Case Study Research Articles

Competence-based trainings for psychological treatments – A transtheoretical perspective

Background Although in most countries psychotherapy trainings focus on one treatment orientation, such an approach is associated with systematic shortcomings. The priorities from teaching one theoretical framework should be moved to a more rigorous orientation in science and evidence-based practice, and to the needs of patients, even if strategies of different theoretical approaches need to be combined. Method We discuss whether competence-based trainings in psychological treatments offer a better framework to facilitate the progress of psychological treatments to a professional academic discipline with transtheoretical exchange, and we provide an example of a transtheoretical education in the basic competences of psychological treatments. A transtheoretical education program requires an umbrella model for case formulation and a transtheoretical definition of intervention goals. Results We provide an adaptation of the traditional model distinguishing vulnerability/resilience, exacerbation, and maintenance of clinical problems for case conceptualization. Dynamic network models offer a further perspective for developing modern, transtheoretical case formulations. Treatment methods should be better classified according to their transtheoretical goals, which offers opportunities to better compare or combine them. We report a case example of how to transform a general competence-based approach in the training of psychological treatments in the academic education system, which found exceptional acceptance from participating students. Conclusion Thus, a rigorous competence-based approach to training early clinicians in applying psychological treatments helps to bridge the artificial divide between psychotherapeutic traditions. It also supports the evolution of psychological treatments into an academically robust and highly professional, integrative discipline.

Negotiations of heritage in and around locally protected forests in Inhambane province, southern Mozambique

ABSTRACT In this paper, I explore negotiations of heritage in heritage forests from three case studies in southern Mozambique using oral history, field walking, video documentation and conversations. I argue that at local level there are processes of negotiation, authorisation, and legitimacy of heritage in forests. Such local forms of heritage negotiation and heritage discourse are authoritative and need to be recognised in both the planning of heritage conservation, and also in nature conservation. This recognition can strengthen local custodians to safeguard forest patches as locally protected areas, and opening room for heritage practitioners to be engaged by local people in the process of cultural heritage management.

Analysis of Business Intelligence Technology in the Big Data Era A Case Study of Alibaba Group

In the age of big data, business intelligence technology is pivotal in enhancing user experiences and driving innovation across industries. This paper focuses on Alibaba Group, a trailblazer in e-commerce, to examine the transformative role of business intelligence. This paper investigates Alibabas cutting-edge application of business intelligence technology, focusing on intelligent recommendation systems, personalized marketing strategies, and efficient supply chain management. The recommendation system harnesses data analysis to provide tailored product suggestions, boosting user satisfaction and sales. Data-driven marketing strategies enable Alibaba to create personalized promotions and coupons, enhancing user experiences and building loyalty. Intelligent supply chain management employs real-time monitoring, optimized transportation, and data-driven decisions to ensure timely deliveries and cost efficiency. A case study of Alibaba's "Singles Day Global Shopping Festival" illustrates how business intelligence technology creates a dynamic, data-powered shopping event. Every decision during this event is informed by real-time analysis and AI insights, enabling swift responses to evolving consumer needs. In summary, business intelligence, a driving force in the age of big data, is at the heart of Alibabas success. Alibaba has tapped the potential of business intelligence by enhancing the user experience and facilitating data-driven decision-making.

Deep learning with TabNet: rapid coal ash content estimation via X-ray fluorescence

ABSTRACT As a paramount index of coal quality, the quick and accurate prediction of ash content bears substantial significance for the coal preparation plant. In this study, an innovative approach that integrates SHapley Additive exPlanations with a deep learning model Tabular Networks has been introduced, which efficiently predict the ash content by employing the compositional data obtained from rapid elemental analysis. Pictures of the relationship between elemental and ash content reveal a significant correlation. To further elucidate this relationship, Polynomial regression, Random Forest regression, and eXtreme Gradient Boosting are used as comparison prediction models to verify the accuracy of the deep learning model. The R2 for TabNet, Poly, XGBoost, and RFR are 0.9867, 0.9755, 0.9797, and 0.9714, respectively. The optimization is continued based on SHAP averages, and the best combination of elemental feature contributions obtained is used to continue the prediction of the experiments. The experimental results show that the TabNet model has better predictive performance than other models (RMSE, MAE, and R2 are 1.5126, 1.0953, and 0.9903). An examination and exploration of the contributions and roles of elements to the ash prediction model has been conducted. The case study presented in this paper illustrates that the interpreted deep learning model holds promising prospects for industrial ash fraction prediction.

