Technology adoption and jobs: The effects of self-service kiosks in restaurants on labor outcomes

This study explores how technology adoption affects labor. I investigate the effect of restaurants' adoption of self-service kiosks on labor outcomes, using survey data from Korea. I find that businesses’ adoption of self-service kiosks had little impact on their number of full-time or part-time workers. However, restaurants with a self-service kiosk decreased both the wages of their part-time workers and the number of unpaid family members they employed. The results are driven by franchise restaurants. Independently owned restaurants that adopted kiosks increased the wages of their full-time workers. These findings provide support for the efficiency wage theory as well as the skill-biased technological change theory. The results suggest that when businesses adopt new technologies, these technologies do not replace unskilled labor, but rather raise the relative wages of skilled workers.     

Technology assessment for clean energy technologies: The case of the Pacific Northwest

This study presents a technology assessment for clean power generation in the Pacific Northwest. Our goal is to incorporate clean production principles into the evaluation process for power alternatives. Two types of technologies are considered: one is for a renewable energy source (wind) and the other is for a traditional, fossil fuel based energy source (coal). The Analytical Hierarchy Process is used to assess the feasibility of both the wind energy and clean burning coal energy technologies. Criteria such as location, cost, feasibility, and availability are used for evaluations. For the wind energy, cost was determined to be the most important criterion when making a technology decision. For the SO₂ emissions technology, the regenerative process was determined to be the best technology to scrub SO₂ emissions from the air. Additionally, efforts towards renewable energy in Oregon should continue. Both federal and state governments offer tax credits that can help mitigate costs and facilitate the adoption of renewable energy options for power companies.     

Determinants of household use of energy-efficient and renewable energy technologies in rural Ethiopia

The poor households living in low-income countries depend on traditional sources for basic energy service; which has a broader socio-economic and environmental adverse effect. To mitigate the problem policy measures were used to increase access to energy-efficient and renewable energy technology. However, there are few studies on demand-side particularly on the drivers of household joint technology adoption behavior. Against this backdrop, this paper examined the determinants of household behavior concerning the adoption decision of energy-efficient and renewable energy technology using cross-sectional data collected from 195 households in central Ethiopia. For identification, the generalized ordered probit model which is a more flexible discrete choice model was applied. The findings reveal that the richer the households, the more likely that they adopt both improved cookstoves and renewable energy technology because of the greater financial capacity to afford to pay the upfront cost of the technologies. Household size and assets such as landholding size and the number of cattle owned positively associated with the use of both technologies. Likewise, a high level of education attained by the head of the household likely reduces the likelihood of adoption of neither technology but increases the likelihood of adoption of renewable energy. Participation in off-farm income-earning activities likely increases the propensity to invest in renewable energy. Similarly, household membership in local cooperatives found to increase the propensity to invest in renewable energy technology. While access to credit found to increase the adoption of energy-efficient technology. The finding of this study implies that poverty reduction and education policies increase the propensity to invest in energy-efficient and renewable energy technology. Likewise, better access to credit, off-farm employment opportunities, and cooperatives are also important.     

Exploring relative deprivation theory in the rice industry: Planting for Food and Jobs (PFJ) in northern Ghana

The determinants of adoption of technologies are mostly focused on socio-economic and demographic characteristics of farmers, overlooking the impact of corruption and preferential treatments (partisanship, nepotism and tribalism). We extend technology adoption predictors to include preferential treatment, and the results are explained with Relative Deprivation Theory. We used survey data collected from participants and nonparticipants of Planting for Food and Jobs (PFJ) programme in 2019. Respondents were rice farmers from three regions (Northern, Savannah and North-East regions) of Northern Ghana. We analysed the data using Systematic Probit Regression model after satisfying variables differential and correlation assumptions. The results revealed that while partisanship and tribalism are significant inverse factors, corruption is an insignificant negative determinant of participation in PFJ. We find nepotism to have a strong positive correlation with participation in PFJ. We recommend that government should plug all the loopholes facilitating corruption and preferential treatment if it intends to increase participation and rice productivity effectively.     

