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Effectiveness of message tactics in social marketing projects often varies across groups of individuals, which suggests the importance of tailoring communication approaches to maximize the success of promotional strategies. This study aims to contribute in this direction by using an innovative approach to promote targeted human papillomavirus vaccination, applying conjoint analysis to understand parental preferences for social media content features.

An online purpose-built quantitative survey was administered to a group of parents meeting eligibility criteria. The survey questions were designed based on inputs from formative qualitative research conducted in a previous phase of the study.

In the overall sample of 285 parents, responses show that image was the most important feature of social media posts overall, followed by source and text. Cluster analysis identified eight segments in the sample based on parental preferences for content features. Significant differences across segments were identified in terms of need for cognition, vaccine hesitancy, parental gender, concerns around side effects, trust in medical providers, information sharing behaviors on social media and information seeking online.

The application of conjoint analysis to promotional content allows to assess which features of the content are most important in persuading different individuals and provide insights on how people process the information, ultimately to inform targeted promotion based on preferences. Conjoint analysis has been widely used in consumer research to explore audience preferences for products or services, but only a few applications of conjoint analysis to the design and testing of promotional content are found in the literature.

As public health professionals strive to promote vaccines for inoculation efforts, fervent anti-vaccination movements are marshaling against it. This study is motived by a need to better understand the online discussion around vaccination. The authors identified the sentiments, emotions and topics of pro- and anti-vaxxers’ tweets, investigated their change since the pandemic started and further examined the associations between these content features and audiences’ engagement.

Utilizing a snowball sampling method, data were collected from the Twitter accounts of 100 pro-vaxxers (266,680 tweets) and 100 anti-vaxxers (248,425 tweets). The authors are adopting a zero-shot machine learning algorithm with a pre-trained transformer-based model for sentiment analysis and structural topic modeling to extract the topics. And the authors use the hurdle negative binomial model to test the relationships among sentiment/emotion, topics and engagement.

In general, pro-vaxxers used more positive tones and more emotions of joy in their tweets, while anti-vaxxers utilized more negative terms. The cues of sadness predominantly encourage retweets across the pro- and anti-vaccine corpus, while tweets amplifying the emotion of surprise are more attention-grabbing and getting more likes. Topic modeling of tweets yields the top 15 topics for pro- and anti-vaxxers separately. Among the pro-vaxxers’ tweets, the topics of “Child protection” and “COVID-19 situation” are positively predicting audiences’ engagement. For anti-vaxxers, the topics of “Supporting Trump,” “Injured children,” “COVID-19 situation,” “Media propaganda” and “Community building” are more appealing to audiences.

This study utilizes social media data and a state-of-art machine learning algorithm to generate insights into the development of emotionally appealing content and effective vaccine promotion strategies while combating coronavirus disease 2019 and moving toward a global recovery.

The peer review history for this article is available at https://publons.com/publon/10.1108/OIR-03-2022-0186

Vaccination is widely conceded as a pivotal measure to achieve community immunization and eradicate COVID-19. The purpose of this paper is to understand vaccination behavior based on the association between the theory of planned behavior (TPB) and health belief model (HBM).

A self-administered questionnaire was designed to collect data from 438 participants through social media in Vietnam and later analyzed using SPSS and AMOS to examine the research model.

The results indicated that attitude toward vaccination is positively influenced by perceived risk and perceived benefits. Additionally, background constructs of TPB (i.e. social norms, attitude and perceived behavioral control) and HBM (i.e. perceived risk, response efficacy, perceived benefits and knowledge about COVID-19) are underlying motivations for individual intention to receive vaccine. Moreover, age is a demographic predictor of vaccination intention. Finally, vaccination intention facilitates COVID-19 vaccination.

The findings will assist health-care bodies and authorities to understand public perceptions, attitude and behaviors and encourage their participation in vaccination campaigns.

To date, this is the first investigation of how disease knowledge and perceived benefits drive vaccination intention in Vietnam. Moreover, this study may be initially successful in adding current health-care behavior literature by combining TPB with HBM. With most studies on vaccination intention at the early stage of COVID-19 outbreak in developed nations, this work provides new insights by testing vaccination behavior in the fourth wave of COVID-19 outbreak and in a developing nation.

Successful social marketing campaign to promote COVID-19 vaccination for the unvaccinated relies on increasing positive reactions but also reducing negative responses to persuasive messages. This study aims to investigate the relative effects of narrative vs non-narrative public service announcements (PSAs) promoting COVID-19 vaccination on both positive and negative reactions. Using social media as a tool for disseminating marketing campaigns provides a great opportunity to examine the effectiveness of narrative PSAs on vaccination intention, especially among unvaccinated young adults, who were the target audience of the social marketing. This study explores the role of empathy and psychological reactance as underlying mechanisms.

