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Agility is an important characteristic that every organisation requires in today’s competitive digital era. Telecommunications companies in Indonesia face various types of competition, both from the same industry and new models. This study aims to identify the agility level of telecommunications companies in Indonesia. It also examines the effect of leadership style directly and indirectly through the mediation of employee readiness, innovation culture, technology capability and organisational structure.

This study used a non-probability sampling technique. The macroprocess was used to identify and measure the direct and indirect effects. The results are based on survey data collected from a telecommunications company in Indonesia with a total of 1,073 employees.

The results of this study showed that an adaptive leadership style has a direct and significant positive effect on the organisational agility level. Employee readiness, innovation culture, technological capability and organisational structure function as mediators between adaptive leadership style and agility.

This study could contribute to the development of programs to ignite and boost organisational agility. Organisations are recommended to conduct periodic evaluations to measure agility levels and amend their programs accordingly.

Adaptive leadership style was used, which expresses the leader’s deep concern for employee needs and organisational achievement. This leader will most likely positively impact employees and favourably influence the organisation (technology, structure, innovation and agility).

Construction industry (CI) has great prominence for the world economy, and it is expected that, with the use of the innovative technologies and approaches of Industry 4.0 (I4.0), the new industrial paradigm, construction can reach higher levels of productivity. This study aims to develop a model (readiness model) to assess the level of use of I4.0 technologies by the construction sector in Brazil and its most relevant applications.

The methodology used was bibliographic research, design-science research and a survey to validate the model, carried out with 162 companies, considered among the main ones in the sector in Brazil. The literature review revealed 13 technologies of I4.0 applied to construction; hence, the views of industry experts were based on these technologies.

The Digital Advancement Within CoNstruction (DAWN) readiness model was proposed, showing that among the 13 evaluated technologies of I4.0 and their applications, the Brazilian construction companies had a low level of utilization; both high and middle-income companies presented this low level of use; some technologies with a greater number of scientific publications were less used in practice in the Brazilian construction.

The originality and theoretical contribution are to present a readiness model to assess the level of use of I4.0 technologies and their most relevant applications in the CI in countries with an economy similar to Brazil’s, making it possible to measure the level of adoption of these technologies.

This study aims to focused on conducting a comprehensive assessment of the technology readiness level (TRL) of Iran’s oil field intelligence compared to other countries with similar oil reservoirs. The ultimate objective is to optimize oil extraction from this field by leveraging intelligent technology. Incorporating intelligent technology in oil fields can significantly simplify operations, especially in challenging-to-access areas and increase oil production, thereby generating higher income and profits for the field owner.

This study evaluates the level of maturity of present oil field technologies from the perspective of an intelligent oil field by using criteria for measuring the readiness of technologies. A questionnaire was designed and distributed to 18 competent oil industry professionals. Using weighted criteria, a mean estimate of oil field technical maturity was derived from the responses of respondents. Researchers evaluated the level of technological readiness for Brunei, Kuwait and Saudi Arabia’s oil fields using scientific studies.

None of the respondents believe that the intelligent oil field in Iran is highly developed and has a TRL 9 readiness level. The bulk of experts believed that intelligent technologies in the Iran oil industry have only reached TRL 2 and 1, or are merely in the transfer phase of fundamental and applied research. Clearly, Brunei, Kuwait and Saudi Arabia have the most developed oil fields in the world. In Iran, academics and executive and contracting firms in the field of intelligent oil fields are working to intelligently develop young oil fields.

This study explores the level of maturity of intelligent technology in one of Iran’s oil fields. It compares it to the level of maturity of intelligent technology in several other intelligent oil fields throughout the globe. Increasing intelligent oil fields TRL enables better reservoir management and causes more profit and oil recovery.

This study aims to investigate how online teaching of faculty members is affected by technological readiness (TR) of using online teaching platforms. The study sheds light on how many faculty members were ready to use different online platforms during COVID-19 period.

This study used TR measures to determine the impact of optimism regarding the perceived usefulness and ease of usage, impact of innovativeness in terms of perceived usability and ease of use, the influence of discomfort on perceived usefulness and ease of usage, the effect of uncertainty on perceived usefulness and ease of use and the influence of perceived usefulness and ease of use on behavior. An online questionnaire survey was conducted among 255 faculty members of different private universities of Bangladesh. The sample was chosen based on a convenience method. The responses were analyzed using partial least square (PLS) approach with the help of software Smart PLS 3.

The finding supported all of the hypotheses except that discomfort and insecurity have a positive relationship with ease of use and usefulness.

The study will help faculty members in developing their competency in using technologies in their pedagogy. Also, this study will provide some guidelines to the university management in developing adequate technological infrastructure to aid teaching.

