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Writing a thesis is a difficult endeavor for undergraduate students, especially in management careers, due to the highly practical approach of the discipline. Students often find difficult to understand and apply research methods in concrete research projects, so a proper set of teaching-learning strategies is critical. This study aimed to examine the effect of these strategies on the academic performance of students in two research seminars in an undergraduate management program in Peru.

The research adopted a mixed approach. The quantitative component included a survey of 249 students in both seminars, while the qualitative one involved only some of the students using three focus groups. The corresponding data analysis included stepwise linear regression models and content analysis.

The study found that a clear course structure, adequate research methods literature, good advisor–student communication and goal planning and achievement were the key determinants of the students' final grades.

This research fills a gap in previous studies on the subject by including a broader set of strategies and by statistically estimating the strategies' effects on academic performance.

While a layman's theory supports the view that “a smile goes a long way,” the authors argue that “not all smiles are created equal” in the sense that the server's smiles need to be genuine and authentic, in particular when the customer has a relationship with the server. The purpose of this study is to test such hypotheses.

A 2 (display authenticity: authentic vs inauthentic) by 2 (state of service relationship: existing service relationship vs no service relationship) experiment was used to test the proposed hypotheses. In total, 768 surveys were distributed and 278 responses were received. Two-way ANOVA analyses were deployed.

Data collected from customers reveal that authentic smiles have a direct positive impact on customers' willingness to tip. Further, such an effect is even stronger when the customer has an existing relationship with the server.

Servers should receive appropriate training regarding “deep acting” techniques. The most important limitation is the use of written scenarios as stimuli.

Showing an authentic smile can be an effective tip-collecting strategy. Employees who are in contact with guests and customers should not only be instructed to provide service with a smile but should also be advised to make that smile appear authentic. Therefore, appropriate training of frontline employees, regarding authenticity of smiles, could be beneficial both for the company and for the employees themselves.

No research has been done investigating whether authentic smiles generate larger tips and if so, whether any boundary conditions exist for such effects.

Plastic pollution is a widespread problem around the world. However, the problem is more severe and ever increasing in developing countries. The literature suggests that the majority of the work and the solutions that have been proposed to address plastic littering have been undertaken in developed countries. Thus, there is a need to explore the problem in developing countries to better understand the issue and to develop context-specific solutions. We explored the norms perspective using ‘The Focus Theory of Normative Conduct’, individual ethical position and place attachment factors. Interviews were conducted in Pakistan with 16 people who were recently at a beach at which there was a large amount of plastic litter. Results showed that people are influenced by the pro-littering social norms of their friends and neighbours. However, people with strong anti-littering personal norms are not influenced by pro-littering social norms. We also found that people have varying moral position, and their lack of attachment with the public place also influences their littering behaviour. Moreover, people believe that other people litter due to lack of education and awareness, lack of garbage bins and a general level of carelessness. Future research needs to focus on activating an individual's idealist moral position and an individuals' attachment with the place to enhance the activation of anti-littering personal norms which will help reduce littering behaviour. Further still, government needs to set up campaigns at public places to create awareness among people about the impact of littering, and government also needs to improve the effectiveness and efficiency of waste management. Businesses can also play a role by providing waste bins which may be used as a source of promoting their support for reducing litter.

Considering the complexity of the airport industry service palette, it is important to identify which air travel factors are distractors and which factors are enhancers of passenger satisfaction. Building on Herzberg's two-factor motivation theory, this study aims to explore most frequently mentioned attributes of airport service quality and distinguish key drivers for passenger satisfaction/dissatisfaction in the airport context.

A content analysis of 1,095 traveler comments posted between 2010 and 2013 on an airport review web site was performed in order to identify satisfiers/dissatisfiers. The web spider randomly selected consumer comments related to 33 popular destinations.

The study results indicated key satisfiers in the airport context such as cleanliness and pleasant environment to spend time in. On the other side, security-check, confusing signage and poor dining offer are recognized as major dissatisfiers in the airport setting.

The study findings provide insight on predominant satisfiers, dissastisfiers and performance factors of airport service quality from passengers' perspectives. Airport management teams may use the study results to renovate airport facility and improve service quality.

To the best of the authors' knowledge, this study is the first to utilize the visual data mining techniques in examining airport users' experience. Visualization produced summaries of qualitative comments in the form of tag clouds, word networks, and word tree images that help discover the most emerging themes of travelers' complaints and compliments.

Concerning trends in graduate education, such as high attrition and underdeveloped skills, drive toward a new doctoral education approach. This paper aims to describe and propose a transformative doctoral education model (TDEM), incorporating elements that potentially address these challenges and expand the current practice. The model envisions discipline-specific knowledge coupled with a broader interdisciplinary perspective and addresses the transferable skills necessary to successfully navigate an ever-changing workforce and global landscape. The overarching goal of TDEM is to transform the doctoral student into a multi-dimensional and adaptive scholar, so the students of today can effectively and meaningfully solve the problems of tomorrow.

The foundation of TDEM is transformative learning theory, supporting the notion learner transformation occurs throughout the doctoral educational experience.

Current global doctoral education models and literature were reviewed. These findings informed the new TDEM.

Designed as a customizable framework for learner-centered doctoral education, TDEM promotes a mentor network on and off-campus, interdisciplinarity and agile career scope preparedness.

