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With the arrival of the big data era, governments have appointed a chief data officer (CDO) to meet the opportunities and challenges brought by big data. The existing research on the CDOs is very limited, and what does exist focuses primarily on what are CDOs do. Little research has explored how CDOs do. To fill this gap, this study employed ambidexterity theory to investigate the ambidexterity of CDOs’ impact on data-driven innovation.

To empirically test the model, a survey study was conducted to empirically test the model. Data were collected from 261 CDOs in government and government employees in big data management centers or bureaus. The collected data were analyzed quantitatively to answer hypotheses using a structural equation model.

The findings suggest that data exploitation and data exploration significantly influence data-driven leadership, culture and value propositions. Data-driven leadership and value propositions significantly impact government performance.

This study is one of the first attempts to investigate how CDOs work, especially when promoting data-driven innovation. In addition, this study extends ambidexterity theory into the issue of the CDO in government.

This paper aims to examine the effects on firms' outcomes of a new government regulation on the private security industry that aimed to enhance the selection and training processes for armed-private security officers.

By using human capital theory and using a data set built from various public sources, this study analyzes the effects of a new regulation implemented in 2013–2014 in Brazil mandating psychological assessments for hiring private security armed officers. Firm-level data and a Difference-in-Differences (DiD) identification strategy are used to investigate the effects on turnover and human capital outcomes.

The study identifies substantial changes resulting from the new government regulation in private security firms. While it has led to increased turnover rates, the regulation has also facilitated firms in enhancing the human capital composition of their workforce by enabling the recruitment of more experienced personnel.

This research informs to current debates on the effects of policy interventions on firm's outcomes by showing how regulations aimed to improve the configuration of human capital can generate win-win situations for both firms and citizens, despite the short-term trade-offs between higher turnover rates and improved human capital outcomes.

Refining selection and training processes can enhance the workforce in private security firms by replacing less capable professionals with more experienced ones. Insights from this study offer guidance to policymakers and industry practitioners in shaping effective business and public policies.

This study underscores the role of training and psychological assessments in enhancing the composition of human capital in the private security industry.

By highlighting the role of policy interventions in establishing barriers to unskilled workers engaging in hazardous activities, this study contributes to the burgeoning literature in strategic management on the interaction between policy interventions and firm outcomes.

This article investigates different terms and concepts of paradox dimensions in Public Administration because these terms are often used interchangeably. The aim is to reveal the theoretically based macro-level concepts and establish a common ground for a shared dialogue about managing paradoxes in the field.

This article uses a complementary review approach. First, a systematic literature review is executed to identify the macro-level paradox concepts and to capture their theoretical common ground. Second, the problematizing literature review aims to reflect Public Administration literature with literature from outside the field, mainly from Organization Studies and General Management.

For the most part, the macro-level paradox concepts in Public Administration are used to illustrate the context or situation of another research topic, rather than as standalone theories to be conceptually or empirically explored. In 63 out of 589 articles, we found a theoretical definition of the mentioned macro-level paradox concept. This definition refers mainly to the sources of paradoxical situations and focuses less on the decisions and reactions thereto. Based on the review findings, an analytical model for the management of paradoxical situations in the public sector is provided and applied, followed by recommendations for further research.

This article aims to combine the macro-level paradox concepts in Public Administration with the insights of Paradox Theory and reveals that paradoxes could be a core topic in the field. Scholars in Public Administration could approach paradoxical situations from their own perspective while simultaneously strengthening the field’s identity by encouraging multiperspectivity.

Social media platforms are highly visible platforms, so politicians try to maximize their benefits from their use, especially during election campaigns. On the other side, people express their views and sentiments toward politicians and political issues on social media, thus enabling them to observe their online political behavior. Therefore, this study aims to investigate user reactions on social media during the 2016 US presidential campaign to decide which candidate invoked stronger emotions on social media.

For testing the proposed hypotheses regarding emotional reactions to social media content during the 2016 presidential campaign, regression analysis was used to analyze a data set that consists of Trump’s 996 posts and Clinton’s 1,253 posts on Facebook. The proposed regression models are based on viral (likes, shares, comments) and emotional Facebook reactions (Angry, Haha, Sad, Surprise, Wow) as well as Russell’s valence, arousal, dominance (VAD) circumplex model for valence, arousal and dominance.

