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The low adoption of mobile banking (m-banking) in Indonesia and limited research on the adoption of m-banking motivate this research to understand the factors needed in developing m-banking to support the achievement of the national digital economy strategy in creating a digital ecosystem in Indonesia. This study aims to analyze the individual perspective factors that influence the adoption of m-banking applications in Indonesia.

This study used a quantitative approach using an online questionnaire to survey 444 respondents who used m-banking applications in Indonesia. The data obtained were processed using covariance-based structural equation modeling.

The results showed that health consciousness, the availability of resources, personal innovativeness and perceived information quality factors influenced the adoption of mobile banking applications in the static stage. In addition, this study found that one adoption stage could positively impact another adoption stage in adopting m-banking applications.

The development of m-banking can be promoted by considering the readiness of operational support infrastructure, regulations and application development, including functionality, security and user experience. Superior m-banking has implemented an end-to-end banking process with integrated customer relationship management (CRM) that supports cross-selling features according to user needs.

This study addresses the knowledge gap on individual perspectives that influence m-banking applications adoption. The authors integrate the e-government adoption model and CRM model in this study.

Drawing upon a systematic literature review in new technology, innovation transfer and diffusion theories, and from interviews with technology leaders in digital transformation programs in the US Oil & Gas (O&G) industry, the authors explore the relationships among O&G industry dynamics, organization's absorptive capacity and resource commitment for new digital technology adoption-implementation process.

The authors employed the empirical survey method to gather the data (a sample size of 172) in the US O&G industry and used structural equation modeling (SEM) to test the measurement model for validity and reliability and the conceptual model for hypothesized structural relationships.

The results provide support for the study’s causal model of adoption and implementation with positive and direct relationships between the initiation and trial stages, between the trial stages and the evaluation of effective outcomes and between the effective outcomes and the effective implementation stages of digital technologies. The results also reveal partial mediating relationships of industry dynamics, absorptive capacity and resource commitment between respective stages.

Based on the current study's findings, managers are recommended to pay attention to the evolving industry dynamics during the initiation stage of new digital technology adoption, to utilize the organization's knowledge-based absorptive capacity during digital technology trial and selection stages and to support the digital technology implementation project when the adoption decision of a particular digital technology has been made.

The empirical research contributes literature on digital technology adoption and implementation by identifying and demonstrating the importance of industry dynamics, absorptive capacity and resource commitment factors as mediating variables at various stages of the adoption-implementation process and empirically validating a process-based causal model of digital technology adoption and a successful implementation project that has been missing in the current body of literature on digital transformation.

The purpose of this paper is to investigate the role of trust and perceived enjoyment in the technology acceptance model by distinguishing distinct stages of adoption among street vendors (initial and advanced adoption stage).

Face-to-face interviews using a structured questionnaire were conducted with 430 street vendors in Bangkok; 415 usable surveys were analyzed. By applying K-means cluster analysis, two segments were found with 200 initial and 215 advanced adopters. A multi-group analysis was employed to investigate differences of relationships between the two groups.

The findings reveal significant similarities and dissimilarities between the two groups of vendors. Both initial and advanced adopters emphasize trust of service providers. The first group relies more on perceived ease of use and perceived enjoyment in motivating m-commerce adoption but depends less on perceived usefulness. On the contrary, for the latter group, the influence of perceived ease of use and perceived enjoyment significantly decreases, but the effect of perceived usefulness significantly increases.

This study sheds light on the managerial implications related to how service providers can tailor their marketing strategies to target vendors in disparate diffusion stages, and it encourages building trust between partners over time.

Due to the lack of theoretical and managerial understanding of factors that drive m-commerce adoption for micro businesses, this study identifies distinct adoption stages and offers valuable insights into the similarities and differences among initial and advanced adopters.

This study investigated the underlying influence mechanism between mHealth service quality (SQ) and users' adoption intention and compared the differences of consumer individual decision-making behaviors between the pre-adoption stage and the post-adoption stages.

