Abstract
Purpose
This research aims to understand how organizational workplace meetings surrounding the COVID-19 pandemic impacted logistics Airmen across the United States Air Force and how these meetings impacted their risk seeking behavior on social media.
Design/methodology/approach
This survey research tested an extended Planned Risk Information Risk Seeking Model (PRISM) with organizational meetings as an antecedent to determine if current meetings influenced an Airman's perceived behavioral control, attitude toward seeking, subjective norms, knowledge sufficiency and intention to seek information regarding COVID-19.
Findings
Results of the CFA showed that the expanded PRISM model had good model fit. Additionally, using a custom dialog PROCESS macro in SPSS, it was found that perceptions of existing meetings were directly, positively related to attitude toward seeking, subjective norms and perceived behavioral control, and indirectly related to knowledge sufficiency threshold and information seeking. Theoretical and managerial implications are discussed.
Originality/value
This research adds to the limited body of knowledge of crisis communication and effectively expands the PRISM model to include an antecedent that helps explain information seeking during times of uncertainty.
Keywords
Citation
Roberts, M.D., Price, C.T. and Joo, S.-J. (2023), "Influencing air force logisticians' information seeking during the COVID-19 pandemic: the role of organizational meetings in an expanded PRISM framework", Journal of Defense Analytics and Logistics, Vol. 7 No. 1, pp. 29-47. https://doi.org/10.1108/JDAL-03-2023-0002
Publisher
:Emerald Publishing Limited
Copyright © 2022, In accordance with section 105 of the US Copyright Act, this work has been produced by a US government employee and shall be considered a public domain work, as copyright protection is not available
Introduction
When the United States Air Force (USAF) Chief of Staff General Charles Q. Brown took office in 2020, his action order for the Air Force was simple, “Accelerate Change or Lose” (Price, 2022). This plan was put to the test in the face of the COVID-19 pandemic. The pandemic generated an extreme level of uncertainty, not only for the Air Force, but for the entire world (Guo and Cannela 2021). As the COVID-19 virus spread throughout the globe, some governments reacted by locking down portions of their economy and populace, and industries reacted by cutting back on services provided or shut down entirely (Foss, 2021). However, the Air Force, and all of the military departments, does not have the luxury of completely shutting down. In a similar vein as police, firemen and other first responders, Air Force personnel are considered essential workers (Rouleau et al., 2021). The Air Force must be able to sustain operations throughout the current and future pandemics to ensure it can fully perform its mission. This is especially true for logistics organizations which are believed to be the key enabler of US military power and the foundation for military operations (Choate, 2020). Due to the importance of logistics organizations in the Air Force, logistics personnel had to remain safe throughout the pandemic to ensure the success of their organizations. With more than 350,000 deaths in the United States due to COVID-19 in 2020 alone, this may not have been an easy task (CDC, 2022). There is little doubt that the pandemic highlighted the importance of General Brown's plan to accelerate change and served as a catalyst for changing the way the Air Force operates on a day-to-day basis.
In Gen Brown's action order, he states, “The world is changing in many ways. Today we operate in a dynamic environment with factors that have us taking various actions to continue the mission and take care of Airmen and Families … If we don't change – if we fail to adapt – we risk losing the certainty with which we have defended our national interests for decades” (Brown, 2020). In the dynamic environment caused by the pandemic, the manner in which Air Force organizations communicated may have been key to continuing the mission and keeping Airmen and their families safe. After all, one of the most important factors in responding to and preventing the spread of, the COVID-19 virus is effective communication (Finset et al., 2020; Reddy and Gupta, 2020). Even more specifically, risk communication, communication between people facing threats, via social media allows for the exchange of real-time information (Abrams and Greenhawt, 2020).
Social media is one of the communication mediums used by USAF wing-level organizations to provide their personnel with information about the COVID-19 pandemic (Price, 2022). This should come as no surprise since the Air Force understands that social media is the primary tool used by Airmen for communication and networking (Department of the Air Force Public Affairs, 2021). The current guidance from the Air Force's Public Affairs is that social media can be used as a bridge to help those unfamiliar with the military understand more about the services, help shape conversations about mission and connect with their Airmen on a more personal level (Department of the Air Force Public Affairs, 2021).
New ways of communicating may have been needed due to the impact the pandemic had on operations in the Air Force. From interviews conducted with multiple logistics personnel across several Air Force organizations, a common operational theme emerged. Split shifts, one where organizations were separated into “A” and “B” teams that did not interact face-to-face, were used to protect the organization against losing personnel to COVID-19 infections and/or quarantine requirements. This separation of personnel was cited as a major reason for the increased importance of communication and new ways of passing along important information regarding the pandemic. Although social media was used to communicate information regarding the pandemic with Air Force personnel, it is unclear whether that communication was actually effective in getting the message across or if Airmen were actually influenced to seek out that information.
