Technology Adoption Literature Research Articles

On the heterogeneity in consumer preferences for electric vehicles across generations and cities in China

China is currently the world's biggest electric vehicle (EV) market, in which mostly mature consumers in first-tier cities are buying EVs. However, the changing market and policy environment are challenging the sustainability of this trend. This study conducts a nationwide stated preference (SP) experiment in China to examine preference heterogeneity towards EVs across (1) different generations and (2) different tiers of cities. Discrete choice analysis reveals that the tier of cities has a significant effect on adoption preferences for EVs. Surprisingly, consumers in smaller cities exhibit stronger preference for EVs, while an insignificant difference in preference is found between consumers of different generations. The interaction effect between the tier of cities and the generations further demonstrates that younger consumers in small cities most prefer EVs. This can be explained by their evaluations of the psychosocial advantages of EVs and their aspiration for a future of EV-based mobility. This research contributes to the broad literature of technology adoption, but more specifically, the research offers new insights on consumers’ EV preference heterogeneity with respect to geographic and demographic dimensions. The study has important business and policy implications relating to the EV transition in China in consideration of the two tested dimensions.

Exploring how internet services can enhance elderly well-being

PurposeThis study aims to investigate how Internet services can improve the well-being of elderly consumers. Drawing on transformative service research (TSR) and technology adoption literature, it examines the main challenges for the elderly when adopting Internet services and how they and their family members can co-create value to improve the elderly service inclusion and well-being.Design/methodology/approachA qualitative methodology is used to identify challenges, value co-creation behaviors and well-being outcomes of elderly individuals and their family members when using Internet services. The data collection method involved 24 in-depth interviews with consumers over 75 years of age and their family members.FindingsThis research first recognizes specific challenges for the elderly in adopting Internet services related to resistance to technology adoption and health impairments. Second, the findings identify value co-creation behaviors held by elderly consumers of Internet services: learning and formal training, complying with indications and seeking help when they encounter problems with technology. Family members also contribute to elderly well-being through two value co-creation behaviors: helping and supporting elderly relatives with technology and being patient and tolerant when they need support. Finally, these behaviors are found to influence five dimensions of elderly consumers’ well-being: enjoyment, personal growth, mastery, autonomy and social connectedness.Originality/valueThis study addresses a gap in the literature by exploring the value co-creation behaviors of elderly consumers of Internet services and their family members for improving well-being outcomes. Understanding value co-creation and well-being for elderly consumers of Internet services is an emerging and under-researched area in TSR and service inclusion literature.

Impact of ERP Implementation on Productivity and Profitability: An Empirical Study on the Largest Bangladeshi Steels Manufacturer

The research aims to evaluate the impact of Enterprise Resources Planning (ERP) implementation on the productivity and profitability of BSRM Steels Limited. The study focuses on addressing the gap in technology adoption literature by undertaking an empirical comparison of the impact of ERP implementation. Five productivity variables called service time, lead time, inventory turnover, output-input ratio, and warehouse cost are evaluated. Gross Profit Margin represents profitability as ERP is mainly implemented in the inventory management system of BSRM. Paired sample t-tests between the pre and post ERP performances have been used to evaluate the impact of ERP. Ten years' data ranging from 2010 to 2019 have been considered for the study. Five years' data (2010-2014) consist of before ERP period, and the other five years' data (2015-2019) represent after ERP implementation period. The study reveals that both the productivity and profitability of BSRM have significantly improved after ERP implementation. This paper will have an impactful contribution to the academic literature of technology adoption in the manufacturing sector, particularly for ERP implementation in the steel industry of Bangladesh, which could be supportive for further study on the topic.