This study built the pre-adoption and post-adoption models based on the stimulus-organism-response (S-O-R) model. Besides, this study collected 14,221 independent samples from 40 studies of pre-adoption intention to use and 12,876 independent samples from 36 studies of post-adoption intention to continue using and used meta-analysis structural equation modeling (MASEM) method to explore the formation of mHealth service quality influence on consumers toward adoption intention.

The results showed that (1) service quality positively trigger users' cognition response (i.e. perceived usefulness, perceived ease of use and perceived trust) and further positively drove the adoption and continuance intention; (2) there are similarities and differences in the relative importance of users' cognitive response between service quality and adoption intention at pre-adoption and post-adoption stages; (3) perceived trust (PTRU) played the most significant mediator in predicting users' adoption intention in both two stages; (4) perceived usefulness had a stronger influence than perceived ease of use (PEOU) on the adoption intention in pre-adoption while the result was just opposite in post-adoption stage.

This study could help service providers effectively allocate their limited resources to improve user adoption intention.

This study is the first one to open the black box of the underlying influence mechanisms between mHealth service quality and individual adoption intention in mHealth services and show differences in consumer decision-making according to the adoption stage. It provides a new perspective to the research in mHealth.

The purpose of this paper is to provide a better understanding of the determinants of business intelligence system (BIS) adoption stages. It develops and empirically tests a conceptual model for assessing the determinants of BIS diffusion on the evaluation, adoption, and use stages in the context of small and medium enterprises (SMEs).

Drawing on data from 181 SMEs the influence of technological, organizational, and environmental factors on BIS adoption stages were analyzed using the PLS-SEM method.

The paper provides empirical insights about how technological, organizational, and environmental factors affect individual BIS adoption stages.

The paper includes implications for managers and solution providers to understand the influence of various determinants to more effectively conclude the adoption process.

This study represents important progress in the theoretical understanding of the role of technological, organizational, and environmental factors across the different BIS adoption stages.

This chapter discusses the use of an extended stage model for the evaluation of the adoption of e-business in small and medium-sized enterprises (SMEs). Empirical studies of e-business adoption are rare in Middle Eastern and developing countries and the chapter provides valuable insight into this region, by presenting an account of the use of the extended stage model to explore the level of e-business adoption among Yemeni SMEs.

In making this examination, the challenges and opportunities that accompany e-business adoption are revealed. The internal drivers and barriers, such as finance and skills, are recognised along with the external factors that include infrastructure and legislation. It also provides valuable insight into the macro-level sociopolitical determinants of e-business adoption that have not previously been appreciated; the study was undertaken during the Yemen Civil War in 2016.

Current adoption models imply that organisations adopt technologies in a linear fashion, gradually increasing complexity and capability. This study makes an important contribution by recognising that there are multiple points at which SMEs may ‘enter’ the technology-adoption ladder.

Research into the construction industry’s adoption of modern equipment technologies, such as remote-controlled trucks, excavators and drones, has been neglected in comparison to the significant body of research into the adoption of information technology in construction. Construction research has also neglected to adequately consider the important role of vendors in the innovation diffusion process, focussing mostly on the role of the customer. Set within the context of Australia’s construction industry, the purpose of this paper is to address these gaps in knowledge by exploring the role of customers and vendors in the diffusion of modern equipment technologies into the construction industry.

Using contemporary models of innovation diffusion which move beyond the simple dualistic problem of whether innovation is supply-pushed or demand-pulled, 19 semi-structured interviews were undertaken with customers and vendors involved in two major modern equipment technology trade exhibitions in Australia. This was followed by the collection of documentary data in the form of photos, directory books, marketing material, catalogues, websites and booth and exhibition layouts to validate the proposed model and provide insights into vendor marketing strategies. These data were analysed using both content analysis and principal component analysis (PCA).

