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The purpose of this paper is to examine the effect of gamification on students’ e-learning adoption. In addition, this paper examines the effect of two mediations, that is, flow and engagement between gamification and e-learning adoption by using sequential mediation analysis.

The authors used the online survey method to collect the 570 responses through convenience sampling procedure. Sequential mediation analysis technique was used to test the mediation hypothesis.

The findings of this paper revealed that gamification elements are an important feature of flow, engagement in e-learning adoption process. Also, the paper found that engagement in the learning process is a key element for students to adopt e-learning.

This paper makes its contribution to the literature related to gamification and e-learning adoption. The paper signifies the importance of gamification as an educational application in e-learning environment and its contribution in designing an interactive learning environment.

Empirically, to the best of the authors’ knowledge, it is the first paper to examine the sequential mediation model of gamification in the education sector in a developing nation like India. Furthermore, this paper also extends engagement and flow theory related to e-learning process by showing how students’ engagement and flow impact the e-learning adoption in the gamified environment.

The purpose of this paper is to identify factors that affect farm acceptance of the new seeds. This paper develops a Bivariate Probit model with adjusted sample selection bias to analyze Chinese farmers' sequential decision‐making process in their adoption of plant new varieties (new seeds) under the new Variety Property Right Protection System.

Face‐to‐face interviews with farm households in 22 provinces were used to gather questionnaire information. A total of 341 surveys were collected and analyzed using a Bivariate Probit model adjusted for sample selection bias problems. Descriptive statistics for each selected variable used in the model are also presented.

This study concluded that farm location, land size, farm perceived dealer reputation, and farmer‐to‐farmer word‐of‐mouth information were found to be important factors that affect farm adoption of new seeds.

This study is based on first‐hand survey information collected by the researchers. Thus, the results are original and were not published elsewhere.

This paper examines the application of real option theory to sequential investment decision-making. In an effort to contribute to the development of criteria that discriminate between investments that confer growth options from those that confer deferral options, we introduce a conceptual model that explains technological adoption as a sequence of embedded options. Upon the introduction of each successive technological generation, a firm may either defer investment and wait for the arrival of a future generation or invest immediately to obtain experience that provides a claim on adoption of subsequent generations. We propose that deferral and growth option value is dependent on the magnitude, frequency, and uncertainty of inter-generational change, and the nature of rivalry.

The purpose of this study is to propose Green Banking best practices for the adoption of this business construct based on the dimensions of environment, social and governance (ESG). This paper proposes a number of green practices under the ESG dimensions that can be adopted by individual banks at any stage of Green Banking adoption. It provides tactics for implementing this business construct that can serve as a tool for regulatory authorities forming Green Banking guidelines or policies for adoption. Such research has not been undertaken up until now.

The Green Banking adoption model is based on the concept of human ecology in which the inter-dependency and inter-connectivity of the variables impacting the phenomenon of environmental sustainability. These influencing variables are, in turn, connected with the natural environment. In the proposed model, the variables of ESG are inter-connected and impacting the natural environment as well. The proposed best practices have been derived from the Green Banking practices of the global industry leaders and Green Banking regulations of developed and developing countries. It can be beneficial to the stakeholders, as it proposes a step-by-step guide to Green Banking adoption that can be followed either sequentially or in parallel by the banks.

Green Banking adoption can be achieved by banks through implementing certain practices in either sequential or parallel manner. The adoption process depends on the various external and internal environmental dependencies. The Green Banking adoption practices can be broken down in three areas, i.e. ESG, allowing the construct optimal depth of coverage and complexity.

The literature on Green Banking is steadily increasing but a lack of research exists in the area of Green Banking adoption. Currently, limited literature exists that can provide the banking industry or the regulatory authorities with a framework or guideline to adopt Green Banking.

The purpose of this paper is to investigate factors influencing manufacturing flexibility adoption and simultaneously explores some of the key issues prevailing in manufacturing flexibility adoption in Indian context. The study also stratifies critical factors for successful manufacturing flexibility adoption.

Using exploratory sequential design, a series of focus group interviews were conducted with Indian manufacturing professionals and these interviews were supplemented by 127 follow-up structured questionnaires.