Impact of visual typicality on the adoption of wearables

AbstractWith the recent influx of IT firms and big‐name fashion brands into the wearables market, the visual design of wearables has become a crucial factor in consumer choices. However, little research exists on this topic. Drawing upon the literature of technology adoption and design aesthetics, this study examines how the visual typicality of wearables affects their adoption by consumers. More specifically, the research tests the impact of the consumer‐perceived visual typicality of smartwatches on purchase intention through the psychological antecedents to wearable adoption (i.e., effort expectancy, performance expectancy, social influence, playfulness). The hypothesized relationships among the variables were tested in an online survey with 409 U.S. participants, where fictitious smartwatch designs were employed as the stimuli. In the results, perceived visual typicality of the smartwatch designs significantly decreased perceived performance and playfulness of the watch. Perceived visual typicality also had a negative impact on participants' purchase intention. Among the four psychological antecedents to wearable adoption, perceived playfulness played the most significant role in the relationship between the visual typicality and purchase intention. The moderation effect of gender was partially supported: Visual typicality significantly decreased purchase intention for females whereas it had no impact on the wearable adoption for males.

Digital Transformation of the Agricultural Sector: Pathways, Drivers and Policy Implications

AbstractThe digital transformation of agriculture is enabling the collection of vast amounts of geo‐referenced information about growing conditions within the field and facilitating the automated implementation of spatially varying input applications. This has the potential to increase production efficiency, reduce overapplication of inputs, lower input waste and pollution, and improve farm profitability. We discuss the pathways by which digital agricultural technologies have the potential to affect crop management, and current trends and patterns of adoption of digital technologies. We provide insights from the technology adoption literature on the factors that can be expected to influence the adoption of emerging digital technologies and the findings from the empirical literature on the determinants of adoption of these types of technologies. We conclude with a discussion of the design of policy incentives to induce the adoption of digital technologies cost‐effectively, the challenges in implementing such policies and the opportunity that digital technologies offer for addressing these challenges.

Predicting the actual use of m-learning systems: a comparative approach using PLS-SEM and machine learning algorithms

ABSTRACT Despite the plethora of m-learning acceptance studies, few have tackled the importance of examining the actual use of m-learning systems from the lenses of social influence, expectation-confirmation, and satisfaction. Additionally, most of the prior technology adoption literature tends to use the structural equation modeling (SEM) technique in analyzing the structural models. To address these limitations, this study extends the technology acceptance model (TAM) with the expectation-confirmation model (ECM) and social influence to predict the actual use of m-learning systems. A comparative approach using the partial least squares-structural equation modeling (PLS-SEM) and machine learning algorithms was employed to test the proposed model with data collected from 448 students. The results revealed that both techniques have successfully provided support to all the hypothesized relationships of the research model. More interesting, the J48 classifier has performed better than the other classifiers in predicting the dependent variable in most cases. The employment of a comparative analytical approach is believed to add a significant contribution to the information systems (IS) literature in general, and the m-learning domain in specific.

A dual-factor theory of WTs adoption in aged care service operations – a cross-country analysis

PurposeThis study focuses on the adoption of wearable technologies in a context where care-providing organizations can offer, in collaboration with caregivers, better care. Drawing on dual-factor theory and from the caregiver perspective, this study identifies and examines factors of technology adoption in four developing countries.Design/methodology/approachThis study was undertaken using a quantitative approach. A survey was distributed among 1,013 caregivers in four developing countries in Asia including Iran, Azerbaijan, Turkmenistan and Iraq and collected quantitative data for model validation and hypotheses analysis. Building on the technology adoption literature, we identified six constructs that impact the behavioral intention of caregivers to use wearable technologies in aged care-providing organizations.FindingsOur dual-factor model was successfully validated, and all hypotheses were supported. However, different results were found in the selected countries within the cross-country analysis.Originality/valueThis study has significant implications for the study of emerging technologies in aged care service operations. It provides a theoretical framework that may be adapted for future research, enabling practitioners in aged care to better understand the crucial role of technology adoption in service operations. Less attention was paid to the adoption of wearable technologies in aged care, particularly in developing countries, where healthcare services in aged care impose heavy costs on care providers.