An experiment involving unvaccinated young adults was conducted with a one-factor, two-condition (message type: narrative vs non-narrative) design.

Results indicated that the narrative (vs non-narrative) PSAs led to greater empathy. While no direct effects of message type emerged on psychological reactance or vaccination intention, results of a serial multi-mediator model confirmed that empathy and psychological reactance mediated the effects of message type on vaccination intention.

The study extends the understanding of narrative persuasion by examining an underlying mechanism behind narrative persuasion in a COVID-19 PSA. This study provides empirical evidence of the important role of empathy in processing narrative PSAs. Moreover, the current study expands narrative persuasion’s applicability to COVID-19 vaccination intervention messages for unvaccinated young adults, highlighting the effectiveness of narrative persuasion as a social marketing communication tool.

This study proposes and validates an integrated theoretical model involving the theory of planned behavior (TPB), health belief model (HBM), personal norms and information privacy to understand determinants of acceptance and resistance to the use of mobile contact tracing app (MCTA) in a pandemic situation.

This study draws on online surveys of 194 research respondents and uses partial least squares structural equation modeling (PL-SEM) to test the proposed theoretical model.

The study establishes that a positive attitude towards MCTA is the most important predictor of individuals' willingness to use MCTA and resistance to use MCTA. Furthermore, barriers to taking action positively influence resistance to the use of MCTA. Personal norms negatively influence resistance to the use of MCTA. Information privacy showed a negative and positive influence on willingness to use MCTA and use the resistance of MCTA, respectively, but neither was statistically significant. The authors found no significant influence of perceived vulnerability, severity, subjective norms and perceived behavioral control on either acceptance or use resistance of MCTA.

The study has been one of the first in the literature to propose an integrated theoretical model in the investigation of the determinants of acceptance and resistance to the use of MCTA in a single study, thereby increasing the scientific understanding of the factors that can facilitate or inhibit individuals from engaging in the use of a protection technology during a pandemic situation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2021-0533

This study aims to examine how different hospitals utilize social media to communicate risk information about COVID-19 with the communities they serve, and how hospitals' social media messaging (firm-generated content and their local community's responses (user-generated content) evolved with the COVID-19 outbreak progression.

This research proposes a healthcare-specific social media analytics framework and studied 68,136 tweets posted from November 2019 to November 2020 from a geographically diverse set of ten leading hospitals' social media messaging on COVID-19 and the public responses by using social media analytics techniques and the health belief model (HBM).

The study found correlations between some of the HBM variables and COVID-19 outbreak progression. The findings provide actionable insight for hospitals regarding risk communication, decision making, pandemic awareness and education campaigns and social media messaging strategy during a pandemic and help the public to be more prepared for information seeking in the case of future pandemics.

For hospitals, the results provide valuable insights for risk communication practitioners and inform the way hospitals or health agencies manage crisis communication during the pandemic For patients and local community members, they are recommended to check out local hospital's social media sites for updates and advice.

The study demonstrates the role of social media analytics and health behavior models, such as the HBM, in identifying important and useful data and knowledge for public health risk communication, emergency responses and planning during a pandemic.

This study aims to explain the factors associated with receiving a specific brand of COVID-19 vaccine within the framework of the theory of reasoned action (TRA). This study extends the TRA with the country-of-origin image (COI), brand image and electronic word of mouth variables.

This study is based on a cross-sectional survey conducted among 460 people who received the Sinofarm vaccine. Participants were selected using an online convenience sampling method. The structural equation modeling technique tests the proposed hypotheses.

The results showed that the essential factor associated with the intent to get the Chinese Sinopharm vaccine is the attitude toward the Signopharm vaccine. Also, word of mouth, subjective norms and brand image are the most critical factors that play a role in forming a favorable attitude toward the Sinopharm vaccine. Finally, the country-of-origin image does not affect attitudes toward the Sinopharm vaccine.

The area of vaccine marketing has been given limited attention in academic literature. This study addresses this area with little research and is greatly attractive to many brands targeting the consumer market. The study results can form a foundation for creating the branding strategy for this product category and assessing its demand in various markets.

This review aims to provide synoptic documentation on acclaimed anecdotal plant-based remedies used by Latin America and the Caribbean (LAC) communities to manage COVID-19. The theoretical approaches that form the basis for using the anecdotally claimed phytotherapies were reviewed against current scientific evidence.

In this paper plant-based remedies for managing COVID-19 were searched on social and print media to identify testimonies of people from different communities in LAC countries. Information was extracted, evaluated and reviewed against current scientific evidence based on a literature search from databases such as Journal Storage (JSTOR), Excerpta Medica Database (EMBASE), SpringerLink, Scopus, ScienceDirect, PubMed, Google Scholar and Medline to explore the scientific basis for anecdotal claims.

