Conceptual Model of Big Data Technologies Adoption in Smart Cities of the European Union

Big data technologies enable cities to develop towards a smart city. However, the adoption of big data technologies is challenging, which is why it is essential to identify factors that influence the adoption of big data technologies in cities. The main goal of the paper is to propose a conceptual model of big data technologies adoption in smart cities of the European Union. In order to derive the conceptual model following is done: i) overview of the previous Technology-OrganisationEnvironment framework - based research on the adoption of selected information and communications technologies crucial for the development of smart cities, and ii) selection of factors based on the critical examination of the previous research. Selected factors, Absorptive Capacity, Technology Readiness, Compatibility, City Managements Support, the Existence of Smart City Strategy and Stakeholders Support, were incorporated into the conceptual model of big data technologies adoption in smart cities of the European Union. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.</p

an empirical study

Martins, R., Oliveira, T., Thomas, M., & Tomás, S. (2019). Firms’ continuance intention on SaaS use: an empirical study. Information Technology and People, 32(1), 189-216. https://doi.org/10.1108/ITP-01-2018-0027Purpose: Although studies have investigated reasons for software as a service (SaaS) adoption, it is unclear how firm-level SaaS use impacts future SaaS intentions. The purpose of this paper is to propose a theoretical model that integrates the technology-organization-environment framework, institutional theory, diffusion-of-innovation theory and the opportunity-risk framework to analyze the drivers of SaaS use and its continuance intention. Design/methodology/approach: The authors evaluated the direct, moderating and mediating effects of determinants on SaaS continuance intentions using structural equation modeling and data from 301 firms. Findings: Results found that top management support and normative pressures influenced SaaS use. Cost saving and security concerns were direct predictors of perceived opportunities and perceived risks, respectively. Perceived opportunities and risks and actual SaaS use influenced SaaS continuance. Interestingly, perceived opportunities were found to be a negative moderator on the relationship between SaaS use and SaaS continuance. Originality/value: The results reveal insightful and controversial findings for SaaS research.authorsversionpublishe

Adoption of AI-empowered industrial robots in auto component manufacturing companies

The usage of AI-empowered Industrial Robots (InRos) is booming in the Auto Component Manufacturing Companies (ACMCs) across the globe. Based on a model leveraging the Technology, Organisation, and Environment (TOE) framework, this work examines the adoption of InRos in ACMCs in the context of an emerging economy. This research scrutinises the adoption intention and potential use of InRos in ACMCs through a survey of 460 senior managers and owners of ACMCs in India. The findings indicate that perceived compatibility, external pressure, perceived benefits and support from vendors are critical predictors of InRos adoption intention. Interestingly, the study also reveals that IT infrastructure and government support do not influence InRos adoption intention. Furthermore, the analysis suggests that perceived cost issues negatively moderate the relationship between the adoption intention and potential use of InRos in ACMCs. This study offers a theoretical contribution as it deploys the traditional TOE framework and discovers counter-intuitively that IT resources are not a major driver of technology adoption: as such, it suggests that a more comprehensive framework than the traditional RBV should be adopted. The work provides managerial recommendations for managers, shedding light on the antecedents of adoption intention and potential use of InRos at ACMCs in a country where the adoption of InRos is in a nascent stage

perspectives from Mozambican institutions

Amade, N., Oliveira, T., & Painho, M. (2020). Understanding the determinants of GIT post-adoption: perspectives from Mozambican institutions. Heliyon, 6(5), [e03879]. https://doi.org/10.1016/j.heliyon.2020.e03879This study aims to understand the determinants of geographical information technologies at the scale of post-adoption use and intention to increase the level of use in Mozambican institutions. Three known theories (diffusion of innovation theory, technology – organisation – environment framework, and institutional theory) have been used in order to accomplish the study. The data analysis showed that the variables compatibility, geographical scope, expansion opportunities, and normative pressure contribute to explaining GIT use. Relative advantage, complexity, coercive pressure, and mimetic pressure contribute to explaining the intention to increase GIT levels of use. The model revealed substantial power of explanation for GIT post-adoption.publishersversionpublishe

Usvajanje tehnologija velikih podataka u pametnim gradovima Europske Unije: Analiza važnosti i performansi tehnoloških čimbenika

Gradovi Europske Unije na svom razvoju prema pametnom gradu usvajaju tehnologije velikih podataka. S obzirom na to da su tehnologije velikih podataka složene i disruptivne tehnologije, potrebno je utvrditi važnost čimbenika i njihovih aspekata za usvajanje tehnologija velikih podataka u gradovima. Cilj rada je identificirati najvažnije aspekte tehnoloških čimbenika usvajanja tehnologija velikih podataka u gradovima Europske Unije. Kako bi se ostvario cilj rada provedeno je istraživanje na uzorku gradova Europske Unije, a na prikupljenim podacima provedena je analiza mape važnosti i performansi čimbenika usvajanja tehnologija velikih podataka. Rezultati istraživanja pokazuju da su aspekti apsorpcijskog kapaciteta i tehnološke spremnosti gradova EU relativno visoke važnosti, no uz niske razine performansi u odnosu na čimbenike organizacije i okoline. Doprinos rada sastoji se od općih smjernica za povećanje razine tehnološke spremnosti i apsorpcijskog kapaciteta gradova kako bi se povećala uspješnost usvajanja tehnologija velikih podataka u gradovima Europske Unije

Usvajanje tehnologija velikih podataka u pametnim gradovima Europske Unije: Analiza važnosti i performansi tehnoloških čimbenika

