Early Stages Of Adoption Research Articles

Robotic adrenalectomy in the pediatric population: initial experience case series from a tertiary center

BackgroundLaparoscopic resection is the most well described minimally-invasive approach for adrenalectomy. While it allows for improved cosmesis, faster recovery and decreased length of hospital stay compared with the open approach, instrument articulation limitations can hamper surgical dexterity in pediatric patients. Use of robotic assistance can greatly enhance operative field visualization and instrument control, and is in the early stages of adoption in academic centers for pediatric populations.Case presentationWe present a single-institution series of pediatric adrenalectomy cases. The da Vinci Xi surgical system was used to perform adrenalectomies on three consecutive patients (ages, 2–13 years) at our center. Final pathology revealed ganglioneuroblastoma (n = 2) and pheochromocytoma (n = 1). Median operating time was 244 min (range, 244–265 min); median blood loss was estimated at 100 ml (range, 15–175 ml). Specimens were delivered intact and all margins were negative. Median post-operative hospital stay was 2 days (range, 1–6 days). All patients remain disease-free at median follow-up of 19 months (range, 12–30 months).ConclusionOur experience continues to evolve, and suggests that robotic surgery is safe, feasible and oncologically effective for resection of adrenal masses in well-selected pediatric patients.

Understanding the influence of environmental production practices on firm performance: a proactive versus reactive approach

PurposeExploring ways to sustain competitive positions as well as improve firm performance through environmental production initiatives has been a major preoccupying topic for mostly practitioners and researchers. Despite several studies on the influence of environmental initiatives on firm performance, many questions remain unanswered as to how to further extract more gains from environmental production initiatives. This study, thus, explores environmental production practices impact on firm performance from proactive and reactive perspectives.Design/methodology/approachThe study adopted a survey research design, a quantitative approach and partial least square structural equation modelling (PLS-SEM) technique in making data analysis and interpretations due to its suitability for predictive research models.FindingsThe results indicated that proactive environmental production practices positively related with process and environmental performances but negatively associated with financial performance. Although the findings contrast with majority of past findings, they gain the support of other scholars in establishing that early adoption stages of proactive environmental production initiatives strain financial capabilities and thus present a negative relationship. Reactive environmental production practices are positively and significantly related with process, environmental and financial performances.Originality/valueThe study is among the first to expose environmental production practices from a proactive and a reactive perspective and in the context of a developing country. As such, the study provides guidance to relevant authorities in further promoting sustainable production practices to preserve the environment by manufacturing safer consumer products through efficient sustainable production processes and practices.

Shaping the digital transformation of the retail banking industry. Empirical evidence from Italy

Although numerous studies have investigated the determinants of users’ acceptance of online channels, little attention has been paid to the continuous usage of a direct bank. To address this research gap, we analysed data collected via semi-structured interviews and a survey questionnaire distributed in 2017 to a sample of Italian bank customers. Responses were evaluated using a different statistical methodology based on the Shapley Value regression analysis. In brief, user-friendliness and economic advantages appear to be more decisive at an early stage of adoption. Moreover, structural assurance mechanisms (e.g. clarifying security policies and guarantees) have a robust impact on keeping customers online and loyal to electronic channels. Surprisingly, accessibility and compatibility do not seem to be determinant factors.

Challenges and Barriers of Building Information Modeling Adoption in the Saudi Arabian Construction Industry