Due to the critical importance of communication during the COVID-19 pandemic, this research seeks to evaluate the effectiveness of pandemic communication in the Air Force. More specifically, the goal of this research is to evaluate USAF logistics Airmen's perceptions of the effectiveness of their existing workplace meetings and wing's social media communication regarding the COVID-19 pandemic and to discover what influences them to seek information regarding the COVID-19 pandemic. Ultimately, results of this study can be used to help improve existing meetings and communication methods regarding the COVID-19 pandemic and future crises. This research is much needed for a number of reasons. First, the pandemic highlighted shortcomings in current corporate communication and internal crisis communication research (Adamu and Mohamad, 2019; Frandsen and Johansen, 2011; Guo and Canella, 2021; Mazzei and Butera, 2021). Guo and Canella (2021) explain that due to the extreme level of uncertainty, information disorder and the overwhelming amount of information available during the pandemic, communication during a crisis is different than typical communication that is studied. Furthermore, we live in a risk society where lessons learned from the COVID-19 pandemic may prove extremely useful in the future (Rouleau et al., 2021). Rouleau et al. (2021) explain that no one should have been surprised by COVID-19 because the idea of a global pandemic was around since 2017. Additionally, Ebola, H1N1, the 1918 Spanish flu are prime examples of pandemics in the past. It is not a reach to believe a future pandemic could occur, and the COVID-19 pandemic allows us the opportunity to study a crisis as it was unfolding. To address the problem, a method to evaluate the effectiveness of our pandemic communication to our internal stakeholders is needed. We seek to determine if an expanded planned risk information seeking model (PRISM) can serve as this tool. The PRISM provides a broad framework for trying to understand what motivates people to seek health and risk information. We add to this model by including perceptions of existing organizational meetings to the framework.
Theoretical background and model development
Effective communication
Although there is no singular definition for effective communication, effective communication is often used to describe a way to connect with others to create mutually satisfying outcomes (Lasater, 2019). There have been several factors identified that may contribute to communication being effective. Reddy and Gupta (2020) highlighted when an organization or individual performs effective communication, several factors are key: effective communication must be provided to the recipient ahead of time to minimize impact of risk, it should be polite, imaginative, contemporary, valuable, efficient, synergetic, enlightening, transparent and authentic. They go on to say that communication should exist at every hierarchy in an organization and should flow vertically both up and down the chains of command, horizontally to peers, co-workers and other departments, as well as diagonal when applied appropriately, such as going to one of your supervisors peers to ask for technical expertise. Effective communication is important because research has shown that effective communication in an organization can drive better performance of its members (Leje et al., 2019).
Effective communication for organizational success
Effective communication has routinely been linked to organizational impacts; however, researchers agree there is no one-size-fits-all model to test these impacts. For instance, Eunson (2007) believes that due to the complexity of the communication field, it is not possible to create a model to answer all types of questions about communication. He does believe that you can tailor models down to specific instances to analyze effective workplace communication. Effective communication within organizations has been proven to increase trust between members, build stronger relationships and help organizations achieve their goals faster (Barker and Gower, 2010).
It is also important to understand that different mediums of communication impact members of groups in various ways. As an example, in Sweden, it was found that workplace meetings had a distinct health-promoting value and gave workers the opportunity to influence decision making (Bergman et al., 2016). Before Air Force operations take place, there must be communication regardless of if it is through meetings, email, electronic systems, cellular phone, etc. Internal Air Force communication occurs when the organization directly communicates to its members at home station and deployed. The Air Force externally communicates when its audience is mass media, congressional members and foreign dignitaries. All the Air Force's internal and external audience members are critical to the Air Force's communication strategy and global reach as noted by former Chief of Staff of the Air Force Gen Mark A. Welsh III (Board, A.F.S. and National Academies of Sciences, Engineering and Medicine, 2016). The United States Air Force may be able to capitalize on effective communication research which will help build stronger teams at every hierarchal level ultimately increasing mission readiness, especially in times such as the COVID-19 pandemic.
Growth use of social media as a communication method
As previously stated, effective communication between an organization's members has been shown to expedite goal achievement. There are alternative means of communication and one of the more dynamic forms is social media. Social media has experienced exponential growth within the past 2 decades. In 2005, when the Pew Research Center (2022) began tracking social media usage it found only five percent on Americans used social media. By contrast that number had risen to 50% around late May 2011 and up to 72% early February 2021. Even as the amount of usage grows over time, the data shows that there are clusters of closely related groups. In most countries, younger adults between the ages of 18–29 have much higher social media usage than adults of age 50 or older as shown (Schumacher and Kent, 2020). According to the Air Force Personnel Center, as of 30 June 2021, the average age of the enlisted force is 28 years old with 44% of enlisted members being under 26. Being that the enlisted members account for 81% of the 326,885 active-duty members it is important to understand that they use social media more frequently than previous generations of Airmen.
Facebook is the most active social media site in the world with over 2.7 billion active monthly users. As many as 49% of Facebook users claim they visit the site several times a day, 70% of adults log on their Facebook accounts daily and up to about 87% who claim they log on at least weekly (Auxier and Anderson, 2021). Since Facebook is the most actively used social media platform and the primary tool used by Airmen for communication and networking, the Air Force should ensure Airmen are motivated to look for Air Force information on Facebook and ensure that information is being effectively communicated.
Crisis communication and social media
Crisis communication recently evolved from risk communication and includes communication strategies to address ongoing public health challenges, such as global pandemics (Malecki et al., 2021). Coombs (2015, p. 3) defines a crisis as “an unpredictable event that threatens important expectancies of stakeholders and can seriously impact an organization's performance and generate negative outcomes.” There is little doubt that the COVID-19 pandemic meets the definition of a crisis, and as such, we may be able to learn from recent literature regarding crisis communication. Recent crisis communication literature investigates the role social media plays in informing and influencing the public regarding the actual crisis that is occurring.
