Search results

This paper aims to clarify the complex path of negative externalities in the sharing economy and proposes corresponding policy recommendations.

This paper aims to establish an analytical framework for the negative externalities of the sharing economy and to extract the main factors that produce negative externalities, and then, through qualitative comparative analysis method find out how these factors interact to form a negative externality.

Negative externalities in the sharing economy come from the joint effect of the sharing degree of the product or service and constraint mechanism, and the current main modes of the shared economy increase the possibility of negative externalities.

The paper proposes a complex path resulting from negative externalities in the shared economy.

Smart learning analytics (Smart LA) – i.e. the process of collecting, analyzing and interpreting data on how students learn – has great potentials to support opportunistic learning and offer better – and more personalized – learning experiences. The purpose of this paper is to provide an overview of the latest developments and features of Smart LA by reviewing relevant cases.

The paper studies several representative cases of Smart LA implementation, and highlights the key features of Smart LA. In addition, it discusses how instructors can use Smart LA to better understand the efforts their students make, and to improve learning experiences.

Ongoing research in Smart LA involves testing across various learning domains, learning sensors and LA platforms. Through the collection, analysis and visualization of learner data and performance, instructors and learners gain more accurate understandings of individual learning behavior and ways to effectively address learner needs. As a result, students can make better decisions when refining their study plans (either by themselves or in collaboration with others), and instructors obtain a convenient monitor of student progress. In summary, Smart LA promotes self-regulated and/or co-regulated learning by discovering opportunities for remediation, and by prescribing materials and pedagogy for remedial instruction.

Characteristically, Smart LA helps instructors give students effective and efficient learning experiences, by integrating the advanced learning analytics technology, fine-grained domain knowledge and locale-based information. This paper discusses notable cases illustrating the potential of Smart LA.

The purpose of this paper is to generalize the traditional risk evaluation methods and to specify a multi-level risk evaluation framework, in order to prepare customized risk evaluation and to enable effectively integrating the elements of risk evaluation.

A real case study of an electric motor manufacturing company is presented to illustrate the advantages of this new framework compared to the traditional and fuzzy failure mode and effect analysis (FMEA) approaches.

The essence of the proposed total risk evaluation framework (TREF) is its flexible approach that enables the effective integration of firms’ individual requirements by developing tailor-made organizational risk evaluation.

Increasing product/service complexity has led to increasingly complex yet unique organizational operations; as a result, their risk evaluation is a very challenging task. Distinct structures, characteristics and processes within and between organizations require a flexible yet robust approach of evaluating risks efficiently. Most recent risk evaluation approaches are considered to be inadequate due to the lack of flexibility and an inappropriate structure for addressing the unique organizational demands and contextual factors. To address this challenge effectively, taking a crucial step toward customization of risk evaluation.

Prior research has emphasised the importance of the early phases of construction projects, as well as the difficulties of procuring engineering services – especially due to the uncertainties. Despite that, studies on the public procurement of engineering services are scarce. Although scholars have shown that uncertainty may affect the choice of control modes, the level of uncertainty that characterises services is not addressed by the two task characteristics: knowledge of the transformation process and output measurability. The purpose is to investigate organisational control in public procurement of engineering services.

The existing control model was adjusted in this study by conceptually adding uncertainty as a third aspect to the two task characteristics. A single case study of the Swedish Transport Administration was used. The empirical data, comprising 14 interviews with managers from the client and engineering consulting companies, were analysed using flexible pattern matching and visual mapping approaches and then illustrated using the model.

The public client did not base its choice of control modes on uncertainty, but rather on the other two task characteristics. Consequently, the service providers argued that the chosen control modes reduced their creativity, increased their financial risks and caused unclear responsibilities. This study therefore shows that uncertainty is an important factor to consider in the choice of control modes, both from a theoretical perspective and from the service providers' point of view. The developed model may therefore be useful for researchers as well as practitioners.

This study is the first attempt to add uncertainty as a task characteristic when choosing control modes. The results contribute to the scarce control literature regarding the procurement of engineering services for construction projects and the procurement of other services with high uncertainty.

COVID-19 has changed the way we teach and learn, including service-learning (S-L). This study examines the impacts of the work-from-home (WFH) mode on the work performance and learning outcomes of student interns on an eight-week S-L internship programme, and the key factors in terms of its success.

A qualitative research methodology is adopted by interviewing nine student interns and four supervisors from three community partner organisations (CPOs) to understand their experiences of how the WFH mode has impacted intern work performance and learning outcomes. Thematic analysis is used for the data analysis.

