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The purpose of this paper is to address the challenging issue of developing a quantitative approach for the representation of cultural significance data in heritage information systems (HIS). The authors propose to provide experts in the field with a dedicated framework to structure and integrate targeted data about historical objects' significance in such environments.

This research seeks the identification of key indicators which allow to better inform decision-makers about cultural significance. Identified concepts are formalized in a data structure through conceptual data modeling, taking advantage on unified modeling language (HIS). The design science research (DSR) method is implemented to facilitate the development of the data model.

This paper proposes a practical solution for the formalization of data related to the significance of objects in HIS. The authors end up with a data model which enables multiple knowledge representations through data analysis and information retrieval.

The framework proposed in this article supports a more sustainable vision of heritage preservation as the framework enhances the involvement of all stakeholders in the conservation and management of historical sites. The data model supports explicit communications of the significance of historical objects and strengthens the synergy between the stakeholders involved in different phases of the conservation process.

This study aims to conduct performance and clustering analyses with the help of Digital Government Reference Library (DGRL) v16.6 database examining the role of emerging technologies (ETs) in public services delivery.

VOSviewer and SciMAT techniques were used for clustering and mapping the use of ETs in the public services delivery. Collecting documents from the DGRL v16.6 database, the paper uses text mining analysis for identifying key terms and trends in e-Government research regarding ETs and public services.

The analysis indicates that all ETs are strongly linked to each other, except for blockchain technologies (due to its disruptive nature), which indicate that ETs can be, therefore, seen as accumulative knowledge. In addition, on the whole, findings identify four stages in the evolution of ETs and their application to public services: the “electronic administration” stage, the “technological baseline” stage, the “managerial” stage and the “disruptive technological” stage.

The output of the present research will help to orient policymakers in the implementation and use of ETs, evaluating the influence of these technologies on public services.

The research helps researchers to track research trends and uncover new paths on ETs and its implementation in public services.

Recent research has focused on the need of implementing ETs for improving public services, which could help cities to improve the citizens’ quality of life in urban areas. This paper contributes to expanding the knowledge about ETs and its implementation in public services, identifying trends and networks in the research about these issues.

Although governments have used social media platforms to interact with the public in an attempt to minimize anxiety and provide a forum for public discussion during the pandemic, governments require sufficient crisis communication skills to engage citizens in taking appropriate action effectively. This study aims to examine how the National Health Commission of China (NHCC) has used TikTok, the leading short video–based platform, to facilitate public engagement during COVID-19.

Building upon dual process theories, this study integrates the activation of information exposure, prosocial interaction theory and social sharing of emotion theory to explore how public engagement is related to message sensation value (MSV), media character, content theme and emotional valence. A total of 354 TikTok videos posted by NHCC were collected during the pandemic to explore the determinants of public engagement in crises.

The findings demonstrate that MSV negatively predicts public engagement with government TikTok, but that instructional information increases engagement. The presence of celebrities and health-care professionals negatively affects public engagement with government TikTok accounts. In addition, emotional valence serves a moderating role between MSV, media characters and public engagement.

Government agencies must be fully aware of the different combinations of MSV and emotion use in the video title when releasing crisis-related videos. Government agencies can also leverage media characters – health professionals in particular – to enhance public engagement. Government agencies are encouraged to solicit public demand for the specific content of instructing information through data mining techniques.

This paper aims to establish an efficient maintenance management system tailored for healthcare facilities, recognizing the crucial role of medical equipment in providing timely and precise patient care.

The system is designed to function both as an information portal and a decision-support system. A knowledge-based approach is adopted centered on Semantic Web Technologies (SWTs), leveraging a customized ontology model for healthcare facilities’ knowledge capitalization. Semantic Web Rule Language (SWRL) is integrated to address decision-support aspects, including equipment criticality assessment, maintenance strategies selection and contracting policies assignment. Additionally, Semantic Query-enhanced Web Rule Language (SQWRL) is incorporated to streamline the retrieval of decision-support outcomes and other useful information from the system’s knowledge base. A real-life case study conducted at the University Hospital Center of Oran (Algeria) illustrates the applicability and effectiveness of the proposed approach.