Defect modelling and correlation mapping for bridge inspection

PurposeThis paper covers the development of a novel defect model for concrete highway bridges. The proposed defect model is intended to facilitate the identification of bridge’s condition information (i.e. defects), improve the efficiency and accuracy of bridge inspections by supporting practitioners and even machines with digitalised expert knowledge, and ultimately automate the process.Design/methodology/approachThe research design consists of three major phases so as to (1) categorise common defect with regard to physical entities (i.e. bridge element), (2) establish internal relationships among those defects and (3) relate defects to their properties and potential causes. A mixed-method research approach, which includes a comprehensive literature review, focus groups and case studies, was employed to develop and validate the proposed defect model.FindingsThe data collected through the literature and focus groups were analysed and knowledge were extracted to form the novel defect model. The defect model was then validated and further calibrated through case study. Inspection reports of nearly 300 bridges in China were collected and analysed. The study uncovered the relationships between defects and a variety of inspection-related elements and represented in the form of an accessible, digitalised and user-friendly knowledge model.Originality/valueThe contribution of this paper is the development of a defect model that can assist inexperienced practitioners and even machines in the near future to conduct inspection tasks. For one, the proposed defect model can standardise the data collection process of bridge inspection, including the identification of defects and documentation of their vital properties, paving the path for the automation in subsequent stages (e.g. condition evaluation). For another, by retrieving rich experience and expert knowledge which have long been reserved and inherited in the industrial sector, the inspection efficiency and accuracy can be considerably improved.

PFoods: selecting a segment for a sustainable product

Learning outcomes After working on the assignment questions, the learners can achieve the following learning outcomes: understand the buying behavior towards sustainable products in the context of mindful consumption and product characteristics, appraise the market segmentation and positioning strategy of a sustainable business, understand the application of 5C’s framework for a sustainable business and critically evaluate a new sustainable business’s challenges in the emerging business environment. Case overview/synopsis Dr Joe Fenn, founder and director of PFoods, with extensive experience in the pharma industry overseas, observed a decline in the consumption of traditional dairy foods. Alternative plant foods come as a savior to people who are lactose intolerant and offer a host of health benefits with low environmental impact. Riding on the waves of veganism and sustainable foods, he saw an opportunity in India. PFoods developed and launched two products, namely, Just Plants (plant-based milk alternative) and Plotein (plant-based protein alternative), in collaboration with scientists at the Indian Institute of Science, a premier scientific institution in India, and PMEDS (PreEmptive Meds), a US-based nutraceutical Company. PFoods launched and pilot-tested Just Plant, a dairy alternative substitute for milk in select reputed organizations in Bangalore. The upcoming challenges for Fenn would be to select the right segment, educate the market and position the product that would resonate well with the target customers. Complexity academic level The case study suits undergraduate and graduate courses such as marketing management, sustainable marketing and sustainable business. The case study can also be used in entrepreneurship management and entrepreneurial marketing courses to introduce the challenges of a sustainable startup. The case study highlights the marketing challenges faced by the disruptive and growing plant-based foods or alternative dairy industry in emerging markets. Supplementary materials Teaching notes are available for educators only. Subject code CSS 8: Marketing.

