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This paper aims to explore whether internal context – decision-makers’ perception of characteristics of the information content – might predict the variation in adoption rates of different types of content, and whether innovation adoption theory might represent important factors of this decision-making process Corporate management decides what types of environmental information content to disclose/adopt.

Actual adoption rates of 13 information content categories are computed using content analysis of annual reports for 62 listed companies. Each content category is seen as an innovation the company decides to adopt or not. Interviews with management in several companies illustrate the decision process of disclosure, and help predict adoption rates. Predicted and actual adoption rates are compared.

Adoption rates vary considerably among the 13 types of content. The absolute level of adoption rates is affected by company size and environmental risk. However, those content categories that have either relatively high or low adoption rates are consistent among the subsamples, regardless of these corporate characteristics. This consistent variation in adoption rates seems to be predicted well by innovation adoption theory and its focus on the five attributes of the information itself: compatibility, trialability, complexity, observability and relative advantage.

The theoretical framework allows for different or changing internal and general contexts, and should be applicable to other settings, even though the particular predictions for adoption rates in this paper may not be applied as such.

The level of analysis is changed from company level, which dominates previous research, to information content (individual content categories). Perceived attributes of the information content itself and innovation adoption theory are used for the first time to explain reason for the reporting practice, and are considered fruitful tools to predict consistent variations in adoption rates among different types of content. This approach provides new insight into the driving forces of supply of disclosure.

This study aims to examine the experiences of Vietnamese enterprises with respect to the adoption and benefits of Western management accounting practices (MAPs) during a period when the economy was in transition toward a more market‐oriented system.

Questionnaire responses were obtained from the head or vice‐head of the accounting department in 181 enterprises, and follow‐up interviews conducted with 20 of the respondents. The responses were analysed with simple statistical tests and ANOVA.

Two of the key findings are in line with results reported previously for other countries: adoption rates for “traditional” Western MAPs are higher than for “contemporary” ones; and state‐owned enterprises tend to exhibit lower adoption rates than other enterprises. A third key finding represents new insight, but it may be applicable to only Vietnam (and possibly a limited number of other transition economies). This third finding arises from our identification of a group of Western MAPs which closely resemble the type of accounting and planning activities routinely undertaken under the former central planning (CP) system. These CP‐compatible MAPs are adopted far more widely (even at present) than are other MAPs. Overall, the findings are broadly consistent with the diffusion of innovation theory.

This study examines the Western MAP adoption experiences of a developing economy in transition, one which has received relatively little attention in the MA literature to date.

The Bass model is widely used in the literature to capture the diffusion of innovations and shows excellent predictive power in the context of durable goods. However, the model's efficacy fades when services are the target of analysis. Services that users adopt and subsequently utilize regularly are regarded as a continuous process that entails the possibility of dis-adoption and re-adoption. These aspects are not accounted for in the traditional Bass model. Thus, this study extends the Bass model to information system (IS)-based services by taking into account the unique nature of service adoption: the possibility of dis-adoption and re-adoption.

The proposed hypotheses were empirically tested using a longitudinal study of mobile service usage over 18 months. The longitudinal design provides a stronger position than the typical cross-sectional survey to understand the dynamics and infer causality.

Results show that the inclusion of the dis-adoption and re-adoption rates in the Bass model significantly improves the explanatory power over the traditional Bass model.

Consumption of services delivered through IS has exponentially increased. However, understanding on the diffusion pattern of IS-based services is limited. Our study is the first to examine the effect of dis-adoption and re-adoption together in the innovation diffusion process. The study offers significant implications for researchers and practitioners. The extended Bass model can help service firms develop an accurate prediction about the number of adopters at different periods of time.

This paper aims to examine the dynamism of causal relationships among cloud computing (CC) adoption factors in the Indian context, considering the perspectives of both the cloud adopter and cloud provider.

