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The term smartness has been discussed in the academia for many years; prior research has listed numerous advantages and encouraged business entities to implement smart technologies. However, stakeholders’ knowledge level, support intention and barriers to smart technology have been under investigated. Without the support of stakeholders, smart projects can hardly be implemented. This paper aims to explore the above-mentioned under investigated area and identify the gaps between academia and the hotel industry in Taiwan.

In-depth interviews were conducted with nine hotel stakeholders in Taiwan with investors, owners, managers, technology suppliers and information technology consultants. Three key areas were focused on: smart hotel definition, expectations from smart hotel and known barriers for implementing smart technologies.

The definition of smart hotel among all stakeholders was inconsistent. Stakeholders defined a smart hotel according to their role in the organization: revenue boost, service customization, operations effectiveness and in-room automation. However, the key functions of smart technologies, such as interconnectivity and interoperability with business partners’ application (e.g. online travel agencies) and linkage to external Big data for accurate revenue forecast, were not mentioned by the interviewees. In addition, social media monitoring, robots and artificial intelligence were not mentioned during the interview.

This study attempted to identify Taiwanese hotel stakeholders’ perspective on smart hotel and to compare the outcome with academic research. The result indicated that there is a big gap in the definition of “smart hotel” among stakeholders and academia and reflected several barriers that prohibit hotel owners and investors in implementing smart systems.

Through the resource-based view (RBV) and contingency theory, this study empirically investigates the impacts of smart manufacturing systems' maturity levels on the performance of small and medium-sized enterprises (SMEs). Moreover, it aims to examine how industry types (i.e. high- and low-tech industries) and human-resource factors (i.e. the proportion of production workers to total workers) as contingency factors influence the effects of smart manufacturing systems.

The study conducted an empirical investigation of a sample of 163 Korean manufacturing SMEs. This study used an ordinary least squares regression to examine the impacts of the maturity levels of smart manufacturing systems on financial performance. Moreover, the impacts on operational efficiency were analysed using data envelopment analysis based on bootstrap methods and Tobit regression.

The RBV results indicate that the higher the maturity levels of smart manufacturing systems, the higher the financial performance and operational efficiency. Moreover, based on contingency theory, this study reveals that the effect of the maturity levels of smart manufacturing systems on financial performance and operational efficiency depends on firms' industry types and the proportion of production workers.

This study shows that the introduction of smart manufacturing systems can help SMEs achieve better financial performance and operational efficiency. However, their effectiveness is contingent on firms' industry types and the characteristics of their human resources.

Since the effects of the maturity levels of smart manufacturing systems on SME performance differ depending on their industries and the characteristics of human resources, managers need to consider them when introducing or investing in smart manufacturing systems.

Based on the RBV and contingency theory, this is the first empirical study to examine the moderating effects of industry types and the proportion of production workers on the impacts of the maturity levels of smart manufacturing systems on the financial performance and operational efficiency of SMEs.

At present the energy generation and distribution landscape is changing rapidly. The energy grid is becoming increasingly smart, relying on an information network for the purposes of monitoring and optimization. However, because of the particularly stringent regulatory and technical constraints posed by smart grids, it is not possible to use ordinary communication protocols. The purpose of this paper is to revisit such constraints, reviewing the various options available today to realize smart‐metering networks.

After describing the regulatory, technological and stakeholders' constraints, the authors provide a taxonomy of network technologies, discussing their suitability and weaknesses in the context of smart‐metering systems. The authors also give a snapshot of the current standardization panorama, identifying key differences among various geographical regions.

It is found that the field of smart‐metering networks still consists of a fragmented set of standards and solutions, leaving open a number of issues relating to the design and deployment of suitable systems.

This paper addresses the need to better understand state‐of‐the‐art and open issues in the fast‐evolving area of smart energy grids, with particular attention to the challenges faced by communication engineers.

The paper aims to present a systematic literature review to analyze interrelated enablers of Industry 4.0 for implementation. Industry 4.0 is an integrated manufacturing strategy embedded with disruptive technologies. Adapting these technologies with the present industrial scenario is dependent on understanding the dynamics of various critical enablers in the existing literature. In this paper, an effort has been taken to validate and reinforce these enablers by experts in the field of Industry 4.0 for implementation.

