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The main aim of this study is to understand the role of smart technologies and show the rankings of various smart technologies in collection and classification of electronic waste (e-waste).

This study presents a framework integrating the concepts of collection and classification mechanisms and smart technologies. The criteria set includes three main, which are economic, social and environmental criteria, including a total of 15 subcriteria. Smart technologies identified in this study were robotics, multiagent systems, autonomous tools, smart vehicles, data-driven technologies, Internet of things (IOT), cloud computing and big data analytics. The weights of all criteria were found using fuzzy analytic network process (ANP), and the scores of smart technologies which were useful for collection and classification of e-waste were calculated using fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR).

The most important criterion was found as collection cost, followed by pollution prevention and control, storage/holding cost and greenhouse gas emissions in collection and classification of e-waste. Autonomous tools were found as the best smart technology for collection and classification of e-waste, followed by robotics and smart vehicles.

The originality of the study is to propose a framework, which integrates the collection and classification of e-waste and smart technologies.

This study aims to establish an assessment model to measure big data readiness in the public sector, specifically targeting local governments at the provincial and city/regency levels. Additionally, the study aims to gain valuable insights into the readiness of selected local governments in Indonesia by using the established assessment model.

This study uses a mixed-method approach, using focus group discussions (FGDs), surveys and exploratory factor analysis (EFA) to establish the assessment model. The FGDs involve gathering perspectives on readiness variables from experts in academia, government and practice, whereas the survey collects data from a sample of selected local governments using a questionnaire developed based on the variables obtained in FGDs. The EFA is used on survey data to condense the variables into a smaller set of dimensions or factors. Ultimately, the assessment model is applied to evaluate the level of big data readiness among the selected Indonesian local governments.

FGDs identify 32 essential variables for evaluating the readiness of local governments to adopt big data. Subsequently, EFA reduces this number by five and organizes the remaining variables into four factors: big data strategy, policy and collaboration, infrastructure and human resources and data collection and utilization. The application of the assessment model reveals that the overall readiness for big data in the selected local governments is primarily moderate, with those in the Java cluster displaying higher readiness. In addition, the data collection and utilization factor achieves the highest score among the four factors.

This study offers an assessment model for evaluating big data readiness within local governments by combining perspectives from big data experts in academia, government and practice.

The article investigates the institutional setup of e-lending in public libraries in Denmark, Norway and Sweden. Our point of departure is that e-lending has necessitated new library collaborations between local, regional and national levels, and therefore, institutional e-lending setups have emerged. The study seeks to provide better understanding of how the institutional setups are structured, how governance logics have shaped them and what tensions and dynamics become visible in the key actors’ problematisations of these setups.

The study is situated in the neo-institutional tradition and applies the institutional logics perspective. The research questions are answered by taking a qualitative approach, grounded in an extensive interview study with representatives of libraries, publishers and policy actors in three Scandinavian countries. To provide in-depth insight into e-lending setups, the scope of empirical material is then limited to accounts the central library and policy actors involved in establishing e-lending.

The analysis shows that the e-lending setups are both similar (especially when it comes to financing), and different across Scandinavia, especially when it comes to centralisation and involvement of librarians in this task. The differences are attributed to the influence of different governance logics (question of administrative autonomy, collaboration in the field and existing legal and political frames), and to what extent the digital and market logics are incorporated or rejected in the field.

The study provides new insights into the question of how Scandinavian public libraries face the consequences of the digitalisation of book distribution and consumption by investigating how they organise their e-lending services. This has not been explored before, notably in a comparative perspective.

General Data Protection Regulation (GDPR) of the European Union (EU) was passed to protect data privacy. Though the GDPR intended to address issues related to data privacy in the EU, it created an extra-territorial effect through Articles 3, 45 and 46. Extra-territorial effect refers to the application or the effect of local laws and regulations in another country. Lawmakers around the globe passed or intensified their efforts to pass laws to have personal data privacy covered so that they meet the adequacy requirement under Articles 45–46 of GDPR while providing comprehensive legislation locally. This study aims to analyze the Malaysian and Saudi Arabian legislation on health data privacy and their adequacy in meeting GDPR data privacy protection requirements.

