Search results

To date, little research has been undertaken to test the effectiveness of team coaching, with past work focusing on models, frameworks and competencies. This study aimed to examine the effectiveness of team coaching within real world organizational teams and its impact on individual perceptions of team cohesion and psychological safety.

A randomized control trial (RCT) using the comparable interventions: (1) team coaching (intervention) and (2) team facilitation (control) was employed with multiple teams and multiple facilitators, measuring the impact on team cohesion and psychological safety.

The data indicate participants engaging in the team coaching intervention made greater gains in terms of their individual perceptions of psychological safety and team cohesion than individuals who received the team facilitation intervention (T1–T2).

Facilitators should apply a team coaching approach when seeking to address issues of cohesion and psychological safety within workplace teams.

This study provides the first evidence, using an RCT method, of the effectiveness of team coaching as a workplace intervention for enhancing individual perceptions of psychological safety and team cohesion.

In an era where complex technological advances increasingly govern service delivery, it is incumbent on service firms to pioneer innovative strategies to sustain customer engagement and cultivate loyalty. This conceptual paper examines the transformative potential of artificial intelligence (AI) in the realm of online customer communities, with a particular focus on its creation, management and enhancement facets. The authors explore how AI can revolutionize the dynamics of customer interaction, feedback mechanisms and overall engagement within the service industry.

This conceptual paper draws from marketing and management literature focusing on customer communities and AI in service and customer engagement contexts with a robust future research agenda.

A classification of online customer community engagement is provided along with a conceptual framework to guide our understanding of the integration of AI into online customer communities.

This exploration underscores the imperative for service firms to embrace AI-driven approaches to online customer community management, not only as a means to optimize their operations but as a vital strategy to stay competitive in the ever-evolving digital landscape. This paper examines the novel combination of AI with online customer communities and provides the framework in the form of an input-process-output (IPO) model for future research into this integration.

This study aims to explore the constructs of spirituality (SP) and entrepreneurial performance (EP) and their measurements to identify their connections. Attending to the needs of entrepreneurs to face the current global crisis, this research establishes a framework that integrates SP to enhance EP.

This study focuses on a comprehensive literature review and a comparison between constructs to come across with the proposal of a conceptual framework.

For SP, spiritual well-being was found as a good measure which, to the best of the authors’ knowledge, has never been used in entrepreneurship. EP has been typically measured by economic indicators, but recently, noneconomic benefits and effects on stakeholders have also been considered, so an integrated approach is proposed. The main contribution is a framework called holistic entrepreneurial inventory (HEI), which integrates the main elements of the constructs in a matrix showing their interconnection. It is accompanied by a scorecard for entrepreneurs to identify strengths and weaknesses in SP and EP.

This is a theoretical research and proposal; further empirical research could help confirm the present conceptual findings.

To help entrepreneurs identify the areas where they would like to improve, understanding the connection between SP and EP, which are dynamic states in constant change.

EP has been mainly focused on exogenous causes. The HEI scorecard may give entrepreneurs a different perspective from the innermost part of their being.

A sense of collective free-thinking with tangible goals makes co-creation an enlightening experience. Yet despite the freedom and organic flow of the methodology, there remain barriers to deploying co-creation in the real-world context. The aim was to understand the barriers and solutions to co-creation, reflect on applying co-creation in practice and co-create an applicable framework for co-creation.

These reflections and conceptual developments were completed using a Participatory Action Research Approach through the co-creation of the Erasmus+ funded Co-creating Welfare course.

Results presented are centric to the experiences in the United Kingdom but led to application at an international level. Problem formulation led to solutions devised about who should co-create, what co-creation aims to achieve, how to receive management buy-in, co-creating beyond the local face to face context and evaluation.