The results of regression analysis indicate how Facebook users felt about both presidential candidates. For Clinton’s page, both positive and negative content are equally liked, while Trump’s followers prefer funny and positive emotions. For both candidates, positive and negative content influences the number of comments. Trump’s followers mostly share positive content and the content that makes them angry, while Clinton’s followers share any content that does not make them angry. Based on VAD analysis, less dominant content, with high arousal and more positive emotions, is more liked on Trump’s page, where valence is a significant predictor for commenting and sharing. More positive content is more liked on Clinton’s page, where both positive and negative emotions with low arousal are correlated to commenting and sharing of posts.

Building on an empirical data set from Facebook, this study shows how differently the presidential candidates communicated on social media during the 2016 election campaign. According to the findings, Trump used a hard campaign strategy, while Clinton used a soft strategy.

This paper aims to identify the mechanism through which consumer empowerment, created via the Facebook brand page (FBBP), is transformed into brand page stickiness. Specifically, a model examining the mediating role of FBBP experience and the moderating role of brand love is proposed and tested.

Data from 283 FBBP users were analyzed using structural equation modeling with partial least squares.

The findings reveal the positive effect of consumer empowerment and brand page experience on brand page stickiness. The mediating role of brand page experience and the moderating role of brand love were prominent in the consumer empowerment–brand page stickiness link.

This paper is novel in inaugurating the association between consumer empowerment and FBBP stickiness, which is mediated by brand experience and moderated with brand love. This paper enriches the understanding of how brand page stickiness can be enhanced in the social media context.

This paper guides managers to best utilize FBBP to create a pleasant experience and yield stickiness.

This study aims to examine the correlation between the readability of financial statements and the likelihood of future stock price crashes in nonfinancial companies listed on the Egyptian Stock Exchange. It further explores the possible moderating effect of audit quality on this relationship.

The study uses ordinary least squares regression, generalized least squares estimation and two-stage least squares methodology to examine and validate the research hypotheses. The sample comprises 107 nonfinancial companies registered on the Egyptian Stock Exchange from 2016 to 2019.

The results reveal a significant negative association between the readability of financial statements and stock price crash risk. This suggests that companies with more complex financial statements tend to experience higher future crash risks. Additionally, the study identifies audit quality as a significant moderating factor. Higher audit quality, often indicated by engagements with Big-4 audit firms, strengthens the influence of financial statements readability on stock price crash risk. This implies that while high audit quality enhances investor confidence and market stability, it also accentuates the negative consequences of complex financial statements.

The findings of this paper have significant implications for regulators and standard-setting bodies in Egypt. They should consider refining and revising existing standards to emphasize the importance of enhancing the readability of financial reports. Additionally, auditing firms should actively engage in efforts to ensure clearer and more transparent financial reporting. These actions are vital for boosting investor confidence, strengthening Egypt’s capital market and mitigating potential risks associated with information opacity and complexity.

This study represents a pioneering endeavor within the Arab and Egyptian financial environments. To the best of the author’s knowledge, it is the first examination of the association between the readability of financial statements and stock price crash risk in these contexts. Furthermore, it explores factors such as audit quality that may influence this connection.

This investigation is designed to quantify and appraise the efficiency of resource distribution in the provision of public digital cultural services in China. By acknowledging and incorporating the realities of China's social development, the authors offer recommendations for enhancement derived from the study’s data analysis results. The research zeroes in on the dissection and analysis of the integral elements that structure the provision of public digital cultural services, and it concentrates on the associated data computation. The conclusions drawn herein are expected to serve as a significant point of reference for ongoing academic investigations and practical explorations in affiliated domains.

In this research, the authors utilize a hybrid methodology to meticulously evaluate the efficiency of the components that underpin the provision of public digital cultural services (PDCS) in China. The authors embark on deconstructing the various constituents within the PDCS supply framework, conducting in-depth analyses and providing cogent interpretations of each integral element. Subsequently, the authors deploy the well-regarded SBM super-efficiency model to ascertain the operational efficiency of these components. Ultimately, through a comprehensive interpretation of the measured data and the integration of extant societal development conditions, the authors put forth relevant recommendations.

