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1 – 10 of over 6000Kasmad Ariansyah, Ahmad Budi Setiawan, Alfin Hikmaturokhman, Ardison Ardison and Djoko Walujo
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
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Xubu Ma, Yafan Xiang, Chunxiu Qin, Huigang Liang and Dongsu Liu
With the worldwide open government data (OGD) movement and frequent public health emergencies in recent years, academic research on OGD for public health emergencies has been…
Abstract
Purpose
With the worldwide open government data (OGD) movement and frequent public health emergencies in recent years, academic research on OGD for public health emergencies has been growing. However, it is not fully understood how to promote OGD on public health emergencies. Therefore, this paper aims to explore the factors that influence OGD on public health emergencies.
Design/methodology/approach
The technology–organization–environment framework is applied to explore factors that influence OGD during COVID-19. It is argued that the effects of four key factors – technical capacity, organizational readiness, social attention and top-down pressure – are contingent on the severity of the pandemic. A unique data set was created by combining multiple data sources which include archival government data, a survey of 1,034 Chinese respondents during the COVID-19 outbreak and official COVID-19 reports.
Findings
The data analysis indicates that the four factors positively affect OGD, and pandemic severity strengthens the effects of technical capacity, organizational readiness and social attention on OGD.
Originality/value
This study provides theoretical insights regarding how to improve OGD during public health emergencies, which can guide government efforts in sharing data with the public when dealing with outbreak in the future.
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Fernando Kleiman, Sylvia J.T. Jansen, Sebastiaan Meijer and Marijn Janssen
The opening of government data is high on the policy agenda of governments worldwide. However, data release faces barriers due to limited support of civil servants, whereas the…
Abstract
Purpose
The opening of government data is high on the policy agenda of governments worldwide. However, data release faces barriers due to limited support of civil servants, whereas the literature neglects civil servants' role in opening data. This paper aims at understanding why civil servants can be reluctant to support the disclosure of data. The authors developed a model to explain civil servants' behavioral intention to open data.
Design/methodology/approach
The authors test a series of hypotheses by collecting and analyzing survey data from 387 civil servants and by applying multivariate hierarchical regression.
Findings
The results indicate the factors influencing the behavior of civil servants. Social influences, performance expectancy, data management knowledge and risks have a significant influence. Personal characteristics control these effects.
Research limitations/implications
Caution is needed to generalize the findings towards the support to open data provision by civil servants. Though the analyzed sample was limited to Brazil, other countries and cultures might yield different outcomes. Larger and more diversified samples might indicate significant effects on variables not found in this research.
Practical implications
The insights can be used to develop policies for increasing the support of civil servants towards governmental data disclosure.
Originality/value
This study suggests factors of influence to civil servants' behavior intentions to disclose governmental data. It results in a model of factors, specifically for their behavioral intention at the individual level.
Maryam Zulfiqar, Michael Sony, Shreeranga Bhat, Jiju Antony, Willem Salentijn and Olivia McDermott
The integration of Lean Six Sigma (LSS) and Industry 4.0 (I4.0) is in the nascent stage and promises to achieve new optimums in operational excellence. This study aims to…
Abstract
Purpose
The integration of Lean Six Sigma (LSS) and Industry 4.0 (I4.0) is in the nascent stage and promises to achieve new optimums in operational excellence. This study aims to empirically examine the enablers, barriers, benefits and application of I4.0 technologies in LSS and I4.0 integration.
Design/methodology/approach
A pilot survey was chosen as an appropriate methodology, as LSS and I4.0 integration is still budding. The survey targeted senior quality management professionals, quality managers, team leaders, LSS Black Belts and operations managers to collect the relevant research data. The questionnaire was sent to 200 respondents and received 53 valid responses.
Findings
This study reveals that “top management support” is an essential enabler for LSS and I4.0 integration. The most significant barrier was “poor understanding of data analysis” and “lack of top management support”. The findings further illustrated that LSS and I4.0 integration resulted in greater efficiency, lower operational costs, improved productivity, improved customer satisfaction and improved quality. Regarding I4.0 technology integration at different phases of LSS, the authors noticed that big data analytics and artificial intelligence (AI) are the most prominent technologies used in all phases of LSS implementation.
Research limitations/implications
One of the limitations of this study is the sample size. LSS and I4.0 are emerging concepts; hence, obtaining a larger sample size is difficult. In addition, the study used non-parametric tests to analyse the data. Therefore, future studies should be conducted with large sample sizes across different continents and countries to understand differences in the key findings.
