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Digital technologies, and the affordances they provide, can shape institutional processes in significant ways. In the last decade, social media and other digital platforms have redefined civic engagement by enabling new ways of connecting, collaborating, and mobilizing. In this article, we examine how technological affordances can both enable and hinder institutional processes through visibilization – which we define as the enactment of technological features to foreground and give voice to particular perspectives and discourses while silencing others. We study such dynamics by examining #SchauHin, an activist campaign initiated in Germany to shine a spotlight on experiences of daily racism. Our findings show how actors and counter-actors differentially leveraged the technological features of two digital platforms to shape the campaign. Our study has implications for understanding the role of digital technologies in institutional processes as well as the interplay between affordances and visibility in efforts to deinstitutionalize discriminatory practices and institutions.

The purpose of this paper is to explore the benefits of co-creation/co-design using extended reality (XR) technologies during the initial stages of the design process. A review of the emerging co-creation tools within XR will be examined along with whether they offer the potential to improve the design process; this will also highlight the gaps on where further research is required.

The paper draws on professional and academic experiences of the authors in creative practices within the realm of XR technology, co-creation and co-design. In addition, a review of the current literature on emerging technologies and work-based learning will offer further insight on the themes covered.

To design, collaborate, iterate and amend with colleagues and peers in a virtual space gives a wide range of obvious benefits. Creative practitioners both in education and employment are working more collaboratively with the advancement of technology. However, there is a need to find a space where collaboration can also offer the opportunity for co-creation that improves the initial stages of the design process. This technology also offers solutions on the constraints of distance and ameliorates creative expression.

There is an opportunity to test the ideas expressed in this paper empirically; this can be done through testing co-creation tools with professionals, work-based learners and students.

The paper will add to the existing literature on emerging technologies as a unique environment to improve co-create/co-design the visuals created during the fuzzy front end of the design process and offer a potential framework for future empirical work.

In this volatile and increasingly fast-revolving world, it has become crucially important to monitor, measure and manage nation image and its dynamic changes in real time. However, few studies have been conducted on a model to measure the image and/or its changes. The purpose of this paper is to find an economically affordable methodology to measure nation image and its changes online in real time.

The study took an approach to build dynamic ontology that may reflect to change nation image in real-time. With it, the authors attempted to measure nation image in real time.

Among many social media, the authors found that Wikipedia is particularly suitable for the purpose of measuring nation image. An ontology of nation image was built from the keywords collected from the pages directly related to the big three exporting countries in East Asia, i.e. Korea, Japan and China. The click views on the pages of the countries in two different language editions of Wikipedia, Vietnamese and Indonesian were counted.

The study confirms the objective: the data from a social media service, Wikipedia, may work very well as an economically affordable real-time supplement to offline nation image indices that are currently used.

For the purpose of reducing the incidence of hazardous materials transport accident, eliminating the potential threats and ensuring their safety, aiming at the shortcomings in the process of current hazardous materials transportation management, this paper aims to construct the framework of hazardous materials transportation safety management system under the vehicle-infrastructure connected environment.

The system takes the intelligent connected vehicle as the main supporter, integrating GIS, GPS, eye location, GSM, networks and database technology.

By analyzing the transportation characteristics of hazardous materials, this system consists of five subsystems, which are vehicle and driver management subsystem, dangerous sources and hazardous materials management subsystem, route analysis and optimization subsystem, early warning and emergency rescue management subsystem, and basic information query subsystem.

Hazardous materials transportation safety management system includes omnibearing real-time monitoring, timely updating of system database, real-time generation and optimization of emergency rescue route. The system can reduce the transportation cost and improve the ability of accident prevention and emergency rescue of hazardous materials.

The purpose of this paper is to propose a concept of cloud auction robot (CAR) and its execution platform for transforming perishable food supply chain management. A new paradigm of goods-to-person auction execution model is proposed based on CARs. This paradigm can shift the management of traditional manual working to automated execution with great space and time saving. A scalable CAR-enabled execution system (CARES) is presented to manage logistics workflows, tasks and behavior of CAR-Agents in handling the real-time events and associated data.

An Internet of Things enabled auction environment is designed. The robot is used to pick up and deliver the auction products and commends are given to the robot in real-time. CARES architecture is proposed while integrating three core services from auction workflow management, auction task management, to auction execution control. A system prototype was developed to show its execution through physical emulations and experiments.

The CARES could well schedule the tasks for each robot to minimize their waiting time. The total execution time is reduced by 33 percent on average. Space utilization for each auction studio is improved by about 50 percent per day.

The CAR-enabled execution model and system is simulated and verified in a ubiquitous auction environment so as to upgrade the perishable food supply chain management into a new level which is automated and real-time. The proposed system is flexible to cope with different auction scenarios, such as different auction mechanisms and processes, with high reconfigurability and scalability.

Digital communication technologies have become ubiquitous for various firm processes related to international business (IB) and global strategy. However, IB and strategy scholars lack an encompassing and theory-based typology of these technologies that facilitates analysis and discussion of their uses and effects. Likewise, managers have a large choice of technologies at their disposal making it difficult to determine what technology to use in different IB areas. This paper aims to develop a typology of digital communication technologies based on the synchronicity and interactivity of these technologies and capture their fundamental social and temporal dimensions. This results in four ideal types: broadcasting, corresponding, aggregating and collaborating technologies.