Factors explaining why some citizens engage in E-participation, while others do not

Governments have adopted e-participation, but citizens' engagement in e-participation is limited. While studies have visited the topic of e-participation factors, few have considered why some citizens engage in e-participation, while others do not. Drawing on social capital literature and technology adoption literature, this research suggests an integrated model of citizens' e-participation and empirically tests the model. Using an e-participation survey data collected in 2019, this study finds that citizens with a stronger social capital—a commitment to the community, ownership of the community, and trust in government—are more likely to engage in e-participation. However, the results do not show the significance of most TAM and TPB variables—perceived usefulness, perceived ease of use, and attitude toward e-participation. Only subjective norm and perceived behavioral control, core constructs of TPB, are significantly and positively related to citizens' engagement in e-participation. These findings demonstrate that individual social capital factors are more significant than TAM and TPB factors in explaining why some citizens use e-participation channels or applications, while others do not. The study contributes to the literature by providing empirical evidence of the significance of social capital factors and non-significance of technology adoption factors when considered in a model that compares between users and non-users.

Adoption of artificial intelligence (AI) for talent acquisition in IT/ITeS organizations

PurposeHuman resource managers are adopting AI technology for conducting various tasks of human resource management, starting from manpower planning till employee exit. AI technology is prominently used for talent acquisition in organizations. This research investigates the adoption of AI technology for talent acquisition.Design/methodology/approachThis study employs Technology-Organization-Environment (TOE) and Task-Technology-Fit (TTF) framework and proposes a model to explore the adoption of AI technology for talent acquisition. The survey was conducted among the 562 human resource managers and talent acquisition managers with a structured questionnaire. The analysis of data was completed using PLS-SEM.FindingsThis research reveals that cost-effectiveness, relative advantage, top management support, HR readiness, competitive pressure and support from AI vendors positively affect AI technology adoption for talent acquisition. Security and privacy issues negatively influence the adoption of AI technology. It is found that task and technology characteristics influence the task technology fit of AI technology for talent acquisition. Adoption and task technology fit of AI technology influence the actual usage of AI technology for talent acquisition. It is revealed that stickiness to traditional talent acquisition methods negatively moderates the association between adoption and actual usage of AI technology for talent acquisition. The proposed model was empirically validated and revealed the predictors of adoption and actual usage of AI technology for talent acquisition.Practical implicationsThis paper provides the predictors of the adoption of AI technology for talent acquisition, which is emerging extensively in the human resource domain. It provides vital insights to the human resource managers to benchmark AI technology required for talent acquisition. Marketers can develop their marketing plan considering the factors of adoption. It would help designers to understand the factors of adoption and design the AI technology algorithms and applications for talent acquisition. It contributes to advance the literature of technology adoption by interweaving it with the human resource domain literature on talent acquisition.Originality/valueThis research uniquely validates the model for the adoption of AI technology for talent acquisition using the TOE and TTF framework. It reveals the factors influencing the adoption and actual usage of AI technology for talent acquisition.

The effect of the privacy policy of Health Information Exchange (HIE) on patients’ information disclosure intention

Health Information Exchanges (HIEs) enable personal information sharing between providers. Patients’ information disclosure intention is critical for a successful rollout of HIE networks. Existing studies mostly demonstrate that perceived privacy policy only influences the cognitive beliefs of patients about disclosing health information. However, little is know whether it also affects the emotion provoked by the sharing nature of the technology. Based on the Theory of Reasoned Action (TRA), the technology adoption literature, and the trust literature, we theoretically explain and empirically test the impacts of perceived transparency of privacy policy on cognitive trust and emotional trust in an HIE, and the effects of trust dimensions on the intention to disclose health information. An online survey was conducted using data from individuals who were aware of HIE through experiences with a (or multiple) providers participating in an HIE network. The SEM analysis results provide empirical support for the proposed model. The model highlights the critical role of perceived transparency of privacy policy in building trust in HIE. Findings suggest that awareness about HIE security measures and sharing procedures encourages patients to be cognitively and emotionally involved with the HIE system. Consequently, when the trust is formed, they become more likely to disclose health information.

