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Intelligent prediction of node localization in wireless sensor networks (WSNs) is a major concern for researchers. The huge amount of data generated by modern sensor array systems required computationally efficient calibration techniques. This paper aims to improve localization accuracy by identifying obstacles in the optimization process and network scenarios.

The proposed method is used to incorporate distance estimation between nodes and packet transmission hop counts. This estimation is used in the proposed support vector machine (SVM) to find the network path using a time difference of arrival (TDoA)-based SVM. However, if the data set is noisy, SVM is prone to poor optimization, which leads to overlapping of target classes and the pathways through TDoA. The enhanced gray wolf optimization (EGWO) technique is introduced to eliminate overlapping target classes in the SVM.

The performance and efficacy of the model using existing TDoA methodologies are analyzed. The simulation results show that the proposed TDoA-EGWO achieves a higher rate of detection efficiency of 98% and control overhead of 97.8% and a better packet delivery ratio than other traditional methods.

The proposed method is successful in detecting the unknown position of the sensor node with a detection rate greater than that of other methods.

Developing technological capabilities to enhance innovation performance is essential for firms to respond to external changes and competition. Based on the effect of organizational structure on organizational capability development, this study assesses whether a specific R&D organizational structure design can be used to develop different technological capabilities.

Combining organizational theory and the resource-based view as an integrated view, we propose several contrasting hypotheses to show the effects of three general R&D organizational structure designs (centralized, decentralized, and hybrid) on developing exploitative and explorative capabilities. We propose R&D slack as a moderator. 82 Taiwanese listed manufacturing firms were selected. Data on the firms' annual reports and their patent applications to the Taiwan Patent Office from 2005 to 2017 were collected.

Firms’ adoption of centralized and decentralized R&D structures has a significant positive effect on developing exploitative capability and an opposite effect on developing explorative capability. A high or low R&D slack can moderate the impact of R&D organizational structure on non-routine capability development.

This study concludes that R&D organizational structure affects the development of different technological capabilities and that the effect of R&D organizational structure on the development of technological capabilities can be changed under the moderation of R&D slack, which means that the possibility of developing different technological capabilities under the same organizational structure will increase.

The top manager should consider the relationship between R&D structure design and technological capability development to manage the R&D routines to influence the generation of technological capabilities. Also, they must utilize the provision of R&D slack to modulate technological capability development.

This study reexamines the relationship between organizational structure and capability development. It shows that organizational structure can shape unique technological capabilities and that firms may be able to change structural elements through slack resources, enabling ambidexterity or dynamic capability development without organizational change.

Drawing on the stakeholder theory, this study aims to empirically analyse the impact of platform enterprises’ corporate social responsibility (CSR) announcements on corporate stock market value. This study also estimates the moderating effect of stakeholder orientation and responsibility categories of CSR announcements, the platform enterprise type and the degree of CSR disclosure.

The event study method is used to analyse the change in stock market value of 191 CSR announcements from 137 Chinese platform enterprises. In addition, a case analysis is presented for two platform enterprises with the best practices to validate and complement study findings.

CSR announcements improve platform enterprises’ stock market value. Specifically, CSR announcements responding to platform enterprises’ external stakeholders, and CSR announcements with economic responsibility, have obvious positive impacts on stock market value. Furthermore, the maker platform’s CSR announcement has a more positive impact on stock market value than the exchange platform.

To the best of the authors’ knowledge, this study is the first attempt to identify the link between platform enterprises’ CSR announcements and stock market performance by empirical evidence, and it contributes to new knowledge of operating and evaluating platform enterprises’ CSR.

Technology-mediated learning (TML) is gaining popularity among business organizations for upskilling their employees. However, high dropout rates have limited its effectiveness. Thus, we explore, if and how personalization of TML can improve its adoption and effectiveness in workplaces from the lens of the unified theory of acceptance and use of technology (UTAUT2) theory.

An exploratory sequential mixed-method design was used for this study. Study 1 included interviews (N = 27) of Learning and Development (L&D) leaders and employees (learners) of large global organizations, about their experiences with TML. Emergent themes led us to our research model, which integrates constructs of personalization, technology adoption and transfer of training (TT). In Study 2, a cross-sectional study was conducted. Data were collected from employees who have experienced TML (N = 406) and analyzed using PLS-SEM.

Findings suggested that personalization of TML positively influenced intent to use TML and transfer skills, thereby improving TML effectiveness and proving its relevance in workplaces. Precisely, personalized TML recommendations from managers impacted (1) behavioral intention (BI) and TT directly; (2) BI through performance expectancy (PE); (3) TT through social influence and BI individually; and (4) TT through PE and BI sequentially. Likewise, allowing employees the flexibility to choose TML based on their interests influenced (1) BI directly and via hedonic motivation (HM) and (2) TT via HM and BI individually and sequentially.