The case-study method has been used to understand the dynamics among the factors. Using data from specific cases in India, causal loop diagrams (CLDs) have been developed. System dynamic modeling (SDM) and simulation are used to study the relationships and their effect on the adoption rate.

The results revealed that adoption of CC depends on various factors such as persuasion (time-saving, cost-saving and word of mouth) and constraint factors (security and financial loss). However, it is seen that the adoption rate is very sensitive to changes in adoption per contact and word of mouth. Further, the adopter firm has a quicker time to market, which gives an added advantage to the firm. Also, with CC services, a firm can fulfill its projects or clients' requirements with little to no upfront investment in information technology (IT) services.

Lack of security, standardization and undefined service-level agreements are a few pressing issues that make it difficult for firms to evaluate the performance and reliability of services. Hence, immediate attention is needed to make transparent policies on CC and its services, thereby building trust.

This is the first and only work that has tried to explore and empirically test the dynamics of critical factors while making an adoption decision, considering both the adopter and provider perspectives. This study shows the journey of a firm, starting from being a prospective adopter to an adopter and continuous user. The work also empirically tested how adopters of technology benefit from the technology.

While there was heightened awareness on the technologies of the fourth industrial revolution (IR 4.0) prior to COVID-19, studies have shown that the adoption of these advanced technologies (e.g. Big Data, robotics, Internet of Things, etc.) continues to remain low across global industries. This qualitative study sought to explore the reasons for the low rate of adoption of these technologies and appropriate measures to enhance their adoption at hotels, through the lens of hotel executives.

Based on interpretivist's ideals, this study follows a case study design and adopts a qualitative method of enquiry. The heterogenous purposive sampling technique was employed to gather data for the study, using semi-structured interviews.

Grounded on the technology-organisation-environment (TOE) framework, the thematic analysis revealed technology, organisation and environment-related reasons for the low rate of IR 4.0 technologies adoption at hotels in Malaysia. Also, the study uncovered some interesting measures that will enhance the adoption of these advanced technologies at hotels.

This study unearths technology, organisation and environment-related reasons for low adoption, and measures to enhance the adoption of IR 4.0 technologies in hotels. This study also enlightens hotel owners and technology providers about practical issues that will ensure the successful adoption of such technologies to enhance hotel business. In line with SDG 9, this study also seeks to promote sustainable innovation in the hospitality industry. Practical and theoretical implications have also been discussed in this study.

This study examines how the Fortune 500 use transactional public Web sites (TPWS). It applies innovation diffusion theory to identify variables and construct a model to explain differences in adoption rates of TPWS across industries. The study finds high rates of TPWS adoption in the airline, computer and office equipment, commercial banking, and retailing industries. The study also explains why the rates of TPWS adoption vary across different industries. Characteristics of both the innovation and the industry’s environment affect TPWS adoption. A high level of TPWS adoption is associated with industries where: products, services, and sales processes “fit” electronic transactions, the level of price competition is extreme, competitors are aggressively adopting the same technology, and firms are experienced with related technologies and have already developed the necessary information technology infrastructure. The study is significant because it identifies the specific innovation and environmental characteristics that drive varying rates of TPWS adoption among large firms across different industries.

The digital divide has persisted in California and the USA as a whole at approximately the same level for the past decade. This is despite multiple programs being created and billions of dollars being spent to close it. This paper examines why the efforts to date have been ineffective and to offers policy alternatives that might be more successful.

Using data from three, variable constrained projects in California, this paper examines the effectiveness of information-based outreach efforts at closing the digital divide. The projects tested various outreach and enrollment methods to see which, if any, could increase broadband adoption in low-income households.

This project found that providing low-income households’ information about low-cost broadband offerings was ineffective at closing the digital divide. The findings in this paper were similar to those of two other works that examined the federal Broadband Technology Opportunities Program (BTOP) grants under the American Recovery and Reinvestment Act.