Xu (2020) conducted a meta-analysis of 8 studies to determine if the communication medium matters when it comes to crisis communication. The study focused on persuasiveness and crisis responsibility and found that, compared to traditional media, social media lessened consumers' perceived crisis responsibility. This difference was stronger for fictitious organizations, however. When it came to persuasiveness, no difference was found between traditional and social media. These results hint that social media may be an effective medium for crisis communication. Oh et al. (2020) investigated the effects of social media use on preventive behaviors during the 2015 Middle East Respiratory Syndrome coronavirus (MERS-CoV) outbreak in South Korea. The researchers explored the mediating role of fear and anger on the relationships between social media use, risk perception and preventive behaviors and found that social media use was positively related to fear and anger. Furthermore, fear and anger mediated the positive relationship between social media use and risk perception, and social media use was found to significantly increase preventive behaviors. Similar themes are found throughout the literature where researchers study the impact social media use may have on the public during crises, and results have shown social media can be effective (Barbe and Pennington-Gray, 2018; Christensen and Lagreid, 2020; Dalrymple et al., 2016; Lwin et al., 2018). With the growth of social media and its impact on crisis communication, it is not a question of whether or not to integrate social media into crisis management, but a question of how (Jin et al., 2014). However, the research efforts mentioned above focus on external communication to the general public during a crisis instead of internal communication to the organization. Internal crisis communication, where all organizational members are receivers, senders and sense-makers of information, is an important yet understudied dimension of crisis communication (Adamu and Mohamad, 2019; Frandsen and Johansen, 2011; Mazzei and Butera, 2021). The importance of internal crisis communication cannot be understated, as it is considered a necessary element for managing a crisis and preventing future crises (Frandsen and Johansen, 2017). Therefore, this current research adds to the limited body of knowledge regarding social media and internal crisis communication.
Expanded planned risk information seeking model and hypotheses
Because there is no one clear definition or method to determine if communication has been effective, one can look to other means or models to make this determination. One such model is the Planned Risk Information Seeking Model (PRISM) (Kahlor, 2010). PRISM (as shown in Figure 1) has its roots in the Theory of Planned Behavior, Griffin et al.’s (1999) Risk Information Seeking and Processing Model (RISP), and Freimuth et al.’s (1989) Health Information Acquisition Model (HIAM).
PRISM provides a broad framework for trying to understand what motivates people to seek health and risk information and treats risk information seeking as a deliberate behavior (Kahlor, 2010). Relevant channel beliefs, also known as attitude towards seeking (ATS), are an individual's beliefs about the communication channels that will provide them information on the topic of interest. These beliefs of an individual can be gauged on if they view it as useful, trustful, beneficial, etc. Prior research suggests that ATS interacts positively with information insufficiency (Inf-Ins) and information seeking (SEEK) (Griffin et al., 1999). Inf-Ins is a variable proposed by Griffin et al. (2004) to gauge a person's judgmental confidence. Current knowledge combined with sufficiency threshold are needed to test a person's Inf-Ins. The size of the gap between current knowledge and information needed will affect the information seeking to learn more about the risk. PRISM suggests that Inf-Ins is the gap between what people know and what they think they need to know to feel confident enough to act on behavior with any given risk (Huurne et al., 2009).
ATS will be positively related to Inf-Ins.
ATS will be positively related to SEEK.
Inf-Ins will be positively related to SEEK.
Informational subjective norms (SN) are how people are inclined to act based on social norms (Yang and Kahlor, 2013). SN can be defined as normative influences that causes a person to perform behaviors based on those past communication experiences. Social environments have been shown to increase an individual's desire to seek knowledge. If individuals believe other people expect them to possess a certain level of knowledge, then they are more inclined to seek information. Prior research has shown a positive relationship between SN and SEEK (Griffin et al., 2008). Similarly, the more an individual is motivated to seek out information, it can be expected that individual's knowledge on the subject would increase.
SN will be positively related to Inf-Ins.
SN will be positively related to SEEK.
Perceived seeking control, also known as perceived behavioral control (PBC), is the belief that an individual has control over their actions. PBC is assessed by the ease or difficulty of a behavior (Wallston and Baltes, 2001) and is comprised of two dimensions. First a person must be able to access information. The other dimension is the ability to understand the information that they have accessed. Several studies have found a positive relationship between PBC and current knowledge (Kahlor et al., 2006; Griffin et al., 2008; Huurne et al., 2009). PBC is also believed to be positively related to information seeking behavior (Yang and Kahlor, 2013).
PBC will be positively related to Inf-Ins.
PBC will be positively related to SEEK.
This current research effort builds upon the PRISM and includes perceptions of existing meetings (OM) to see how it influences the other factors that play a role into risk information seeking. OM is a measure of how an individual feels regarding a meeting's (1) social presence, (2) communication effectiveness and (3) communications interface (Chidambaram and Jones, 1993). Social presence is when the communication medium allows members of the group to perceive a physical sensation of the communicator (Short et al., 1976). Social presence has been measured by personalness, sensitiveness, sociability and warmth (Short et al., 1976). As an example of measuring social presence, emails would have a lower social presence than face-to-face meetings. Communication effectiveness is the suggestion that certain types of communication media are better suited for meetings than they are for another meeting. An example of communication effectiveness would be a manager deciding if he or she should hold a face-to-face meeting or send an email for a 10-min debriefing. A face-to-face meeting might be better to communicate the message, but it also might waste other's time. Therefore, the manager must decide which communication medium will be most effective before presenting the information. Communications interface refers to the actions needed within the communication medium to exchange information with participants of the meeting. Two examples of communication interface are the “raise your hand” button during a Zoom teleconference or the “talk” switch on a two-way radio.