The aim of the study was to investigate the faculty members' readiness level with respect to online teaching. The technology assessment model (TAM) was used to determine the readiness index. The study intended to validate the hypotheses regarding the extent to which the faculty members perceived that TAM factors affect Ease of Use and Usefulness of online teaching. Also, this research analyzed the perception of faculty members that Ease of Using online teaching affects its Usefulness. Lastly, the study examined how their perception of Ease of Use and Usefulness affect Intention to Use online as a mode of teaching. It was found from the study that each of the TAM factors, Optimism, Innovativeness, Insecurity and Discomfort has positive and significant contribution on the Ease of Use. On the other hand, Optimism, Innovativeness, Insecurity and Discomfort have positive and significant contributions on the Usefulness. The study also revealed that Ease of Use has positive and significant contribution on the Usefulness. Lastly, it was found that Ease of Use and Usefulness have positive and significant contribution on the Intention to use. Teaching remotely is still a novel concept, and it is more difficult for people who have not done it before. Many teachers became burned out as a result of trying to adjust to new teaching methods, especially after the lockdown began. They were having a difficult time since there was so much ambiguity. When a teacher is well-versed in communication tools, it can improve learning efficiency. When they are properly trained, deploying engaging features of virtual learning, such as audio-visual lessons, quizzes, and so on, becomes simple, and students become eager to learn more. Teachers can plan their classes, prepare and master technology and create innovative and stimulating discussion topics (Mishra et al., 2020). They need to utilize a variety of technological options. They can rehearse virtual classroom management with colleagues if they face any difficulty. All of the aforementioned abilities can be honed with the assistance of an integrated academic system. Teachers can be trained by educational institutions to ensure a smooth learning process through the use of ICT (information and communication technologies) (Scherer et al., 2021; Mishra et al., 2020). The training will assist teachers in efficiently taking online classes. Institutions should ensure that teachers are well-suited to teach online and are skilled at keeping students engaged during remote learning. To make every chapter engaging, aspects such as videos, slides, images and digital copies of books and workbooks can be used. This allows students to receive personalized support and counseling in order to maintain their motivation (Sahu et al., 2022; Lapitan et al., 2021). Every other day, group doubt resolution classes ensure that there are no gaps in learning (Lapitan et al., 2021). All teachers require is a digital mindset, the appropriate tools and a committed approach (Sahu et al., 2022). If teachers can hold their students' attention, they can easily deliver an effective learning experience (Lapitan et al., 2021).

This study was conducted to identify technological preparedness of faculty members of private universities in Bangladesh during COVID-19 period. Some studies were there to assess such kind of preparedness but none of those used TAM and technology readiness model either in isolation or in combination. Also, this paper focused on teachers' readiness in contrast to students' readiness specific to private universities.

This paper aims to establish and empirically investigate a research model examining the effect of four dimensions of the technology readiness index – optimism, innovativeness, discomfort and insecurity – on customer engagement that further influences purchase intention in the context of online shopping through artificial intelligence voice assistants (AI VAs).

Data were collected in India from 429 customers in a self-administered online survey. Data analysis uses the structural equation modelling technique.

Technology readiness dimensions, e.g. optimism, innovativeness, discomfort and insecurity, are critical factors driving customer engagement. Customer engagement further results in purchase intention in online shopping through AI VAs.

This study adds to the literature by understanding how customers’ technology readiness levels drive engagement and purchase intention. However, this study includes customer engagement as a unidimensional construct. Further research can consist of customer engagement as a multidimensional construct.

The findings offer guidelines for e-retailers to enhance customer engagement that matches their personality traits, thereby strengthening their purchase intention through AI VAs.

The research contributes to the literature by empirically investigating a research model, revealing optimism, innovativeness, discomfort and insecurity as crucial parameters for customer engagement and purchase intention.

This research empirically investigates how service employees' ratings of technology readiness (TRI), negative attitudes towards robots (NARS), Big Five personality traits (BFI) and emotional demands (ED) affect their willingness to work with service robots (WTW).

One set of data is collected from 410 service employees expected to work with service robots in Study 1. Another set of field data is collected from 102 employees working with service robots in Study 2. Hierarchical regression is used to test hypotheses about the impact of technology readiness, negative attitudes towards robots and Big Five personality traits on WTW. Additionally, the interactions of emotional demands in the workplace are analysed.

TRI-optimism and TRI-insecurity significantly affect WTW in Study 2 but are nonsignificant in Study 1. The impacts of NARS-emotions in interaction with robots and NARS-interaction with robots situations on WTW are significant in Study 1 but nonsignificant in Study 2. Moreover, BFI-neuroticism negatively affected WTW in Study 1, while these effects were nonsignificant in Study 2. Finally, emotional demands significantly interact with three of eleven dimensions of IVs in Study 1, but all interactions are nonsignificant in Study 2.

This research provides a guiding framework for service companies to screen employees expected to cowork with service robots, to enhance newly hired employees' WTW and to improve existing employees' WTW.

Integrating the characteristics of service employees, service robots and jobs into a theoretical framework, this research is the first to empirically examine the effects of service employees' several critical characteristics (technology readiness, negative attitudes towards robots and Big Five personality) on WTW and the moderation of job characteristics (emotional demands).