Understanding the determinants of mHealth apps adoption in Bangladesh: A SEM-Neural network approach

Due to the low adoption rate of mHealth apps, the apps designers need to understand the factors behind adoption. But understanding the determinants of mHealth apps adoption remains unclear. Comparatively less attention has been given to the factors affecting the adoption of mHealth apps among the young generation. This study aims to examine the factors influencing behavioral intention and actual usage behavior of mHealth apps among technology prone young generation. The research model has extracted variables from the widely accepted Unified Theory of Acceptance and Use of Technology (UTAUT2) alongside privacy, lifestyles, self-efficacy and trust. Required data were collected from mHealth apps users in Bangladesh. Firstly, this study confirmed that performance expectancy, social influence, hedonic motivation and privacy exerted a positive influence on behavioral intention whereas facilitating conditions, self-efficacy, trust and lifestyle had an influence on both behavioral intention and actual usage behavior. Secondly, the Neural Network Model was employed to rank relatively significant predictors obtained from structural equation modeling (SEM). This study contributes to the growing literature on the use of mHealth apps in trying to elevate the quality of patients' lives. The new methodology and findings from this study will significantly contribute to the extant literature of technology adoption and mHealth apps adoption intention especially. Therefore, for practitioners concerned with fostering mHealth apps adoption, the findings stress the importance of adopting an integrated approach centered on key findings of this study.

An empirical investigation of the adoption of mobile health applications: integrating big data and social media services

With the advancement of digital technologies, the mobile healthcare industry aims to enhance health intelligence through delivering transformational digital services. This study integrates knowledge derived from three models of innovation diffusion, privacy calculus, and information systems success with the current studies on technology acceptance literature in the context of mHealth apps. It focuses on the contribution of big data and social media in enhancing mobile health apps and their impact on patients’ behavior and adoption. Through structural equation modeling of 582 questionnaires, this study develops a framework analyzing the impact of data quality, social interactivity, personalization, data risk, and performance risk. The study confirms the association between personalization, data quality, and data risk on the adoption decisions, while it did not find a link between social connectivity and the adoption decision. Theoretically, this paper builds new knowledge on the technology adoption literature by emphasizing digital services in the context of mobile health apps. Practically, this paper can assist the healthcare care industry to re-engineer its traditional business models by delivering enhanced digital services during the design of mobile health apps.

The impacts of the privacy policy on individual trust in health information exchanges (HIEs)

PurposeHealth information exchange (HIE) initiatives utilize sharing mechanisms through which health information is mostly transmitted without a patient's close supervision; thus, patient trust in the HIE is the core in this setting. Existing technology acceptance theories mainly consider cognitive beliefs resulting in adoption behavior. The study argues that existing theories should be expanded to cover not only cognitive beliefs but also the emotion provoked by the sharing nature of the technology. Based on the theory of reasoned action, the technology adoption literature, and the trust literature, we theoretically explain and empirically test the impact of perceived transparency of privacy policy on cognitive trust and emotional trust in HIEs. Moreover, the study analyzes the effects of cognitive trust and emotional trust on the intention to opt in to HIEs and willingness to disclose health information.Design/methodology/approachAn online survey was conducted using data from individuals who were aware of HIEs through experience with at least one provider participating in an HIE network. Data were collected from a wide range of adult population groups in the United States.FindingsThe structural equation modeling analysis results provide empirical support for the proposed model. The model highlights the strategic role of the perceived transparency of the privacy policy in building trust in HIEs. When patients know more about HIE security measures, sharing procedures, and privacy terms, they feel more in control, more assured, and less at risk. The results also show that patient trust in HIEs may take the forms of intention to opt in to an HIE and willingness to disclose health information exchanged through HIE networks.Originality/valueThe findings of this study should be of interest to both academics and practitioners. The research highlights the importance of developing and using a transparent privacy policy in the diffusion of HIEs. The findings provide a deep understanding of dimensions of HIE privacy policy that should be addressed by health-care organizations to exchange personal health information in a secure and private manner.