By adding OM to the PRISM framework (see Figure 2), this research aims to get a better understanding of how well existing meetings have informed logistics Airmen on the topic of COVID-19, and how OM may have influenced other relevant PRISM constructs such as PBC, ATS, SN and Inf-Ins. With regards to perceptions in existing communication methods, the Air Force has placed an increased importance on battling the COVID-19 pandemic from a strategic aspect. This research expects that this drive from organizational leaders at the top will influence policy, guidelines and requirements at the wing level. When information of this magnitude gets to the wing level, it is expected to arrive at the squadron level, then down to Airmen to accomplish organizational goals. Thus, Airmen at all hierarchal levels will view the information trustworthy and ensure it is made accessible to their subordinates, which would influence all Airmen's ATS. When the COVID-19 information arrives at the Airmen's meetings, it is expected that there will be an increase in each Airman's current knowledge due to the education provided at the meeting. It is also suspected, due to the priority that has been given to overcome the COVID-19 pandemic, that PBC will be affected. This is because leaders are expected to ensure their subordinates can access COVID-19 information and provide an outlet that can help them seek answers to questions. Lastly, it is anticipated that OM will play a role in SN because meetings are typically led by a higher-ranking individual who has influence on those attending the meeting. Therefore, we expect.
OM will be positively related to ATS.
OM will be positively related to SN.
OM will be positively related to PBC.
OM will be positively related with perceived knowledge insufficiency (Inf-Ins).
OM will be positively related to information seeking intent (SEEK).
Methodology
Survey instrument and data collection
An online self-administered survey was designed to test the expanded PRSIM model in Figure 2. The model was adapted from Khalor et al. (2010) and was expanded to capture the perceptions of Airmen's existing meetings. The online survey was approved by Headquarters Air Force, Logistics Force Development (HAF/A4LR). Once approved, HAF/A4LR sent an initial email to commanders of logistics organizations across the Air Force in order to garner support for the current study. Once logistics squadron commanders gave approval for their organizations to participate, the researchers sent an introductory email to potential participants informing them of the intent of the research and to inform potential participants that it was an optional and anonymous survey. A link to the online survey was included in the emails. Participants received three separate courtesy emails as a reminder during the one month that the survey was active. The unit of analysis was the individual Airman.
Overall, 186 individuals responded to the survey. Screening of the data led to 57 cases being removed due to missing data or unengaged responses. This left a final sample size of 129 individuals spanning 35 organizations. Respondents age ranged from 19 to 65 (SD = 34.26), 69.8% of the respondents were male and 70% of respondents identified as conservative-leaning versus liberal leaning. The rank and race breakdowns are included in Table 1 and Table 2.
The latent construct of OM was represented by 20 questions each rated on a Likert scale of one to seven and was modified from Chidambaram and Jones (1993). Information insufficiency was assessed with two questions, one for current knowledge and another for sufficiency threshold (Griffin et al., 2004). Both questions were measured on a scale of zero to 100. SN consisted of four questions each on a Likert scale from one to six. PBC consisted of three questions all on a Likert scale from one to five; each question on PBC was reverse coded. ATS was represented by seven questions on a Likert scale of one to six; two of the ATS questions were reverse coded. Information seeking (SEEK) was represented by five questions on a Likert scale of one to six. SN, PBC, ATS and SEEK were taken from the Yang and Khalor (2013). All scales have been used in previous research and have shown high reliability in multiple settings. A complete list of the scale items can be found in the Appendix.
Results
Statistical analysis
First, a confirmatory factor analysis was performed using AMOS 28 to verify the measurement model. Then, the hypotheses were tested using the PROCESS custom dialog (Version 4.1) developed by Hayes (2022) for SPSS 28.
Measurement model results
Internal consistency was examined using Cronbach's α and composite reliability scores. All constructs had alpha levels at or above the recommended minimum level of 0.70 (Nunnally and Bernstein, 1994). A rule of thumb of composite reliability is that if the constructs have five to eight variables, then they should meet a minimum score of 0.8 (Netemeyer et al., 2003). All five of the latent variables met the minimum scores.
To assess construct and discriminant validity, a CFA was performed using IBM SPSS AMOS 28. Several variables were removed due to poor factor loadings. The final measurement model resulted in the following fit indices: χ2 (514.39, df = 311, p-value <0.001); comparative fit index (CFI) (0.94); incremental fit index (IFI) (0.94); standardized root mean residual (SRMR) (0.057); and root mean square error of approximation (RMSEA) (0.071, 90% CI (0.061, 0.082)). The fit indices indicate an adequate model fit except for the χ2 statistic (Hu and Bentler, 1999). Although a significant χ2 statistic was obtained, the normed χ2 statistic was 1.65 which fell well below the recommended maximum of 3.0 (Kline, 2011).
To test for convergent validity, factor loadings were assessed along with the average variance extracted (AVE) for each construct. Standardized factor loadings and AVEs are shown in Table 3. All items loaded onto their corresponding constructs with p < 0.001, and all variables had factor loadings exceeding the 0.6 threshold recommended by Hair et al. (2010). The rule of thumb for using AVE to assess convergent validity is 0.5, which means that the variance explained by the construct is greater than what is due to measurement error (Hair et al., 2010). All constructs had AVEs above the 0.50 threshold. These results provide evidence of convergent validity.
Discriminant validity was assessed by performing the Fornell and Larcker (1981) test. According to this test, discriminant validity is supported if the square root of a construct's AVE is greater than the correlations between that construct and other constructs used in the model. As shown in Table 4, all constructs passed this test, which provides evidence of discriminant validity.
