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This study aims to contribute to the social media agility literature by examining the impact of perceived social media agility on customer purchases. More specifically, this study seeks to reveal whether perceived social media agility positively affects customer purchases. Furthermore, this study examines the moderating roles of social media self-efficacy and social anxiety to increase the model's explanatory power. That is, this study investigates whether social media self-efficacy positively moderates the impact of perceived social media agility on customer purchases. Similarly, this study examines whether social anxiety negatively moderates the impact of perceived social media agility on customer purchases.

An online survey was conducted on Qualtrics platforms to test the research hypotheses. To test the main effect, a linear regression was used. To test moderating relationships, PROCESS Macro Model 1 was used. Finally, the moderating effects were probed with the Johnson–Neyman technique to gain further insights into the interaction effects.

The study results show that when customers perceive a brand as agile on social media platforms, they are more willing to buy the goods/services of the brand. Notably, individuals who are high on social media self-efficacy (relative to low on it) display more willingness to purchase the brand's products/services. However, customers who are high on social anxiety (relative to low on it) are less willing to purchase the brand's products/services.

This study examines the effect of perceived social media agility on customer purchases while accounting for the moderating role of perceived social media self-efficacy and social anxiety. The results provide noteworthy theoretical and managerial contributions.

In response to shortages in personal protective equipment (PPE) during the COVID-19 pandemic, makers, community groups and manufacturers around the world utilised 3D printing to fabricate items, including face shields and face masks for healthcare workers and the broader community. In reaction to both local and global needs, numerous designs emerged and were shared online. In this paper, 37 face shields and 31 face masks suitable for fused filament fabrication were analysed from a fabrication perspective, documenting factors such as filament use, time to print and geometric qualities. 3D print times for similar designs varied by several hours, meaning some designs could be produced in higher volumes. Overall, the results show that face shields were approximately twice as fast to 3D print compared to face masks and used approximately half as much filament. Additionally, a face shield typically required 1.5 parts to be 3D printed, whereas face masks required five 3D printed parts. However, by quantifying the print times, filament use, 3D printing costs, part dimensions, number of parts and total volume of each design, the wide variations within each product category could be tracked and evaluated. This data and objective analysis will help makers, manufacturers, regulatory bodies and researchers consolidate the 3D printing response to COVID-19 and optimise the ongoing strategy to combat supply chain shortages now and in future healthcare crises.

This paper examines the impact of state control on stock price crash risk given whether and how ownership structure affects stock price crash risk is relatively underexplored.

The sample includes 2,285 Chinese firms listed in the Shanghai and Shenzhen Stock Exchanges. Panel data is used for conducting the analysis and endogeneity is addressed with instrumental variable estimation and by testing how stock price crash risk is affected when the ultimate controller changes from a private-owned company to a state-owned enterprise.

The authors find that state control is negatively associated with future stock price crash risk. The mechanism analysis shows that state control reduces stock price crash risk through the implementation of conservative corporate policies. Furthermore, the impact of state control is more pronounced with more intensive state involvement, e.g. in strategic industries and when a company's ultimate controller is a non-corporate government agency or the central government.

This paper enriches the literature on the controversy of the role of state control and the results of this study highlight the importance of the conservatism of state control on reducing stock return tail risk. The authors also add to the literature on the importance of the policy-risk sharing effect of state ownership.

This study aimed to develop a taxonomy of research areas in open government data (OGD) through a bibliometric mapping tool and a qualitative analysis software.

In this study, the authors extracted metadata of 442 documents from a bibliographic database. The authors used a bibliometric mapping tool for familiarization with the literature. After that, the authors used qualitative analysis software to develop taxonomy.

This paper developed taxonomy of OGD with three research areas: implementation and management, architecture, users and utilization. These research areas are further analyzed into seven topics and twenty-eight subtopics. The present study extends Charalabidis et al. (2016) taxonomy by adding two research topics, namely the adoption factors and barriers of OGD implementations and OGD ecosystems. Also, the authors include artificial intelligence in the taxonomy as an emerging research interest in the literature. The authors suggest four directions for future research: indigenous knowledge in open data, open data at local governments, development of OGD-specific theories and user studies in certain research themes.