The Three Co’s Framework is proposed using the outline of: Co-Define, Co-Design and Co-Refine. Those who take part in co-creation processes are recommended to be called co-creators, with less focus on “empowerment” and more about facilitating people to harness the power they already have. Utilising online and hybrid delivery methods can be more inclusive, especially in response to the COVID-19 pandemic. The use of co-creation needs to be evaluated more moving forwards, as well as the output co-created.

Triggered by the extensive use of social media brand communities (SMBCs) in interactive marketing, this article aims to explore how brand connectedness (BC) affects consumer engagement behavior (CEB) in SMBCs.

The research model was verified with the partial least squares structural equation modeling applied to the actual data collected from the web crawling largest microblogging platform in China (Sina Weibo).

Results indicate that BC may positively influence consumer emotions (CEs), eventually leading to engagement behavior in SMBCs. In addition, gender and duration of membership act as vital moderators in the model. One of the most interesting findings is the differences between posting and commenting, although both are CEBs. BC has a more significant effect on commenting than posting, and the mediating effect of CEs between BC and posting behavior is not significant.

This research contributes to the literature on interactive marketing by examining BC in the context of SMBCs, which is under-researched in the literature but is highly pertinent to social media contexts. Moreover, we measure BC through social network analysis for the first time, which not only supports the empirical work but also expands the social network theory and social capital theory. This research also extends the body of knowledge on consumer engagement by investigating the differences between posting and commenting behaviors.

This study investigates how firms build strong dynamic marketing capability (DMC) from open innovation (OI) to enhance the performance of entrepreneurial firms. Moreover, this study unfolds DMC's mediating and moderating mechanisms underlying inbound and outbound OI and performance relationships, respectively.

To test the research model and hypotheses, this study drew a sample of 251 firms operating in Malaysia using the time-lagged survey method. Structural equation modelling was used in this study to investigate the model relationships.

The findings of this study reveal the positive interplay between inbound OI (knowledge acquisition) and DMC. The outbound OI (knowledge exploitation) in this study is found to mediate the relationship between inbound OI and firm performance. In addition, while the DMC has a mediating effect in the relationship between inbound OI and firm performance, such a capability reinforces the positive relationship between outbound OI and performance.

This study provides a noble insight into the complex interplay between OI and entrepreneurial firms' performance by developing and testing an integrated framework underpinned by a knowledge-based view and dynamic capability theory. The findings highlight the significance of taking an interdisciplinary and integrated approach to better understand the determinants of entrepreneurial firms' performance in an emerging country context.

This study aims to achieve superior localization and mapping performance in point cloud degradation scenarios through the effective removal of dynamic obstacles. With the continuous development of various technologies for autonomous vehicles, the LIDAR-based Simultaneous localization and mapping (SLAM) system is becoming increasingly important. However, in SLAM systems, effectively addressing the challenges of point cloud degradation scenarios is essential for accurate localization and mapping, with dynamic obstacle removal being a key component.

This paper proposes a method that combines adaptive feature extraction and loop closure detection algorithms to address this challenge. In the SLAM system, the ground point cloud and non-ground point cloud are separated to reduce the impact of noise. And based on the cylindrical projection image of the point cloud, the intensity features are adaptively extracted, the degradation direction is determined by the degradation factor and the intensity features are matched with the map to correct the degraded pose. Moreover, through the difference in raster distribution of the point clouds before and after two frames in the loop process, the dynamic point clouds are identified and removed, and the map is updated.

Experimental results show that the method has good performance. The absolute displacement accuracy of the laser odometer is improved by 27.1%, the relative displacement accuracy is improved by 33.5% and the relative angle accuracy is improved by 23.8% after using the adaptive intensity feature extraction method. The position error is reduced by 30% after removing the dynamic target.

Compared with LiDAR odometry and mapping algorithm, the method has greater robustness and accuracy in mapping and localization.

To support achieving sustainable development goals (SDGs), we integrated science, technology, engineering and math (STEM) and extended reality technologies into an artificial intelligence (AI) learning activity. We developed Feature City to facilitate students' learning of AI concepts. This study aimed to explore students' learning outcomes and behaviors when using Feature City.