Common method variance
The common latent factor method was used to test the presence of common method variance in the data (Serrano et al., 2018). A latent factor was added to the CFA model and connected to all observed items. Analysis showed there were no large differences between the standardized regression weights for the model with a common latent factor and the model without the common latent factor. Additionally, no item loaded higher on the common latent factor than it did on the construct of interest. Although we cannot rule out common method variance completely, research and simulations over the last 10 years indicate the probability of significant distortion of the estimates due to common method variance is very limited (Bozionelos and Simmering, 2021). Therefore, we conclude that common method variance is not significant in the model.
Regression results
We tested the hypotheses using a custom model dialog in SPSS PROCESS and employed bootstrapping with 5,000 resamples to test the significance of the indirect effects (Hayes, 2022). Results are shown in Table 5. Hypotheses 1 and 2 sought to determine direct relationships of ATS with Inf-Ins and SEEK. Hypothesis 1 stated ATS would be positively related to Inf-Ins, and we found support for this hypothesis (β = 5.544, SE = 2.043 p = 0.008); however, we did not find support for Hypothesis 2 as there was no statistically significant relationship between ATS and SEEK (β = 0.104, SE = 0.105 p = 0.326).
Hypothesis 3 tested whether Inf-Ins would be positively related to SEEK. Results of the analysis give support for Hypothesis 3 since Inf-Ins had a positive, statistically significant relationship with SEEK (β = 0.012, SE = 0.005 p = 0.009).
The relationship between SN, Inf-Ins and SEEK were tested in Hypotheses 4 and 5. SN had a significant, positive relationship with Inf-Ins (β = 4.411, SE = 1.574 p = 0.006) which offers support for Hypothesis 4. Hypothesis 5 was also supported as SN was positively related to SEEK (β = 0.429, SE = 0.081 p < 0.001).
Hypotheses 6 and 7 investigated the relationship between PBC, Inf-Ins and SEEK. We found no support for Hypothesis 6 as there was no statistically significant relationship between PBC and Inf-Ins (β = −4.444, SE = 3.004, p = 0.142). We also found no support for Hypothesis 7 since PBC and SEEK were not statistically related (β = −0.082, SE = 0.152 p = 0.592).
Hypothesis 8 stated OM would positively impact ATS, and the analysis offers support for this hypothesis (β = 0.821, SE = 0.098, p < 0.001). OM were also positively related to SN (β = 0.298, SE = 0.114, p = 0.01) and PBC (β = 0.480, SE = 0.065, p < 0.001), which supports Hypotheses 9 and 10. Hypothesis 11 posited that OM would be positively related to Inf-Ins; however, this hypothesis was not supported (β = 4.812, SE = 2.579, p = 0.065) at the α = 0.05 level. Hypothesis 12 stated that OM would have a positive influence on SEEK, and this hypothesis was partially supported. Although there was no direct relationship between OM and SEEK (β = 0.115, SE = 0.131, p = 0.273), there were multiple significant indirect relationships as shown in the bottom of Table 5. The total indirect effect of OM on SEEK was: β = 0.274, SE = 0.118, 99% Bootstrap CI (0.042, 0.511). Table 6 summarizes results of the hypotheses testing.
Discussion
Although the amount of communication research performed is vast, there is a lack of corporate communication and internal crisis communication research (Adamu and Mohamad, 2019; Frandsen and Johansen, 2011; Guo and Canella, 2021; Mazzei and Butera, 2021). This study addressed this gap and focused on evaluating whether or not Air Force logistics communication during the pandemic was effective. More specifically, this research, through an expanded PRISM model, evaluated how Airmen feel about their existing workplace COVID-19 meetings and how those meetings played a role in other factors that contributed to their risk information seeking on their wing's social media page. The expanded PRISM model was found to have adequate model fit, and thus proved itself as a valuable tool for this research.
Results from the survey study revealed that logistic Airmen's perceptions of their organizational meetings had a direct, positive influence on their attitude toward seeking COVID-19 information on their wing's social media website, their subjective norms regarding seeking out COVID-19 information, and their perceived behavioral control regarding seeking out COVID-19 information on their wing's social media website. Although all wing social media websites were acceptable sources of COVID-19 information, it was discovered in the survey open-ended responses that wing Facebook pages were the major sources of information. Results also showed that logistic Airmen's perceptions of their organizational meetings were indirectly related to their information insufficiency threshold and their intention to seek COVID-19 information. In other words, organizational meetings appear to be a key element in influencing logistics Airmen to seek out vital pandemic information from their wing's social media pages during a crisis. Overall, logistics Airmen's organizational meetings on COVID-19 influenced their perceptions on whether or not seeking out COVID-19 information on their wing's social media page was valuable, helpful, productive, expected and also influenced their opinions on where to look to find that information.
Although logistic Airmen's perceptions of COVID-19 organizational meetings were not directly related to their information insufficiency threshold or their intention to seek COVID-19 information on their wing's social media website, there was a fully mediated relationship through their attitudes toward seeking and subjective norms. Therefore, it appears that organizational meetings' most significant influence on logistics Airmen's information seeking behavior is due to their organization and peers expecting them to seek out the information, and their organization and peers communicating that the wing's social media website is a valuable source of information.
This research found that an expanded PRISM model was useful in examining the relationships between organizational COVID-19 meetings, perceived behavioral control, attitude toward seeking, subjective norms, information insufficiency and information seeking behaviors. However, it is more difficult to assess whether or not the organizational meetings were effective in communicating the importance of gaining information on COVID-19. To do this, a post-hoc ANOVA was performed using only organizations with greater than 5 respondents (8 organizations). Results showed that organizations with the lowest scores on organizational meetings also had the lowest scores on attitude toward seeking, subjective norms and information seeking behavior. Possibly most important, Airmen in those organizations felt they needed to know the least about COVID-19. On the other hand, Airmen in the organizations with the highest scores on organizational meetings felt they needed to know the most about COVID-19. It appears organizational meetings can influence logistics Airmen by imparting how important it is to learn about COVID-19, whether or not it is expected to learn about COVID-19, and whether or not the wing's social media page is an effective repository of beneficial pandemic information.