According to the PCA and content analysis, vendor’s engagement in the adoption of modern equipment technologies falls into three stages that correspond to three stages in the customer’s adoption process. In the first stage, customers identify possible solutions and recognise new technologies following a previous recognition of a need. Vendors provide facilities for attracting potential customers and letting customers know that their technology exists and can help solve the customer’s problem. The second stage involves customers gaining knowledge about the details of the new technology, and vendors focusing on detailed knowledge transfer through written materials and demonstrations of the functionality of the new technology. In the third stage, customers have specific questions that they want answered to assist them in comparing different vendors and solutions. By this stage, vendors have built a close relationship with the customer and in contrast to earlier stages engage in two-way communication to help the customer’s decision process by addressing specific technical and support-related questions.

The originality and value of this research is in addressing the lack of research in modern equipment technology adoption for building construction and the lack of data on the role of vendors in the process by developing a new empirical framework which describes the stages in the process and the ways that customers and vendors interact at each stage. The results indicate that conceptually, as the construction industry becomes more industrialised, current models of innovation adoption will need to develop to reflect this growing technological complexity and recognise that vendors and customers engage differently in the adoption process, according to the type of technology they wish to adopt.

While traditional theories of information and communication technology (ICT) adoption have been deployed to study ICT adoption in the past, these theories considers ICT adoption as static and rely on conceptualising factors as variables and predicting their levels of outcome at a single decision stage. Although much has been credited to these theories, they have continuously ignored the fact that as decisions to adopt are made and challenged along the adoption process, such decision can be influenced by the same, different or combination of factors at different stages of the adoption process. This paper aims to examine ICT adoption from a dynamic process perspective and to explore the key determinants and how these differ from one stage of the adoption process to another.

Qualitative method was adopted in this study. Both unstructured and semi-structured interviews were conducted in two separate stages using purposeful random sampling. Hybrid approach of thematic analysis was adopted in analysing the data.

This study develops a framework informed by actor network theory (ANT) concepts and finds that using ANT to examine the process of adoption helps to unveil the recursive nature of the process. The study reveals that the 14 determinants identified in this study influenced adoption at different stages. Factors such as ease of use, managerial time, customer focus and adoption influenced adoption at all the stages. This reveals that factors influencing ICT adoption are not static at one particular stage rather it may influence ICT adoption at different stages.

Qualitative research is often subjective and interpretive in nature, and one of the limitations is the sample used in this research. Considering the small number of interviews carried out in this study, the generalisation of finding and the framework remains to be established across a wider population. Therefore, the factors presented could be limited considering that a number of practitioners that are involved in establishing emerging ICT are numerous. Therefore, other factors are prevailing to other industries or sectors that may provide scholars another way of examining these factors. Also, the framework demonstrates that it is a valuable analytical tool for researchers to examine how and why different actors including small and medium enterprise (SME) managers act around emerging ICT.

This study develops a framework that revealed the interactive and recursive nature of ICT adoption and the determinants influencing the process of ICT adoption at different stages thereby advancing ICT adoption research. The study challenges researchers to always consider ICT adoption as dynamic and unpredictable instead of one-off action as factors influencing its adoption are not static rather; they vary from one stage to another.

The purpose of this paper is to develop a research model that links Radio Frequency Identification (RFID) adoption issues with established technology adoption stages suggested by Rogers theory of diffusion of innovation (DOI). The research model proposed in this study suggests that RFID adoption in retail industry progresses in different stages.

A mixed methodological perspective is used in this research. Key research issues were identified from a systematic content analysis of trade and academic articles in the first phase.

Data collected from Delphi study is used to test the propositions. It confirms key research issues associated with different adoption stages. Finally, it also confirms that the stages (knowledge, persuasion, design and decision, and implementation) influence RFID adoption decision.

The propositions that are developed in the model can be used in future studies for further development. More relevant items should be added to measure each variable. It can also allow future researchers and practitioners to take a more comprehensive approach to look at RFID adoption process as a whole and thus focus on relevant issues across all adoption stages.

The research model can provide insights to practitioner to make more informed RFID adoption decisions.