The provision of PDCS in China as of 2021 had been characterized by overall good efficiency, significant regional disparity and a disconnect between inputs and outputs with weak correlations to economic and demographic data.

In this study, the authors provide an exhaustive deconstruction and interpretation of the public digital cultural services supply system, thereby proposing a framework for evaluating the efficiency of supply element allocation. Additionally, the authors have determined a set of distinct measurable indicators that are readily accessible for open collection. Notably, this analytical and evaluative framework designed for element analysis and measurement may also find application in efficiency evaluation research of the supply systems of other related cultural endeavors.

Drawing upon uses and gratifications (U&G) theory and customers' online brand-related activities framework, the present study aims to examine the influence of customers’ motivations to engage with brand-related social media content on different social media engagement behaviors (consumption, contribution and creation) and brand-related outcomes (brand trust and brand loyalty) in the quick service restaurant (QSR) context.

Based on a self-administered survey dataset of 500 social media users who are customers of QSR brands, partial least square structural equation modeling is used to verify the hypotheses.

Results showed that interactivity motivation and information motivation drive all the social media engagement behaviors (consumption, contribution and creation). The results also confirmed the mediating effect of brand trust on the relationship between two levels of social media engagement behaviors (consumption and contribution) and brand loyalty.

To entice customers to engage with QSR brands on social media, social media marketing managers should incorporate elements of interactivity, information, entertainment and incentive into QSR social media brand posts rather than relying solely on delivering social media content in a variety of ways such as photos, videos and status updates.

This study makes a novel contribution to hospitality and social media engagement literature, thus uncovering opportunities for managers to engage their customers on social media.

The home page design of a digital news website is a key factor in determining its attractiveness to readers. This study aims to propose an approach to manage the frequent adjustment of the dynamic layout of the news content on the website home page in a real-time environment to increase its attractiveness to readers.

This paper shows that this news website layout design problem can be modeled as an optimization problem based on the information of news contents that change within a multiple-period planning horizon similar to the dynamic facility layout problem. A hybrid genetic algorithm-based approach integrated with local search heuristic methods is also proposed to improve the solution.

This paper finds that the DPLP model is effective in modeling the changing layout of a digital news website. The problem can solved in a timely manner using the proposed hybrid genetic algorithm.

This paper was based on hypothetical data and on the assumption of equal section size. Actual data would help fine-tune the application of the dynamic facility layout model. As well the algorithm could be enhanced for unequal size sections.

The model should help online newspapers apply sophisticated algorithms to optimize the layout of news websites dynamically in a timely manner.

News websites are increasingly the desired medium to consume news. So it has an important role in educating society. Thus optimizing and improving the process will help in this regard.

To the best of the authors’ knowledge, this paper is the first one to apply the DPLP model to the digital newspaper website dynamic design problem.

The study aims to pioneer an innovative approach for the evaluation of government portal websites (GPWs) by introducing an eye-tracking-based method. The research meticulously pinpoints and analyses the distinct usability issues and challenges that users encounter while navigating and interacting with GPWs.

This study devises an eye-tracking-based GPW usability evaluation approach, which focuses on the major functions (i.e. government information disclosure, government services and interactive responses) of GPWs. An Entropy Weighted Technique for Order Preference by Similarity to an Ideal Solution (EW-TOPSIS) method is employed to process eye-tracking indicator results for deriving GPW usability results.

The proposed approach is demonstrated to assess the usability of 12 GPWs in pilot smart cities in China, and it is found that most GPWs have lower-than-average usability. GPWs with low usability require more cognitive load that exhibit increased fixation and saccade. The comparisons among the GPW usability results from (1) the eye-tracking experiment, (2) questionnaire surveys and (3) the ready-made performance evaluation report validate the effectiveness of eye-tracking-based GPW usability evaluation.

The work contributes to shifting the GPW usability evaluation approach from a subjective judgment paradigm to an objective paradigm, as well as provides implications for enhancing GPW usability, including improving search function, reducing website complexity and prioritizing user needs.