Theoretical implications
From a theoretical standpoint, this study extends current corporate communication research to crisis and pandemic situations (Guo and Canella, 2021). Guo and Canella (2021) go on to explain that pandemic communication is distinctly different than traditional corporate communication due to the pandemic being characterized by an extreme level of uncertainty, having high levels of information disorder which disrupts information processing and decision making, and because there is an overwhelming amount of information to navigate. The expanded PRISM model, which has roots in the Theory of Planned Behavior, was effectively used in this research and results provided evidence that organizational meetings were able to break through the uncertainty and flood of information in order to influence logistics Airmen to seek out credible information regarding the pandemic.
This study also extends the PRISM model and adds perceptions of organizational meetings as an antecedent to Kahlor's (2010) original model. This addition to the model is important because organizations need to understand how they can overcome the high-level of uncertainty brought on by the pandemic. By using perceptions of organizational meetings as an antecedent, we were able to see that when logistics Airmen felt COVID-19 meetings were good, accessible, accurate, true, humanizing and interesting, they were more likely to feel and act out on an expectation to seek out COVID-19 information from their wing's social media website. Logistics Airmen were also more likely to feel their wing's social media website would have valuable and productive COVID-19 information available. Even in times of information overload and extreme uncertainty, organizational meetings were able to impact attitude toward seeking, perceived behavioral control and subjective norms of logistics Airmen. Thus, we have provided evidence that an expanded PRISM model holds true during crisis situations.
Managerial implications
The COVID-19 pandemic provided a unique opportunity to study crisis communication as the phenomena unfolded. Because of this, our research has important implications for managers, especially those in Air Force logistics organizations which are counted on to operate during crisis situations. Through interviews and personal experience from one of the authors who commanded a logistics organization during the pandemic, it was found that many of the logistics organizations had strict quarantine rules for those that were infected by the COVID-19 virus. This quarantine policy was in place to try to limit the number of infected Airmen, and thus limit the potential shut down of the organization during the pandemic. Since effective communication is seen as one of the most important factors in preventing the spread of COVID-19 (Finset et al., 2020; Reddy and Gupta, 2020), this study focused on how to influence Airmen to seek out accurate and reliable information to keep them safe and working during the pandemic. With the crises of the recent past such as Ebola, H1N1 and SARS added to the recent COVID-19 pandemic, organizations should be prepared for the next crisis.
This research shows that organizational meetings can in fact cut through the fog of confusion and influence Airmen to seek out relevant wing-level information in order to prevent being lost to infection. Although it may be more difficult for organizational leaders to understand what makes an Airmen feel a meeting is “good” or “pleasurable”, leaders can ensure their crisis meetings are accessible. Typical squadron-level meetings only include non-commissioned officers, flight chiefs and officers while leaving lower-ranking Airmen out. A retrospective analysis of the data showed that lower ranking Airmen (E-1 through E-4) felt they needed to know the least about COVID-19. This could potentially be overcome by including lower-ranking Airmen in the organizational meetings. Organizational leaders can also ensure their crisis meetings have accurate information and are held in spacious rooms where attendees do not feel constricted. Leaders can also ensure the meetings are sensitive and humanizing to the attendees instead of blunt or forceful. These meeting characteristics were shown to positively influence the Airmen's subjective norms, attitude toward seeking and perceived behavioral control during the pandemic. Thus, this research provides evidence on how leaders can structure their meetings in order to help keep their Airmen safe and available throughout a crisis.
Limitations and future research
This research has helped advance the understanding of how Airmen's existing meetings impact key variables that play a role into their risk information seeking on their wing's social media website during the COVID-19 pandemic. However, this study is not without its limitations. First, this study is correlational in nature and represents only one point in time. Although results of this study are in line with previous Theory of Planned Behavior and PRISM studies, one cannot definitively state organizational meetings influenced Airmen to seek out the information. Before that can be stated, longitudinal or experimental studies would have to be performed.
Additionally, this research is limited to Air Force logistics organizations and results may not be transferable to other organization types. Although logistics organizations from 35 different wings are represented in this study, not all organizations had multiple respondents. Therefore, a comparison between organizations could not be made for every organization or wing. Future research could include multiple respondents from each organization to allow for more comparison and/or hierarchical regression. Future studies could also include other organization types to determine if meetings have the same impact across the Air Force. Additionally, case studies could be performed in order to look at culture and artifacts of the organizations to identify potential best practices of organizations that appeared to score higher on meeting scores since higher scores were related to higher levels of information seeking and lower levels of information insufficiency. Any best practices found could be codified and relied upon to help operate during future crises. Finally, it would be beneficial to gain access to organizational logistics metrics and COVID-19 infection rates of the organizations included in this study to determine if perceptions of organizational meetings led to lower infection rates and improved performance. Findings from this could provide insight into the effectiveness of using social media for internal crisis communication, and it could prove invaluable when planning for future pandemic or crisis situations.