Comparing domestic water heating technologies

Solar water heaters (SWH) and drain water heat recovery (DWHR) systems are two household technologies currently available in the marketplace that can lower usage of utility-supplied energy. While there is considerable interest in utilizing these technologies to reduce energy costs and environmental impact, actual implementation of these systems in houses remains low. This study examines possible reasons for this low adoption rate using Guelph (Ontario) as a case study representative of medium-sized Canadian cities. A model was created to determine the implementation rate required for each technology to meet the goals of Guelph's Community Energy Plan and the level of financial incentive required to achieve the desired implementation rate. Water conservation and the need to address both new development and the existing housing stock emerge as critical factors. Solar water heating was found to require significantly higher subsidies than drain pipe heat recovery, corresponding to a higher cost per unit of energy saved. Non-economic factors that reduce the adoption rate of new technology are discussed, and it is observed that a need for community education related to the new technologies and inertia associated with current water heating technology are the primary factors for adoption rates below levels predicted based on economics alone.     

Technology adoption and the challenges of inclusive participation in economic activities: Evidence from small scale oil palm fruit processors in southwestern Nigeria

The lack of technology adoption has been mentioned as a source of lack of inclusive participation of low income groups in economic activities leading to income disparity in developing countries. The study utilized an input-process-output framework to develop a set of indicators to inform the development of policies and practices to ensure the participation of low income groups in economic activities. The input element consists of technology adoption influencing factors such as socio-economic characteristics and innovating units and institutions that provide support for innovation activities. The process and output elements consist of the level of technology adoption in production processes and productivity measures respectively. Focusing on small-scale oil palm fruit processors in Nigeria, the study revealed that inadequate funding of the input processes lead to inadequate technology adoption in specific unit operations of palm oil production. Utilising selected physicochemical properties of palm oil as indicators of productivity, the samples of palm oil assessed were found to be unsuitable for industrial use and may limit the processors from participating in formal sectors of palm oil production. The study recommends policy levers that will enhance input factors through adequate funding to improve the technological base of the small-scale oil palm fruit processing.     

What advantages of blockchain affect its adoption in the elderly care industry? A study based on the technology–organisation–environment framework

Blockchain technology is considered a logical solution to the problems of security, privacy and trust in the collection, storage and sharing of data related to the elderly in the elderly care industry (ECI); however, its adoption in the ECI remains in its initial stage. To improve the efficiency of adopting this technology in the ECI and to facilitate decision-making by managers, this study combines the diffusion of innovation theory and the technology–organisation–environment framework models to study the factors affecting blockchain adoption intention in the ECI. In addition, the direct predictors of the relative advantages of blockchain technology in the ECI are explored. Through a questionnaire survey of 124 elderly care institutions in China, we collected 181 valid questionnaires and analysed them using a partial least squares regression structural equation model. The results show that relative advantage, corporate social responsibility, top management support and organisational readiness have a positive effect on blockchain adoption intention in the ECI, while the effects of complexity, government support and competitive pressure are insignificant. However, competitive pressure and government support can indirectly promote blockchain adoption intention by influencing top management support. Furthermore, technology trust and information security positively affect the relative advantages of blockchain technology and indirectly affect blockchain adoption intention, while privacy protection is insignificant.     