The Short-Term Price Elasticity, Temperature Elasticity, and Wind Speed Elasticity of Electricity: A Case Study from Norway

Energy production using hydropower has a 150-year history in Norway. High mountains, lots of rain, and a well-developed technology laid the foundation for low and stable electricity prices. The Norwegian electricity market is unique and different from any other country. Nearly all electricity produced (98.3 percent) comes from renewable energy sources and 75 percent of the energy used for heating is electricity. From autumn 2020, major changes have been observed in the electricity market in Norway. In 2021, Norway opened two transmission cables, one to Germany and one to England. Both cables have a capacity of 1400 MW. The average price per MWh was NOK 263 in southern Norway in the period 2013–2020, which more than quadrupled to NOK 1192 per MWh in the period 2021–2023. We have investigated how the market reacted to the large price increase. We found that price elasticity is low even when the price is very high. It is the temperature that controls the consumption. When it is cold—below zero degrees Celcius—the temperature elasticity is close to zero; the temperature elasticity is not constant. When the temperature is above zero, the temperature elasticity is about −0.7. Price variations or changes in wind speed only lead to minor adjustments in electricity consumption. It is the variations in temperature that result in the observable fluctuations in electricity consumption. Since Norway exports electricity to Sweden, Denmark, Finland, Germany, the Netherlands, and England, knowledge of the Norwegian electricity market is relevant for many market participants. The Norwegian electricity market differs from those in other countries. Therefore, there is a risk that conclusions drawn about the Norwegian electricity market based on research conducted in other countries may be incorrect or inaccurate. Our contribution with this case study is to deepen the knowledge of how the electricity market in Norway operates.

Flextory: Flexible Software Factory of IoT Data Consumers

The success of the Internet of Things (IoT) has driven the development, among others, of many different software architectures for producing, processing, and analyzing heterogeneous data. In many cases, IoT applications share common features, such as the use of a platform or middleware, also known as message broker, that collects and manages data traffic between endpoints. However, in general, data processing is very dependent on the case study (sensors that send temperature data, drones that send images, etc.). Thus, the applications responsible for receiving and processing data, which we call consumers, have to be built ad hoc, since some of their elements have to be specially configured to solve specific needs of the case study. This paper presents Flextory, a software factory tool to make it easier for IoT developers to automatically construct configurable consumer applications, which we call FLEX-consumers. Flextory guides developers through the process of generating Java consumers by selecting some desired features such as, for instance, the particular communication protocol to be used. This way, the developer only has to concentrate on designing the algorithm to process the data. In short, the use of Flextory will result in consumer applications with configurable behavior, namely FLEX-consumers, that can connect to a messaging server (for example RabbitMQ) and process the received messages.

Using augmented reality in molecular case studies to enhance biomolecular structure-function explorations in undergraduate classrooms.

Molecular case studies (MCSs) are open educational resources that use a storytelling approach to engage students in biomolecular structure-function explorations, at the interface of biology and chemistry. Although MCSs are developed for a particular target audience with specific learning goals, they are suitable for implementation in multiple disciplinary course contexts. Detailed teaching notes included in the case study help instructors plan and prepare for their implementation in diverse contexts. A newly developed MCS was simultaneously implemented in a biochemistry and a molecular parasitology course at two different institutions. Instructors participating in this cross-institutional and multidisciplinary implementation collaboratively identified the need for quick and effective ways to bridge the gap between the MCS authors' vision and the implementing instructor's interpretation of the case-related molecular structure-function discussions. Augmented reality (AR) is an interactive and engaging experience that has been used effectively in teaching molecular sciences. Its accessibility and ease-of-use with smart devices (e.g., phones and tablets) make it an attractive option for expediting and improving both instructor preparation and classroom implementation of MCSs. In this work, we report the incorporation of ready-to-use AR objects as checkpoints in the MCS. Interacting with these AR objects facilitated instructor preparation, reduced students' cognitive load, and provided clear expectations for their learning. Based on our classroom observations, we propose that the incorporation of AR in MCSs can facilitate its successful implementation, improve the classroom experience for educators and students, and make MCSs more broadly accessible in diverse curricular settings.

Survival of the fittest

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings This paper identified that the mindset of the leader plays a crucial role in determine whether the organization can manage and adapt to change effectively. Originality/value The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

How to Measure Polymer Degradation? An Analysis of Authors' Choices When Calculating the Carbonyl Index.

