Purpose This paper aims to understand how strong brand attachment can intensify the feeling of perceived betrayal, leading to brand hate after a negative experience with the brand. The study further investigates how consumers make causal attributions for negative experiences when strong brand attachment exists. The moderating effect of a narcissistic personality in the dissemination of negative electronic word of mouth (eWOM) following brand hate is also tested. Design/methodology/approach The study uses a within-the-subject repeated measures experimental design. A total of 202 college students were exposed to two treatments (high versus no brand attachment), involving a situation of product failure of a smart phone brand. A total of 135 responses were used to compare the outcomes of the two treatments using multivariate analysis. The data of high brand attachment treatment (N = 202) were used to test the proposed research model using partial least square-structural equation modelling. Findings The results suggest that having a strong positive relationship with the brand can generate stronger feelings of perceived betrayal and brand hate after the brand transgresses the consumer’s expectations. The results indicate that resentful customers can resort to eWOM after feeling betrayed, even though the prior relationship with the brand was strong. Originality/value This paper extends the work on perceived betrayal to study brand hate and proposes that brand hate can arise even if there is a strong brand attachment. It contributes to the growing body of literature on brand hate and its possible antecedents. Additionally, the study poses some crucial managerial implications for the brand managers by suggesting that strong brand relationships not always ensure loyalty or commitment and can lead to consequences that are damaging for the brand equity.
PurposeThe study explores the readiness of government agencies to adopt artificial intelligence (AI) to improve the efficiency of disaster relief operations (DRO). For understanding the behavior of state-level and national-level government agencies involved in DRO, this study grounds its theoretical arguments on the civic voluntarism model (CVM) and the unified theory of acceptance and use of technology (UTAUT).Design/methodology/approachWe collected the primary data for this study from government agencies involved in DRO in India. To test the proposed theoretical model, we administered an online survey questionnaire to 184 government agency employees. To test the hypotheses, we employed partial least squares structural equation modeling (PLS-SEM).FindingsOur findings confirm that resources (time, money and skills) significantly influence the behavioral intentions related to the adoption of AI tools for DRO. Additionally, we identified that the behavioral intentions positively translate into the actual adoption of AI tools.Research limitations/implicationsOur study provides a unique viewpoint suited to understand the context of the adoption of AI in a governmental context. Companies often strive to invest in state-of-the-art technologies, but it is important to understand how government bodies involved in DRO strategize to adopt AI to improve efficiency.Originality/valueOur study offers a fresh perspective in understanding how the organizational culture and perspectives of government officials influence their inclinations to adopt AI for DRO. Additionally, it offers a multidimensional perspective by integrating the theoretical frameworks of CVM and UTAUT for a greater understanding of the adoption and deployment of AI tools with organizational culture and voluntariness as critical moderators.
PurposeThis research is conducted in the context of beauty salons in India, to investigate how enhanced perceived acceptance in interpersonal relationships through consuming beauty salon services can generate narcissistic brand love among consumers via the mediation of brand happiness. It also investigates the moderating impact of consumer's anxious interpersonal attachment style and cynicism on the relationship between perceived salon brand-interpersonal acceptance goal congruence and salon brand happiness.Design/methodology/approachTo test the hypothesized relationships, a survey was conducted among 225 regular consumers of beauty salon brands. The data were analyzed using Hayes' (2017) process macro in SPSS.FindingsThe results suggest that perceived goal congruence between beauty salon brand-interpersonal acceptance positively influences brand happiness, which in turn predicts consumer's narcissistic brand love. Consumer's anxious interpersonal attachment style positively moderates the effect of brand-interpersonal acceptance goal congruence on brand happiness, while cynicism negatively moderates the path.Originality/valueValue of the study lies in extending interpersonal acceptance and rejection (IPAR) theory to the domain of consumer–salon brand relationship, to posit that if salon brands satisfy consumers' interpersonal acceptance goals, there is a potential for such happy consumers to love the salon brand, albeit narcissistically.
Background To strengthen health systems, the shortage of physicians globally needs to be addressed. However, efforts to increase the numbers of physicians must be balanced with controls on medical education imparted and the professionalism of doctors licensed to practise medicine. Methods We conducted a multi-country comparison of mandatory regulations and voluntary guidelines to control standards for medical education, clinical training, licensing and re-licensing of doctors. We purposively selected seven case-study countries with differing health systems and income levels: Canada, China, India, Iran, Pakistan, UK and USA. Using an analytical framework to assess regulations at four sequential stages of the medical education to relicensing pathway, we extracted information from: systematically collected scientific and grey literature and online news articles, websites of regulatory bodies in study countries, and standardised input from researchers and medical professionals familiar with rules in the study countries. Results The strictest controls we identified to reduce variations in medical training, licensing and re-licensing of doctors between different medical colleges, and across different regions within a country, include: medical education delivery restricted to public sector institutions; uniform, national examinations for medical college admission and licensing; and standardised national requirements for relicensing linked to demonstration of competence. However, countries analysed used different combinations of controls, balancing the strictness of controls across the four stages. Conclusions While there is no gold standard model for medical education and practise regulation, examining the combinations of controls used in different countries enables identification of innovations and regulatory approaches to address specific contextual challenges, such as decentralisation of regulations to sub-national bodies or privatisation of medical education. Looking at the full continuum from medical education to licensing is valuable to understand how countries balance the strictness of controls at different stages. Further research is needed to understand how regulating authorities, policy-makers and medical associations can find the right balance of standardisation and context-based flexibility to produce well-rounded physicians.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.