Background: The Building Information Modeling (BIM) revolution can provide a solution for problems in the Saudi Arabian construction industry and improve its outcomes. Though this technology is increasingly and rapidly adopted in advanced countries, developing countries such as Saudi Arabia and the Gulf Cooperation Council countries (GCC) are still in the early stages of BIM adoption. Objective: This study investigates the current state of BIM technology adoption by exploring and analyzing the critical challenges and barriers to BIM technology utilization in the construction sectors. Methods: The quantitative approach is adopted via a survey questionnaire distributed to participants in the field of construction projects in the Architecture, Engineering, and Construction (AEC) industry. A total of 228 questionnaires are collected and analyzed using the statistical packaging for social science software. Results: Findings show that several significant barriers negatively affect the utilization of BIM. The major barriers to BIM adoption are related to the lack of demand, lack of experts, and poor awareness of BIM benefits, which have relative importance indexes of (RII = 89.910), (RII = 88.475), and (RII = 87.130), respectively. Meanwhile, unspecified data responsibilities, difficulty of learning BIM, lack of data sharing, and sufficient current technology constitute the lowest-ranking barriers with their relative importance indexes of (RII = 71.704), (RII = 70.807), (RII = 66.413), and (RII = 65.874), respectively. Conclusion: The findings of this study are highly significant and can become more helpful and interesting if further research can measure the methodologies to implement BIM technology in the Kingdom of Saudi Arabia.

Factors Influencing the Intention to Continue using B2B e-Commerce in Manufacturing SMEs

Business-to-Business (B2B) electronic commerce plays a tremendous role in nurturing the growth of Small and Medium Enterprises (SMEs) in developed and developing countries. However, the growth of B2B e-commerce in developing nations remains at the early adoption stage. The purpose of this paper is to examine the factors that influence B2B e-commerce adoption in SMEs in a developing country. The current study employs the questionnaire survey technique to gather information from 245 manufacturing SMEs in Jordan. It uses Structural Equation Modeling (SEM) to investigate the different factors that affect the intention to adopt or continue using B2B e-commerce. The study reveals that compatibility and outsourcing IT support have significant effects on the intention to continue using B2B e-commerce in Jordanian manufacturing SMEs. The implications of the findings are discussed.

Abstract WP437: Where Are We Located Now With Artificial Neural Network? Application of Deep Learning for the Development of Culturally Sensitive Social Support Interventions for Dementia Caregivers

Introduction: Little is known about culturally sensitive interventions for Hispanic and African American family caregivers for persons living with vascular dementia. Applications of deep-learning neural networks have expanded rapidly in recent years, from the first uses in character recognition (1989) to the high-profile AlphaGo (2016) from Google DeepMind. The purpose of this study is to visualize topics from health literature that use deep learning, exploring the techniques’ ability to provide a foundation for developing culturally sensitive Twitter-based social support interventions for Hispanic and African American dementia caregivers. Methods: The corpus of deep learning literature was extracted from 506 studies mentioning deep learning from PubMed library. Text mining was conducted using AutoMap to identify topics and semantic relations from the corpus. Results were visualized as network clusters of frequently applied topics and isolated topics. Results: Literature applying deep learning are limited to 1) imaging and radiology, 2) genomics, 3) cancer (N=506 studies). Topics on dementia and drug discovery were identified as an emerging area for the adaptation of deep learning techniques (Figure 1). Only seven journals in the PubMed library were identified as having published more than 10 studies applying deep learning methods. Conclusion: Despite its popularity in art and science research, deep learning is at an early stage of adoption in health science, largely focused on limited topics, e.g., imaging and disease diagnosis. Applying deep learning methods may provide insights for developing culturally sensitive Twitter-based interventions for Hispanic and African American dementia caregivers. Implementing education on applying deep learning to imaging and vascular-dementia prediction may be a good start to adapt, deepen and broaden the scope of health analytics to improve vascular dementia patients’ health outcomes.

Some pedagogical observations on using augmented reality in a vocational practicum

AbstractThe use of augmented reality (AR) in vocational education and training can still be considered as being in its infancy, although interest in it is growing in response both to its potential for teaching and its adoption as a practical tool in various industry sectors. One example of early‐stage AR use is illustrated from a practicum for training apprentices in the chemical industry; this involves the use of various AR objects for learning a simple production operation. Although this application had been conceived of purely in terms of substitution for existing instructional methods, it also gave learners greater control of the learning process and created opportunities for collaborative learning. Pedagogically, AR can be considered as a mildly disruptive technology that favours learner managed learning, a factor that is aligned with its ability to support localised decision‐making in industry. Practitioner NotesWhat is already known about this topic Augmented reality (AR) tends to favour exploratory, learner managed and increasingly, collaborative learning. Evaluations of AR for vocational learning are on balance positive, with improved understanding, fewer errors and faster task completion or improved learning performance all reported. AR is still in the early stages of adoption in vocational education and training (VET), with trials and small‐scale applications dominating. What this paper adds Introducing AR even for simple learning tasks affects the pedagogical approaches that are used. Effects include greater learner control of the learning process and encouragement of reflection‐in‐action. Implications for practice and/or policy AR is a mildly disruptive technology that needs to be considered in terms of its pedagogical implications as well as its effectiveness as a learning tool. The directions favoured by AR in education and training appear consistent with changing skill and learning demands in industry.