The carbonyl index aims to measure the degradation level and is used in plastic degradation research as a proxy for the general degradation level of collected plastic pieces. According to the choices for carbonyl index calculation, comparison using this index is prevented and must be unveiled by the authors, which does not always happen. In order to study the proper usage of the carbonyl index, regarding the choice of the reference band and the usage of the band intensity or the absorption area, we systematically reviewed the methodologies used for polypropylene as a case study. Based on 95 studies gathered from 2000 to 2024, two main methods were used to determine the carbonyl index: the ratio between the carbonyl band area and the reference band area (33.68%) and the ratio between the highest intensity of the carbonyl band and the reference band (66.31%). The reference band of choice and the type of calculation method produce different carbonyl index values for the same spectra and mean different information, preventing comparison among works with different calculations.

Do we really need machine learning interatomic potentials for modeling amorphous metal oxides? Case study on amorphous alumina by recycling an existing ab initio database

Abstract In this study, we critically evaluate the performance of various interatomic potentials/force fields against a benchmark ab initio database for bulk amorphous alumina. The interatomic potentials tested in this work include all major fixed charge and variable charge models developed to date for alumina. Additionally, we introduce a novel machine learning interatomic potential constructed using the NequIP framework based on graph neural networks. Our findings reveal that the fixed-charge potential developed by Matsui and coworkers offers the most optimal balance between computational efficiency and agreement with ab initio data for stoichiometric alumina. Such balance cannot be provided by machine learning potentials when comparing performance with Matsui potential on the same computing infrastructure using a single Graphical Processing Unit. For non-stoichiometric alumina, the variable charge potentials, in particular ReaxFF, exhibit an impressive concordance with density functional theory calculations. However, our NequIP potentials trained on a small fraction of the ab initio database easily surpass ReaxFF in terms of both accuracy and computational performance. This is achieved without large overhead in terms of potential fitting and fine-tuning, often associated with the classical potential development process as well as training of standard deep neural network potentials, thus advocating for the use of data-efficient machine learning potentials like NequIP for complex cases of non-stoichiometric amorphous oxides.

Tackling the social marketing formative research bottleneck: comparative analysis of the complementary nature of community-generated personas and focus groups

Purpose This study aims to understand the utility of personas and illustrate, through a case study, how a persona-building exercise in a Community Based Prevention Marketing (CBPM) training of community leaders elicited important insights that complemented findings from ongoing formative research on vaccine hesitancy in the Hispanic/Latino population in the USA during COVID-19 pandemic. Design/methodology/approach An exploratory concurrent parallel qualitative study design compared three personas created by community-based organization members (n = 37) to transcripts from five formative research focus groups (n = 30) from the same project. All participants in this study were recruited by the National COVID-19 Resiliency Network as part of their capacity-building and formative research activities. Grounded theory guided the content analysis. Findings This study found personas and focus groups to be complementary. A high degree of co-occurrence was observed when investigating the uptake of the COVID-19 vaccine under the categories of barriers, culture and communication. Between the two methods, the authors found strong associations between fear, disruption to the value system, work-related barriers, inaccessibility to health care and information sources and misinformation. Areas of divergence were negligible. Research limitations/implications While personas provided background information about the population and sharing “how” to reach the priority population, focus groups provided the “why” behind the behavior, followed by “how”. Practical implications A community-driven persona-building process built on cultural community knowledge and existing data can build community capacity, provide rich information to assist in the creation of tailored messages, strategies and overall interventions during a public health crisis and provide user-centered, evidence-based information about a priority population while researchers and practitioners wait on the results from formative research. Originality/value This case study provided a unique opportunity to analyze the complementary effectiveness of two methods acting in tandem to understand the priority population: stakeholder-informed persona-building and participant-informed focus group interviews. Understanding their complementary nature addresses a time gap that often exists between researchers and practitioners during times of crises and builds on recommendations associated with bringing rigor into practice, promoting academic contribution to real-world issues and building collaborative partnerships. Finally, it supports the utility of a nimble tool that improves social marketers’ ability to know more about their audience for intervention design when time is of the essence and formative research is ongoing.

