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Representations of time are commonly used to construct narratives in visualisations of data. However, since time is a value-laden concept, and no representation can provide a full, objective account of “temporal reality”, they are also biased and political: reproducing and reinforcing certain views and values at the expense of alternative ones. This conceptual paper aims to explore expressions of temporal bias and politics in data visualisation, along with possibly mitigating user approaches and design strategies.

This study presents a theoretical framework rooted in a sociotechnical view of representations as biased and political, combined with perspectives from critical literacy, radical literacy and critical design. The framework provides a basis for discussion of various types and effects of temporal bias in visualisation. Empirical examples from previous research and public resources illustrate the arguments.

Four types of political effects of temporal bias in visualisations are presented, expressed as limitation of view, disregard of variation, oppression of social groups and misrepresentation of topic and suggest that appropriate critical and radical literacy approaches require users and designers to critique, contextualise, counter and cross beyond expressions of the same. Supporting critical design strategies involve the inclusion of multiple datasets and representations; broad access to flexible tools; and inclusive participation of marginalised groups.

The paper draws attention to a vital, yet little researched problem of temporal representation in visualisations of data. It offers a pioneering bridging of critical literacy, radical literacy and critical design and emphasises mutual rather than contradictory interests of the empirical sciences and humanities.

Previous research suggests that the compensation offered to customers after a service failure has to be substantial to make customer satisfaction surpass that of an error-free service. However, with the right service recovery strategy, it might be possible to reduce compensation size while maintaining happy customers. The aim of the current study is to test whether an anchoring technique can be used to achieve this goal.

After experiencing a service failure, participants were told that there is a standard size of the compensation for service failures. The size of this standard was different depending on condition. Thereafter, participants were asked how much they would demand to be satisfied with their customer experience.

The compensation demand was relatively high on average (1,000–1,400 SEK, ≈ $120). However, telling the participants that customers typically receive 200 SEK as compensation reduced their demand to about 800 SEK (Experiment 1)—an anchoring effect. Moreover, a precise anchoring point (a typical compensation of 247 SEK) generated a lower demand than rounded anchoring points, even when the rounded anchoring point was lower (200 SEK) than the precise counterpart (Experiment 2)—a precision effect.

Setting a low compensation standard—yet allowing customers to actually receive compensations above the standard—can make customers more satisfied while also saving resources in demand-what-you-want service recovery situations, in particular when the compensation standard is a precise value.

The purpose of this study is to explore the antecedents of uncaptured sustainable value and strategies to generate opportunities to capture it in the circular supply chain of post-consumer used clothing.

This study is based on an inductive analysis of 21 semi-structured interviews conducted with various stakeholders in the circular clothing supply chain (for-profit and not-for-profit) using the value mapping approach, as previously applied in the literature on sustainable business models.

Fifteen antecedents of uncaptured sustainable value, and thirteen value opportunity strategies were revealed that hinder or generate multi-dimensional value types. Economic value is impacted the most, while there is lack of explicit understanding of the impact of these antecedents and strategies on environmental and social value capture. From a multi-stakeholder perspective, the ecosystem is emerging as new for-profit actors are developing novel process technologies, while not-for-profit actors are consolidating their positions by offering new service options. There is also an emerging “coopetition” between the different stakeholders.

More granularity in the different types of uncaptured value could be considered, and external supply chain stakeholders, such as the government, could be included, leading to more detailed value mapping.

This research provides practitioners with a value-mapping tool in circular clothing supply chains, thus providing a structured approach to explore, analyse and understand uncaptured value and value opportunities.

This extended value perspective draws upon the value-mapping approach from the sustainable business model literature and applies it in the context of the circular clothing supply chain. In doing so, this research illustrates circular clothing supply chains in a new way that facilitates an improved understanding of multi-dimensional and multi-stakeholder value for embedded actors.

Based on complex network theory, a method for critical elements identification of China Railway High-speed 2 (CRH2) train system is introduced in this paper.

