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Professional development (PD) is an essential component of continuing learning for in-service teachers. This paper discusses a school-based example of using the best practice of coaching in early childhood education supported by a professional development school partnership. We explain how a teacher identified need led to a collaborative, multistep approach to meeting that need in connection to State mandates.

In this research, we used a case study methodological approach with a team of preschool teachers at one school. The model combines use of PD sessions, classroom coaching, classroom observation and reflection.

Teachers’ feedback indicates that using the strategy positively impacted most of the participants’ ability to support communication, community-building and inclusive practices in their classrooms. The data that emerged in the following year evidenced increased use of visual supports in classrooms, use in connection with literacy goals and interest in creating new uses in the school.

This article contributes an action-oriented school-based example of bridging research to practice to support teachers’ needs through PD and coaching in a PDS. The design and practical implications may interest preschool educators, instructional coaches, administrators, professional development schools and others involved with monitoring teacher development initiatives.

The goal of this study is to test the real-world use of an emotion recognition system.

The researchers chose an existing algorithm that displayed high accuracy and speed. Four emotions: happy, sadness, anger and surprise, are used from six of the universal emotions, associated by their own mood markers. The mood-matrix interface is then coded as a web application. Four guidance counselors and 10 students participated in the testing of the mood-matrix. Guidance counselors answered the technology acceptance model (TAM) to assess its usefulness, and the students answered the general comfort questionnaire (GCQ) to assess their comfort levels.

Results from TAM found that the mood-matrix has significant use for the guidance counselors and the GCQ finds that the students were comfortable during testing.

No study yet has tested an emotion recognition system applied to counseling or any mental health or psychological transactions.

This study aims to investigate different types of platform providers (PPs) to gain a deeper understanding of the characteristics and underlying logic of this group within collaborative consumption (CC). As CC occurs with three groups of actors (PP, peer service provider and customer) and is predominantly viewed from the customer perspective, this study offers insights from the under-researched PP perspective.

This research applies a multiple case study approach and analyzes descriptively and thematically 92 cases of CC PPs gathered through the Crunchbase database.

The authors derive four archetypes of CC PPs, namely, the hedonist, functionalist, environmentalist and connector, that differ in their offered values, dominating motives and activities across industries.

The authors conceptualize CC by clearly describing the four archetypes and their characteristics. However, further research would benefit from including databases other than Crunchbase.

PPs need to understand their value offerings and customer preferences to develop convincing value propositions and offer engaging activities. PPs would benefit from a more active social media presence to build strong relations with customers and peer service providers to effectively communicate their values.

The paper is pioneering as it encompasses the perspective of CC PPs and operationalizes the concept of CC. The authors address the lack of research on CC by conducting an extensive case study.

This study aims to introduce an alternative model, “volatility, uncertainty, complexity and ambiguity (VUCA), Virtue and Vice” (3V’s), to unleash leadership skills, promote organisational collaborative change and impact sales performance during an unprecedented crisis.

The methodology outlines action research based on the 3V’s model and its application in an international business-to-business sales organisation during Covid-19. It explores alternative paths informed by play-at-work and Plato’s philosophy applied to work-based-learning. Each action/iteration adds to the model, which becomes more likely appropriate for various situations.

The 3V’s boosted change implementation and improved sales performance. The 3V’s conceptualised an invitation to immerse oneself in the constant “river of change” (VUCA) and a means of understanding the role of leadership in navigating this change by embracing simple rules: searching for justice (Virtue) and overcoming the barrier of public opinion (Vice).

The 3V’s model is grounded in leadership literature and a sole application, providing real international data relevant to organisations and leaders. This has yet to be evaluated further.

3V’s can enhance the understanding of a leading collaborative change and re-frame team dynamics in post-pandemic times for the broader public.

The approach advocated is a practice of “swimming alongside the team”, which should enable empowerment and collaboration rather than a top-down direction. Focussing on leaders who are moral people, this approach becomes a differentiator in a digital world.

This study examines Plato’s philosophy, play-at-work and other leadership theories in a model which prepares organisations to respond to crisis by providing the ability to reflect on human aspects and straightforward, transferable skills.

The European Union (EU) has recently adopted gender quotas for corporate boards (CBQ), anticipating ripple effects on women’s careers in the companies concerned, as well as throughout the economy. The purpose of this paper is to investigate whether CBQ has spurred ripple effects and discuss mechanisms hindering or facilitating women’s occupancy of top executive positions.

Norway was the first country in the world to introduce CBQ in 2003, with full effect from 2008. The policy requires company boards to be composed of 40% of each gender. Drawing on original data mapping boards and executive committees in Norway’s 200 largest companies, the authors analyze the association between CBQ and the gender composition of executive management almost 15 years after the full implementation. The data include both companies covered by the CBQ and large companies not covered.

The investigation does not find a positive association between CBQ and more women in executive positions. Thus, the ripple effect hypothesis of CBQ is not supported. CBQ may have contributed to an increased awareness of gender imbalances, yet these findings indicate that to achieve more gender balance in executive positions, scholars and practitioners may need to focus more on gendered conditions and processes in organizations and society throughout executive careers than on the gender composition of boards.

This paper provides empirical analyses of original data 15 years after the implementation of CBQ. The authors further contribute to scholarly debate by identifying and discussing possible mechanisms that explain how requiring more women on corporate boards may – or may not – have ripple effects on executive management.

This article aims to map the expectations of manufacturing companies towards suppliers in terms of implementing improvement activities. The article poses two research questions: RQ1: What kind of improvement of activities do the surveyed producers expect from their suppliers? RQ2: Do factors such as size, capital or implemented systems influence different assessments of the analyzed requirements toward suppliers?