Two major themes emerged from the first phase of the study – role played by some of the unexplored antecedents of manufacturing flexibility and key issues in manufacturing flexibility adoption. In the second phase, a list of factors was categorized based on their degree of importance in manufacturing flexibility adoption.

Being qualitative in nature, the study suffers from inherent risk of subjectivity associated with manufacturing practitioners. A large-scale survey and rigorous quantitative analysis would be helpful to further validate the list of factors and underlying relationships among proposed factors.

The identified list of factors and some of the key issues in manufacturing flexibility adoption can be of great help to practitioners. The stratified list of factors can be further used by academicians to develop an instrument for manufacturing flexibility adoption.

The paper identifies a set of factors that affects manufacturing flexibility adoption. It offers a basis for instrument development for manufacturing flexibility adoption and provides direction for future quantitative research in manufacturing flexibility area.

The purpose of this paper is to explore how hubs’ social influence on social network decisions can cause the behavior of information cascades in a market.

The authors establish understanding of the fundamental mechanism of information cascades through a computational simulation approach.

Eigenvector centrality, betweenness centrality, and PageRank are statistically correlated with the occurrence of information cascades among agents; the hubs’ incorrect decisions in the early diffusion stage can significantly cause misled shift cascades; and the bridge role of hubs is more influential than their pivotal position role in the process of misled shift cascades.

This implication can be extendable in the field of marketing, sequential voting, and technology, or innovation adoption.

The purpose of this paper is to investigate internet adoption of very small B2B firms in Greece. This study aims to construct a model which will classify companies according to internet activities undertaken and then to explore whether different adoption can be interpreted by business demographics and a limited number of perceived barriers.

This empirical research was carried out by the means of survey focussing on the Greek jewellery industry. Data were submitted to a sequence of statistical analyses resulting to a model of Internet adoption. The model was then bench marked to representative domestic and international adoption patterns.

Firms can be classified into three groups, ranging from non-adopters to relatively mature adopters, similarly to previous patterns of international B2B small to medium enterprises. Business size and type, international cooperation and knowledge with regards to internet proved to be significantly correlated to adoption status.

The paper focusses on one Greek business sector and thus the applicability of its results to cross-type international micro-businesses remains questionable.

The findings of this study can assist company owners to plan their internet strategy, software vendors to target firms by offering tailored solutions and governmental authorities to implement initiatives aiming to confront the highlighted internet adoption disablers.

This is one of a few information and communication technology studies that focus on very small companies and perhaps the only one providing an empirical classification model of internet adoption for this business size.

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 two main objectives of this study are to systematically and formally test for differences in the impact of various determinants of e‐commerce adoption depending on the current level of e‐commerce, and to investigate the possible direct impact of the current level of adoption on the intention to further adopt.

A conceptual framework is developed from the literature. The model is tested using survey data from 98 small and medium‐sized enterprises in The Netherlands.

The results indicate significantly smaller effects of both knowledge and satisfaction for companies at the advanced level of e‐commerce compared with companies at the basic level. The current adoption level has a highly significant positive direct effect on adoption intention. These findings imply that at the higher levels of adoption the classical adoption determinants have less effect and other less explored factors are more important.

This study is one of the first empirical studies to deal with multiple levels of innovation adoption. It is concluded that, when innovations can be adopted at various levels, the determinants of innovation adoption vary between different levels of adoption. This finding deserves further attention from researchers, consultants and policy makers.

The purpose of this paper is to show how accelerated technology innovations lead to shorter product lifecycles, and consumers often face the dilemma of choosing between keeping the existing product and upgrading to a new version. They may enact certain coping strategies to deal with the stress and uncertainty. Based on the work of Mick and Fournier, this study aims to propose a set of coping strategies, which include refusal, delay, extended decision‐making, and pretest.

Based on a survey of consumers regarding the 3G mobile phones, the authors test the effects of coping strategies within the framework of the technology acceptance model.

The results of canonical analyses suggest that coping strategies have significant influence on consumers' product beliefs, which in turn mediate the effects of coping strategies on consumers' attitude toward adoption and their purchase intention.

Coping strategies help better understand consumers' adoption of new technology products and furnish meaningful implications for marketing technology products to today's tech‐savvy consumers.

This study develops measures of coping strategies and provides an empirical test of their effect on product beliefs and behavioral intentions with respect to consumers' decision whether to upgrade to a new technology product.