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This study aims to extend and explore patterns and trends of research in the linkage of big data and knowledge management (KM) by identifying growth in terms of numbers of papers and current and emerging themes and to propose areas of future research.

The study was conducted by systematically extracting, analysing and synthesizing the literature related to linkage between big data and KM published in top-tier journals in Web of Science (WOS) and Scopus databases by exploiting bibliometric techniques along with theory, context, characteristics, methodology (TCCM) analysis.

The study unfolds four major themes of linkage between big data and KM research, namely (1) conceptual understanding of big data as an enabler for KM, (2) big data–based models and frameworks for KM, (3) big data as a predictor variable in KM context and (4) big data applications and capabilities. It also highlights TCCM of big data and KM research through which it integrates a few previously reported themes and suggests some new themes.

This study extends advances in the previous reviews by adding a new time line, identifying new themes and helping in the understanding of complex and emerging field of linkage between big data and KM. The study outlines a holistic view of the research area and suggests future directions for flourishing in this research area.

This study highlights the role of big data in KM context resulting in enhancement of organizational performance and efficiency. A summary of existing literature and future avenues in this direction will help, guide and motivate managers to think beyond traditional data and incorporate big data into organizational knowledge infrastructure in order to get competitive advantage.

To the best of authors’ knowledge, the present study is the first study to go deeper into understanding of big data and KM research using bibliometric and TCCM analysis and thus adds a new theoretical perspective to existing literature.

Secure children’s homes (SCHs) restrict the liberty of young people considered to be a danger to themselves or others. However, not all young people referred to SCHs find a placement, and little is known about the outcomes of the young person after an SCH or alternative placement. The purpose of this paper is to understand which characteristics most likely predict allocation to an SCH placement, and to explore the outcomes of the young people in the year after referral.

A retrospective electronic cohort study was conducted using linked social care data sets in England. The study population was all young people from England referred to SCHs for welfare reasons between 1st October 2016 to 31st March 2018 (n = 527). Logistic regression tested for differences in characteristics of SCH placement allocation and outcomes in the year after referral.

In total, 60% of young people referred to an SCH were allocated a place. Factors predicting successful or unsuccessful SCH allocation were previous placement in an SCH (OR = 2.12, p = 0.01); being female (OR = 2.26, p = 0.001); older age (OR = 0.75, p = 0.001); and a history of challenging behaviour (OR = 0.34, p = 0.01). In the year after referral, there were little differences in outcomes between young people placed in a SCH versus alternative accommodation.

The study raised concerns about the capacity of current services to recognise and meet the needs of this complex and vulnerable group of young people and highlights the necessity to explore and evaluate alternatives to SCHs.

The COVID-19 pandemic severely impacted tourism, and the hotel and restaurant industry was the most affected sector, which faced issues related to business uncertainty and unemployment during the crisis. The analysis of recovery time and the influence factors is significant to support policymakers in developing an effective response and mitigating the risks associated with the tourism crisis. This study aims to investigate numerous factors affecting the recovery time of the hotel and restaurant sector after the COVID-19 crisis by using survival analysis.

This study uses the quarterly value added with the observation time from quarter 1 in 2020 to quarter 1 in 2023 to measure the recovery status. The recovery time refers to the number of quarters needed for the hotel and restaurant sector to get value added equal to or exceed the value added before the crisis. This study applies survival models, including lognormal regression, Weibull regression, and Cox regression, to investigate the effect of numerous factors on the hazard ratio of recovery time of hotels and restaurants after the COVID-19 crisis. This model accommodates all cases, including “recovered” and “not recovered yet” areas.

The empirical findings represented that the Cox regression model stratified by the area type fit the data well. The priority tourism areas had a longer recovery time than the non-priority areas, but they had a higher probability of recovery from a crisis of the same magnitude. The size of the regional gross domestic product, decentralization funds, multiplier effect, recovery time of transportation, and recovery time of the service sector had a significant impact on the probability of recovery.

This study contributes to the literature by examining the recovery time of the hotel and restaurant sector across Indonesian provinces after the COVID-19 crisis. Employing survival analysis, this study identifies the pivotal factors affecting the probability of recovery. Moreover, this study stands as a pioneer in investigating the multiplier effect of the regional tourism and its impact on the speed of recovery.

This research investigates the mechanism by which big data capability enables superior supply chain resilience (SCRe) by empirically examining the links among big data analytics (BDA), supply chain flexibility (SCF) and SCRe, with innovation-focused complementary assets (CA-I) as the moderator.