Conclusion
The recent COVID-19 pandemic created an atmosphere of uncertainty, created information disorder and led to an overbearing amount of information (Guo and Cannella, 2021). However, it was critical for essential workers and organizations to remain operating during this time, and this was especially true for Air Force logistics organizations. Effective communication is seen as a key element to preventing the spread of COVID-19, and thus a key element in keeping a logistics organization operating during the pandemic. The purpose of this research was to evaluate the effectiveness of pandemic communication in Air Force logistics organizations. By using an expanded PRISM model, we were able show strong empirical support for a relationship between organizational meetings and perceived behavioral control, attitude towards seeking, subjective norms and information seeking behavior of logistics airmen during the pandemic. These results can be used by leaders to prepare their organizations for future pandemic and crisis situations and help their organizations remain operating during critical times.
Figures
Rank of respondents
| Enlisted | Civilian | Officer | |||
|---|---|---|---|---|---|
| E-2 | 1 | GS-5 | 1 | O-1 | 6 |
| E-3 | 12 | GS-7 | 5 | O-2 | 9 |
| E-4 | 12 | GS-8 | 5 | O-3 | 5 |
| E-5 | 10 | GS-9 | 4 | O-4 | 8 |
| E-6 | 17 | GS-10 | 1 | O-5 | 11 |
| E-7 | 10 | GS-11 | 1 | ||
| E-8 | 2 | GS-12 | 3 | ||
| E-9 | 1 | GS-13 | 2 | ||
Note(s): 3 respondents declined to respond
Source(s): Table by authors
Race of respondents
| Race | # |
|---|---|
| White | 80 |
| African American | 19 |
| American Indian or Alaskan Native | 3 |
| Asian | 9 |
| Native Hawaiian or Pacific Islander | 4 |
| Hispanic | 6 |
| Multiple Races | 4 |
Note(s): 4 respondents declined to respond
Source(s): Table by authors
Results of CFA
| Constructs and scale items | Factor loadings | Constructs and scale items | Factor loadings |
|---|---|---|---|
| Organizational meetings (AVE = 0.509) | Perceived Behavioral Control (AVE = 0.641) | ||
| OM3 | 0.831 | PBC1 | 0.841 |
| OM4 | 0.605 | PBC2 | 0.758 |
| OM5 | 0.807 | Attitude Toward Seeking (AVE = 0.836) | |
| OM7 | 0.706 | ATS1 | 0.893 |
| OM8 | 0.611 | ATS2 | 0.850 |
| OM11 | 0.810 | ATS4 | 0.949 |
| OM12 | 0.649 | ATS5 | 0.944 |
| OM15 | 0.767 | ATS7 | 0.931 |
| OM17 | 0.742 | Information Seeking (AVE = 0.901) | |
| OM18 | 0.734 | SEEK1 | 0.957 |
| OM19 | 0.637 | SEEK2 | 0.941 |
| OM20 | 0.603 | SEEK3 | 0.943 |
| Subjective norms (AVE = 0.613) | SEEK4 | 0.963 | |
| ISN2 | 0.828 | SEEK5 | 0.941 |
| ISN3 | 0.615 | ||
| ISN4 | 0.880 |
Note(s): All t-values were significant with p < 0.001. OM1, OM2, OM6, OM9, OM10, OM13, OM14, OM16, ISN1, PBC3, ATS3 were removed due to poor factor loadings
Source(s): Table by authors
Means, standard deviations, reliability, AVE, and correlations
| Construct | CR | AVE | MSV | SEEK | OM | ATS | SN | PBC |
|---|---|---|---|---|---|---|---|---|
| SEEK | 0.978 | 0.901 | 0.334 | 0.949 | ||||
| OM | 0.925 | 0.509 | 0.419 | 0.310 | 0.713 | |||
| ATS | 0.962 | 0.836 | 0.526 | 0.360 | 0.639 | 0.914 | ||
| SN | 0.823 | 0.613 | 0.334 | 0.578 | 0.263 | 0.325 | 0.783 | |
| PBC | 0.781 | 0.641 | 0.526 | 0.192 | 0.647 | 0.725 | 0.212 | 0.801 |
Source(s): Table by authors
SPSS PROCESS analysis results
| Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| ATS | SN | PBC | Inf_Ins | SEEK | ||||||
| Regression results | Coeff | SE | Coeff | SE | Coeff | SE | Coef | SE | Coeff | SE |
| OM | 0.821*** | 0.098 | 0.298* | 0.114 | 0.480*** | 0.065 | 4.812ns | 2.579 | 0.145ns | 0.131 |
| ATS | 5.544** | 2.043 | 0.104ns | 0.105 | ||||||
| SN | 4.411** | 1.574 | 0.429*** | 0.081 | ||||||
| PBC | −4.444ns | 3.004 | −0.082ns | 0.152 | ||||||
| Inf_Ins | 0.012** | 0.005 | ||||||||
| R2 | 0.357 | 0.051 | 0.296 | 0.230 | 0.364 | |||||
| F-value | 70.440 | 6.807 | 53.410 | 7.346 | 14.058 | |||||
| Indirect effects | ||||
|---|---|---|---|---|
| Path | Indirect effect | Boot SE | 95% boot CI | Result |
| OM→ATS→SEEK | 0.085 | 0.104 | (−0.119, 0.286) | Non-significant |
| OM→SN→SEEK | 0.128 | 0.062 | (0.023, 0.265) | Significant |
| OM→PBC→SEEK | −0.039 | 0.079 | (−0.202, 0.113) | Non-significant |
| OM→Inf_Ins→Seek | 0.058 | 0.041 | (−0.006, 0.149) | Non-significant |
| OM→ATS→Inf_Ins→SEEK | 0.054 | 0.030 | (0.003, 0.117) | Significant |
| OM→SN→Inf_Ins→SEEK | 0.016 | 0.012 | (0.001, 0.045) | Significant |
| OM→PBC→Inf_Ins→SEEK | −0.025 | 0.019 | (−0.064, 0.023) | Non-significant |
| Total Indirect Effect | 0.274 | 0.118 | (0.042, 0.511) | Significant |
Note(s): ***p < 0.001 **p < 0.01 * p < 0.05 ns = non-significant
Source(s): Table by authors
Summarized hypotheses results
| Hypothesis | Relationship | Supported | Hypothesis | Relationship | Supported |
|---|---|---|---|---|---|
| H1 | ATS→Inf-Ins (+) | Yes | H7 | PBC→SEEK (+) | No |
| H2 | ATS→SEEK (+) | No | H8 | OM→ATS (+) | Yes |