The interns uncover a number of negative WFH impacts on the S-L internship, including ineffective communication and management practice, low work efficiency and quality, a lack of task variety and learning opportunities and distractions in the home environment. Furthermore, five critical factors for WFH success are also identified, including prior preparation, effective communication systems, personal motivators at work, the nature of the job in relation to it being suited to the WFH mode, and organisational support.

The study examines impacts on student work performance and learning outcomes in an S-L summer internship programme operating under the WFH mode as a result of the COVID-19 pandemic. Key success factors and practical recommendations have been developed for enhancing the future success of S-L internships operating under the WFH mode.

This paper aims to understand the trade transportation situation between China and Koreas, and to explore the possibility of establishing the surface transportation corridor between China and Koreas in the future. Moreover, the paper also intends to find out the mode choice behaviors of shippers, which can be used to analyze the substitute effects of the surface modes on the water one.

The paper first analyzes the Sino-Korean bilateral trade and the corresponding trade transportation between China and Koreas. Secondly, it presents the surface transportation network between China and Koreas, and analyzes the warming relations between the North and South. Finally, the modal split of trade transportation between China and Koreas is estimated by establishing a mode choice model based on a questionnaire survey.

With the increasingly stable political environment and the physical highway and railway connections, the surface transportation network would become possible. Moreover, the shippers need the multimodal transportation system between China and Koreas, and many shippers would select road or rail mode if a suitable road or rail network were available. Especially, between China and South Korea, the road, rail and water mode may be used evenly, while the road mode may play a more important role between China and North Korea. The surface modes would have a huge substitute effect on the water mode.

The existing literature conducted research mainly from the perspective of economy and geopolitics, while the topics of transportation between China and Koreas are rarely concerned. This paper intends to throw some light on the situation of the trade transportation between China and Koreas, consider the potential of relation improvement on the Korean Peninsula proactively and study the surface transportation issues between China and Koreas.

The purpose of this work is to optimize the monitoring of vibrations on dynamometric test rigs for railway brakes. This is a quite demanding application considering the continuous increase of performances of high-speed trains that involve higher testing specifications for brake pads and disks.

In this work, authors propose a mixed approach in which relatively simple finite element models are used to support the optimization of a diagnostic system that is used to monitor vibration levels and rotor-dynamical behavior of the machine. The model is calibrated with experimental data recorded on the same rig that must be identified and monitored. The whole process is optimized to not interfere with normal operations of the rig, using common inertial sensor and tools and are available as standard instrumentation for this kind of applications. So at the end all the calibration activities can be performed normally without interrupting the activities of the rig introducing additional costs due to system unavailability.

Proposed approach was able to identify in a very simple and fast way the vibrational behavior of the investigated rig, also giving precious information concerning the anisotropic behavior of supports and their damping. All these data are quite difficult to be found in technical literature because they are quite sensitive to assembly tolerances and to many other factors. Dynamometric test rigs are an important application widely diffused for both road and rail vehicles. Also proposed procedure can be easily extended and generalized to a wide value of machine with horizontal rotors.

Most of the studies in literature are referred to electrical motors or turbomachines operating with relatively slow transients and constant inertial properties. For investigated machines both these conditions are not verified, making the proposed application quite unusual and original with respect to current application. At the same time, there is a wide variety of special machines that are usually marginally covered by standard testing methodologies to which the proposed approach can be successfully extended.

This paper aims to propose a technique based on cognitive assessments to quantify identified operational risks from the perspective of container shipping or logistics system administrators. The results derived from the risk quantification could be used to prioritize risks as well as support the decision-making process in risk prevention and mitigation.

This paper identified container shipping operational risks (CSORs) from a logistics perspective. A multivariate risk evaluation mechanism by fuzzy rules Bayesian network (FRBN) was established. An improved two-level parameter set based on the failure mode and effects analysis (FMEA) was used to support the input extraction process. By feeding cognitive assessments into the model, the identified risks are evaluated based on their utility values. An illustration example and a sensitivity analysis were carried out to justify and validate the proposed model.

The highest positions in the prioritized list of CSORs in the case study are dominated by risks in the physical flow with the first three are piracy and terrorism, force majeure and port congestion. The results derived from the case study with the satisfaction of all pre-defined axioms proved the feasibility and illustrated the functionality of the proposed risk assessment and prioritization technique.

Controlling risk is irrefutably a significant issue of container shipping and logistics management because of the inconsistency of risk definitions and the involvement of uncertainties. The proposed risk evaluation mechanism and the identified list of CSORs could be beneficial in system management, decision-making and reliability performance.