WITHDRAWN

The document associated with this DOI has been withdrawn.

E-Procurement Practices to improve the efficiency of Vendor Transactions in Indian Cement companies

E-procurement ensures an end-to-end integrated purchase of materials right from indent management until final payment through internet which results into cost efficiency in a supply chain management. While the e-procurement has been successfully practiced in global markets, it is in the early stage of adoption among cement companies in India. The main objective of this study is to explore the factors influencing e-procurement of materials in the cement industry. The other objective is to measure the impact of e-procurement practices on materials purchase in the value chain of the said industry. Initially, the study conducted a Delphi interview with selected managers. Based on the information from interview, a structured questionnaire was framed and the same was used to collect information from 126 employees of five cement companies. Besides descriptive analysis, the factor analysis was applied to identify the significant factors in e-procurement. A confirmatory factor analysis was carried out to verify the factor structure of the set of observed variables. The study identified the significant factors that contribute to e-procurement practices in India. Interestingly, it was also found that the employees are comfortable to use e-procurement but require adequate training and better e-infrastructure.

E-procurement practices to improve the efficiency of vendor transactions in Indian cement companies

E-procurement ensures an end-to-end integrated purchase of materials right from indent management until final payment through internet which results into cost efficiency in a supply chain management. While the e-procurement has been successfully practiced in global markets, it is in the early stage of adoption among cement companies in India. The main objective of this study is to explore the factors influencing e-procurement of materials in the cement industry. The other objective is to measure the impact of e-procurement practices on materials purchase in the value chain of the said industry. Initially, the study conducted a Delphi interview with selected managers. Based on the information from interview, a structured questionnaire was framed and the same was used to collect information from 126 employees of five cement companies. Besides descriptive analysis, the factor analysis was applied to identify the significant factors in e-procurement. A confirmatory factor analysis was carried out to verify the factor structure of the set of observed variables. The study identified the significant factors that contribute to e-procurement practices in India. Interestingly, it was also found that the employees are comfortable to use e-procurement but require adequate training and better e-infrastructure.

The kindergarten Early Development Instrument predicts third grade academic proficiency

School readiness skills predict later educational achievement, health, and social-emotional outcomes. Measures of school readiness can provide valuable information to assess both the impact of strategies and policies that prepare children for school as well as informing strategies for improving children’s educational trajectories across their school years. The Early Development Instrument (EDI) is a measure of school readiness skills based on teacher-reported observational recall. It has been used extensively in Canada and Australia and is in the early stages of adoption in a number of U.S. cities. The current study uses data from roughly 3000 children followed longitudinally from kindergarten through third grade from 7 school districts in Orange County, California. The study assesses whether EDI ratings in kindergarten predict third grade proficiency in mathematics and English Language Arts on state assessments. Ratings on the EDI were strongly associated with proficiency in both academic areas, even in the presence of controls for child-level factors and neighborhood fixed effects. Among its components, ratings on the language and cognitive development, communication skills and general knowledge, and social competence domains strongly differentiated children’s likelihood of later proficiency in both academic areas. Implications for improving comprehensive early childhood education and schooling policies based on indicators of school readiness are discussed.