Within the TDEM framework, doctoral students develop valuable knowledge and transferable skills. These developments increase doctoral student career adaptability and preparedness, as well as enables graduates to appropriately respond to global and societal complex problems.

This proposed doctoral education framework was formulated through a review of the literature and experiences with curricular design and pedagogical practices at a research-intensive university’s teaching and learning center. TDEM answers the call to develop frameworks that address issues in doctoral education and present a flexible and more personalized training. TDEM encourages doctoral student transformation into adaptive, forward-thinking scholars and thriving in an ever-changing workforce.

Investigates the influence of land pattern pad designs and solder volume on reliability of solder joint attachments for surface mounted passive chip devices. All boards were thermal cycled and periodically tested to induce a damage mechanism in less time than in real service use. The difference in the number of failures for different pad designs and for different stencil thicknesses was recorded. Failure analysis with respect to stencil thickness and position of resistor on board is studied and a new approach for the comparison of resistor reliability by using Weibull distribution is shown. The time period for this testing was kept to a minimum by accelerated ageing of tested samples. This test aims to predict the onset of the wear‐out period under the normal conditions of service. The results from measurements during thermal cycling are also given and the basic rules for practical application are summarised.

The majority of Hong Kong filmmakers have pursued co-production with China filmmakers for having the Mainland market at the expense of local styles and sensitivities. To many critics, the two-part series of Ip Man and Ip Man II provide a paradigmatic case of film co-production that sell the tricks of Chinese kung fu, regurgitating the overblown Chinese nationalism against Japanese and kwai-lo. The purpose of this study is to rectify such observation of the Ip Man series.

The authors read the series deconstructively as a postcolonial text in which Hong Kong identity is inscribed in the negotiated space in between different versions of Chinese nationalism.

The analysis points to the varying subversive features in the series from which Hong Kong’s colonial experiences are tacitly displayed, endorsed and rewritten into the Chinese nationalistic discourse whose dominance is questioned, if not debased.

This paper advances new research insights into the postcolonial reinvention of kung fu film and, by implication, the Hong Kong cinema in general.

This paper aims to study the characteristics and evolution rules of tagging knowledge network for users with different activity levels in question-and-answer (Q&A) community represented by Zhihu.

A random sample of issue tag data generated by topics in the Zhihu network environment is selected. By defining user quality and selecting the top 20% and bottom 20% of users to focus on, i.e. top users and bot users, the authors apply time slicing for both types of data to construct label knowledge networks, use Q-Q diagrams and ARIMA models to analyze network indicators and introduce the theory and methods of network motif.

This study shows that when the power index of degree distribution is less than or equal to 3.1, the ARIMA model with rank index of label network has a higher fitting degree. With the development of the community, the correlation between tags in the tagging knowledge network is very weak.

It is not comprehensive and sufficient to classify users only according to their activity levels. And traditional statistical analysis is not applicable to large data sets. In the follow-up work, the authors will further explore the characteristics of the network at a larger scale and longer timescale and consider adding more node features, including some edge features. Then, users are statistically classified according to the attributes of nodes and edges to construct complex networks, and algorithms such as machine learning and deep learning are used to calculate large-scale data sets to deeply study the evolution of knowledge networks.

This paper uses the real data of the Zhihu community to divide users according to user activity and combines the theoretical methods of statistical testing, time series and network motifs to carry out the time series evolution of the knowledge network of the Q&A community. And these research methods provide other network problems with some new ideas. Research has found that user activity has a certain impact on the evolution of the tagging network. The tagging network followed by users with high activity level tends to be stable, and the tagging network followed by users with low activity level gradually fluctuates.

Research has found that user activity has a certain impact on the evolution of the tagging network. The tagging network followed by users with high activity level tends to be stable, and the tagging network followed by users with low activity level gradually fluctuates. For the community, understanding the formation mechanism of its network structure and key nodes in the network is conducive to improving the knowledge system of the content, finding user behavior preferences and improving user experience. Future research work will focus on identifying outbreak points from a large number of topics, predicting topical trends and conducting timely public opinion guidance and control.

In terms of data selection, the user quality is defined; the Zhihu tags are divided into two categories for time slicing; and network indicators and network motifs are compared and analyzed. In addition, statistical tests, time series analysis and network modality theory are used to analyze the tags.

The increasing frequency and intensity of the extreme weather events could cause devastating consequences in tourism. Climate change–related extreme weather events and their relation to tourism is an emerging field for education and research. The purpose of this study is to categorize the impact of climate change on tourist destinations with regard to extreme weather-related risks in outdoor recreation and tourism. Managerial implications for policymakers and stakeholders are discussed.

To outline the risks from climate change associated with tourism, this study uses the Prisma analysis for identification, screening, checking for eligibility and finding relevant literature for further categorization.

Based on a thoroughly examination of relevant literature, risks and threats posed by climate change could be categorized into following four areas: reduced experiential value in outdoor winter recreation; reduced value in beach scenery and comfort; land degradation and reduced biodiversity; and reduced value in personal safety and comfort in tourism. It also focuses on the significance of using big data applications in catastrophic disaster management and risk reduction. Recommendations with technology and data analytics to continuously improve the disaster management process in tourism education are provided based on findings of this study.

Primary contributions of this study include the following: providing a summarized overview of the risks associated with climate change in terms of tourist experiential value for educational implications; and revealing the role of data analytics in disaster management in the context of tourism and climate change for tourism education.