connections as they adapt to real-world conditions and dynamic shifts in data, highlighting that information exchange in an interconnected network is more than bilateral; it generates ripple effects that extend beyond immediate connections. These reciprocal exchanges simultaneously alter both the digital and analog domains, with data constantly bifurcating into multiple pathways and outcomes. A significant challenge addressed in this article is the question of how to frame information materially, inviting further exploration. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has posed formidable challenges to economic mobility and corporate expansion. Among these challenges is its pronounced effect on knowledge innovation, a cornerstone upon which many organizations depend. To re-establish the flow of internal knowledge, organizations are compelled to refine their knowledge management strategies and amplify employees' motivation and eagerness to share and transfer information. This study delves into the influence of knowledge management processes on employees' knowledge-sharing and transfer behaviors, viewed through the lens of the social exchange theory. It also probes the role of social capital in fostering and augmenting employees' involvement in refining these processes. Data was gleaned from 30 information service firms in mainland China, resulting in 483 valid responses. Our findings highlight that both relational and structural forms of social capital positively influence the knowledge management processes, subsequently enhancing employees' knowledge-sharing and transfer behaviors. [ABSTRACT FROM AUTHOR]

The modern medical system is convergence of cutting-edge technologies and advancements in the healthcare environment. In the modern medical system, the storage of electronic health records is generally leased out to third-party cloud service providers (CSPs). But, CSPs cannot be entirely relied upon due to the potential security and privacy issues. This article presents Multi-Authority and Hierarchical Attribute-Based Encryption Scheme (MH-ABE) scheme to promote secure information sharing and protect patient's privacy. The utilization of CP-ABE in conjunction with multiple Attribute Authorities within the proposed MH-ABE scheme presents a scalable and fine-grained approach to data access control. The proposed MH-ABE scheme incorporates the utilization of a Hierarchical Access Tree to effectively encrypt numerous files concurrently, hence reducing the computational and storage cost. The proposed scheme has also been evaluated using a comparative analysis with existing schemes, emphasizing the assessment of computational and storage costs. The findings of this analysis demonstrate improved performance and efficiency of the proposed ciphertext policy based encryption scheme. The proposed MH-ABE scheme incorporates features such as policy hiding and revocation, and it exhibits resilience against attacks, including collusion resistance, Indistinguishability under chosen-plaintext attack and forward secrecy. [ABSTRACT FROM AUTHOR]

Existing attribute-based proxy re-encryption schemes suffer from issues like complex access policies, large ciphertext storage space consumption, and an excessive authority of the authorization center, leading to weak security and controllability of data sharing in cloud storage. This study proposes a Weighted Attribute Authority Multi-Authority Proxy Re-Encryption (WAMA-PRE) scheme that introduces attribute weights to elevate the expression of access policies from binary to multi-valued, simplifying policies and reducing ciphertext storage space. Simultaneously, the multiple attribute authorities and the authorization center construct a joint key, reducing reliance on a single authorization center. The proposed distributed attribute authority network enhances the anti-attack capability of cloud storage. Experimental results show that introducing attribute weights can reduce ciphertext storage space by 50%, proxy re-encryption saves 63% time compared to repeated encryption, and the joint key construction time is only 1% of the benchmark scheme. Security analysis proves that WAMA-PRE achieves CPA security under the decisional q-parallel BDHE assumption in the random oracle model. This study provides an effective solution for secure data sharing in cloud storage. [ABSTRACT FROM AUTHOR]

Hierarchical clustering is a widely used data analysis technique. Typically, tools for this method operate on data in its original, readable form, raising privacy concerns when a clustering task involving sensitive data that must remain confidential is outsourced to an external server. To address this issue, we developed a method that integrates Cheon-Kim-Kim-Song homomorphic encryption (HE), allowing the clustering process to be performed without revealing the raw data. In hierarchical clustering, the two nearest clusters are repeatedly merged until the desired number of clusters is reached. The proximity of clusters is evaluated using various metrics. In this study, we considered two well-known metrics: single linkage and complete linkage. Applying HE to these methods involves sorting encrypted distances, which is a resource-intensive operation. Therefore, we propose a cooperative approach in which the data owner aids the sorting process and shares a list of data positions with a computation server. Using this list, the server can determine the clustering of the data points. The proposed approach ensures secure hierarchical clustering using single and complete linkage methods without exposing the original data. [ABSTRACT FROM AUTHOR]

Finger vein recognition methods, as emerging biometric technologies, have attracted increasing attention in identity verification due to their high accuracy and live detection capabilities. However, as privacy protection awareness increases, traditional centralized finger vein recognition algorithms face privacy and security issues. Federated learning, a distributed training method that protects data privacy without sharing data across endpoints, is gradually being promoted and applied. Nevertheless, its performance is severely limited by heterogeneity among datasets. To address these issues, this paper proposes a dual-decoupling personalized federated learning framework for finger vein recognition (DDP-FedFV). The DDP-FedFV method combines generalization and personalization. In the first stage, the DDP-FedFV method implements a dual-decoupling mechanism involving model and feature decoupling to optimize feature representations and enhance the generalizability of the global model. In the second stage, the DDP-FedFV method implements a personalized weight aggregation method, federated personalization weight ratio reduction (FedPWRR), to optimize the parameter aggregation process based on data distribution information, thereby enhancing the personalization of the client models. To evaluate the performance of the DDP-FedFV method, theoretical analyses and experiments were conducted based on six public finger vein datasets. The experimental results indicate that the proposed algorithm outperforms centralized training models without increasing communication costs or privacy leakage risks. [ABSTRACT FROM AUTHOR]