Effectual and causal reasoning in the adoption of marketing automation

Research on technology adoption in organizations traditionally assumes that these organizations follow rational, strategic and planned adoption processes. However, a gradually emerging view is that the adoption of technology is also characterized by entrepreneurial or effectual reasoning, primarily due to technological and market uncertainties that call for more agile and experimental approaches at the digital age. Drawing on effectuation theory, we develop a research framework to examine the managerial reasoning during the adoption of marketing automation technology. Based on the results of a comparative multiple-case study on four large-sized industrial firms, we develop a maturity model of marketing automation adoption and show that even large-sized B2B companies apply effectual reasoning, which problematizes the rationality assumption in the technology adoption literature. Second, we show that during the adoption process, organizations' dominant reasoning mode follows an iterative pattern in which the adopting organization moves back and forth between effectuation and causation. Finally, we identify five key domains of marketing automation (customer knowledge, information systems infrastructure, analytics, interdepartmental dynamics and change management) and describe their gradual evolution at different stages of the adoption process.

Why Do Not We Use Password Managers? A Study on the Intention to Use Password Managers

Why don't individuals follow the best information security practices? We address an aspect of this question by focusing on one of the most common authentication methods – passwords. To promote better password habits, security experts consistently recommend the use of password managers as a best practice, but recent research shows their usage rate is low. Therefore, understanding the factors that influence the use of a password manager is important. We contribute to this cause by drawing on information security and technology adoption literature. Survey results from 120 participants with varying numbers of internet accounts yield some counterintuitive findings. As proposed, perceived severity and perceived vulnerability of password loss strongly influenced intent to use password managers. However, perceived ease of use diminished the intent to use password managers, and trust is only partially supported. Our results indicate that 'security' aspects of password managers are more important than 'usability' aspects. The implications of these findings for password management are discussed.

The Impacts of the Perceived Transparency of Privacy Policies and Trust in Providers for Building Trust in Health Information Exchange: Empirical Study.

BackgroundIn the context of exchange technologies, such as health information exchange (HIE), existing technology acceptance theories should be expanded to consider not only the cognitive beliefs resulting in adoption behavior but also the affect provoked by the sharing nature of the technology.ObjectiveWe aimed to study HIE adoption using a trust-centered model. Based on the Theory of Reasoned Action, the technology adoption literature, and the trust transfer mechanism, we theoretically explained and empirically tested the impacts of the perceived transparency of privacy policy and trust in health care providers on cognitive and emotional trust in an HIE. Moreover, we analyzed the effects of cognitive and emotional trust on the intention to opt in to the HIE and willingness to disclose health information.MethodsA Web-based survey was conducted using data from a sample of 493 individuals who were aware of the HIE through experiences with a (or multiple) provider(s) participating in an HIE network.ResultsStructural Equation Modeling analysis results provided empirical support for the proposed model. Our findings indicated that when patients trust in health care providers, and they are aware of HIE security measures, HIE sharing procedures, and privacy terms, they feel more in control, more assured, and less at risk. Moreover, trust in providers has a significant moderating effect on building trust in HIE efforts (P<.05). Results also showed that patient trust in HIE may take the forms of opt-in intentions to HIE and patients’ willingness to disclose health information that are exchanged through the HIE (P<.001).ConclusionsThe results of this research should be of interest to both academics and practitioners. The findings provide an in-depth dimension of the HIE privacy policy that should be addressed by the health care organizations to exchange personal health information in a secure and private manner. This study can contribute to trust transfer theory and enrich the literature on HIE efforts. Primary and secondary care providers can also identify how to leverage the benefit of patients’ trust and trust transfer process to promote HIE initiatives nationwide.

The impact of blockchain adoption on competitive performance: the mediating role of process and relational innovation

ABSTRACTWhile Blockchain is heralded as an industry ‘game changer’, empirical studies have yet to demonstrate how it has positive performance impacts. Building on emerging blockchain research and the information technology adoption literature, this study develops a research model that links blockchain adoption in the supply chain to competitive performance through process innovation and relational innovation. The study uses data collected from 344 supply chain professionals working in companies with Blockchain experience and partial least squares modelling to test the proposed model. The results support the research model and confirm that competitive performance is directly improved through blockchain adoption and also indirectly through blockchain-enabled process and relational innovation. Our findings advance practice and theory by contributing to the emerging literature on blockchain and enriching our understanding of the performance impacts of blockchain adoption and use in the supply chain.

