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In the literature of industrial management, the focus is normally given on examining the factors that contribute to product innovation acceptance. The advocates of “pro-innovation bias” assume that consumers are open to new products and are willing to accept an innovative product. However, there is a high failure rate of technological innovations and most of the technological innovations were rejected due to users' resistance. Since the inception of innovation resistance theory (IRT), the number of studies that used IRT has gained much attention from scholars. However, the findings from these studies from various contexts are inconsistent, lack universality, and a clear understanding of technological innovation barriers. The study aims to determine whether the IRT theory is indeed valid and whether IRT is culturally invariant from the Eastern and Western cultures.

A meta-analysis based on a random-effects model and studies drawn from 24 countries and/or regions with a consolidated sample size of 10,463 was conducted. Cultural invariance was identified based on subgroup analysis. Moderator analysis was performed by applying the weighted linear regression.

The results reveal that tradition is the strongest barrier followed by the value, risk, image and usage barrier. Interestingly, there is a cultural invariance in IRT from the Eastern and Western cultures. Besides, there are significant moderating effects due to the temporal factor.

The study has contributed useful theoretical and managerial implications in advancing the product innovation literature.

This study aims to integrate Delone and McLean’s information system success (DMISS) model with the innovation resistance model to evaluate the relationship between behavioural intention to use (BIU) and innovation resistance in the context of neo-banking. The primary objective of this study is to identify the drivers of neo-banking adoption and the barriers to its adoption and incorporate constructs such as e-trust (ETR) and personal innovativeness (PIV) to provide a more comprehensive understanding of the factors influencing neo-banking adoption.

A structured survey-based questionnaire was used to gather data from a diverse sample population in India. The Partial Least Squares Structural Equation Modeling (PLS-SEM) model was employed to further examine the adoption of neobanking services and users' intention to use neobanking services.

This study reveals a significant correlation between BIU and the uptake of neobanking services, demonstrating the value of consumers' readiness to embrace these offerings. However, resistance to usage has emerged as a major obstacle for consumers concerned about data security, technology reluctance and perceived risks associated with digital-only neobanks.

Analysing the driving and restraining factors will provide substantial information on the formation of consumers' decision-making processes in the Indian banking industry, which is undergoing rapid digital transformation. This information is of great importance to scholars, practitioners and policymakers, as it highlights the factors that may facilitate or impede the adoption of neobanking in India. The outcomes of this analysis will be of particular interest to researchers, experts and stakeholders in the field as they will provide valuable insights into the dynamics of consumer behaviour in the Indian banking sector.

This study represents an initial effort to examine BIUs and usage resistance within the rapidly developing neobanking sector in India. The findings of this study build on the existing research in this area and contribute to the ongoing discussion on the adoption of neo-banking.

The purpose of this study is to develop and assess the effects of unified theory of acceptance and use of technology (UTAUT 2) constructs – effort expectancy (EE), social influence (SI) and hedonic motivation (HM) – on behavioural intention (BI), as well as the impact of innovation resistance theory (IRT) constructs – usage barrier (UB) and tradition barrier (TB) – on innovation resistance (IR) behavior in the context of digital zakat payment in Aceh. In addition, this study also examines how knowledge of fiqh zakat influences both BI and IR.

This was a quantitative study including 350 Acehnese persons who paid zakat online. This research used a Likert scale, and the sampling technique was purposive sampling applied for the Acehnese people. The research respondents were civil servants, private employees, BUMN employees (employees of State-Owned Enterprises), merchants, restaurant owners, professionals and other occupations who had paid professional zakat through a digital system mechanism. The data were analysed using partial least squares structural equation modelling.

This research found that the constructs built through the theory of UTAUT 2 explained the position of the EE variable, which had a significant effect on BI. On the other hand, the variable of SI and HM did not significantly affect BI in digital zakat payment. This finding demonstrated that BI significantly influenced actual usage (AU). UB and TB had no impact on IR, according to the theoretical framework developed by IRT. Yet, the knowledge about the fiqh zakat (KFZ) significantly affected the AU. In terms of the moderation role, the KFZ variable moderated the relationship between BI and AU. However, the KFZ variable did not moderate the relationship between IR and AU.

This research had limitations and could still be investigated further by involving a larger sample. This study does not include all UTAUT 2 and IRT constructs, but only involves UTAUT 2 and IRT constructs based on the phenomenon of digital zakat paying behavior in the people of Aceh.