Rogers stage model is very important for technology diffusion studies but is not explored much. There is limited research on understanding the overall RFID adoption process. This study is an attempt to bridge that gap and draw attention toward future research in that direction. The research model that is developed links RFID research with existing research in the area of DOI.

Information and communications technology (ICT) offers enormous opportunities for individuals, businesses and society. The application of ICT is equally important to economic and non-economic activities. Researchers have increasingly focused on the adoption and use of ICT by small and medium enterprises (SMEs) as the economic development of a country is largely dependent on them. Following the success of ICT utilisation in SMEs in developed countries, many developing countries are looking to utilise the potential of the technology to develop SMEs. Past studies have shown that the contribution of ICT to the performance of SMEs is not clear and certain. Thus, it is crucial to determine the effectiveness of ICT in generating firm performance since this has implications for SMEs’ expenditure on the technology. This research examines the diffusion of ICT among SMEs with respect to the typical stages from innovation adoption to post-adoption, by analysing the actual usage of ICT and value creation. The mediating effects of integration and utilisation on SME performance are also studied. Grounded in the innovation diffusion literature, institutional theory and resource-based theory, this study has developed a comprehensive integrated research model focused on the research objectives. Following a positivist research paradigm, this study employs a mixed-method research approach. A preliminary conceptual framework is developed through an extensive literature review and is refined by results from an in-depth field study. During the field study, a total of 11 SME owners or decision-makers were interviewed. The recorded interviews were transcribed and analysed using NVivo 10 to refine the model to develop the research hypotheses. The final research model is composed of 30 first-order and five higher-order constructs which involve both reflective and formative measures. Partial least squares-based structural equation modelling (PLS-SEM) is employed to test the theoretical model with a cross-sectional data set of 282 SMEs in Bangladesh. Survey data were collected using a structured questionnaire issued to SMEs selected by applying a stratified random sampling technique. The structural equation modelling utilises a two-step procedure of data analysis. Prior to estimating the structural model, the measurement model is examined for construct validity of the study variables (i.e. convergent and discriminant validity).

The estimates show cognitive evaluation as an important antecedent for expectation which is shaped primarily by the entrepreneurs’ beliefs (perception) and also influenced by the owners’ innovativeness and culture. Culture further influences expectation. The study finds that facilitating condition, environmental pressure and country readiness are important antecedents of expectation and ICT use. The results also reveal that integration and the degree of ICT utilisation significantly affect SMEs’ performance. Surprisingly, the findings do not reveal any significant impact of ICT usage on performance which apparently suggests the possibility of the ICT productivity paradox. However, the analysis finally proves the non-existence of the paradox by demonstrating the mediating role of ICT integration and degree of utilisation explain the influence of information technology (IT) usage on firm performance which is consistent with the resource-based theory. The results suggest that the use of ICT can enhance SMEs’ performance if the technology is integrated and properly utilised. SME owners or managers, interested stakeholders and policy makers may follow the study’s outcomes and focus on ICT integration and degree of utilisation with a view to attaining superior organisational performance.

This study urges concerned business enterprises and government to look at the environmental and cultural factors with a view to achieving ICT usage success in terms of enhanced firm performance. In particular, improving organisational practices and procedures by eliminating the traditional power distance inside organisations and implementing necessary rules and regulations are important actions for managing environmental and cultural uncertainties. The application of a Bengali user interface may help to ensure the productivity of ICT use by SMEs in Bangladesh. Establishing a favourable national technology infrastructure and legal environment may contribute positively to improving the overall situation. This study also suggests some changes and modifications in the country’s existing policies and strategies. The government and policy makers should undertake mass promotional programs to disseminate information about the various uses of computers and their contribution in developing better organisational performance. Organising specialised training programs for SME capacity building may succeed in attaining the motivation for SMEs to use ICT. Ensuring easy access to the technology by providing loans, grants and subsidies is important. Various stakeholders, partners and related organisations should come forward to support government policies and priorities in order to ensure the productive use of ICT among SMEs which finally will help to foster Bangladesh’s economic development.