Modelling and analysis of big data platform group adoption behaviour based on social network analysis

Due to the importance of big data technology in decision-making, production and service provision, enterprises have adopted various big data technologies and platforms to improve their operational efficiency. However, the number of enterprises that have adopted big data is not promising. The purpose of this study is to explore the current status of big data adoption by Chinese enterprises and to reveal the possible factors that hinder big data adoption from the group behaviour network perspective. Based on a real case survey of 54 big data platforms (BDPs), four types of networks—i.e., the enterprise-platform network, enterprise network, platform network and industry similarity and difference (ISD) network—are constructed and analysed on the basis of social network analysis (SNA). This study finds that among Chinese enterprises, the level and scope of big data adoption are generally low and are imbalanced among industries; the cognitive level and adoption behaviour of enterprises on BDPs are inconsistent, the compatibility of BDPs is different, and the density and distance-based cohesion of networks are weak; although the current big data adoption behaviours of Chinese enterprises have formed some structural features, core-periphery structures and maximal complete cliques are found, and the current network structure has little impact on individual enterprises and platforms; enterprises in the same industry prefer to adopt the same kind of big data technology or platform. Based on these findings, several strategies and suggestions to improve big data adoption are provided.     

Exploring adoption of augmented reality smart glasses: Applications in the medical industry

This study explores the use of augmented reality smart glasses (ARSGs) by physicians and their adoption of these products in the Turkish medical industry. Google Glass was used as a demonstrative example for the introduction of ARSGs. We proposed an exploratory model based on the technology acceptance model by Davis. Exogenous factors in the model were defined by performing semi-structured in-depth interviews, along with the use of an expert panel in addition to the technology adoption literature. The framework was tested by means of a field study, data was collected via an Internet survey, and path analysis was used. The results indicate that there were a number of factors to be considered in order to understand ARSG adoption by physicians. Usefulness was influenced by ease of use, compatibility, ease of reminding, and speech recognition, while ease of use was affected by ease of learning, ease of medical education, external influence, and privacy. Privacy was the only negative factor that reduced the perceived ease of use, and was found to indirectly create a negative attitude. Compatibility emerged as the most significant external factor for usefulness. Developers of ARSGs should pay attention to healthcare-specific requirements for improved utilization and more extensive adoption of ARSGs in healthcare settings. In particular, they should focus on how to increase the compatibility of ARSGs. Further research needs to be conducted to explain the adoption intention of physicians.     

Barriers to the adoption of new technologies in rural areas: The case of unmanned aerial vehicles for precision agriculture in India

Technological advances can significantly transform agrarian rural areas by increasing productivity and efficiency while reducing labour intensive processes. For instance, the usage of Unmanned Aerial Vehicles (UAVs) can offer flexibility collecting real-time information of the crops enabling farmers to take timely decisions. However, little is known about the barriers to the adoption of such technologies by rural farmers in emerging economies like India. Building on an extensive literature review, focussed group discussions, and field visits, the barriers impacting the adoption are identified and classified into technical, social, behavioural, operational, economic, and implementation categories. The relevance of each barrier and its importance is evaluated using a hybrid multi-criteria framework built on the theory of Fuzzy Delphi and Fuzzy Analytical Hierarchy Process to identify the most crucial barriers to the adoption of UAVs to implement precision agriculture in rural India. The paper suggests new avenues for accelerating technology adoption in rural areas of emerging economies.     

Generic and SME-specific factors that influence the BIM adoption process: An overview that highlights gaps in the literature

Building information modeling/management (BIM) is an emerging technological and procedural shift in the architecture, engineering, construction and operation industry. In this study, we use an extensive state-of-the-art method to clarify the BIM adoption process and the factors that can influence the success or failure of BIM adoption, particularly during the implementation stage, which are not frequently found in the literature. As an innovation, the lexical field allocated to the spread of innovations is assigned to BIM (diffusion, adoption, and implementation). After recalling the definition of relevant terms and then removing the resulting inconsistencies in vocabularies, we investigate various studies to identify factors that influence BIM adoption and then unify all these studies in one coherent and consistent BIM adoption process model. We focus on factors that play a role in the adoption of BIM in small- and medium-sized enterprises (SMEs) because SMEs constitute the majority of companies in the construction sector. This research highlights and intends to fill in some gaps found in the current BIM adoption literature.     

