Empirical Case Study Research Articles

A survival analysis with random parameter approach for assessing temporal instability in treatment effect

Before-after analysis methods in traffic safety often aggregate traffic crashes into crash frequencies using relatively long aggregation time periods, such as a year. The implicit assumption is that the treatment effect is temporally stable over the aggregation period. However, certain “treatments”, such as the COVID-19 pandemic, may result in fast-evolving changes to road safety. By aggregating individual crashes, it is difficult to investigate the temporal characteristics of crashes and capture the potential temporal instability in treatment effect at detailed temporal levels, such as within a year. Therefore, this study exploits the disaggregated nature of crashes and proposes a survival analysis with random parameter (SARP) before-after analysis approach that can flexibly accommodate the temporal instability in treatment effect at various temporal levels. To validate and test the proposed approach, a statistical simulation study and an empirical case study that investigates the safety impact of COVID-19 lockdown in Manhattan, New York, are conducted. The statistical simulation study shows that the SARP method can unbiasedly estimate different patterns of temporally instable treatment effect at various temporal levels. The estimated monthly crash modification factors from the case study display an increasing trend after the largest decrease in the first month after the lockdown, which implies that traffic safety conditions are gradually returning to normal and provides evidence of temporal instability in treatment effect. The proposed SARP approach is promising to investigate the evolving safety impact of emerging technologies in transportation, such as the deployment of connected and autonomous vehicles.

Co-design workshops for cultural landscape planning

In the last twenty years, citizen participation has become a formal requirement in landscape and heritage planning all over Europe. The European Landscape Convention (2000), in particular, encourages public participation in defining landscape heritage values and identifying strategies for its protection, management and planning. However, despite the development of various participatory methods, citizen participation in landscape planning remains rarely applied in practice. With an empirical case study, the research presented in this article tries to bridge the gap between theory and practice, evaluating a methodology in which citizens, stakeholders, planners, and heritage experts are invited to co-design a spatial strategy for local cultural landscape valorisation.

Unravelling the impact of courtyard geometry on cooling energy consumption in buildings

At present, the energy used for air conditioning in buildings in urban areas accounts for over 36% of total global energy consumption. Energy efficiency has become a critical factor in the urban planning of cities worldwide. Courtyard buildings in hot cities are a prime example of the approach used in traditional vernacular architecture to mitigate the effects of extreme weather. However, given the challenge of guaranteeing accurate modelling of microclimates within these courtyards, their impact on energy demand in buildings has been routinely overlooked by energy certification tools.This work examines three empirical case studies selected in Seville city (Spain), where temperatures during the summer months are extreme. The case studies selected display distinct geometric variations, and the primary objective of the research is to assess the influence of this geometric factor on the cooling energy demand of the building indoors. To achieve this, a validated methodology combining experimental and numerical data was implemented to evaluate the energy performance of buildings with courtyards. Different simulations were conducted to detect the impact of individual courtyard features. The results show a reduction in cooling demand of 8–18% depending on the geometry of the courtyard. Analysis was also carried out on the influence of the floor level and the orientation of adjacent rooms, revealing differences of 15% and 22%, respectively. The main conclusion of the research is that the use of courtyards as functional devices, paying particular attention to their geometry, is a key factor in the cooling energy demand of buildings.

Evaluate the drivers for digital transformation in higher education institutions in the era of industry 4.0 based on decision-making method

The digitalization of higher education (HE) institutions and relevant issues have attracted the attention of many educational stakeholders. ICT has become a subject of high importance in every context, particularly in the workplace; thus, a principal goal for universities and schools is to prepare future professionals capable of dealing with problems and searching for effective solutions by their digital competence as a key skill. In this regard, a new framework is developed to evaluate the main drivers of digital transformation in higher education institutions (HEIs) in the era of industry 4.0. The developed framework is proposed a decision approach that can effectively use the presented information to make decisions of high rationality. This framework is applied to compute the subjective and objective criteria weights, and it is used to assess the preferences of organizations. An empirical case study to evaluate the main drivers for the implementation of digital transformation in HEIs is taken. According to the findings, the most significant drivers for the implementation of digital transformation in HEIs in the era of Industry 4.0 are developing, updating, and adapting a curriculum (0.0425), integration of digital technologies for universal education (0.0420), and cloud computing (0.0419), respectively. Hence, the evaluation results also show that the option higher education institution (HEI)-4 has the highest overall utility degree (1.845) over different drivers for the implementation of digital transformation in HEIs in the era of Industry 4.0. Also, comparison and sensitivity investigation are made to show the superiority of the developed framework.