This research had a managerial contribution and an evaluation of the use of digital zakat collection services in Aceh and zakat management institutions in various countries. The existence of significant EE should be a reference for zakat institutions to produce continuous payment applications with a higher level of convenience in the future. In addition, the government should encourage more organised fiqh zakat education in society to plan a more optimal zakat collection. The reason for this is that KFZ has been shown to moderate zakat intentions towards actual digital zakat payment behaviour.

The results of this study were then accommodated by the government to design a digital zakat collection system so that it resulted in optimising the collected zakat funds. The greater the zakat funds collected, the greater the economic impact and social resilience of the community was in the midst of the post-covid and global crisis.

This research provided an essential value in the aspect of collecting zakat funds, especially in the study of the behaviour of paying zakat digitally. The theory of planned behaviour predominated in earlier studies that investigated zakat-paying behaviour. Yet, this research was even more focused as it used the constructs of UTAUT 2 and IRT theory and applied the involvement of a moderator variable like fiqh zakat knowledge that was barely discussed.

Despite the efforts of governments and firms, consumer resistance toward digital innovations in the retail finance space continues to manifest rather visibly. Yet, the causes of consumer resistance toward innovations such as online procurement of financial products continue to remain under-explored. The present study attempts to address this gap by examining barriers that may constitute Indian consumers' resistance to buying financial products marketed digitally, using insurance as an exemplar. Precisely, the study measures five classic innovation resistance theory (IRT) barriers constituting consumers' resistance toward procuring digitally marketed insurance and examines the influence of consumers' demographic characteristics, measured through age and gender.

The conceptual model, resting on the theoretical proposition of IRT, was tested using data collected from 420 smartphone users. Given that, the data did not satisfy the multivariate assumptions of normality, homoscedasticity and linearity, artificial neural network approach was used for analysis. The analysis served as the basis for determining the relative importance of the five barriers in influencing consumer resistance.

The results indicated that the image barrier was the most influential barrier impacting consumer resistance, followed by usage, tradition, risk and value barriers. Moreover, as revealed by the values of correlations, the direction of influence was positive. Notably, the relationship of all barriers except tradition with consumer resistance was found to be nonlinear.

The study makes a novel contribution in two ways – one by extending IRT to a new area, i.e., resistance to buying financial products online, thereby further enhancing its applicability, and the other by exploring consumer resistance to e-procurement of life and nonlife insurance, which to the best of the authors' knowledge, has not been examined so far despite the established exigency.

The new ways to complete financial transactions have been developed by setting up mobile payment (m-payment) platforms and such platforms to access banking in the financial mainstream can transact as never before. But, does m-payment have veiled consequences? To seek an answer, the research was undertaken to explore the dark sides of m-payment for consumers by extending the theory of innovation resistance (IR) and by measuring non-adoption intention (NAI).

Three hundred individuals using popular online m-payment apps such as Paytm, PhonePe, Amazon Pay and Google Pay were surveyed for the primary data. IBM AMOS based structural equation modelling (SEM) was used to analyse the data.

Each m-payment transaction leaves a digital record, making some vulnerable consumers concerned about privacy threats. Lack of global standards prevents consumers from participating in the m-payment system properly until common interfaces are established based on up-to-date standards. Self-compassion (SC) characteristics such as anxiety, efficacy, fatigue, wait-and-see tendencies and the excessive choice of technology effect contribute to the non-adoption of m-payment.

This study proposes a threat model and empirically explores the dark sides of m-payment. In addition, it also unveils the moderator's role of SC in building the structural relationship between IR and NAI.

This paper aims to investigate the effect of factors that inhibit adoption of mobile payments service in India.

Based on the extant literature on mobile payment service and other related literature, factors were identified that drive consumer resistance toward its adoption. It engaged “innovation resistance theory” framework for understanding consumer resistance. The framework addressed five categories of barriers, namely, usage, value, risk, image and tradition that lead to negative perception of innovation, and therefore, induces positive impact on its resistance. Additionally, the study considered a few lesser investigated barriers (habitual use of cash, surveillance, technology) for the study, thus extending the existing theoretical framework. Hypotheses were framed, field data were collected and then analyzed using multivariate techniques.

Few interesting observations were made from the study. Usage, image and value barriers hindered adoption of mobile payment service. In case of men, usage, value and image were the primary barriers. For women, usage, image, habitual use of cash and technology acted as barriers that curbed mobile payments service adoption. Additionally, except risk, tradition and surveillance barriers, relationships of all other constructs with adoption intention were moderated by gender.

This research was limited to the views of the urban population in India who used mobile payments service. The results may vary across geographical contexts because of culture or socioeconomic differences.