Artificial intelligence adoption in the physical sciences,natural sciences,life sciences,social sciences and the arts and humanities: A bibliometric analysis of research publications from 1960-2021

Analysing historical patterns of artificial intelligence (AI) adoption can inform decisions about AI capability uplift, but research to date has provided a limited view of AI adoption across different fields of research. In this study we examine worldwide adoption of AI technology within 333 fields of research during 1960–2021. We do this by using bibliometric analysis with 137 million peer-reviewed publications captured in The Lens database. We define AI using a list of 214 phrases developed by expert working groups at the Organisation for Economic Cooperation and Development (OECD). We found that 3.1 million of the 137 million peer-reviewed research publications during the entire period were AI-related, with a surge in AI adoption across practically all research fields (physical science, natural science, life science, social science and the arts and humanities) in recent years. The diffusion of AI beyond computer science was early, rapid and widespread. In 1960 14% of 333 research fields were related to AI (many in computer science), but this increased to cover over half of all research fields by 1972, over 80% by 1986 and over 98% in current times. We note AI has experienced boom-bust cycles historically; the AI “springs” and “winters”. We conclude that the context of the current surge appears different, and that interdisciplinary AI application is likely to be sustained.     

Improved rice variety adoption and farm production efficiency: Accounting for unobservable selection bias and technology gaps among smallholder farmers in Ghana

Ghana's agricultural sector is dominated by smallholder farmers who often face substantial challenges such as limited access to improved production inputs and technology, financial capital and extension services. These challenges jointly contribute to low agricultural productivity and hinder Ghana's ability to meet the rising demand for food caused by increasing population, urbanization, and changing dietary habits of consumers. Adoption of agricultural technologies and innovations has often been recognized as important pathways for ensuring smallholder farming systems transformation and improved agricultural productivity, food security, rural economic growth, and reduced poverty and vulnerability among smallholder farmers. This study examines the productivity and efficiency effects of improved rice technology adoption among 412 smallholder rice farmers in Northern Ghana. Using sample selection stochastic production frontier model, selection bias stemming from observable and unobservable farmer characteristics was accounted for because farmers self-select into adopting improved rice technologies. The results indicate that adopters are 24% more technically efficient than non-adopters. In addition, adoption of improved rice varieties is associated with about 76% increase in rice farmers’ productivity, relative to non-adoption. Moreover, IRVs adoption is positively and significantly influenced by access to irrigation, access to credit, and farmer group membership. Farm size, fertilizer, chemicals, irrigation, and soil quality are the main positive determinants of rice productivity for both adopters and non-adopters.     

Household Adoption of Technology: The Case of High-Speed Broadband Adoption in Australia

Within the home context a high-speed broadband Internet connection is seen as a key enabler for effective access to and use of the Internet. This article examines the factors contributing to household adoption of high speed broadband in Australia. Building on the Theory of Reasoned Action and seminal research on technology adoption in the home and the workplace, the article presents and evaluates a hypothesized model of Household Adoption of Technology.     

Adoption of unmanned aerial vehicles for pesticide application: Role of social network,resource endowment,and perceptions

Unmanned aerial vehicle technology is a promising alternative for sustainable agriculture production to more traditional technologies used in China. This paper considers factors affecting adoption of unmanned aerial vehicles for spraying pesticides among farmers in Jilin Province, China. Gender (male), percentage of income from agriculture, cultivated land area, within-family village leadership, number of borrowing channels, and positive attitudes towards the technology had a positive effect on adoption intention. Positive attitude toward traditional technology and higher income had a negative effect. Policy recommendations include continued work in improving access to rural financing, facilitating early adopters, and technology promotion.     

