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Road traffic emissions are generally believed to contribute immensely to air pollution, but the effect of road traffic data sets on air quality (AQ) predictions has not been fully investigated. This paper aims to investigate the effects traffic data set have on the performance of machine learning (ML) predictive models in AQ prediction.

To achieve this, the authors have set up an experiment with the control data set having only the AQ data set and meteorological (Met) data set, while the experimental data set is made up of the AQ data set, Met data set and traffic data set. Several ML models (such as extra trees regressor, eXtreme gradient boosting regressor, random forest regressor, K-neighbors regressor and two others) were trained, tested and compared on these individual combinations of data sets to predict the volume of PM_2.5, PM₁₀, NO₂ and O₃ in the atmosphere at various times of the day.

The result obtained showed that various ML algorithms react differently to the traffic data set despite generally contributing to the performance improvement of all the ML algorithms considered in this study by at least 20% and an error reduction of at least 18.97%.

This research is limited in terms of the study area, and the result cannot be generalized outside of the UK as some of the inherent conditions may not be similar elsewhere. Additionally, only the ML algorithms commonly used in literature are considered in this research, therefore, leaving out a few other ML algorithms.

This study reinforces the belief that the traffic data set has a significant effect on improving the performance of air pollution ML prediction models. Hence, there is an indication that ML algorithms behave differently when trained with a form of traffic data set in the development of an AQ prediction model. This implies that developers and researchers in AQ prediction need to identify the ML algorithms that behave in their best interest before implementation.

The result of this study will enable researchers to focus more on algorithms of benefit when using traffic data sets in AQ prediction.

This paper undertakes a structured literature review to analyse the literature on performance management and measurement (PMM) in universities over the last four decades. Over that time, PMM has emerged as an influential force in universities that impacts their operations and redefines their identity.

A structured literature review approach was used to analyse a sample of articles on PMM research from a broad range of disciplines over four decades. This was undertaken to understand the impacts of PMM practices on universities, highlight changes over time and point to avenues for future research.

The analysis highlights the fact that research on PMM in universities has grown significantly over the 40 years studied. We provide an overview of published articles over four decades regarding content, themes, theories, methods and impacts. We provide an empirical basis for discussing past, present and future university PMM research. The future research avenues offer multiple provocations for scholars and policymakers, for instance, PMM implementation strategies and relationships with various government programs and external evaluation and the role of different actors, particularly academics, in shaping PMM systems.

Unlike a traditional literature review, the structured literature review method can develop insights into how the field has changed over time and highlight possible future research. The sample for this literature review differs from previous reviews in covering a broad range of disciplines, including accounting.

As knowledge management increasingly becomes critical for the success of professional service firms, this paper uses social exchange theory to investigate the interactive impact of transformational leadership and organizational innovation on online knowledge sharing by employees in professional service firms. This study aims to investigate the mediating roles of job autonomy and job engagement in this process.

Data were collected from a survey of 350 frontline employees in professional service providers, including banking, telecommunication and insurance. Structural equation modeling was used for data analysis.

The results show that transformational leadership positively affects job autonomy, which in turn has a positive impact on online knowledge sharing through job engagement. Thus, job autonomy and job engagement mediate the relationship between transformational leadership and online knowledge sharing. Finally, organizational innovation moderates the relationship between transformational leadership and job autonomy.

This paper extends the knowledge management literature by studying the impact of transformational leadership on the online knowledge-sharing behavior and exploring the focal roles of job autonomy and job engagement in online-sharing behavior in professional service firms. The findings also provide useful implications for practitioners to help them engage employees in the adoption of digital technologies to optimize outcomes.

The purpose of this paper was identification and empirical assessment of the differentiation of consumers' attitudes in Ukraine and Poland to Russian brands and other brands offered on the Russian market after Russia’s aggression against Ukraine on February 24, 2022.

The main research methods include a systematic literature review and the authors' own surveys conducted in November 2022. The research sample comprised 950 consumers – 67% of them were Poles, 30% – Ukrainians and 3% from other countries.