Using our model, L&D practitioners may design and personalize their TML ecosystems to foster adoption and transfer of training in workplaces.

Personalization of learning in workplaces has received scant attention; thereby, our study expands existing knowledge in this relatively nascent field of research.

This study aims to develop a model that explains the relationship between broad personality traits and specific aspects of smart technology acceptance among visitors to smart destinations. It incorporates privacy and safety risks as moderating factors within the Unified Theory of Acceptance and Use of Technology (UTAUT) model, thereby advancing research in this area.

The cross-sectional study collected data from 519 respondents using purposive sampling. The questionnaire was administered across two smart destinations to validate the study’s findings.

Performance expectancy, effort expectancy and facilitating conditions significantly influence behavioral intentions for smart technology use, emphasizing the importance of user-centric design. While social influence’s impact is modest compared to the practical benefits users gain from the technology. Privacy and safety concerns act as barriers, reducing the influence of these drivers and underscoring the need for their mitigation in technology adoption.

This study enhances smart destination theory and practice by emphasizing the critical role of privacy and data security in the deployment of smart technologies. By addressing both the benefits and challenges of these technologies, it offers valuable insights into improving visitors’ overall experience and satisfaction, contributing to more effective smart tourism strategies.

The originality of this research lies in integrating the UTAUT model with risk theory by incorporating perceived privacy and safety risks as moderating factors in the context of smart destinations. This approach deepens the understanding of smart technology acceptance and offers valuable insights into the complex dynamics of technology adoption in tourism environments.

本研究旨在构建一个模型, 阐释广泛人格特质与智慧技术在智慧目的地中接受程度的具体方面之间的关系, 同时将隐私和安全风险作为调节因素纳入UTAUT模型, 以推动相关研究的发展。

本研究采用横断面设计, 通过目的性抽样从两个智慧目的地的519名受访者中收集数据。问卷调查用于验证研究发现的有效性。

绩效期望、努力期望和促进条件显著影响智慧技术使用的行为意图, 强调以用户为中心的设计重要性。尽管社会影响的作用相对较小, 但用户从技术中获得的实际利益更为显著。隐私和安全担忧是技术采纳的障碍, 减弱了上述驱动因素的作用, 突显了在技术推广中缓解这些风险的必要性。

本研究的原创性体现在通过引入感知隐私和安全风险作为调节因素, 将UTAUT模型与风险理论结合, 应用于智慧目的地的背景中。此方法深化了对智慧技术采纳的理解, 并为旅游环境中技术采纳的复杂动态提供了宝贵见解。

本研究通过强调隐私和数据安全在智慧技术部署中的关键作用, 增强了智慧目的地理论和实践。通过解决这些技术的优势与挑战, 本研究为提升游客整体体验与满意度、制定更高效的智慧旅游策略提供了重要参考。

The purpose of this research is to investigate the importance and status of conditional accounting conservatism indicators and financial flexibility for the management of legal claims of the company during the outbreak of Corona.

The research method was implemented using statistical analysis in the SPSS environment. The participants of this research can be experts and specialists working in companies admitted to the stock exchange and expert professors in accounting fields; auditing; economy; financial engineering and financial management, categorized. The data related to the localization tool of research variables were collected by snowball sampling method in the summer of 2022.

One of the main results of the research is that based on the opinions and professional experience of experts and professionals working in companies admitted to the stock exchange and academic experts, within a range of seven, “The number of legal claims of the company with electronic businesses” under the title of the main indicator in the legal claims of the company in the outbreak of Corona from the importance dimension; “Exchange rate fluctuations in financial resilience” under the title of the main indicator in financial resilience in the Corona outbreak from the functional dimension; “The number of legal claims of the company with government institutions” under the title of the main indicator in the company’s legal claims in the Corona outbreak from the functional dimension; “The company’s conservatism score” under the title of the main indicator in the conditional conservatism of accounting in the Corona outbreak from the functional dimension; “oil price fluctuations in financial resilience” under the title of the main indicator in financial resilience in the Corona outbreak from the importance dimension; and “type of industry based on total assets” under the title of the main indicator in the conditional conservatism of accounting in the Corona outbreak was calculated from the importance dimension.

Although the previous literature has studied the direct correlation between accounting conservatism and financial flexibility, this work focuses on examining the direct association between accounting conservatism and financial flexibility in the post-Corona era and is carried out to resolve legal claims.

The purpose of this study is to map the intellectual structure of sustainable finance and accounting (SFA) literature by identifying the influential aspects, main research streams and future research directions in SFA.

The results are obtained using bibliometric citation analysis and content analysis to conduct a bibliometric review of the intersection of sustainable finance and sustainable accounting using a sample of 795 articles published between 1991 and November 2023.