This is a conceptual paper incorporating theoretical perspectives to theorize about four ideal types of digital communication technologies. A subsequent empirical test of this typology has been provided in the appendix.

The authors discuss how the typology might be applied in IB decisions and some of the contingencies that impact this choice. Building on that, the authors develop directions for future research to increase their understanding of the use of digital communication technologies to help improve IB functions. Overall, the authors suggest future research explores contingencies about where and when different types of digital communication technologies should be used. Finally, the authors provide implication of having a unified typology for both academics and managers.

The authors offer a robust framework for thinking about and capturing different types of digital communication technologies that can be applied by researchers and used by managers when making decisions related to IB. The authors also provide some initial testing of the typology with a three-country study design helping to determine its validity.

Traffic density is one of the most important parameters to consider in the traffic operation field. Owing to limited data sources, traditional methods cannot extract traffic density directly. In the vehicular ad hoc network (VANET) environment, the vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) interaction technologies create better conditions for collecting the whole time-space and refined traffic data, which provides a new approach to solving this problem.

On that basis, a real-time traffic density extraction method has been proposed, including lane density, segment density and network density. Meanwhile, using SUMO and OMNet++ as traffic simulator and network simulator, respectively, the Veins framework as middleware and the two-way coupling VANET simulation platform was constructed.

Based on the simulation platform, a simulated intersection in Shanghai was developed to investigate the adaptability of the model.

Most research studies use separate simulation methods, importing trace data obtained by using from the simulation software to the communication simulation software. In this paper, the tight coupling simulation method is applied. Using real-time data and history data, the research focuses on the establishment and validation of the traffic density extraction model.

Unlike quantitative studies, interview data generally cannot be validated; yet, they are typically the only evidence of the research. This study develops protocols for using verbatim interview quotations in research and for assessing the quality of interview quotations.

This research reviews 20 empirical papers using in-depth interviews containing 600 interview quotations to examine authors' approaches to verbatim interviewee quotations. The research analyses the sample papers for interview transcript handling, selection of quotations, the number and length of interview quotations, how they are placed and presented, the proportion of interviewee voices reproduced in quotations and the disclosure of protocols for translating and editing quotations. This paper includes illustrative interview quotations as exemplars of best practice.

Given the modest discussion of the principles influencing the reproduction of quotations in research, this study develops a framework for evaluating prior research. Researchers use a wide variety of practices to reproduce interview quotations in accounting research. The issues derived from this review, and their application to interview-based papers, frame an argument for a general set of quality criteria and protocols rather than rigid rules for assessing qualitative work. These criteria can serve as anchor points for qualitative evaluation.

There is little guidance on the use of interview quotations in qualitative research which this study bridges.

Social media networks like Twitter, Facebook, WhatsApp etc. are most commonly used medium for sharing news, opinions and to stay in touch with peers. Messages on twitter are limited to 140 characters. This led users to create their own novel syntax in tweets to express more in lesser words. Free writing style, use of URLs, markup syntax, inappropriate punctuations, ungrammatical structures, abbreviations etc. makes it harder to mine useful information from them. For each tweet, we can get an explicit time stamp, the name of the user, the social network the user belongs to, or even the GPS coordinates if the tweet is created with a GPS-enabled mobile device. With these features, Twitter is, in nature, a good resource for detecting and analyzing the real time events happening around the world. By using the speed and coverage of Twitter, we can detect events, a sequence of important keywords being talked, in a timely manner which can be used in different applications like natural calamity relief support, earthquake relief support, product launches, suspicious activity detection etc. The keyword detection process from Twitter can be seen as a two step process: detection of keyword in the raw text form (words as posted by the users) and keyword normalization process (reforming the users’ unstructured words in the complete meaningful English language words). In this paper a keyword detection technique based upon the graph, spanning tree and Page Rank algorithm is proposed. A text normalization technique based upon hybrid approach using Levenshtein distance, demetaphone algorithm and dictionary mapping is proposed to work upon the unstructured keywords as produced by the proposed keyword detector. The proposed normalization technique is validated using the standard lexnorm 1.2 dataset. The proposed system is used to detect the keywords from Twiter text being posted at real time. The detected and normalized keywords are further validated from the search engine results at later time for detection of events.

This paper aims to reschedule the freight train timetable in case of disturbance to restore the train services as soon as possible.

Hence, an integer linear programming model for the real-time freight heavy-haul railway traffic management is developed in case of large primary delays caused by the delayed cargos loading. The proposed model based on the alternative graph at the microscopic level depicts the freight train movements in detail. Multiple dispatching measures such as re-timing and re-ordering are taken into account. Moreover, two objective functions, namely, the total final delays and the consecutive delays, are minimized in the freight trains dispatching problem.

Finally, a real-world computational experiment based on the Haolebaoji-Ji’an freight heavy-haul railway is implemented. The results of all disrupted cases are obtained within 10 s. The results give insight into that the consecutive delays are more than the total final delays when the same disrupted situation and the consecutive or total final delays increase as the primary delays increase.

An integer linear programming model based on the alternative graph for the real-time freight heavy-haul railway traffic management is developed in case of large primary delays caused by the delayed cargos loading. The method can be developed as the computer-aided tool for freight train dispatchers.