Gradovi Europske Unije na svom razvoju prema pametnom gradu usvajaju tehnologije velikih podataka. S obzirom na to da su tehnologije velikih podataka složene i disruptivne tehnologije, potrebno je utvrditi važnost čimbenika i njihovih aspekata za usvajanje tehnologija velikih podataka u gradovima. Cilj rada je identificirati najvažnije aspekte tehnoloških čimbenika usvajanja tehnologija velikih podataka u gradovima Europske Unije. Kako bi se ostvario cilj rada provedeno je istraživanje na uzorku gradova Europske Unije, a na prikupljenim podacima provedena je analiza mape važnosti i performansi čimbenika usvajanja tehnologija velikih podataka. Rezultati istraživanja pokazuju da su aspekti apsorpcijskog kapaciteta i tehnološke spremnosti gradova EU relativno visoke važnosti, no uz niske razine performansi u odnosu na čimbenike organizacije i okoline. Doprinos rada sastoji se od općih smjernica za povećanje razine tehnološke spremnosti i apsorpcijskog kapaciteta gradova kako bi se povećala uspješnost usvajanja tehnologija velikih podataka u gradovima Europske Unije

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

A new perspective to evaluate the antecedent path of adoption of digital technologies in major projects of construction industry: A case study in China

The adoption of digital technologies is key to the digital transformation of the construction industry. However, the current adoption of digital technologies is limited. This study uses China as a case, combines the DOI and TOE theories to identify impact factors of the adoption of digital technologies in major projects. The configuration analysis is complemented with fuzzy-set qualitative comparative analysis. As a result, the study constructs the “TOE-D Technology Adoption Antecedent Framework”, including 11 antecedents, and identifies three distinct configurations types, namely: “Needs-Resource-Collaboration”; “Resource” under high competitive pressure; and “Resource” under low competitive pressure. Comparing the configurations horizontally, the core or edge characteristics of factor in configurations are analyzed. The results can help major projects in the construction industry to ascertain a combination of elements, which promote the adoption of digital technologies so that project practitioners can make targeted and precise adjustments to enable digital transformation of the construction industry

A CRITICAL REVIEW OF CHANGE MANAGEMENT AND TECHNOLOGY ADOPTION FACTORS TO DRIVE ORGANISATIONAL PERFORMANCE: A STUDY OF THE ABU DHABI NATIONAL OIL COMPANY (ADNOC)

The study of technology-based change and innovation is receiving much attention from academics and practitioners as change/innovation plays a vital role in organisations’ growth success and improved performance. Despite the potential benefits associated with new technologies, employees and organisations are generally reluctant to adopt them. In response to this issue, this study aims to enhance the general understanding concerning the factors that affect employees’ adoption of technology in a Middle Eastern country (UAE), where the results can also be applied to other Arab countries in the region. In spite of the recent progress in understanding how radio frequency identification (RFID) systems can substantially advance logistics and other services within the oil and gas sector, there is a significant gap in the literature concerning determinants of RFID application in managing various forms of operations. Hence, this study attempts to fill this gap by examining the key enablers and impediments of adopting RFID systems in the UAE oil and gas sector using the technology, organisation and environment framework (TOE). The purpose of this research is to refine and expand technology adoption theory for the oil and gas sector by testing the technology–organisation–environment framework in the Abu Dhabi National Oil Company (ADNOC) UAE. The research work identifies and ranks factors impacting employees’ decision to implement RFID in ADNOC UAE. A theoretical model was developed using a variety of TOE factors that may enable or impede RFID adoption in managing operations within the oil and gas sector. Then, the model was empirically tested by means of Structural Equation Modelling (SEM) based on survey data of 301 online questionnaire responses that were collected from managers, technicians, physicians and general employees working in ADNOC UAE. Results showed that Technology Competence, Top Management, Competitive Pressure, Firm’s Size and Government Regulations showed significant and positive relationship with employees’ intention to adopt RFID. However, perceived usefulness, perceived ease of use and perceived financial cost were found to have no significant effect on employees’ willingness to adopt RFID. The study contributes to the empirical research within the field of RFID and technology adoption in the UAE oil and gas sector. Furthermore, the findings of this study enable managers to make an informed decision about technology adoption within the oil and gas logistics setting

Exploring the antecedents of AI adoption for effective HRM practices in the Indian pharmaceutical sector

Purpose: The aim of this research is to investigate the factors that facilitate the adoption of artificial intelligence (AI) in order to establish effective human resource management (HRM) practices within the Indian pharmaceutical sector.Design/methodology/approach: A model explaining the antecedents of AI adoption for building effective HRM practices in the Indian pharmaceutical sector is proposed in this study. The proposed model is based on task-technology fit theory. To test the model, a two-step procedure, known as partial least squares structural equational modeling (PLS-SEM), was used. To collect data, 160 HRM employees from pharmacy firms from pan India were approached. Only senior and specialized HRM positions were sought.Findings: An examination of the relevant literature reveals factors such as how prepared an organization is, how people perceive the benefits, and how technological readiness influences AI adoption. As a result, HR systems may become more efficient. The PLS-SEM data support all the mediation hypothesized by proving both full and partial mediation, demonstrating the accuracy of the proposed model.Originality: There has been little prior research on the topic; this study adds a great deal to our understanding of what motivates human resource departments to adopt AI in the pharmaceutical companies of India. Furthermore, AI-related recommendations are made available to HRM based on the results of a statistical analysis