Analysis of Barriers and Drivers for BIM Adoption

Research on 'digitalization and collaboration' in the construction industry has been gaining momentum in the recent academic engagements. Despite its existence in many industries (i.e. financial services, retailing, publishing and travelling) for over ten years, it is yet to catch up by the construction market; this is due to several challenges whose existence are more dynamic and contextual than generic to various countries. The problems are defined in many studies across borders, but their impacts varied with countries. This case is equally the same to drivers toward the adoption of BIM. This study analyses barriers and drivers to BIM adoption in the Nigerian construction industry from adopters and non-adopters perspectives as to allow an informed decision in developing a strategy for macro BIM adoption. Primary data fetched from professional stakeholders through an online questionnaire survey were analysed using SPSS software and Microsoft Excel. This investigation reveals the most significant barriers against BIM adoption as Lack of expertise, Lack of standardization and protocols to mention but a few. And, most influential drivers from both adopters and non-adopters as Availability of trained professionals to handle the tools, Proof of cost savings by its adoption, BIM Software affordability, and awareness of the technology among the industry stakeholders. The adopters and non-adopters groups have nearly equal Percentage Disagreement (PD) and Percentage Agreement (PA) for both the barriers and drivers to BIM adoption. Thus, this suggests that the adopters are still at the early stage of BIM adoption, so have nearly the same perceptions with the non-adopters. The study recommends proper consideration of the established barriers and drivers while developing any strategy for effective BIM adoption. Further face-to-face (interview) study is necessary to explore more and in-depth challenges to adoption of BIM in the industry; and as the industry is getting more aware of the BIM, periodic evaluation of the critical barriers and drivers is vital.

Open innovation in the public sector: creating public value through civic hackathons

ABSTRACT This article examines the outcomes of open innovation (OI) and their contribution to public value by analysing 19 subnational civic hackathons across the US. Our analysis identifies three outcomes (digital prototypes, public engagement and relationship building, and government awareness of open data and OI) and lends support to the predominance of public engagement and relationship building over digital prototypes. Further, our study shows that OI initiatives may contribute to public value by enhancing substantive outcomes, democratic accountability, and procedural legitimacy. However, such contribution is constrained by the early stage of adoption of these initiatives and by the limited participation of external actors.

On-Demand Telemedicine as a Disruptive Health Technology: Qualitative Study Exploring Emerging Business Models and Strategies Among Early Adopter Organizations in the United States.

BackgroundOn-demand telemedicine is increasingly adopted by health organizations to meet patient demand for convenient, accessible, and affordable services. Little guidance is currently available to new entrant organizations as they consider viable business models and strategies to harness the disruptive potential of on-demand telemedicine services (in particular, virtual urgent care clinics [VCCs] as a predominant and catalyst form of on-demand telemedicine).ObjectiveWe recognized on-demand telemedicine as a disruptive technology to explore the experiences of early adopter organizations as they launch on-demand telemedicine services and deploy business models and strategies. Focusing on VCC service lines, this study addressed the following research questions: (1) what is the emerging business model being deployed for on-demand telemedicine?; (2) what are the core components of the emerging business model for on-demand telemedicine?; and (3) what are the disruptive business strategies employed by early adopter organizations as they launch on-demand telemedicine services?MethodsThis qualitative study gathered data from 32 semistructured phone interviews with key informants from 19 VCC early adopter organizations across the United States. Interview protocols were developed based on noted dissemination and implementation science frameworks. We used the constant comparison method to transform study data into stable dimensions that revealed emerging business models, core business model components (value proposition, key resources, key processes, and profit formula), and accompanying business strategies.ResultsEarly adopters are deploying business models that most closely align with a value-adding process model archetype. By and large, we found that this general model appropriately matches resources, processes, and profit formulas to support the disruptive potential of on-demand telemedicine. In total, 4 business strategy areas were discovered to particularly contribute to business model success for on-demand disruption among early adopters: fundamental disruptions to the model of care delivery; outsourcing support for on-demand services; disruptive market strategies to target potential users; and new and unexpected organizational partnerships to increase return on investment.ConclusionsOn-demand telemedicine is a potentially disruptive innovation currently in the early adopter stage of technology adoption and diffusion. On-demand telemedicine must cross into the early majority stage to truly be a positive disruption that will increase accessibility and affordability for health care consumers. Our findings provide guidance for adopter organizations as they seek to deploy viable business models and successful strategies to smooth the transition to early majority status. We present important insights for both early adopters and potential early majority organizations to better harness the disruptive potential of on-demand telemedicine.