A respondents' country (Poland and Ukraine) does not impact attitudes to brands offered on the Russian market after Russia's invasion of Ukraine on February 24, 2022. Moreover, it does not affect and differentiate emotional engagement in the conflict and assistance to war victims. Cluster analysis resulted in identifying two groups on the basis of consumers' declared emotional reactions to the war. The first group was smaller (N = 353, 37.2%), referred to as “indifferent consumers”, and was characterized by a greater inclination to purchase brands offered in Russia. The other cluster, referred to as “sensitive consumers” (N = 597, 62.8%), comprises those engaged in offering assistance to war victims, showing strong emotions in connection with the aggression and military activities and characterized by a clearly negative attitude to Russian and other offered brands and an inclination to boycott these brands.

A short time horizon, the study confined to two countries, difficulties in reaching Ukrainian respondents due to power failures in Ukraine in the period of conducting the survey (November 2022), a non-representative research sample – overrepresentation of people aged 18–25 years.

The research study contributes to the knowledge about consumer brand attitudes and preferences under unique social, economic and market conditions. These conditions were created by Russia's invasion of Ukraine in 2022, as well as the international and global character of the war in Ukraine. The significant implications of the study refer to brand communication policies and companies' CSR-related declarations. A number of consumers' errors were recorded, resulting from wrong brand retrieval, which were rectified at a later stage as a result of international restrictions imposed on Russia, harsh media criticism and social international embargoes imposed on brands offered in Russia. The marketing communication of contemporary global brands should give consideration to the informative function of CSR activities, and the communication process should be continuous. Critical attitudes and an inclination to boycott brands point to the possible consequences faced by inconsistent and ethically doubtful brand policies. This implication is clearly confirmed by the results of the study.

The authors also wish to highlight the implications for practice and society. As mentioned earlier, Polish consumers involved in providing aid to victims of the war also expressed their opposition to the war by boycotting Russian products and international brands remaining in Russia. Popularization of the research results obtained by the authors can be a form of sensitizing the public to the need for long-term relief, awakening global awareness of the essence and importance of sanctions imposed on Russia, as well as the possibility of expressing opposition through individual purchasing decisions and boycotting brands still present in Russia.

The study allowed for identifying consumers' differentiated brand attitudes in two countries: a country inflicted by war (Ukraine) and a front-line country, strongly supporting Ukraine (Poland). The research contributes to consumer behavior theories and studies of consumer attitudes and preferences from the perspective of international corporations' CSR activities under the unique conditions of war. Also, it contributes to the knowledge of the mechanism of forming attitudes to Russian and international brands offered in Russia among CEE consumers.

This study aims to examine adolescents’ social media environment connected to unhealthy food marketing. As social media have become a ubiquitous part of young people’s everyday lives, marketers have also shifted their focus to these channels. Literature on this phenomenon is still scarce and often takes a quite narrow view of the role of marketing in social media. Furthermore, the experiences of the adolescents are seldom considered.

Using a sociocultural approach and netnographic methodology, this study presents findings from a research project conducted in Finland. The data consist of both social media material and focus group interviews with adolescents.

The findings elaborate on unhealthy food marketing to adolescents in social media from two perspectives: sociocultural representations of unhealthy foods in social media marketing and social media influencers connecting with adolescents.

The study broadens and deepens the current understanding of unhealthy food marketing to adolescents taking place in social media. The study introduces a novel perspective to the topic by looking at it as a sociocultural phenomenon.

This study aims to empirically test how sponsored video customization (i.e. the degree to which a sponsored video is customized for a sponsoring brand) affects video shares differently depending on influencer characteristics (i.e. mega influencer and expert influencer) and brand characteristics (i.e. brand establishment and product involvement).

This study uses a unique real-world data set that combines coded variables (e.g. customization) and objective video performance (e.g. sharing) of 365 sponsored videos to test the hypotheses. A negative binomial model is used to analyze the data set.

This study finds that the effect of video customization on video shares varies across contexts. Video customization positively affects shares if they are made for well-established brands and high-involvement products but negatively influences shares if they are produced by mega and expert influencers.

This study extends the influencer marketing literature by focusing on a new media modality – sponsored video. Drawing on the multiple inference model and the persuasion knowledge theory, this study teases out different conditions under which video customization is more or less likely to foster audience engagement, which both influencers and brands care about. The chosen research setting may limit the generalizability of the findings of this study.

The findings suggest that mega and expert influencers need to consider if their endorsement would backfire on a highly customized video. Brands that aim to engage customers with highly-customized videos should gauge their decision by taking into consideration their years of establishment and product involvement. For video-sharing platforms, especially those that are planning to expand their businesses to include “matching-making services” for brands and influencers, the findings provide theory-based guidance on optimizing such matches.

