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The purpose of this paper is to develop an automated industrial robotic system for handling steel castings of various sizes and shapes in a foundry.

The authors first designed a prismatic gripper for pick-and-place operations that incorporates underactuated passive hydraulic contact (PHC) phalanges that enable the gripper to easily adapt to different casting shapes. The authors then optimized the gripper parameters and compared it to an adaptive revolute gripper using two methods: a planar physics based quasistatic simulation that accounts for object dynamics and validation using physical prototypes on a physical robot.

Through simulation, the authors found that an optimized PHC gripper improves grasp performance by 12 per cent when compared to an human-chosen PHC configuration and 60 per cent when compared to the BarrettHand™. Physical testing validated this finding with an improvement of 11 per cent and 280 per cent, respectively.

This paper presents for the first time optimized prismatic grippers which passively adapt to an object shape in grasping tasks.

Social networking sites (SNS) have become extensively used communication environments as a result of the advancements in online technologies, and among various SNS platforms, Instagram is currently the most prominent image-based network. Since usage motives for alternative SNS environments with different outstanding benefits are expected to vary, this study has focused mainly on extracting the key context-specific usage motives of Instagram. Another purpose of this study is to figure out personality traits differences among Instagram user segments.

An online survey was designed, and a total of 690 fully completed questionnaires was collected, and 507 of the respondents were Instagram users. After conducting factor analysis, six main usage motive categories have been revealed and named as self-expression, recording, socialization, recreation, creativity, and prying.

Instagram users have been clustered as passionate, distant, and spectator users based on their usage motives. Ultimately, personality differences among these clusters have been explored using the Big Five Inventory (BFI) and two additional traits, social interaction anxiety, and fear of negative evaluation. Openness to experience, social interaction anxiety, and fear of negative evaluation were found to be significantly different among these clusters.

Discovering the motives of SNS usage, segmenting users based on these motives, and then portraying the personality traits of each segment gives important clues about how SNSs can better design their interfaces and generate content for attracting users in different segments.

The study aims to investigate the impact of additive manufacturing (AM) on the performance of a spare parts supply chain with a particular focus on underlying spare part demand patterns.

This work evaluates various AM-enabled supply chain configurations through Monte Carlo simulation. Historical demand simulation and intermittent demand forecasting are used in conjunction with a mixed integer linear program to determine optimal network nodal inventory policies. By varying demand characteristics and AM capacity this work assesses how to best employ AM capability within the network.

This research assesses the preferred AM-enabled supply chain configuration for varying levels of intermittent demand patterns and AM production capacity. The research shows that variation in demand patterns alone directly affects the preferred network configuration. The relationship between the demand volume and relative AM production capacity affects the regions of superior network configuration performance.

This research makes several simplifying assumptions regarding AM technical capabilities. AM production time is assumed to be deterministic and does not consider build failure probability, build chamber capacity, part size, part complexity and post-processing requirements.

This research is the first study to link realistic spare part demand characterization to AM supply chain design using quantitative modeling.

The objective of this work is to identify the strategies of digitalization embraced by the European Capitals of Culture 2020 (ECoC) in replying to the limitations due to COVID-19 emergence and to understand how DT have impacted in terms of resilience and innovation. This study aims to provide a contribution at the understanding of the effects and benefits of the digitalization in supporting the reorganization of the cultural projects of ECoC 2020 in replying to the COVID-19.

This paper is based on an exploratory multiple case study methodology. As a suitable investigative tool for the analysis of a contemporary phenomenon in their natural settings, case study methodology allows to integrate evidences resulting from multiple sources (Yin, 2006, 2008; Eisenhardt, 1989). Data collection, monitoring and analysis rely on the combination of Web-based desk analysis and social big data analytics. The integration of such sources has been addressed towards the investigation of the strategies of digitalization undertaken by the two ECoC cities, Galway in Ireland and Rijeka in Croatia, respectively.

Evidences in terms re-organization of the cultural projects, digitalization of the tourist experiences, commitment of local communities and visitors have been derived from the study while the cross comparison of the two cases has allowed to identify common and specific patterns.

The paper presents some limitations. Firstly, the methodological approach as well as the nature of data collected suggest the need of future investigation with the inclusion of a larger sample of ECoCs and the inclusions of quantitative date related to trends of online cultural experiences and travel data. Secondly, the theoretical perspective of digitalization used in this study can be accompanied by other perspectives such as innovation and resilience capabilities of an ECoC.