Case study results reveal that 40% of processed equipment is highly critical, 40% is of medium criticality, and 20% is of negligible criticality. The system demonstrates significant efficacy in determining optimal maintenance strategies and contracting policies for the equipment, leveraging combined knowledge and data-driven inference. Overall, SWTs showcases substantial potential in addressing maintenance management challenges within healthcare facilities.

An innovative model for healthcare equipment maintenance management is introduced, incorporating ontology, SWRL and SQWRL, and providing efficient data integration, coordinated workflows and data-driven context-aware decisions, while maintaining optimal flexibility and cross-departmental interoperability, which gives it substantial potential for further development.

Purpose: The business world has become more turbulent than ever. Organisations must be proactive to meet the challenges of the increasingly disruptive, dynamic, and unpredictable world. One technique that has supported leaders and organisations under challenging circumstances is ‘backcasting’, which works by envisioning a desirable future state and then working backwards to attain it. The current study aims to extend an understanding of the backcasting practices and strategic approaches that can be used by leadership teams in different industries in order to survive in turbulent times and can be adapted within and beyond any pandemic.

Methodology: The research employs a desktop research method to review and compare the most commonly used strategies that leaders from different sectors can use for their respective organisations to thrive in the VUCA world.

Findings: There needs to be more research on the applicability and relevance of backcasting that the leaders of different sectors can employ. The study would provide insights that would bridge the existing research gap and come up with suitable strategies that can be employed for dealing with VUCA challenges in the Indian context.

Significance: The outcome of the study will be helpful to the leaders in designing and aligning ‘out of the box’ backcasting strategies to survive in the highly disruptive world.

This study aims to look at challenges that hinder small- and medium-sized enterprises (SMEs) from using open data (OD). The research gaps identified are then used to propose a next generation of OD platform (ODP+).

This study proposes a more effective platform for SMEs called ODP+. A proof of concept was implemented by using modern techniques and technologies, with a pilot conducted among selected SMEs and government employees to test the approach’s viability.

The findings identify current OD platforms generally, and in Gulf Cooperation Council (GCC) countries, they encounter several difficulties, including that the data sets are complex to understand and determine their potential for reuse. The application of big data analytics in mitigating the identified challenges is demonstrated through the artefacts that have been developed.

This paper discusses several challenges that must be addressed to ensure that OD is accessible, helpful and of high quality in the future when planning and implementing OD initiatives.

The proposed ODP+ integrates social network data, SME data sets and government databases. It will give SMEs a platform for combining data from government agencies, third parties and social networks to carry out complex analytical scenarios or build the needed application using artificial intelligence.

The findings promote the potential future utilisation of OD and suggest ways to give users access to knowledge and features.

To the best of the authors’ knowledge, no study provides extensive research about OD in Qatar or GCC. Further, the proposed ODP+ is a new platform that allows SMEs to run natural language data analytics queries.

This paper aims to identify the relevant contributing constructs of readiness for the implementation of intelligent contracts (iContracts) in the construction industry. This study investigates the relationship between the personality dimensions of technology readiness index (TRI) and the system specific factors of technology acceptance model (TAM) within the context of iContracts.

Drawing insights from the extant literature and the author's previous qualitative investigations into iContract readiness constructs, a quantitative approach is used to operationalise the constructs by offering relevant statements to be measured and validated through a multiple-item scale against the users intent to accept the future iContract technology.

This study confirms and validates the relationship of the proposed iContract readiness index (iCRI) statements against the established TAM factors by offering 18 new constructs influencing technology readiness of the iContract technology. This study proves 9 of the 12 hypotheses highlighting key factors to be addressed for the successful development of the iContract technology.

This paper contributes to the body of knowledge by proposing a novel iCRI that informs an iContract technology readiness acceptance model (iCTRAM) for a trending technology. The iCTRAM can guide developers in producing an appropriate iContract solution and assess the readiness of users and organisations for the successful adoption of the iContract concept.

This study offers a unique theoretical framework, in an embryonic field, for predicting the success of iContract implementation within construction organisations. This study combines the established studies of TRI and TAM in producing a predictive iContract readiness assessment tool.

The Internet has changed consumer decision-making and influenced business behaviour. User-generated product information is abundant and readily available. This paper argues that user-generated content can be efficiently utilised for business intelligence using data science and develops an approach to demonstrate the methods and benefits of the different techniques.