This paper fulfills an urgent research need to study how brands and influencers should produce sponsored videos to achieve optimal outcomes.

This study aims to deepen the understanding of the challenges and implications entailed by deploying mobile clinics in conflict zones to reach populations affected by violence and cut off from health-care services.

This research combines an integrated literature review and an instrumental case study. The literature review comprises two targeted reviews to provide insights: one on conflict zones and one on mobile clinics. The case study describes the process and challenges faced throughout a mobile clinic deployment during and after the Iraq War. The data was gathered using mixed methods over a two-year period (2017–2018).

Armed conflicts directly impact the populations’ health and access to health care. Mobile clinic deployments are often used and recommended to provide health-care access to vulnerable populations cut off from health-care services. However, there is a dearth of peer-reviewed literature documenting decision support tools for mobile clinic deployments.

This study highlights the gaps in the literature and provides direction for future research to support the development of valuable insights and decision support tools for practitioners.

Perspiration and heat are produced by the body and must be eliminated to maintain a stable body temperature. Sweat, heat and air must pass through the fabric to be comfortable. The cloth absorbs sweat and then releases it, allowing the body to chill down. By capillary action, moisture is driven away from fabric pores or sucked out of yarns. Convectional air movement improves sweat drainage, which may aid in body temperature reduction. Clothing reduces the skin's ability to transport heat and moisture to the outside. Excessive moisture makes clothing stick to the skin, whereas excessive heat induces heat stress, making the user uncomfortable. Wet heat loss is significantly more difficult to understand than dry heat loss. The purpose of this study is to provided a good compilation of complete information on wet thermal comfort of textile and technological elements to be consider while constructing protective apparel.

This paper aims to critically review studies on the thermal comfort of textiles in wet conditions and assess the results to guide future research.

Several recent studies focused on wet textiles' impact on comfort. Moisture reduces the fabric's thermal insulation value while also altering its moisture characteristics. Moisture and heat conductivity were linked. Sweat and other factors impact fabric comfort. So, while evaluating a fabric's comfort, consider both external and inside moisture.

The systematic literature review in this research focuses on wet thermal comfort and technological elements to consider while constructing protective apparel.

This paper aims to examine how the fields of social enterprise, social entrepreneurship and social innovation have theorised and applied the concepts of narrative and storytelling.

A literature review and subsequent thematic analysis were used. A keyword search of three databases identified 93 relevant articles that were subsequently reviewed for this paper.

Four main roles for storytelling and narrative were found in the literature: to gain support for social innovation, to inspire social change, to build a social-entrepreneurial identity and to debate the meaning and direction of social innovation itself.

Following the literature review, capacities and applications of storytelling and narrative in other, related fields are discussed to highlight practical use cases of storytelling that might currently be underdeveloped in the social enterprise and innovation sectors.

The paper argues that the social innovation and enterprise literature predominantly views storytelling as a form of mass communication, while often overlooking its ability to foster communal debate and organise intrapersonal dialogue as possible aspects of strategic thinking and innovation management in social enterprise, social entrepreneurship and social innovation.

The purpose of this paper is twofold: first, a case study on applying lean principles in manufacturing operations to redesign and optimize an electronic device assembly process and its impact on performance and second, introducing cardboard prototyping as a Kaizen tool offering a novel approach to testing and simulating improvement scenarios.

The study employs value stream mapping, root cause analysis, and brainstorming tools to identify root causes of poor performance, followed by deploying a Kaizen event to redesign and optimize an electronic device assembly process. Using physical models, bottlenecks and opportunities for improvement were identified by the Kaizen approach at the workstations and assembly lines, enabling the testing of various scenarios and ideas. Changes in lead times, throughput, work in process inventory and assembly performance were analyzed and documented.

Pre- and post-improvement measures are provided to demonstrate the impact of the Kaizen event on the performance of the assembly cell. The study reveals that implementing lean tools and techniques reduced costs and increased throughput by reducing assembly cycle times, manufacturing lead time, space utilization, labor overtime and work-in-process inventory requirements.

This paper adds a new dimension to applying the Kaizen methodology in manufacturing processes by introducing cardboard prototyping, which offers a novel way of testing and simulating different scenarios for improvement. The paper describes the process implementation in detail, including the techniques and data utilized to improve the process.