Technology convergence assessment: Case of blockchain within the IR 4.0 platform

Technological evolutions are leveraged by organizations to assess and formulate their strategic goals for achieving market dominance. Disruptive technologies have challenged organizations to address and transform their technological infrastructure and operational processes anew based on the market dynamics. Blockchain is considered as the disruptive technology of the decade, which has led incumbents to reassess their business models. Various applications of Blockchain have been explored by previous researchers. However, fourth industrial revolution (IR 4.0) technologies have also paved way towards the disruptive technological landscape. The purpose of this research is to identify the convergence across Blockchain and IR 4.0 technologies. This research conducts the bibliometric analysis approach, including performance analysis and network analysis to identify the research trends and themes for the convergence of select technologies. The results indicate four major thematic clusters for the convergence trends with basic, established, niche, and emerging technologies. Furthermore, the citation analysis reveals four clusters based on basic Blockchain technology domain, Blockchain and IR 4.0 technology domains, supply chain management (SCM), and healthcare applications of the convergence of select technologies. This article provides a novel approach by identifying the bibliometric trends across the concept of technological convergence of Blockchain and IR 4.0 technologies.     

Adoption readiness in service innovation: the case of digital money

One challenge for firms seeking to develop new services is to understand the conditions likely to affect the rates of adoption. Understanding relative degrees of ‘adoption readiness’ provides innovators with information to choose market segments and indicates opportunities to influence adoption environments. However, there is a little research into the adoption readiness of countries upon which firms can base their new service development decisions. This paper considers these issues through the case of digital money, a service innovation some claim to have the potential to provide major economic and social benefits. Defined as ‘currency exchange by electronic means’, we conceptualise digital money as a socio-technical system, and propose a Digital Money Readiness Index. This composite index integrates institutional, financial, technological, economic, industrial and social attributes to measure adoption readiness. We identify four stages of readiness and systematically analyse the factors that drive under or over adoption of digital money technologies.     

Collaborative adoption of blockchain technology: A supply chain contract perspective

The outbreak of COVID-19 has significantly affected the development of enterprises. In the post-pandemic era, blockchain technology has become one of the important technologies to help enterprises quickly gain market competitiveness. The heavy investment required of supply chain stakeholders to employ blockchain technology has hindered its adoption and application. To tackle this issue, this study aims to facilitate the adoption of blockchain technology in a supply chain consisting of a core enterprise and a small/medium-sized enterprise through an effective supply chain contract. We analyze the performance of a cost-sharing (CS) contract and a revenue-sharing (RS) contract and propose a new hybrid CS-RS contract for better performance. We conduct comparative analyses of the three contracts and find that the hybrid CS-RS contract can more effectively incentivize both parties to reach the highest level of blockchain technology adoption and achieve supply chain coordination.     

Adoption of the Multidivisional Structure: Analyzing History from the Start

The multidivisional structure represents one of the most studiedand important organizational innovations. Chandler's historicalaccount stresses the imitation effects of industry adoption,and of firm efficiency, as influenced by such characteristicsas size and diversification, on the diffusion of the divisionalstructure. Recent statistical work in the marketing literaturehas, however, found either no imitation or no firm characteristiceffects on adoption. Studies in organizational sociology havequestioned the role of efficiency in the adoption process. Bycollecting data from the time of the first adoption to 1980,the following study is able to analyze the critical early historyof diffusion. A hazard model with imitation and firm covariatesis used to predict the hazard rates. A sample of 62 firms issplit into fast and slow adopters, and an inverse Gaussian hazardmodel is estimated to compare the drift among the split samples.The results largely confirm Chandler's historical account, butwith some important qualifications that point to the importanceof the local nature of information within industries.     

Information technology diffusion in higher education

This project examines information technology (IT) planning, implementation, and diffusion in an academic environment, that of Portland Community College (PCC), the largest college in Oregon. PCC tries to keep pace with the latest technologies by anticipating and implementing new technology solutions in efficient and effective deployments. IT managers and employees at PCC were asked to complete a survey that included questions about IT planning, implementation, and diffusion. This paper proposes a conceptual framework based on previous models of technology adoption. The integrated, three-stage framework involves IT planning, actual IT implementation, and IT diffusion. The study identified adequate training and resistance to change as leading obstacles to IT deployment processes.