The findings of this paper along with the works cited that evaluated the BTOP program should be enough to change public policy. For the past ten years, efforts to close the digital divide have focused on providing information to low-income households. However, two independent surveys show broadband adoption has remained virtually flat during that period.

The digital divide brings concomitant economic and education harms and challenges that plague those unable to access information, services, educational and employment opportunities with the same ease, speed and sufficiency as their connected peers and neighbors. Those harms exacerbate the already existing education and income divides. This paper shows that without a change in strategy, those harms will persist.

This paper breaks new ground and addresses one of the weaknesses identified in existing research. To the best of author’s knowledge, this is the first paper of its type to use programs designed to generate data that can be empirically evaluated for effectiveness. Prior studies attempted to assess program effectiveness by using data generated from fully implemented government programs. However, those programs contained a vast number of unidentified variables and insufficient data collection. They were not designed to facilitate academic evaluation, and as such made a true effectiveness evaluation challenging.

This paper aims to develop a parsimonious and innovative model that captures the dynamics of new product diffusion in the recent high-technology markets and thus assist both academicians and practitioners who are eager to understand the diffusion phenomena. Accordingly, this study develops a novel diffusion model to forecast the demand by centering on the dynamic state of the product’s adoption rate. The proposed study also integrates the consumer’s psychological point of view on price change and goodwill of the innovation in the diffusion process.

In this study, a two-dimensional distribution function has been derived using Cobb–Douglas’s production function to combine the effect of price change and continuation time (goodwill) of the technology in the market. Focused on the realistic scenario of sales growth, the model also assimilates the time-to-time variation in the adoption rate (hazard rate) of the innovation owing to companies changing marketing and pricing strategies. The time-instance upon which the adoption rate alters is termed as change-point.

For validation purpose, the developed model is fitted on the actual sales and price data set of dynamic random access memory (DRAM) semiconductors, liquid crystal display (LCD) monitors and room air-conditioners using non-linear least squares estimation procedure. The results indicate that the proposed model has better forecasting efficiency than the conventional diffusion models.

The developed model is intrinsically restricted to a single generation diffusion process. However, technological innovations appear in generations. Therefore, this study also yields additional plausible directions for future analysis by extending the diffusion process in a multi-generational environment.

This study aims to assist marketing managers in determining the long-term performance of the technology innovation and examine the influence of fluctuating price on product demand. Besides, it also incorporates the dynamic tendency of adoption rate in modeling the diffusion process of technological innovations. This will support the managers in understanding the practical implications of different marketing and promotional strategies on the adoption rate.

This is the first attempt to study the value-based diffusion model that includes key interactions between goodwill of the innovation, price dynamics and change-point for anticipating the sales behavior of technological products.

This paper aims to investigate how awareness influences the adoption of positive selection (PS) technology among smallholder yam farmers in West Africa. PS has the potential of increasing yield and reducing disease incidence and severity in yam production.

This paper applies the average treatment effect (ATE) methodology to estimate the rates of awareness and adoption of the PS technology and associated factors using data from 678 smallholder seed yam farmers in Ghana and Nigeria.

The results indicate that the actual adoption rates of PS technology are 58 and 55%, while the potential adoption rates are estimated at 89.5 and 79.3% for Ghana and Nigeria, respectively, if the PS technology was fully disseminated. This leads to adoption gaps of 31.7 and 24.8%, respectively, for Ghana and Nigeria stemming from incomplete awareness of the PS among the population of yam growing farmers. The PS adoption is high among the educated young farmers who are members of farmer based organizations and participate in demonstrations.

Promotional efforts for enhancing awareness and adoption of PS should target educated youth willing to participate in field demonstrations and should focus on scaling up of PS technology to ensure quality farmer saved seed yams and enhance yam productivity in West Africa.

The introduction of PS in seed yam production is quite recent also its introduction to seed yam farmers in West Africa. Subsequently, a better understanding of what the adoption status would be should everyone in the population of yam farmers are aware of PS is vital for policy, research and development.