Early career researchers and doctoral students can use the taxonomy to familiarize themselves with the literature. Also, established researchers can use the proposed taxonomy to inform future research. Taxonomy-building procedures in this study are applicable to other fields.

This study developed a novel taxonomy of research areas in OGD. Taxonomy building is significant because there is insufficient taxonomy of research areas in this discipline. Also, conceptual knowledge through taxonomy creation is a basis for theorizing and theory-building for future studies.

Since the development of the COVID-19 vaccinations, questions surrounding race have been prominent in the literature on vaccine uptake. Early in the vaccine rollout, public health officials were concerned with the relatively lower rates of uptake among certain racial/ethnic minority groups. We suggest that this may also be patterned by racial/ethnic residential segregation, which previous work has demonstrated to be an important factor for both health and access to health care.

In this study, we examine county-level vaccination rates, racial/ethnic composition, and residential segregation across the U.S. We compile data from several sources, including the American Community Survey (ACS) and Centers for Disease Control (CDC) measured at the county level.

We find that just looking at the associations between racial/ethnic composition and vaccination rates, both percent Black and percent White are significant and negative, meaning that higher percentages of these groups in a county are associated with lower vaccination rates, whereas the opposite is the case for percent Latino. When we factor in segregation, as measured by the index of dissimilarity, the patterns change somewhat. Dissimilarity itself was not significant in the models across all groups, but when interacted with race/ethnic composition, it moderates the association. For both percent Black and percent White, the interaction with the Black-White dissimilarity index is significant and negative, meaning that it deepens the negative association between composition and the vaccination rate.

The analysis is only limited to county-level measures of racial/ethnic composition and vaccination rates, so we are unable to see at the individual-level who is getting vaccinated.

We find that segregation moderates the association between racial/ethnic composition and vaccination rates, suggesting that local race relations in a county helps contextualize the compositional effects of race/ethnicity.

The authors probe the relationships between country institutional support for entrepreneurship and new venture survival. Specifically, the authors unpack the nuanced influences of entrepreneurs' perceived environmental uncertainty and their subsequent entrepreneurial behavioral profiles and how this particularly bolsters venture survival in contexts with underdeveloped institutions for entrepreneurship.

Coleman (1990) ‘bathtub’ framework is applied to develop a model and propositions surrounding how and when emerging market entrepreneur's perceptions of their countries institutional support toward entrepreneurship can ultimately enhance new venture survival.

Entrepreneurs' interpretations of regulatory, cognitive and normative institutional support for private enterprise helps them embrace uncertainties more accurately reflective of “on the ground” realities and stimulates constructive entrepreneurial behaviors. These are critical for increasing survival prospects in characteristically turbulent, emerging market contexts that typically lack reliable formal resources for cultivating nascent ventures.

This paper has implications for international policymakers seeking to stimulate and sustain entrepreneurial ventures in emerging markets. The authors shed light on the practical importance of understanding the social realities and interpretations of entrepreneurs in a given country relating to their actual perceptions of support for venturing—cautioning a tendency for outsiders to over-rely on aggregated econometric indices and various national ‘doing business' rankings.

This study is the first to create a conceptual framework on the mechanisms of how entrepreneurs in emerging economies affect new venture survival. Drawing on Coleman's bathtub (1990), the authors develop propositional arguments for a multilevel sequential framework that considers how developing economies' country institutional profiles (CIP) influence entrepreneurs' perceptions of environmental uncertainty. Subsequently, this cultivates associated entrepreneurial behavior profiles, which ultimately enhance (inhibit) venture survival rates. Further, the authors discuss the boundary conditions of this regarding how the national culture serves to moderate each of these key relationships in both positive and negative ways.

The disparities of COVID-19 vaccination rates between the rural and urban areas have become apparent during this pandemic. There is a need to understand the root causes of vaccine hesitancy demonstrated by the rural population to increase coverage and to contain the disease spread throughout the United States. This study aimed to explore other factors influencing vaccine hesitancy among rural dwellers besides the geography-related barriers such as poor health care access and individuals having no or suboptimal insurance coverage.

By reviewing existing data and literature about vaccination, health literacy, and behaviors, and prevailing ideologies, we discuss the potential causes of vaccine hesitancy in rural areas that could create barriers for successful public health efforts related to vaccine coverage and provide suggestions to ameliorate the situation.