Reconstruction‐based methods are commonly used in industrial visual anomaly detection. They rely on a well‐reconstructed normal mode of the model. However, it is difficult to manage the boundary of generalization. The strength of the model's generalization capability can directly affect the fidelity of the reconstruction, resulting in the occurrence of false positives. To address the above challenges, a novel dual branch reconstruction anomaly detection approach is proposed to control the model generalization capability at two dimensions. It reconstructs abnormal images into normal ones by resolution recovery and denoising branches. Detection results are generated from their comparison. In addition, an innovative channel adjustment module is introduced to improve information exchange between branches. It uses multiple dilated convolutions for interactions over different scales. Simulation experiments demonstrate that the method outperforms most inspection methods on the MVTec AD and MVTec 3D‐AD datasets. It also shows good results on the self‐generated automotive paint scratches dataset of this study. [ABSTRACT FROM AUTHOR]

In multi‐agent systems (MASs), not only do agents engage in cooperative relationships, but they also compete with one another. The topic of collaborative group in MASs has garnered significant attention. Due to the possibility of explicit interaction among agents, the complete sharing of known information among nodes presents a risk of privacy leakage. Therefore, this article explores the problem of asymmetric bipartite consensus control for MASs with strong‐privacy‐preserving. A novel state decomposition privacy‐preserving algorithm is proposed to achieve asymmetric bipartite consensus of MASs. This algorithm can ensure that the initial and final states of each agent will not be compromised, via a preservation coefficient designed in proposed algorithm. By employing algebraic graph theory and automatic control theory, a thorough analysis of the algorithmic performance is conducted. It is demonstrated that our algorithm can preserve the privacy of all agents in MASs while achieving asymmetric bipartite consensus, i.e. the consensus values are different in sign and modulus. Finally, the effectiveness of the main results is validated through simulation examples. [ABSTRACT FROM AUTHOR]

Competition in today’s corporate environment pressures organizations to develop creative employee behaviors to generate organizational success. This research aims to assess the reasons for innovative employee work behaviors (IWB) such as training, knowledge sharing, and knowledge hiding in the Kurdistan region of Iraq. Data were collected from 240 employees from various service organizations in the Suleymaniyah and analyzed using structural equation modeling (SEM). The results show that training improved both knowledge sharing and IWB. Furthermore, knowledge sharing significantly mediated the link between training and IWB. Nevertheless, knowledge hiding did not have any significant impact on employee IWB. These findings emphasize the importance of training and KS in improving IWB in businesses. [ABSTRACT FROM AUTHOR]

Graph convolutional networks (GCNs) have achieved remarkable performance in the 2D-to-3D human pose estimation (HPE) task. The adjacency matrix in GCNs is crucial for feature aggregation in 3D HPE. However, existing GCN-based methods excessively rely on the fixed adjacency matrix to aggregate joint features from one-hop neighbor at a single scale, which limits the feature representation of skeleton data. To better improve the performance of 3D HPE, we have designed a multi-scale parallel adaptive graph network (MPA-GNet) for 3D HPE. The proposed network consists of three parallel multi-scale subgraph networks (PMS-Net) to efficiently capture human joint features at different scales. Specially, a multi-scale feature fusion module is devised to process multi-scale graph structural features and exchange information to generate rich hierarchical representations for skeleton data. To flexible construct graph topology in different scales, a special designed adaptive attention adjacency graph convolution network and a cluster graph pooling module are designed to construct the MPA-GNet in a parallel manner and capture the local subgraphs information in each PMS-Net. Finally, we conduct experiments on two 3D human pose challenging benchmark datasets Human3.6M and HumanEva-I for evaluating the effectiveness of the proposed model. The experimental results demonstrate that our model achieves competitive performance compared with some state-of-the-art 3D HPE methods. [ABSTRACT FROM AUTHOR]

Aim: Previous research has shown patients and the public in Australia generally support medical researchers in making de‐identified research data available to other scientists. However, this research has focussed on certain types of data and recipients. We surveyed Australians affected by cancer to characterize their attitudes toward the sharing of research data with multiple third parties, including the public. Methods: A short, anonymous online survey of Australians with a previous diagnosis of cancer was advertised between October 27, 2022, and February 27, 2023. Quantitative responses were analyzed with descriptive statistics. Free‐text responses were coded deductively and summarised using content analysis. Results: In total, 551 respondents contributed data to the survey. There was strong support for cancer researchers sharing non‐human and de‐identified human research data with clinicians (90% and 95%, respectively) and non‐profit researchers (both 94%). However, fewer participants supported sharing data with for‐profit researchers (both 64%) or publicly (both 61%). When asked if they would hypothetically consent to researchers at their treatment location using and sharing their de‐identified data publicly, only half agreed. In contrast, after being shown a visual representation of the de‐identified survey data, 80% of respondents supported sharing it publicly. Conclusion: Australians affected by cancer support the sharing of research data, particularly with clinicians and non‐profit researchers. Our results also imply that visualization of the data to be shared may enhance support for making it publicly available. These results should help alleviate any concerns about research participants' attitudes toward data sharing, as well as boost researchers' motivation for sharing. [ABSTRACT FROM AUTHOR]