The research used a systematic literature review, legal content analysis and comparative analysis to critically analyze the health data protection in Malaysia and Saudi Arabia in comparison with GDPR and to see the adequacy of health data protection that could meet the requirement of EU data transfer requirement.

The finding suggested that the private sector is better regulated in Malaysia than the public sector. Saudi Arabia has some general laws to cover health data privacy in both public and private sector organizations until the newly passed data protection law is implemented in 2024. The finding also suggested that the Personal Data Protection Act 2010 of Malaysia and the Personal Data Protection Law 2022 of Saudi Arabia could be considered “adequate” under GDPR.

The research would be able to identify the key principles that could identify the adequacy of the laws about health data in Malaysia and Saudi Arabia as there is a dearth of literature in this area. This will help to propose suggestions to improve the laws concerning health data protection so that various stakeholders can benefit from it.

This study investigates determinant factors (influence of the third party (ITP), credit policy (CP) and follow-up process (FP)) of micro, small and medium enterprises' (MSMEs) accounting processes (APs) and strategic debtors' management.

The study employed a sequential mixed-method approach, combining quantitative and qualitative methods for comprehensive data analysis. Phase I involved purposively selecting and interviewing 10 MSME owners or accountants to gain insights into debtors' management. In Phase II, a quantitative approach was used for collecting survey data from 72 MSME owners or accountants. Structural equation modeling-partial least squares (SEM-PLS) are the statistical tools that validated the study's proposed hypotheses.

The findings indicate that determinant factors (ITP, CP and FP) positively affect MSMEs' AP, significantly influencing strategic debtors' management. As a result, sole proprietors can use this study's findings to create value through systematic management of their debtors, guaranteeing sustainable firm growth and profitability.

The sample has restricted to MSMEs in Oman, where the findings may not be generalized to other companies. Overall, the findings suggest that it requires considering the proposed determinant factor of MSMEs' AP to manage their debtors or accounts receivable (AR) to be more profitable.

MSMEs play an essential role in the growth of any country's economy. However, the dearth of comprehensive research on influential factors of MSMEs' debtors’ management studies justifies the significance of the current study.

From the perspective of local government tax administration, the impact of geographic dispersion on the corporate tax burden is investigated in this paper.

Using unbalanced panel data with a sample of listed companies from 2003 to 2020 in China, this paper focuses on the effect of geographic dispersion on corporate tax burden and the mechanisms.

It is found that corporate tax burden is positively related to geographic dispersion. It is also found that geographic dispersion affects the corporate tax burden by increasing the effort of local government tax administration. In addition, the relation between geographic dispersion and corporate tax burden is more pronounced for local SOEs prior to the implementation of Golden Tax Project III and in cases where local governments face stronger financial pressure to obtain revenue.

This study has important implications for the promotion of the coordinated development of the regional economy, as well as the legalization, modernization and informatization of tax administration.

The purpose of this study is to address the generalised lack of guidance on ethical treatment of corporate (e.g. non-research) data in higher education institutions, by focusing on the case of the University of Queensland (Brisbane, Australia). No actionable framework is currently available in the country to govern the ethical usage of corporate data. As such, this research takes a stakeholder-centred approach to data ethics; the lived experience of the stakeholders involved coupled with a theory-based ethical framework allowed the authors build to build a framework to guide ethical data practice.

Adopting a revised canonical action research approach focused on intervention on the context, the authors conducted a review of the literature on ethical usage of data in higher education institutions; administered one survey to university students (n = 168); and facilitated three workshops with professional staff (two) and students (one).

Collected data highlighted how, among other themes, the role and ethical importance of transparency was the dominant claim among all stakeholder groups. Findings helped the authors develop an Enhanced Enterprise Data Ethics Framework (EEDEF) emphasising transparency and stakeholder-centricity.

Legislation is the driver to regulate the use of corporate data in higher education; however, this can be problematic because legislation is retrospective, lacks normativity and offers scarce directions for cases that do not exactly follow within the legislative mandate. In light of these regulatory limitations, the authors’ EEDEF offers operators guidance on how to ethically manage corporate data in the higher education environment.

