Search results

This chapter aims to shed light on the role that a sustainable orientation plays in strengthening the relationships between global consumers and online brands. Despite many previous studies about the importance of sustainability considerations for national consumers’ brand commitments and purchase intentions, there is a lack of empirical studies focussing on this relationship from a global consumer perspective. A pre-study (consisting of focus group discussions) and a widely distributed international survey with responses from 74 countries show mixed results. Whereas the results from the focus groups imply that a sustainable orientation influences both global consumers’ purchase intentions and brand commitments towards online brands, the survey results imply that global consumers’ sustainable orientations do not affect purchase intentions directly, even though they influence brand commitments. An implication of these results is that an international online brand’s possibility to portray a sustainable orientation plays an important role in strengthening the relationship with global consumers, especially regarding brand commitment.

This paper focuses on governance in higher education in China. It sees that governance as distinctive on the world scale and the potential source of distinctiveness in other domains of higher education. By taking an historical approach, reviewing relevant literature and drawing on empirical research on governance at one leading research university, the paper discusses system organisation, government–university relations and the role of the Communist Party (CCP), centralisation and devolution, institutional leadership, interior governance, academic freedom and responsibility, and the relevance of collegial norms. It concludes that the party-state and Chinese higher education will need to find a Way in governance that leads into a fuller space for plural knowledges, ideas and approaches. This would advance both indigenous and global knowledge, so helping global society to also find its Way.

Efficient traffic incident management is needed to alleviate the negative impact of traffic incidents. Accurate and reliable estimation of traffic incident duration is of great importance for traffic incident management. Previous studies have proposed models for traffic incident duration prediction; however, most of these studies focus on the total duration and could not update prediction results in real-time. From a traveler’s perspective, the relevant factor is the residual duration of the impact of the traffic incident. Besides, few (if any) studies have used dynamic traffic flow parameters in the prediction models. This paper aims to propose a framework to fill these gaps.

This paper proposes a framework based on the multi-layer perception (MLP) and long short-term memory (LSTM) model. The proposed methodology integrates traffic incident-related factors and real-time traffic flow parameters to predict the residual traffic incident duration. To validate the effectiveness of the framework, traffic incident data and traffic flow data from Shanghai Zhonghuan Expressway are used for modeling training and testing.

Results show that the model with 30-min time window and taking both traffic volume and speed as inputs performed best. The area under the curve values exceed 0.85 and the prediction accuracies exceed 0.75. These indicators demonstrated that the model is appropriate for this study context. The model provides new insights into traffic incident duration prediction.

The incident samples applied by this study might not be enough and the variables are not abundant. The number of injuries and casualties, more detailed description of the incident location and other variables are expected to be used to characterize the traffic incident comprehensively. The framework needs to be further validated through a sufficiently large number of variables and locations.

The framework can help reduce the impacts of incidents on the safety of efficiency of road traffic once implemented in intelligent transport system and traffic management systems in future practical applications.

This study uses two artificial neural network methods, MLP and LSTM, to establish a framework aiming at providing accurate and time-efficient information on traffic incident duration in the future for transportation operators and travelers. This study will contribute to the deployment of emergency management and urban traffic navigation planning.

The purpose of this paper is to present the initial results of the Camp Performance Indicator (CPI) system to illustrate the importance of self-reliance of refugee camp dwellers with regard to infrastructure and service investments.

Data, derived from a field trip to Zaatari in autumn 2016 and thorough literature research, were taken to develop a new CPI system. The findings from the literature research were merged with available camp data to validate each other.

Self-reliance is a fundamental human right and anchored in the UN sustainable development goals. Yet, presented findings reveal that even in one of the most modern refugee camps in the world – Zaatari – the level of self-reliance is rather low. However, organisations and humanitarian logisticians can influence self-reliance by identifying clearly where challenges are.

Data from a diverse range of reports were extracted. As most of these reports lack reliable and comparative quantitative data, the limitation of the study must be taken into account. So far data were only validated on one case study. To develop the tool further, more data need to be taken into account.

To this point, there is no performance measurement tool available focusing on self-reliance of encamped refugees. In addition, no academic research has measured the interrelation between the level of investments in infrastructure and services and the improvement of the lives of camp residents, especially regarding the level of self-reliance.

Air quality and its assessment in urban areas has become a necessity. This is attributed to the increasing air pollution in urban landscape from anthropogenic activities necessary for economic growth and development. This study investigates air quality and potential health risk posed from nitrogen dioxide (NO₂) to the residents of low town of Mohammedia city, Morocco.

The NO₂ concentration was measured on an hourly basis for the winter season of the year 2014, 2015 and 2016. The air quality was assessed in terms of Air Quality Index (AQI). Noncarcinogenic risk assessment was done to evaluate possible health risk to the inhabitant of low town from NO₂ exposure.

The maximum concentration reached 85–96 µg/m³ (at 6 p.m., 2014), 96–104 µg/m³ (7–9 p.m., 2015) and 102–117 (8–11 p.m., 2016). The AQI during maximum NO₂ levels (peak hours) ranged between 0–50 µg/m³ (good) to 51–100 µg/m³ (unhealthy for sensitive group). The risk quotient (RQ) was calculated for average daily intake and average hourly intake of NO₂. RQ was found to be less than 1 (no potential health risk, lifetime and hourly) for all three years. However, increase in RQ value from 0.84 (2014) to 0.98 (2016) indicates increase in potential health risk. Hence, policy and measures should be adopted to reduce the potential health risk.

This study is very first of its kind for the area and hence can serve as reference study for future works. Further studies are required to assess air pollution in other seasons (summer, spring, autumn), impact of climatic condition and parameters on air quality. Also, for direct impact assessment number of cases attributed to air pollution needs to be investigated.

This study aims to add to the understanding of the interactive nature of brand love by using a multilayer perspective that incorporates individual, group and societal contexts.

The qualitative empirical study uses abductive reasoning. Its theories and conclusions are grounded in naturally occurring data from an online brand community. The approach revealed new interactive processes of brand love.

This study extends our understanding of the interactive nature of brand love by adopting a layered perspective incorporating micro- (individual), meso- (in-group), macro- (in-group vs out-group) and mega-layer (societal) social dynamics that complements the predominant focus on individual psychological processes. It challenges the linear, monodirectional trajectory approach to brand love, suggesting that brand love is in constant flux as individuals move across the layers in their identification with the brand.

This study provides data from one destination brand in Finland. Future studies could consider other types of brands and contexts in other countries and cultures.

This study shows brand managers that brand lovers can be divided into subgroups with distinct drivers of their love to which brand managers should attend.

To the best of the authors’ knowledge, this is the first attempt to describe the interactive nature of brand love through interactions between and within four layers of brand love. Furthermore, this study enhances our understanding of the contradictory aspects of brand love.