A mixed-methodology is designed in this paper. A text mining approach with an expert’s linguistic assessment method is planned to discover the enablers from literature 2010 to 2019. The most critical enablers and their dependencies on other enablers are studied by using correlation analysis.

The research explores the power driving enablers in three groups: technology, features and requirements for implementing Industry 4.0 in the existing factory. In each group, a high degree of associated and dependent enablers is fragmented in detail.

This paper will benefit the research communities and practitioners to understand the significance of an integrated ecosystem of Industry 4.0 technologies, features and requirements for implementation.

The text mining approach integrated with expert’s linguistic assessment to explore the pairwise relationship among the enablers using word correlation is a novel approach in this paper. Moreover, to best of the authors’ knowledge, this is the first-ever attempt to conduct a structured literature review combined with text analysis and linguistic assessment to identify the enablers of Industry 4.0 for implementation.

Today, the use of smart technologies in healthcare systems is experiencing exponential growth, and the future of healthcare is seemingly closely intertwined with such technologies. Thus, any exploration of the factors that influence human health and healthcare systems inevitably touches upon the subject of new technologies. This study aims to design a conceptual model to investigate the elements that affect individuals' openness to accepting and using mobile healthcare applications (mHealth apps) and their reciprocal effects.

After a brief review of the literature, the authors identify the influential factors in the acceptance of smart technologies in healthcare systems and present a conceptual model in this regard. Next, the authors analyze the factors and variables and the extent of their impact by a structural equation modeling (SEM) approach. The statistical population of this study consists of 421 individuals including the developers, consultants and users (i.e. patients) of mHealth apps. Data analysis was done on the statistical software SPSS v.26, while SEM was carried out using the partial least squares (PLS) method on the modeling software SmartPLS.

The results indicate that user, consultant and developer preferences have a positive and significant impact on time, quality of life, managing chronic conditions and cooperation, and these constructs (system performance) finally have a positive and significant impact on the acceptance of mobile healthcare technologies.

This paper shows that mHealth apps can have a remarkable role in the prevention and treatment of medical conditions, and it is strongly recommended that this technology be utilized in the studied region.

This study aims to examine and analyse data relating to cultural heritage, smart tourism and smart tourism tools for preserving cultural heritage in the Baltic states – Estonia, Latvia and Lithuania.

The paper is based on a qualitative review of data from National tourism board web sites, the UNESCO World Heritage Convention, and the European Heritage Label sites. The paper analyses various sources in terms of cultural heritage and smart tourism and examines different ways of applying smart tourism tools to cultural heritage.

The findings show that smart tourism, and especially the preservation of cultural heritage in the Baltic states, is not a new thing, and it is rapidly progressing by inventing new technological tools for tourists to use and as well by digitising cultural heritage. Comprehensive examination of three countries shows that there is significant potential already and that there is a way to grow further for each of the countries by applying new technological tools for preservation of a cultural heritage.

The paper reviews data on cultural heritage and smart tourism tools in the Baltic states where it already plays a steady and significant role. Specifically, it contributes to recognition of each of the states on a global level in terms of variety of cultural heritage that is being preserved and digitalised. The originality of the paper is determined by the assessment of the smart tools used for cultural tourism.

The purpose of this paper is to reveal the smart collaborative learning service. This concept aims to build teams of learners based on the complementarity of their skills, allowing flexible participation and offering interdisciplinary collaboration opportunities for all the learners. The success of this environment is related to predict efficient collaboration between the different teammates, allowing a smartly sharing knowledge in the Smart University environment.

A random forest (RF) approach is proposed, which is based on semantic modelization of the learner and the problem-solving allowing multidisciplinary collaboration, and heuristic completeness processing to build complementary teams. To achieve that, this paper established a Konstanz Information Miner workflow that integrates the main steps for building and evaluating the RF classifier, this workflow is divided into: extracting knowledge from the smart collaborative learning ontology, calculating the completeness using a novel heuristic and building the RF classifier.