The most influential factors in the SFA literature are identified, highlighting three primary areas of research: corporate social responsibility and environmental disclosure; financial and economic performance; and regulations and standards.

SFA has experienced rapid development in recent years. The results identify the current research domain, guide potential future research directions, serve as a reference for SFA and provide inspiration to policymakers.

SFA typically encompasses sustainable corporate business practices and investments. This study contributes to broader social impacts by promoting improved corporate practices and sustainability.

This study expands on previous research on SFA. The authors identify significant aspects of the SFA literature, such as the most studied nations, leading journals, authors and trending publications. In addition, the authors provide an overview of the three major streams of the SFA literature and propose various potential future research directions, inspiring both academic research and policymaking.

This research paper aims to provide a comprehensive overview of the determinants influencing organisations decisions to adopt crowdsourcing. By synthesising existing literature, it seeks to identify critical factors that act as enablers or inhibitors in the adoption process and propose a framework for understanding crowdsourcing adoption within organisational contexts.

This study employed a systematic literature review methodology to examine the determinants influencing organisations' decisions to adopt crowdsourcing. The review encompassed research articles from the Web of Science and Scopus databases, spanning 2006 to 2021. Additionally, morphological analysis was conducted to categorise the identified determinants into three distinct contexts: technological, organisational and environmental. This methodological approach facilitated a comprehensive exploration of the factors shaping crowdsourcing adoption within organisational settings, allowing for a nuanced understanding of the phenomenon across different dimensions.

The study identifies 12 determinants influencing crowdsourcing adoption, categorised into technological, organisational and environmental dimensions. These determinants include technological compatibility, organisational readiness, top management support, crowd readiness and availability of third-party platforms. While some determinants primarily act as enablers, others exhibit dual roles or serve as inhibitors depending on contextual factors.

The findings offer valuable insights for scholars, practitioners, and organisational leaders seeking to leverage crowdsourcing as a strategic tool for innovation and competitiveness. The assessment scale of drivers and barriers developed in this research offers a systematic approach for evaluating the factors influencing crowdsourcing adoption, providing a nuanced understanding of innovation adoption dynamics. Theoretical implications include advancements in morphological analysis methodology and a nuanced understanding of innovation adoption dynamics. Managerial implications highlight strategies for enhancing organisational readiness, leveraging leadership support and mitigating adoption risks. Overall, the study provides a foundation for future empirical research and practical guidance for organisations planning to adopt crowdsourcing initiatives.

This research contributes significantly to crowdsourcing by presenting an integrated and theoretically grounded framework. By consolidating adoption determinants from diverse contexts, this study clarifies the understanding of crowdsourcing adoption. The framework offers practical value to managers and decision-makers, equipping them with a structured approach to assess and navigate the challenges associated with effectively adopting crowdsourcing. As such, this study contributes to advancing crowdsourcing practices and supports more informed managerial decision-making in innovation and knowledge sourcing.

Blockchains used by e-commerce consortia are a novel form of governance that facilitates coordination and collaboration among the numerous organisations that comprise e-commerce supply chains. Despite the increasing prevalence of consortium blockchain networks for e-commerce, there is a limited understanding of the economic and social dynamics that influence the behaviour of blockchain consortium members. By utilising transaction cost theory and social exchange theory, this research investigates the interplay between blockchain transaction-specific investment (BTSI), trust, adaptive collaboration (ADC) and the overall performance of supply chains in consortium blockchains

A quantitative research approach was employed to collect data from a representative sample of blockchain organisations affiliated with e-commerce consortium blockchains worldwide. Following this, the data obtained from 361 participants were analysed using descriptive and inferential statistics.

The results of our study indicate that BTSI has a substantial impact on trust. Furthermore, trust plays a pivotal role in shaping ADC, and ADC, in turn, acts as a mediator in the relationship between trust and performance outcomes.

This study underlines these economic and social dynamics in the evolving context of consortium blockchain networks, offering insights into their significance within a technology-driven environment.

This study aims to explore the dynamic interplay between employee resilience (ER) and learning organisations, specifically examining the mediating influence of psychological empowerment (PE).

Drawing on responses from 208 participants working in the United Arab Emirates, we used regression analysis with bootstrapping to scrutinise the data.

The results unveil a positive correlation between ER and learning organisation. Furthermore, PE is found to mediate this relationship.

In practical terms, organisations are urged to prioritise the cultivation of ER and the establishment of an environment fostering PE. Such initiatives contribute to a culture of continuous learning within the organisation and equip it with the adaptability needed to navigate new challenges.

This research contributes to a deeper comprehension of the importance of ER highlighting its positive effect on both organisational learning and PE.