Geography-related barriers, health literacy, and preconceived notions are key determinants of adopting healthy behaviors and complying with public health authorities' recommendations among rural individuals during a public-health crisis. We argue that ideology, which is much deeper than preconception or misconception on vaccination, should be incorporated as a key factor to redefine the term “vulnerable populations” in public health research.

The limitation of our study is that we have not found an effective way to encourage the populations who hold conservative religious and political ideologies to join the efforts for public health. Even though geography-related barriers may strongly impact the rural dwellers in achieving optimal health, the various forms of ideologies they have toward certain health behaviors cannot be discounted to understand and address vaccine-related disparities in rural areas. There is a need to redefine the term “vulnerable population” particularly as it relates to rural areas in the United States. During large-scale public health disasters, scholars and public health authorities should consider the ideologies of individuals, in addition to other factors such as race/ethnicity, area of residence (rural vs. urban), and socioeconomic factors influencing the existing vulnerabilities and health disparities.

Forecasting demand of emergency supplies under major epidemics plays a vital role in improving rescue efficiency. Few studies have combined intuitionistic fuzzy set with grey-Markov method and applied it to the prediction of emergency supplies demand. Therefore, this article aims to establish a novel method for emergency supplies demand forecasting under major epidemics.

Emergency supplies demand is correlated with the number of infected cases in need of relief services. First, a novel method called the Intuitionistic Fuzzy TPGM(1,1)-Markov Method (IFTPGMM) is proposed, and it is utilized for the purpose of forecasting the number of people. Then, the prediction of demand for emergency supplies is calculated using a method based on the safety inventory theory, according to numbers predicted by IFTPGMM. Finally, to demonstrate the effectiveness of the proposed method, a comparative analysis is conducted between IFTPGMM and four other methods.

The results show that IFTPGMM demonstrates superior predictive performance compared to four other methods. The integration of the grey method and intuitionistic fuzzy set has been shown to effectively handle uncertain information and enhance the accuracy of predictions.

The main contribution of this article is to propose a novel method for emergency supplies demand forecasting under major epidemics. The benefits of utilizing the grey method for handling small sample sizes and intuitionistic fuzzy set for handling uncertain information are considered in this proposed method. This method not only enhances existing grey method but also expands the methodologies used for forecasting demand for emergency supplies.

1. An intuitionistic fuzzy TPGM(1,1)-Markov method (IFTPGMM) is proposed.

2. The safety inventory theory is combined with IFTPGMM to construct a prediction method.

3. Asymptomatic infected cases are taken to forecast the demand for emergency supplies.

An intuitionistic fuzzy TPGM(1,1)-Markov method (IFTPGMM) is proposed.

The safety inventory theory is combined with IFTPGMM to construct a prediction method.

Asymptomatic infected cases are taken to forecast the demand for emergency supplies.

This paper aims to investigate the potential influence of managers on sustainability assurance. When the quality of sustainability reporting is questionable because of subsequent restatements, the authors explore whether assurance is used to enhance its credibility as a legitimization tool or as an impression management strategy. Additionally, the authors analyze how capital markets react to this potential managerial capture and, particularly, whether investors penalize this practice through the cost of capital.

Using an international sample from 2012 to 2016 and panel data regressions, this study relies on DICTION’s master variables of optimism and certainty to examine the impact of managers on assurance and the market’s reaction to these practices.

The study shows that some managers might use assurance as a legitimization tool rather than as a means of reinforcing the credibility of sustainability reporting. In such cases, the results reveal that investors penalize (reward) managerial influence (no influence) on assurance.

The new findings help companies understand that they will not improve their financing terms if investors perceive that managers have influenced assurance. Moreover, these findings emphasize the need for standardization to clarify assurance criteria and prevent managerial influence.

Managerial influence on assurance raises doubts about its value in terms of reducing information asymmetry and especially improving investors’ decision-making.

The present study represents the first evidence of the potential use of assurance for non-informative purposes. The authors provide clear evidence of how investors penalize managerial influence on assurance, in contrast to the mainstream literature, which shows that this practice always improves investors’ decision-making and is rewarded.