A study of the decentralised administrative arrangements between the central and local governments in Bangladesh during the COVID-19 pandemic crisis

PurposeDecentralised administrative arrangements and the active function of local government organisations are essential to tackle crisis effectively. Using Bangladesh as a case study, this paper examines the central and local government administrative arrangements during COVID-19 pandemic.Design/methodology/approachThis study applies qualitative content analysis and interviews to explore the local government’s role in Bangladesh’s COVID-19 management by interviews of 18 participants including government officials, experts, non-government organisations (NGOs) representatives, and the general public. This paper also analysed academic papers, policy documents and other publicly available documents, including newspaper reports.FindingsThe Constitution of Bangladesh intensified the active participation of local government in each administrative unit through decentralised administrative management. This paper however reveals that the administrative arrangement during the COVID-19 pandemic in Bangladesh was primarily a centrally led system. The local government was not sufficiently involved, nor had it integrated into the planning and coordination process. This indicated the absence of active decentralised administration.Originality/valueThis study fills the research gap of the administrative pattern and local relations in COVID-19 management by exploring the local government’s role during the catastrophic situation and highlights the importance of decentralised administrative actions in managing the crisis.

Problem-based learning and the integration of sustainable development goals

PurposeThis study explores how problem-based learning (PBL) programs can address Sustainable Development Goals (SDGs) via the higher education (HE) curriculum, teaching materials and relevant assessments, supporting learning at scale for HE institutions.Design/methodology/approachEmploying SDGs and their indicators as the coding framework, our two-phase study evaluates the curriculum and teaching materials of seven PBL programs at a leading higher education institution (HEI). The first phase involved a content analysis to assess the degree of sustainability integration in 156 relevant courses. The second phase applied a semi-automated mapping protocol to analyze learning and teaching materials in 120 relevant courses.FindingsThe school aligns with 17 SDGs (100%), covering 94 indicators (55.62%). On average, each program within the school addresses over ten of these goals and incorporates more than 24 associated indicators. However, the study reveals an imbalance in the incorporation of SDGs, with some goals not yet deeply and comprehensively embedded in the curriculum. While there is a substantial focus on sustainability theories, the practical implications of SDGs in emerging countries, particularly through case studies and assessments, require significant enhancement.Practical implicationsMapping SDGs allows HEIs to identify strengths and gaps in SDG integration, thereby improving the PBL approach to enhance student work readiness in sustainability-focused careers.Originality/valueThrough the lens of transformative learning theory, this study provides evidence of SDG integration into PBL curricula. It highlights a mapping methodology that enables HEIs to evaluate their sustainability readiness in curriculum, teaching materials and relevant assessments.

COVID-19 Mitigation in a K-12 School Setting: A Case Study of Avenues: The World School in New York City.

In this case study, we describe a well-resourced private school in New York City that implemented COVID-19 mitigation measures based on public health expert guidance and the lessons learned from this process. Avenues opened in New York City in 2012 and has since expanded, becoming Avenues: The World School, with campuses in São Paulo, Brazil; Shenzhen, China; the Silicon Valley, California; and online. It offers education at 16 grade levels: 2 early learning years, followed by a prekindergarten through grade 12. We describe the mitigation measures that Avenues implemented on its New York campus. We compare COVID-19 case prevalence at the school with COVID-19 case positivity in New York City, as reported by the New York State Department of Health. We also compare the school's indoor air quality to ambient indoor air quality measures reported in the literature. The school's mitigation measures successfully reduced the prevalence of COVID-19 among its students, staff, and faculty. The school also established a consistently high level of indoor air quality safety through various ventilation mechanisms, designed to reduce common indoor air pollutants. The school received positive parent and community feedback on the policies and procedures it established, with many parents commenting on the high level of trust and quality of communication established by the school. The successful reopening provides useful data for school closure and reopening standards to prepare for future pandemic and epidemic events.