Practical implications
The outcomes of this study can be useful for organisational managers to understand the enablers and barriers before integrating LSS and I4.0 for adoption in their organisations. Secondly, it helps to convince top management and human resource personnel by providing a list of benefits of LSS and I4.0 integration. Finally, it can help decision-makers understand which I4.0 technologies can be used in different stages of LSS methodology.
Originality/value
LSS and I4.0 integration was studied at a conceptual level. This is the first empirical study targeted toward understanding the LSS and I4.0 integration. In addition, this study investigates the application of widely used I4.0 technologies in different phases of LSS.
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Aya Khaled Youssef Sayed Mohamed, Dagmar Auer, Daniel Hofer and Josef Küng
Data protection requirements heavily increased due to the rising awareness of data security, legal requirements and technological developments. Today, NoSQL databases are…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
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Meri Pulkkinen, Lotta-Maria Sinervo and Kaisa Kurkela
In this paper, the authors focus on participatory budgeting (PB) as an organizational issue in local government. The aim of this study is to analyze the premises of PB becoming…
Abstract
Purpose
In this paper, the authors focus on participatory budgeting (PB) as an organizational issue in local government. The aim of this study is to analyze the premises of PB becoming institutionalized in local governance by scrutinizing the factors that enable or disable PB as a collaborative innovation process, and that in turn build innovative capacity. The authors study how the collaborative innovation process constructs the innovation capacity of local government and further how this enables PB to institutionalize in local government. With this study, the authors deepen the understanding of PB as a collaborative innovation process that may encounter obstacles and hindrances, but also enablers and drivers for creating and transforming sustainable collaborative practices in local government.
Design/methodology/approach
In this paper, the authors present a case study from one Finnish local government, the city of Lahti. The authors employ multifaced empirical data collected from the city of Lahti in two PB rounds between 2019 and 2022. Data include surveys for citizens and employees and municipal councilors and altogether 24 interviews with employees and councilors. The authors also gathered data by observing the PB process in Lahti, taking parts in workshops and meetings between 2019 and 2022. Municipal documents were likewise used as data in this study.
Findings
The institutionalization of PB in a local government organization requires organizational innovation capacity, not only individuals who are keen, motived and committed to work on PB. However, the Lahti case shows that successful PB results from the citizens' viewpoint can on one hand be reached while simultaneously the sustainability of PB needs more organizational commitment and support that materializes into managerial activities. The authors found that adequate resourcing is a key question in the institutionalization of PB.
Originality/value
In the present study, the authors approach the often-neglected topic of PB from the professional viewpoint in public administration. The originality of the empirical setting is the multifaced data collection during the first two rounds of PB in Lahti. It is highly relevant to analyze PB in its early stages as the organizational difficulties and resistance are at the time at their highest. This study offers a unique perspective on to the initialization of a novel participatory method in a city where no such efforts on this scale have been implemented before.
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Sheshadri Chatterjee, Nripendra P. Rana and Yogesh K. Dwivedi
The purpose of this article is to identify how the organisations are able to improve their business value through acquisition of business analytics capabilities and by improving…
Abstract
Purpose
The purpose of this article is to identify how the organisations are able to improve their business value through acquisition of business analytics capabilities and by improving their performance.
Design/methodology/approach
With the help of literature survey, along with standard resource-based view framework, a conceptual model has been developed. These have been statistically tested by collecting the data using the survey questionnaire from 306 selected respondents from various service sector- and product-based organisations in India. To analyse the data we have used partial least square–based structural equation modelling.
Findings
The study highlights that by the help of data acquisition and tool acquisition as two vital components the acquisition of business analytics capabilities could improve the business value of the organisation by strengthening its organisational performance. The findings of this research also indicated that acquisition of business analytics capabilities has a significant influence on an organisation's business process performance and business decision, which in turn significantly influences organisational performance. And organisational performance eventually positively influences its business value. The model was found to provide an explanative power of 71%.
Research limitations/implications
The proposed research model can provide effective recommendations to the management of the organisations to realise the importance of acquisition of effective business analytics capabilities to eventually improve the business value of the organisation.
Originality/value
No specific studies, as yet, have analysed the effects of acquisition of business analytics capabilities for improving organisational performance mediated through business process performance and business decision. Therefore, this research has explored the distinctive effort to empirically validate this understanding.