Junior high school students were the subjects who used Feature City in an AI learning activity. The learning activity consisted of 90-min sessions once per week for five weeks. Before the learning activity, the teacher clarified the learning objectives and administered a pretest. The teacher then instructed the students on the features, supervised learning and unsupervised learning units. After the learning activity, the teacher conducted a posttest. We analyzed the students' prior knowledge and learning performance by evaluating their pretest and posttest results and observing their learning behaviors in the AI learning activity.

(1) Students used Feature City to learn AI concepts to improve their learning outcomes. (2) Female students learned more effectively with Feature City than male students. (3) Male students were more likely than female students to complete the learning tasks in Feature City the first time they used it.

Within SDGs, this study used STEM and extended reality technologies to develop Feature City to engage students in learning about AI. The study examined how much Feature City improved students' learning outcomes and explored the differences in their learning outcomes and behaviors. The results showed that students' use of Feature City helped to improve their learning outcomes. Female students achieved better learning outcomes than their male counterparts. Male students initially exhibited a behavioral pattern of seeking clarification and error analysis when learning AI education, more so than their female counterparts. The findings can help teachers adjust AI education appropriately to match the tutorial content with students' AI learning needs.

This paper aims to understand how immigrant entrepreneurs use digital opportunities to overcome the liability of newness and foreignness and how an immigrant's ethnicity can be digitally performed as an asset in business.

The study adopts an inductive multiple case study approach using social media content. The data consist of over 3,500 posts, images and screenshots from Facebook, Instagram and the webpages of seven successful Vietnamese restaurants in Sweden. Grounded content analysis was conducted using NVivo.

The findings suggest that digitalising ethnic artifacts can mediate and facilitate three digital performances that together can turn ethnicity from a liability to an asset: (i) preserving performance through digital ethnicising, (ii) embracing performance through digital generativitising and (iii) appropriating performance through digital fusionising. The results support the introduction of a conceptual framework depicting the interwoven duality of horizontal and vertical boundary blurring, in which the former takes place between the offline and online spaces of immigrant businesses, and the latter occurs between the home and host country attachment of the immigrant businesses.

This study responds to calls for understanding how immigrant entrepreneurs can overcome the liability of foreignness. It offers a fresh look at ethnicity, which has been seen in a negative light in the field of immigrant entrepreneurship. This study illuminates that ethnicity can be used as a resource in immigrant entrepreneurship, specifically through the use of digital artifacts and digital platforms.

The present research aims to investigate how lean project management (LPM) and agile project management (APM) affect project performance outcomes in the construction sector in Jordan. This study focuses on six key project performance outcomes, namely cost, time, quality, client satisfaction, innovation and responsiveness.

The present study employed a quantitative approach to achieve the research objectives. Accordingly, a multi-item survey questionnaire was prepared to gather data from 392 project managers from construction companies in Jordan. The study’s model showed acceptable levels regarding reliability, validity, fit indices and discriminant validity. In order to test the hypotheses of this study, path analysis was employed using Amos 24.0 software.

LPM demonstrated a remarkably high positive impact on cost performance. It also positively affected quality performance and client satisfaction. However, LPM insignificantly affected time, innovation and responsiveness performance measures. On the other hand, APM showed a notably high positive impact on innovation and responsiveness. The findings also revealed that APM positively impacted quality performance and client satisfaction. In addition, APM negatively impacted cost performance and insignificantly impacted time performance.

This study is one of the first comprehensive studies to empirically examine the impact of both LPM and APM on various project performance outcomes in the construction industry in the context of a developing country. It reveals some similarities and differences between LPM and APM with regard to their impacts on project management outcomes. The findings are expected to guide managers in selecting the appropriate project management approach based on the desired performance outcomes. Accordingly, it offers important implications for project managers in construction companies.