Sustainability in English Language Teaching: Strategies for Empowering Students to Achieve the Sustainable Development Goals

This article systematically reviews the studies integrating sustainability into English Language Teaching (ELT), underlining the critical role of education in addressing global environmental challenges through language learning. Through an extensive literature review encompassing empirical studies, theoretical articles, and case studies from 2013 to 2023, we evaluate the methodologies for incorporating sustainability in ELT, identify the challenges faced by educators, and propose practical solutions. Key findings demonstrate various effective approaches, such as interdisciplinary curriculum designs, innovative classroom activities, specialized teacher training, and novel assessment methods, which enhance language proficiency and significantly raise students’ language-learning awareness. Despite challenges such as limited resources and alignment issues between sustainability topics and language-learning objectives, strategies like developing open educational resources and professional development programs have shown promise in overcoming these obstacles. The review underscores the importance of embedding sustainability in ELT to foster informed, responsible global citizens and highlights future research directions to further this aim. It calls for continued innovation, research, and policy support to fully realize the potential of ELT in contributing to a more sustainable future.

The Relationship Between Preparedness for Caregiving and Spiritual Well-Being in the Carers of Stroke Patients: A Case Study in Türkiye.

This study was conducted to determine the relationship between preparedness for caregiving and spiritual well-being in the carers of stroke patients. This descriptive and cross-sectional study was conducted with 130 primary carers of patients hospitalized with the diagnosis of stroke at the neurology clinic of a hospital. It was determined that the participants had moderate levels of preparedness for caregiving, they had high levels of spiritual well-being, and there was a positive significant relationship between these two variables. According to the regression analysis results, the spiritual well-being level of the participants was a predictor of their preparedness for caregiving (B: 0.144, p < 0.001). The results of this study demonstrated that the spiritual well-being of the carers of stroke patients is important in increasing preparedness for caregiving. In this context, to ensure that the carers of all stroke patients feel prepared for the caregiving process, it is recommended to evaluate their preparedness levels, support them in their preparation for their caregiving roles, and identify their spiritual needs.

An FEM framework for modeling forces between NdFeB magnets and HTS bulks

Purpose This paper aims to introduce an alternative for modeling levitation forces between NdFeB magnets and bulks of high-temperature superconductors (HTS). The presented approach should be evaluated through two different formulations and compared with experimental results. Design/methodology/approach The T-A and H-ϕ formulations are among the most efficient approaches for modeling superconducting materials. COMSOL Multiphysics was used to apply them to magnetic levitation models and predict the forces involved.The permanent magnet movement is modeled by combining moving meshes and magnetic field identity pairs in both 2D and 3D studies. Findings It is shown that it is possible to use the homogenization technique for the T-A formulation in 3D models combined with mixed formulation boundaries and moving meshes to simulate the whole device’s geometry. Research limitations/implications The case studies are limited to the formulations’ implementation and a brief assessment regarding degrees of freedom. The intent is to make the simulation straightforward rather than establish a benchmark. Originality/value The H-ϕ formulation considers the HTS bulk domain as isotropic, whereas the T-A formulation homogenization approach treats it as anisotropic. The originality of the paper lies in contrasting these different modeling approaches while incorporating the external magnetic field movement by means of the Lagrangian–Eulerian method.

Globalization of Automobile Supply Chain: A Case Study Based on BYD’s Globalization strategy

With the development of global trade and the acceleration of economic globalization, it has become normal for automobile manufacturers to expand their production and sales to transnational markets. BYD is famous for its innovation in hybrid and pure electric vehicles. The company’s example provides a useful reference for studying the application and landing of new energy vehicle technology on a global scale. Through the analysis of BYD case, we can understand the role and influence of new energy technology in the globalization of automobile supply chain, which is of positive significance to promoting sustainable transportation and reducing carbon emissions. The globalization of automobile supply chain not only involves market demand and technological innovation, but also is influenced by national and regional economic development and policy support. Through the case study of BYD, we can analyze the role of national policies and economic environment in the globalization of automobile supply chain, and provide reference for formulating relevant policies and strategies.