| H3 | Inf-Ins→SEEK (+) | Yes | H9 | OM→SN (+) | Yes |
| H4 | SN→Inf-Ins (+) | Yes | H10 | OM→PBC (+) | Yes |
| H5 | SN→SEEK (+) | Yes | H11 | OM→Inf-Ins (+) | No |
| H6 | PBC→Inf_Ins (+) | No | H12 | OM→SEEK (+) | Partially* |
Note(s): * The relationship between OM and SEEK was fully mediated
Source(s): Table by authors
Perceptions of existing meetings measurement scale
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | |||
|---|---|---|---|---|---|---|---|---|---|
| 1 | Constrained | * | * | * | * | * | * | * | Free |
| 2 | Complex | * | * | * | * | * | * | * | Simple |
| 3 | Good | * | * | * | * | * | * | * | Bad |
| 4 | Inaccessible | * | * | * | * | * | * | * | Accessible |
| 5 | Distorted | * | * | * | * | * | * | * | Accurate |
| 6 | Impersonal | * | * | * | * | * | * | * | Personal |
| 7 | True | * | * | * | * | * | * | * | False |
| 8 | Pleasurable | * | * | * | * | * | * | * | Painful |
| 9 | Hot | * | * | * | * | * | * | * | Cold |
| 10 | Distant | * | * | * | * | * | * | * | Close |
| 11 | Dehumanizing | * | * | * | * | * | * | * | Humanizing |
| 12 | Expressive | * | * | * | * | * | * | * | Inexpressive |
| 13 | Difficult | * | * | * | * | * | * | * | Easy |
| 14 | Emotional | * | * | * | * | * | * | * | Unemotional |
| 15 | Meaningless | * | * | * | * | * | * | * | Meaningful |
| 16 | Slow | * | * | * | * | * | * | * | Fast |
| 17 | Successful | * | * | * | * | * | * | * | Unsuccessful |
| 18 | Insensitive | * | * | * | * | * | * | * | Sensitive |
| 19 | Interesting | * | * | * | * | * | * | * | Boring |
| 20 | Constricted | * | * | * | * | * | * | * | Spacious |
Source(s): Table by authors
Attitude towards seeking measurement scale
 |
Source(s): Table by authors
Funding: This research was supported by KBR Wyle Services, LLC (Grant # FA807518D0015).
Disclaimer: The views expressed are those of the authors and do not reflect the official guidance or position of the United States Government, the Department of Defense the United States Air Force or the United States Space Force.
This article has not been published previously in its current or substantially similar form and permission has been granted for this version to appear on AFIT scholar at scholar.afit.edu. Emerald does not grant permission for this article to be further copied/distributed or hosted elsewhere without the express permission from Emerald Publishing Limited.
Previous work: This research is based on, and an extension of, the following Air Force Institute of Technology Master's thesis. This current work has been substantially revised (Price, 2022).
Perceptions of existing meetings (rated on a scale from 1 to 7)
The scales below are designed to assess feelings and attitudes towards Wing, Group, Squadron, Flight and Shift Call meetings regarding to COVID-19. Please consider the meetings you attend and circle the point along the scale which you consider to be the most appropriate for these meetings. Work rapidly; do not return to previously completed responses.
Subjective norms (rated on a scale from 1 to 6)
SN1. It is expected of me that I seek information about the COVID-19 pandemic from my wing's social media.
SN2. Most people who are important to me think that I should seek information on the COVID-19 pandemic.
SN3. I feel that there is an expectation of me to seek information about the COVID-19 pandemic.
SN4. My family expects me to seek information about the COVID-19 pandemic.
SN5. People in my life whose opinions I value seek information about the COVID-19 pandemic from their wing's social media pages.
Perceived behavioral control (rated on a scale from 1 to 5; reverse coded)
PBC1. It is difficult to find credible/accurate information about COVID-19 on my wing's social media page.
PBC2. I don't know where to find credible/accurate information about COVID-19 on my wing's social media.
PBC3. I have a hard time understanding information about COVID-19.
Attitude towards seeking (rated on a scale from 1 to 6)
Indicate on a scale from 1 to 6 the degree to which you feel that seeking information about COVID-19 on your wing's social media is.
Information insufficiency
Current knowledge: On a scale of 0–100, estimate your current knowledge of the COVID-19 pandemic with 0 = knowing nothing and 100 = knowing everything you could possibly know about the topic.
Sufficiency threshold: This time, using that same scale, estimate how much knowledge you think you NEED on this same topic (0–100).
Information seeking (rated on a scale from 1 to 6)
SEEK1. I plan to seek information about COVID-19 in the near future.
SEEK2. I will try to seek information about COVID-19 in the near future.
SEEK3. I intend to find more information about COVID-19 soon.
SEEK4. I intend to look for information about COVID-19 in the near future.
SEEK5. I will look for information related to COVID-19 in the near future.
Source(s): Appendix by authors
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