Consensus under strain: policy ideas and decline of Finnish public innovation funding in the 2010s

Over the last three decades, the literature on innovation policy and ideas has expanded. Yet the ideas deployed by governments and elected politicians in day-to-day budgetary discourses have mostly escaped research attention. Against this background, this article provides an extensive empirical case study on the policy ideas (policy solutions and related problem definitions) invoked in the Finnish government and parliamentary discourses over budget allocations to the Finnish innovation funding and governance agency in the 2010s. The article argues that the interplay of three policy ideas motivated the Finnish governments and members of parliament to decrease public innovation funding in the 2010s. It is suggested that policymakers’ interpretations of macroeconomic developments, institutions and industrial change shaped the salience and feasibility of these ideas. The Finnish case illustrates that during prolonged economic crises austerity and business subsidies are particularly powerful policy ideas.

A condition evaluation ensemble for power metering HPLC units within complex data scenarios

Abstract The High-Speed Power Line Carrier Communication (HPLC) enables the connections among power metering devices in integrated energy systems, and thus their satisfying operations are indispensable for system reliabilities. In order to more precisely diagnose their conditions especially in real complex data scenes, a multi-model evaluation ensemble is proposed in this paper. Firstly, typical IoT application contexts of customer-side metering equipment are analyzed, thus the corresponding main impact factors along with their performance evaluation indices can be probed. Next, to handle the multi-source, heterogeneous, high-dimensional datasets during applications, the Kernel Independent Component Analysis (KICA) is established to diminish data dimensionalities, thus the individual weights of each index can be rated. On the other hand, the Component Importance Measure (CIM) model is built to differentiate the impact degree of each indicator on the overall IoT connection performance, where the influence of dissimilar index on the entire performance, rather than the proportion or frequency, will be directly assessed to determine their impact weights. Ergo, a comprehensive diagnosis can be achieved via these two-fold total weights accordingly. Finally, the feasibility and effectiveness of the proposed method can be verified by an empirical case study, which is conducive to further improving the accuracy and rationality of HPLC condition evaluations.

The Efficiency and the Performance of the Logistics Global Supply Chain Activities to Vietnam Exportation: an Empirical Case Study

Purpose: This research paper aims to determine the factors affecting the efficiency and logistics performance index (LPI) of Vietnam's exports to foreign partners during 2018-2022 are due to the impact of the COVID-19 pandemic. Theoretical Framework: Based on the primary factors affecting the efficiency and performance of global supply chain activities in logistics for Vietnam's exports, including practical impact and logistics results of enterprises in Vietnam. Based on the primary factors affecting the efficiency and performance of global supply chain activities in logistics for Vietnam's exports, including (1). Customs efficiency (speed, simplicity and predictability of customs clearance procedures) (2). Quality of infrastructure related to trade and transport, including Roads, railways, ports, airports, warehouses and information technology ...(3). The level of ease when arranging to transport import and export goods with competitive prices (costs such as warehousing fees, port fees, tolls ... ) (4). Capacity and quality of logistics service providers ... (5). Ability to track and trace shipments. (6). Timeliness of the shipment to the destination within the specified time limit. The practical impact and logistics results of enterprises in Vietnam. Method: The panel approach allows the authors to explore the heterogeneity in data across countries. Fixed effects (FE) and random effects (RE) models were used to estimate the model. Then, the Hausman test is carried out to decide which model is appropriate. The data were collected from 240 observations from Vietnam and 80 major export partner countries of Vietnam. Findings: The research results show that the cost, time and capacity of providing logistics services have the most significant impact on Vietnam's exports. Practical & social implications: Overall, to increase the efficiency and logistics efficiency of enterprises. The Vietnamese Government needs to cooperate and propose ideas to partner countries to improve logistics activities for exports from Vietnam. Logistics is beginning to play an increasingly important role in the competitiveness of economies. Originality values: This study also confirms the sustainability of the extended gravity model using OLS and RE methods by substituting different variables for the country's logistics efficiency and solving the endogenous problem in the model while applying the regression method to industrial variables. We find that an 1% improvement in Vietnam's logistics would increase Vietnam's exports by 1.443%, and an 1% improvement in a partner country’s performance would help promote Vietnam's exports to this country by 0.546%.

Swedish study circles encounter Kenyan chamas: a case study on the global interaction of traditions in non-formal adult education

ABSTRACT This article reports an empirical case study of a community self-help group (chama) in Western Kenya, utilising the study circle model promoted by a Swedish non-governmental organisation. Methodologically, it is a qualitative study using semi-structured interviews and participant observation for data collection. The results show that the study circle idea was transferred and translated through a locally pre-existing social infrastructure for learning, i.e. a farming collective organised and based on the widespread Kenyan tradition of chama. When the chama embraced the study circle and made local sense of it, they did so by mainly sticking to the same form of meetings and activities they previously had. The added value of referring to the activity as a study circle was that it expanded the group’s networks and increased its chances to invite specialists for consultation. Also, some increase in status for the group compared to other (non – study circle) chamas was noted.