The growth of mobile payment service has remained sluggish in India despite high levels of digitization. The study results will offer valuable insights to the Indian business managers and policymakers to identify what action plan needs to be instituted to make mobile payments service more attractive and acceptable to users.

This empirical study extended and tested the classical innovation resistance theory framework by adding three less studied barriers (surveillance, habitual use of cash and technology) in a developing nation, thus enriching the current literature on consumer resistance toward mobile payments. It also examined the moderating effect of gender on mobile payments service adoption.

There are two main objectives in this study. First, we aim to develop a set of constructs for health task management support (HTMS) features to evaluate which health-related tasks are supported by mobile health application (mHealth app) functions. Second, drawing on innovation resistance theory (IRT), we examine the impacts of the newly developed HTMS dimensions on perceived usefulness, alongside other barrier factors contributing to technology anxiety.

Using a mixed-method research design, this research seeks to develop new measurement scales that reflect how mHealth apps support older adults’ health-related needs based on interviews. Subsequently, data were collected from older adults and exploratory factor analysis was used to confirm the validity of the new scales. Partial least squares structural equation modeling (PLS-SEM) was used to analyze survey data from 602 older adults.

The PLS-SEM results indicated that medical management task support, dietary task support, and exercise task support were positively associated with perceived usefulness, while perceived complexity and dispositional resistance to change were identified as antecedents of technology anxiety. Perceived usefulness and technology anxiety were found to positively and negatively influence adoption intention, respectively.

This study enriches the information systems literature by developing a multidimensional construct that delineates how older adults’ health-related needs can be supported by features of mHealth apps. Drawing on IRT, we complement the existing literature on resistance to innovation by systematically examining the impact of five types of barriers on technology anxiety.

The rise of artificial intelligence (AI) applications has driven enterprises to provide many intelligent services to consumers. For instance, customers can use chatbots to make relevant inquiries and seek solutions to their problems. Despite the development of customer service chatbots years ago, they require significant improvements for market recognition. Many customers have reported negative experiences with customer service chatbots, contributing to resistance toward their use. Therefore, this study adopts the innovation resistance theory (IRT) perspective to understand customers’ resistance to using chatbots. It aims to integrate customers’ negative emotions into a predictive behavior model and examine users’ functional and psychological barriers.

In this study, we collected data from 419 valid individuals and used structural equation modeling to analyze the relationships between resistance factors and negative emotions.

The results confirmed that barrier factors affect negative emotions and amplify chatbot resistance influence. We discovered that value and risk barriers directly influence consumer use. Moreover, both functional and psychological barriers positively impact negative emotions.

This study adopts the innovation resistance theory perspective to understand customer resistance to using chatbots, integrates customer negative emotions to construct a predictive behavior model and explores users’ functional and psychological barriers. It can help in developing online customer service chatbots for e-commerce.

Robots have been adopted in numerous tourism and hospitality sectors, including restaurants. This study aims to investigate fast-food employees' use of service robots (SRs) in Pakistan.

This study used a conceptual model based on innovation resistance theory (IRT). By employing structural equation modeling (SEM) in Smart-PLS 3.2.8, we evaluated data from 247 valid respondents.

The findings demonstrated that drivers of robot adaptation significantly influenced image barriers, risk barriers, traditional barriers, usage barriers and value barriers. The results also revealed that usage, image and traditional barriers significantly affect usage intention.

This study enhances the research on robotics acceptance in tourism and hospitality and subsequently aids in the planning for post-COVID-19 resumption. This study offers several practical and theoretical insights for further investigation.

The current study tries to better understand the resistance toward food delivery applications (FDAs). This study has adapted the existing criteria to measure different consumer barriers toward FDAs. It also examined the relationships between various consumer barriers, intention to use FDAs and word-of-mouth (WOM).

This study utilized the innovation resistance theory (IRT) and a mixed-method approach comprised of qualitative essays submitted by 125 respondents and primary surveys (N = 366) of FDA users.

Tradition barrier (trust) shared a negative association with use intention, while image barrier (poor customer service) shared a negative association with WOM. The intention to use was positively associated with WOM. Additionally, the study results reveal that image barrier (poor customer experience) and value barrier (poor quality control) were, in fact, positively related to WOM. This study also discusses the managerial and theoretical implications of these findings and the scope for further research on FDAs.

FDAs have revolutionized the food delivery industry and made it more comfortable and convenient for the consumers. However, FDA service providers are facing challenges from both customers and restaurants. Although scholars investigated customer behavior toward FDAs, no prior study has focused on consumer barriers toward FDA usage.