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The purpose of this paper is to adopt the uses and gratifications theory to tourism.

Prior work underscores the important role of customer advocacy for brands. The purpose of this study is to explore the critical role customers can play as brand heroes. The authors developed and validated a measurement scale composed of properties that are derived from distinct brand hero motivational mechanisms.

The authors conducted one exploratory pilot, using semi-structured interviews, with industry and academic experts, and employed three main studies across varying brands and market settings.

This study explores and empirically demonstrates how the brand hero scale (BHS) is related to, yet distinct from, existing scales of opinion leaders, market mavens, attachment and customer advocacy. The six-item BHS demonstrates convergent, discriminant, nomological and predictive validity across several different brand contexts.

This research extends the extant body of work by identifying and defining brand heroes, developing and validating a parsimonious BHS, and demonstrating how its predictive validity extends both to a range of key advocacy and loyalty customer behaviors.

The study provides provocative insights for marketing researchers and brand managers and ascertains the important role heroes may play for brands in terms of strong customer advocacy and loyalty behaviors.

Building on the theory of meaning, this study shows that identifying and working with brand heroes is of great managerial importance and offers critical avenues for future research.

The transportation system in any city is complex and evolving, shaped by various driving forces and uncertainties in the social, economic, technological, political and environmental situations. Its development and demands upon it cannot be projected by simply extrapolating past and current trends. This paper aims to present a foresight study examining the future of urban mobility, focusing on the dense Asian city-state of Singapore. The objective is to develop scenarios for the future of urban mobility, to facilitate future policy implementation by highlighting long term challenges and opportunities for transportation planning in cities.

To create future scenarios, the authors first sought to identify key drivers of change through environmental scanning, expert interviews, focus group discussions and technology scanning. These drivers of change were subsequently used in a scenario planning workshop, organized to co-create alternative future visions for urban mobility 2040 with experts and local stakeholders.

Two scenarios emerged, called the Shared World and the Virtual World. For each scenario, the authors described the key features in terms of dominant transport modes for the movements of passengers and freight. Subsequently, the authors discussed possible implications of each scenario to the individual, society, industry and government.

As cities grow and develop, city and transport planners should not only address daily operational issues but also develop a well-informed, long-term understanding of the evolving mobility system to address challenges that lie beyond the five- or even ten-year horizon. By using scenario planning approach, the authors hope to prepare stakeholders for the uncertain futures that are continuously shaped by the decisions today.

This study aims to explore virtual leadership work within educational settings in the light of social disruption. In 2020, a global pandemic changed the way we work. For school leaders, that involved running a virtual school overnight. Although there is a stream of research that explores leadership in solely virtual communities, there is a gap in the literature regarding practices that transition from analog to virtual practices and the changes in leadership in those types of work practices.

The data gathering method constitutes a questionnaire to explore school leaders’ experiences of virtual work and virtual leadership in light of social disruption. One hundred and five Swedish school leaders answered the questionnaire covering both fixed and open questions.

The results show that school leaders’ general experiences of transition to virtual school have worked relatively well. We show how the work changes and shift the focus in the virtual workplace.

The author’s contributions include theorizing about leadership affordances in virtual schools and providing implications for practice. The authors summarize our main contribution in five affordances that characterize virtual leadership, including a focus on core activities, trust-based government, 1:1 communication with staff, structure and clarity and active outreach activities. The results could be interesting for understanding the radical digitalization of leadership in the digital workplace.

Mobile phone-based human activity recognition (HAR) consists of inferring user’s activity type from the analysis of the inertial mobile sensor data. This paper aims to mainly introduce a new classification approach called adaptive k-nearest neighbors (AKNN) for intelligent HAR using smartphone inertial sensors with a potential real-time implementation on smartphone platform.

The proposed method puts forward several modification on AKNN baseline by using kernel discriminant analysis for feature reduction and hybridizing weighted support vector machines and KNN to tackle imbalanced class data set.

Extensive experiments on a five large scale daily activity recognition data set have been performed to demonstrate the effectiveness of the method in terms of error rate, recall, precision, F1-score and computational/memory resources, with several comparison with state-of-the art methods and other hybridization modes. The results showed that the proposed method can achieve more than 50% improvement in error rate metric and up to 5.6% in F1-score. The training phase is also shown to be reduced by a factor of six compared to baseline, which provides solid assets for smartphone implementation.

This work builds a bridge to already growing work in machine learning related to learning with small data set. Besides, the availability of systems that are able to perform on flight activity recognition on smartphone will have a significant impact in the field of pervasive health care, supporting a variety of practical applications such as elderly care, ambient assisted living and remote monitoring.

The purpose of this study is to build and test an accurate offline model by using only a compact training data that can reduce the computational and memory complexity of the system. This provides grounds for developing new innovative hybridization modes in the context of daily activity recognition and smartphone-based implementation. This study demonstrates that the new AKNN is able to classify the data without any training step because it does not use any model for fitting and only uses memory resources to store the corresponding support vectors.