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Roberto Falcão, Eduardo Cruz, Murilo Costa Filho and Maria Elo
The purpose of this paper is to discuss the issues in studying hard-to-reach or dispersed populations, with particular focus on methodologies used to collect data and to…
Abstract
Purpose
The purpose of this paper is to discuss the issues in studying hard-to-reach or dispersed populations, with particular focus on methodologies used to collect data and to investigate dispersed migrant entrepreneurs, illustrating shortcomings, pitfalls and potentials of accessing and disseminating research to hard-to-reach populations of migrant entrepreneurs.
Design/methodology/approach
A mixed methodology is proposed to access hard-to-reach or dispersed populations, and this paper explores these using a sample of Brazilian migrants settled in different countries of the world.
Findings
This paper explores empirical challenges, illustrating shortcomings, pitfalls and potentials of accessing and disseminating research to hard-to-reach populations of migrant entrepreneurs. It provides insights by reporting research experiences developed over time by this group of researchers, reflecting a “mixing” of methods for accessing respondents, contrasting to a more rigid, a-priori, mixed methods approach.
Originality/value
The main contribution of this paper is to showcase experiences from, and suitability of, remote data collection, especially for projects that cannot accommodate the physical participation of researchers, either because of time or cost constraints. It reports on researching migrant entrepreneurship overseas. Remote digital tools and online data collection are highly relevant due to time- and cost-efficiency, but also represent solutions for researching dispersed populations. These approaches presented allow for overcoming several barriers to data collection and present instrumental characteristics for migrant research.
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Thi Huyen Pham, Thuy-Anh Phan, Phuong-Anh Trinh, Xuan Bach Mai and Quynh-Chi Le
This study aims to ascertain the impact of data collecting awareness on perceived information security concerns and information-sharing behavior on social networking sites.
Abstract
Purpose
This study aims to ascertain the impact of data collecting awareness on perceived information security concerns and information-sharing behavior on social networking sites.
Design/methodology/approach
Based on communication privacy management theory, the study forecasted the relationship between information-sharing behavior and awareness of data collecting purposes, data collection tactics and perceived security risk using structural equation modeling analysis and one-way ANOVA. The sample size of 521 young social media users in Vietnam, ages 18 to 34, was made up of 26.7% men and 73.3% women. When constructing the questionnaire survey method with lone source respondents, the individual’s unique awareness and experiences with using online social networks (OSNs) were taken into account.
Findings
The results of the investigation demonstrate a significant relationship between information-sharing and awareness of data collecting, perceptions of information security threats and behavior. Social media users have used OSN privacy settings and paid attention to the sharing restriction because they are concerned about data harvesting.
Research limitations/implications
This study was conducted among young Vietnamese social media users, reflecting specific characteristics prevalent in the Vietnamese environment, and hence may be invalid in other nations’ circumstances.
Practical implications
Social media platform providers should improve user connectivity by implementing transparent privacy policies that allow users to choose how their data are used; have clear privacy statements and specific policies governing the use of social media users’ data that respect users’ consent to use their data; and thoroughly communicate how they collect and use user data while promptly detecting any potential vulnerabilities within their systems.
Originality/value
The authors ascertain that the material presented in this manuscript will not infringe upon any statutory copyright and that the manuscript will not be submitted elsewhere while under Journal of Information, Communication and Ethics in Society review.
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Value-based healthcare suggested using patient-reported information to complement the information available in the medical records and administrative healthcare data to provide…
Abstract
Purpose
Value-based healthcare suggested using patient-reported information to complement the information available in the medical records and administrative healthcare data to provide insights into patients' perceptions of satisfaction, experience and self-reported outcomes. However, little attention has been devoted to questions about factors fostering the use of patient-reported information to create value at the system level.
Design/methodology/approach
Action research design is carried out to elicit possible triggers using the case of patient-reported experience and outcome data for breast cancer women along their clinical pathway in the clinical breast network of Tuscany (Italy).
Findings
The case shows that communication and engagement of multi-stakeholder representation are needed for making information actionable in a multi-level, multispecialty care pathway organized in a clinical network; moreover, political and managerial support from higher level governance is a stimulus for legitimizing the use for quality improvement. At the organizational level, an external facilitator disclosing and discussing real-world uses of collected data is a trigger to link measures to action. Also, clinical champion(s) and clear goals are key success factors. Nonetheless, resource munificent and dedicated information support tools together with education and learning routines are enabling factors.
Originality/value
Current literature focuses on key factors that impact performance information use often considering unidimensional performance and internal sources of information. The use of patient/user-reported information is not yet well-studied especially in supporting quality improvement in multi-stakeholder governance. The work appears relevant for the implications it carries, especially for policymakers and public sector managers when confronting the gap in patient-reported measures for quality improvement.
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