The impact of BIM application on construction delays and cost overrun in developing countries

Delays and cost overruns are generally acknowledged in the construction industry as serious issues that require the use of advanced technologies. However, the adoption of new technologies has not kept pace with the growth of the industry. This is due to low studies on the impact of these technologies in the industry. Building Information Modelling (BIM) as an alternative technology for management of construction is still in its early stage of adoption in many countries. This research tends to determine the relationship between the use of BIM and the causes of delay and cost overrun in construction industry. Data were obtained through admininstered questionnaires to Contractors, which was analysed using Pearson’s product-moment correlation to determine their relationships at 0.05 level of significance. The results from the analysis of the causes of delay and the causes of cost overrun shows that there is a positive correlation between the two (r=0.737, n = 69, p = 0.000). More also, the result of the analysis shows that there is a significant negative relationship between the application of BIM and the causes of delay and cost overrun (r = -0.246, n = 69, p = 0.041) and (r = -0.313, n = 69, p = 0.009). The result of this research shows that an increase in the use of BIM in the management of construction projects reduces the occurrence of delay and cost overrun.

The role of adoption norms and perceived product attributes in the adoption of Dutch electric vehicles and smart energy systems

We studied to what extent perceived adoption norms affect the likelihood of adopting sustainable innovations, next to evaluations of the instrumental, environmental and symbolic attributes of these innovations. As hypothesised, results showed that people are more likely to adopt a sustainable innovation the more they evaluate the attributes of these sustainable innovations favourably and the more they think significant others would consider adoption (i.e., when adoption norms are strong). Moreover, we hypothesised and found that positive evaluations of the symbolic attributes are more likely to promote the adoption of sustainable innovations when people expect that few significant others would consider adoption. These findings suggest that weak adoption norms that are typical in the early adoption stage may both inhibit and promote adoption of sustainable innovations, via different routes.

Environmental Attributes of Person-Centered Care

The purpose of this study was to document the existing environmental, organizational, and operational patterns of PEAK 2.0 participating homes at early stages of adoption and the patterns of sustained adopters to determine whether there were notable or distinguishing features that were different between these two groups. Using a case-study approach, a qualitative mixed-methods research design was employed. The patterns of staffing structures and patterns of spatial layout are used to understand the environmental affordances provided to residents and staff of these settings. The theory of environmental affordances has been applied here as a perceptual framework for understanding how person-centered care (PCC) behaviors can be enacted within a space. Environmental assessments revealed that advanced adopters had patterns of building use that were notably different from those of early adopters. Advanced adopters designated more staff to a single area; early adopters expected staff to cover multiple areas on each shift. Additionally, advanced adopters created more environmental affordances for residents and staff through the types of space allocations and features present. Results demonstrated that if considered holistically and strategically, impactful changes to institutionally shaped buildings can be made to accomplish and sustain PCC goals.

Emissions of N2O and CO2 Following Short-Term Water and N Fertilization Events in Wheat-Based Cropping Systems

Greenhouse gas (GHG) emissions result from short-term perturbations of agricultural systems such as precipitation and fertilization events. We hypothesized those agricultural systems with contrasting management histories may respond differently to application events of water and N fertilizer with respect to GHG emissions. Studies with long-term management histories consisting of no-tillage (NT) and conventional tillage (CT) were coupled with high temporal resolution, automated chambers that monitored N2O and CO2 emissions for 22 hours following treatments. Treatments applied to NT and CT were a) control (no water or N additions), b) simulated precipitation to achieve approximately 80% water-filled pore space, and c) precipitation plus fertilizer additions of 150 kg N ha-1as ammonium nitrate. Emissions of CO2 increased with increase in moisture and temperature and decreased under fertilizer application. Water and nitrogen treatments in CT at the sites with 2 and 12-year history produced N2O fluxes greater than NT by 142% and 68%, respectively. The site with 10-year history of NT produced similar amounts of N2O from CT and NT treatments. The same treatments at the site with 31 yearlong no-till history, despite being one of the lowest among all sites, demonstrated 380% higher N2O fluxes from the NT than CT, which was likely due to higher levels of labile organic matter present in NT treatments. GHG emissions data regressed on measured soil C and N properties, fractionation, and mineralization data showed that N2O flux increased with reduction of acid-hydrolyzable N and increase of NH4-N in soil, which suggested that N2O production in the short-term water and water and N additions events is mostly produced via nitrification process. This indicates that neither the length of no-till treatment nor the fertilizer application rate define the rate of N2O emissions, but the soil N availability controlled by organic matter mineralization rate. The current study shows that the early stages of no-till adoption can result in reduction of N2O spikes during short-term precipitation events similar to some long-term no-till sites.