Extensive surveys were conducted to gather 308 responses from Malaysian manufacturing firms in order to explore this framework. The structural and measurement models were examined and evaluated by using partial least squares structural equation modelling.

The findings revealed that BDA is linked to flexibilities in a manufacturing firm’s value chain, which in turn is related to the firm’s SCRe. However, the association between BDA and SCRe is surprisingly non-significant. Additionally, CA-I was discovered to moderate the connections between all of the constructs, except for the relationship between BDA and SCRe. Such findings imply that with the aim of enhancing resilience, a company should concentrate on SCF; and that BDA capability is a prerequisite for increasing these flexibilities.

This research extrapolates the findings of previous studies regarding BDA’s influence on SCRe by investigating the indirect effect of SCF, as well as the moderating influence of CA-I. This research is one of the first few studies to empirically examine the relationships between BDA, SCF and SCRe across manufacturing firms, with CA-I acting as a moderator.

This study's main goal is to expand the theoretical perspective and discuss the unique influence of age and tenure on R&D teams' incremental innovation outcomes. We answer scholars call for additional research on age-related processes by testing pathways through which older employees can benefit organizational performance. The current study advances the literature by relating to the context-related process of cohesion and investigating its moderating influence on the relationship between team antecedents (i.e. age and tenure) and incremental innovation.

This research sample consists of 108 R&D teams operating in six mature high-tech organizations located in Israel. The participating entities design and manufacture state-of-the-art innovations in the semiconductors, communications and information technology sectors. The number of teams in each participating entity was 35, 21, 21, 19, 7 and 5, respectively. The sample consisted of 443 R&D employees and 212 team leaders/managers. The total sample comprised 655 participants. Team members filled out questionnaires to assess the independent variables. The dependent-variable questionnaire focusing on the team's incremental innovation accomplishments was completed by two managers for each team.

We found a negative association between team members' age and incremental innovation. Hypothesis 2, which predicted a positive association between team members' tenure and incremental innovation, was marginally supported. The interaction between team members' age and team members' tenure on incremental innovation was marginally supported. Hypothesis 4, which predicted that the negative association between team members' age and incremental innovation would be mitigated when the level of team cohesion is low, was supported. Hypothesis 5, which assumed that the positive association between team members' tenure and incremental innovation would be stronger when the level of cohesion is high, was supported.

This research's results regarding the negative influence of R&D employees' age on incremental innovation are crucial for managers and team leaders in the high-tech industry. Following the age stereotype, many of them avoid recruiting and assigning older employees to R&D teams dealing in innovation creation and development. They should expand their perspective and consider additional attributes in order to assign the employees that best match the team's mission. The results show that R&D teams produce high and similar levels of incremental innovation when the level of team members' tenure is high, regardless of their age.

This study benefited from a relatively high number of respondents and teams from leading high-tech organizations, a high response rate and a research design that made it possible to establish a linkage between data on the independent variables and data on incremental innovation collected from separate independent sources. The data on the dependent variable—incremental innovation—was based on independent assessments made by two managers for each team. The study's measurements were based on leading studies on innovation.

The study aims to investigate the influence of leader mindfulness on employee innovative work behaviour mediated by work engagement and moderated by employee learning orientation.

That data set of 337 was collected from full-time working professionals from IT industry in India through survey design. The proposed mediated moderation model was tested through Process Macro.

The findings highlighted the positive role of leader mindfulness in enhancing employee innovative work behaviour. Furthermore, the authors found that this relationship was partly mediated by work engagement and moderated by employee learning orientation. Results suggested that the relationship between work engagement and innovative work behaviour was stronger for employees who score high on learning orientation.

The main contribution of the study lies in delineating the interpersonal lens of mindfulness at workplace, particularly the leader–employee interface. It offers a more nuanced delineation of the process through which leader mindfulness encourages employee innovative work behaviour.

This study aims to analyze the development of digital market characteristics particularly focusing on how the strategic choices of platforms are not fully reflected in pricing. In addition, the implications for the development of theories of harm are investigated to explore the necessity of a relevant market definition in assessing infringement and evaluating the adequacy of Indonesian competition law.

This study is a legal analysis that uses statutory approaches, cases, comparative law and the development of theories of harm in digital mergers. The case approach is conducted by analyzing three cases decided by the Indonesia Business Competition Supervisory Commission. This approach provides insight into the response of Komisi Pengawas Persaingan Usaha concerning the merger and acquisition cases in the digital era as well as the provision of different analyses in conventional markets. However, competition can be potentially damaged in digital markets and a comparative law approach is taken by analyzing digital merger cases decided by authorities in other countries.