The Computer Assisted Telephone Interview (CATI) technique was used to collect data. The sample consists of 150 producers (employing over 50 people) who were suppliers for enterprises from the automotive, electromechanical and chemical sectors operating in the Polish business-to-business (B2B) market. We analyzed 11 improvement activities, while their correlation structure was examined by exploratory factor analysis.

We have identified three latent factors – risk reduction, product innovation and increasing efficiency – which summarize the main expectations of manufacturing companies towards suppliers. Expectations for these factors are independent of the implemented management system, although the analysis showed higher expectations for product innovation in organizations with the implementation of Kaizen.

The article fills the research gap in the literature. The research results presented in the literature so far have focused on the expectations of enterprises towards suppliers in terms of meeting the criteria for their initial and periodic assessment. The research gap in the article is the result of empirical research presenting the expectations of manufacturers towards suppliers in terms of improving their processes. Based on the findings of the presented study, development trends and implications for managers responsible for purchasing processes and relationships with suppliers can be determined.

With Industry 4.0 and the extensive rise of smart technologies, we are seeing remarkable transformations in work practices and workplaces. Scholars report the phenomenal progress of smart technologies. At the same time, we can hear the rhetoric emphasising their potential threats. This study focusses on how and where intelligent machines are leveraged in the workplace, how humans co-working with intelligent machines are affected and what they believe can be done to mitigate the risks of the increased use of intelligent machines.

We conducted in-depth interviews with 15 respondents working in various leadership capacities associated with intelligent machines and technologies. Using NVivo, we coded and churned out the themes from the qualitative data collected.

This study shows how intelligent machines are leveraged across different industries, ranging from chatbots, intelligent sensors, cognitive systems and computer vision to the replica of the entire human being. They are used end-to-end in the value chain, increasing productivity, complementing human workers’ skillsets and augmenting decisions made by human workers. Human workers experience a blend of positive and negative emotions whilst co-working with intelligent machines, which influences their job satisfaction level. Organisations adopt several anticipatory strategies, like transforming into a learning organisation, identifying futuristic technologies and upskilling their human workers, regularly conducting social learning events and designing accelerated career paths to embrace intelligent technologies.

This study seeks to understand the emotional and practical implications of the use of intelligent machines by humans and how both entities can integrate and complement each other. These insights can help organisations and employees understand what future workplaces and practices will look like and how to remain relevant in this transformation.

The purpose of this paper is to analyze if the sport trajectory could be an impact factor in leadership development.

A qualitative research method has been adopted by conducting 17 in-depth, semi-structured interviews. The data were analyzed with the program Open Code (4.03).

The findings of this study revealed that the interviewed managers perceived that their sport trajectory has had an important influence in the development of their leadership. This influence is determined by four factors: (1) sport profile, (2) sport referents, (3) competences, values and abilities and (4) experiences from different sport roles played during their lifespan.

The research is based on interviews with a small sample of managers. In order to develop the research further, a more extensive sample is required.

The paper is unique as it examines the impact of the sport trajectory as an impact factor in leadership development.

In this article, we reflect on how smart technology is transforming service research discourses about service innovation and value co-creation. We adopt the concept of technology smartness’ to refer to the ability of technology to sense, adapt and learn from interactions. Accordingly, we seek to address how smart technologies (i.e. cognitive and distributed technology) can be powerful resources, capable of innovating in relation to actors’ agency, the structure of the service ecosystem and value co-creation practices.

This conceptual article integrates evidence from the existing theories with illustrative examples to advance research on service innovation and value co-creation.

Through the performative utterances of new tech words, such as onlife and materiality, this article identifies the emergence of innovative forms of agency and structure. Onlife agency entails automated, relational and performative forms, which provide for new decision-making capabilities and expanded opportunities to co-create value. Phygital materiality pertains to new structural features, comprised of new resources and contexts that have distinctive intelligence, autonomy and performativity. The dialectic between onlife agency and phygital materiality (structure) lies in the agencement of smart tech–enabled value co-creation practices based on the notion of becoming that involves not only resources but also actors and contexts.

This paper proposes a novel conceptual framework that advances a tech-based ecology for service ecosystems, in which value co-creation is enacted by the smartness of technology, which emerges through systemic and performative intra-actions between actors (onlife agency), resources and contexts (phygital materiality and structure).

Gathering knowledge regarding personality traits has long been the interest of academics and researchers in the fields of psychology and in computer science. Analyzing profile data from personal social media accounts reduces data collection time, as this method does not require users to fill any questionnaires. A pure natural language processing (NLP) approach can give decent results, and its reliability can be improved by combining it with machine learning (as shown by previous studies).

In this, cleaning the dataset and extracting relevant potential features “as assessed by psychological experts” are essential, as Indonesians tend to mix formal words, non-formal words, slang and abbreviations when writing social media posts. For this article, raw data were derived from a predefined dominance, influence, stability and conscientious (DISC) quiz website, returning 316,967 tweets from 1,244 Twitter accounts “filtered to include only personal and Indonesian-language accounts”. Using a combination of NLP techniques and machine learning, the authors aim to develop a better approach and more robust model, especially for the Indonesian language.

The authors find that employing a SMOTETomek re-sampling technique and hyperparameter tuning boosts the model’s performance on formalized datasets by 57% (as measured through the F1-score).

The process of cleaning dataset and extracting relevant potential features assessed by psychological experts from it are essential because Indonesian people tend to mix formal words, non-formal words, slang words and abbreviations when writing tweets. Organic data derived from a predefined DISC quiz website resulting 1244 records of Twitter accounts and 316.967 tweets.