The mediating impact of demonetisation on customer acceptance for IT-enabled banking services

PurposeThe purpose of this paper is to explore the mediating role of demonetisation in the usage of IT-enabled banking services (ITeBS). The study extends the theory of technology readiness (TR) (Parasuraman and Colby, 2015) by incorporating the behavioural intention and actual usage of ITeBS.Design/methodology/approachBased on the theory of TR and encompassing the impact of demonetisation, the study examines the functional relationship of TR, behavioural intention and actual usage. Structural equation modelling and mediation analysis are applied on a data set of 474 usable responses.FindingsThe study confirms that TR is a significant factor in customer’s intention to use ITeBS. The demonetisation variable fully mediates the relationship model, which implies a significant finding in the consumer acceptance literature.Practical implicationsThe result of this study proposes three major implications. Primarily, the banks should focus on providing simple and user-friendly ITeBS interface and its uninterrupted access. It is necessary to educate the customers by giving them a trial of the service. Furthermore, social media platforms may be utilised as an effective and efficient tool to resolve customer complaints.Originality/valueThis study is first of the attempts to investigate government’s digital push in the technology adoption literature. The results indicate significant influence of demonetisation on the usage of ITeBS.

Does unified theory of acceptance and use of technology (UTAUT) reduce resistance and anxiety of individuals towards a new system?

Purpose Technology acceptance is an incremental approach that has developed over the years. Taking technology acceptance or adoption literature into consideration, the paper aims to investigate the mediating role of adoption readiness, constructed on the basis of the unified theory of acceptance and use of technology (UTAUT), on the relationship between user resistance as well as user anxiety and attitude toward using a system. Design/methodology/approach In consideration of previous studies, the public personnel’s adaptation of electronic document management systems is within the scope of the present research. Gathering data from 262 administrative personnel working in a public university, explanatory and second-order confirmatory factor analyses were done for the UTAUT scale. In addition, reliability and construct validity were tested for each scale; UTAUT, user resistance, user anxiety and attitude toward using. Relationships among variables of the research were controlled by the measurement model and then the structural model was tested. Findings Confirming previous research, the scales of UTAUT, user resistance, user anxiety and attitude toward using were found to have acceptable reliability and internal consistency. In addition, the implications of the paper showed user resistance influenced attitude toward using indirectly, by affecting adoption readiness. It also indicated that adoption readiness fully mediated the relationship between user anxiety and attitude toward using. Originality/value Negative behavioral antecedents of UTAUT are the focus of the paper. Reducing the negative effects of resistance as well as anxiety of individuals on their attitudes using a system is emphasized in the technology acceptance literature. Furthermore, defining each dimension of UTAUT as a single construct, adoption readiness, and proving the intervening role of adoption readiness between user resistance, as well as anxiety, on the attitude toward using a system are contributions to the literature.

Factors Influencing Smartphone Adoption: A Study in the Indian Bottom of the Pyramid Context

The usage of smartphones is increasing with each passing day. The growth of wireless subscription in India in the last 5 years is very high. However, the penetration rate of smartphones among low-income people is significantly low. Looking at the near saturation and high competition of markets at the higher side of the economic pyramid, companies are trying to explore the segment of low-income people termed ‘Bottom of the Pyramid’ (BOP). In order to explore the BOP market for smartphones, one needs to realize the factors influencing the adoption of smartphones at the BOP. Our study explores these factors with reference to the existing literature of technology adoption. A theoretical framework is proposed and tested with 266 valid data points. Structural equation modelling (SEM) is used to test the proposed framework. The empirical analysis revealed that ‘performance expectancy’, ‘effort expectancy’ and ‘perceived monetary value’ have a positive impact on the ‘behavioural intention’ of using smartphones at BOP. ‘Smartphone anxiety’ and ‘smartphone self-efficacy’ are found to have an impact on ‘effort expectancy’.