This study contributes to the academic literature by providing a better understanding of the level of resilience generated vis-à-vis the COVID-19 pandemic and the role of DT in promoting participation in culture and implementing cultural initiatives of ECoCs. However, despite the relevance of the topic, the attention from the academic literature on the topic of digitalization in cultural and creative industries is still limited. Moreover, even more limited is the knowledge about the effects of DT and if their opportunities are actually transformed in positive outcomes.

The purpose of this paper is to build a bridge between climate change adaptation and spatial planning and design. It aims to develop a spatial planning framework in which the properties of climate adaptation and spatial planning are unified.

Adaptive and dynamical approaches in spatial planning literature are studied and climate adaptation properties are defined in a way they can be used in a spatial planning framework. The climate adaptation properties and spatial planning features are aggregated in coherent groups and used to construct the spatial planning framework, which subsequently has been tested to design a climate adaptive region.

The paper concludes that the majority of spatial planning methods do not include adaptive or dynamic strategies derived from complex adaptive systems theory, such as adaptive capacity or vulnerability. If these complex adaptive systems properties are spatially defined and aggregated in a coherent set of spatial groups, they can form a spatial planning framework for climate adaptation. Each of these groups has a specific time dimension and can be linked to a specific spatial planning “layer”. The set of (five) layers form the spatial planning framework, which can be used as a methodology to design a climate adaptive region.

Previous research did not connect the complex issue of climate change with spatial planning. Many frameworks are developed in climate change research but are generally not aiming to meet the needs of spatial planning. This article forms the first attempt to develop a spatial planning framework, in which non‐linear and dynamical processes, such as climate adaptation, is included.

Based on the assumption that the identity and self-understanding of an academic discipline determines how it conceptualizes different domains of social reality, including how it imports and/or exports concepts from or to other disciplines, this chapter presents some of the findings of a major ongoing comparative and cross-disciplinary study of how five key concepts within the combined fields of crisis management and reputation management are applied in three different disciplinary contexts. In this chapter, however, the focus is on just one of these concepts: the concept of reputation.

The purpose of this paper is to identify mechanisms and strategies involved in individual and local responses to complex global sustainability issues such as climate change.

This paper describes an innovative approach to understanding the role of informal leadership and its utility in influencing societal attitudes and practice. The approach builds on theories of diffusion in which learning about new ideas, practices or technologies occurs through interpersonal communication with informal opinion leaders. It draws on findings from studies in other fields of social research, such as community health, development aid, and agriculture, in which the engagement of opinion leaders has been found to speed up the spread of responsive behaviours. The approach also analyses linkages between the concepts of response capacity to climate change and social capital with the strategies of opinion leaders for influencing societal change through informal social networks.

Research related to social change in response to climate change has focused predominantly on the need for reform at the public policy and institutional level, and at the other extreme, on individual behaviour change. The role of leaders has been cited as an important component of social change in case studies of adaptive management of natural resources, sustainability studies, and in research on social capital.

Development of the approach will contribute to the understanding of social mechanisms and processes involved in community engagement with complex problems and more specifically, response capacity for climate change at the regional level.

This study aims to provide an analysis and evaluation of infrastructure resilience, one of the components of disaster resilience, to natural hazards.

The analysis of this study consists of four stages. First, descriptive statistical analyses were carried out on the soft and hard infrastructure resilience and natural hazard index. Second, the spatial data were visualized through the exploratory spatial data analysis to understand the spatial distribution and spatial characteristics of variables of the data. Third, the local indicators of the spatial association method were used to identify areas in clusters where infrastructure resilience is weak. Fourth, comparisons were made between the soft and hard infrastructure resilience and natural hazard index: the level of natural hazard is high but the soft and infrastructure resilience remain very vulnerable to disaster.

The study found that infrastructure resilience varies from community to community, particularly in the same community, in terms of hard infrastructure and soft infrastructure. In addition, the comparative analysis between infrastructure resilience and disaster risk levels resulted in communities that were likely to suffer greatly in the event of a disaster.

This study is meaningful in that infrastructure resilience of Korean local governments was discussed by dividing them into soft and hard infrastructure and comparing them to natural disaster risk levels. In particular, the comparison with the natural disaster risk level identified local governments that are likely to experience significant damage from the natural disaster, which is meaningful in that it serves as a basis for policy practitioners to actively build infrastructure and respond to disasters.