A total of 23 medicinal plants belonging to 15 families were identified as phytotherapies used in managing COVID-19 in LAC communities.

The plant-based remedies contained valuable phytochemicals scientifically reported for their anti-inflammatory, antiviral, antioxidant and anticancer effects. Anecdotal information helps researchers investigate disease patterns, management and new drug discoveries. The identified acclaimed plant-based remedies are potential candidates for pharmacological evaluations for possible drug discovery for future pandemics.

The purpose of this study is to examine the impact of the shift towards a circular economy and marketing strategies on the collaborative purchasing behaviour of consumers in India. The study uses the theory of planned behaviour (TPB) and the marketing mix to understand the factors affecting a consumer’s intention to participate in collaborative consumption (CC).

A Web-based survey was conducted, and 349 valid responses were analysed using AMOS (Analysis of Moment Structures) structural equation modelling. The study emphasised the impact of price, promotion and perceived behaviour control on CC and provided direction and advice for companies that rent and swap apparel.

According to the study, promotion and perceived behaviour control are the two key characteristics that significantly impact a consumer’s willingness to participate in CC in India. The study also found that perceived behaviour control plays a significant direct role in behavioural usage. These findings emphasise the impact of price, promotion and perceived behaviour control on CC and offer direction and advice for companies that rent and swap apparel.

This article can be used to evaluate the business in different countries and can be developed further. It does, however, have some restrictions. Because most respondents are from northern and central India, in addition, some respondents are from the southwestern and southern regions, especially in the Mumbai and Chennai locales. Hence, the geographical sample was not diverse in terms of demographics. Furthermore, the gender identity of the respondents might essentially affect how the authors interpret customer buying behaviour, but the study missed this. Researchers could enhance this by using various sampling techniques and ensuring that other demographic characteristics are considered in the future. Furthermore, the survey could not distinguish between online and in-person transactions.

The study provides practical advice for companies that rent and swap apparel, emphasising the impact of price, promotion and perceived behaviour control on consumer willingness to participate in CC. The findings suggest that companies can improve consumer participation by focusing on promotion and perceived behaviour control. In addition, the significance of perceived behaviour control on behavioural usage highlights the importance of empowering consumers to control their decisions to participate in CC.

To the best of the authors’ knowledge, this study is one of the first to examine the factors influencing consumer willingness to participate in CC in the context of the shift towards a circular economy in India. By examining the impact of the TPB and the marketing mix on consumer intention, the study provides valuable insights for companies that rent and swap apparel. The findings highlight the importance of promotion and perceived behaviour control in shaping consumer behaviour and provide practical direction for companies to promote and market their products effectively. The study adds to the existing knowledge on the circular economy and the role of CC in reducing waste and promoting sustainability.

This survey explores the application of real options theory to the field of health economics. The integration of options theory offers a valuable framework to address these challenges, providing insights into healthcare investments, policy analysis and patient care pathways.

This research employs the real options theory, a financial concept, to delve into health economics challenges. Through a systematic approach, three distinct models rooted in this theory are crafted and analyzed. Firstly, the study examines the value of investing in emerging health technology, factoring in future advantages, associated costs and unpredictability. The second model is patient-centric, evaluating the choice between immediate treatment switch and waiting for more clarity, while also weighing the associated risks. Lastly, the research assesses pandemic-related government policies, emphasizing the importance of delaying decisions in the face of uncertainties, thereby promoting data-driven policymaking.

Three different real options models are presented in this study to illustrate their applicability and value in aiding decision-makers. (1) The first evaluates investments in new technology, analyzing future benefits, discount rates and benefit volatility to determine investment value. (2) In the second model, a patient has the option of switching treatments now or waiting for more information before optimally switching treatments. However, waiting has its risks, such as disease progression. By modeling the potential benefits and risks of both options, and factoring in the time value, this model aids doctors and patients in making informed decisions based on a quantified assessment of potential outcomes. (3) The third model concerns pandemic policy: governments can end or prolong lockdowns. While awaiting more data on the virus might lead to economic and societal strain, the model emphasizes the economic value of deferring decisions under uncertainty.

This research provides a quantified perspective on various decisions in healthcare, from investments in new technology to treatment choices for patients to government decisions regarding pandemics. By applying real options theory, stakeholders can make more evidence-driven decisions.

Decisions about patient care pathways and pandemic policies have direct societal implications. For instance, choices regarding the prolongation or ending of lockdowns can lead to economic and societal strain.

The originality of this study lies in its application of real options theory, a concept from finance, to the realm of health economics, offering novel insights and analytical tools for decision-makers in the healthcare sector.