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A new research domain known as the Quantified Self has recently emerged and is described as gaining self-knowledge through using wearable technology to acquire information on self-monitoring activities and physical health related problems. However, very little is known about the impact of time window models on discovering self-quantified patterns that can yield new self-knowledge insights. This paper aims to discover the self-quantified patterns using multi-time window models.

This paper proposes a multi-time window analytical workflow developed to support the streaming k-means clustering algorithm, based on an online/offline approach that combines both sliding and damped time window models. An intervention experiment with 15 participants is used to gather Fitbit data logs and implement the proposed analytical workflow.

The clustering results reveal the impact of a time window model has on exploring the evolution of micro-clusters and the labelling of macro-clusters to accurately explain regular and irregular individual physical behaviour.

The preliminary results demonstrate the impact they have on finding meaningful patterns.

This study aims to investigate the role of green strategic alliances (GSAs) in fostering a green shared vision (GSVis) and green shared value (GSV) and their impact on green organizational identity (GOI) and sustainability.

The authors employed structural equation modeling to analyze data collected through a 60-item questionnaire administered in Portugal and China, allowing the authors to test their theoretical model.

The findings of the authors' study indicate that green strategic alliances have a positive influence on the development of a GSVis and GSV in both countries. This, in turn, contributes to improved sustainability and the establishment of a GOI. Furthermore, the authors' results demonstrate that these alliances enhance GSV, resulting in enhanced sustainability performance and a stronger green identity, with a notable increase in awareness of environmental and social practices.

This article is innovative as it applies organizational learning and value creation theories to gain a deeper understanding of how alliances can shape the green identity of companies and contribute to their overall sustainability.

This study investigates the impacts of the Russia–Ukraine conflict on the cross-correlation between agricultural commodity prices and crude oil prices.

The authors used MultiFractal Detrended Fluctuation Cross-Correlation Analysis (MF-X-DFA) to explore the correlation behavior before and during conflict. The authors analyzed the price connections between future prices for crude oil and agricultural commodities. Data consists of daily futures price returns for agricultural commodities (Corn, Soybean and Wheat) and Crude Oil (Brent) traded on the Chicago Mercantile Exchange from Aug 3, 2020, to July 29, 2022.

The results suggest that cross-correlation behavior changed after the conflict. The multifractal behavior was observed in the cross correlations. The Russia–Ukraine conflict caused an increase in the series' fractal strength. The study findings showed that the correlations involving the wheat market were higher and anti-persistent behavior was observed.

The study was limited by the number of observations after the Russia–Ukraine conflict.

This study contributes to the literature that investigates the impact of the Russia–Ukraine conflict on the financial market. As this is a recent event, as far as we know, we did not find another study that investigated cross-correlation in agricultural commodities using multifractal analysis.

This article explores how the social media usage affect team creative performance via transactive memory system, knowledge interaction and expertise coordination.

The study is based on the perspective of transaction memory system and expertise coordination theory. A research model was constructed and tested, involving 289 individuals from 67 distributed agile software development teams.

The results indicate that social media usage is positively correlated with transactive memory system, and social media usage and transactive memory system have positive relations to knowledge interaction and expertise coordination. Moreover, this analysis shows that knowledge interaction has a positive relationship with expertise coordination, and expertise coordination positively affects team creative performance. However, knowledge interaction has no direct relationship on team creative performance, and its indirect impact on team creative performance was fully mediated by expertise coordination. This research shows that social media usage by distributed agile software development teams can support the development of transactive memory system and promote expertise coordination. In addition, knowledge interaction alone is not enough, and expertise coordination must be achieved to increase team creative performance.

First, this paper explores the mechanism of transactive memory system in distributed Agile Software Development teams from the perspective of social media, which is different from the previous information processing theory framework that confined transactive memory system to the cognitive aspects of knowledge coding, storage and retrieval. Second, this research focuses on the knowledge interaction and expertise coordination formed by team members in the process of communication in the context of social media usage, which confirms the crucial roles of social media usage and transactive memory system in team knowledge management and team creative performance. Then, this research also shows that the development of transactive memory system in the team is indeed an important factor to promote knowledge interaction and professional expertise coordination.

This paper aims to examine why retail firms seldom achieve full integration of online and offline channels as prescribed in omni-channel literature. It examines the intermediate process of channel integration from an internal, operational perspective.

This study is composed of two parts. In the first part, the authors interviewed informants from nine firms that were engaged in channel integration. In the second part, the authors conducted case studies with three firms from the cosmetics and skincare industry against the backdrop of the COVID-19 pandemic to find evidence to support or negate the propositions made in the first part.

The first part identified six operational challenges to channel integration. The authors categorized these challenges into two groups: inter-channel communication and inter-channel competition. Inter-channel competition carries more weight at the latter stage of integration. The authors also identified two antecedents that affect the seriousness of these challenges: heterogeneity among channels in business operation and external competitive pressure. In the second part, the authors found that both inter-channel communication and inter-channel competition were improved because of the external competitive pressure exerted by the COVID-19 pandemic. However, the heterogeneity of offline channels against online channels in business operation is a double-edged sword.

The study identifies the changing effects of the challenges of channel integration and their antecedents in the midst of integration. The positive influence of a specific dimension of channel heterogeneity against other channels increases and then decreases along channel integration. The identification of the changing effects lays the foundation for a finer stage model of channel integration.

This research paper aims to explore the added value of knowledge management (KM) and its antecedents for innovation and organizational performance (OP) in marginal healthcare organizations.