First, two methods, reliability theory and complex theory, are introduced, and the advantages and disadvantages for their application in identifying critical elements of high-speed train system are summarized. Second, a multi-layer multi-granularity network model including virtual and actual nodes is proposed, and the corresponding fusion rules for the same nodes in different layers are given.

Finally, taking CRH2 train system as an example, the critical elements are identified by using complex network theory, which provides a reference for train operation and maintenance.

A method of identifying key elements of CRH2 train system based on integrated importance indices is introduced, which is a meaningful extension of the application of complex network theory to identify key components.

Technological developments and new customer expectations of immediacy have driven businesses to adopt on-demand service models. The purpose of this paper is to study the characteristics of a range of on-demand services in order to better understand the meaning of “on-demand” and its implications for service management. This enables the on-demand service logic to be applied to other service contexts, where it may add value for customers.

The study starts with a focused literature review and continues with a multiple case study methodology, as the on-demand service concept is in the early stages of theory development. Seven cases were studied, based on a maximum variation sampling strategy.

The results show that on-demand services are characterized by three interrelated characteristics: being highly available, responsive and scalable. Analysis further reveals that on-demand services display differences within the conceptual boundaries of these characteristics, i.e. they vary in terms of their availability, responsiveness and scalability.

Drawing on these findings, the study contributes to the service literature by being the first to specifically conceptualize and define the on-demand services concept and reveal three key characteristics that clarify the distinctive nature of this service type. Accordingly, on-demand services are clearly differentiated from other services. Additionally, the paper discusses the variety within on-demand services and develops an on-demand service continuum that gives detailed insights into the conceptual variations within such services.

Data protection requirements heavily increased due to the rising awareness of data security, legal requirements and technological developments. Today, NoSQL databases are increasingly used in security-critical domains. Current survey works on databases and data security only consider authorization and access control in a very general way and do not regard most of today’s sophisticated requirements. Accordingly, the purpose of this paper is to discuss authorization and access control for relational and NoSQL database models in detail with respect to requirements and current state of the art.

This paper follows a systematic literature review approach to study authorization and access control for different database models. Starting with a research on survey works on authorization and access control in databases, the study continues with the identification and definition of advanced authorization and access control requirements, which are generally applicable to any database model. This paper then discusses and compares current database models based on these requirements.

As no survey works consider requirements for authorization and access control in different database models so far, the authors define their requirements. Furthermore, the authors discuss the current state of the art for the relational, key-value, column-oriented, document-based and graph database models in comparison to the defined requirements.

This paper focuses on authorization and access control for various database models, not concrete products. This paper identifies today’s sophisticated – yet general – requirements from the literature and compares them with research results and access control features of current products for the relational and NoSQL database models.

Limited facilities operating and modernization budgets require organizations to carefully identify, prioritize and authorize projects to ensure allocated resources align with strategic objectives. Traditional facility prioritization methods using risk matrices can be improved to increase granularity in categorization and avoid mathematical error or human cognitive biases. These limitations restrict the utility of prioritizations and if erroneously used to select projects for funding, they can lead to wasted resources. This paper aims to propose a novel facility prioritization methodology that corrects these assessment design and implementation issues.

A Mamdani fuzzy logic inference system is coupled with a traditional, categorical risk assessment framework to understand a facilities’ consequence of failure and its effect on an organization’s strategic objectives. Model performance is evaluated using the US Air Force’s facility portfolio, which has been previously assessed, treating facility replicability and interruptability as minimization objectives. The fuzzy logic inference system is built to account for these objectives, but as proof of ease-of-adaptation, facility dependency is added as an additional risk assessment criterion.

Results of the fuzzy logic-based approach show a high degree of consistency with the traditional approach, though the value of the information provided by the framework developed here is considerably higher, as it creates a continuous set of facility prioritizations that are unbiased. The fuzzy logic framework is likely suitable for implementation by diverse, spatially distributed organizations in which decision-makers seek to balance risk assessment complexity with an output value.

This paper fills the identified need for portfolio management strategies that focus on prioritizing projects by risk to organizational operations or objectives.