Framework for Big Data integration in e-government

This article describes researches regarding Big Data integration in e‑government decision‑making, for instance, in areas like solar energy provisioning, environmental protection, agricultural and natural resources exploitation, health and social care, education, housing and transportation management, among others. These studies refer to regions that have integrated Big Data in e‑government, where South America is still in the early adoption stages. Hence, this study proposes three steppingstones for Big Data integration in e‑government decision‑making, production, management and application. The proposed framework aims to be a reference in South America for Big Data adoption in e‑government and thus help to mitigate the technology delay regarding other regions. Finally, a case study with open data obtained from the Instituto Nacional de Estadística y Censos of Ecuador (Ecuadorian Statistics and Census Agency) is presented.

BIG DATA ADOPTION IN SELECTED COMPANIES OF THE RETAIL SECTOR IN THE REPUBLIC OF MACEDONIA

In a highly digitalized world, big data and analytics are among major trends companies worldwide are facing. As companies generate data across different sources (information systems), which is increasing rapidly in volume, variety and velocity, big data analytics becomes essential. Big data is a term that describes the large volume of data (both structured and unstructured), that overwhelms a business on a day-to-day basis. But the importance of big data doesn’t revolve around how much data one organization has, but what organizations do with the data that matters. Big data and analytics, provide organizations with the opportunity to analyze data generated from any source and to find answers that enable cost reductions, time reductions, new product development and optimized offerings, and smart decision making.Big data is affecting companies from different size and in almost every industry, and has the potential not only to transform the business world, but the society as well at large extent. Emerging literature and the empirical evidence suggest that companies from the retail sector can gain competitive advantage from data if they adopt big data analytics technologies. In spite of that, companies in the country are still in the early stages of adoption of big data analytics technologies. Hence, the goal of this paper is to determine factors affecting the big data analytics adoption in selected companies in the Republic of Macedonia from the retail sector. This is a pilot study and as such represents the first attempt to assess the level of big data analytics adoption in the country. This small scale preliminary study will provide evaluation of the feasibility of the key steps of the proposed research model (methodology) in order to conduct future research in larger extent and sample.There have been several theoretical models that explain technology acceptance. The research model in this study is based on Technology-Organization-Environment (TOE) framework (Tornatzky & Fleischer, 1990). The TOE framework explains that adoption of technological innovations is influenced by a range of factors in the context of the technology, organization and external environment. The framework explains that these three factors stimulate and influence the technology innovation adoption-decision in companies. It is considered as multi-perspective framework and an integrative model that is developed for studying factors affecting adoption of innovative technologies and has been used to assess organizations’ adoption of big data analytics technologies mostly in telecommunications, e- commerce and other.The proposed research model specifies the following technological characteristics (technical capacity, relative advantage and complexity), intra-organizational factors (top management support, organizational culture, organizational size and IT expertise/ technological competence), and inter-organizational factors (competitive pressure, external support, and regulatory /government policy as well as data security and privacy) as determinants of big data analytics adoption. The preliminary results of this pilot study support the research model and the methodology. The significance of the proposed determinants/factors can help managers formulate their analytics strategies and increase the use of big data technology in order to fulfil organizational goals and achieve better organizational performance.