This study fills gaps in praxis and theory; that is the lack of literature and guiding ethical frameworks to inform data practice in higher education. This research fosters a more ethical data management by virtue of genuine and authentic engagement with stakeholders and emphasises the importance of strategic decision-making and maturity of data culture in the higher education sector.

In the online environment, consumers increasingly feel vulnerable due to firms’ expanding capabilities of collecting and using their data in an unsanctioned manner. Drawing from gossip theory, this research focuses on two key suppressors of consumer vulnerability: transparency and control. Previous studies conceptualize transparency and control from rationalistic approaches that overlook individual experiences and present a unidimensional conceptualization. This research aims to understand how individuals interpret transparency and control concerning privacy vulnerability in the online environment. Additionally, it explores strategic approaches to communicating the value of transparency and control.

An interpretivism paradigm and phenomenology were adopted in the research design. Data were collected through semi-structured interviews with 41 participants, including consumers and experts, and analyzed through thematic analysis.

The findings identify key conceptual dimensions of transparency and control by adapting justice theory. They also reveal that firms can communicate assurance, functional, technical and social values of transparency and control to address consumer vulnerability.

This research makes the following contributions to the data privacy literature. The findings exhibit multidimensional and comprehensive conceptualizations of transparency and control, including user, firm and information perspectives. Additionally, the conceptual framework combines empirical insights from both experiencers and observers to offer an understanding of how transparency and control serve as justice mechanisms to effectively tackle the issue of unsanctioned transmission of personal information and subsequently address vulnerability. Lastly, the findings provide strategic approaches to communicating the value of transparency and control.

The housing policies targeting low-income households have not been effective to address the housing needs of target groups in Iran over the past four decades. According to the World Bank’s data on population living in slums (% of urban population) in Iran in 2018 was 25% which is slightly higher than the rate 23% of upper-middle-income countries. This study aims to understand what major revisions are required in the process of housing policymaking to have more effective policies.

The authors conduct one-to-one interviews with 41 housing experts and apply discourse analysis and interpretive–structural modeling to achieve the goals.

The panel of experts argue that the success of housing policies in Iran depends on the following: all academic disciplines should be included in the process of housing policymaking process; land policymaking should be modified; housing policy is a regional issue, and it should be designed and implemented differently in each province; main modifications are required in the tax and tenancy system; and new policies are required to push vacant houses into the rental market.

This study is a prescriptive study based on a general trend (four decades).

Upon the realization of the need for guideline in cross-organizational data integration, in an exploratory manner, this study developed a public data governance framework, specifically, the governance for integrated public data (GIPD) framework and identified the influential factors of its successful implementation. This framework was then subjected to an analysis of a real data integration case in the South Korean public sector to test its efficacy.

To develop the GIPD framework, the authors conducted an extensive meta study, focus group interviews and the analytic hierarchy process involving field experts. Further, the authors performed topic modeling on documents from Korean research and development data integration projects, and compared the extracted factors to those of the GIPD to illustrate the latter's usefulness in a real case.

Legislation, policy goals and strategies, operation organization, decision-making council, financial support size and objective, system development and operation, data integration, data generation, system/data standardization and master data management were derived as the 10 important factors in implementing the GIPD framework. The illustrative case of Korea revealed that decision-making council, financial support size and objective, legislation, data generation and data integration were insufficient.

Although this study reveals important findings, it has a few limitations. First, the potential factors for data governance might vary depending on the attribute of the “interviewee” (such as their career or experience period) and the goal and area of GIPD framework building. Second, the inherent limitation of topic modeling in determining topics from groups of extracted keywords means that topics may be interpreted in various ways, depending on the perspective of the expert.

This study is highly significant in that it provides a starting point for discussions on the issue of data integration among public institutions. Therefore, although this study examined public data governance based on R&D data, it will contribute to providing a sufficient guideline for any type of inter-institutional data governance framework, what to discuss and how to discuss between institutions.

The findings are expected to provide a roadmap to formulate practical guidelines on inter-institutional data cooperation and a diagnostic matrix to improve the existing data governance system, especially in the public sector, from the existing practice of empirical analysis using a mixed methodology approach.