Innovation output around the world is concentrated in very few economies possessing the requisite skills, knowledge and market acumen to capitalize on emerging technologies. Within the broader European Union, Central and Eastern Europe countries persistently lag in innovation rankings compared to their Western Europe counterparts. The existence of cultural barriers to innovation has been offered as an explanation for the lag, in the sense that perceptions about innovation affect innovation performance. The purpose of this paper is to provide evidence-based analysis on whether there are divergent perceptions at the firm level between East and West.

The focus is on four countries with distinct socioeconomic profiles (Germany, Poland, Portugal and North Macedonia) for which innovation data of sufficient granularity exist. Using Probit analysis across the regressors of firm size, sector and innovativeness, a detailed picture of perceptions of innovation emerges naturally.

The analysis demonstrates that there is no discernible East-West cultural divide but rather a palette of shades regarding perceptions of innovation, entrenched in firm-level characteristics. Specifically, firm size colors perceptions of innovation and such perceptions in turn are moderated by whether a firm is involved or not in innovation activities.

A better understanding of innovation culture at the firm level is essential to drive policy interventions aiming to remove barriers to innovation. The results of this study provide sufficient clues for more refined interventions, both internal (“procedures”) and external (“policies”) to the firm, targeting well-defined size segments as well as addressing differently innovative and non-innovative companies.

This paper proposes a holistic, proactive and adaptive approach to cybersecurity from a service lens, given the continuously evolving cyber-attack techniques, threat and vulnerability landscape that often overshadow existing cybersecurity approaches.

Through an extensive literature review of relevant concepts and analysis of existing cybersecurity frameworks, standards and best practices, a logical argument is made to produce a dynamic end-to-end cybersecurity service system model.

Cyberspace has provided great value for businesses and individuals. The COVID-19 pandemic has significantly motivated the move to cyberspace by organizations. However, the extension to cyberspace comes with additional risks as traditional protection techniques are insufficient and isolated, generally focused on an organization's perimeter with little attention to what is out there. More so, cyberattacks continue to grow in complexity creating overwhelming consequences. Existing cybersecurity approaches and best practices are limited in scope, and implementation strategies, differing in strength and focus, at different levels of granularity. Nevertheless, the need for a proactive, adaptive and responsive cybersecurity solution is recognized.

This paper presents a model that promises proactive, adaptive and responsive end-to-end cybersecurity. The proposed cybersecurity continuity and management model premised on a service system, leveraging on lessons learned from existing solutions, takes a holistic analytical view of service activities from source (service provider) to destination (Customer) to ensure end-to-end security, whether internally (within an organization) or externally.

This paper aims to explore the impact of a recent earthquake activity on house prices and their spatial distribution in the Istanbul housing market.

The paper uses a multi-level approach within an event study framework to model changes in the pattern of house prices in Istanbul. The model allows the isolation of the effects of earthquake risk and explores the differential impact in different submarkets in two study periods – one before (2007) and one after (2012) recent earthquake activity in the Van region, which although in Eastern Turkey served to alter the perceptions of risk through the wider geographic region.

The analysis shows that there are variations in the size of price discounts in submarkets resulting from the differential influence of a recent earthquake activity on perceived risk of damage. The model results show that the spatial impacts of these changes are not transmitted evenly across the study area. Rather it is clear that submarkets at the cheaper end of the market have proportionately larger negative impacts on real estate values.

The robustness of the models would be enhanced by the addition of further spatial levels and larger data sets.

The methods introduced in this study can be used by real estate agents, valuers and insurance companies to help them more accurately assess the likely impacts of changes in the perceived risk of earthquake activity (or other environmental events such as flooding) on the formation of house prices in different market segments.

The application of these methods is intended to inform a fairer approach to setting insurance premiums and a better basis for determining policy interventions and public investment designed to mitigate potential earthquake risk.

The paper represents an attempt to develop a novel extension of the standard use of hedonic models in event studies to investigate the impact of natural disasters on real estate values. The value of the approach is that it is able to better capture the granularity of the spatial effects of environmental events than the standard approach.