An increasing number of immersive technologies have been adopted in museum tourism in response to shifting consumer habits in the digital era. In contrast, the authenticity experience of museum tourists relies on genuine relics, the environment and activities, which are ancient or traditional. This raises the question of whether tourists can perceive authenticity in immersive technology-based museum tourism. To address this question, this study aims to explore the impact of virtual reality (VR) attributes on tourists’ presence, tourism authenticity and subsequent behavioral intentions in virtual museums.

Data were collected via scenario-based surveys of participants who had taken virtual museum tours based on VR. A total of 174 effective questionnaires were collected for exploratory factor analysis via SPSS 25. Afterward, 597 questionnaires were obtained for confirmatory factor analysis and path analysis via Mplus 7.4.

A conceptual model of how VR attributes influence presence, authenticity and visit intention was developed. There is a chain intermediary between presence and visit intentions, from original authenticity to interactive authenticity and then to emotional authenticity. Technology readiness and museum familiarity moderate some relationships between VR attributes and presence.

The findings can guide museums in improving the use of VR. For example, managers can improve the quality of virtual systems and adopt various interactive forms to enhance tourists’ participation experiences.

These research findings contribute to the research area of immersive technology adoption, enhance the understanding of tourism authenticity in the new context of technology application and extend the presence-emotion-intention theory.

This research aims to extract Industry 4.0 technological building blocks (TBBs) capable of value generation in collaborative consumption (CC) and the sharing economy (SE). Furthermore, by employing a mixed methodology, this research strives to analyse the relationship amongst TBBs and classify them based on their impact on CC.

Due to the importance of technology for the survival of collaborative consumption in the future, this study suggests a classification of the auxiliary and fundamental Industry 4.0 technologies and their current upgrades, such as the metaverse or non-fungible tokens (NFT). First, by applying a systematic literature review and thematic analysis (SLR-TA), the authors extracted the TBBs that impact on collaborative consumption and SE. Then, using the Bayesian best-worst method (BBWM), TBBs are weighted and classified using experts’ opinions. Eventually, a score function is proposed to measure organisations’ readiness level to adopt Industry 4.0 technologies.

The findings illustrated that virtual reality (VR) plays a vital role in CC and SE. Of the 11 TBBs identified in the CC and SE, VR was selected as the most determinant TBB and metaverse was recognised as the least important. Furthermore, digital twins, big data and VR were labelled as “fundamental”, and metaverse, augmented reality (AR), and additive manufacturing were stamped as “discretional”. Moreover, cyber-physical systems (CPSs) and artificial intelligence (AI) were classified as “auxiliary” technologies.

With an in-depth investigation, this research identifies TBBs of Industry 4.0 with the capability of value generation in CC and SE. To the authors’ knowledge, this is the first research that identifies and examines the TBBs of Industry 4.0 in the CC and SE sectors and examines them. Furthermore, a novel mixed method has identified, weighted and classified pertinent technologies. The score function that measures the readiness level of each company to adopt TBBs in CC and SE is a unique contribution.

The purpose of this study is to explore the determinants influencing industrial adoption of green hydrogen amidst the global transition towards sustainability. Recognizing green hydrogen as a pivotal clean energy alternative for industrial applications is critical for understanding its potential integration into sustainable practices.

This research examines the impact of factors such as innovativeness, perceived ease of use, user comfort, optimism and governmental policies on the industrial intention towards green hydrogen usage. Using responses from 227 Indian industry professionals and conducting analysis via the SmartPLS software, the study reveals a discernible discomfort among industrial workers pertaining to the daily application of green hydrogen.

The research presents an array of policy recommendations for stakeholders. Emphasized strategies include the introduction of green hydrogen certificates, sustainable public procurement mechanisms, tax incentives, green labelling protocols and the establishment of a dedicated hydrogen skill development council, all of which can significantly influence the trajectory of green hydrogen adoption within the industrial sector.

This research synthesizes various elements, from industry perception and challenges to policy implications, presenting a holistic view of green hydrogen’s potential role in industry decarbonization and SDG realization. In essence, this study deepens not only the empirical understanding but also pioneers fresh theoretical frameworks, setting a precedent for subsequent academic endeavours.

The main purpose of this paper is to examine the adoption of big data analytics (BDA) in the Tanzania banking industry by investigating the influence of technological, environmental and organizational (TOE) factors while exploring the moderating role of perceived risk (PR).

The study employed a qualitative research design, and the research instrument was developed using per-defined measurement items adopted from prior studies; the items were slightly adjusted to fit the current context. The questionnaires were distributed to top and middle managers in selected banks in Tanzania using the snowball sampling technique. Out of 360 received responses, 302 were considered complete and valid for data analysis. The study employed partial least squares structural equation modeling (PLS-SEM) to examine the developed conceptual framework.

Top management support and financial resources emerged as influential organizational factors, as did competition intensity for the environmental factors. Notably, bank size and perceived trends showed no significant impacts on BDA adoption. The study's novelty lies in revealing PR as a moderating factor, weakening the link between technological readiness, perceived usefulness and the intent to adopt BDA.

This study extends literature by extending the TOE model, through examining the moderating roles of PR on technological factors. Furthermore, the study provides useful managerial support for the adoption of BDA in banking in emerging economies.