Using Python Selenium, Beautiful Soup and various text mining approaches in R to access, retrieve and analyse user-generated content, we argue that (1) companies can extract information about the product attributes that matter most to consumers and (2) user-generated reviews enable the use of text mining results in combination with other demographic and statistical information (e.g. ratings) as an efficient input for competitive analysis.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The study makes several contributions to the marketing and management literature, mainly by illustrating the methodological advantages of text mining and accompanying statistical analysis, the different types of distilled information and their use in decision-making.

The article aims to investigate how washing practices focused on appeasing sceptics of diversity work in for-profit organizations play out in corporate online communication of diversity and inclusion efforts, and how these enable communication to a wide audience that includes social equity advocates.

Online corporate communication data of diversity and inclusion themes were compiled from the websites of eight Swedish-based multinational corporations. The data included content from the companies’ official websites and annual reports and sustainability reports as well as diversity and inclusion-themed blog posts. A thematic analysis was conducted on the website content.

The study showcases how tensions between conflicting external demands are navigated by keeping the communication open to several interpretations and thereby achieving multivocality. In the studied corporate texts on diversity and inclusion, this is achieved by alternating between elements catering to a business case audience and those that appeal to a social justice audience, with some procedures managing to appease both audiences at the same time.

The article complements previously described forms of washing by introducing an additional type of washing – business case washing – an articulation of the business case rhetoric that characterizes the diversity management discourse. While much has been written about washing to satisfy advocates of social change and equity, washing to appease shareholders and boardroom members, who are focused on profit and economic growth, has received less attention. The article suggests that online corporate communication on diversity and inclusion, by appeasing diverse audiences, can be seen as aspirational talk.

This article aims to analyse the relationship between the environmental, social and governance (ESG) score and the cost of capital of 600 large, mid and small capitalization companies across 17 countries that are component of the EURO STOXX 600 Index. By examining whether ESG has an impact on the cost of capital, this article contributes to the solutions to improve the impact of organizations and societies on sustainable development. The article further examines whether the effect is because of the environmental, social and/or governance components. In addition, the article analyses which WACC component (i.e. the cost of equity, the cost of debt, the beta or the leverage ratio) is affected. Furthermore, this article analyses whether a high ESG score can substitute for a weaker legal environment.

The results were obtained by using ordinary least squares panel data modelling to analyse the relationship between the ESG score and the cost of capital. The sample consists of companies that are part of the STOXX Europe 600 Index over the period 2018–2021, which is composed of 600 companies, including large, mid and small capitalization firms listed across 17 countries. The sample finally includes 1,960 firm-year observations.

Companies with a higher ESG score tend to have a lower cost of capital, but this relationship holds only for firms domiciled in countries with a weaker legal environment. In addition, these firms should not only increase their ESG score to create a more sustainable environment but also to reduce their cost of debt. Environmental and social factors have a significantly negative impact on the cost of capital only in countries with a weaker legal environment, while the governance component positively impacts the cost of capital by allowing firms to borrow more.

There is not yet a standardized taxonomy to define ESG, making the study dependent on commercial data providers.

The new insights can be used by companies domiciled in countries with weaker legal environments to reduce their cost of capital. The results also allow us to know on which components of the ESG score to focus. It can also help policymakers, specifically those in countries with a weaker legal environment, to provide incentives to further stimulate ESG investments and disclosure, thereby contributing to a more sustainable society.

To achieve the sustainable development goals put forward by the United Nations, it is important for firms to invest in ESG projects. It is nevertheless insightful to know whether these ESG investments, which are currently observed as a cost, also provide benefits to firms and in which countries. If firms clearly see the advantages of investing in ESG projects, they are likely to proactively engage in them.

This article is the first, to the best of the authors’ knowledge, to focus on 17 European countries, thereby capturing divergent legal environments. This setting allows us to answer the main novel research question, namely, whether the ESG score can act as a substitute for the legal environment in which the company is domiciled. The article also goes further than previous articles by examining whether the effect is because of the environmental, social and/or governance component and whether these impact the components of the weighted cost of capital, namely, the cost of equity, the cost of debt, the beta or the leverage ratio of the companies.