Using insights from the resource-based view and knowledge-based theory of the firm, the model explains the effects of technology capabilities (TC) and organizational culture (OC) on the KM process, process innovation (PIN), administrative innovation (AIN) and OP. The authors used partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to analyze data collected from 168 healthcare practitioners in Cameroon using a survey.

The authors reveal that TC and OC positively impact some KM components. Knowledge sharing (KS), knowledge acquisition (KA) and responsiveness to knowledge (RK) influence PIN, while only PIN and KA influence OP. FsQCA provided several configurations that lead to high OP within healthcare centers. As a result, the results are adaptable to any healthcare center that wishes to set up one or more KM processes.

Given that the results will help the health workforce make concerted decisions about medical care, the authors contribute significantly to the definition and optimization of KM in healthcare by implementing various processes and policies to ensure the continued existence of high-quality and outstanding healthcare systems. The KM propositions will enable healthcare centers to: (1) improve the quality of patient care through collegiality in medical practice; (2) optimize processes in the patient care chain; and (3) leverage knowledge gained though knowledge sharing among the medical team. The propositions open up avenues for future research in addition to providing practical implications for healthcare center practitioners.

This study sheds new empirical light on the relationships between KM antecedents and processes, innovation and OP in healthcare centers. This research is one of the few to examine the relationship between TC, OC, KM processes, innovation and OP in developing countries. This paper aims to fill this gap and inform future research concerning KM in the healthcare sector. Further, this study goes beyond testing the PLS-SEM approach's hypotheses by applying fsQCA to provide practical and comprehensive knowledge on how to increase the efficiency of a healthcare center through KM.

This paper aims to understand Chinese tourists’ changing shopping experience in Macao. In scrutinizing reviews posted in the pre-COVID and during COVID eras, the study has identified changing patterns in Chinese tourists’ shopping experiences, including increased leisure components while shopping, decreased luxury pursuits and an improved overall leisure and shopping experience because of decreased prices in accommodation and a less crowded retail and leisure environment. An emergent opportunity to provide “retail-tainment” experience is discussed.

In recent years, environmental issues and resource depletion have posed significant challenges to firms and society. To address these environmental challenges, firms seek to build strategic alliances of green supply chain management (GSCM) with their supply chain partner. As the largest developing country in the Asia–Pacific region, China needs to take more responsibility for environmental protection, which requires more Chinese firms to participate in GSCM. Therefore, focusing on the issue of GSCM and innovation persistence in the context of an increasingly harsh ecological environment is essential.

To test the hypothesis, the authors perform an empirical analysis on a sample of 124 listed firms in China from 2014 to 2019. The results are robust to a battery of robustness analyses the authors performed to take care of endogeneity.

Empirical results indicate that GSCM can promote innovation persistence and both market environment turbulence and technology environment turbulence have a positive moderating effect on the relationship between the two. Mechanism tests show that GSCM can improve innovation efficiency, ensure innovation quality and alleviate financing constraints, thus promoting the innovation persistence of firms.

This study can provide a theoretical basis for the country to promote GSCM orientation, raise firms' awareness of the value of GSCM, convey the significance of GSCM to investors, influence firms' investment decisions and give experience to other developing countries.

Despite being an authentic carrier of various cultural practices, the human body is often underutilised to access the knowledge of human body. Digital inventions today have created new avenues to open up cultural data resources, yet mainly as apparatuses for well-annotated and object-based collections. Hence, there is a pressing need for empowering the representation of intangible expressions, particularly embodied knowledge within its cultural context. To address this issue, the authors propose to inspect the potential of machine learning methods to enhance archival knowledge interaction with intangible cultural heritage (ICH) materials.

This research adopts a novel approach by combining movement computing with knowledge-specific modelling to support retrieving through embodied cues, which is applied to a multimodal archive documenting the cultural heritage (CH) of Southern Chinese martial arts.

Through experimenting with a retrieval engine implemented using the Hong Kong Martial Arts Living Archive (HKMALA) datasets, this work validated the effectiveness of the developed approach in multimodal content retrieval and highlighted the potential for the multimodal's application in facilitating archival exploration and knowledge discoverability.

This work takes a knowledge-specific approach to invent an intelligent encoding approach through a deep-learning workflow. This article underlines that the convergence of algorithmic reckoning and content-centred design holds promise for transforming the paradigm of archival interaction, thereby augmenting knowledge transmission via more accessible CH materials.

The purpose of this study is to investigate the effect of transformational leadership (TL) of school leaders on tacit and explicit knowledge sharing (KS) of teachers via the mediating roles of knowledge self-efficacy. This study also attempts to bring a deeper insight on the correlation between TL and KS by exploring the moderating effect of knowledge-oriented school culture (KSC).

The paper used the quantitative approach and structural equation modeling to test the relationship among the latent factors in the proposed research model using data collected from 335 teachers in Vietnamese universities.

The findings revealed that TL might be an important precursor to create significant influences on tacit and explicit KS behaviors of teachers directly or indirectly through its positive effect on knowledge self-efficacy. In addition, the paper highlights the moderating role of KSC in strengthening the impact of TL on tacit and explicit KS behaviors of teachers.

This paper offers principals and managers in higher education a novel approach and valuable understanding of the effective pathways to foster KS behaviors of teachers.

This study is unique in its attempts to bridge research gaps in the literature and advance the insights of how school leadership fosters knowledge self-efficacy and KS willingness of teachers through practicing TL style and building a knowledge-oriented climate in higher education.