Planning in the “LGBTQ Capital”: Choreographing Transgender In and Out of Policy

Greater consideration of transgender communities within planning has been called for from research highlighting their absence in policy and practice. However, there is little work that outlines how trans is considered within current planning practice. This article presents an empirical case study of how trans becomes articulated into city-level policy and practice in Brighton & Hove, the “LGBTQ capital” of England. A poststructural approach is used to analyse how trans is problematized within planning documents and interviews with planning practitioners. We develop the concept of “choreographing” to reflect the constrained rhythms and selective positioning at work in the articulation of trans in and out of planning policy and practices. By tracing the only consideration of a specific identified need of the transgender population in Brighton & Hove planning policy, we evidence the previous siloing of these concerns that positioned them in relation to other municipal services, but not planning. We show how interpretive practices within a Health and Equalities Impact Assessment process do not allow the specific needs of trans people and communities to be considered, instead positioning trans people as having greater “sensitivity” to generic changes in the built environment. This research concludes that current planning practices can facilitate the consideration of trans communities in planning and policy-making, yet simultaneously constrain and inhibit the ability to enhance trans liveability in the city. This article opens up theorizing into how consideration of trans and LGBTQ communities and knowledge are integrated into planning processes and calls for a creative disruption of current practice.

How to really quantify the economic value of customer information in corporate databases

This paper presents a novel solution to evaluate the real impact of information and information technology (IT) in companies as fundamental tools to assess how valuable the company’s customers are. The focus is on the concept of information and knowledge as an asset with intrinsic economic value and a variable to consider in order to achieve effective customer management. It is dual research. On the one hand, it is an exploratory-conceptual type based on a review of the literature and, on the other hand, it is descriptive-quantitative through the application of an empirical case study. The proposed new customer relationship management (CRM) information value model (VICRM) offers significantly different results from other traditional models. Its main advantages include the possibility of carrying out new segmentations of customers and estimations of the company’s value. On the other hand, the model corrects some of the classic problems in customer evaluation models, such as their high dependence on the retention rate or being very regressive in the first years. The results of this research aim to serve any company whose business model is Business to Consumer (B2C) to calculate, in an effective way, the value of a large amount of information companies have about their customers.

Normative Study on English Translation of Metro Public Signs in China under the Cognitive Translatology

With the acceleration of its internationalization, China is faced with epochal task of optimizing its international-standard linguistic environment, which is especially impending for Chengdu, the host city for the Universiade. The neo-analysis, at first, sorts out and analyzes different versions of official translation norms for toponyms through document research, as well as from the first-hand resources on public signs of rail transit from TFL and MTA, and then, continues the empirical case study under the theoretical guidance of Cognitive Translatology. This paper has proposed several translation principles and a new method - Conceptual Motivation Mapping - for public signs, attempting to explore the way to build up its international discourse system consistent with the status of Chengdu as a global hub.

Improved assessment model for health-care waste management based on dual 2-tuple linguistic rough number clouds

The management of medical waste disposal is a major challenge faced by different cities in developing countries. The choice of optimal medical waste treatment technology is a complex multi-criteria group decision-making problem that requires consideration of multiple alternatives against conflicting criteria. Decision makers evaluating disposal municipalities may conduct random evaluations from different linguistic term sets according to different preferences and contexts. Various fuzzy numbers based approaches have been studied in HCWM (health-care waste management) process, however they have certain limitations such as lacking manipulation tools of diverse information, additional adjustments and suppositions, ignoring randomness and multi-granularity in experts’ judgements. In response, this research article proposes a novel mathematical models by integrating 2-tuple linguistic setting into rough approximations and cloud theory. First, three novel linguistic manipulation models, namely, 2-tuple linguistic clouds, 2-tuple linguistic rough numbers and dual 2-tuple linguistic rough number (D2tLRN) clouds are developed to handle uncertainty with randomness and multi-granularity simultaneously. Secondly, a hybrid weighting scheme is utilized to evaluate the relative importance of waste factors using both subjective and objective aspects of uncertainty. Thirdly, the proposed D2tLRN cloud model is integrated with the technique for order of preference by similarity to ideal solution (TOPSIS) method to design an evaluation approach for the selection of HCWM technologies. Finally, the application of the proposed method is studied with an empirical case study of health care waste management in the most crowded municipality. The sensitivity analysis of the proposed approach is also discussed in detail to study the effect of various parameters on the results. The out-performance and significance of the proposed D2tLRN cloud TOPSIS method is illustrated by comparing it with existing approaches.