The smart collaborative learning service enables efficient collaboration and democratized sharing of knowledge between learners, by using a semantic support decision support system. This service solves a frequent issue related to the composition of learning groups to serve pedagogical perspectives.

The present study harmonizes the integration of ontology, a new heuristic processing and supervised machine learning algorithm aiming at building an intelligent collaborative learning service that includes a qualified classifier of complementary teams of learners.

In recent years, a new transformation known as Industry 4.0 has drawn much attention throughout the world, and numerous investigations have fundamentally looked into the uprising concept. However, few have concentrated on the literature review. Taking this as motivation, the authors endeavored to assess the different attributes of Industry 4.0. The paper aims to discuss these issues.

This review concentrated on linking the articles from different database and distinguishing the attributes of Industry 4.0. The authors assessed 85 articles from scholarly database and peer-reviewed journals on Industry 4.0 through the selection of the Mayring (2004) procedure. The examination included a four-advance process, in particular, material gathering, engaging investigation, classification of the choice and material assessment.

The study backs experts and readers to comprehend the spread of Industry 4.0 in various ventures. For academicians, this gives an extensive rundown of Industry 4.0 attributes. Besides, the writing review gives a chance to comprehend the idea of Industry 4.0 in detail. Further, the outcome aggregates the success factor, failure factor, business model, potential and difficulties in the context of Industry 4.0.

Many areas such as supply chain, circular economy and healthcare have started exploring Industry 4.0. However, few specific cases have reported about it, and no generic model is found for real-time application.

The study serves as reference material for researchers and practitioners to understand the spread of Industry 4.0 and utilize the concept of Industry 4.0 for real-life application.

The study focuses on reporting the potential, challenges, business model and pre-requites of Industry 4.0.

According to the authors’ research, while top-level executives look forward to the potential of artificial intelligent systems in their firms, line managers are much more skeptical. This article advises on i8mplementation strategy.

Drawing on findings from Accenture’s survey of 1,770 managers in 14 countries and interviews with 37 senior executives responsible for digital transformation, the authors have identified patterns in managers’ attitudes and offer strategies for effective adoption of the new technology.

When managers have a say and involvement in initial training efforts, they gain a sense of ownership throughout the learning process as well as familiarity with intelligent systems.

The introduction of AI will put a premium on “soft” skills such as collaboration, creativity and good judgment, which may be just as important, if not more important, than technical skills in the future.

The emergence of artificial intelligence (AI) promises to transform the nature of work and the relationship among human beings and machines in organizations. When the authors asked whether leaders would be comfortable with AI monitoring and evaluating their work, 42 percent of the top managers in our survey strongly agreed, while only 15 percent of first-line managers shared the same sentiment.” This research discovered that top executives cannot assume that mid- and lower-level managers will share their appreciation for AI.

This paper aims to study the relationship between information and communication technology (ICT) readiness, use, and intensity and environmental sustainability factors in the lower and middle lower-income countries from 2012 to 2018.

ICT readiness, use and intensity are measured with the impact of ICT on access to basic services, phone penetration and Internet penetration, while CO₂ emissions per capita, fossil fuel energy consumption and methane emissions are used as indicators for air pollution. To achieve this goal, a two-step generalized method of moments (GMM) estimation was performed which thresholds are computed contingent on the validity of tested hypotheses.

The results demonstrate that increasing ICT readiness, use and intensity in lower and lower-middle-income countries enhance environmental sustainability by decreasing CO₂ emissions and energy consumption.

One of the limitations of this study is that the conclusions and policy recommendations do not take into account the specificities of each country. Indeed there are some differences in the growth pattern of ICT in the lower and middle-lower-income countries. Taken together, the authors conclude that increasing ICT has a positive net effect on CO₂ and methane emissions per capita, while increasing the impact of ICT access in basic services has a net negative effect on CO₂ fossil fuel energy consumption and methane emissions.

The world needs immediate emissions reduction to avoid the long-term danger of climate change. Second, government authorities should give additional efforts in the more pollutant sector such as transport and industry to monitor their energy consumption.

To explore this issue further, the negative net effects suggest that ICT needs to be further developed beyond the determined thresholds, to attain the required negative net effect on fossil fuel energy consumption.