Results reveal that the digital market has created a “relevant market” that is challenging and blurred due to multi-sided network effects and consumer data usage characteristics. Platform-based enterprises’ prices fluctuate due to the digital market’s network effect and consumer data statistics. Smartphone prices depend on the number of apps and consumer data. Neoclassical theory focusing on product markets and location applied in Indonesia must be revised to establish a relevant digital economy market. To evaluate digital mergers, new harm theories are needed. The merger should also protect consumer data. Law Number 27 of 2022 on Personal Data Protection and Government Regulation on the Implementation of Electronic Systems and Transactions protects online consumers, a basic step in due diligence for digital mergers. The Indonesian Government should promptly strengthen the notion of “relevant markets” in the digital economy, which could lead to fair business competition violations like big data control. Notify partners or digital merger participants of the accessibility of sensitive data like transaction history and user location.

The development of digital market characteristics has implications for developing theories of harm in digital markets. Indonesian competition law needs to develop such theories of harm to analyze the potential for anticompetitive digital mergers in the digital economy era.

The main aim of this study is to explore the relationship between information system flexibility and dynamic capabilities to build sustainable and net zero supply chains under the influence of environmental dynamism.

We have formulated a self-administered survey, with 359 participants contributing responses. Prior to delving into foundational assumptions, such as homoscedasticity and normality, a nonresponse bias analysis was executed. The integrity of the data, in terms of reliability and construct validity, was gauged using confirmatory factor analysis. Subsequent regression outputs corroborated all the proposed assumptions, fortifying the extant scholarly literature.

The empirical findings of this research underscore a positive correlation between Information system flexibility, dynamic capabilities and a net zero supply chain, especially in the context of environmental dynamism. Data sourced from the cement manufacturing sector support these observations. We also found that environmental dynamism moderates the relationship between data analytics capability and sustainable supply chain flexibility but does not moderate the relationship between Resource flexibility and sustainable supply chain flexibility. Additionally, this research strengthens the foundational principles of the dynamic capability theory.

The conceptual framework elucidates the interplay between information system flexibility, dynamic capabilities, and sustainable supply chain flexibility, emphasizing their collective contribution towards achieving sustainable chain net zero, introducing environmental dynamics as a moderating variable that augments the scholarly discourse with a nuanced layer of analytical depth.

Develop a comprehensive framework for assessing the knowledge organization systems (KOSs), including the taxonomy of Wikipedia and the ontologies of Wikidata, with a specific focus on enhancing management and retrieval with a gender nonbinary perspective.

This study employs heuristic and inspection methods to assess Wikipedia’s KOS, ensuring compliance with international standards. It evaluates the efficiency of retrieving non-masculine gender-related articles using the Catalan Wikipedian category scheme, identifying limitations. Additionally, a novel assessment of Wikidata ontologies examines their structure and coverage of gender-related properties, comparing them to Wikipedia’s taxonomy for advantages and enhancements.

This study evaluates Wikipedia’s taxonomy and Wikidata’s ontologies, establishing evaluation criteria for gender-based categorization and exploring their structural effectiveness. The evaluation process suggests that Wikidata ontologies may offer a viable solution to address Wikipedia’s categorization challenges.

The assessment of Wikipedia categories (taxonomy) based on KOS standards leads to the conclusion that there is ample room for improvement, not only in matters concerning gender identity but also in the overall KOS to enhance search and retrieval for users. These findings bear relevance for the design of tools to support information retrieval on knowledge-rich websites, as they assist users in exploring topics and concepts.

This chapter provides an in-depth look at how digital supply chain management (DSCM) can revolutionize supply chains in the post-COVID world. The COVID-19 pandemic exposed the vulnerabilities of traditional supply chains, highlighting the need for resilience and adaptability. The chapter begins by examining these COVID-induced disruptions, setting the foundation for the discussion on DSCM. DSCM, leveraging advanced technologies and data insights, offers a solution to these challenges, promoting agility, transparency, and sustainability in supply chain operations. This represents a significant shift from traditional practices, equipping organizations to cope with the dynamic postpandemic environment. Key capabilities of DSCM, such as resilience, integration, agility, and risk management, are discussed, supported by real-world examples from leading companies. These examples showcase the successful implementation of DSCM and its benefits in navigating the complexities of modern supply chains. However, the adoption of DSCM is not without challenges, including cybersecurity risks and integration difficulties. The chapter suggests strategies to overcome these challenges, emphasizing the importance of technology, collaboration, sustainability, and data-driven decision-making. By embracing these strategies, organizations can effectively manage their supply chains in the evolving global market, leveraging DSCM to withstand future uncertainties.