Pursuing the Innovation Economy: Implications for Startup Labour

Abstract This article considers how the UK and Scottish governments’ policy push to promote the innovation economy affects labour. It applies a regulatory approach to consider the issue, focusing specifically on the co-ordinated efforts of government, universities and the private sector to promote and support technology startups. Data is drawn from an empirical case study of the digital technology sector in Scotland. My analysis is 2-fold. First, I demonstrate how the performance of this regulation constitutes people as startup employees. It does this by increasing the quantitative supply of labour, but also by shaping the qualitative features of that supply. The practices of government, universities and the private sector give rise to particular norms within the startup community that shape the way that startups operate as well as startup actors’ knowledge, values and general sense of how things should be done in the sector. Second, I examine how labour law interacts with these newly situated employees. I focus on the legally structured relation of subordination of employees to employers and argue that the norms the multi-actor regulatory effort promotes within the startup community have direct bearing on how this manifests in the sector.

How fast do we forget our past social interactions? Understanding memory retention with parametric decays in relational event models

AbstractIn relational event networks, endogenous statistics are used to summarize the past activity between actors. Typically, it is assumed that past events have equal weight on the social interaction rate in the (near) future regardless of the time that has transpired since observing them. Generally, it is unrealistic to assume that recently past events affect the current event rate to an equal degree as long-past events. Alternatively one may consider using a prespecified decay function with a prespecified rate of decay. A problem then is that the chosen decay function could be misspecified yielding biased results and incorrect conclusions. In this paper, we introduce three parametric weight decay functions (exponential, linear, and one-step) that can be embedded in a relational event model. A statistical method is presented to decide which memory decay function and memory parameter best fit the observed sequence of events. We present simulation studies that show the presence of bias in the estimates of effects of the statistics whenever the decay, as well as the memory parameter, are not properly estimated, and the ability to test different memory models against each other using the Bayes factor. Finally, we apply the methodology to two empirical case studies.

Values and Value Conflicts in the Context of OSINT Technologies for Cybersecurity Incident Response: A Value Sensitive Design Perspective

The negotiation of stakeholder values as a collaborative process throughout technology development has been studied extensively within the fields of Computer Supported Cooperative Work and Human-Computer Interaction. Despite their increasing significance for cybersecurity incident response, there is a gap in research on values of importance to the design of open-source intelligence (OSINT) technologies for this purpose. In this paper, we investigate which values and value conflicts emerge due to the application and development of machine learning (ML) based OSINT technologies to assist cyber security incident response operators. For this purpose, we employ a triangulation of methods, consisting of a systematic survey of the technical literature on the development of OSINT artefacts for cybersecurity (N = 73) and an empirical value sensitive design case study, comprising semi-structured interviews with stakeholders (N = 9) as well as a focus group (N = 7) with developers. Based on our results, we identify implications relevant to the research on and design of OSINT artefacts for cybersecurity incident response.

Invited Review: Applications of unsupervised machine learning in livestock behavior: Case studies in recovering unanticipated behavioral patterns from precision livestock farming data streams

The objective of this article is to review fun- damental differences between model-dependent and mod- el-free approaches to data analysis, and to explore the potential advantages of more open-ended machine learn- ing approaches in recovering complex behavioral patterns from precision livestock farming data streams. Case studies using simulated data were de- signed to mimic a real-world scenario. Data from a feeding trial in an organic dairy were reanalyzed using the Live- stock Informatics Toolkit. Case studies using simulated data are used to demonstrate how incomplete information about the management system can prohibit the development of an appropriate model for information compression, allow- ing aggregation bias to mask important behavioral indi- cators of compromised welfare. These hidden behavioral patterns are then recovered using unsupervised machine learning approaches that are able to leverage the intrinsic behavioral codependencies of group-housed animals. This simulated case study is then extended to demonstrate how model-based approaches can also overlook causes of com- promised welfare when the link between environmental factors and behavioral responses is strong but nonlinear, whereas model-free information-theoretic tools can easily recover and characterize such complex dynamics. Finally, in an empirical case study with data from a commercial organic dairy, the Livestock Informatics Toolkit is used to recover from milk parlor metadata complex associations between herd age structure, levels of milk production, and order of milking. Model-free machine learning algorithms provide a more open-ended approach to knowledge discovery that require fewer up-front as- sumptions about the management system. This can yield more comprehensive insights into large precision livestock farming data sets now commonly encountered in on-farm research trials and in applied data auditing scenarios.

Technological capabilities in the era of the digital economy for integration into cyber-physical systems and the IoT using decision-making approach

In the digital economy, innovators have to deal with the value-capture problem, which necessitates different capabilities. They need to be fully aware of the dynamics of platforms and ecosystems. Such capabilities are needed to enable technologies mainly focused on in the present study. The current digital economy (where businesses are experiencing a big shift from a traditional setting to a widely-digitalized setting) requires companies and enterprises to incorporate innovation into their performance. The present paper aims to offer a novel realm of modern technologies by recognizing the roles the technological capabilities could play in the digital economy regarding for integration of cyber-physical systems (CPS) and the Internet of Things (IoT) into the digital economy. This paper develops an integrated decision-making framework called the Pythagorean fuzzy (PF)- method based on the removal effects of criteria (MEREC)-rank sum (RS)-double normalization-based multiple aggregation (DNMA) model by combining the PF-MEREC-RS and PF-DNMA methods. In this framework, the PF-MEREC-RS method computes the subjective and objective weights of the technological capabilities of the digital economy for the integration of IoT and the CPS. The PF-DNMA method uses to obtain the firms’ preference order over various technological capabilities in the digital economy for integration of the IoT and the CPS. In addition, this paper involves an empirical case study evaluating the key technological capabilities in the digital economy for integration of the IoT and the CPS. Furthermore, comparison and sensitivity investigation are made to show the superiority of the developed framework.

신흥 강대국의 규범적 저항 전술들

How do emerging powers attempt normative resistance to influence normative changes in the international order? By viewing emerging powers as agents of productive normative change, this study aims to examine how China as an emerging power influences the normative change of the responsibility to protect through an in-depth case study of its normative resistance tactics to the norm. For this analysis, this article first reviews related theoretical discussions and presents a theoretical framework for analysis. Then, focusing on the three important periods in the process of normative development of the responsibility to protect (the process of introducing and institutionalizing the norm from 2000 to 2005, the process of implementing the norm after the 2005 World Summit (2005-2011), and the process of implementing the norm in the 2011 Libyan crisis and thereafter), it analyzes which normative resistance tactics China has used to influence the process of change and implementation of the norm. For this analysis, an empirical case study is conducted, including text analysis of China's statements and speeches as well as meeting records and resolutions related to the responsibility to protect at the UN Security Council and the UN General Assembly. Based on the analysis results, this article discusses the implications for the debate on the role and influence of emerging powers in the normative change of international order.

Conceptualizing platformed conspiracism: Analytical framework and empirical case study of BitChute and Gab

This article introduces the notion of platformed conspiracism to conceptualize reconfigured forms of conspiracy theory communication as a result of the mutual shaping between platform specificities and emergent user practices. To investigate this relational socio-technological shaping, we propose a conceptual platform-sensitive framework that systematically guides the study of platformed conspiracism. To illustrate the application of the framework, we examine how platformed conspiracism unfolds on BitChute and Gab during the COVID-19 pandemic. Our findings show that both platforms have positioned themselves as technological equivalents to their “mainstream” counterparts, YouTube and Twitter, by offering similar interfaces and features. However, given their specific services, community-based and politically marketed business models, and minimalist approaches to content moderation, both platforms provide conspiracy propagators a fertile refuge through which they can diversify their presence and profit monetarily from their supply of conspiracy theories and active connection with their followers.

What makes strategic narrative efficient: Ukraine on Russian e-news platforms

Contributing to the ‘narrative turn’ in International Relations and offering an answer to the question ‘What makes a strategic narrative efficient?’, this article adds to the methodological theorization of the formation and projection phases of the narrative’s lifecycle. We suggest that the impact of the constructed image in the narrative can be reinforced by the interplay of at least three projection properties: (1) content accentuation and priming, through iterations; (2) content contextualization, through historical and cultural resonance with the consumers’ memories; and (3) content verbalization, through narrative tactics that evoke a range of the consumers’ involved attitudes to the framed image. These properties, being intrinsic ingredients of the projected content, tend to enhance emotions. In our work, they get traction in the antagonistic narrative tailored by the Russian propaganda to depict Ukraine orientated towards the European Union (EU). The empirical case study analyses articles published on the Russian e-news platforms portraying the EU granting Ukrainians visa-free travel to the Schengen area in 2017, a milestone in Ukraine–EU relations. We define Russia’s narrative, created in reaction to this event, as antagonistic and consider it to be a precursor of the aggressive narrative crafted/employed by Russia to justify its 2022 military assault on Ukraine’s sovereignty.